Molecular
Identification
of Fungi
Youssuf Gherbawy
Kerstin Voigt
Editors
123
Molecular Identification of Fungi
.
Youssuf Gherbawy
l
Kerstin Voigt
Editors
Molecular Identification
of Fungi
Editors
Prof. Dr. Youssuf Gherbawy
South Valley University
Faculty of Science
Department of Botany
83523 Qena, Egypt
youssuf_gherbawy@hotmail.com
Dr. Kerstin Voigt
University of Jena
School of Biology and Pharmacy
Institute of Microbiology
Neugasse 25
07743 Jena, Germany
kerstin.voigt@uni-jena.de
ISBN 978-3-642-05041-1 e-ISBN 978-3-642-05042-8
DOI 10.1007/978-3-642-05042-8
Springer Heidelberg Dordrecht London New York
Library of Congress Control Number: 2009938949
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Dedicated to Prof. Lajos Ferenczy (1930–2004) microbiologist, mycologist and
member of the Hungarian Academy of Sciences, one of the most outstanding
Hungarian biologists of the twentieth century
.
Preface
Fungi comprise a vast variety of microorganisms and are numerically among the
most abundant eukaryotes on Earth’s biosphere. They enjoy great popularity in
pharmaceutical, agricultural, and biotechnological applications. Recent advances
in the decipherment of whole fungal genomes promise a continuation and acceleration of these trends. New techniques become available to facilitate the genetic
manipulation of an increasing number of fungal organisms to satisfy the demand of
industrial purposes. The increasing importance-driven search of novel detection
techniques and new fungal species initiated the idea for a book about the molecular
identification of fungi.
The kingdom of the fungi (Mycota) appears as the sister group of the multicellular animals (Metazoa) as an independent, apparently monophyletic group
within the domain Eukarya, equal in rank to green plants (Viridiplantae) and
animals (Metazoa). Fungi are originally heterotrophic eukaryotic microorganisms
harboring chitin in their cell walls and lacking plastids in their cytoplasm.
Formerly, the oomycetes, slime moulds and plasmodiophorids were considered
as fungi based on their ability to produce fungus-like hyphae or resting spores.
Whereas the Oomycota are classified to the stramenopile algae (Chromista or
Heterokonta), and the plasmodial and cellular slime moulds (Mycetozoa) belong
to the Amoebozoa. The Plasmodiophoromycota are among the cercozoan Rhizaria closely related to the foraminifers. A three-protein phylogeny of the fungi
and their allies confirms that the nucleariids, phagotrophic amoebae with filose
pseudopods in soil and freshwater, may represent descendants of a common
ancestor at the animal–fungal boundary (Fig. 1). The fungal kingdom encompasses the Asco-, Basidio-, Glomero-, Zygo- and Chytridiomycota. The former
four phyla are terrestrial fungi developing nonflagellated spores (aplanosporic),
whereas the Chytridiomycota represent aquatic and zoosporic (planosporic) fungi,
which split into three individual taxon groups, the aerobic Blastocladio- and
Chytridiomycota sensu stricto and the anaerobic Neocallimastigomycota. The
Zygomycota are among the most basal terrestrial fungi, which evolved in a
paraphyletic manner. Hence, the phylum was divided into different subphyla,
vii
viii
Preface
Fig. 1 The evolution of the fungi and allied fungi-like microorganisms based on a concatenated
neighbor-joining analysis using mean character differences as distance measure on 1,262 aligned
amino acid characters comprising translation elongation factor 1 alpha, actin, and beta-tubulin
(500, 323 and 439 characters, respectively) from 80 taxa. The prokaryotic elongation factor Tu,
MreB (TM1544), and FtsZ (both homologous to actin and tubulin, respectively) from Thermotoga
maritima were used as out group taxon representing the bacterial domain
the Mucoro-, Kickxello-, Zoopago- and Entomophthoromycotina, whose phylogenetic relationships are not fully understood yet. In the phylogenetic tree shown
in Fig. 1, the Entomophthoromycotina group together with the Ichthyosporea, a
relationship, is not well supported by clade stability proportions.
Fungi develop a wide diversity of morphological features, which are shared with
many fungi-like microorganisms (Fig. 2), among those the white rust and downy
mildew “fungi” (Fig. 2g) are obligate parasites of plants and develop fungus-like
hyphae with haustoria (ht) in asexual and thick-walled, ornamented oospores (os)
from fertilized oospheres after fusion of an oogonium (og) with an antheridium (at)
during sexual reproduction (Fig. 3).
The distribution of fungi among the various ecological niches of the biosphere
seems to be infinite. Estimates suggest a total of 1.5 million fungal species, only less
than a half has been merely described yet. This implies a backlog demand, which
comes along with a rising importance of novel techniques for a rapid and
Preface
ix
Fig. 2 The morphological diversity of fungi and fungi-like microorganisms. (a–f ): basidiomycetes (Agaricomycotina; Photos: M. Kirchmair); (g) oomycetes (Peronosporales; Photo: O.
Spring); (h–j): multicellular conidia from imperfect stages of ascomycetes (Pezizomycotina);
(k–s): zygomycetes (Mucoromycotina; Photos: K. Hoffmann, scanning electron microphotographs o & q: M. Eckart & K. Hoffmann): (k, l, p, r, s) – different types of multispored sporangia,
(m, n, o): different types of uni‐fewspored sporangiola; (t–x): reproductive structures (zoosporangia) from anaerobic chytridiomycetes (Neocallimastigomycota; Photos: K. Fliegerova);
(y, z): plasmodiophorids (Plasmodiophoromycota; Photos: S. Neuhauser & M. Kirchmair).
x
Preface
Fig. 3 Cross-section of a leaf
infected with Pustula
tragopogonis
(Peronosporales, Oomycota)
causing white rust on
sunflower. The
microphotograph shows
structures, which are typical
for the sexual reproduction of
oomycetes: ht – haustorium,
ld – lipid droplet inside an
oospore, os – oospore, og –
oogonium, at – antheridium
fused to an oogonium (Photo:
A. Heller)
unambiguous detection and identification of fungi to explore the fungal diversity as
a coherent whole. Molecular techniques, particularly the technology of the polymerase chain reaction, have revolutionized the molecular biology and the molecular
diagnosis of fungi. The incorporation of molecular techniques into what has been
traditionally considered as morphology-based taxonomy of fungi helps us in the
differentiation of fungal species and varieties. Databases of genomes and genetic
markers used as sources for molecular barcodes are being created and the fungal
world is in progress to be unveiled with the help of bioinformatics tools. Genome
projects provide evidence for ancient insertion elements, proviral or prophage
remnants, and many other patches of unusual composition. Consequently, it
becomes increasingly important to pinpoint genes, which characterize fungal
organisms at different taxonomic levels without the necessity of previous cultivation. Unfortunately, the initiative of an excessive use of molecular barcoding has
been hampered by a lack of sufficient and novel synapomorphic nucleotide
<
Fig. 2 (continued) (a) – basidiocarp of Schizophyllum commune, (b) – basidiocarp of Daedalea
quercina, (c) – hymenophor from basidiocarp of Daedalea quercina, (d) – basidiocarp of Trametes
sp., (e) – mycelium of Antrodia sp spreading over a trunk of a tree, (f ) – dry rot caused by Serpula
lacrymans on timber, (g) –symptomatology from Plasmopara viticola, the causal agent of grapevine downy mildew, (h) – Pestalotiopsis clavispora (Photo: C. Kesselboth), (i) – Bipolaris cf.
sorokiniana (Photo: G. Newcombe), ( j) – Fusarium sp. (Photo: C. Kesselboth), (k) – Mucor
indicus, (l) – Helicostylum elegans, (m) – Thamnidium elegans, (n) – Dichotomocladium sp., (o)
– Dichotomocladium robustum, (p) – Absidia psychrophilia, (q) – zygospores from Lentamyces
parricida, (r) – Mucor rouxii, (s) – Absidia cylindrospora, (t) – Caecomyces sp. isolated from sheep
(lugol staining), (u) – Caecomyces sp. isolated from sheep, (v) – Neocallimastix frontalis (bisbenzimide staining of nuclei), (w) – Anaeromyces mucronatus isolated from cow (bisbenzimide
staining of nuclei), (x) – Neocallimastix frontalis isolated from cow (lugol staining); (y) – thick
walled resting spores from Sorosphaera veronicae, (z) – sporosori from Sorosphaera veronicae
Preface
xi
characters and signature sequences. Moreover, high intraspecific variability of
conventional molecular characters makes it difficult to identify species borders.
However, DNA sequences and other genetic markers provide large amounts of data
which are cultivation-independent and do not depend on physiological inconsistencies. Genetic markers constantly reflect the identification treasure hidden in the
genetic information and allow to control the degree of resolution by choosing the
appropriate genes.
In this book, we highlight the advances of the past decade, both in methodology
and in the understanding of genomic organization and approach problems of the
identification and differentiation of fungi using molecular markers and compare
those with classical procedures traditionally used for species designation. The
limitations in the availability of type material, reference strains, and reference
nucleotide sequences set boundaries in the molecular identification. For example,
the image displaying multicellular, melanin-pigmented conidia (size: 90 mm)
from strain CID1670 (Fig. 2i), which was kindly provided by George Newcombe
(University of Idaho, Center for Research on Invasive Species and Small Populations, Moscow, ID, USA), may serve as an appropriate cautionary note for readers
of this book. The strain was recovered as an endophytic ascomycete from the asterid
perennial herb Centaurea stoebe (spotted knapweed). The fungus could be attributed by conventional ITS barcoding to the pleosporalean genus Drechslera and in a
narrower sense to Bipolaris sorokiniana. Since species of Bipolaris had never been
reported from any species of Centaurea in earlier reports, neither its effects on its
host nor the final taxonomic delimitation are known. Nucleotide sequences of
additional genes and a more in-depth phylogenetic study may even suggest that
this strain was a new species. Therefore, it would make sense to distinguish between
refined identification of fungi uncommonly found in exceptional biotopes in order
to explore new species, e.g., as endophytes, and high-throughput molecular identification of well-studied fungi in order to serve the needs of industrial application.
The role of fungi as pathogens of evolutionarily naive plants including a
hypothesis about the plant invasion-mediated progression of novel phytopathogens
will be discussed in the first chapter. The second and third chapter concerns with the
diagnostics and the challenge to identify “fungus-like” plant pathogens from the
oomycetes and the plasmodiophorids, respectively. The fourth chapter leads over
the applications of molecular markers and DNA sequences in the identification of
fungal pathogens in grain legumes and cereals followed by various aspects of
qualitative and quantitative detection of Fusarium spp. and Macrophomina phaseolina, pathogenic on maize and other corn crops or economic plants. During the
course of the book, the detection of ochratoxigenic fungi, mainly aspergilli and
penicilli, and other postharvest pathogens like Mucor and Rhizopus is elucidated.
The molecular identification of wood rotting and endophytic fungi as well as
anaerobic rumen fungi finish the first part on plant pathological and environmental
biological aspects. The second part deals with human pathological and clinical
aspects. The introduction gives a contribution about new approaches in fungal DNA
preparation from whole blood following multiplex PCR detection. Novel techniques in the depletion of the background host DNA in favour of enrichment of the
xii
Preface
fungal contaminant DNA following different modifications of PCR approaches
represent powerful tools in the detection of a wide variety of human pathogenic
fungi causing sepsis and other life-threatening diseases that result from excessive
host responses to fungal infections. The survey continues with conventional strategies for the molecular detection of Malassezia, dermatophytes, opportunistic fungi,
and causative agents of deep mycoses as well as paracoccidioidomycosis and
Ochroconis gallopava infection via a novel tool, the loop-mediated isothermal
amplification method (LAMP). The book closes with reviews about prospects and
perspectives of molecular markers for the identification of Absidia-like fungi and
other zygomycetes.
The editors thank all contributors for their valuable reviews and comments,
which were crucial for the accomplishment of this book. Furthermore, we express
our gratitude to all authors who contributed figures and images for the cover and
miscellaneous parts adding a great deal to the illustration of this book. The cover of
the book was kindly supported by “leography.com.”
January 2010
Youssuf Gherbawy
Kerstin Voigt
Contents
Part I
Plant Pathological and Environmental Biological Aspects
1
Fungal Pathogens of Plants in the Homogocene . . . . . . . . . . . . . . . . . . . . . . . . 3
George Newcombe and Frank M. Dugan
2
Molecular Techniques for Classification and Diagnosis of Plant
Pathogenic Oomycota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
Otmar Spring and Marco Thines
3
Plasmodiophorids: The Challenge to Understand Soil-Borne,
Obligate Biotrophs with a Multiphasic Life Cycle . . . . . . . . . . . . . . . . . . . . 51
Sigrid Neuhauser, Simon Bulman, and Martin Kirchmair
4
Applications of Molecular Markers and DNA Sequences
in Identifying Fungal Pathogens of Cool Season
Grain Legumes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
Evans N. Njambere, Renuka N. Attanayake, and Weidong Chen
5
Quantitative Detection of Fungi by Molecular Methods:
A Case Study on Fusarium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
Kurt Brunner and Robert L. Mach
6
DNA-Based Tools for the Detection of Fusarium spp.
Pathogenic on Maize . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
Ivan Visentin, Danila Valentino, Francesca Cardinale,
and Giacomo Tamietti
7
Molecular Detection and Identification of Fusarium oxysporum . . . . . 131
Ratul Saikia and Narendra Kadoo
xiii
xiv
Contents
8
Molecular Chemotyping of Fusarium graminearum,
F. culmorum, and F. cerealis Isolates From Finland
and Russia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
Tapani Yli-Mattila and Tatiana Gagkaeva
9
Molecular Characterization and Diagnosis of Macrophomina
phaseolina: A Charcoal Rot Fungus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179
Bandamaravuri Kishore Babu, Ratul Saikia, and Dilip K Arora
10
Molecular Diagnosis of Ochratoxigenic Fungi . . . . . . . . . . . . . . . . . . . . . . . 195
Daniele Sartori, Marta Hiromi Taniwaki, Beatriz Iamanaka,
and Maria Helena Pelegrinelli Fungaro
11
Molecular Barcoding of Microscopic Fungi with Emphasis
on the Mucoralean Genera Mucor and Rhizopus . . . . . . . . . . . . . . . . . . . . . 213
Youssuf Gherbawy, Claudia Kesselboth, Hesham Elhariry,
and Kerstin Hoffmann
12
Advances in Detection and Identification of Wood Rotting
Fungi in Timber and Standing Trees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 251
Giovanni Nicolotti, Paolo Gonthier, and Fabio Guglielmo
13
Molecular Diversity and Identification of Endophytic Fungi . . . . . . . 277
Liang-Dong Guo
14
Molecular Identification of Anaerobic Rumen Fungi . . . . . . . . . . . . . . . . 297
Martin Eckart, Katerina Fliegerová, Kerstin Hoffmann,
and Kerstin Voigt
Part II
Human Pathological and Clinical Aspects
15
New Approaches in Fungal DNA Preparation from Whole
Blood and Subsequent Pathogen Detection Via Multiplex PCR . . . . 317
Roland P. H. Schmitz, Raimund Eck, and Marc Lehmann
16
Classification of Yeasts of the Genus Malassezia by Sequencing
of the ITS and D1/D2 Regions of DNA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 337
Lidia Pérez-Pérez, Manuel Pereiro, and Jaime Toribio
17
DNA-Based Detection of Human Pathogenic Fungi:
Dermatophytes, Opportunists, and Causative Agents
of Deep Mycoses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 357
Lorenza Putignani, Silvia D’Arezzo, Maria Grazia Paglia,
and Paolo Visca
Contents
xv
18
Applications of Loop-Mediated Isothermal Amplificaton
Methods (LAMP) for Identification and Diagnosis of Mycotic
Diseases: Paracoccidioidomycosis and Ochroconis
gallopava infection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 417
Ayako Sano and Eiko Nakagawa Itano
19
Identification of the Genus Absidia (Mucorales, Zygomycetes):
A Comprehensive Taxonomic Revision . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 439
Kerstin Hoffmann
20
Molecular Characters of Zygomycetous Fungi . . . . . . . . . . . . . . . . . . . . . . . 461
Xiao-yong Liu and Kerstin Voigt
Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 489
.
Contributors
Dilip K. Arora National Bureau of Agriculturally Important Microorganisms
(ICAR), Mau, Uttar Pradesh 275101, India, aroradilip@yahoo.co.in
Renuka N. Attanayake Department of Plant Pathology, Washington State
University, Pullman, WA 99164, USA
Kurt Brunner Institute of Chemical Engineering, Research Area Gene Technology
and Applied Biochemistry, Gene Technology Group, Vienna University of
Technology, Getreidemarkt 9, A-1060 Vienna
Simon Bulman Plant & Food Research, Private Bag 4704, Christchurch,
New Zealand; Bio-Protection Research Centre, Lincoln University, P.O. Box 84,
7647 Canterbury, New Zealand
Francesca Cardinale DiVaPRA – Plant Pathology, University of Turin, I-10095
Grugliasco, Turin, Italy
Weidong Chen Department of Plant Pathology, Washington State University,
Pullman, WA 99164, USA; USDA ARS Grain Legume Genetics and Physiology Research Unit, Washington State University, Pullman, WA 99164, USA,
w-chen@wsu.edu
Silvia D’Arezzo National Institute for Infectious Diseases “Lazzaro Spallanzani”
I.R.C.C.S., Via Portuense 292, 00149 Rome, Italy
Frank M. Dugan USDA-ARS, Washington State University, Pullman, WA
99163-6402, USA
Raimund Eck SIRS-Lab GmbH, Winzerlaer Str. 2, 07745 Jena, Germany
xvii
xviii
Contributors
Martin Eckart Institute of Microbiology, School of Biology and Pharmacy,
University of Jena, Neugasse 25, 07743 Jena, Germany, martin.eckart@uni-jena.de
Hesham Elhariry Biological Sciences Department, Faculty of Science, Taif
University, P.O. Box 888 Taif, Kingdom of Saudi Arabia
Katerina Fliegerová Department of Biological Basis of Food Quality and Safety,
Institute of Animal Physiology and Genetics, Czech Academy of Sciences, v.v.i.,
Vı́deňská 1083, 14220 Prague 4, Czech Republic, fliegerova@iapg.cas.cz
Tatiana Gagkaeva Laboratory of Mycology and Phytopathology, All-Russian
Institute of Plant Protection (VIZR), 196608 St. Petersburg-Pushkin, Russia,
t.gagkaeva@yahoo.com
Youssuf Gherbawy Botany Department, Faculty of Science, South Valley
University, 83523 Qena, Egypt
Paolo Gonthier Di.Va.P.R.A., Department of Exploitation and Protection of the
Agricultural and Forestry Resources, Plant Pathology, University of Torino, via
L. da Vinci 44, I-10095 Grugliasco (TO), Italy
Maria Grazia Paglia National Institute for Infectious Diseases “Lazzaro Spallanzani” I.R.C.C.S., Via Portuense 292, 00149 Rome, Italy
Fabio Guglielmo Di.Va.P.R.A., Department of Exploitation and Protection of
the Agricultural and Forestry Resources, Plant Pathology, University of Torino,
via L. da Vinci 44, I-10095 Grugliasco (TO), Italy
Liang-Dong Guo Systematic Mycology & Lichenology Laboratory, Institute of
Microbiology, Chinese Academy of Sciences, Beijing 100101, China, guold@sun.
im.ac.cn
Kerstin Hoffmann Institute of Microbiology, School of Biology and Pharmacy,
University of Jena, Neugasse 25, 07743 Jena, Germany, Hoffmann.Kerstin@
uni-jena.de
Beatriz Iamanaka Departamento de Biologia Geral, Centro de Ciências Biológicas, Universidade Estadual de Londrina, Caixa Postal 6001, CEP 86051-970
Londrina-Paraná, Brazil
Eiko Nakagawa Itano Department of Pathological Science, CCB, State University of Londrina, P.O. Box 6001, 86051-970 Londrina, Paraná, Brazil,
itanoeiko@hotmail.com
Contributors
xix
Narendra Kadoo PMB Group, Biochemical Sciences Division, National Chemical
Laboratory, Pune 411008, Maharashtra, India, ny.kadoo@ncl.res.in
Claudia Kesselboth Botany Department, Faculty of Science, South Valley
University, 83523 Qena, Egypt
Martin Kirchmair Institute of Microbiology, Leopold Franzens – University
Innsbruck, Technikerstr. 25, 6020 Innsbruck, Austria, Martin.Kirchmair@uibk.ac.at
Bandamaravuri Kishore Babu National Bureau of Agriculturally Important
Microorganisms (ICAR), Mau, Uttar Pradesh 275101, India, aroradilip@yahoo.
co.in; present address: Environmental Microbiology Lab, Department of Environmental Engineering, Chosun University, Gwang ju-501759, South Korea,
kishore_bandam@yahoo.co.in
Marc Lehmann SIRS-Lab GmbH, Winzerlaer Str. 2, 07745 Jena, Germany
Xiao-yong Liu Key Laboratory of Systematic Mycology and Lichenology, Institute of Microbiology, Chinese Academy of Sciences, No. 1 Beichen West Road,
Chaoyang District, Beijing 100101, P. R. China, liuxiaoyong@im.ac.cn
Robert L. Mach Institute of Chemical Engineering, Research Area Gene Technology and Applied Biochemistry, Gene Technology Group, Vienna University of
Technology, Getreidemarkt 9, A-1060 Vienna, Austria, rmach@mail.zserv.tuwien.
ac.at
Sigrid Neuhauser Institute of Microbiology, Leopold Franzens – University
Innsbruck, Technikerstr. 25, 6020 Innsbruck, Austria
George Newcombe Department of Forest Resources, and Center for Research on
Invasive Species and Small Populations, University of Idaho, Moscow, ID 838441133, USA, georgen@uidaho.edu
Giovanni Nicolotti Di.Va.P.R.A., Department of Exploitation and Protection of
the Agricultural and Forestry Resources, Plant Pathology, University of Torino, via
L. da Vinci 44, I-10095 Grugliasco (TO), Italy, giovanni.nicolotti@unito.it
Evans N. Njambere Department of Plant Pathology, Washington State University,
Pullman, WA 99164, USA
Maria Helena Pelegrinelli Fungaro Departamento de Biologia Geral, Centro de
Ciências Biológicas, Universidade Estadual de Londrina, Caixa Postal 6001, CEP
86051-970, Londrina-Paraná, Brazil, fungaro@uel.br
xx
Contributors
Manuel Pereiro Department of Dermatology, Laboratory of Mycology, Faculty of
Medicine, University Hospital Complex of Santiago de Compostela, C/San Francisco
S/N, 15706 Santiago de Compostela, Spain
Lidia Pérez-Pérez Department of Dermatology, University Hospital Complex of
Vigo, C/Porriño 5, 36209 Vigo, Spain, lidiacomba@yahoo.es
Lorenza Putignani Microbiology Unit, Children’s Hospital, Healthcare and
Research Institute Bambino Gesù, Piazza Sant’Onofrio 4, 00165 Rome, Italy
Ratul Saikia Biotechnology Division, North-East Institute of Science &
Technology, Jorhat 785006, Assam, India, rsaikia19@yahoo.com
Ayako Sano Medical Mycology Research Center, Chiba University, 1-8-1,
Inohana, Chuo-ku, 260-8673 Chiba, Japan, aya1@faculty.chiba-u.jp
Daniele Sartori Centro de Ciências Biológicas, Departamento de Biologia
Geral, Universidade Estadual de Londrina, Caixa Postal 6001, CEP 86051-970,
Londrina-Paraná, Brazil
Roland P.H. Schmitz SIRS-Lab GmbH, Winzerlaer Str. 2, 07745 Jena, Germany,
schmitz@sirs-lab.com
Otmar Spring Institute of Botany, University of Hohenheim, 70593 Stuttgart,
Germany, spring@uni-hohenheim.de
Giacomo Tamietti DiVaPRA – Plant Pathology, University of Turin, I-10095
Grugliasco, Turin, Italy, giacomo.tamietti@unito.it
Marta Hiromi Taniwaki Departamento de Biologia Geral, Centro de Ciências
Biológicas, Universidade Estadual de Londrina, Caixa Postal 6001, CEP 86051970, Londrina-Paraná, Brazil
Marco Thines Institute of Botany, University of Hohenheim, 70593 Stuttgart,
Germany
Jaime Toribio Department of Dermatology, Laboratory of Mycology, Faculty
of Medicine, University Hospital Complex of Santiago de Compostela, C/San
Francisco S/N, 15706 Santiago de Compostela, Spain
Danila Valentino DiVaPRA – Plant Pathology, University of Turin, I-10095
Grugliasco, Turin, Italy
Contributors
xxi
Paolo Visca National Institute for Infectious Diseases “Lazzaro Spallanzani”
I.R.C.C.S., Via Portuense 292, 00149 Rome, Italy; Department of Biology, University of Roma Tre, Viale Marconi 446, 00146 Rome, Italy, visca@uniroma3.it
Ivan Visentin DiVaPRA – Plant Pathology, University of Turin, I-10095
Grugliasco, Turin, Italy
Kerstin Voigt Institute of Microbiology, School of Biology and Pharmacy,
University of Jena, Neugasse 25, 07743 Jena, Germany, kerstin.voigt@uni-jena.de
Tapani Yli-Mattila Laboratory of Plant Physiology and Molecular Biology,
Department of Biology, University of Turku, FIN-20014 Turku, Finland, tymat@
utu.fi
.
Part I
Plant Pathological and
Environmental Biological Aspects
Chapter 1
Fungal Pathogens of Plants in the Homogocene
George Newcombe and Frank M. Dugan
Abstract As the pace of biotic homogenization has accelerated over time, the
threat of novel phytopathogens has become a question of growing importance for
mycologists and plant pathologists. Meanwhile, this question is but one of a whole set
of related questions that invasion biologists are attempting to answer. Pathogen release
is of interest to both sets of scientists because it provides a measure of the extent to
which previously isolated mycobiotas have undergone cryptic homogenization, and at
the same time it is the basis for a promising hypothesis to explain plant invasions. We
argue that only a fraction of all first encounters between novel pathogens and evolutionarily naive plants could result in susceptible outcomes. This is analogous to the fact
that only a fraction of all plant introductions result in plant invasions.
1.1
Introduction
Geologists define the last 10,000 years, or our current epoch, as the Holocene
(Bishop 2003). What has been described as the “Neolithic Revolution” also dates
from 10,000 years ago (Wells 2007). Spurred by early developments in crop
domestication in regions such as the Fertile Crescent (Wells 2007), Neolithic
farmers began to move to and settle in new areas with their crops ten millennia
ago (Vaughan et al. 2007). What was no doubt at first gradual and local ultimately
became global. Human migrations and population expansions during the Holocene
are mixing the previously isolated biotas of the world at an accelerating pace
(Mooney and Cleland 2001). Organisms outside their native ranges bear many
G. Newcombe
Department of Forest Resources, and Center for Research on Invasive Species and Small
Populations, University of Idaho, Moscow, ID 83844-1133, USA
e-mail: georgen@uidaho.edu
F.M. Dugan
USDA-ARS, Washington State University, Pullman, WA 99163-6402, USA
Y. Gherbawy and K. Voigt (eds.), Molecular Identification of Fungi,
DOI 10.1007/978-3-642-05042-8_1, # Springer-Verlag Berlin Heidelberg 2010
3
4
G. Newcombe and F.M. Dugan
descriptors: non-native, nonindigenous, exotic, introduced, or alien. Non-native
pathogens are additionally called “novel.” Some non-native organisms have proven
invasive, and invasion biologists have begun to describe the latter part of our epoch
as the Homogocene a term coined by Gordon Orians (Rosenzweig 2001a). This
term invokes the global scope and increasing rate of anthropogenic, biotic homogenization that is defined as the “gradual replacement of native biotas by locally
expanding non-natives” (Olden et al. 2004). The consequences of homogenization
for biotic communities and ecosystem processes are the subject of a growing
research effort; here we focus on fungal pathogens in the Homogocene.
Unsurprisingly, most of the literature of invasion biology focuses on plants and
animals (Pyšek et al. 2006), leaving mycologically oriented ecologists to wonder
about fungi. Crop pathogens are of course exceptional in this regard as they are
often discussed in the phytopathological literature (Rossman 2009; Stukenbrock
and McDonald 2008) and lists of such pathogens that are thought to be non-native
are frequently compiled (Madden 2001). The most famous historical example is
arguably the pseudo-fungus (oomycete) associated with the Irish potato famine,
Phytophthora infestans. Both the host and pathogen probably originated from the
Andes (Gómez-Alpizar et al. 2007), and their reunion in Ireland proved disastrous
both for the crop and the people who depended on it. Other examples include black
Sigatoka and yellow Sigatoka of banana (causal agents Mycosphaerella musicola
and M. fijiensis, respectively). In these cases, the host is from Southeast Asia, and
this may also be true for these fungi that were nevertheless first documented in Fiji;
both diseases now constitute global epidemics on banana (Marı́n et al. 2003). Other
instances from agriculture are concisely mentioned here and there in what follows.
However, this review emphasizes examples of plants from natural plant communities (i.e., nonagricultural settings). Chestnut blight and white pine blister rust
(discussed below) are widely investigated, but we present many other instances
much less familiar to the scientific public. We believe that a careful examination of
the behavior of fungal phytopathogens in the Homogocene reveals ecologically
significant patterns. These patterns should be of as much interest to invasion
biologists and ecologists as they are to mycologists and plant pathologists, because
fungi influence plants even while going unnoticed.
Voyaging peoples have likely always brought useful and favored plants and
animals with them to be deliberately introduced to new lands that they encountered.
Before Captain Cook landed in Hawaii in 1778, Polynesian seafarers had already
discovered these remote, volcanic islands and introduced such plants as candlenut
(Aleurites moluccana), ti (Cordyline fruticosa), taro (Colocasia esculenta), sweet
potato (Ipomoea batatas), sugarcane (Saccharum officinarum), and perhaps two
dozen other species (Carlquist 1980). Such early plant introductions were certainly
not limited to Polynesia, or to plants brought with European colonists to the New
World. Plant-hunting expeditions were probably initiated as early as 3,000 years
before Columbus, as hieroglyphs appear to show that the Queen of Egypt sent out
collectors of exotic plants for her gardens (Baskin 2003). Mycologists know that at
least some endophytic and phytopathogenic fungi must have quietly accompanied
these plant introductions (Palm 1999, 2001; Palm and Rossman 2003). But what
can we say today about these co-introductions and their effects on Hawaiian
1 Fungal Pathogens of Plants in the Homogocene
5
and other ecosystems around the world? Were those co-introduced endophytes so
host-specific that we can be sure that they remained exclusive to their original
hosts? If they jumped to other hosts, presumably related ones (Gilbert and Webb
2007), what ecological effects might they have had, and how can we distinguish
them today from co-evolved interactions?
These questions go well beyond Hawaii, and include all fungi globally. Maritime
explorations by western Europeans that began in the early fifteenth century (Love
2006) were initially restricted in scope, but they gradually became global and much
more ambitious. Scientific travelers such as Alexander von Humboldt, Charles
Darwin, and Alfred Russell Wallace began in the nineteenth century to discover
how life’s diversity was distributed around the world. At the same time, plant
explorers of many nationalities were seeking to deliberately introduce desirable plants
to their home countries (Reichard and White 2001). Crop plants had already been
introduced almost everywhere that they would grow profitably; Columbus, for example, wasted no time in introducing one of the most important New World domesticates, maize, into Europe in 1493 (Rebourg et al. 2003); during the same year
Columbus introduced orange trees of Asian origin to Hispaniola (Haughton 1978).
Ten thousand years ago, homogenization was undoubtedly not occurring at
modern rates, although it had probably been initiated on local or regional scales.
So, the Homogocene cannot be said to have begun with the Holocene. Instead, 1500
would appear to be a good year to choose for the beginning of the Homogocene.
This date is also in agreement with the judgment of ecological, economic, and
social historians, whose titles or subtitles accordingly include phraseology suggestive of worldwide movement of goods and peoples beginning at this time, e.g.,
“Accumulation on a World Scale,” “Expansion of Europe,” “Modern WorldSystem,” etc. (Amin 1974; Crosby 2004; Wallerstein 1974, 1980, 1989). Five
hundred and nine years ago, the “Age of Discovery” was under way, and today,
deliberate plant introductions are so common that the “majority of woody invasive
plants in the United States were introduced for horticultural purposes – one study
found that 82% of 235 woody plant species identified as colonizing outside of
cultivation had been used in landscaping” (Reichard and White 2001). The
“Homogocene” may not yet be a serious term in science but it does simply and
directly evoke global commingling during the last half a millennium.
Plant-oriented invasion biologists in Europe already use 1500 to divide alien
plants (Pyšek et al. 2004) into those that are called “archaeophytes” if introduced
before 1500, and “neophytes” if introduced later. However, we hasten to make
explicit what we have already hinted at: migration or purposeful import of plant
materials well prior to 1500 probably made important contributions to homogenization on a regional, and sometimes even continental or oceanic, scale. In addition
to the example of Polynesia above, expansion of Neolithic farming cultures such as
the Arawak (from the upper Amazon and Orinoco basins to the West Indies), Bantu
(from western to southern Africa), and Indo-European (from a still disputed location, perhaps Anatolia or the European steppes, but eventually throughout Europe
and much of western and central Asia) moved plant materials considerable distances (Diamond and Bellwood 2003). Pronounced effects have been postulated for
movement of plant pests and diseases in these distant times, e.g., the “honeymoon
6
G. Newcombe and F.M. Dugan
hypothesis” of a comparatively pest- and disease-free agriculture in Neolithic
Europe (Dark and Gent 2001), or the introduction of Ascochyta blight of chickpea,
resulting in summer cropping systems in the Levant (Abbo et al. 2003). Literature
on movement of plant pathogenic fungi from the Neolithic through classical
antiquity has been summarized recently (Dugan 2008). Archaeobotanical or textbased analyses are particularly numerous for tracing the complex introduction of
crops into medieval Europe (Behre 1992; Campbell 1988; Harvey 1984, 1992;
Kroll 2005 ; Preston et al. 2004; Taavitsainen et al. 1998).
Introduced plants are not all equal ecologically. Introduced or alien plants can
become naturalized if they survive and regularly reproduce outside of cultivation
(Richardson et al. 2000b). Of course, only a small fraction of introduced plants
become naturalized. For example, in Florida, of approximately 25,000 non-native
or alien plant species, only 900 have become naturalized (Pimentel et al. 2005). A
further winnowing occurs as only a small fraction of naturalized species become
invasive, with invaders defined as species that have successfully spread away from
sites of introduction (Richardson et al. 2000b). These successive winnowings
characterize what is called the “tens rule” (Williamson and Fitter 1996), a rule of
thumb that reflects the fact that relatively few aliens become invaders (Kolar and
Lodge 2001). Plant and community ecologists are keenly interested in understanding this phenomenon.
In this chapter, we shall see how well concepts and definitions borrowed from
invasion biology might apply to fungi, especially fungal pathogens of plants. Is
there a “tens rule” for fungal pathogens, or are all alien fungal pathogens equally
likely to attack evolutionarily naive plants or a host from which they had been
separated? In describing the plants and pathogens that take part in “first encounters”
as evolutionarily “naive” and “novel,” respectively, we are following the example
of Parker and Gilbert (2004). If the “tens rule” does apply, do we have, or can we
develop, hypotheses to predict which fungal pathogens will naturalize and which
will become invaders? The threat of fungi as novel pathogens is a traditional topic
for plant pathologists and mycologists (Rossman 2001). But, apart from the notorious example of chestnut blight, do novel pathogens generally act as “transformers”
that “change the character, condition, form or nature of ecosystems over a substantial area” (Pyšek et al. 2004)? What are the roles of fungi as potential facilitators of
plant invasions in the Homogocene? Recognizing and predicting invasions are the
central objectives of invasion biology (Kolar and Lodge 2001). But both objectives
seem to be predicated on knowing the native, geographic ranges of the organisms in
question, a problematic area for mycology.
1.2
Native Ranges of Fungi
In the eighteenth century, the French naturalist, Georges Buffon, had observed
that different continents had different assemblages of macrobes (i.e., plants and
animals) (Cox and Moore 2005). In the nineteenth century, Humboldt had
1 Fungal Pathogens of Plants in the Homogocene
7
discovered the predictability of species area relationships in that larger areas
held more species (Rosenzweig 1995), but again this was known to apply only to
macrobes. Spatial scaling and diversification of fungi were little studied until
recently when species-area relationships of fungi were demonstrated to be
similar to those of macrobes (Green et al. 2004). This was not a trivial finding
because even today some microbiologists maintain the view that microbial
eukaryotes have global ranges (Fenchel and Finlay 2004). The views of Beijerinck, that species of bacteria were cosmopolitan, or of Baas-Becking, that
“everything is everywhere” (Fenchel and Finlay 2004), have also been
challenged recently by application of the sequence-based phylogenetic species
concept of fungi (Taylor et al. 2006).
Mycologists are now learning that most fungi do conform to Buffon’s Law and
to spatial scaling rules for macrobes. However, it does not follow that it will be easy
to determine the native ranges of those fungi that do conform, for reasons that will
be discussed. And then there are undoubtedly fungi that do not conform. For
example, some saprophytic hyphomycetes, such as common Cladosporium species,
are associated with a very broad range of substrata. Such species do indeed seem to
have cosmopolitan distributions as evidenced by their incorporation over long time
periods into Arctic ice, alpine glaciers, and permafrost throughout the Northern
Hemisphere (summarized in Dugan 2008).
Macrobiologists may be surprised to learn that the native ranges of fungi are
largely unknown. Yet, how could it be otherwise? Today, 83% and 90% of vascular
plants and vertebrates, respectively, are known to macrobiologists, whereas, at best,
from 7% to perhaps 20% of the fungi are presently described (Cox and Moore
2005; Hawksworth 2001; Rossman 2009). Now when a new species of fungus is
described, its current, geographic pattern of occurrence might suggest an original
native range. Unfortunately, that pattern could also be the product of homogenization since 1500. In contrast, the native ranges of macrobes are largely known, not
only because the species are largely known, but because their ranges were documented early in the Homogocene before homogenization had had large effects.
Disputes do exist, but they appear minor in scope to a mycologist. For instance,
Gayther Plummer proposed that the most mysterious of native trees of North
America, Franklinia alatamaha, or the Franklin tree, was actually introduced
from Asia a few decades before the Bartrams discovered a small grove in 1765
(Rowland 2006). Most botanists, however, disagree with Plummer (USDA n.d.).
The native ranges of annual brome-grasses have more recently presented more
serious challenges to botanists (Smith 1986), and other examples exist of course,
but botanists have a set of criteria for dealing with problematic taxa: paleobotanical
evidence of native status, records of their presence in their current range by early
botanists, and current presence in natural habitats (Pyšek et al. 2004).
Mycologists face the unknown species problem, and the problem of the near
total lack of knowledge of pre-Homogocene distributions. Mycologists were not on
board the ships of the explorers and palaeomycology can hardly arbitrate disputes,
as it is “in its infancy” (Stubblefield and Taylor 1988); others have even argued
that the fungi lack “any significant fossil record” (Cain 1972). Even today fungi
8
G. Newcombe and F.M. Dugan
are more intensively studied in managed habitats, as pathogens of agicultural crops,
than in natural habitats where fungi provide ecosystem services on a massive
scale. Last, but not least for a book on the molecular identification of fungi,
“molecular diagnostic tools are only as good as the systematic underpinnings
upon which these tools are based” (Rossman 2009), and upheavals in fungal
systematics are common today.
What can we make of a new species such as Cladosporium subtilissimum that
was described recently from material in Slovenia and the northwestern United
States (Schubert et al. 2007)? It could have been cosmopolitan prior to the Homogocene, but can we rule out the role of homogenization in producing its current
distribution? Climate change can of course also cause range shifts (Parmesan 2006),
but homogenization is more likely to be the source of the error that we are
concerned with here: calling an invaded or naturalized range a native range or
part of a native range. How can this error be avoided? And to what extent have
previously isolated mycobiotas already been cryptically homogenized?
1.3
Pathogen Release
A roundabout but fruitful way to approach the latter question is through the
pathogen release hypothesis, according to which alien plants are less regulated by
pathogens than native plants (Keane and Crawley 2002). But first, if all fungi were
everywhere, as Beijerinck, Baas-Becking, Fenchel, and Finlay have asserted is the
case for other microbes (Fenchel and Finlay 2004), there would be no pathogen
release for plants from plant pathogenic fungi. Plants would have the same set of
fungal pathogens in both their native and invaded ranges. The environment (i.e., the
host plant) would select.
Is pathogen release a real phenomenon? Using the USDA Fungus–Host Distributions database of the Systematic Mycology and Microbiology Laboratory,
Mitchell and Power showed that for “473 plant species naturalized to the United
States from Europe” there were 84% fewer rust, smut, and powdery mildew species
infecting plants in their naturalized ranges than in their native ranges (Mitchell and
Power 2003). The SMML database is by far the most extensive of its kind with
“reports of fungi on plant hosts throughout the world that includes over 94,000
fungal species” (Rossman 2009). One could also cite specific examples of fungi that
have been deliberately introduced for classical biocontrol of weedy plants that more
directly confirm the pathogen release hypothesis for phytopathogenic fungi (Cullen
et al. 1973), but Mitchell and Power’s paper was the first study to show the
generality of this phenomenon. Another way of phrasing this is that if phytopathogenic fungi were everywhere, then pathogen introductions would not be a threat. To
prove that this belief represents a completely false sense of security, one has to look
no further than the chestnut blight fungus that transformed an ecosystem (Cox
1999; Liebhold et al. 1995; Rizzo and Garbelotto 2003).
1 Fungal Pathogens of Plants in the Homogocene
9
Although plants may at first leave their fungal enemies behind when introduced
outside their native ranges, in keeping with pathogen release, one can imagine that
inadvertent introductions of those same enemies would slowly counter the pathogen
release effect over time. These “pathogen reunions” do occur, and they are perhaps
the best measure that we have of the rate of introduction of fungi (i.e., fungal
homogenization) around the world. For example, when rust occurred on Centaurea
diffusa, an invasive plant of Eurasian origin, for the first time in North America in
1989 (Mortensen et al. 1989) or for the first time in the United States in 1992
(Dugan and Carris 1992; Palm et al. 1992), these pathogen reunions ended more
than 80 years of release from rust dating from 1907, the year that C. diffusa itself
was introduced into North America (Maddox 1982). This rust, Puccinia jaceae var.
diffusae of Eurasian origins (Savile 1970b), is easily distinguished from the only
rust fungus, Puccinia irrequiseta, that occurs on the only North American species
of Centaurea, C. americana (Savile 1970a).
In the case of tansy, or Tanacetum vulgare, plants were introduced and
cultivated by English colonists in North America for culinary and medicinal
purposes (Haughton 1978). Rust, common in its native range, was absent from
this introduced range. Some 400 years after the introduction of tansy, Puccinia
tanaceti was finally reunited with its host for the first time in the North American
range of tansy (Newcombe 2003b).
Cochliobolus carbonum provides an example of serial pathogen reunions in that
it must have followed the introduction of its host, Zea mays, around the world to the
point where the fungus itself is now cosmopolitan. Some of the reunions were
relatively recent. For instance, C. carbonum only reached Great Britain in 1972
(Jones and Baker 2007), which is presumably long after Z. mays was introduced
there, as the plant was introduced into Europe in 1493 by Columbus (Rebourg et al.
2003). C. carbonum had reached Australia 6 years before it arrived in the U.K. (Farr
et al. n.d.). Soybean rust, caused by Phakopsora pachyrhizi and P. meibomiae, also
took considerable time to be reunited with its agriculturally important host around
the world (Rossman 2009).
It is not clear how lengthy periods of pathogen release might potentially be as
many pathogen reunions have yet to occur. Morus alba, the white mulberry,
was deliberately introduced from China in an attempt to establish a silk industry
in the U.S. more than 400 years ago (Duncan and Duncan 1988). The tree
has naturalized, and even become locally invasive in the U.S., but its rust
fungi (i.e., species of Cerotelium, Peridiopsora, Phakopsora, and Kuehneola)
have remained in the native range of their host (Farr et al. n.d.). Powdery
mildews, on the other hand, have reunited with introduced populations of
white mulberry in western Europe and Central America, although not yet in
North America (Farr et al. n.d.).
Similarly, St.-John’s-wort, Hypericum perforatum, was introduced into North
America by Rosicrucian pilgrims in 1696 (Haughton 1978), and it has since become
weedy and invasive across the entire continent (USDA n.d.). But more than
400 years later Melampsora hypericorum has yet to be reunited with H. perforatum,
10
G. Newcombe and F.M. Dugan
as this rust fungus has only been recorded in St.-John’s-wort’s native range in
Europe (Farr et al. n.d.). On the other hand, it was close to 2,000 years ago that the
Romans introduced H. perforatum to the U.K. (Haughton 1978), where reunion
with M. hypericorum eventually did occur sometime before 1913 (Grove 1913 ).
The “honeymoon hypothesis” of Dark and Gent (2001), mentioned above, posited
that some reunions of grave consequence to European agriculture were postponed
for centuries, but these reunions eventually took place as long distance movement
of seeds became more routine in the late Iron Age and Roman times.
Plants native to North America were also introduced to Europe where some
remain in a state of at least partial pathogen release. Helianthus tuberosus, the
inappropriately named “Jerusalem artichoke,” was brought to Europe from North
America in the early 1600s (Hedrick 1950). Although Puccinia helianthi was then
reunited with its host in western Europe nearly 400 years later, other rust fungi
remain restricted to the native range (e.g., Coleosporium helianthi) (Farr et al. n.d.).
A similar pattern of pathogen release is known for Helianthus annuus, the
cultivated sunflower, also a native of North America that became widely cultivated
around the world.
It is important to note that pathogen reunions may be confused with infection by
morphologically similar fungi that are native to the naturalized range of an introduced plant. For instance, Populus nigra is Eurasian, but it has been widely planted
in North America as cv. ‘Italica,’ the columnar Lombardy poplar. Venturia infection of P. nigra in North America could potentially represent pathogen reunion by a
Eurasian Venturia, or host switching by a Venturia that is native to North American
Populus. As it turns out, Venturia populina, a Eurasian fungus, was determined to
be causing leaf and shoot blight of P. nigra (Newcombe 2003a), so this was a case
of pathogen reunion. Venturia inopina, occurring on a North American species of
Populus, P. trichocarpa, is morphologically similar to V. populina, but it has not
switched to P. nigra. It was the specificities of these two species of Venturia for
their respective hosts, expressed in a common environment, that actually led to
discernment of subtle, but consistent, differences in morphology and in ITS
sequences. In retrospect, Venturia blight of P. nigra in North America could easily
have been misinterpreted as host switching, or simply as the product of a fungus
with a broader host range and larger geographic range than either of these species of
Venturia actually has.
In general, most of the introductions of alien or so-called “invasive” plant
pathogens appear to be pathogen reunions. In a recent study of 1970–2004,
among the introductions of non-native plant pathogens into the U.K., 85% were
reunions on plants that were themselves introduced. Only 15% were first reports of
pathogens on native, wild plants of the U.K., and not all of these were necessarily
reports of alien pathogens (Jones and Baker 2007); some could have been native
pathogens that had been overlooked because their hosts lacked economic importance. Pathogen reunions may be the best measure that we have of the rate of
introduction of fungi, but what do they tell us about the native ranges of fungi, the
primary question of this section?
1 Fungal Pathogens of Plants in the Homogocene
1.4
11
Inferring Native Ranges of Fungi from Pathogen Release
It is tempting to think that fungi with restricted host ranges must be native where
their hosts are native. Camellia, a genus of some 200 species, is endemic in eastern
Asia, with its center of diversity in southern China (Ta and Bartholomew 1984).
As Ciborinia camelliae is restricted to Camellia, its discovery on C. japonica in
Great Britain in 1999 (Jones and Baker 2007) should ultimately be traced back to a
native range in eastern Asia even though other parts of the world may have been
stepping stones. If species of Camellia had never been introduced outside eastern
Asia, the inference of sympatry for its host-restricted fungi would be unequivocal.
Ornamental species of Deutzia provide such an example in that they are also
endemic to Asia where seven taxa of rust fungi commonly infect them (Farr et al.
n.d.). Unlike C. camelliae, records of rust on Deutzia outside the native range are
absent even though D. scabra was introduced to the U.S. as early as 1822 (Rehder
1940).
Searches of the SMML Fungus–Host Distribution Database (Farr et al. n.d.)
suggest restricted host and geographic ranges of fungi too numerous to comprehensively list here, but it is instructive to provide examples. Three species of Pucciniastrum occur only on Asian species of Acer, maple, and only in Asia. Rust occurs
on the English oak, Quercus robur, in its native range but not in its introduced range
in North America, even though Uredinales is well represented on North American
Quercus. Amelanchier alnifolia supports 17 rust taxa in its native range in North
America, but none in Europe where it has naturalized (Zerbe and Wirth 2006).
Presence in the host’s native range and absence in its naturalized range allow for
strong inference of the native range of a fungus (Table 1.1); presence in both of the
host’s ranges is problematic only in the absence of historical records of absence of
the fungus in one of them.
It is even more tempting to think that the combination of Fahrenholz’s
rule and knowledge of the native ranges of plants can be used to further
strengthen inferences of native ranges of fungi. Fahrenholz’s rule postulates
that “parasites and their hosts speciate in synchrony” (Hafner and Nadler 1988).
If host switching were not an issue, then native ranges of hosts should also be
native ranges of their parasites. However, host switching is an issue (Jackson
2004).
Host switching is best exemplified by absence in the host’s native range and
presence in its naturalized range. This requires some explanation, aided by the
example of Eucalyptus rust (Grgurinovic et al. 2006). Puccinia psidii causes
Eucalyptus rust but the first reports of this disease were not from the native
range of species of Eucalyptus in Australia. Instead, this rust fungus was first
reported on plantations of eucalypts grown in Brazil. Evidently, P. psidii had
switched, or jumped, from species of Myrtaceae native to South America to
introduced species of Eucalyptus that also belongs to Myrtaceae. Host switching
can also be inferred from the early years of agriculture, e.g., for formae speciales
of Blumeria graminis. Strict coevolution was apparently absent between this
12
G. Newcombe and F.M. Dugan
Table 1.1 Three categories of first encounters between evolutionarily naive plants and novel pathogens that depend on two factors: (1) which party to the
encounter is alien, and (2) whether opportunities for encounters will be prolonged or brief. The category of the encounters in turn affects how susceptible and
resistant outcomes of first encounters contribute, or not, to biotic resistance
Time
Evolutionarily naive parties to first encounter
Biotic resistance (BR) of native biotic community
versus alien plants or alien pathogens
Examples of encounters
Naive Plant
Novel Pathogen
Expected outcome of
Category Opportunities for encounters
(discussed in text)
encounters, if
(prolonged by pathogen
contributing to BR
reunion)
1
Extended, as naturalized, alien
Alien
Native
Susceptible (S)
R (Prunus serotina resistant to
Uredinales in Europe). S
plants remain exposed to
(individuals of Pinus
pathogens of native plants
(no)
sylvestris susceptible to
Endocronartium harknessii
in North America)
2
Extended, when alien
Native
Alien
Resistant (R)
R (6 of 7 taxa of Malus resistant
to Podosphaera leucotricha
pathogens are reunited with
alien, naturalized plants
in N. America). S (Malus
(yes)
angustifolia, the seventh
taxon, susceptible to P.
leucotricha in N. America)
3
Short (no)
Native
Alien
Resistant (R)
R (North American pines with
Cr genes for resistance to
Cronartium ribicola, an
Asian fungus). S
(individuals lacking these
genes, in the same North
American pines)
1 Fungal Pathogens of Plants in the Homogocene
13
powdery mildew and its grass family hosts in western Asia (Wyand and Brown
2003). Likewise, the barley scald pathogen, Rhynchosporium secalis, apparently
evolved on other hosts outside the center of diversity for barley (Zaffarano et al.
2006).
1.5
Genetic Criteria for Native Range
Host range is sometimes not specific enough to even suggest a particular native
range for a fungus. For example, Venturia inaequalis, the apple scab pathogen,
affects all species of Malus, some of which are native to North America although
most are Eurasian. Records of occurrence of V. inaequalis might be misleading in
that the apple, first domesticated in central Asia, was introduced by early explorers
everywhere that it would grow (Hedrick 1950). It is common in such cases to
hypothesize that genetic variation will be greatest in the native range. Using this
criterion, Gladieux et al. showed that V. inaequalis is likely native to the same area
in Asia in which apple itself was domesticated (Gladieux et al. 2008). Similarly, an
Asian origin of the dry rot fungus, Serpula lacrymans, has been inferred from a
study of its genetic variation (Kauserud et al. 2007). Genetic variation also places
the amphibian chytrid fungus, Batrachochytrium dendrobatidis, in a native range in
South Africa (Weldon et al. 2004) from where it has spread to cause a pandemic.
Interestingly, the highest genotypic diversity for the human dermatophyte, Trichophyton rubrum, is in Africa, where Homo sapiens itself evolved (Gräser et al. 2007).
Genetic diversity is not likely to be by itself an infallible criterion of native range,
however. Plants with outcrossing mating systems are frequently as genetically
diverse in their naturalized or invaded ranges as they are in their native ranges
(Novak and Mack 2005). Ambrosia artemisiifolia, a North American plant, maintains high genetic diversity in its invaded range in France (Genton et al. 2005).
Studies of Bromus tectorum have shown that even selfing plants may be as diverse in
the invaded range, in North America, as in the native, Eurasian range, if the invasion
involved multiple introductions (Novak and Mack 2005). A recent summary of 20
analyzes of genetic diversity in invasive plant populations showed that estimates of
total genetic diversity vary from “none detected” to “high” (Ward et al. 2008).
Similar caveats may apply to sole use of a genetic criterion for determination of
native ranges of fungi; genetic diversity of pine-associated Sphaeropsis sapinea
is high in South Africa where the fungus must have been introduced from the
northern hemisphere (Smith et al. 2000). Conversely, North American populations
of Entoleuca mammata are genetically more variable than introduced populations in
Europe (Kasanen et al. 2004). The oak wilt fungus, Ceratocystis fagacearum, is only
known to occur in the middle and eastern United States, but its genetic homogeneity
has led some researchers to hypothesize an exotic origin; the oak populations of
Mexico or Central America have been suggested (Juzwik et al. 2008). An alternative
hypothesis to explain low diversity is “the local genesis of a new and reproductively
isolated strain or species” (Zambino and Harrington 2005).
14
G. Newcombe and F.M. Dugan
However, low genetic variation can also characterize ancient and relictual species. For example, the Wollemi pine, Wollemia nobilis, is the only extant member
of its genus, surviving only as a single, small population in a canyon in Australia
(Peakall et al. 2003). No genetic variation whatsoever has been detected in
W. nobilis. Genetic drift can reduce genetic variation in small and isolated populations
of plants (Ouborg et al. 2006), and of organisms generally, but this explanation for
genetic homogeneity of fungal species has not been widely considered.
1.6
Inferring Native Ranges of Pathogenic Fungi
from Resistance
Given historical examples of extreme susceptibility of plants to novel pathogens
(e.g., chestnut blight, and white pine blister rust), and the resistance of related plants
elsewhere, it is tempting to think that host resistance can indicate native range of a
pathogen. Many plant pathologists have followed this line of thinking. Their
evolutionary explanation is that of selection for resistance in the presumptive native
range, and the absence of such selection elsewhere. The host in the presumptive
native range is thought to be evolutionarily adapted, whereas the host in the invaded
range is said to be evolutionarily naive with respect to the novel pathogen. The
Asian species of Castanea and Pinus were certainly more resistant to the chestnut
blight and white pine blister rust fungi, respectively, than were North American
species of Castanea and Pinus. With these examples as paradigm, researchers have
tried to infer the native range or origin of many other pathogenic fungi that were
unknown or poorly known prior to an epidemic.
The difficulties in doing so are twofold. First, the pathogen has to be present in
the native range of a mostly resistant, putative host. Secondly, the resistance of the
latter has to be adaptive and cannot be complete; the pathogen has to be able to
survive and reproduce, so there must either be some susceptible individuals of
an otherwise resistant species, or the adapted host could be tolerant (Roy and
Kirchner 2000). Even then, it may prove surprisingly difficult to distinguish adaptive resistance, which is associated with ongoing selection, from exapted resistance
(Newcombe 1998). Exaptations are characters that in a new evolutionary context
can have selective value even if they resulted from selection for something else
(Gould and Vrba 1982). For example, the resistance of Populus maximowiczii, a
poplar native to eastern Asia, to species of Venturia and Taphrina on Canada’s
Vancouver Island could only have been construed as adaptive if there had been
evidence that those fungi were native to eastern Asia. Needless to say, that would
not have been a parsimonious interpretation (Newcombe 2005).
The evolution of plant-pollinator and plant-herbivore interactions may be linked
through exaptations (Armbruster 1997). However, the linkages of exaptations for
resistance to pathogens are unknown. One can only speculate that the function of
genes in a poplar species in eastern Asia for resistance to Vancouver Island fungi
1 Fungal Pathogens of Plants in the Homogocene
15
would presumably be related to defense of some kind. Adaptive resistance must
also be distinguished from nonhost resistance that is predicted, but not explained,
by phylogenetic signal (Gilbert and Webb 2007; Newcombe 2005).
Unfortunately, little attention has been paid to these distinctions when inferring
native ranges of plant pathogens. In discussing root rot of Port Orford cedar caused
by Phytophthora lateralis, the assumed relationship between resistance and origin
of a pathogen was stated in this way: “P. lateralis was described in 1942. It is
suspected to be of Eurasian origin because Asiatic species of Chamaecyparis resist
it; resistance may have arisen through coevolution with the pathogen (Sinclair et al.
1987).” Eighteen years later however, Sinclair adopted a much more cautious
position: “P. lateralis, origin unknown” (Sinclair and Lyon 2005). This caution in
inferring native ranges of pathogens from the geographic distribution of resistance
is warranted as the examples which follow will hopefully make clear. In the
instance just discussed, the nature of resistance (i.e., adaptive versus exapted/
nonhost) of Asian Chamaecyparis to P. lateralis remains unclear.
Dogwood anthracnose, for example, is also thought to be caused by a highprofile, alien pathogen, Discula destructiva. Discula destructiva has been regarded
as an alien pathogen in North America (Redlin 1991), that has more recently
appeared in the U.K. (Jones and Baker 2007), and in western Europe (Holdenrieder
and Sieber 2007). Its appearances in the U.K. and Europe have been on Cornus
florida that is native to North America. Susceptibility associated with severe
damage and mortality in nature is only seen in the North American species,
C. florida and C. nuttallii (Sinclair and Lyon 2005). Inferring the native range of
D. destructiva from these observations, one would conclude that its origins were
Eurasian. But, actually, resistance is not a helpful criterion because it characterizes
at least some species of Cornus native to each one of the three continents where
D. destructiva could be native: North America, Europe, and Asia (Holdenrieder and
Sieber 2007; Sinclair and Lyon 2005). Although the native range of D. destructiva
has been hypothesized on the basis of host resistance to specifically coincide with
that of Cornus kousa in eastern Asia (Redlin 1991), the fungus has never been
reported on C. kousa in its native range. Fourteen fungi have been recorded on
C. kousa in eastern Asia (Farr et al. n.d.), but D. destructiva is not one of them.
Interestingly, C. florida, grown as an introduced ornamental in Japan, has proven
susceptible there to endemic Pucciniastrum corni, a number of taxa of Erysiphales,
and a few other fungi, but D. destructiva has not been recorded on it. This evidence
of absence in Japan is not definitive but it does suggest that resistance-based
inferences of origin can be quite misleading.
Butternut canker provides another example. Sirococcus clavigignenti-juglandacearum is thought to be an alien pathogen in North America that might have
been introduced on seed of Asian species of Juglans such as J. ailantifolia (Ostry
and Moore 2007). But the only record of S. clavigignenti-juglandacearum on
J. ailantifolia is from the U.S. (Ostry 1997), and records of this fungus from Asia
are lacking on any host (Farr et al. n.d.). Nine fungal taxa have been recorded
on J. ailantifolia in Asia, so the fungi of the putative, adaptive host are not
completely unresearched (Farr et al. n.d.).
16
G. Newcombe and F.M. Dugan
Records of eastern filbert blight, caused by Anisogramma anomala, are also
restricted to North America (Farr et al. n.d.). But possibly because there were
records of this disease from the late 1800s, A. anomala is not thought to be alien
to North America (Sinclair and Lyon 2005). In fact, the native host of A. anomala is
hypothesized to be Corylus americana (Coyne et al. 1998). But if resistance
patterns were the sole criterion for native range, the resistance of some species of
Corylus native to each of North America, Europe, and Asia would again be
problematic (Coyne et al. 1998; Sinclair and Lyon 2005). Furthermore, if
A. anomala is not present in Europe and Asia, and is truly native to North America,
then the resistance of Eurasian species of Corylus must be of the exapted or nonhost
variety rather than adaptive. As some individuals of the European hazelnut,
C. avellana, are susceptible, nonhost resistance would seem to be ruled out. So,
the dominant, “Gasaway” gene that is inherited from resistant individuals of the
European hazelnut (Coyne et al. 1998) would be interpreted here as exapted.
Seiridium cankers of cypress are caused by three species of Seiridium. Relatively resistant species of Calocedrus, Chamaecyparis, Cupressus, Juniperus, Taxodium, Thuja, and Thujopsis are native to both Eurasia and North America (Sinclair
and Lyon 2005). Once again, the lack of any discrete, geographic source of
resistance known to be adaptive would thwart any attempt to pin any of the three
species of Seiridium to any particular native range, at least using the sole criterion
of resistance.
Fusiform rust, caused by Cronartium quercuum f.sp. fusiforme, is also instructive. The fusiform rust fungus is thought by many to be native to the region where it
is currently most damaging: the southeastern U.S. However, after testing 45 species
of Pinus for susceptibility/resistance to C. quercuum f.sp. fusiforme, an origin of
C. quercuum f.sp. fusiforme in Central America was hypothesized (Tainter and
Anderson 1993). This hypothesis was congruent with the relatively strong resistance of species of Pinus from Central America. However, equally strong resistance
of Asian and Mediterranean species was evident in this study. To be consistent in
applying the criterion of resistance, the authors would then have had to propose a
native range for C. quercuum f.sp. fusiforme involving widely scattered, disjunct
populations in Asia, Europe, and Central America, quite unlike that of any species
of Pinus that hosts the fusiform rust fungus.
The oak wilt fungus, Ceratocystis fagacearum, of the middle and eastern United
States, has already been mentioned. Its genetic homogeneity has led some researchers to hypothesize an exotic origin (Juzwik et al. 2008). But, it is impossible to infer
the native range of C. fagacearum from host resistance alone for no other reason
than that this subject remains seriously understudied in some 530 species of
Quercus (Mabberley 2008). So, in addition to the challenging need to distinguish
adaptive and exapted/nonhost resistance, undersampling issues can be formidable.
One might imagine that difficulties in determining native ranges of fungi from
resistance are only encountered when alien pathogens are obscure and of little
importance. But not only are the examples just cited important, but even fungi as
important as the Ophiostoma species that have caused global pandemics of Dutch
elm disease in the past century, remain of uncertain, geographic origin (Brasier and
1 Fungal Pathogens of Plants in the Homogocene
17
Buck 2001). Surveys in China (Brasier 1990) and in the Himalayas (Brasier and
Mehrotra 1995) were undertaken because resistant species of Ulmus are naturally
distributed there. However, O. ulmi and O. novo-ulmi.were not found in either
surveyed region. Absence of the relevant pathogens implies that the resistance of
Asian elms is exapted or nonhost, rather than adaptive. It should be noted that
Ophiostoma species related to the Dutch elm fungus are one possible, and greatly
debated, cause of the great mortality of elms in Europe during the Neolithic
(summarily reviewed in Dugan 2008).
The above examples should not only encourage caution in inferring native
ranges of fungi from resistance. They should also provoke questions about the
threat of novel pathogens of plants. Even if adaptive resistance is obviously, by
definition, absent in naive plants encountering novel pathogens, could not exapted
or nonhost resistance protect them, and if so, at what frequency?
1.7
First Encounters Between Evolutionarily Naive Plants
and Novel Pathogens
As previously mentioned, predicting outcomes of invasions is one of the central
objectives of invasion biology (Kolar and Lodge 2001). With plants and animals,
nonrelational hypotheses focus either on the relative invasiveness of potential
invaders or the relative invasibility of potentially invaded communities (Heger
and Trepl 2003). Relational hypotheses consider both. In all cases, however, it is
considered essential to know the original, pre-Homogocene, geographic ranges of
the organisms in question to develop and test hypotheses. To test the pathogen
release hypothesis (Keane and Crawley 2002), for example, one needs to compare
the enemies of a particular plant or animal in its native and invaded ranges. Novel
weapons might aid a plant invader but only when wielded against species that are
evolutionarily naive in the sense that they have never faced the weapons in question
(Callaway and Ridenour 2004). Even Darwin’s hypothesis, the first hypothesis of
invasiveness (Rejmánek 1996), that invasive species are more likely from alien
genera than from genera found in both ranges is, of course, predicated on knowing
what those ranges are (Darwin 1859).
For fungal pathogens involved in pathogen reunions, prediction of outcomes is
straightforward. Plant species “ABC,” known to be susceptible in its native range to
pathogen “abc,” is likely to be susceptible everywhere else to “abc,” provided that
the environment is conducive to infection and disease expression. We might assume
that the native range of “abc” is the same as that of “ABC,” but all we really need to
know for predictive purposes is that the latter is susceptible to the former somewhere else. But, pathogen reunions are not first encounters.
Outcomes of true, first encounters between naive plants and novel pathogens appear
to be much more challenging to predict. Thus far, we have been operating under
the assumption that for predictive purposes the native ranges of phytopathogenic
18
G. Newcombe and F.M. Dugan
fungi must be known. However, the status of a first encounter may be ascertained
merely by knowing that the two parties differ in their native ranges. In some cases,
we may know their native ranges: the host switching that, for instance, occurred
when naive Eucalyptus was introduced to South America and novel Puccinia psidii
switched to Eucalyptus from native Myrtaceae. But, in the case of Dutch elm
disease or dogwood anthracnose, as discussed above, neither the native ranges of
the novel pathogens nor the identities of their adaptive hosts have ever been
determined. Nevertheless, it is clear that these diseases do represent first encounters
that must involve host switching.
Such encounters also represent the fungal component of what invasion biologists
call “biotic resistance” (Parker and Gilbert 2004). Any and all organisms in a native
community can provide biotic resistance to repel invaders. When pathogenic fungi
switch from native plants to naive, alien plants, as in rust of Eucalyptus, they
contribute to biotic resistance. This scenario represents one of three categories of
first encounters between naive plants and novel pathogens that we emphasize here
(Table 1.1): (1) alien plants versus native pathogens; (2) native plants versus alien
pathogens involved in pathogen reunions, i.e., the majority of alien pathogens,
which exist in their new, non-native environments on alien but naturalized hosts
(Jones and Baker 2007); (3) native plants versus alien pathogens not involved in
pathogen reunions. The first two categories allow pathogens considerable lag
periods during which host switching may occur from their adaptive hosts. It is
important to recall that alien organisms frequently become invasive only after
considerable lag periods (Mack et al. 2000). The third category is distinct because
it involves alien pathogens that must switch to the naive host immediately upon
introduction because their adaptive host is absent.
The null hypothesis might be argued that these distinctions of three categories
are unnecessary because evolutionarily naive plants will always be decimated by
alien pathogens, particularly if the plants are closely related to the host of the alien
pathogen in question. The examples of white pine blister rust and chestnut blight
surely suggest as much. In the absence of selection for resistance, is not genetic
susceptibility to pathogens of exotic congeners inevitable and complete? The short
answer is no. Much of what we have already discussed implies this. The easiest way
to expand that answer is to further discuss resistance to pathogens that were clearly
alien, starting with the white pine blister rust fungus, Cronartium ribicola. The
latter was a “Category 3” alien pathogen in North America (Table 1.1), but with an
asterisk; it was introduced without an adaptive host but on a naive host, Pinus
strobus, to which it had already switched outside North America (Kinloch 2003).
Cronartium ribicola is considered native to eastern Asia where its adaptive hosts
are thought to include Pinus sibirica, P. armandii, P. koraiensis, P. wallichiana,
and P. pumila (Kinloch 2003; Kinloch and Dupper 2002; Sinclair and Lyon 2005).
The host range of C. ribicola spans the species of Pinus belonging to subgenus
Strobus that includes sections Quinquefoliae and Parrya (Gernandt et al. 2005).
These sections are especially speciose in North America and Asia, and less so in
Europe where P. cembra and P. peuce are native. When the latter two European
species, seven Asian species, and eight North American species were tested for
1 Fungal Pathogens of Plants in the Homogocene
19
blister rust resistance in Europe, only P. cembra and the Asian species, P. armandii
and P. pumila were completely resistant (Stephan 2001). Among the North
American species, P. aristata of section Parrya was more resistant than the
seven species representing section Quinquefoliae: P. strobiformis, P. balfouriana,
P. lambertiana, P. albicaulis, P. flexilis, P. monticola, and P. strobus. When blister
rust resistance was tested in North America, P. strobiformis was more resistant than
other species of North American origin (Sniezko et al. 2008).
The point of emphasis here is the fact that none of the North American species
encountering C. ribicola for the first time were completely susceptible because
resistant individuals have been found in each (Stephan 2001; Sniezko et al.
2008). In fact, four species (i.e., P. strobiformis, P. monticola, P. flexilis, and
P. lambertiana) have been shown in separate studies to possess major genes for
resistance, albeit at low frequencies (Kinloch 1992; Kinloch and Dupper 2002;
Kinloch et al. 1999, 2003). Although phenotypic evidence for these Cr genes was
not detected in whitebark pine (P. albicaulis), Mexican white pine (P. ayacahuite),
foxtail pine (P. balfouriana), and Great Basin bristlecone pine (P. longaeva), all of
these species might possess such genes at low frequencies that would simply
require additional sampling for their discovery (Kinloch and Dupper 2002). The
authors conclude that although “blister rust traditionally is considered an exotic
disease in North America, these results, typical of classic gene-for-gene interactions, suggest that genetic memory of similar encounters in past epochs has been
retained in this pathosystem” (Kinloch and Dupper 2002).
Before considering examples of exapted resistance other than the Cr genes, the
implications of gene-for-gene interactions require explanation. Disease resistance
in plants is often tackled by using some conceptual dichotomy. Van Der Plank
famously distinguished between vertical and horizontal resistance, for example
(Van Der Plank 1975). Gene-for-gene interactions characterize Van Der Plank’s
vertical resistance (Briggs and Johal 1994; Flor 1971; Thompson and Burdon
1992). Flor (1971) developed the gene-for-gene theory by performing correlated
studies of the inheritance of both host resistance and pathogen virulence using
cultivated flax and flax rust. Flor is typically quoted for defining these interactions
in this way: “for each gene that conditions reaction in the host there is a
corresponding gene that conditions pathogenicity in the pathogen.” Gene-for-gene
interactions can also be inferred, somewhat less rigorously (Thompson and Burdon
1992), by proving that there are a number of distinct, major genes for resistance
that allow pathogen isolates to be differentially distinguished as pathotypes. By
this definition, gene-for-gene interactions do characterize white pine blister rust
(Kinloch and Dupper 2002) and also poplar leaf rust that we shall discuss next as
it also involves the sudden appearance of “genetic memory” in first encounters
(Newcombe et al. 2001).
Recall that gene-for-gene interactions are thought to be the product of continuous coevolution (Person 1959, 1967). But both the poplar leaf rust pathosystem of
the Pacific Northwestern region and the blister rust pathosystems of the white pines
of North America appear to be the product of recent pathogen introductions,
exapted resistance genes, and recent, adaptive changes in the pathogen populations.
20
G. Newcombe and F.M. Dugan
Attempts to explain the Cr genes in terms of selection have been made; the highest
frequencies of Cr1 and Cr2 are in the American Southwest near overlaps with
pinyon pines of section Parrya and pinyon blister rust caused by an American
native rust fungus, Cronartium occidentale (Kinloch and Dupper 2002). However,
to positively demonstrate that C. occidentale was the selective agent that explains
evolutionary retention of Cr genes, one would have to show that Cr genes protect
species in section Quinquefoliae against C. occidentale (Kinloch and Dupper
2002). Otherwise, the retention of Cr genes in North American white pines appears
paradoxical given the absence of selection (Kinloch and Dupper 2002).
In the case of poplar leaf rust also, resistance genes were revealed by pathogen
introductions, raising again the question of their retention in the absence of selection. Complex pathogenic variation indicative of gene-for-gene interactions also
appeared very quickly in this system, once the pathogen population had undergone
hybridization to match that of its hybrid host (Newcombe et al. 2001). Some
background is needed to explain current gene-for-gene interactions in poplar leaf
rust in the Pacific Northwest of North America. Populus trichocarpa, the western
black cottonwood, is native to the region, along with its coevolutionary rust,
Melampsora occidentalis. When P. trichocarpa (T) from section Tacamahaca is
crossed with P. deltoides (D), the eastern cottonwood, from section Aigeiros, fastgrowing F1 hybrid clones can be selected. These TxD hybrids have been the
mainstay of commercial poplar plantations in the region for nearly three decades.
Initially TxD hybrids were rust-free. The resistance of P. deltoides to
M. occidentalis (Newcombe et al. 2000), was transmitted to all TxD F1 hybrids
indicating that these P. deltoides parents are dominant homozygotes in this respect.
In 1991, Melampsora medusae, the coevolutionary rust of P. deltoides, was found
in the region. It quickly became apparent that some TxD F1 hybrids were susceptible to M. medusae. Analysis of the inheritance of resistance to M. medusae in a TxD
hybrid poplar pedigree demonstrated that the Mmd1 gene for resistance was inherited from the P. trichocarpa parent (Newcombe et al. 1996). It is important to
note that this gene had gone unnoticed in previous studies of the resistance of
P. trichocarpa to M. occidentalis. The gene-for-gene explanation for the detection
of Mmd1 with M. medusae is that the latter evidently possesses the matching
avirulence allele, unlike the coevolutionary rust, M. occidentalis. Both P. trichocarpa
and M. medusae could even be fixed for this gene-for-gene pair as their interaction phenotype was always resistant, although testing was limited to nine
individuals of the former and four isolates of the latter from the southeastern U.S.
(Newcombe et al. 2000). Resistance to M. medusae was observed to segregate in the
TxD F1 because the P. trichocarpa parent was heterozygous at Mmd1 (Newcombe
et al. 1996).
Until 1995, there was no pathogenic variation in the rust population that simply
consisted of M. medusae. F1 clones either possessed the dominant Mmd1 allele for
resistance, or not. Emergence in the mid-1990s of the hybrid of M. medusae and
M. occidentalis, M. x columbiana, changed this situation. Previously resistant
TxD F1 clones became susceptible. It rapidly became apparent that there was
abundant pathogenic variation in the new hybrid population of M. columbiana
1 Fungal Pathogens of Plants in the Homogocene
21
(Newcombe et al. 2001). Just as M. medusae had allowed the Mmd1 gene to be
detected, new pathotypes of M. columbiana were the means by which three new
genes for resistance, Mxc1, Mxc2, and Mxc3 were discovered. A new gene-for-gene
pathosystem had appeared with exapted resistance genes and matching exapted
avirulence genes. Resistance genes appear to be quite common in Populus, perhaps
totaling in the hundreds (Tuskan et al. 2006). Hybridization has been hypothesized
to be a stimulus for the evolution of invasiveness in plants (Ellstrand and Schierenbeck
2000), and it may be so also for pathogenic fungi (Brasier 2000).
Hybridization of both host and parasite that merged two separate pathosystems
appears to account for the emergence of this gene-for-gene system. Reciprocal
hybridization of the kind discussed here could have had an evolutionary history of
repeated occurrence, as there is evidence of ancient hybridization between Populus
sections Tacamahaca and Aigeiros, at least since the Miocene (Eckenwalder 1984).
The genes for resistance and avirulence that now appear exapted could have been
selected episodically in the past in recurring, hybrid zones. Populus trichocarpa
and P. deltoides do currently hybridize naturally in parts of western North America
(Eckenwalder 1996). The ancient introgression of Pinus banksiana into Pinus
contorta in western North America (Critchfield 1985), has also left a signal in
terms of resistance genes, that is still evident today (Wu et al. 1996).
But the evolutionary basis for genes for resistance to a Eurasian poplar rust
fungus, Melampsora larici-populina, that are possessed by the North American
species of Populus, P. deltoides (Cervera et al. 1996; Villar et al. 1996), is harder to
imagine. We know that M. larici-populina was only introduced to North America in
the early 1990s (Newcombe and Chastagner 1993), so the selective force or agent
could not have been this fungus. The same question is raised by the abovementioned “Gasaway” gene that confers resistance to a fungus found only in
North America even though the gene itself is from a European plant, Corylus
avellana.
We have already mentioned that species and hybrids of Eucalyptus, introduced
to South America, encountered there for the first time a novel rust fungus, Puccinia
psidii, which shifted to Eucalyptus from native Myrtaceae (Grgurinovic et al.
2006). Many hybrids of E. grandis of widespread use in Brazilian plantations
have proven to be very susceptible to P. psidii; the latter also has a wide host
range in the Myrtaceae having been reported on 11 genera and 31 species
(Rayachhetry et al. 2001). Nevertheless, there are individuals of E. grandis that
are resistant; one harbors a major gene for resistance to P. psidii, the Ppr1 gene
(Junghans et al. 2003). How can we explain in terms of selection an Australian gene
for resistance to a South American fungus, without going back in time to the Late
Paleocene/Early Eocene thermal maximum, 55 mya, when there is evidence for
floristic exchange between South America and Australia that included Myrtaceae
(Morley 2003)? Moreover, some evolutionarily naive species of Myrtaceae appear
resistant, as species, to P. psidii (Rayachhetry et al. 2001). Another example is
found in the native, North American range of western gall rust, caused by Endocronartium harknessii. Scots pine (Pinus sylvestris), one of the most widely grown
of Eurasian pines in North America, possesses a recessive major gene for resistance
22
G. Newcombe and F.M. Dugan
to western gall rust (Van der Kamp 1991). This gene may be common in Scots
pine, at least in relation to the population of the western gall rust fungus in
British Columbia where the study was performed. Two Asian hard pines, Pinus
thunbergii and P. densiflora, are also resistant to western gall rust (Hopkin and
Blenis 1989), although genetic analyses of their resistance have not been performed.
From Populus deltoides of eastern North America were inherited QTL for resistance
to a Pacific Northwestern population of Mycosphaerella populicola (Newcombe and
Bradshaw 1996). Asian elms possess genes for resistance to black leaf spot caused
by the North American population of Stegophora ulmea (Benet et al. 1995). A last
example in this section is that of the NRSA-1 gene for resistance to Striga asiatica
that is found in a nonhost, Tagetes erecta, or marigold (Gowda et al. 1999).
1.8
A “Tens Rule” for Novel Pathogens
Exapted genes for resistance, such as the Cr, Mmd, Gasaway, and Ppr genes, have
been found in resistant individuals in otherwise susceptible species. As such,
exapted resistance differs from nonhost resistance in that the latter is presumed to
be fixed in species outside the host range of the pathogen in question. But the
evolutionary basis for this semantic distinction is unclear. In order to predict outcomes of first encounters between novel pathogens and evolutionarily naive plants,
some estimate of frequency is needed, even though the evolutionary basis for the
resistant outcome may be unknown. Examples suggest that the frequency of
resistant outcomes is probably high. For example, an Asian maple species planted
in North America is naive with respect to the “Category 1” pathogens (Table 1.1) of
North American native maples. Would Rhytisma americanum infect an Asian
maple grown in the U.S.? The answer appears to be no in that R. americanum is
limited to North American natives, Acer rubrum and A. saccharinum (Farr et al.
n.d.; Hudler and Jensen-Tracy 1998). Asian maples in North America are also
apparently resistant to the “Category 2” R. acerinum that occurs on Norway maples,
A. platanoides, in North America. The “Category 1” taxa of Mycosphaerellales that
are quite common on North American maples in North America also do not appear
to attack Asian maples at all (Farr et al. n.d.).
Would this pattern hold if we considered a North American plant that has
been introduced into a different continent? Consider Pinus contorta, or the North
American lodgepole pine, that is utilized quite commonly in forest plantations in
northern Europe. Three decades ago, Roll-Hansen noted that P. contorta is “immune
or nearly immune to all European rust fungi,” and “more resistant than P. sylvestris
to Phacidium infestans and Lophodermium pinastri” (Roll-Hansen 1978). Prunus
serotina, or black cherry, provides another good example because it is a North
American tree that has become invasive in European forests (Chabrerie et al.
2008). Although eight rust taxa affect Eurasian species of Prunus in Europe, none
of these “Category 1” pathogens infect P. serotina (Farr et al. n.d.). In other words,
none provide biotic resistance against this plant invader. This is not because
1 Fungal Pathogens of Plants in the Homogocene
23
P. serotina is immune to all rust fungi; in its native range in North America, four rust
taxa affect it (Farr et al. n.d.). Similarly, the “Category 2” pear trellis rust, Gymnosporangium fuscum, has remained confined in North America to the Eurasian genus
Pyrus as indigenous rosaceous genera are not known to be aecial hosts, and indigenous Juniperus populations are apparently resistant (Ziller 1974).
“Category 1” pathogens may switch immediately to long-term, alien plants, or
they may eventually produce some virulent propagules that successfully infect the
alien. Some past switches were likely not recorded immediately, so the importance
of the extended opportunities of a lag period that is used to distinguish categories
2 and 3 (Table 1.1) is not yet clear. For example, Hibiscus syriacus, the popular
rose-of-Sharon, was introduced to the Americas in the late sixteenth century from
its native range in Asia. In the ensuing, 400 years in the Americas H. syriacus
acquired five rust taxa that are not known to occur in its native range (Farr et al.
n.d.). But the exact dates of switching are not known. Oddly, the one rust species
that does occur on H. syriacus in India, Uromyces heterogeneus, has never been
reunited with its host in its introduced range.
“Category 2” pathogens are alien pathogens that have been reunited with their
adaptive hosts. The latter provide these pathogens with a lag period that they may
need to successfully infect naive, native plants. Podosphaera leucotricha causes
powdery mildew of apple, Malus domestica, that was domesticated in Eurasia. Like
Venturia inaequalis that was shown to be Eurasian in origin (Gladieux et al. 2008)
P. leucotricha appears to be Eurasian also. But, P. leucotricha has been reunited
with apple in every part of North America in which apples are cultivated (Farr et al.
n.d.) such that the seven Malus taxa native to North America have undoubtedly
been exposed to its inoculum. Six of the seven appear to be resistant to
P. leucotricha in that there are no records of this fungus on them. But one native
species of Malus in the southeastern part of the U.S., M. angustifolia, has proven to
be susceptible (Table 1.1). Phylogenetic signal does not appear to explain this
susceptible exception as M. angustifolia is no more closely related to adaptive
host species of Malus than resistant species of North America (e.g., M. coronaria)
(Robinson et al. 2001). So, in this case, resistance appears to be exapted rather than
nonhost. P. leucotricha has also been reunited in North America with Eurasian
species of Photinia, P. glabra and P. serratifolia. Extended opportunities for first
encounters with three species of Photinia native to North America have thus also
been assured, but outcomes thus far apparently involve nothing but resistance as no
records are known. This trend toward resistant outcomes of first encounters continues with two other genera of Rosaceae, Crataegus and Spiraea. Crataegus is
especially speciose in North America (USDA n.d.) but there are no records of any
of its taxa hosting P. leucotricha, even though C. cuneata in Japan does host
P. leucotricha; perhaps this record is of a pathotype that has never been introduced
into North America. In the case of Spiraea, P. leucotricha has been recorded on
Japanese spiraea, S. bumalda, in North America, but has not been recorded on 12
taxa of Spiraea native to North America (Farr et al. n.d.). If lag periods do not figure
in the outcomes of first encounters, then the three categories of Table 1.1 could be
collapsed.
24
G. Newcombe and F.M. Dugan
Examples such as these have not been subjected to genetic analysis, but they do
suggest a relatively high frequency of resistant outcomes when novel pathogens and
naive plants meet. Furthermore, first encounters must be common as naturalized
plants in the U.S. belong to 549 genera (USDA n.d.), of which 305, or 56%, are
represented in the U.S. by both the naturalized species and native congeners. Other
parts of the homogenized world are likely similar in affording many opportunities
for plants to encounter “Category 1” or “Category 2” pathogens in particular.
A variant of the “tens rule” may thus apply to alien, plant pathogenic fungi in
that only a fraction of all first encounters result in susceptible outcomes. This is
analogous to the fact that only a fraction of all plant introductions result in plant
invasions. This analogy, of course, does not imply that the same mechanism
explains both phenomena. Improvements in our knowledge of the “tens rule” for
novel fungal pathogens of plants will be built upon advances in the systematics and
diagnostics of fungi that allow us to distinguish between pathogen reunions and first
encounters. Improvements in our ability to predict which first encounters will result
in relatively rare, but devastating, susceptible outcomes will come with a deeper
understanding of the evolution and retention of genes for resistance.
1.9
Transformers
Susceptible outcomes of novel encounters can however be “transformative” if they
change the “character, condition, form or nature of ecosystems over a substantial
area” (Pyšek et al. 2004). The chestnut blight fungus, Cryphonectria parasitica,
was clearly a “transformer” in the range of Castanea dentata, the American
chestnut. The latter was an abundant species in eastern North America at the time
of the introduction of the blight fungus (Paillet 2002). C. dentata is no longer a
dominant, overstory tree species in those deciduous forests that are starting to be
dominated by oak and hickory (McGormick and Platt 1980). Unfortunately, “we
know very little concerning ecosystem response to the loss of chestnut” (Orwig
2002). Effects of blight on the food web were probably profound, but they were not
studied except anecdotally. The American chestnut itself was not driven to extinction by blight, but chestnut-specific insects likely were (Opler 1978).
A particular class of transformer among novel fungal pathogens would be one
which does cause the extinction of an evolutionarily naive plant species. However,
examples of this are not known. Possibly, novel pathogens came closest with the
above-mentioned Franklinia alatamaha. This tree species is not now extinct, but its
only natural population was extirpated shortly after the Bartrams discovered it.
Were it not for ex situ cultivation, F. alatamaha would now be extinct. Speculation
about the causes of the loss of the single, naturally occurring population abounds
(Rowland 2006), and that speculation includes the introduction of novel pathogens.
Small populations are notoriously susceptible to stochastic forces of extinction
that might include pathogens (Rosenzweig 2001b), as we have also briefly
1 Fungal Pathogens of Plants in the Homogocene
25
discussed. This is a serious concern for Wollemia nobilis that lacks genetic variation
(Peakall et al. 2003); that finding might indicate that W. nobilis has lost through
genetic drift genes for exapted resistance. Little is yet known however of the
susceptibilities of W. nobilis other than that it has been shown to be susceptible to
Phytophthora cinnamomi and to a species of Botryosphaeria (Bullock et al. 2000).
Genetic uniformity certainly affected the magnitude of tree mortality caused by the
Dutch elm fungus to Ulmus procera, the English elm, that turned out to be a 2,000year-old Roman clone (Gil et al. 2004).
1.10
Deliberate Introductions of Fungi
Deliberate introductions of fungi have likely been uncommon. Some introductions
have been made to control plant invaders (i.e., classical biological control) with
pathogens with narrow host ranges such as rust fungi (Bruckart and Dowler 1986).
Edible, cultivable mushrooms are certainly cultivated outside their native ranges
(Arora 1986). Australian ectomycorrhizal fungi “were likely introduced with eucalypt seedlings brought into peninsular Spain before plant quarantine restrictions
were observed” (Dı́ez 2005), and this introduction may have been deliberate if the
people transporting the seedlings knew of the dependence of eucalypts on these
fungi. For the same purpose, ectomycorrhizal associates of pine seedlings were
deliberately introduced into the southern hemisphere (Wingfield et al. 2001).
Unfortunately, these introductions also inadvertently brought with them soil pathogens of some concern.
For example, Rhizina undulata, native to the northern hemisphere, now causes
root disease in plantations of northern hemisphere conifers grown in plantations in
southern Africa (Wingfield et al. 2001). Armillaria mellea, the root rot fungus, may
also have entered South Africa in this way (Coetzee et al. 2001). Another nontarget
effect of these ectomycorrhizal introductions, deliberate or inadvertent, has involved
competition with native ectomycorrhizal fungi in the exotic tree plantations (Dı́ez
2005). There are no doubt other examples, but in brief summary, deliberately
introduced fungi represent just a tiny fraction of global, fungal diversity.
1.11
Inadvertent Co-Introductions of Fungi in Plants
Brasier highlights the dangers of inadvertent introductions of fungi by the modern
plant trade (Brasier 2008). Even trees “up to 10 m tall with large root balls attached”
are being moved from one country to another. Homogenization of previously
isolated fungal communities above and belowground is thought to be inevitable if
this trade persists. Not only can such shipments not be made safe, but the exotic
plant itself contributes to changes in microbial community structure and function in
26
G. Newcombe and F.M. Dugan
the soil (Kourtev et al. 2002). As belowground mutualisms (e.g., arbuscular mycorrhizal fungi) (Wolfe et al. 2005) affect aboveground mutualisms (e.g., pollinators)
the effects of co-introductions of plants and fungi in the burgeoning plant trade may
be profound even if researchers have not yet elucidated all of them. The movement
of fungi in international food shipments can only be guessed at.
Pathogen release might seem almost miraculous when considered in the light
of the ease with which pathogens have sometimes been moved with their host.
For example, decades ago, Savile noted the inconspicuous adherence of teliospores
of Puccinia carthami to seeds of safflower that when “planted in an isolated garden
produced seedlings with pycnia” (Savile 1973). How then in 1876 did Henry
Wickham succeed in moving 70,000 seeds of rubber-producing Hevea brasiliensis
from its native Amazon basin to the Old World tropics via Kew without any
propagules of the notorious blight fungus, Microcyclus ulei (Hobhouse 2003)?
Wickham’s move and the subsequent pathogen release enjoyed by rubber plantations in Southeast Asia changed the course of the twentieth century. And if Henry
Ford had understood pathogen release better, he might have thought twice about
trying to duplicate the success of Asian rubber plantations by attempting to establish in the 1920s plantations in the Amazon that failed miserably due to blight.
Even if seeds and other plant propagules are surface-sterilized, endophytes are
still moved around the world in the plant trade (Palm 1999). Endophytes can affect
the ecology of plants in many ways, from tolerance to stressful conditions (Redman
et al. 2002), through growth effects (Ernst et al. 2003), to plant community diversity
(Clay and Holah 1999). We are still filling in the knowledge gaps of the functional
roles in what has been called the “endophytic continuum” (Schulz and Boyle 2005).
Endophytes in one invasive plant, Centaurea stoebe or spotted knapweed, were
recently reported to be remarkably diverse in both the native and invaded ranges of
the plant (Shipunov et al. 2008), with interesting effects on its ecology (Newcombe
et al. 2009). Analyses of these communities suggested that both host switching and
co-introduction “took place during the knapweed invasion.” It is possible that the
origins of such fungi as the Dutch elm disease and dogwood anthracnose pathogens
have not been determined because these fungi are only endophytic in the native
ranges of their hosts.
1.12
Fungi as Facilitators of Plant Invasions
Release from phytopathogenic fungi is but one hypothesis to explain plant invasions (Mitchell and Power 2003). Recently, plant invasion biologists have taken a
new interest in mycorrhization and other mutualisms (Richardson et al. 2000a), and
in plant–soil feedback processes more generally (Ehrenfeld et al. 2005). Fungi in
soil appear to be central to plant–soil feedbacks that promote alien plant invasions
(Klironomos 2002). Alien plants may become abundant in part because they are
1 Fungal Pathogens of Plants in the Homogocene
27
relatively resistant to fungal pathogens in soil that limit the abundance of many
native plants (Klironomos 2002). Interpreted in light of the foregoing discussion of
a “tens rule” for novel plant pathogens this would again indicate that first encounters below ground of novel pathogens and naive plants may more often than not
involve incompatibility or resistance, just as aboveground encounters do. This point
is reinforced by a meta-analysis of biotic resistance that revealed that native
communities are defended against plant invaders by resident competitors and
herbivores, but not by soil fungi (Levine et al. 2004).
In other words, an improved understanding of the outcomes of first encounters
between novel pathogens and naive plants can potentially contribute simultaneously to questions that have been treated separately by different disciplines. On
the one hand, mycologists and plant pathologists have had a traditional interest in
predicting the outcome of introductions of novel plant pathogens. On the other,
plant ecologists and invasion biologists have been trying to understand the mechanism of plant invasions. When the fungal pathogens in a plant community are native
(i.e., Category 1 of Table 1.1), they fail to contribute to biotic resistance to plant
invasions insofar as they fail to cause disease of alien plants, as summarized by
Levine. This result is consistent with examples in categories 2 and 3 where resistant
outcomes again prevail.
1.13
Conclusions
Ideally, on the eve of the Homogocene in 1499, trained scientists around the globe
would have already described all species of life. A pre-Homogocene “Encyclopedia
of Life” (Wilson 2003) would have provided the baseline from “Day 1” for
subsequent tracking of every human-aided introduction of an alien that followed.
Knowing the outcomes of every introduction of an alien species during the past
500 years, we might well be further along in our attempt to understand why some
organisms are invasive and why most are not. Unfortunately, 1500 predates the
development of Linnean taxonomy by 253 years (Linnaeus 1753), Christiaan H.
Persoon’s Synopsis Methodica Fungorum by 301 years, and Elias Magnus Fries’
first volume of Systema Fungorum by 321 years.
Falling far short of the ideal, we instead find ourselves drawing inferences from
patterns of pathogen release, and scattered studies of resistance relative to first
encounters of plants and pathogens. Fortunately, for inferences from pathogen
release, the SMML Fungus–Host Distribution Database and other databases of
records of fungi on plants have proven invaluable. Homogenization itself has
created opportunities for discoveries that otherwise might not have been made.
Finally, the merging of the study of novel pathogens of plants with the general
framework and terminology of invasion biology is bound to be helpful to all
students of this global experiment of the last 500 years.
28
G. Newcombe and F.M. Dugan
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Columbia
Chapter 2
Molecular Techniques for Classification
and Diagnosis of Plant Pathogenic Oomycota
Otmar Spring and Marco Thines
Abstract With a delay of approximately 10 years, molecular techniques came in
use for the investigation of phylogenetic, taxonomic, and diagnostic problems in
oomycetes. The particular problem in plant pathogenic Oomycota lies in their
biotrophic nature, which prohibits axenic cultivation of the majority of species, in
particular downy mildews and white blister rusts, on artificial media. This impeded
the broad employment of basic techniques such as RFLP (restriction fragment
length polymorphism) in investigations of Oomycota and required the development
of specific PCR-based tools for identification and detection of minute pathogen
amounts. When the first sequence analysis of genomic loci of oomycetes was
conducted in the late 1980s, specific primers became available which allowed
selective analysis of oomycete DNA in the presence of much higher amounts of
host DNA. Since about 8 years, these methods have become routine in this field of
research and have started turning the systematics of Oomycota upside down. A
wide array of tools for the amplification of coding and noncoding gene loci helped
to differentiate pathogen accessions, to restructure the phylogeny, to form monophyletic entities on all taxonomic levels, and to resolve unrealistically broad species
concepts. Recent progress in sequencing ancient DNA from Oomycota allows the
extension of taxonomic studies to herbarium collections. This broadens the basis of
samples considerably and gives the chance to link molecular phylogenetic taxonomy with the traditional phenotype-based system. Moreover, molecular techniques
gain growing importance in the identification of downy mildews and white blister
rusts in plant pathology and in ecological studies. Their employment allows detection of Oomycota in asymptomatic infections of host plants and enables the
identification of infested seeds or soils in agriculture. With the first whole genome
sequencing of a Phytophthora species in 2003, the basis for functional genomics
studies has been established. This will not only stimulate phylogenetic, taxonomic,
O. Spring and M. Thines
Institute of Botany, University of Hohenheim, 70593 Stuttgart, Germany
e-mail: spring@uni-hohenheim.de
Y. Gherbawy and K. Voigt (eds.), Molecular Identification of Fungi,
DOI 10.1007/978-3-642-05042-8_2, # Springer-Verlag Berlin Heidelberg 2010
35
36
O. Spring and M. Thines
and diagnostic research in plant pathogenic Oomycota, but also provide the basis
for gaining deeper insights in their biology and interaction with their hosts.
2.1
Introduction
Molecular techniques have altered the understanding of the evolution and phylogeny of life within the past 30 years in an unprecedented dimension. It is only natural
that this process started with the most familiar and the easiest accessible groups of
organisms such as animals and higher plants. These investigations revealed a
multitude of inconsistencies of the evolutionary relationships compared to the
established taxonomy, especially above the generic level. The consequences for
the reorganization of the systematics and taxonomy of these already well-known
groups were however moderate and manageable, when compared with less-familiar
groups such as prokaryotes, protozoa, algae, or fungi. The taxonomic rearrangement of the fungi started long before molecular techniques were at hand. The
separation in Myxomycetes, Eumycetes, and Oomycota was based on fundamental
cytological and biochemical differences. The particular mode of sexual reproduction of the diploid Oomycota is unparalleled in any other fungus-like entity
(Tommerup 1981). In addition, their cellulosic cell wall (Bartnicki-Garcia 1968),
the lysine synthesis pathway (Vogel 1960), and their sterol biosynthesis (Warner
et al. 1982) are biochemical evidence to separate them from eumycotic fungi, to
whom they resemble only superficially with respect to their hyphoidal organization
and osmotrophic nutrition. The phylogenetic roots of the Oomycota became obvious from the flagellum, which because of the anterior insertion and its tripartite
hairs unraveled them as part of the Straminipila (Vlk 1939; Patterson 1989; Dick
2001). Molecular data supported this origin (Leipe et al. 1994) and hinted at the
possibility that Oomycota had separated before or after the uptake of secondary
chloroplasts in this clade. Sequencing of the nucleus-encoded glyceraldehyde-3phosphate dehydrogenase in Oomycota supports close relationships with the photosynthetic heterokonts in which this enzyme is plastid-targeted, thus favoring the
loss of plastids in the nonphotosynthetic heterokonts (Harper and Keeling 2003).
However, the initial rearrangements of the higher-level classification of the fungal
organisms gave but a glimpse of the changes to come on all taxonomic levels with
the advent of molecular phylogenetic investigations.
Within the Oomycota, until recently, the taxonomic concept was solely based on
the few morphological characters available from the sparse features of an unsepted
mycelium, sexually or asexually produced spores, and the mode of sporulation. In
biotrophic sections of this phylum, additional information could be gained from
host specificity, provided that vital material was accessible and the assumptions
from field observation could be ensured by infection experiments. The host-based
concept for species was broadly applied by Gäumann (1918, 1923) and still
predominates in taxonomy. Paucity in differentiating morphological characters, in
2 Molecular Techniques for Classification and Diagnosis
37
addition to the lack of knowledge in host specificity and sexual reproduction
between populations found on closely related hosts, resulted in a taxonomy of the
plant pathogenic Oomycota with relatively few, but broad taxa (Yerkes and Shaw
1959) that were adopted especially by applied plant pathologists. For Plasmopara
halstedii, one of the most relevant sunflower pathogens, no less than ca. 80 genera
of the Asteraceae were listed as potential hosts (Leppik 1966) regardless of their
evolutionary distance, geographic distribution, and untested susceptibility to strains
from different hosts. Agronomic experiences showed that such a species concept
was inappropriate and additional classifications on the level of formae speciales
were introduced to handle important crop pathogens, as for instance the tobacco
blue mould Peronospora hyoscyami de Bary f.sp. tabacina (Adam) Skalický.
Meanwhile, molecular tools are available to reinvestigate species delimitation
and phylogeny of the Oomycota. In the following chapters we summarize the recent
progress in classification and diagnosis of the two major groups of obligate biotrophic (i.e., depending on a living substrate) Oomycota, the downy mildew pathogens, and the white blister rusts.
2.2
Upheaval of Oomycete Taxonomy in the Molecular Era
Ten years ago, only very few and punctual genetic data of Oomycota were available
in public databases. The species selected for early studies were Achlya bisexualis
(Gunderson et al. 1987), Lagenidium giganteum (Förster et al. 1990), and Phytophthora megasperma (Förster et al. 1990); all of these species can be cultured on
artificial media. They stood exemplary for the Oomycota and early data served
predominantly for supporting the separation of oomycetes from other fungal groups
and to confirm the relationships with other straminipilous entities. The sequence
loci used for early molecular phylogenetic studies were the mitochondrial cytochrome oxidase (cox2) (Hudspeth et al. 2000) and the nuclear 18S rDNA on the
phylogenetic analysis of which Dick et al. (1999) justified the separation of the
subclass division of the Peronosporomycetes into Saprolegniomycetidae and Peronosporomycetidae (Fig. 2.1). The molecular era of the obligate biotrophic Oomycota started when Petersen and Rosendahl (2000) sequenced partial 28S rDNA of
Peronospora farinosa and Albugo candida to include these organisms in their
phylogenetic analysis.
Meanwhile, a greater number of genetic loci are accessible for sequence comparison (Hudspeth et al. 2000; Riethmüller et al. 2002; Voglmayr 2003; Thines
et al. 2006; Göker et al. 2007) and led to massive taxonomic rearrangements on all
levels. The most fundamental steps were perhaps the separation of the white blister
rusts from Peronosporomycetidae and the subsequent placement within the new
subclass Albuginomycetidae (Thines and Spring 2005) and the reclassification of
the graminicolous downy mildews within the Peronosporaceae (Riethmüller et al.
2002; Hudspeth et al. 2003; Thines et al. 2008). Although the former step was not
entirely based on molecular data, sequence comparison of nrLSU (Riethmüller
38
O. Spring and M. Thines
Oomycetes
Peronosporomycetes
Lagenidiales
Rhipidiomycetidae
Rhipidiales
Leptomitales
Saprolegniomycetidae
Leptomitales
Salilagenidiales
Saprolegniales
Sclerosporales
Saprolegniales
Peronosporales
Phytiaceae
Albuginaceae
Peronosporaceae
(Sparrow1960; Dick 1973)
18S rDNA
Peronosporomycetidae
Pythiales
Peronosporales
(Dick 2001)
Fig. 2.1 Classification of the Oomycota in the pre molecular era and the consequences of first
DNA sequences of the nuclear 18S rDNA, before the first comprehensive molecular phylogenies
Albuginomycetidae
Peronosporomycetes in 2001
and current status of former
Peronosporomycetidae
Rhipidiomycetidae
Saprolegniomycetidae
Albuginales
Albuginaceae
Separation
based on
phenotypic
and molecular
data
Peronosporomycetidae
Pythiales
Peronosporales
Albuginaceae
Albugo
Peronospororaceae
Basidiophora
Benua
Bremia
Bremiella
Paraperonospora
Peronospora
Plasmopara
Pseudoperonospora
Molecularbased
formation of
monophyletic
entities
Albugo
Pustula
Wilsoniana
Peronosporomycetidae
Pythiales
Peronosporales
Peronospororaceae
Basidiophora
Benua
Bremia
Graminivora
Hyaloperonospora
Novotelnova
Paraperonospora
Perofascia
Peronospora
Peronosclerospora
Plasmopara
Plasmoverna
Poakatesthia
Protobremia
Pseudoperonospora
Sclerophthora
Sclerospora
Viennotia
Fig. 2.2 Peronosporomycetes according to Dick (2001) and the current status of the former
Peronosporomycetidae. Close relationships to Peronosporaceae of the paraphyletic genus Phytophthora, formerly placed in the Pythiales, have been recognized (Riethmüller et al. 2002; Göker
et al. 2007); however, no formal solution for this has yet been proposed
et al. 2002), and cox2 (mitochondrial cytochrome C oxidase gene) (Hudspeth et al.
2003; Thines et al. 2008) supported this view, therefore necessisating major
changes in the taxonomy of plant parasitic oomycetes (Fig. 2.2).
2 Molecular Techniques for Classification and Diagnosis
39
As a consequence of intensive sampling of molecular genetic data and phylogenetic analysis, eight new genera were described within the Peronosporaceae alone,
one genus was relegated into synonymy with Plasmopara, and it was realized that
the graminicolous downy mildews are to be placed within the Peronosporaceae.
Numerous transfers of taxa were made to newly formed monophyletic entities
(Constantinescu and Fatehi 2002; Göker et al. 2004; Voglmayr et al. 2004;
Constantinescu et al. 2005; Thines et al. 2006, 2007; Voglmayr and Thines 2007;
Voglmayr and Constantinescu 2008). In many cases, this reorganization renewed
the search for reliable phenotypic characters which coincide with the molecular
genetic classification, a prerequisite for the adoption of such new concepts in
applied phytopathology, as was urged previously (Spring and Thines 2004). In
particular, it could be shown that fine morphology of the sporangiophores
(Constantinescu and Fatehi 2002; Thines 2006), as well as haustoria (Voglmayr
et al. 2004; Thines et al. 2006, 2007), and the oospore ornamentation (Voglmayr
and Riethmüller 2006; Choi et al. 2007, 2008) are critically important characters.
For extensive review see Voglmayr (2008).
The ongoing research activities are bidirectional. On the one side, a large
number of taxa are still leant at very broad species concepts that require a more
precise resolution, especially for large families, such as Fabaceae (Garcia-Blázquez
et al. 2008), Brassicaceae (Göker et al. 2004), Lamiaceae, Asteraceae, and
Amaranthaceae (Choi et al. 2007). On the other hand, whole genome sequencing
has reached Oomycota and will soon accelerate research in physiological and
ecological aspects of this group (Birch et al. 2008). The genomes of four Phytophthora species are fully sequenced (for review see Lamour et al. 2007) and
selected species of Hyaloperonospora, Albugo, and Pustula are currently under
investigation. The results of genome sequencing will be an important source for the
search of useful genes for taxonomic and phylogenetic investigations in Oomycota.
2.3
Molecular Tools for Reclassification and Identification
of Oomycota
The application of molecular tools for the characterization of biotrophic organisms
is a particular challenge because the obligate biotrophy hampers cultivation and the
accumulation of pathogen material; therefore, these techniques were first used in
non-biotrophic groups. Most stages of their life cycle are inevitably and tightly
linked to living cells of their hosts. In Oomycetes this is true for all Albuginales
(white blister rusts) and for the downy mildews (Peronosporaceae pro partem),
whereas members of the second order “Pythiales” – a para- and polyphyletic
assemblage – can be cultivated axenically on artificial media (e.g. Pythium, Phytophthora). The only cells of the biotrophic taxa which are accessible without
contamination through host material are the spores, and these are often not available
in sufficient amounts for several DNA or protein analyzes. For that reason, isozyme
analysis and RFLP (restriction fragment length polymorphism) studies which had
40
O. Spring and M. Thines
Table 2.1 Molecular-based techniques and their potential use for classification of biotrophic
Oomycota as demonstrated for selected groups
Research field of Example and reference
Useful at taxonomic
application
level of
Isozyme analysis Sub-species
Classification
Plasmopara
(Komjáti et al. 2008)
Plasmopara
RAPDs
Species to sub-species Classification
(Roeckel-Drevet et al. 1997)
Plasmopara
AFLPs
Species to sub-species Classification
(Roeckel-Drevet et al. 1997)
Plasmopara
iSSRs
Species to sub-species; Classification
(Intelmann and Spring 2002;
crossing experiments
Gobbin et al. 2003)
SSU rDNA
Kingdom to genus
Phylogeny
Peronosporomycetes
Sequencing
(Dick et al. 1999)
LSU rDNA
Class to species
Phylogeny
Peronosporomycetes
sequencing
(Riethmüller et al. 1999, 2002;
Petersen and Rosendahl 2000)
COX2 sequencing Kingdom to species
Phylogeny and
Peronosporomycetes
(Hudspeth et al. 2000, 2003;
calssification
Thines et al. 2007; Choi
et al. 2007b, 2008)
ITS sequencing
Family to species
Phylogeny and
Peronosporoaceae
(Göker et al. 2004; Voglmayr
classification
2003; Choi et al. 2006,
2007, 2008; Spring et al.
2006; Thines 2007)
SNPs
Species to sub-species; Phylogeny,
Phytophthora; Plasmopara
crossing analysis
classification, (Martin 2008; Delmotte et al.
population
2008)
studies
–
DNA barcoding
Species
Classification
successfully been employed for the investigation of Phytophthora (Oudemans
and Coffey 1991; Förster and Coffey 1989) were in general not useful, unless
large amounts of sporangia were gained through cultivation of the pathogen on
host plants as was recently demonstrated for P. halstedii pathotypes screened by
Komjáti et al. (2008).
Before PCR (polymerase chain reaction) techniques with oomycete-specific
primers had been developed, various so-called fingerprint techniques were used
for classification and taxonomic studies (Table 2.1). RAPD (randomly amplified
polymorphic DNA) and AFLP (amplified fragment length polymorphism) fingerprints were used for differentiation of isolates of P. halstedii, the downy mildew
pathogen of sunflower (Roeckel-Drevet et al. 1997). However, a reliable classification of pathotypes (physiological races) could not be achieved with this technique.
Another fingerprint technique is on the basis of the polymorphism of microsatellite
markers and simple sequence repeats which are widely distributed elements in
eukaryotic genomes (Tautz 1989; Lagercrantz et al. 1993) and revealed to be
2 Molecular Techniques for Classification and Diagnosis
41
helpful for generating highly diverse fingerprint patterns in sporangial DNA samples of some downy mildew pathogens of crop plants (Intelmann and Spring 2002;
Gobbin et al. 2003; Spring et al. 2007a; Komjati et al. 2007; Zipper et al. 2009).
The amplification patterns allowed the differentiation of two related pathogen
species on Xanthium and Helianthus (Komjáti et al. 2007). On the infraspecific
level, population studies revealed low genetic variation in the grapevine downy
mildew pathogen Plasmopara viticola (Gobbin et al. 2006; Delmotte et al. 2006)
and in P. halstedii (Intelmann and Spring 2002), thus prohibiting identification of
physiological races. In contrast, differentiation between fungicide sensitive and
resistant genotypes of tobacco blue mould Peronospora tabacina based on iSSR
polymorphisms was recently shown and used for a population study in field
accessions from Europe (Zipper et al. 2009).
With the identification of DNA sequences of specific genes, analyzes regarding
the identity and evolutionary history of obligate biotrophic oomycetes were greatly
advancing. Because of the paucity of material, particularly those genomic regions
for which multiple copies per cell exist were chosen for comparative studies. Such
prerequisites were found in the repetitive elements of the nuclear ribosomal DNA
and in the mitochondrial-encoded cytochrome C oxidase gene (cox2). The small
subunit of the 18S rDNA (SSU) was used by Dick et al. (1999) to justify the
separation of the Peronosporomycetes into the subclass taxa Saprolegniomycetidae
and Peronosporomycetidae while other studies used cox2 for tracing the phylogeny
of these entities (Hudspeth et al. 2000, 2003; Cook et al. 2001, Choi et al. 2007,
2008; Thines et al. 2007, 2008). The large subunit of the 28S rDNA (LSU) initially
served for the generic resolution of the Saprolegniomycetidae (Riethmüller et al.
1999) and has since been broadly used in many revisions of oomycete taxa
(Riethmüller et al. 2002; Göker et al. 2003; Voglmayr et al. 2004; Thines et al.
2006; Voglmayr and Thines 2007). A major advantage of sequence-based classification and identification is its applicability on infected host plant tissue, because
specific primers are used for amplifying the target gene in the presence of high
amounts of host DNA background. On the other hand, SSU and LSU sequences
often do not provide sufficient resolution for the classification of subgeneric taxa,
and genomic regions of higher variability were searched for. Meanwhile, the ITS
(internal transcribed spacer) region, and to a lesser extent the IGS (inter-genic
spacer) region, two noncoding elements of the nuclear rDNA (Bachmann 1994),
have become the most preferred sequences for studies on the lower ranking levels
(Schurko et al. 2003; Wattier et al. 2003, for additional references see Spring 2004).
Thereby, broad species concepts such as the Hyalopernospora complex on Brassicaceae can be tested (Choi et al. 2003; Göker et al. 2003) or the A. candida complex
on the same host family (Choi et al. 2006, 2007a, 2008). ITS sequencing is also a
useful tool for the classification of pathogens on crop plants, when morphological
characters like sporangial size are unsecure. Thus, the downy mildew of poppy
(Papaver somniferum) is caused by two phenotypically similar, but not closely
related taxa, Peronospora arborescens and P. cristata, and molecular data confirmed the latter to be responsible for epidemics in Tasmania (Scott et al. 2004),
while the former is the prominent pathogen of poppy in Europe.
42
O. Spring and M. Thines
The potential of variation in ITS has not yet been fully explored. Repetitive
elements were recently found in P. halstedii (Thines et al. 2005; Thines 2007) and
P. angustiterminalis (Komjáti et al. 2008) which extended this noncoding region to
an almost fourfold size in comparison to basal groups of the Peronosporaceae and
may enable to trace the speciation process within this lineage.
On the infraspecific level, the above-mentioned molecular tools may sometimes
provide insufficient resolution. In such cases, SNPs (single nucleotide polymorphisms) provide a promising new type of molecular marker, if sufficient genomic data
have been established in the respective group of organisms (Schlotterer 2004). In
plant pathogens, SNPs have sparsely been used so far (Morin et al. 2004), and this is
true in particular for Oomycota. SNP-based population studies were carried out in
Phytophthora ramorum (Martin 2008) and Hyaloperonospora parasitica s.l.
(Clewes et al. 2007). In a recent study on P. halstedii field accessions, independent
introduction events of the pathogen in French sunflower cultivation were traced on
the basis of SNP data (Delmotte et al. 2008).
For the classification of unknown samples, genetic barcoding was shown to be a
helpful tool (Hebert et al. 2003). In land plant taxonomy, the use of short genetic
markers located in mitochondrial or plastidal DNA for the identification of organisms was introduced few years ago (Hebert and Gregory 2005; Chase et al. 2005)
and meanwhile standardized protocols have been proposed (Chase et al. 2007). The
technique has been adopted for the investigation in bryophytes (Pedersen et al.
2006), algae (Saunders 2008), and partly also for fungi (Seifert et al. 2007). For
Oomycota, such attempts have to be considered still preliminary (Göker et al. 2007;
Blair et al. 2008), but it is to be expected that a unifying approach will close this gap
shortly. The mitochondrial cytochrome C oxydase gene could be one of the
candidate genes for genetic barcoding in Oomycota and would allow comparison
with other phyla, where this region was also selected (Seifert et al. 2007).
Recent advances in the investigation of herbarium specimens (May and
Ristaino 2004; Ristaino 2006; Liu et al. 2007; Telle and Thines 2008) are promising
to enable the inclusion historical specimens in molecular phylogenetic investigations and molecular barcoding. Telle and Thines (2008) have reported the use of
only 2 mg of infected plant tissue of more than 100-year-old specimens. This incites
the hope that it might be possible to include type specimens in the investigations,
thereby linking the classical, Linnean system to modern molecular barcoding
approaches.
2.4
Molecular Approaches for Tracing Occurrence
of Oomycetes in Plants and Habitats
Molecular techniques provide unprecedented possibilities to identify plant pathogens on or within their hosts and in the environment. In Oomycota, only few reports
yet exist on the employment of molecular markers for tracing their occurrence in
2 Molecular Techniques for Classification and Diagnosis
43
host organisms or in soil (e.g. Aegerter et al. 2002; Belbahri et al. 2005; Hukkanen
et al. 2006). This is remarkable, taking into account that for many biotrophic
species on wild host plants, little more than the mode of sporulation and the disease
symptoms are known. Ways of overwintering and developmental stages between
penetration of the host and sporulation on its surface are mostly unexplored, even in
many economically important diseases of crop plants.
Several observations of recurrent and epidemic infections of plants in a certain
developmental stage and subsequent seemingly unaffected growth without infection symptoms support the assumption that the pathogen may pass through an
asymptomatic or endophytic life stage. Typical examples are the white blister
rusts of the genus Albugo on Brassicaceae, for which Jacobson et al. (1998) had
postulated an endophytic persistence, because in their study oomycetes were
detected by means of specific ITS primers in DNA extracts from symptomless
host tissue. According to our own unpublished observations, this appears not to be
an exception in biotrophic Oomycota, but may be paralleled by several downy
mildew species, e.g. Peronospora veronicae on Veronica spp., and Hyaloperonospora spp. on Cardamine and Erysimum.
Such latent types of infection are also known from pathogens on crop plants such
as P. halstedii on sunflower (Cohen and Sackston 1974; Spring 2001) or Peronopora
sparsa on arctic bramble and boysenberry (Hukkanen et al. 2006). In the latter case,
symptomless phases in woody parts and in the root stock of the host (Lindquist et al.
1998) ensure overwintering of the pathogen. Similarly, the survival of the grape
downy mildew P. viticola with perennial mycelium in Vitis shoots and dormant buds
had been postulated (Pioth 1957; Rumbou and Geissler 2006). The root system and
rhizome of perennial hosts can be inhabited by the pathogen that undergoes unrecognized hibernation until symptoms appear on aerial plant parts in the next season.
This has been observed for P halstedii in the perennial sunflower Helianthus
divaricatus (Nishimura 1922) and more recently in the hybrid species Helianthus
x laetiflorus (Spring et al. 2003). In the rootstock of hop plants, hyphae of Pseudoperonospora humuli were detected microscopically, when epidemics of the pathogen had reached for the first time in hop gardens in England (Salmon and Ware
1925). The perennial mycelium is responsible for the occurrence of diseased,
stunted shoots in April and May, and gives rise to secondary infection. Tracing
pathogen contamination in asymptomatic host tissue is particularly important in
plant propagation which is based on cuttings and grafting. Aegerter et al. (2002), for
instance, used PCR techniques successfully for the detection of P. sparsa in the
shoot cortex and crown tissue of asymptomatic rose plants which were chosen to
serve as a source of propagation material. In plant breeding, sensitive tests for the
detection of asymptomatic infections could be helpful to avoid false evaluations of
seemingly resistant plants. For the quantification of the infection, real-time PCR
with downy mildew specific primers was shown to be useful (Hukkanen et al. 2006).
Another important developmental stage of symptomless occurrence of vital
structures of biothrophic oomycetes involves seeds. Besides ensuring the survival
during winter this stage supports the distribution of the pathogen and the spread
through seed dispersal. For oomycetes on wild host plants, this phenomenon has not
44
O. Spring and M. Thines
been explored yet, whereas seed contamination of crop plants was shown for the
downy mildew pathogen of basil (Belbahri et al. 2005) as well as for the white
blister rust Pustula on sunflower (Viljoen et al. 1999). With the globalization of
seed trading, this way of pathogen distribution has become one of the major
problems in agri- and horticulture. Quarantine regulations try to impede seed
transmission of diseases, but fast, sensitive and reliable detection methods are
still mostly lacking. While germinating and cultivating an appropriate amount of
seeds, evaluating the plants for disease symptoms is still the common way of testing
seed contamination; molecular techniques have slowly been developed for oomycetes, but tests have not yet been brought into practical usage. For example,
sunflower seed contamination with P. halstedii was investigated with various
methods. PCR-based detection was attempted with selective oligonucleotide primers (Roeckel-Drevet et al. 1999; Says-Lesage et al. 2000) and with LSU-based
primers (Ioos et al. 2007). An ELISA test was developed by Bouterige et al. (2000)
and pathogen-specific fatty acids were used for the detection by Spring and Haas
(2004). In Peronospora parasitic to basil, specific primers deduced from ITS
sequences not only allowed the detection of the downy mildew of basil in seeds and
plant tissue, but also enabled quantification of the contamination by using real-time
PCR (Belbahri et al. 2005). However, in many cases, the problem for bringing such a
test into practice is not only the sensitivity of system, which, in case of sunflower, has
proven to be close to market needs and allowed the detection of one contaminated seed
out of 50 (Spring and Haas 2004) or even out of 400 (Thines et al. 2004). Perhaps the
major obstacle is drawing of a representative sample from large seed batches.
A similar problem is the detection of soil contamination with infective structures
of the pathogen. Oospores of Oomycota can survive over 10 years or more, hence
crop rotation is usually ineffective to prevent yield loss when replanting is made on
a previously diseased field. The ability to determine whether a field contains a
pathogen is of value both to growers and to researchers, but reports for oomycetes
on this topic are still fairly rare. Pratt and Janke (1978) documented the infestation
of soil with oospores of Peronosclerospora sorghii and Van der Gaag and Frinking
(1997) enriched and extracted oospores of Peronospora viciae from soil by means
of sieves. An estimation of inoculum potential for the infection of host plants by
planting seeds in oospore contaminated soil was reported for Aphanomyces
euteiches, a root pathogen of pea (Malvick et al. 1994) and for the sunflower
downy mildew P. halstedii (Gulya 2004). As in the latter case, the applied technique is often a time and resource consuming bioassay that counts the ratio of
infected seedlings after planting them in the soil sample under investigation. The
adoption of PCR-based techniques to trace oomycetes in soil has so far been limited
to Pythium (Wang and Chang 2003) and Phytophthora species (Hussain et al. 2005;
Wang et al. 2006; Pavon et al. 2008) and no similar reports exist for downy mildews
or white blister rusts. The progress made by molecular approaches in comparison to
the bioassay technique is considerable with respect to time consumption and
sensitivity. Thus, detection from soil required only 6 h (Wang et al. 2006), whereas
bioassays take weeks (Gulya 2004). The limits in sensitivity improved significantly
from approximately ten oospores per gram soil (Wang and Chang 2003) to one
2 Molecular Techniques for Classification and Diagnosis
45
oospores per 10 g of soil (Wang et al. 2006), but this depends on the soil screening
technique (e.g. Pavon et al. 2008) employed before DNA extraction, and still
represents at most a heavily contaminated soil. A burdensome problem for the
practical application of such tests is similar as in the seed contamination tests
mentioned above, lying in the acquisition of representative soil samples from the
fields. The molecular techniques for tracing oomycetes in soil could be used in a
modified way also for horticulture where hydroponic irrigation has become popular.
Continuous monitoring of the irrigation water could help to identity pathogen
contamination at a very early stage and to prevent epidemics in greenhouse
cultures. Multiplex detection systems, as recently developed for the detection of
fungal and oomycete pathogens of solanaceous crops (Zhang et al. 2008) could help
to reduce the costs for the disease management.
2.5
Concluding Remarks
The progress made within the past few years in using molecular tools for exploring
evolution, taxonomy, and classification of Oomycota is brisk and diminished the
distance in knowledge to other eukaryotic organisms rapidly. As the first genomes
of plant pathogenic oomycetes were unraveled, the base has been established to
resolve the long list of compelling questions. Besides reorganizing the diversity of
Oomycota by forming monophyletic entities and splitting unnatural broad taxa, the
focus of research will soon shift to aspects of virulence mechanisms, coevolution,
oomycete ecology, and agronomically relevant problems.
Acknowledgments Funding by the DFG granted to M. Thines is gratefully acknowledged.
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Chapter 3
Plasmodiophorids: The Challenge to Understand
Soil-Borne, Obligate Biotrophs with a
Multiphasic Life Cycle
Sigrid Neuhauser, Simon Bulman, and Martin Kirchmair
Abstract Plasmodiophorids are an enigmatic group of obligate biotrophic pathogens of higher plants. Together with their sister group phagomyxids, which infect
stramenopiles, they form the monophyletic eukaryote clade phytomyxids. They
have long been treated as a basal group of fungi, but recent molecular phylogenies
point to a close affiliation with the protozoan phylum Cercozoa. The soil-borne and
plant-associated nature of plasmodiophorids as well as their multi-stage life cycle
with zoosporic, plasmodial, and resting stages has hindered comprehensive
research on this group. Plasmodiophorids cannot be cultured without their hosts,
and direct observations of any stage of the plasmodiophorid life cycle are difficult
and time-consuming. Molecular techniques provide valuable tools for the identification and monitoring of organisms which are difficult to assess with traditional
approaches – such as plasmodiophorids. Several different immunological or nucleic
acid-based techniques, and more recently genomic and proteomic approaches have
been used to investigate plasmodiophorids, their life style, and their interactions
with their host plants. Nonetheless, advances in knowledge about plasmodiophorids
provided by molecular techniques are mainly restricted to the few economically
important species that cause diseases of agricultural crops. Although their taxa may
be well described, the available phylogenies of phytomyxids are rather incomplete,
as they include only a few selected species. A main reason for this bias is that
most specimens deposited in herbaria are too old, soaked in fixatives or otherwise
unavailable for DNA analyses. To fully understand this group of protists, more
research on “rare”, under-recorded species is needed.
S. Neuhauser and M. Kirchmair
Institute of Microbiology, Leopold Franzens – University Innsbruck, Technikerstr. 25, 6020
Innsbruck, Austria
e-mail: Martin.Kirchmair@uibk.ac.at
S. Bulman
Plant & Food Research, Private Bag 4704, Christchurch, New Zealand
Bio-Protection Research Centre, Lincoln University, P.O. Box 84, 7647 Canterbury, New Zealand
Y. Gherbawy and K. Voigt (eds.), Molecular Identification of Fungi,
DOI 10.1007/978-3-642-05042-8_3, # Springer-Verlag Berlin Heidelberg 2010
51
52
S. Neuhauser et al.
In this review, we discuss the impact of molecular techniques on the detection,
monitoring, and characterisation of plasmodiophorids. First, we will briefly introduce plasmodiophorid biology and the taxonomic twists and turns the group has
taken to reach its current taxonomic position. Development of methods and experimental progress towards better understanding of plasmodiophorids are then
sketched, from classical approaches to the recent “-omics” approaches. We will
also discuss future implications of molecular methods, which it is hoped will help to
improve knowledge about the role of plasmodiophorids within ecosystems.
3.1
Introduction
The phytomyxids (plasmodiophorids and phagomyxids) comprise a monophyletic
group of eukaryotes which were originally considered as protists, later as fungi, and
are now considered as members of the protist supergroup Rhizaria (see below).
Partly to avoid specific taxonomic placement, we use the informal term “plasmodiophorids”, as introduced by Braselton (1995), throughout this review.
Plasmodiophorids first came to the attention of scientists and society at the end
of the nineteenth century when a severe epidemic of clubroot disease destroyed
many of the cabbage crops around St. Petersburg, Russia. The economic loss caused
by this disease was tremendous and yet the causative organism or agent was
unknown at the time. In 1872, the Russian Gardening Society offered a prize to
anyone who could identify the cause of the disease, and who could suggest a control
for clubroot. Michail Woronin, a Russian botanist and plant pathologist started his
research on the epidemic plague in 1873. A few years later, he described the
causative organism – Plasmodiophora brassicae – as novel microorganism to the
scientific community (Woronin 1877). Woronin observed plasmodia in diseased
root parenchyma cells, the metamorphosis of the plasmodia into spores, as well as
the hatching of amoebae out of these spores. His discovery of this new organism
stimulated interest in this mysterious group of organisms and many plasmodiophorid plant parasites were described during the next decades (Table 3.1).
3.1.1
What are Plasmodiophorids?
Plasmodiophorids are obligate intracellular parasites of green plants. They are
characterised by a complex life cycle which will be illustrated by the example of
Pl. brassicae, the best-studied plasmodiophorid (Fig. 3.1). The life cycle starts with
a primary zoospore that attaches to the wall of a root hair of a cruciferous plant.
Soon the flagella are retracted and the zoospore encysts. Aist and Williams (1971)
demonstrated clearly and in detail that after the primary zoospore attaches to the
cabbage root hair, a projectile-like structure (“Stachel”) is formed within a tubular
cavity (the “Rohr”) inside the cyst (terminology according to Keskin and Fuchs
3 Plasmodiophorids: The Challenge to Understand Soil-Borne, Obligate Biotrophs
53
Table 3.1 Plasmodiophorid species on green plants (no sign), *Oomycetes, +Phaeophyceae,
#
diatoms, $green algae. y ¼ causing hypertrophies in host plants; n ¼ no hypertrophies visible
Genus
Species
Host species
Hypertrophies Additional
comments
Plasmodiophora brassicae Woronin
Crucifers
y, roots
–
halophilae Ferd. &
Halophila
y, petioles
Found only once
Winge
diplantherae (Ferd. &
Diplanthera
y, internodes Found only once
Winge) Ivimey Cook
fici-repentis Andreucci Ficus
y, branches
Found only once
bicaudata Feldmann
Zostera
y, internodes
maritima Feldm.-Maz.
Triglochinis
y, apex
Found only once
Tetramyxa
parasitica K.I. Goebel
Ruppia,
y
–
Zannichellia,
Potamogeton
rhizophaga Lihnell
Juniperus
n
Found only once
triglochinis Molliard
Triglochin
y
no resting spores
known
elaeagni Y. Yendo &
Elaeangus
y, roots
Found only once
K. Takase
marina Lipkin & Avidor
–
1974
n
–
Octomyxa
achlyae Couch, J. Leitn. Achlya*
& Whiffen
n
–
brevilegniae Pend.
Brevilegnia*,
Geolegnia*
Sorosphaera
veronicae J. Schröt.
Veronica
y, shoots
–
radicalis Ivimey Cook
Poa,
y, root hairs
–
& Schwartz
Molinea,
Catabrosa
viticola Kirchm., Neuh. Vitis
n
–
& L. Huber
Sorodiscus
callitrichis Lagerh. &
Callitriche
y, shoot
–
Winge
radicicolous Ivimey
Gynandropsis
y
–
Cook
karlingii Ivimey Cook
Chara
y, internodes –
cokeri Goldie-Sm.
Pythium*
n
–
Membranosorus heterantherae Ostenf. & Heteranthera
y, roots
–
H.E. Petersen
Spongospora
subterranea (Wallr.)
Solanaceae
y, fine roots
–
Lagerh.
nasturtii M. W. Dick
Nasturtium
y
–
campanulae (Ferd. &
Campanula
y, roots
Found only once
Winge) Ivimey Cook
cotulae Barrett
Cotula
y
–
n
–
Ligniera
verrucosa Maire &
Veronica
other hosts
A. Tisson
n
–
junci (Schwartz) Maire Juncus
other hosts
& A. Tisson
pilorum Fron. & Gaillat Poa
n
probably
identical with
L. junci
(continued)
54
S. Neuhauser et al.
Table 3.1 (continued)
Genus
Species
Woronina
Polymyxa
Phagomyxa
Maullinia
Host species
isoetes Palm
betae (Němec) Karling
Isoetes
Beta
hypogeae (Borzı́)
Karling
plantaginis (Němec)
Karling
polycystis Cornu
pythii Goldie-Sm.
glomerata (Cornu)
A. Fisch
aggregata Zopf
Numerous hosts
leptolegnia Karling
graminis Ledingham
betae Keskin
algarum Karling
chattonii (P.A. Dang.)
Karling
bellerocheae Schnepf
odontellae Kühn,
Schnepf & Bulman
ectocarpi I. Maier, E.R.
Parodi, Westermeier
& D.G. Müll.
Plantago
Saprolegniaceae*
Pythium*
Vaucheria+
Hypertrophies Additional
comments
n
Found only once
n
probably
identical with
L. junci
n
no resting spores
known
n
no resting spores
known
n
–
n
–
n
–
Mougeotia$
n
Oedogonium$
Different grasses
Cenopodiaceae
Pylaiella+
Ectocarpus+
–
n
n
n
Found only once
on both hosts
only once
–
–
–
Found only once
–
–
Bellerochea#
Odontella#
n
n
–
–
Ectocarpus+
–
–
1969). The “Rohr” is evaginated to form a bulbous adhesorium which is attached to
the host cell wall. The Stachel passes down the “Rohr”, punctures the host wall and
then, within 1 s, an amoeboid infection unit (myxamoeba) is injected into the root
hair. The total time from adhesorium formation to host penetration is about 1 min
(Aist and Williams 1971). Inside the root hair, the myxamoeba develops into a
multinucleate plasmodium which cleaves into a sporangiosorus consisting of
numerous zoosporangia. Three to sixteen secondary zoospores hatch from each
zoosporangium (Ingram and Tommerup 1972). According to Tommerup and
Ingram (1971), two secondary zoospores undergo plasmogamy and the binucleate
spore infects the roots of the host, but such a fusion of zoospores has not been
confirmed by other authors studying the plasmodiophorid life cycle (LudwigMüller and Schuller 2008). Nevertheless, there is consensus that soon after the
infection by secondary zoospores, multinucleate secondary plasmodia are formed
in a process accompanied by pronounced cell division and the formation of
hypertrophic cells of the host plant. At this time the typical symptoms of clubroot
disease become obvious. During further development, the plasmodium cleaves
3 Plasmodiophorids: The Challenge to Understand Soil-Borne, Obligate Biotrophs
55
Fig. 3.1 Life cycle of Plasmodiophora brassicae: (a) Primary zoospores hatching out of resting
spores. (b) Encysted zoospore injects its protoplast into the root hair by the help of a special
extrusosome (“Rohr”) and a projectile-like structure (“Stachel”). (c) Primary plasmodia in root
hairs. (d) zoosporangia in root hairs. (e) Secondary zoospores infect cabbage root or (f) undergo
karyogamy according to Ingram and Tomerup (1971); but plasmogamy could not be confirmed by
other authors. (g)–(h) Secondary plasmodia are developed. (i) Formation of resting spores.
According to Ingram and Tomerup (1971) karyogamy and meioses (R!) take place prior to resting
spore formation. Alternative “microcycles” may occur: Mithen and Margath (1992) concluded that
secondary plasmodio may also be developed from primary zoospores. Naiki et al. (1984) demonstrated that secondary zoospores can re-infect root hairs and produce further zoosporangia. (a) and
(c)–(i) according to Woronin 1878; (b) according to Aist and Wiliams 1971
into numerous resting spores. These resting spores can survive in soil for at least
7–8 years (Jørstad 1923; Nielsen 1933 cited in Karling 1968). The formation of
primary zoospores closes the cycle. Recent studies provide evidence that the life
cycle may be more complicated. Naiki et al. (1984) demonstrated that secondary
zoospores can re-infect root hairs and produce further zoosporangia. Mithen and
Magrath (1992) concluded that secondary zoospores may not be necessary to
develop secondary plasmodia. Myxamoeba derived from primary zoospores may
migrate from root hairs to cells of the cortical tissue and form secondary plasmodia
and galls. This view was supported by observations by Narisawa et al. (1996) who
successfully infected the roots with single resting spores and detected plasmodia in
the cortical root cells. However, the formation of resting spores and therefore a
56
S. Neuhauser et al.
complete life cycle could be initiated only when plants were inoculated with a
dikaryotic or two monokaryotic resting spores (Narisawa and Hashiba 1998).
Although the life cycle of Pl. brassicae is now relatively well known, there
is still a lack of knowledge especially with respect of karyogamy. Moreover, the
life cycles of other plasmodiophorids differ in some degree or are not fully
known. Braselton (2001) summarised the current knowledge of sexuality in plasmodiophorids as “largely indirect and presumptive”. Seven years later, we know
only a little more about this topic. A comprehensive knowledge on the spatiotemporal distribution of the stages of the plasmodiophorids life cycle would provide
strategies for identification and detection of these important, plant-associated
organisms.
3.1.2
The Plasmodiophorids in the Tree of Life
Since the description of the first plasmodiophorid, their taxonomic position
remained unresolved for a considerable time. When Woronin established the
genus Plasmodiophora, he proposed an affiliation to the protists in the sense of
Haeckel and considered them as the simplest group of the Myxomycetes (Woronin
1878). Historically, Myxomycetes and therefore the plasmodiophorids were considered as fungi. In his monograph on the parasitic slime-moulds, Cook (1932)
discussed them as “some of the simplest, if not the most primitive, parasitic fungi
known”. There was much speculation on the evolution of plasmodiophorids in the
pre-molecular era. Mycologists placed the plasmodiophorids in the division Mastigomycota with other flagellate “fungi” (Alexopoulos and Mims 1979). The
presence of chitin in the cell wall of resting spores led to the conclusion that
plasmodiophorids may be related to Chytridiomycetes (Buczacki 1983). On the
basis of the ultrastructure of zoospores, Barr (1992) reverted to the view of Woronin
(1878) and classed the plasmodiophorids within the Protozoa. The transitional
region of the plasmodiophorid flagellum was found similar to that of “many protists
such as the amoeboflagellate Naegleria gruberi”, a species belonging to the
Heterolobosea classified among the discicristates (Keeling et al. 2008). CavalierSmith (1993) placed the order Plasmodiophorida in the class Phytomyxea, subphylum Proterozoa, phylum Opalozoa, where he grouped protists with tubular
mitochondrial cristae that lack plastids, cortical alveoli, and tubular ciliary hairs.
The progress of DNA sequencing has allowed a more profound classification of
the plasmodiophorid plant parasites. Molecular phylogenies based on 18S ribosomal rDNA data confirmed that plasmodiophorids were not related to fungi, but no
linkage with any other eukaryotic group was found (Castlebury and Dormier 1998;
Ward and Adams 1998). Using 18S rDNA data, Cavalier-Smith and Chao (1996/
1997) concluded that the Plasmodiophorida are most closely allied with a group
containing chlorarachneans and sarcomonads and placed them in the class Phytomyxea within a phylum temporarily called Rhizopoda. This phylum was then
renamed Cercozoa (Cavalier-Smith 1998, 2000; Cavalier-Smith and Chao 2003).
3 Plasmodiophorids: The Challenge to Understand Soil-Borne, Obligate Biotrophs
57
Protein sequence data indicate that the closest relatives of Cercozoa are the
Foraminifera (Keeling 2001). This relationship was confirmed by Archibald and
Keeling (2004) who analysed actin and ubiquitin protein sequences of plasmodiophorids. They found a single amino acid residue insertion at the functionally
important processing point between ubiquitin monomers, at the same position in
which an otherwise unique insertion exists in the cercozoan and foraminiferan
proteins. It was concluded that plasmodiophorids are related to Cercozoa and
Foraminifera, although the relationships among these groups remained unresolved.
Nikolaev et al. (2004) calculated SSU and actin phylogenies of amoeboid eukaryotes. They found that the Phytomyxea was a sister group to a clade consisting of
Phaeodarea, core Cercozoa, and Desmothoracida. In 2005, a revision of the classification of unicellular eukaryotes was suggested (Adl et al. 2005). A hierarchical
system without formal rank design (class, order, etc.) was adopted. According to
this scheme the Phytomyxea are embedded within the Cercozoa in the super-group
Rhizaria. It should be a task of future research to resolve the open questions on the
“true” alliance of plasmodiophorids.
3.1.3
Phylogenetic Relationships Within the Plasmodiophorids
In his monograph of the “Plasmodiophorales”, Karling (1968) accepted 11 genera
and 35 species (plus three varieties which are raised to species level in current
publications). Since then, six new species and one new genus of phytomyxids were
described (Table 3.1). Only eight of these 44 phytomyxid species were included in
phylogenetic DNA analyses: the plasmodiophorids Pl. brassicae, Polymyxa graminis Ledingham, Px. betae Keskin, Spongospora subterranea (Wallr.) Lagerh.,
Sp. narsturtii M.W. Dick, Sorosphaera veronicae J. Schröt., and the phagomyxids
Phagomyxa bellerocheae Schnepf and Ph. odontellae Kühn, Schnepf & Bulman.
Archibald and Keeling (2004) included five sequences from a total of three plasmodiophorid species in their phylogenetic study based on actin protein sequences.
The plasmodiophorid clade was divided into two sub-clades. One was formed by
Sp. subterranea and So. veronicae and a second clade consisted of sequences of two
Pl. brassicae isolates. The most comprehensive phylogeny was based on 18S rDNA
sequences of eight phytomyxid species (Bulman et al. 2001). In that study, two
major clades of phytomyxids were found: the plasmodiophorids parasiting green
plants and the phagomyxids parasiting diatoms. The two clades were designated as
“orders” according to zoological nomenclature (Phagomyxida, Plasmodiophorida).
The phagomyxids consisted of two Phagomyxa species (Ph. bellerocheae, Ph.
odontellae) and the plasmodiophorids consisted of Sp. subterranea, Sp. nasturtii
(¼ subterranea f. sp. nasturtii), Pl. brassicae, So. veronicae, Px. betae, and Px.
graminis. A subclade comprising So. veronicae and the two Polymyxa-species was
supported with bootstrap values of 100% in neighbour joining and parsimony
analysis.
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S. Neuhauser et al.
Although little is known about the “deep” roots of phytomyxid phylogeny, there
are some species whose intraspecific phylogeny has been studied in some detail.
Polymyxa species are only distinguishable by their host preferences. To resolve
whether Px. betae and Px. graminis are distinct taxonomic units, restriction analysis
of the ITS1-5.8S-ITS2 ribosomal rDNA region was applied by Ward et al. (1994).
This study confirmed that Px. betae is distinct from Px. graminis. Moreover, the
latter species could be divided into two subgroups (ribotypes). A third ribotype of
Px. graminis was found on Sorghum plants in India (Ward and Adams 1998). The
number of ribotypes increased to six when African and Japanese Polymyxa samples
were included in the phylogenetic analyses (Ward et al. 2005b). Legrève et al.
(2002) divided Px. graminis into five special forms (formae speciales) analysing
ITS sequences of a similar set of strains. Legrève and co-workers (2002) argued
that, in addition to sequence data, these special forms can be differentiated by
specific combination of host range and temperature requirements. Although the
f. speciales of Legrève et al. (2002) correspond to the ribotypes of Ward et al.
(2005b; Table 3.2, Fig. 3.2), there is no consensus on the naming of these taxa. For a
Table 3.2 Infraspecific taxa in Polymyxa graminis according to Ward et al. (2005a, b) and
Legrève et al. (2002). Genbank accession numbers for ITS1-5.8S-ITS2 rDNA sequences used in
these studies are given. Sequences used in both studies are printed in bold
Polymyxa graminis ribotype
Polymyxa graminis formae speciales
(Ward et al. 2005)
(Legreve et al. 2002)
ribotype I
Y12824
f. sp. temperata
AJ311572, AJ311573,
AJ3111574
ribotype II
Y12826
f. sp. tepida
Y12826
ribotype III
AJ311580, Y12825
f. sp. tropicalis
AJ311575, AJ311576,
AJ311580, Y12825
ribotype IV
AJ311577, AJ311579
f. sp. subtropicalis
AJ311577, AJ311578,
AJ311579
ribotype V
AJ010424, AM075820,
f. sp. colombiana
AJ010424
AM075821, AM075822
ribotype VI
AM075823
Fig. 3.2 Cladograms of infraspecific taxa within Polymyxa graminis according to Ward et al.
(2005b) and Legrève et al. (2002). Ward et al. (2005b) described ribotypes which correspond to
formae speciales suggested by Legrève et al. (2002)
3 Plasmodiophorids: The Challenge to Understand Soil-Borne, Obligate Biotrophs
59
general acceptance of the “new” infraspecific taxonomic units, more data from
different genes and more isolates should be analysed.
3.1.4
Economic Importance of Plasmodiophorids
A small number of plasmodiophorids are quite well studied, especially plasmodiophorids which cause plant diseases and/or have economic significance as vectors of
plant viruses. Loss caused by clubroot disease (Pl. brassicae; Figs. 3.3 and 3.4) was
estimated to be approximately 10% of all cruciferous crops in Australia (Faggian
et al. 1999). The hypertrophic roots of infested plants are a sink for sugars and
therefore the clubbed roots lead to stunted growth of the plants. As further example
of the economic impact of clubroot disease, in Nepal (province of Palung) the
economic loss was estimated at US$ 1.4 million in 2004 and 2005 (Timila et al.
2008). Another plasmodiophorid of economic significance is Sp. subterranea, the
causal agent of powdery scab of potatoes (Figs. 3.5 and 3.6). Powdery scab lesions
are usually small, circular, and uniform in size and are surrounded by a fringe of
potato skin when mature. As the tuber skin over the pustules ruptures, a shallow
depression filled with a brown, powdery mass of spores and broken-down tissue is
exposed. Infected tubers are predisposed to other maladies such as Fusarium dry rot
during storage. Moreover, Sp. subterranea can transmit the potato mop-top virus
(PMTV). Foliar symptoms of PMTV include yellow rings, V shape markings, and
blotches, especially on the lower leaves. Stems can also be stunted, giving a “moptop” effect. Tuber symptoms are called “spraing”, rustbrown discoloration, in the
form of arcs or rings and flecks that appears with internal rust-coloured spots on
tubers (reviewed by Merz 2008).
Rhizomania (lit. “crazy root” or “root madness”) is a serious disease of sugarbeet
caused by the beet necrotic yellow vein virus (BNYVV) which is transmitted by the
plasmodiophorid Px. betae (reviewed by Varrelmann 2007). Root symptoms include
a mass of fine, hairy secondary roots giving the taproot a beard-like appearance. This
reduces sugar yield because tonnage or sugar content or both are reduced. Losses can
amount to 50–70% of root weight and 2–4% or more of sugar content (EPPO 1997).
Px. graminis can cause significant yield reductions in cereal crops. Like Px. betae,
the plasmodiophorid itself does not obviously harm its host, but it can acquire and
transmit a range of plant viruses (reviewed by Kanyuka et al. 2003). The soil-borne
wheat mosaic virus (SBWMV), for example, causes serious diseases in many cereal
species, including winter wheat, durum wheat, barley, rye, and triticale (Brakke
1971). Losses of 40–50% occur in infected areas of commercial fields in Florida,
USA (Kucharek and Walker 1974). A complete life cycle of Px. graminis has only
been observed in monocotyledonous plants, but can be a vector for the Indian Peanut
Clump Virus as well (IPCV; Ratna et al. 1991). The dicot “groundnut” serves only as
an intermediate host and is not a “natural” reservoir for the plasmodiophorid vector.
Peanut clump viruses are among the most damaging soil-borne pathogens of
60
S. Neuhauser et al.
groundnut, causing crop losses estimated at over US$38 million per year world-wide
(Delfosse et al. 1999).
3.2
3.2.1
Experimental Strategies to Detect and Monitor
Plasmodiophorids
Direct Observations, Bioassays, and Bait Tests
“Easy” direct observations are limited to those plasmodiophorids that cause distinct
disease symptoms. Hypertrophies caused by some plasmodiophorid species
(Table 3.1) can be easily observed with the naked eye. Examples are the clubbed
roots of cruciferous plants (Fig. 3.4) or the shoot galls of Veronica spp. caused by
So. veronicae (Fig. 3.7). The lesions on potato tubers caused by Sp. subterranea are
also easy to recognise (Figs. 3.5 and 3.6). But not all plasmodiophorids cause
hypertrophies, so for those without obvious symptoms on their host plants, more
sophisticated monitoring methods are needed. Sporosori of So. viticola exhibit a
characteristic green–yellow autofluorescence (Fig. 3.8 and 3.9) at 450–490 nm.
This autofluorescence has been used to screen grapevine roots for its presence and
to assess the distribution of this plasmodiophorid in commercial vineyards (Huber
et al. 2006). Detection methods for identifying plasmodiophorids which do not
cause hypertrophies on the host plant or exhibit autofluorescence – like Px. graminis or L. junci – are restricted to microscopical screenings of plant roots.
One strategy for the detection of fungal or protozoan pathogens in soils and
composts are bioassays or bait tests (Ciafardini and Marotta 1989). These techniques
are particularly useful for detecting non-culturable, obligate parasites (Noble and
Roberts 2004). Sensitive indicator plants are grown in the test material (e.g. soil),
and the presence of the pathogen is indicated by the development of typical disease
symptoms on the indicator plants. The benefits of bioassays are that the viability and
pathogenicity are indicated as well as the presence of the pathogen. Drawbacks are
that bioassays can take several weeks and can be hampered by low inoculum levels
or by microbial interactions (Christensen et al. 2001). Nevertheless, bioassays and
bait tests are standard procedures in different national and international regulations.
For example, the German “Ordinance on Biowaste” (BioAbfV) regulates a testing
for Pl. brassicae of biowastes which should be spread on agricultural, silvicultural,
or horticultural land. The aim of this regulation is to minimise the risk of spreading
viable Pl. brassica resting spores. The method is based on the work of Knoll et al.
(1980) and Bruns et al. (1994). To evaluate the efficacy of composting on removing
pathogenic propagules, meshbags containing Plasmodiophora root galls mixed with
compost are incorporated into biowaste. After composting, the samples are mixed
with sterilised sand and peat. Test plants (Brassica juncea variety “Vitasso”) are
potted into this mixture, and then incubated for 5 weeks. Affected plants are counted
and the root gallings are graded. An infection index can be calculated.
3 Plasmodiophorids: The Challenge to Understand Soil-Borne, Obligate Biotrophs
61
Figs. 3.3–3.9 Host symptoms of plasmodiophorid infestations. Figs. 3.3–3.4: Clubroot disease on
cauliflower (3: healthy roots, 4: clubbed roots) caused by Plasmodiophora brassicae (bars ¼ 1 cm).
Figs. 3.5–3.6: Powdery scab of potatoes caused by Spongospora subterranean (5: bar ¼ 1 cm;
6: bar ¼ 5 mm). Fig. 3.7: Shoot gall on Veronica persica induced by Sorosphaera veronicae
(bar ¼ 5 mm). Figs. 3.8–3.9: Epifluorescence of sporosori of Sorosphaera viticola in vine roots at
450–490 nm (8: bar ¼ 1 mm; 9: bar ¼ 20 mm)
3.2.2
Molecular Approaches
Methods based on molecular components of cells have opened new possibilities in
the study of plasmodiophorids. These methods allow the detection of plasmodiophorids in host tissue and in environmental samples such as soil or water, which is
of great interest for scientists who want to understand the parasite’s life cycle. The
methods also permit risk assessments to be made, which are important for breeders
and growers of susceptible crops who face economic losses either from the symptoms caused by plasmodiophorids or the viruses they transmit. Many nucleic acidbased and immunological methods have been developed to facilitate an easy,
fast, and highly sensitive detection of plasmodiophorids. These can be used for
62
S. Neuhauser et al.
large-scale screenings for infected plants in plantations or for pre-planting tests of
soils for the presence of the pathogen. Different molecular approaches to identify
plasmodiophorids, including their implementation in the field, will be discussed in
the following sections.
3.2.2.1
Antibody-Based Methods
Immunological test methods are quick and detect mainly living material, but the
laborious development of assays and possible cross-reactions with related species
or the host plant are serious drawbacks (Ward et al. 2004a, b). The development of
antibodies and sensitive test systems which are ideally applicable in the field
requires considerable optimisation. This process is expensive compared with the
development of nucleic acid-based methods for the identification of plasmodiophorids. Although dip-stick tests or lateral flow devices could facilitate on-site
testing, ELISA (enzyme linked immunosorbent assay) protocols are most commonly used, probably because of their wide application in plant virus detection
(Merz et al. 2005): the detection of plasmodiophorid parasites and the viruses they
transmit can be done with the same equipment.
The obligate biotrophic and endophytic nature of plasmodiophorids makes it
very important, but difficult, to avoid cross-reactions, especially with the host plant.
Even if protocols for the purification and accumulation of plasmodiophorid resting
spores are used, the resulting preparations are never completely free of contaminating plant material or other microorganisms (Wakeham and White 1996; Walsh et al.
1996; Delfosse et al. 2000; Qu and Christ 2006a). Two types of antibodies are used:
polyclonal antibodies (a mixture of antibodies; usually obtained from immunised
animals) and monoclonal antibodies (a specific antibody against a protein or
component of the cell). Polyclonal antibodies have been used in ELISA tests for
Sp. subterranea (Harrison et al. 1993; Wallace et al. 1995; Walsh et al. 1996; Merz
et al. 2005); Px. betae (Walsh et al. 1996; Mutasa-Göttgens et al. 2000; Kingsnorth
et al. 2003a), Px. graminis (Delfosse et al. 2000) and Pl. brassicae (Wakeham and
White 1996). All authors reported a (semi-)quantitative detection of resting spores
in plant material and soil samples. All antibodies used were reported to be highly
specific for the targeted pathogen; only between the two Polymyxa species did some
cross-reactions occur (Delfosse et al. 2000). Besides ELISA-tests, polyclonal antibodies for Pl. brassicae were used in western blots, dot blots, dip-sticks, and
indirect immunofluorescence microscopy (Arie et al. 1988; Wakeham and White
1996).
More specific, but also more laborious, is the production of monoclonal antibodies. An ELISA method based on monoclonal antibodies against a glutathioneS-transferase (GST) specific for Px. betae was established (Mutasa-Göttgens et al.
2000; Kingsnorth et al. 2003a). The GST cDNA was cloned and expressed, then
purified and used for antibody production. Monoclonal antibodies were used with
varying success for Sp. subterranea: Wallace et al. (1995) derived five different
monoclonal antibodies recognising zoospores and plasmodia but not cytosori. They
3 Plasmodiophorids: The Challenge to Understand Soil-Borne, Obligate Biotrophs
63
observed a cross-hybridisation with Px. graminis, whereas Merz et al. (2005)
reported the production of a highly sensitive and specific antibody detecting all
stages of the life cycle.
In plant pathology, immunological tests are especially popular to detect plant
viruses. As some viruses need a plasmodiophorid as vector to infect plants, the
presence of the virus gives indirect evidence of the presence of the plasmodioporid.
For some of the viruses transmitted by plasmodiophorids, serological detection
methods are available. An overview is published at DPVweb (see Description of
Plant Viruses; Adams and Antoniw 2006, http://www.dpvweb.net/ and the references therein).
3.2.2.2
Nucleic Acid-Based Methods
Nucleic acid-based detection methods were quickly appreciated by plant pathologists dealing with plasmodiophorids (Ward et al. 1994; Buhariwalla et al. 1995).
The supplementation or substitution of classical observation methods with PCRbased detection methods for the first time allowed large-scale screening and
epidemiological studies (Legrève et al. 2000; Legrève et al. 2003; Legrève et al.
2005; Qu and Christ 2006b). However, the obligate biotrophic lifestyle of the
plasmodiophorids remains problematic. Plasmodiophorids cannot grow in the
absence of their particular host plants and if it is possible to establish a dual system
plant–pathogen, it is virtually impossible to keep it without any environmental
contamination. Against this background, it is no surprise that, again, only those few
plasmodiophorid species causing plant diseases or transmitting plant viruses have
been the focus of DNA detection research. During recent years, emphasis has been
placed on the development of highly specific detection methods and speciesspecific primers for the plasmodiophorid crop pathogens (see Table 3.3 and the
references therein).
Most plasmodiophorid DNA-sequences are available from the ITS1-5.8S-ITS2
region of the rDNA tandem repeat. The majority of the species-specific primers
have been designed from the highly variable spacers in this region; as a multi-copy
gene, the ribosomal repeat is relatively easy to access (Fig. 3.10, Ward and Adams
1998; Bell et al. 1999; Faggian et al. 1999; Bulman et al. 2001; Wallenhammar and
Arwidsson 2001; Down and Clarkson 2002; Legrève et al. 2003; Meunier et al.
2003; van de Graaf et al. 2003; Ward et al. 2004a, b, 2005a, b). There were also
attempts to find other, unique plasmodiophorid regions for PCR-based detection.
For Pl. brassicae, a single copy gene unique to the pathogen was used (Ito et al.
1997, 1999; Wallenhammar and Arwidsson 2001). The single-copy GST-gene
(Mutasa-Göttgens et al. 2000) and another single copy gene (Genbank accession
number X83745) were used for the detection of Px. betae (Mutasa et al. 1995;
Mutasa et al. 1996; Kingsnorth et al. 2003b). Using the latter gene, a nested PCR
(nPCR) method and a single-tube nested PCR (stnPCR) method were developed to
identify Px. betae without the risk of a co-amplification of host DNA (Ciafardini
and Marotta 1989; Mutasa et al. 1995; Mutasa et al. 1996). The RNA transcript of
64
S. Neuhauser et al.
Table 3.3 PCR primers used for the detection of plasmodiophorids. Abbreviations of “Reaction type”: PCR ¼ standard PCR. qPCR ¼ real-time PCR,
nPCR ¼ nested PCR, stnPCR ¼ single-tube-nested PCR, mRT-PCR ¼ multiplex reverse transcriptase PCR
Taxa
Gene
Primer
Primer sequence (50 –30 )
Reaction
Reference
type
Plasmodiophorids
rDNA PNS1
gTT ATC Tgg TTg ATC CTg CC
PCR
Bulman et al. (2001)
Pl. brassicae
D85819 PBTZS-2
CCg AgT TCg CgT CAg CgT gA
stnPCR
Ito et al. (1997)
Pl. brassicae
D85819 PBTZS-3
CCA CgT CgA TCA CgT TgC AAT
stnPCR
Ito et al. (1997)
Pl. brassicae
D85819 PBTZS-4
gCT ggC gTT gAT gTA CTg gAA TT
stnPCR
Ito et al. (1997)
Pl. brassicae
D85819 PBAW-10
CCC Cgg ggA TCA CgA TAA ATA ACA nPCR
Wallenhammar and Arwidsson
(2001)
Pl. brassicae
D85819 PBAW-11
ggA Agg CCg CCC Agg ACT ACC
nPCR
Wallenhammar and Arwidsson
(2001)
Pl. brassicae
D85819 PBAW-12
gCC ggC CAg CAT CTC CAT
nPCR
Wallenhammar and Arwidsson
(2001)
Pl. brassicae
D85819 PBAW-13
CCC CAg ggT TCA CAg CgT TCA A
nPCR
Wallenhammar and Arwidsson
(2001)
Pl. brassicae
rDNA PbITS1
ACT TgC ATC gAT TAC gTC CC
nPCR
Faggian et al. (1999)
Pl. brassicae
rDNA PbITS2
ggC ATT CTC gAg ggT ATC AA
nPCR
Faggian et al. (1999)
Pl. brassicae
rDNA PbITS6
CAA CgA gTC AgC TTg AAT gC
nPCR
Faggian et al. (1999)
Pl. brassicae
rDNA PbITS7
TgT TTC ggC TAg gAT ggT TC
nPCR
Faggian et al. (1999)
Pl. brassicae
rDNA CR2
TAT gCC gCA gCA AAg CTC
PCR
Bulman et al. (2001)
Px. betae
GST
male
gAC ATT gCC gCT CTg ACT T
qPCR
Kingsnorth et al. (2003a, b)
Px. betae
GST
female
AATg AgC TgT TgC CTT ATT TTg gA
qPCR
Kingsnorth et al. (2003a, b)
Px. betae
GST
probe
CAA gCA ggC TCA CgC TgC CAT g
qPCR Probe Kingsnorth et al. (2003a, b)
Px. betae
rDNA 698F
CAT gTC ggC AAC CgA AAg T
qPCR
Ward et al. (2004b)
Px. betae
rDNA 760R
Tgg TTC ggg CgCC CAT
qPCR
Ward et al. (2004b)
Px. betae
rDNA 718 T
Cgg ATT CTT ggA ACg AAT CCg C
qPCR Probe Ward et al. (2004b)
Px. betae
rDNA BET1
CgA ATC gAC TCT CAT TgT CC
PCR
Bulman et al. (2001)
Px. betae
X83745 Pb-5a
CAg ggg CAg ACg gAT CgC Ag
stnPCR
Mutasa et al. (1996)
Px. betae
X83745 Pb-5b
CgT CgA gCg CAg TTC TTg gC
stnPCR
Mutasa et al. (1996)
X83745 Pb-6a
AgA TgA ggA TgT CAg TCA gg
stnPCR
Mutasa et al. (1996)
Px. betae
Px. betae
X83745 Pb-4b
CTA TgT ggC AAA CCC AAg
stnPCR
Mutasa et al. (1996)
Px. betae
X83745 Pb-3a
ACg ATg gAC gAC TAT TgA ggg g
nPCR
Mutasa et al. (1995)
X83745
X83745
X83745
X83745
X83745
rDNA
rDNA
rDNA
rDNA
rDNA
Pb-3b
Pb-N3a/2
Pb-N3b/2
PB4for
PB4rev
Pxfwd1
Pxfwd2
Pxrev7
PxRealF
PxRealR
Px. graminis
Px. graminis
Px. graminis
Px. graminis
Px. graminis
Px. graminis f.sp. temperata
Px. graminis f.sp. temperata
Px. graminis f.sp. temperata
Px. graminis f.sp. temperata
Px. graminis f.sp. temperata
Px. graminis f.sp. tepida
Px. graminis f.sp. tepida
Px. graminis f.sp. tepida
Px. graminis f.sp. tepida
Px. graminis f.sp. tepida
Px. graminis ribotype II
Px. graminis ribotype II
Px. gramins ribotype I
Px. gramins ribotype I
Polymyxa spp.
Polymyxa spp.
rDNA
rDNA
rDNA
rDNA
rDNA
rDNA
rDNA
rDNA
rDNA
rDNA
rDNA
rDNA
rDNA
rDNA
rDNA
rDNA
rDNA
rDNA
rDNA
rDNA
rDNA
PxRealP
690F
758R
713 T
GRA2
PgtempN-F
PgtempN-R
Pgtemp-F
Pgtemp-R
Pgtemp-S
PgtepN-F
PgtepN-R
Pgtep-F
Pgtep-R
Pgtep-S
Pg.F2
Pg.R2
Pg.F1
Pg.R1
ITS2mod
mITS5rc
gCA gCC TAg TCA CAA ATg gCg
Tgg Agg AAA ggg
ACT TgT CAg TTg CC
CAC ACg CCT gAA ATC ATC TAA C
gAT ggC CAA TT CTT ACA C
CTg Cgg AAg gAT CAT TAg CgTT
ggA Agg ATC ATT AgC gTT gAA T
gAg gCA TgC TTC CAg ggC TCT
CgT CgC TTC TAC CgA TTg gT
CCT TgT TAC gAC TTC TTC TTC CTC
TAg T
CCg gTg AAC AAT Cg
CAg CCC gCA TgC ATC TC
Cgg ATT gTC gTT CCA AgA A
TCA gCA CgT CCA AAg TCC AT
gTT CCA AgA ACC CgA Tgg AC
AgC gTT gAA TTTg gTC TTg gT
TAg CCA ATT CTC CCg AgT TC
ggA gTT gCA TCC CgC ATg
CgCC ATg ACg gAT TgT CgT T
AgT CAg CAC gTC gC CAA AgT CCA
TAg CgT TgA ATg gTT gTT gC
TTC gAC TTT AgC CAC CgT TT
AAT gTg gAT CgT CTC TgT TgC Tg
CAC CT TTT gAT CCA ATT CgT gAA
Cgg gAT ggA ACg CCC TCg Tgg Tgg
ATg Tgg ATC gTC TCT gTT gCT ggA
CCT CAT CTg AgA TCT TgC CAA gT
AAC ATg Tgg ATT gTg ggC TAT gTg
AAC TCC CAT TCT CCA CAA CgC AA
gCT gCg TTC TTC CAT CgT TgT gg
CCT ACg gAA ACC TTg TTA Cg
Mutasa et al. (1995)
Mutasa et al. (1995)
Mutasa et al. (1995)
Meunier et al. (2003)
Meunier et al. (2003)
Ward and Adams (1998)
Ward and Adams (1998)
Ward and Adams (1998)
Ward et al. (2005a, b)
Ward et al. (2005a, b)
qPCR Probe
qPCR
qPCR
qPCR Probe
PCR
PCR
PCR
qPCR
qPCR
qPCR Probe
PCR
PCR
qPCR
qPCR
qPCR Probe
PCR
PCR
PCR
PCR
PCR
PCR
Ward et al. (2005a, b)
Ward et al. (2004b)
Ward et al. (2004b)
Ward et al. (2004b)
Bulman et al. (2001)
Vaianopoulos et al. (2005)
Vaianopoulos et al. (2005)
Vaianopoulos et al. (2005)
Vaianopoulos et al. (2005)
Vaianopoulos et al. (2005)
Vaianopoulos et al. (2005)
Vaianopoulos et al. (2005)
Vaianopoulos et al. (2005)
Vaianopoulos et al. (2005)
Vaianopoulos et al. (2005)
Ward et al. (2005a, b)
Ward et al. (2005a, b)
Ward et al. (2005a, b)
Ward et al. (2005a, b)
Ward and Adams (1998)
Ward and Adams (1998)
(continued)
65
nPCR
nPCR
nPCR
mRT-PCR
mRT-PCR
PCR
PCR
PCR
qPCR
qPCR
3 Plasmodiophorids: The Challenge to Understand Soil-Borne, Obligate Biotrophs
Px. betae
Px. betae
Px. betae
Px. betae
Px. betae
Px. graminis
Px. graminis
Px. graminis
Px. graminis
Px. graminis
Gene
Primer
Primer sequence (50 –30 )
Polymyxa spp.
Polymyxa spp.
Sp. subterranea
Sp. subterranea
Sp. subterranea
rDNA
rDNA
rDNA
rDNA
rDNA
Psp1
Psp2rev
SsTQF1
SsTQR1
SsTQP1
Sp. subterranea
Sp. subterranea
Sp. subterranea
Sp. subterranea
Sp. nasturtii
Sp. nasturtii
Sp. nasturtii
So. veronicae
So. viticola
(Plasmodiophorids?)
So. viticola
(Plasmodiophorids?)
rDNA
rDNA
rDNA
rDNA
rDNA
rDNA
rDNA
rDNA
rDNA
rDNA
66
Table 3.3 (continued)
Taxa
Legrève et al. (2003)
Legrève et al. (2003)
van de Graaf et al. (2003)
van de Graaf et al. (2003)
van de Graaf et al. (2003)
Sps1
Sps2
Spo8
Spo9
SSN18
SPO2
WC1
SV1
Psvit F
TAg ACg CAg gTC ATC AAC CT
Agg gCT CTC gAA AgC gCA A
CCg gCA gAC CCA AAA CC
Cgg gCg TCA CCC TTC A
CAg ACA ATC gCA CCC Agg TTC
TCA Tg
CCT ggg TgC gAT TgT CTg TT
CAC gCC AAT CCT TAg AgA Cg
CTg ggT gCg ATT gTC TgT Tg
CAC gCC AAT ggT TAg AgA Cg
ATT ATC TCC ggA TAg TTC TTg gA
Agg CAg ACA gAT TTg ACT CT
gCA gAC AgA TTT gAC TCT gg
gCC gAC AAT CAC ATT CAA CC
ACg CgT TCC AAC TTC TTA gAg ggA
Reaction
type
PCR
PCR
qPCR
qPCR
qPCR Probe
Reference
PCR
PCR
PCR
PCR
PCR
PCR
PCR
PCR
PCR
Bell et al. (1999)
Bell et al. (1999)
Bulman and Marshall (1998)
Bulman and Marshall (1998)
Down and Clarkson (2002)
Down and Clarkson (2002)
Bulman et al. (2001)
Bulman et al. (2001)
This article
Psvit R
CAT gCC TCT CTg AgT ATC ggT TTC
PCR
This article
S. Neuhauser et al.
3 Plasmodiophorids: The Challenge to Understand Soil-Borne, Obligate Biotrophs
67
Fig. 3.10 Diagrammatic illustration of species specific PCR primers and their position on the
18S – ITS1 – 5.8S – ITS2 – 28S ribosomal rDNA region. Primer sequences and the corresponding
references can be found in Table 3.3
this gene was used in a multiplex reverse-transcriptase PCR (mRT-PCR) for the
simultaneous detection of Px. betae and the viruses it transmits (BNYVV, BSBV,
and BVQ, Meunier et al. 2003). An advantage of using RNA as template for PCR is
that only active cells are detected and consequently positive results will only be
obtained when the pathogen is active in the host plant. But, when resting spores
need to be detected, this method has the serious drawback that resting spores
contain little RNA. For growers and breeders, it is important to detect soil-inoculum
68
S. Neuhauser et al.
prior to planting, so DNA-based methods may be preferred. One disadvantage of
nucleic acid-based methods is that processing of samples usually has to be done in
the lab with specialised equipment and specially trained staff. For other plant
pathogens, on-site PCR methods have been described recently (Tomlinson et al.
2005). Results can be obtained within a few hours in the field, but on-site detection
is more difficult. For example, there is the need for electric power supply and a high
risk of cross-contamination. Specialist staffs are also required. Therefore, the onsite PCR detection methods are to date not technically mature enough to provide
robust high-throughput screenings in the field.
The intimate contact of plasmodiophorids with their host plants or with soil
matrix is the reason for another problem: the sensitivity for all PCR methods was
high for purified zoospore or resting spore preparations, but decreased when
plasmodiophorids needed to be detected in plant material or soil samples (Faggian
et al. 1999). These problems are not restricted to plasmodiophorids: the biggest
difficulty in the application of PCR-based methods in phytopathology is to reproducibly extract high quality DNA from plants and soil (Mumford et al. 2006). The
presence of various impurities, co-extracted with soil – such as humic acids,
polysaccharides, or metal ions – can hamper PCR (Wilson 1997; Robe et al.
2003). Inhibitory compounds from plant tissues (e.g. polyphenolic substances like
tannins or polysaccharides) interfere in the DNA extraction process as well as in
later processing steps like PCR. These compounds vary between soil types, within
plants, between plant species, and with different (soil) management systems.
Hence, it is not surprising that many methods have been published for DNA
extraction from soil samples (for reviews see Lakay et al. 2007; Robe et al. 2003;
Wilson 1997). Microorganisms are unevenly distributed in soil: they can be bound
to soil particles or aggregated around organic matter. Therefore, strong sampling
strategies are required to detect soilborne pathogens. However, the production of
high quality DNA extracts from plants or soil remains the critical step in nucleicacid-based detection systems for plasmodiophorids.
3.3
Plasmodiophorid Genomics
A more complete understanding of the different phases of plasmodiophorid life
cycles is of great interest. Much effort has been made to develop DNA-based
methods for the detection of plant pathogenic plasmodiophorids, but basic questions about how and which biochemical processes the plasmodiophorid manipulates
in the host plant remains unresolved. Even in the “molecular era”, species and
genus concepts within the plasmodiophorids are mainly based on the morphology
of the sporosori (Figs. 3.11–3.16) and on the host plants (Braselton 2001). Of the
different stages of plasmodiophorids, only the resting spores can be used to identify
and diagnose a plasmodiophorid in the host plant. Observation of zoosporangia, or
even more so, plasmodia and zoospores, is time consuming, demanding, and does
not allow discrimination at the species level. Molecular tools are needed to
3 Plasmodiophorids: The Challenge to Understand Soil-Borne, Obligate Biotrophs
69
Figs. 3.11–3.16 Resting spores of different plasmodiophorids: Fig. 3.11: Plasmodiophora brassicae in roots of Brassica oleacea (cauliflower). Fig. 3.12: Ligniera junci in roothairs of Juncus
triglumis. Fig. 3.13: Polymyxa graminis in roots of Poaceae. Fig. 3.14: Sorosphaera veronicae
in shoot of Veronica persica. Fig. 3.15: Spongospora subterranean on tubers of Solanum tuberosum (potato). Fig. 3.16: Sorosphaera viticola in roots of Vitis berlandieri riparia SO4
(bar ¼ 10 mm)
determine the species or resolve the processes at the plant-parasite interface.
Until the first plant genomes were fully sequenced and annotated, few workers
met the challenge of studying the molecular basis of plasmodiophorid infection
(Buhariwalla and Mithen 1995; Mutasa et al. 1995; Subr et al. 2002; Brodmann
et al. 2002; Graf et al. 2004). The fully sequenced and annotated genome of
70
S. Neuhauser et al.
Arabidopsis thaliana, which serves as a host plant for Pl. brassicae, opened new
possibilities to study plant/host interactions. In recent years the Arabidopsis/Plasmodiophora pathosystem has been increasingly used to understand processes
induced by the pathogen and the subsequent physiological changes in the plant
(Winkel-Shirley 2002). A search in the ISI Web of Knowledge database (isiknowledge.com) using the term “Plasmodiophora AND Arabidopsis” produces 60 hits
(Accession date: 09.10.2008, 20:35 CET). Only 13 of these works were undertaken
between 1992, when the first work was published, and 2000 when the Arabidopsis
genome was launched (The Arabidopsis Genome Initiative 2000). Since 2001, 47
works have been published, with 29 of these published from 2006 onwards.
Therefore, progress in the genome sequencing of other susceptible plants should
help us to understand the mode of interaction of host plants and plasmodiophorids
to shed light on their biotic interactions.
Transcriptome analysis of Arabidopsis plants suffering from clubroot disease
has revealed that more than 1,000 genes are differentially expressed in infected
roots (Siemens et al. 2006). The use of Arabidopsis microarrays has demonstrated
that genes involved in cell division and expansion, as well as genes associated with
plant growth hormones like auxin and cytokinin, are upregulated (Siemens et al.
2006). Interestingly, genes involved in pathogen defence showed either no response
to an infection or were downregulated shortly after the infection. This indicates an
even closer interplay between plasmodiophorid parasites and their host plant than
suspected. The susceptible biotic interaction and the partial resistance of some
Arabidopsis varieties to clubroot infection have stimulated the study of differences
in resistant and susceptible plants at the molecular level (Jubault et al. 2008) as
well.
Cao et al. (2008) investigated proteome-level changes in the roots of clubbed
roots of Brassica napus. They found 20 proteins to be differentially produced when
canola plants were challenged by Pl. brassicae. Results indicate that lignin biosynthesis in the host plant decreased, as did enzymes that are involved in the reactive
oxygen species metabolism. This again points toward a very close interplay
between plasmodiophorids and their hosts. As found in A. thaliana, proteins
involved in plant growth hormone pathways were increasingly produced.
Arabidopsis and Pl. brassicae have not only been used to study the changes in
the host plant after infection but have also been used to identify genes from the
plasmodiophorid (Bulman et al. 2006; Bulman et al. 2007). The obligate nature of
the parasite means that a mixture of pathogen and plant is obtained from metabolically active plasmodia. To lessen the number of plant genes, suppression subtractive hybridization between the pathogen and plant RNA was used. The annotated
genome of the host plant also allowed the exclusion of host-sequences from the
analysis. Seventy six new plasmodiophorid genes were identified (Bulman et al.
2006). In a subsequent work, an intron-rich structure of Pl. brassicae genes was
described (Bulman et al. 2007).
Almost everything we know about plasmodiophorid plant interactions is compiled from experiments with Pl. brassicae, whereas we know very little about
the interactions of plasmodiophorids that do not form galls (e.g. Px. graminis).
3 Plasmodiophorids: The Challenge to Understand Soil-Borne, Obligate Biotrophs
71
Even less is known about species without economic impact. It will be an interesting
task for future research to investigate how these plasmodiophorids influence host
metabolism and communicate with the plant.
3.4
How Common are Plasmodiophorids?
It is unclear whether plasmodiophorids are genuinely rare, or if their abundance is
currently underestimated. As an illustration of this, almost nothing is known about
plasmodiophorids infecting plants without agricultural value. This lack of information is reflected in the molecular data available: At NCBI Genbank, there are
sequences of only 11 phytomyxid species (3 phagomyxids, 8 plasmodiophorids),
amounting to a total of 152 nucleotide sequences (Search term “txid37358”,
accession date: 26.9.2008, 19:23 CET). Furthermore, only seven of the sequences
from plasmodiophorids infecting green plants are from economically “unimportant” species [So. veronicae (4), Ligniera sp. (2), and So. viticola (1)]. These
nucleotide sequences were all derived from one isolate each. Genomic survey
sequences (GSS) were deposited only for Pl. brassicae (9) and expressed sequence
tags (ESTs) have been deposited only for Pl. brassicae (93) and Px. graminis (1).
Sixty protein sequences have been obtained from five species, with the vast
majority again from Pl. brassicae (49). Only five sequences derived from environmental clone-libraries are assigned as “plasmodiophorid” although our unpublished
sequence comparisons show that there are some unrecognised plasmodiophorids
assigned as “uncultured fungus” or “uncultured eukaryote”. Given the progress of
environmental screenings using clone-libraries (López-Garcı́a and Moreira 2008),
this number is low.
The idea that the abundance of plasmodiophorids may be underestimated is
encouraged by the results of our sampling of Juncus sp. from five different locations
in Austria during summer and autumn 2008. When the root hairs were screened by
microscopy, Ligniera junci could be observed easily in four samples. In one Juncus
sample, an unintentionally co-sampled Poaceae was found to be infested with Px.
graminis. At the same location, So. veronicae was previously found in shoots of
Veronica persica (Neuhauser et al. 2005). Another Ligniera-positive Juncus sp.
was collected in an area where fungal soil-clone libraries were constructed during a
3 year survey on alterations of soil fungal communities. No plasmodiophorid
sequences were detected in that study (Oberkofler 2008) although the primers
used have been employed to obtain sequences from plasmodiophorids (Ward
et al. 1994). In these examples, the random sampling of potential host plants
indicated a high abundance and diversity of plasmodiophorids. It will be highly
desirable to develop new PCR primers which preferentially amplify phytomyxids to
learn more about these biotrophic parasites. In a preliminary experiment of this
kind, we have designed primers for the amplification of partial SSU, ITS 1, and
5.8S rDNA from So. viticola (Table 3.3). These primers were successfully used for
direct sequencing of different isolates of L. junci, Px. graminis, and So. veronicae
72
S. Neuhauser et al.
from plant material. Those primers have not yet been fully tested, but they seem to
be suitable to directly sequence plasmodiophorids from different hosts and give
good PCR results when used with soil DNA extracts. PCR primers specific for
plasmodiophorids as well as the phagomyxids would allow an active inclusion in
analyses of different habitats, which would be a valuable step towards a better
understanding of this enigmatic group of eukaryotes. As noted earlier, there are a
small but increasing number of unassigned plasmodiophorid sequences appearing
in DNA-databases. A coordinated study of these sequences together with specific
environmental screening has the potential to reveal new diversity among plasmodiophorids.
3.5
Conclusions and Future Research
Although, much recent progress has been made in understanding plasmodiophorids
and their interactions with their host plants, they remain a cryptic group of organisms. Few species have been studied in detail, and what is known about these raises
more questions than answers. The ecological importance of the plasmodiophorids
cannot be evaluated, because their distribution and abundance in non-agricultural
areas are not known. Classical screenings are time-consuming and laborious as
most plasmodiophorids have a biotrophic interaction with their host plants. It will
be important to gain data about the abundance of plasmodiophorids in terrestrial,
fresh water, and marine ecosystems. Plasmodiophorids have a large impact on their
hosts and may have an important role in shaping certain ecosytems. With the
progress of DNA-based taxonomy and detection methods, it will be important to
define suitable regions for barcoding in plasmodiophorids. To date mostly rDNA
sequence data are available and the 18S region seems to be a promising target.
Because of their obligate affiliation with their host plants and to decrease the risk of
negative-primer bias, it would be of great use to identify a unique region in the
plasmodiophorid genome to minimize the risk of cross-reactions with host plants
and other endophytic organisms. First studies on Pl. brassicae genes indicate that
there are genes which have no similarity with genes from any other organism
(Bulman et al. 2006; Bulman et al. 2007). To define if one of these regions is
suitable for barcoding of phytomyxids will be task of future research. DNA data
from several regions of the plasmodiophorid genomes would also be desirable to
create a multigene phylogenetic tree. This would facilitate a better understanding of
the intra- and infragenetic relationships between plasmodiophorid species and
related organisms and help the plasmodiophorids to occupy a well defined place
in the tree of life. As the life cycle of many plasmodiophorids is not resolved in
detail, molecular data should be supplemented with morphological data. This would
allow a new, more comprehensive classification and characterization of the plasmodiophorids.
Random samplings indicate that in certain habitats plasmodiophorids occur in
high abundance. To evaluate their possible regulatory or selective role in these
3 Plasmodiophorids: The Challenge to Understand Soil-Borne, Obligate Biotrophs
73
ecosystems, data on their distribution and their interaction with primary and
alternative host plants are needed. It is not known if there is a difference in the
interaction with the host plant when primary or secondary plasmodia are formed.
The primary sporogenic plasmodia can be formed in different intermediate host
plants (Karling 1968; Legrève et al. 2000; Legrève et al. 2005; Qu and Christ
2006b) and do not cause any visible symptoms in the host plant. More information
about this life cycle stage and comparative analysis with the primary plasmodia
could help to understand the compatible interactions leading to hypertrophic growth
of the host plant. This information could provide a guide for the breeding of
resistant plants.
There remains a great deal to be learnt about the biology of this fascinating and
increasingly important group of organisms.
Acknowledgements The authors wish to thank Ueli Merz and Lars Huber for providing plasmodiophorid samples. We are indebted to Reinhold Pöder for passing on valuable comments and for
his kind support with taking the micrographs. The work was partially supported by the FWF
(Austrian Science Fund, grant T379-B16, SN).
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Chapter 4
Applications of Molecular Markers and DNA
Sequences in Identifying Fungal Pathogens
of Cool Season Grain Legumes
Evans N. Njambere, Renuka N. Attanayake, and Weidong Chen
Abstract Molecular techniques have now been widely applied in many disciplines
of biological sciences including fungal identification in microbial ecology and in
plant pathology. In plant pathology, it is now common to use molecular techniques to
identify and study plant pathogens of many agronomical and horticultural crops
including cool season grain legume crops. In this chapter, we present two examples
in which molecular techniques have been applied in order to identify and investigate
multiple fungal pathogens causing two important diseases of chickpea and lentil. In
each case, molecular techniques improved over traditional morphological identification and allowed timely and unambiguous identification of fungal pathogens. The
first example involves identification of two Sclerotinia species (S. sclerotiorum and
S. trifoliorum) causing stem rot of chickpea. Traditional method requires induction of
carpogenic germination and observation of dimorphic ascospores in S. trifoliorum,
which takes up to eight weeks. Taking advantage of the group I introns present in the
nuclear small subunit rDNA of S. trifoliorum but absent in the same DNA region of
S. sclerotiorum, a simple PCR amplification of the targeted DNA region allowed
timely and reliable differentiation and identification of the species. The second example is of powdery mildew of lentil. Identification of powdery mildew fungi requires
observing the teleomorphic (sexual) state of the pathogens, but this is not always
available. In studying lentil powdery mildew in the US Pacific Northwest, we found
that the powdery mildew on lentil does not fit previously reported species (Erysiphe
pisi and E. diffusa). Further investigation confirmed that the lentil powdery mildew in
the US is E. trifolii, a new pathogen of lentil. This discovery was mainly based on the
rDNA ITS sequences and further confirmed by morphological and pathogenicity
E.N. Njambere and R.N. Attanayake
Department of Plant Pathology, Washington State University, Pullman, WA 99164, USA
W. Chen
Department of Plant Pathology, Washington State University, Pullman, WA 99164, USA
USDA ARS Grain Legume Genetics and Physiology Research Unit, Washington State University,
Pullman, WA 99164, USA
e-mail: w-chen@wsu.edu
Y. Gherbawy and K. Voigt (eds.), Molecular Identification of Fungi,
DOI 10.1007/978-3-642-05042-8_4, # Springer-Verlag Berlin Heidelberg 2010
79
80
E.N. Njambere et al.
studies. These two examples demonstrate the important role of modern molecular
techniques in solving practical agricultural problems. The ITS and adjacent rDNA
could be ideal target regions for developing DNA barcodes for identifying these and
related fungal species.
4.1
Introduction
Cool season grain legumes (chickpea, Cicer arietinum; faba bean, Vicia faba;
lentil, Lens culinaris, and pea, Pisum sativum) are important crops worldwide.
They are staple food crops in West Asian and North African countries and are
important rotational and specialty crops in developed nations. Fungal diseases are
important constraints in grain legume productions. Accurate identification of the
fungal pathogens is in many cases a prerequisite for effective management of the
diseases they cause and for ecological and population genetics studies. However,
many fungal species are similar morphologically, and accurate species identification can be difficult. With current advances in biotechnology, molecular genetic
markers have been employed for rapid identification of different kinds of fungi
(White et al. 1990; Lieckfeldt and Seifert 2000; Njambere et al. 2008; Attanayake
et al. 2009). The development of gene-specific primers for PCR amplification
(White et al. 1990) has facilitated systematic studies, and the detection and
identification of fungal pathogens. The internal transcribed spacer (ITS) region
of nuclear ribosomal DNA has generally been considered a convenient marker for
molecular identification of fungi at species level because of its conserved feature
within species and multi-copy number per genome (Sanchez-Ballesteros et al.
2000). Henry et al. (2000) identified the fungus Aspergillus at species level and
differentiated it from other true pathogenic and opportunistic molds using ITS 1 and
ITS 2, allowing for early diagnosis and screening of effective antifungal agents for
patients. Schneider et al. (1997) developed a method for detection of Rhizoctonia
solani isolates, pathogenic and nonpathogenic to tulips, using ITS rDNA sequences,
and they could further identify various anastomosis groups. Recent advancement in
identifying fungal species using DNA markers is to develop DNA barcodes using
species-specific oligonucleotides that are diagnostic of targeted species (Druzhinina
et al. 2005). Such specific DNA regions need to be explored for different groups of
fungi. In this chapter, we present two examples of applying molecular techniques in
identifying fungal pathogens of cool season grain legumes.
4.2
Sclerotinia Stem Rot of Chickpea
Sclerotinia stem rot (Fig. 4.1a) is an important disease of chickpea under conducive
environmental conditions and is caused by three species of Sclerotinia: S. sclerotiorum, S. minor, and S. trifoliorum (Bretag and Mebalds 1987). Sclerotinia minor
4 Applications of Molecular Markers and DNA Sequences
81
Fig. 4.1 Symptoms and signs of Sclerotinia stem rot of chickpea caused by Sclerotinia trifoliorum
(a), and powdery mildew of lentil caused by Erysiphe trifolii (b)
can be easily differentiated from the other two species based on its numerous,
scattered small-sized sclerotia in culture and in the field. Morphological difference
between S. sclerotiorum and S. trifoliorum is subtle. The ultimate differentiation
between S. sclerotiorum and S. trifoliorum requires observation of ascospore morphology which entails carpogenic germination of sclerotia. Ascospores of S. trifoliorum show spore-size dimorphism (two different-sized ascospores within a single
ascus), whereas ascospores of S. sclerotiorum show no dimorphism (Kohn 1979;
Uhm and Fujii 1983a, b). Induction of carpogenic germination of sclerotia of
Sclerotinia spp. is a time-consuming process, and may take up to several months.
To further complicate the matter, some isolates of S. trifoliorum are heterothallic and
require mating with a compatible strain for carpogenic germination and ascospore
production (Uhm and Fujii 1983a, b). Even though the process of identifying
members of the genus Sclerotinia through sclerotia and other morphological characteristics has been refined over time (Kohn 1979; Rehnstrom and Free 1993), there
are limitations to this approach. For instance, the differentiation of S. trifoliorum
from S. sclerotiorum based on sclerotial characteristics is difficult because of instability of some sclerotia characteristics with subsequent sub-culturing (Cother 1977).
Therefore, to facilitate the separation of the two species, research efforts have
been made in searching for molecular techniques that are reliable and convenient to
use. Power et al. (2001) reported that S. trifoliorum contains group I introns in the
nuclear small subunit rDNA, whereas S. sclerotiorum and S. minor do not contain
any introns in the same DNA region. Molecular analysis of the ITS region can
eliminate many of the problems associated with the morphological characters and
culturing. Analysis of ITS sequence is usually applied to determine species identity
(or sometimes higher taxonomic categories) and to identify and discriminate
populations within a species. In the genus Sclerotinia, the ITS region is generally
not sufficiently variable to distinguish within species diversity; however, the
nuclear small subunit rDNA (nSSRrDNA) has been used for this type of study
(Holst-Jensen et al. 1999; Power et al. 2001). In this study we explored the
differences in the ITS and the nuclear small subunit regions of the rDNA between
the two species causing Sclerotinia stem rot of chickpea.
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4.2.1
E.N. Njambere et al.
DNA Isolation and ITS Sequence Analysis
DNA was isolated from mycelial mats or sclerotia using the standard extraction
procedures such as the FastDNA1 kit described by Chen et al. (1999). DNA
quality was checked using agarose gel electrophoresis and quantified using the
NanoDropTM spectrophotometer (NanoDrop Technologies, LLC, Wilmington,
Delaware, USA) and the concentration adjusted accordingly before PCR amplification. In our study PCR amplifications were conducted using primers ITS1 and ITS4
described by White et al. (1990). The PCR products were verified by agarose gel
electrophoresis and purified for direct PCR sequencing using ABI PRISM 377
automatic sequencer (Applied Biosystems, Foster City, CA, USA). Sometimes
the PCR fragments are cloned before sequencing. Sequences were determined on
both strands for each of the isolates and were aligned for comparison. Most
sequence comparisons are carried out using BLASTn (http://www.ncbi.nlm.nih.
gov/BLAST) analysis which aligns two or more homologues to detect for presence
of one or more ambiguous region within the segments under comparison. Using
nine isolates from S. slerotiorum and S. trifoliorum, we amplified a 540 bp DNA
fragment of the ITS region (Njambere et al. 2008). Sequence alignment among the
nine isolates identified two single nucleotide polymorphic sites (SNPs) within this
homologous region that differentiated the two groups of isolates. The two SNPs
were located at position 120 (transversion T ! G) and position 376 (transition
T ! C) of the amplicon. Three sequences of the isolates were deposited in the
GenBank and assigned accession numbers EU082464, EU082465, and EU082466.
BLASTn analysis of the ITS locus of some of the chickpea isolates (including
EU082464, EU082465) displayed 100% homology to ITS locus of S. trifoliorum in
the GenBank, whereas the ITS region of the other isolates (including EU082466)
were identical to GenBank S. sclerotiorum isolates. These results therefore suggest
that these two SNPs could be used as markers to separate S. sclerotiorum from
S. trifoliorum. Although the ITS sequences allowed differentiation between
S. sclerotiorum and S. trifoliorum, this technique is not convenient for routine
identification because it requires DNA sequencing.
4.2.2
Detection of Group I Introns
Group I introns are ribozymes (RNA enzymes) that catalyze chemical reactions,
splicing themselves off of their precursors. Group I introns are widely distributed in
bacteria, lower eukaryotes, and higher plants. They can be found in genes encoding
for rRNA, mRNA, and tRNA, but seem only in rRNA genes in the nuclear genome
of lower eukaryotes. No biological functions are known for the group I introns
except for splicing themselves off the primary transcripts. Although group I introns
are known to spread from location to location and from one organism to another in
evolutionary time, they are quite stable and their locations are highly conserved.
Thus, if differences in existence of group I introns are found between two species,
4 Applications of Molecular Markers and DNA Sequences
83
the introns provide convenient markers for separation of the species because they
can be easily detected through PCR and agarose gel electrophoresis. That is the case
for Sclerotinia spp.
It was reported by Power et al. (2001) that S. trifoliorum contains group I introns
in the nuclear small subunit rDNA, whereas S. sclerotiorum as well as S. minor does
not contain group I introns in the same DNA region. We applied this knowledge in
identifying S. trifoliorum from twelve isolates collected from chickpea plants. PCR
amplifications were done using primer pairs ITS5/ITS4 and NS3/NS6 (White et al.
1990) in an attempt to detect presence or absence of introns in the nuclear small
subunit regions of the rDNA. The reaction conditions were identical to those
described above for PCR amplification of the ITS region. One or more group I
introns were detected in all isolates of S. trifoliorum, and no group I introns were
observed at any isolates of S. sclerotiorum (Fig. 4.2). Amplification with PCR can
facilitate detection of the group 1 introns using PCR primer flanking the introns.
Isolates with introns produce larger PCR products than isolates without introns,
which can be easily detected using agarose gel electrophoresis (Fig. 4.2).
To be certain that the isolates harboring the group I introns are indeed
S. trifoliorum, nine isolates were selected and induced to germinate carpogenically
using a method as previously described (Njambere et al. 2008). For the isolates that
germinated carpogenically, all the isolates that harbored introns in the rDNA region
produced dimorphic ascospores, the ultimate criterion of identifying S. trifoliorum
(Fig. 4.3). These confirmatory tests suggest that the group I introns in the rDNA
region could be used for a quick and accurate identification of S. trifoliorum at
Fig. 4.2 Agarose gels of PCR amplification of the ITS and the nuclear small subunit rDNA regions
of Sclerotinia spp. PCR products with primer pairs ITS1 and ITS4 (top) are monomorphic in size
(no introns), whereas PCR products with primers ITS4 and ITS5 (bottom) are polymorphic in size
(due to presence of introns). The lanes 1, 4, 5, and 11: S. sclerotiorum isolates (without introns);
Lanes 2, 3, 6, 7, 8, 9, 10, and 12: S. trifoliorum (with introns)
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E.N. Njambere et al.
Fig. 4.3 Ascospore morphology of Sclerotinia trifolorium (a and b) showing size dimorphism,
and of S. sclerotiorum (c) showing no size dimorphism
species level. We have employed this technique in identifying more than 100
isolates of S. trifoliorum for population genetic studies.
4.3
Powdery Mildew of Lentil
Powdery mildew is a plant disease caused by many different species of fungi in the
order Erysiphales (Glawe 2008). The disease occurs in a wide range of plants. Its
symptoms are very distinctive, powdery like spots on leaves and stems. The disease
can reduce the yield and quality of many crops and commercial values of ornamental plants. In the field crop lentil, it can be a severe disease on certain cultivars and
in some parts of the world, particularly in India during January to February
(Agrawal and Prasad 1997). Although lentil is a field crop, breeding materials
and many experimental plants are produced in greenhouses. Powdery mildew is a
persistent disease problem of lentil plants in greenhouses (Beniwal et al. 1993), and
poses a threat to precious breeding materials such as F1 plants. Infections by
powdery mildews typically result in small white colonies on leaf surfaces
(Fig. 4.1b). Lesions expand to cover entire leaf surfaces and pods. Mycelial growth
and conidial production can be especially extensive at flowering. In case of severe
4 Applications of Molecular Markers and DNA Sequences
85
infections, leaves become chlorotic, then curled and necrotic prior to abscission.
Yield decline may result and plants sometimes die (Agrawal and Prasad 1997).
Even though powdery mildew symptoms are easily recognized, identification of
the species that causes the disease could be problematic (Glawe 2008). Knowing
the species identity is important in devising management strategies as different
species have different host ranges and different life histories. Identification of
powdery mildew fungi relies on morphology of reproductive structures. Powdery
mildews reproduce sexually by forming sexual structure chasmothecia (teleomorph) and asexually through conidia (anamorph). Traditional belief is that morphology of teleomorphs is more reliable than morphology of anamorphs.
Taxonomy of powdery mildews of legumes is traditionally based on a few teleomorphic features, including chasmothecial appendage morphology (Braun 1995;
Braun 1987) and host range. Powdery mildew pathogens that produce chasmothecia
with multiple asci and dichotomously branched chasmothecial appendages were
grouped into the genus Microsphaera, while otherwise similar, mycelioid appendagebearing species were classified within the genus Erysiphe (Braun 1987).
However, recent phylogenetic studies of powdery mildew fungi using ribosomal
DNA sequences demonstrated that anamorphic features are more indicative of
phylogenetic lineages than are teleomorphic features, and that anamorphic characters are of utility in species determination (Braun and Takamatsu 2000; Cunnington
et al. 2003; Glawe 2008). Chasmothecial appendages traditionally used to distinguish genera are now used to distinguish species (Braun and Takamatsu 2000).
However, teleomorphic state is not always available and most of the time it forms
when plants are senescent late in the growing season or does not form at all. It
prevents timely detection and identification of the pathogen species. Even though
abundant conidia are produced early in the disease development, there are only few
anamorphic characters available (such as morphology and dimensions of conidia
and conidiophores) to describe species and most of them overlap among closely
related species. For example, conidia shape and sizes of E. pisi and E. trifolii are
very similar and overlap considerably. Likewise, it is not reliable to use host ranges
to identify powdery mildew species because many of them have broad and overlapping host ranges (Amano 1986).
Accurate determination of the pathogen species is very important not only for
managing the disease, but also in plant breeding programs because different
resistance genes may confer resistance to different pathogen species (Epinat et al.
1993). In some instances several powdery mildew species have been reported to
occur together on the same host (Epinat et al. 1993; Glawe et al. 2004; Mmbaga
et al. 2004).
Recent advances in molecular techniques have made it possible to investigate
the species level identification of lentil powdery mildew pathogens. Use of molecular characters, especially ITS sequence data, has given promising results for
species determination in some powdery mildews (Braun and Takamatsu 2000;
Cunnington et al. 2003; Mmbaga et al. 2004; Takamatsu et al. 2002).
Powdery mildew of lentil is reported to be caused by two Erysiphe species, E. pisi
(Amano 1986), a common pathogen of pea, and E. diffusa (Banniza et al. 2004), a
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E.N. Njambere et al.
Fig. 4.4 Chasmothecium and its appendages of E. trifolii formed on an infected lentil plant.
Highly branched chasmothecial appendages (a) and long flexuous nature of the chasmothecial
appendages (b)
pathogen of soybean. The two species differ in conidia sizes. E. pisi produces
conidia larger than those of E. diffusa. The major difference between the two species
is that E. diffusa produces chasmothecial appendage with highly branched apices,
whereas E. pisi produces mycelioid appendages. Powdery mildew is a frequent and
serious disease of lentil plants in our greenhouses, but the species identity is not
known. We observed that the conidia sizes larger than those described for E. diffusa.
However, it produced chasmothecial appendages with regularly branched apices
(Fig. 4.4), raising the possibility that it could be E. diffusa. The contradiction
between the anamorphical characters and the teleomorphic characters gave confusion about the species identity. In order to ascertain the species identity of the
powdery mildew fungus on lentil plants, we analyzed sequences of rDNA ITS
region which led to the discovery of a new species of lentil powdery mildew.
4.3.1
Sample Collection and DNA Sequencing
Four samples of powdery mildews were collected from three different greenhouses
over a 3-year period and an additional sample from the field was included in this
study. Because E. diffusa is also a suspect species, a sample of E. diffusa from wild
soybean (Glycine spp., kindly provided by Dr. Randall Nelson of USDA ARS,
Urbana, Illinois, USA) was also included for comparison. Total DNA was isolated
from conidia and/or mycelia from infected lentil plants using FastDNA1 kit
described by Chen et al. (1999). PCR amplification of the ITS region from each
sample was performed using the primers ITS1 and ITS4 (White et al. 1990), or
4 Applications of Molecular Markers and DNA Sequences
87
Erysiphe- specific primers that we designed on the basis of conserved sequences of
the ITS region of Erysiphe spp., EryF (50 TACAGAGTGCGAGGCTCAGTCG30 )
and EryR (50 GGTCAACCTGTGATCCATGTGACTGG30 ) (Attanayake et al.
2009). Amplified DNA fragments were first cloned into plasmid pCR2.1TOPO
(Invitrogen Crop, Calsbad, CA). Plasmids containing inserts were verified by
restriction digestion. The inserts were sequenced from both strands using one of
the six primers: EryF, EryR, ITS1, ITS4, M13F, and M13R at the Sequencing Core
Facility of Washington State University.
4.3.2
Sequence Analysis
All the ITS sequences of lentil powdery mildews collected from greenhouses and
the field used in this study were identical to one another, but they differed in 18
nucleotide positions from the sequence of E. diffusa from a wild soybean Glycine
sp. (Fig. 4.5). Sequences were used in BLASTn searches against the GenBank
database (http://www.ncbi.nlm.nih.gov/BLAST) to identify the most similar
sequences available in the database. The sequences in the GenBank that showed
the highest similarity (one base-pair difference) to the lentil powdery mildew
sequence were three identical sequences (AB079853 to AB079855) of E. trifoliilike Oidium sp. from Japan (Okamoto et al. 2002). The sequences in the GenBank
that showed the next highest similarity (three base pair differences) were five
identical sequences (e.g., AB015913 and AF298542) of E. trifolii (Cunnington
et al. 2003; Matsuda et al. 2005; Takamatsu et al. 1999), and another sequence
(AB015933) of E. baeumleri (Takamatsu et al. 1999). The ITS sequence of the
powdery mildew sample from wild soybean was identical to deposited sequences of
E. diffusa in the GenBank.
Sequence accessions with high similarity values to the sequences determined in
this study were aligned using the ClustalW program and used in phylogenetic
analysis using the DNA Parsimony program of the PHYLIP package at http://
bioweb2.pasteur.fr/phylogeny/intro-en.html. Parsimony analysis produced one
most parsimonious tree with 113 steps. The sequence of lentil powdery mildew
formed a tight cluster (monophyletic group) with sequences of Erysiphe baeumleri,
E. trifolii, and E. trifolii- like Oidium spp., and is distantly related to (paraphylectic)
E. diffusa. Another powdery mildew sequence from wild soybean specimen, also
incorporated in this study, formed a separate clade with E. diffusa sequences in the
GenBank.
4.3.3
Species Confirmation
As E. trifolii is not previously reported to be a pathogen of lentil, we needed to
ascertain that the powdery mildew fungus on lentil is indeed E. trifolii and that it is
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E.trifolii
E.diffusa
GCCGACCCTCCCACCCGTGTCGATTTGTATCTTGTTGCTTTGGCGGGCCGGGCCGCGTCG 60
GCCGACCCTCCCACCCGTGTCGATTTGTATCTTGTTGCTTTGGCGGGCCGGGCCGCGCTG 60
********************************************************* *
E.trifolii
E.diffusa
TCGCTGTTCGCAAGGACCTGCGTCGGCCGCCCACC-GGTTTTGAACTGGAGCGCGCCCGC 119
TTGCAGTCCGCATGGACATGCGTCGGCCGCCCCCCCGGTGTTCCACTGGAGCGCGCCCGC 120
* ** ** **** **** ************** ** *** ** ****************
E.trifolii
E.diffusa
CAAAGACCCAACCAAAACTCATGTTGTTTGTGTCGTCTCAGCTTTATTATGAAAATTGAT 179
CAAAGACCCAACCAAAACTCATGTTGTTTGTATCGTCTCAGCTTTATTATGAAAATTGAT 180
******************************* ****************************
E.trifolii
E.diffusa
AAAACTTTCAACAACGGATCTCTTGGCTCTGGCATCGATGAAGAACGCAGCGAAATGCGA 239
AAAACTTTCAACAACGGATCTCTTGGCTCTGGCATCGATGAAGAACGCAGCGAAATGCGA 240
************************************************************
E.trifolii
E.diffusa
TAAGTAATGTGAATTGCAGAATTTAGTGAATCATCGAATCTTTGAACGCACATTGCGCCC 299
TAAGTAATGTGAATTGCAGAATTTAGTGAATCATCGAATCTTTGAACGCACATTGCGCCC 300
************************************************************
E.trifolii
E.diffusa
CTTGGTATTCCGAGGGGCATGCCTGTTCGAGCGTCATAACACCCCCTCCAGCTGCCTTTG 359
CTTGGTATTCCGAGGGGCATGCCTGTTCGAGCGTCATAACACCCCCTCCAGCTGCCATTG 360
******************************************************** ***
E.trifolii
E.diffusa
TGTGGCTGCGGTGTTGGGGCACGTCGCGATGCGGCGGCCCTTAAAGACAGTGGCGGTCCC 419
TGTGGCTGCGGTGTTGGGGCTCGTCGCGATGCGGCGGCCCTTAAAGACAGTGGCGGTTCC 420
******************** ************************************ **
E.trifolii
E.diffusa
GGCGTGGGCTCTACGCGTAGTAACTTGCTTCTCGCGACAGAGTGACGACGGTGGCTTGCC 479
GACGTGGGCTCTACGCGTAGTAACTTGCTTCTCGCGACAGAGTGACGACGGTGGCTTGCC 480
* **********************************************************
E.trifolii
E.diffusa
AGAACACCCCTCTTTTGCTCCAGTCACATGGATCACAGGTTGACC 524
AGAACAACCCTCTTTTGCTCCAGTCACATGGATCACAGGTTGACC 525
****** **************************************
Fig. 4.5 Alignment of ITS sequences of E. trifolii and E. diffusa determined in this study. An
asterisk indicates an identical base pair. There are 18 base-pair differences between the two
sequences. The E. trifolii sequence is > 99% similar to previously deposited sequences of
E. trifolii in GenBank, and the E. diffusa sequence is identical to previously deposited E. diffusa
sequences in GenBank
pathogenic on lentil. Three experiments were carried out to confirm that the
powdery mildew pathogen of lentil in the US is E. trifolii, and not E. diffusa.
First, conidia of E. trifolii were collected from lentil and used in a detached leaf
assay to determine the pathogenicity on lentil under controlled conditions. Second,
an authentic species of E. trifolii was obtained and compared with the samples from
lentil in the US. The experiment showed that E. trifolii does produce long flexuous
chasmothecial appendages with regularly branched apices similar to lentil samples
(Fig. 4.4a, b). Finally, as E. diffusa is a common pathogen of soybean, soybean
genotypes “L84-2237” and “Harosoy” known to be susceptible to E. diffusa were
inoculated with conidia of powdery mildew from lentil and grown side by side with
infected lentil plants in the greenhouse. The lentil powdery mildew did not infect
soybean plants during the entire life cycle of soybean. These evidences strongly
support the conclusion that the powdery mildew pathogen found on lentil in US was
E. trifolii (Attanayake et al. 2009).
4 Applications of Molecular Markers and DNA Sequences
89
Powdery mildews of plants in the Fabaceae are very complex and have begun to
receive more and more attention. Further taxonomic studies are needed because
E. trifolii has been regarded as a complex of similar species consisting of E. trifolii,
E. baeumleri Magn., and E. asteragali DC. (Braun 1987). The nature of this
complex needs to be verified.
4.4
Conclusions
Modern molecular techniques have been used for identifying fungi in a wide array of
biological science disciplines. In this chapter, we presented two specific examples of
how molecular techniques have helped solve practical problems in identifying fungal
pathogens of cool season grain legumes. In one case, we used molecular markers
(group I introns and ITS sequences) to differentiate S. trifoliorum from a more
common and closely related species S. sclerotiorum. This technique of identification
allowed us to determine the species identity without the time consuming process of
inducing carpogenic germination and ascospore observation. This technique allowed
us to identify more than 100 isolates for studies in population genetics of S. trifoliorum. In the second example, using rDNA ITS sequences we were able to identify a
new pathogen (E. trifolii) of powdery mildew of lentil. There were some ambiguities
in determining the species because the morphology of teleomorph resembled a
previously reported species (E. diffusa), but the anamorph is clearly different from
E. diffusa. By comparing ITS sequences, examining an authentic specimen of
E. trifolii and conducting pathogenicity test of a common host of E. diffusa, we
unequivocally determined that the lentil powdery mildew was caused by E. trifolii.
In doing so, we actually broadened the taxonomical concept of the species E. trifolii
to include regularly branched chasmothecial appendages. Using these two examples,
we have shown that modern molecular technology plays an important role and has
gained increasing widespread applications in solving practical problems in agriculture. Furthermore, similar to what was found in species of Trichoderma and Hypocrea (Druzhinina et al. 2005), our results showed that the ITS region and the adjacent
rDNA could be ideal candidate DNA regions used for developing DNA barcodes for
identifying these and related fungal species.
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Cunnington JH, Takamatsu S, Lawrie AC, Pascoe IG (2003) Molecular identification of anamorphic powdery mildews (Erysiphales). Australas Plant Pathol 32:421–428
Druzhinina I, Kopchinskiy AG, Komon M, Bissett J, Szakacs G, Kubicek CP (2005) An oligonucleotide barcode for species identification in Trichoderma and Hypocrea. Fungal Genet Biol
42:813–828
Epinat C, Pitrat M, Bertrand F (1993) Genetic analysis of resistance of five melon lines to powdery
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Glawe DA (2008) The powdery mildews: a review of the world’s most familiar (yet poorly known)
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Holst-Jensen A, Vaage M, Schumacher T, Johansen S (1999) Structural characteristics and
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pp 315–322
Chapter 5
Quantitative Detection of Fungi by Molecular
Methods: A Case Study on Fusarium
Kurt Brunner and Robert L. Mach
Abstract The determination of fungal biomass in diverse samples plays a key role
for questions in the fields of plant pathology and agriculture. Until a decade ago,
morphological strain determination and quantification by agar-plating methods
were the only techniques to quantify fungal infections. These methods were elaborate and time consuming and the obtained results might not always reflect the
biological situation. At the end of the 1990s, numerous groups all over the world
started with the molecular characterization of the genus Fusarium and defined
several diagnostic sequences in the genome of the most prominent Fusarium
species as suitable for the discrimination of isolates. Based on these characteristic
sequences originally applied for taxonomic studies, quantitative PCR assays were
developed from the turn of the millennium until now. PCR tests for certain species
were also developed as well as tests for whole groups producing a particular class of
toxins. Until now real-time PCR based Fusarium determinations are applied predominantly in niches in agro-biotechnology. However, to further disseminate the
inexpensive and rapid quantitative PCR, the quality of analysis has to be guaranteed
by defining several standards concerning the PCR procedure from DNA isolation to
data analysis. Additionally, plant breeders and agronomists are familiar with toxin
analysis and visual rating systems. So change in people’s mind is necessary to
realize the benefits of a novel technique.
5.1
Introduction
Fungi of the genus Fusarium are worldwide occurring plant pathogens which
cause severe damage to numerous cultivable plants (Weiland and Sundsbak 2000;
Mirete et al. 2004; Youssef et al. 2007; Li et al. 2008) with the highest economical
K. Brunner and R.L. Mach
Institute of Chemical Engineering, Research Area Gene Technology and Applied Biochemistry,
Gene Technology Group, Vienna University of Technology, Getreidemarkt 9, A-1060, Vienna
e-mail: rmach@mail.zserv.tuwien.ac.at
Y. Gherbawy and K. Voigt (eds.), Molecular Identification of Fungi,
DOI 10.1007/978-3-642-05042-8_5, # Springer-Verlag Berlin Heidelberg 2010
93
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K. Brunner and R.L. Mach
losses upon infection of maize, wheat, and barley (Windels 2000; Nganje et al.
2004). Fusarium-caused diseases have the potential to destroy crops within several
weeks and lead to quality losses in grains in two separate ways: besides the deficit
due to reduced yield and kernel size (tombstone kernels), the fungus produces
numerous toxic metabolites while colonizing the plant and thereby heavily impairs
the quality of cereal grains used for the food and feed industry (Marcia McMullen
et al. 1997). The acute or chronic toxicity of Fusarium-released compounds led to
the introduction of national limits for mycotoxins in many nations or even to
supranational applications of regulations (e.g., limits of the European Community
since 2006).
Integrated control strategies are indispensable to fight Fusarium diseases in
modern agriculture and only the combined effect of (1) planting highly resistant
varieties, (2) reasonable crop rotations, and (3) suitable tillage systems can minimize the damages caused by this destructive fungus. Although the knowledge
about the Fusarium life-cycle and infection paths increased dramatically, biologic
difficulties and economic or ecologic interests prevent achieving sustainable success in controlling these pathogenic fungi: throughout the last decade, plant
breeders made substantial progress in the development of Fusarium-tolerant
maize and wheat cultivars by identifying genetic regions which are linked to the
resistance of plants (Anderson et al. 2001; Medianer 2006; Robertson-Hoyt et al.
2006). However, the resistance against Fusarium is spread over several distinct
genetic regions (quantitative trait loci, QTLs) in the plant genome and the breeding
of highly resistant plants is elaborate and time-consuming. The severity of infections due to the nonavailability of completely resistant plants is further increased
by applying unsuitable cropping systems. The influence of crop rotations on the
severity of Fusarium head blight was investigated in several studies (Petcu and
Ionibã 1998; Reid et al. 2001) and the economically most lucrative cultivation of
alternating maize and wheat specially turned out to be problematic. Fusarium
nonhost plants as preceding crops of wheat and maize or as intercrops are often
less profitable and thereby of low interest to farmers. Erosion causes a dramatic
loss of fertile topsoil, especially in North and South America, and no-till systems
have been established in endangered areas to overcome the drawback of conventional farming. Although reduced tillage systems prevent the loss of topsoil,
Fusarium inoculum density in the soil increases compared to plow treated fields
(Steinkellner and Langer 2004). According to the data of the United Nations
Food and Agriculture Organization, more than 250,000 km2 of US farmland are
cultivated with no-till methods, closely followed by Brazil, Argentina, and Canada.
In addition to the above mentioned factors other uncontrollable factors like the
weather conditions at time periods crucial for infections play a key role in affecting
the produce. Due to these complex interacting criteria no management systems
could be established allowing a complete prevention of Fusarium infection of field
crops to avoid mycotoxins in the food and feed chain. As the Fusarium problem in
agriculture is not supposed to be overcome within the near future, elaborate
monitoring programs have been started in many countries with the aim of observing mycotoxin patterns and fungal population dynamics in selected areas.
5 Quantitative Detection of Fungi by Molecular Methods: A Case Study on Fusarium
95
The traditional method used to isolate and characterize fungi is the cultivation on
particular media and microscopic investigations. These conventional identification
methods are very time-consuming and have to be performed by skilled personnel to
prevent incorrect identification and data interpretation. Moreover, conventional
methods used for fungal detection are predominantly semi quantitative by determining the colony forming units from surface sterilized grains plated on particular
solid media (Cantalejo et al. 1998; Krysinska-Traczyk et al. 2007). To overcome
the drawbacks of culture based identifications, throughout the last decade rapid
screening technologies based on DNA identification have been developed and are
nowadays well established for Fusarium species. In contrast to conventional detection methods, samples can be tested directly without any elaborate isolation and
cultivation steps for a proper classification. These novel identification or discrimination methods include PCR based technologies like DGGE, AFLP, or RFLP and
also diagnostic microarrays. All these methods are relatively insensitive to microbial backgrounds and non target organisms.
5.2
Quantification Strategies
The broad application of DNA-based identification technologies increased the
knowledge on diagnostic DNA fragments of Fusarium species: ITS or IGS
sequences (Mishra et al. 2003; Gagkaeva and Yli-Mattila 2004; Konstantinova
and Yli-Mattila 2004; Mirete et al. 2004; Yli-Mattila et al. 2004a, b; Jurado et al.
2006; Kulik 2008), mitochondrial DNA (Láday et al. 2004a, b), the b-tubulin
encoding gene (Gagkaeva and Yli-Mattila 2004; Mach et al. 2004; Yli-Mattila
et al. 2004b), the translation elongation factor gene (Knutsen and Holst-Jensen
2004), and the calmodulin gene (Mulè et al. 2004) were sequenced from numerous
Fusarium spp. to allow the design of highly specific PCR primers. On the other
hand, the genes from biosynthesis pathways for mycotoxins (Niessen and Vogel
1998; Bakan et al. 2002; Lee et al. 2001; González-Jaén et al. 2004; Nicholson et al.
2004; Bezuidenhout et al. 2006; Baird et al. 2008) were studied accurately to
distinguish between producers and nonproducers of certain toxins.
The sequence information gained throughout the different molecular taxonomic
investigations and population studies forms a broad basis not only for qualitative
applications but increasingly for quantitative detection methods. Although different
techniques like DGGE, RFLP, and AFLP were applied for the qualitative identification of targets, only the real-time PCR tended to be practicable for quantitative
detection methods.
5.2.1
Competitive PCR
The first steps toward Fusarium quantification were made around 2000. As realtime PCR technique was still in its infancy, competitive PCR was a common tool to
gain information on initial amounts of target DNA in samples.
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K. Brunner and R.L. Mach
Nicholson et al. (1998) designed primer pairs specific to either F. graminearum
or F. culmorum from RAPD analysis and optimized the reaction for competitive
quantification. The F. culmorum species-specific competitive PCR assay was used
to study the effect of inoculum load and timing on stem base disease of winter
wheat caused by F. culmorum. The extent of fungal colonization, as measured by
fungal DNA content, was greater on plants inoculated earlier in the season and
increased with increasing conidial load. The F. graminearum-species specific
competitive PCR assay was used to study the colonization of wheat grain by
different trichothecene producing and nonproducing isolates of F. graminearum.
Edwards et al. (2001) were the first to quantify toxin producing Fusarium
species based on the presence of a diagnostic fragment of a key gene for trichothecene biosynthesis. The trichodiene synthase encoding gene tri5 is essential for the
first step in trichothecene synthesis and is found only in toxin producing strains. The
authors demonstrated a good correlation (r2 = 0.76) between the deoxynivalenol
(DON) concentrations in winter wheat and the competitive PCR determined fungal
biomass. In contrast to visual ratings which do not frequently correlate which DON
concentrations (Hussein et al. 1991), the PCR method turned out to be suitable as a
rapid test for toxin concentration. The competitive PCR technique was applied
to test the efficiency of seven different fungicides for their potential to reduce
Fusarium biomass if compared to untreated controls.
5.2.2
Real-Time PCR
With the availability of reliable and affordable real-time PCR cyclers this novel
technique found its way into the quantitative detection of plant pathogens including
numerous Fusarium species. Real-time PCR has several advantages over competitive PCR: the dynamic range of real-time PCR is usually five to six orders of
magnitude rather than two for competitive assays. Furthermore, postreaction processing like gel electrophoresis is unnecessary and thereby the real-time detection
of fluorescence saves time and a higher throughput is possible. By using probes
with different fluorescent reporter dyes, amplification of more PCR products can be
used to detect different strains, polymorphisms, or even single point mutations in a
single tube. For the quantification of Fusarium in general, two different approaches
for the design of specific qPCR assays were chosen: (1) the determination of one
particular Fusarium species with a focus on selectivity to allow the quantification of
the target even in a background of highly similar isolates, and (2) the simultaneous
quantification of all strains which produce certain toxins like trichothecenes or
fumonisins, based on genes involved in the biosynthesis of these metabolites.
5.2.2.1
Species Specific Quantification
Reischer et al. (2004) developed a TaqMan based PCR assay for F. graminearum
which is the most prevalent species found in moderate climate zones. The method
5 Quantitative Detection of Fungi by Molecular Methods: A Case Study on Fusarium
97
targets the b-tubulin encoding gene tub1 which was isolated from nine Austrian
F. graminearum isolates and the sequence was aligned with 144 tub1 sequences
from the closely related species F. culmorum, F. poae, F. pseudograminearum,
F. sporotrichioides, F. cerealis, and F. lunulosporum to guarantee the specificity of
the test. The method developed in this study allows a fast, species-specific identification and quantitation of plant-infections by F. graminearum at very early stages
where classical microbiological methods failed to detect the pathogen. The authors
demonstrated that five copies of the tub1 gene were sufficient for reliable quantification. The method can be applied on DNA extracted directly from infected plant
material and is not affected by any unspecific background of either plant or fungal
DNA, even from other pathogens causing head blight.
Other TaqMan-based species specific PCR assays were developed for F. graminearum, F. poae, F. culmorum, or F. avenaceum (Waalwijk et al. 2004), the
predominant species associated with head blight in Europe. The applied primer
pairs were designed from RAPD fragments previously developed (Nicholson et al.
1998) or taken from a previous study (Waalwijk et al. 2003). For all species, the
level of quantification was below 1 pg of genomic DNA (what corresponds to 25
fungal genomes) and all assays showed a dynamic range of at least four magnitudes.
Based on these quantitative tests, a comprehensive monitoring of the Fusarium
community in the Netherlands was performed in 2001 and 2002. Forty wheat fields
well distributed all over the country were chosen for analysis and most samples
turned out to be infected with a mix of different Fusarium species with F. graminearum occurring as the most prominent one. The authors clearly demonstrated the
advantage of reliable PCR systems combined with a high-throughput DNA extraction method over morphologic based monitoring. In contrast to conventional agarplating techniques, the different fungal species can be quantified and usually the
analyses are less time-consuming. In general, the PCR results and the data obtained
by classic microscopy were quite similar but significant discrepancies were
observed for several samples. The authors suppose that these differences were
due to the major advantage of DNA based detection methods: the high stability
of DNA allows detection of the fungal biomass that was produced during the
infection of a kernel, irrespective of whether it stems from live or dead cells.
Agar plate-based investigations depend on intact organisms for successful detection. Interestingly, in this study a nonlinear correlation between the fungal DNA
and the DON content of samples was observed, which is in contrast to other
publications (Schnerr et al. 2002; Fredlund et al. 2008; Yli-Mattila et al. 2008).
However, this effect might also result from low extraction efficiencies of the weak
infected kernels.
Another quantitative PCR assay has been developed recently to quantify Fusarium solani (Li et al. 2008), a soil-borne fungus that infects soybean roots and causes
sudden death syndrome. The goal of this study was to develop a real-time quantitative assay to compare the accumulation of genomic DNA among 30 F. solani
isolates in inoculated soybean roots. The small subunit of the ribosomal RNA
gene was chosen as PCR target and a dual labeled TaqMan probe was designed
to ensure the specificity of the method. The authors demonstrated the correlation
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K. Brunner and R.L. Mach
between colony forming units and DNA amount in infected root tissue. This qPCR
approach provides useful information for evaluating the aggressiveness of isolates
based on the degree of colonization on soybean roots and for selecting F. solani
resistant soybean lines.
A comprehensive study on real-time PCR detection of different Fusarium
species was published only recently (Yli-Mattila et al. 2008). Quantitative tests
for F. graminearum and F. poae were developed and the correlation of fungal
biomass to the production of certain toxic metabolites was demonstrated. F. poae
and F. langsethiae are morphologically almost indistinguishable but the two fungi
produce a different spectrum of toxins and thereby microbiologic infection studies
can easily lead to misestimating the toxin content of samples. Primers were
designed based on a worldwide sequence collection of IGS sequences of F. poae,
F. sporotrichioides, F. langsethiae , and F. kyushuense isolates to exclusively
amplify the F. poae fragment. Selective primers for F. graminearum were obtained
from the sequences of the IGS regions of Finnish F. graminearum isolates. Subsequently, the F. poae specific assay was designed for use in a quantitative multiplex
PCR together with a F. langsethiae/F. sporotrichioides specific primer and probe
combination. The application of multiplex PCR allows the quantification of all
strains in a single run and thus lowers the costs and increases the throughput of
analysis. To date this is the only published quantitative multiplex tests for Fusarium
species. Additionally, the authors included the tox5 assay (Schnerr et al. 2001) in
their monitoring study and compared the respective PCR results with microbiologic
determined contamination levels and the toxin content of cereal grains. A correlation was found between the levels of F. poae DNA and nivalenol and enniatins in
barley and between the levels of F. graminearum DNA and DON in oats. The
correlations between F. poae DNA and nivalenol and F. graminearum DNA and
DON levels were significantly higher than those between the mycotoxins and
morphologically determined Fusarium contamination levels.
5.2.2.2
Group Specific Quantification Based on the Detection of Toxin
Biosynthesis Genes
Frequently quantitative PCR tests are based on toxin biosynthesis key-genes as
targets for amplification. In contrast to the species specific assays, a whole group of
Fusarium spp. that is able to produce a certain class of mycotoxins is quantified in a
single run, regardless of their taxonomic belonging. For many applications these
types of PCR quantification might be of greater interest, as in general a good
correlation between fungal biomass and the toxins in a sample is given.
Most assays developed throughout the last decade focus on trichothecene producing species as this class of metabolites turned out to be most relevant for human
and animal health due to their acute toxicity. The biosynthetic pathway has previously been studied and one enzyme turned out to be a kind of key step for
biosynthesis of all trichothecenes. The trichodiene synthase catalyzes the initial
reaction to form trichodiene (Desjardins et al. 1993). The corresponding gene tri5 is
5 Quantitative Detection of Fungi by Molecular Methods: A Case Study on Fusarium
99
located together with ten other genes for this pathway within the trichothecene
cluster. This cluster is exclusively present in fungi with the capacity to produce
class A and/or class B trichothecenes (Desjardins et al. 1993). The fist tri5 real-time
PCR assay was published by Schnerr et al. (2001) with the tox5 primers which
were previously used for a group specific qualitative detection of toxin producers
(Mulfinger et al. 2000). The test was applied to 30 wheat samples with infections of
0–78% of the kernels. Interestingly, the PCR method showed a high correlation to
microbiological quantification of the infection by the plate counting method.
However, for several samples the detected Fusarium DNA was much higher or
lower than expected from the plate method. This effect is most probably due to the
problem that microbiological methods can only count the number of infected
kernels but give no hint of the severity of the Fusarium infection on a particular
kernel. The intriguing question of the correlation of Fusarium DNA and produced
toxins was further investigated in another study by the same authors (Schnerr et al.
2002). Three hundred wheat samples with DON concentrations between not detectable and 34.3 ppm were tested. Data analysis revealed a correlation coefficient of
0.96 between DON content and DNA amounts. In general the correlation appeared
to be better at higher infection levels. This might have biological reasons as certain
amounts of DON can be metabolized by the plants to DON-3-glucoside (Berthiller
et al. 2005) and/or the efficiency of the DNA extraction varies more at lower
Fusarium DNA-concentrations.
Strausbaugh et al. (2005) investigated the pathogenicity of Fusarium spp.
frequently isolated from wheat and barley roots in southern Idaho during four
growth-chamber experiments and two field studies. A real-time PCR assay for
quantifying the presence of F. culmorum from infected root tissue was developed
based on nucleotide sequence for the tri5 gene. In contrast to previous studies
(Schnerr et al. 2001, 2002) this test targeted highly variable regions of the tri5 gene
to allow specific F. culmorum tests. The TaqMan-based assay is able to quantify
F. culmorum in root tissue down to 61 pg of total extracted DNA. Nevertheless, as
the tri5 gene is highly conserved among the trichothecene producing strains, the
assay also detected F. pseudograminearum and F. graminearum and could not
distinguish between these three Fusarium species.
Besides the class of trichothecenes, some Fusarium species secrete another
threatening class of toxins. Especially in warmer climates the fumonisins produced
mainly by F. verticillioides and F. proliferatum are found on maize but rarely on
other cereals. The fumonisin biosynthetic genes are clustered (Proctor et al. 2003),
and one of these genes, fum1, encodes for a polyketide synthase and was found to be
indispensable for fumonisin biosynthesis (B18: Proctor et al. 1999). All quantitative
assays for fumonisin producers published up to now focused on the detection of
fum1. Bluhm et al. (2004) were the first researchers who used real-time PCR for the
group specific detection of fumonisin producers. Nevertheless, instead of proper
quantification, the assay was designed and applied to control a certain threshold
limit of these strains in barley and maize samples. Another fum1 based quantitative
PCR assay was used to study the contamination of more than 420 maize samples
from South African farms with fumonisin-toxigenic species (Waalwijk et al. 2008).
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Table 5.1 Overview of quantitative real-time PCR tests for Fusarium species
Target species
Diagnostic sequence
Reference
F. graminearum
tub1
Reischer et al. (2004)
F. avenaceum, F. culmorum,
RAPD-derived
Waalwijk et al. (2004)
F. graminearum, F. poae
F. solani
small subunit of
Li et al. (2008)
ribosomal RNA
F. graminearum, F. poae
IGS
Yli-Mattila et al. (2008)
tri5
Schnerr et al. (2001)
Trichothecene producers
F. culmorum, F. graminearum,
tri5
Strausbaugh et al. (2005)
F. pseudograminearum
fum1
Bluhm et al. (2004)
Fumonisin producers
fum1
Waalwijk et al. (2008)
Fumonisin producers
The TaqMan based test detected F. verticillioides, F. proliferatum, F. nygami, and
F. globosum. Notably, fumonisin nonproducers of F. verticillioides gave no response.
The PCR determined DNA amount was compared with the ELISA-based measurements of fumonisin content and a correlation coefficient of 0.87 demonstrated the potential of this method for estimating the toxin content. Table 5.1
shows a summary of previously published quantitative real-time PCR based tests
for various plant pathogenic Fusarium species.
5.2.3
DNA-Arrays
In many research areas microarray techniques gained a great deal of attention with
the growing amount of genetic information of genera and species. Microarrays
have the potential to rapidly identify DNA of different origin. In general, the
hybridization methods are applied as high throughput systems but the accuracy of
quantification is mostly low compared to real-time PCR analysis. A qualitative
oligonucleotide array for the differentiation of toxigenic and nontoxigenic Fusarium isolates was developed by Nicolaisen et al. (2005). Until now only a single
array based method for the quantitative detection of Fusarium species is available
(Kristensen et al. 2007). The capture-oligo sequences for several trichothecene or
moniliformin producing groups were designed based on the tef1 sequence and 15
species can be quantified in a single run. Three different capture-probes, each
spotted as triplets were included for each species to guarantee the specificity of
the assay. The Fusarium chip showed a linear response to diluted Fusarium DNA of
more than two magnitudes and the authors proposed a limit of quantification below
16 haploid Fusarium genomes. Barley, oat, wheat, and spelt samples were analyzed
morphologically for toxin content and for the species pattern using the array.
The results obtained by the novel hybridization method corresponded well with
the established analyzes. Although a dilution series was tested to demonstrate the
quantification capability of the microarray, all field samples were only tested for the
absence or presence of certain species.
5 Quantitative Detection of Fungi by Molecular Methods: A Case Study on Fusarium
5.3
101
Conclusion
The quantitative determination of fungal infections is a useful tool in plant pathology for obtaining information on the aggressiveness of different isolates (Li et al.
2008), for Fusarium monitoring in agricultural practice, for testing fungicide
efficiencies (Edwards et al. 2001) and has also been used for quality control of
wheat, maize, and barley (Schnerr et al. 2001). Microbiologic and morphologic
methods are time consuming – usually 7–21 days, depending on the isolates – and
furthermore the accuracy of the results depends highly on skilled personnel experienced in microscopic differentiation of strains. Furthermore, the classic plate
counting assays to determine colony forming units are often unable to accurately
reflect the amount of fungal biomass that earlier led to the infection of plants as they
depend on living organisms. In cereal grains the infection and the spread of the
pathogen occurred usually 3–7 weeks before harvest. DNA is a relatively stable
biomolecule and therefore represents an optimal target for gaining information on
past stages of infection. Hence, the quantitative PCR is a brilliant tool for plant
pathology related studies because it takes into account living mycelia actively
producing toxins and also dead mycelia, which previously led to a certain grade
of damage and/or had contributed to the toxin amount found in a sample.
Besides microbiologic determination, the analysis of toxins is an established
method to gain information about the severity of an infection. Usually expensive
HPLC or MS approaches are used to get reliable results. Although these methods
are state of the art in mycotoxin analysis, the cost is extremely high and throughput
limited. Since more and more countries introduced limits for toxin content in food
and feed stuff, a market for commercial ELISA based tests systems was created.
However, rapid tests often miss high accuracy and sample preparation is still time
consuming. For the control of national mycotoxin limits the precise knowledge of
the toxin content is indispensable. In contrast, for plant pathology and agriculture
the concentration of a certain metabolite might not be of real interest but until a few
years ago toxin tests were the best methods for gaining information about the grade
of infection. Or – even worse – taking into account the toxins can only lead to false
interpretation of data. Berthiller et al. (2005) demonstrated the high potential of
plants to metabolize DON into deoxynivalenol-3-glucoside (D3G) which is reconverted into DON in the gastro-intestinal tract of mammalians. Nowadays there are
strong hints that Fusarium resistance breeding heads directly toward the potential
of plants to hide fungal toxins like glucosides. Moreover, to save costs these
analyzes are only rarely integrated in monitoring projects or in resistance determination of newly bred cultivars.
Although several studies demonstrated impressive correlations between Fusarium DNA and the mycotoxin concentration in cereal samples, real-time PCR can
only roughly estimate the concentration of these compounds and therefore until
now is unsuitable for official controls of food and feed. In contrast to food and feed
analysis, the power of this method is found in all niche applications where the
fungal biomass plays a key role: (1) quantitative PCR can be used to completely
102
K. Brunner and R.L. Mach
substitute morphological analysis from the national Fusarium monitoring projects.
In a few PCR runs, numerous species can be detected and for the most prominent
strains quantitative assays are available which allow even the analysis of grains
with mixed infections. Nevertheless, many studies have been performed with a
relatively small subset of reference strains. Therefore over-regional applicability
of the tests has to be verified and probably the specificity must be further optimized. (2) Tests for fungicide efficiency can easily be monitored with quantitative
PCR. The determination of the DNA amount that caused the disease symptoms in
comparison to untreated controls precisely reflects the grade of efficiency of a
certain pesticide against Fusarium. The molecular analysis is inexpensive compared to HPLC/MS measurements. (3) Plant breeding and resistance evaluation
(including tests for the national approval of cultivars) might be a field with high
potential for real-time analysis. Although visual rating systems are well established by plant breeders, this method is elaborate as numerous ears are investigated
at several time-points and the grade of infection is plotted against time. A molecular determination of fungal biomass in infected plants is cheaper than any other
method and the results are not influenced by any metabolized – and thereby
“hidden” – toxins.
In general, real-time PCR provides an invaluable potential to facilitate and
cheapen analysis in fields like agriculture and plant breeding. However, as the
method is still rather in its infancy, there are many problems to be solved in the
near future. Until now no validated reference DNA is available on the market.
Research groups isolate fungal DNA according to different protocols and use
different approaches to determine DNA concentration (e.g., fluorimetric or photometric methods) which do not always give the same results. Furthermore DNA
extraction protocols for cereal samples vary from study to study and until now
no generally accepted reference method has been introduced. Only recently
(Fredlund et al. 2008) the efficiencies of different protocols were compared and
almost tenfold differences concerning the concentration of fungal DNA and
coextracted PCR inhibitors were revealed. Combining the errors derived from
inappropriate DNA-standard concentration measurement with the differences
introduced by various DNA extraction protocols makes interlaboratory comparisons of results impossible. Until now no studies with ring-trials or even laborious
method evaluations (e.g., repeatability, reproducibility, ruggedness etc.) are
available. In general, suggestions for quality assurance for real-time PCR in
agro-biotechnology made only recently (Lipp et al. 2005) should be considered
as a good approach to increase the quality of analysis and raise the confidence of
potential users of this novel technique. A change in people’s mindset – away
from established methods – will be necessary to gain high acceptance of the
quantitative PCR technique as a useful application for particular applications in
plant pathology and agriculture.
Acknowledgments The present article was generated in the course of a Fusarium research project
financed by the Austrian Federal Ministry of Agriculture, Forestry, Environment, and Water
Management, project code FP100053.
5 Quantitative Detection of Fungi by Molecular Methods: A Case Study on Fusarium
103
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Chapter 6
DNA-Based Tools for the Detection of
Fusarium spp. Pathogenic on Maize
Ivan Visentin, Danila Valentino, Francesca Cardinale, and Giacomo Tamietti
Abstract Pink and red ear rot of maize are common diseases in temperate cropping
zones. These diseases are caused by toxigenic fungi belonging to the genus Fusarium. Economic losses flow from both reduced yield (shriveled grain) and compromised quality (contamination with mycotoxin). Since the etiology of these diseases
is complex and the taxonomy of the genus Fusarium is fluid, there has been a rapid
evolution of PCR-based assays for the detection and quantification of toxigenic
Fusarium spp. in biological material, and for their assignment to the correct
phylogenetic species. Following a brief overview of the symptoms and epidemiology
of ear rots in maize, we discuss the toxigenicity of the causal agents and their
taxonomy, and finally survey the range of DNA-based tools available for the
detection, identification, and quantification of Fusarium spp. pathogenic on maize.
6.1
Introduction
Maize, like most cereals, can be infected by a range of pathogens, some of which
can significantly damage the economic value of the crop. Fusarium spp. infection of
maize has been of particular concern in recent years, because several of these
pathogens produce toxic metabolites (mycotoxins) which represent significant
contaminants of food and feed (Marasas et al. 1984). Although only a few mycotoxins are considered to represent a realistic threat to human or animal health, some,
especially the trichothecenes, zearalenone, and fumonisins, are very stable during
seed storage and food/feed processing (Widestrand and Pettersson 2001). Despite
extensive toxicological studies, their significance to human health remains unclear,
and even less understood is the risk of synergistic interactions when two or more
I. Visentin, D. Valentino, F. Cardinale, and G. Tamietti
DiVaPRA – Plant Pathology, University of Turin, I–10095 Grugliasco, Turin, Italy
e-mail: giacomo.tamietti@unito.it
Y. Gherbawy and K. Voigt (eds.), Molecular Identification of Fungi,
DOI 10.1007/978-3-642-05042-8_6, # Springer-Verlag Berlin Heidelberg 2010
107
108
I. Visentin et al.
toxins occur together in food or feed. With the decreased use of fungicides resulting
from the move to lower input cropping technologies and organic farming, there is
particular need to monitor the presence of these mycotoxins in cereals and cereal
products.
The (molecular) diagnosis of plant pathogens requires a detailed knowledge of
disease etiology and the taxonomy of the causal agents, and these are complex
issues for the maize/Fusarium spp. interaction. Therefore, following a short survey
of the biochemistry, toxicity, and mechanisms of action of the major Fusarium
toxins which can accumulate in maize, this chapter aims to outline the epidemiology
of the common Fusarium diseases of temperate maize, and the main taxonomic
issues surrounding the Fusarium genus. The focus, however, is on what DNA-based
tools are available to quickly and reliably classify Fusarium isolated from maize,
and to diagnose and quantify toxigenic strains from field samples.
6.2
Major Fusarium Toxins in Maize
6.2.1
Fumonisins
The fumonisins are a group of food-borne carcinogenic mycotoxins produced by
F. verticillioides (Saccardo) Nirenberg, F. proliferatum (Matsushima) Nirenberg,
and F. nygamai Burgess & Trimboli. They can be fatal to horses, causing extensive
necrosis of brain tissue (equine encephalomalacia), to pigs by chronic accumulation
of fluid in the lungs (porcine pulmonary oedema), and to rats by necrosis of the
liver. They are suspected to be the etiological agent of oesophageal carcinoma in
humans (Marasas et al. 1988). Wild type strains of F. verticillioides produce almost
exclusively four B-series fumonisins, molecules consisting of two tricarballylic
esters attached to a carbon backbone (Bezuidehout et al. 1988; Nelson et al. 1993).
Esterification is an essential step in the maturation of the fumonisins, without which
the molecule does not display full biological activity (Seefelder et al. 2003). The
most common fumonisin present in naturally contaminated maize is B1 (FB1,
Fig. 6.1), a molecule with an aminoeicosapentol backbone with two hydroxyl
groups esterified with 3-carboxy-1,5-pentanedioic acid. Less oxygenated fumonisins, which occur at levels considerably lower than FB1, are FB2 (lacking the C-10
hydroxyl group), FB3 (lacking the C-5 hydroxyl group), and FB4 (lacking both
OH
1
2
NH2
3
R1
4
5
OR3
6
7
8
9
10
R2
Fig. 6.1 Structure of the B-series fumonisins
11
12
CH3
13
14
OR3
15
16
CH3
17
18
19
20
6 DNA-Based Tools for the Detection of Fusarium spp. Pathogenic on Maize
109
groups) (Powell and Plattner 1995). The backbone is formed from the reaction
between a C18 polyketide chain and one amino acid. Isotope feeding experiments
have shown that C3–C20 of the backbone are derived from acetate, and that the
amino group and C-1 and C-2 are derived from alanine (Blackwell et al. 1996;
Branham and Plattner 1993).
The effect of fumonisin on the plant host is not well understood. Some inhibitory
effects of FB1 on the growth of maize callus cells have been reported (Van Asch
et al. 1992), and both the induction of foliar symptoms on sweet corn hybrids and
the inhibition of H+-ATPase activity have been documented (Glenn et al. 2008,
Gutierrez-Najera et al. 2005). FB1 can induce cell death in a fashion reminiscent
of the hypersensitive response also in Arabidopsis thaliana, as a result of which
FB1 has been used by some researchers to study defence-related cell death signaling events in this model plant (Asai et al. 2000). It has been suggested that FB1
acts differently in A. thaliana than in other plant species (Chivasa et al. 2005).
However, the wide range of genetic, genomic, and physiological tools developed
in A. thaliana has ensured that much of the exploration of the activity of the
fumonisins on the plant host has been carried out in this model plant.
A natural primary hypothesis is that the toxicity of fumonisin to plant cells is, as
it is for animal cells, associated with the inhibition of ceramide synthase. The
structural similarity of FB1 to sphingosin has been established as being the basis
for its disruption of sphingolipid metabolism, thereby perturbing various membrane
functions and leading to cell death (Abbas et al. 1994; Riley et al. 1996; Williams
et al. 2006). An alternative, but nonexclusive hypothesis is that FB1 perturbs
plasma membrane functionality by interfering with the activity of H+-ATPase,
which is the target for several fungal toxins and elicitors (Marra et al. 1996;
Wevelsiep et al. 1993). Gutiérrez-Nàjera and coworkers identified FB1 as a potent
inhibitor of plasma membrane H+-ATPase in the maize embryo. FB1 has high
affinity for this enzyme, and inhibition is uncompetitive (Gutierrez-Najera et al.
2005). Uncompetitive inhibition is the most effective form of inhibition, but is
rather rare in nature, possibly because of the risk it poses for metabolism (CornishBowden 1986). A twofold toxicity mechanism has therefore been proposed for FB1
and its homologues: one is indirect, and acts by raising the level of endogenous
sphingoid compounds present through their action on sphinganine N-acyltransferase; the second is direct, acting by uncompetitive inhibition of H+-ATPase.
6.2.2
Trichothecenes
The trichothecenes are a group of epoxysesquiterpene molecules which can be
conveniently classified, on the basis of their chemical structure, into three types:
type A, of which T-2 is an example, type B (such as deoxynivalenol – DON), and
the macrocyclic trichothecenes, which are not produced by Fusarium spp. (Fig. 6.2
and not shown). The trichothecenes inhibit eukaryotic translation (McLaughlin
et al. 1977), and act as virulence factors in the wheat/Fusarium interaction
110
I. Visentin et al.
a
b
O
O
O
OH
OH
O
O
O
O
O
O
O
OH
OH
O
Fig. 6.2 Structure of T-2 toxin (a) and DON (b)
(Bai et al. 2002; Proctor et al. 1995). T-2 (Fig. 6.2a), which is one of the most
acutely poisonous of the Fusarium toxins, is produced by F. acuminatum Ell.
Kellerm, F. equiseti (Corda) Sacc, and F. sporotrichioides Scherb. T-2 toxintreated A. thaliana seedlings are stunted and aberrant in their morphology, and
microarray analysis in A. thaliana has suggested that the toxin induces a number of
defence-related responses, inactivates brassinosteroid synthesis, and generates
reactive oxygen species (Masuda et al. 2007). DON (Fig. 6.2b), which is much
more common in wheat, barley, oat, rice and maize than T-2, is produced primarily
by F. graminearum Schwabe (telomorph Gibberella zeae [Schw.] Petch) and F.
culmorum Sacc., the causal agents, respectively, of red ear rot in maize and head
blight in wheat. DON is also known as vomitoxin because of its emetic effect. The
level of DON contamination in cereals varies from harvest to harvest, and is directly
correlated with the presence of F. graminearum and F. culmorum. DON appears to
inhibit translation in A. thaliana cells, but unlike T-2, this activity is not associated
with the induction of a defence response (Masuda et al. 2007).
6.3
Epidemiology and Etiology of Maize Pink and Red Ear Rot
Fusarium spp. that generate pink or red ear rot are classified as belonging to the
Liseola and Discolor section, respectively. The former disease is more frequent in
hot dry climates, typical of the temperate production zones; the latter predominates
in cooler, moister climates (Bottalico 1998; Logrieco et al. 1995). Although the
importance of Fusarium diseases of maize has been understood for many years, high
levels of genetic resistance have yet to be introduced into commercial hybrids, even
though several dominant genes determining resistance to fumonisin-producing
Fusarium spp. have been identified in various inbred lines (Clements et al. 2004).
6.3.1
Pink Ear Rot
This disease occurs on isolated kernels, groups of kernels, or damaged kernels, and
is recognized by the formation of a white to light pink mold (Miller 1994). Maize is
6 DNA-Based Tools for the Detection of Fusarium spp. Pathogenic on Maize
111
typically grown as either a continuous monoculture or in short rotations with one or
two other crops. As a result, most fields retain maize debris in or on the soil, or in
neighboring fields. Such plant residue is the primary source of inoculum (Smith and
White 1988), as Fusarium spp. survive well on maize residue, either as mycelium or
other survival structures (Sutton 1982). In particular, F. verticillioides can produce
thickened surviving hyphae (Nyval and Kommdahl 1968), or colonize senescent
tissues of other crops and weeds not considered as true hosts (Parry 1995). These
heterothallic Fusarium species sporadically produce perithecia, but sexual reproduction is unlikely to play a significant role in their epidemiology. F. verticillioides,
F. proliferatum, and F. subglutinans produce large quantities of micro- and macroconidia on crop residues, which act as the most important source of inoculum
(Smith and White 1988). Microconidia are typically the more numerous and more
easily wind-dispersed than macroconidia. Insects can also play a significant role in
inoculum dispersion (Dowd 1998; Gilbertson et al. 1986); in Europe, Ostrinia
nubilalis (the corn borer) is the most effective of such vectors, its larvae acquiring
the spores from leaf surfaces and transporting them into the kernels (Sobek and
Munkvold 1999). Silk infection is also important in the development of symptomless colonization and pink ear rot, especially where insect damage is limited
(Desjardins et al. 2002; Munkvold and Desjardins 1997; Nelson et al. 1992). The
influence of systemic infection from seed-borne inoculum on the development of
pink ear rot is disputed. F. verticillioides can systemically and asymptomatically
colonize maize from the infected seed or the root, resulting in invasion of the
kernels (Foley 1962; Munkvold et al. 1997). Although there may be certain
environmental conditions which favor systemic transmission, kernel infection via
this route appears to be only of minor importance under standard field conditions
(Desjardins et al. 1998; Munkvold and Carlton 1997). A combination of host
genetic resistance (Clements et al. 2004), pathogen variability (Carter et al. 2002;
Melcion et al. 1997), and drought stress (the latter being a common event during the
grain-filling period in temperate production areas) interacts to modulate the severity
of the disease infection and the accumulation of mycotoxin. Several lines of
evidence indicate that drought stress is associated with elevated levels of F.
verticillioides infection and fumonisin accumulation in kernels (Marin et al. 2001).
6.3.2
Red Ear Rot
Red ear rot of maize is caused by one or more of F. graminearum, F. culmorum,
F. equiseti, F. chlamydosporum Wollenw. & Reinking, F. acuminatum, F. semitectum Berk. & Rav., and less frequently by F. heterosporum Nees, F. sporotrichioides, F. avenaceum (Corda ex Fries) Sacc. (telomorph Gibberella avenacea
Cook), and F. poae (Peck) Wollenw. All these fungi can heavily colonize either the
stalk, resulting in premature plant death, and/or the bract, silk, and grain, resulting
in the cob, starting from its tip, becoming covered in a pink or red mold (Abbas
et al. 1988; Bottalico et al. 1989; Munkvold 2003a). On small grain cereals,
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I. Visentin et al.
infection is associated with reduced seed germination, seedling death, and head
blight (Garcia Júnior et al. 2007; Matusinsky et al. 2008; Osborne and Stein 2007;
Xu et al. 2008). During the colonization process, a range of mycotoxins is produced,
including zearalenone, zearalenol, DON, 3-acetyl DON, 15-acetyl DON, and T-2,
all of which accumulate in kernels and serve to enhance disease development
(Desjardins et al. 1993, Ohsato et al. 2007; Rocha et al. 2005; Wang et al. 2006).
The epidemiology of the diseases incited by the fungi responsible for maize red ear
rot has been widely investigated in the small grain crops, but much of the derived
knowledge can be readily transferred to maize.
The causal agents survive in the seed in plant debris colonized when senescent or
dead, in alternative hosts (other crops or weeds) and as chlamydospores on plant
debris, and in the soil (Munkvold 2003a; Parry 1995). Debris from potato, sugar
beet, and soybean crops have been identified as the source of inoculum for wheat
head blight (Broders et al. 2007; Burlakoti et al. 2007). Seed infection is very
common and efficient for these Fusarium spp., and allows a ready dispersal of
strains (Gilbert et al. 2005; Guo et al. 2008; Shah et al. 2005). Perithecia and/or
conidia are produced from colonized plant debris. Gibberella zeae perithecia
differentiate when the temperature falls in the range 16–29 C and the substrate
moisture level lies between 0.45 and 1.30 MPa (Dufault et al. 2006; Munkvold
2003a). At lower temperatures, or when precipitation exceeds 5 mm, ascospores are
ejected from dehydrated perithecia, and are wind-dispersed over long distances
(Broders et al. 2007; Osborne and Stein 2007; Trail et al. 2005). The aerial
concentration of ascospores begins to rise between 3 and 5 pm, when relative
humidity is at its lowest, and peaks at 9 pm. Compared with the population of
ascospores, only small numbers of macroconidia are produced from sporodochia on
colonized residues (Inch et al. 2005). The temperature optimum for this process
is about 29 C and their dispersal mechanism is similar to that of ascospores
(Bergstrom and Shields 2002; Tschanz et al. 1976). Within the temperature range
4–30 C and at 100% relative humidity, 50% of ascospores germinate within 33 h.
Germination also succeeds at relative humidity levels as low as 53%, but the percentage of germination decreases with the relative humidity (Beyer and Verreet 2005).
Host plants are most susceptible to infection at, and shortly after anthesis
(Osborne and Stein 2007), but wheat can be infected up until the hard dough
stage. Late infections are associated with significant accumulations of DON
but not with a loss in grain weight (Ponte et al. 2007). The critical time for
F. graminearum infection of the small grain cereals depends on the flowering
habit. Thus, barley cultivars with a gaping flower become susceptible just after
anthesis, but closed flowering types are only attacked 10 days after anthesis, and
this has a significant influence on the amount of mycotoxin accumulated in the grain
(Yoshida et al. 2007). A detailed description of the infection process of maize
grains via the silk has been given by Miller and co-workers (Miller et al. 2007).
Briefly, after germination, the hyphae penetrate the silk and grow towards the cob,
ultimately infecting the developing kernels directly through the silk attachment
point or indirectly through the ovary wall. Cobs can also be colonized directly via
the seed pedicel or glumes. Rainy and humid conditions are particularly conducive
6 DNA-Based Tools for the Detection of Fusarium spp. Pathogenic on Maize
113
for disease development, and air temperature has a selective effect on the identity of
the pathogen – thus F. graminearum predominates in warm areas and F. culmorum
in temperate or cooler ones (Munkvold 2003b, Osborne and Stein 2007). In a survey
of wheat and maize grain infected by Fusarium spp. in NW Italy, a low incidence of
wheat head blight (1.2–1.4%), and negligible red ear rot and grain mycotoxin
contamination in maize were observed over the years 2005–2007, which were
characterized by hot, dry weather. However, wheat head blight was extremely
common in 2008 (96% for zero tillage crops, and 45% for cultivated ones), a year
in which heavy rain and cool conditions prevailed during May and June. Data on
maize ear rot for 2008 in the same area are not available yet (G. Tamietti et al,
unpublished data). The dependence on cultivation practice underlines the role of
crop residues as a source of inoculum (Schaafsma et al. 2005) although the effect
can be attenuated where prevailing winds promote long-distance inoculum dispersal (Osborne and Stein 2007). G. zeae ascospores were abundant in the planetary
boundary layer throughout crop seasons independent of the time of day, but highly
dependent on the extent of cloudiness (Maldonado-Ramirez et al. 2005). Instead, no
significant effect of soil management on the incidence of Fusaria as stem-base
pathogens in winter wheat was noted (Matusinsky et al. 2008). In wheat, grain
colonization by F. graminearum occurs when the temperature is in the range
15–30 C and when water activity (aW) is between 0.900 and 0.995, whereas
DON production occurs in the narrower aW range of 0.95–0.995 (Ramirez et al.
2006). Thus cereal varieties able to dry quickly at maturity are probably less prone
to DON contamination.
6.4
General Species Concepts and Species Borders Within
the Genus Fusarium
Mayden considered species concepts as being either theoretical or operational, with
the latter being the most relevant in the context of diagnosis (Mayden 1997). All the
three common operational species concepts – morphological, biological, and phylogenetic (respectively, MSC, BSC and PSC) – aim to recognize evolutionary
distinct species. The theoretical Evolutionary Species Concept (ESC) defines a
species as being “.. a single lineage of ancestor-descendent populations which
maintains its identity from other such lineages and which has its own evolutionary
tendencies and historical fate” (Wiley 1978). The ESC is not informative for
species identification, as it is not associated with particular recognition criteria. In
contrast, MSC, BSC, and PSC do specify such criteria, but none of the methods of
species recognition derived from morphological, biological, and phylogenetic
species recognition (respectively, MSR, BSR and PSR) are able to recognize the
point at which an ancestral species split into distinct derived species, because
changes in morphology, mating behavior, or gene sequences require the passage
of time. Under ESC, species are recognized by MSR, BSR, or PSR, but several
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I. Visentin et al.
examples are available of fungal species in which the borders defined in this way do
not fully coincide, and this complicates the elaboration of an unequivocal evolutionary pedigree for this kingdom (Taylor et al. 2000). Phylogenetic analyzes based
on variable DNA sequences are thought to be more effective in recognizing species
consistent with ESC. PSR performs well because evolutionary changes in gene
sequence can be recognized long before any changes in mating behavior or morphology (Taylor et al. 2000). Allelic variation at the DNA sequence level does,
however, present a problem for PSR, as it can lead to the artefactual splitting of two
con-specific isolates into two distinct species; this is a drawback especially in the
case of a fungal species lacking a teleomorph (so BSR cannot be applied). This
problem is best overcome by consideration of multiple gene genealogies (genealogical concordance phylogenetic species recognition) (Taylor et al. 2000).
The content of the genus Fusarium, created by Link (1809), has been variously
modified. The first round of reclassifications organized the genus into 16 sections
including 65 species, 55 varieties, and 22 forms (Toussoun and Nelson 1975;
Wollenweber and Reinking 1935). The main discriminating criteria between sections were morphological, in particular the presence and shape of microconidia, the
presence and position along the hyphae of chlamydospores, and the shape of
macroconidia and basal cells. All species, varieties, and forms within a section
were further characterized by the color of the stroma, the presence of sclerotia, and
the number and dimensions of the macroconidial septa. This approach also relied on
the observation of fungal growth on different and specific culture media. In 1983, a
simpler classification method was proposed, in which the genus was divided into 12
sections and 30 species, and current taxonomic treatments are based on this concept
(Burgess et al. 1994; Nelson et al. 1983). In this chapter only the Discolor and
Liseola sections are considered, as all the major maize pathogens belong to one or
other of these two groups.
6.4.1
Section Liseola
This section includes the fumonisin-producing maize pathogens, and comprises the
four morphological species F. moniliforme, F. proliferatum, F. subglutinans, and
F. anthophilum according to Nelson et al. (1983). Later this was extended to six
(F. anthophilum, F. fujikuroi, F. proliferatum, F. sacchari, F. succisae, and
F. verticillioides) by Nirenberg (Nirenberg 1989). G. fujikuroi (Sawada) Ito in Ito
e K. Kimura is the teleomorph of several Fusarium species within Section Liseola,
in which Hsieh et al. identified the three Mating Populations (MP) A, B, C (Hsieh
et al. 1977). Subsequently, Kuhlman identified a fourth species and introduced the
terminology MP-A (G. fujikuroi var. moniliformis), MP-B (G. fujikuroi var. subglutinans), MP-C (G. fujikuroi var. fujikuroi), and MP-D (G. fujikuroi var. intermedia) (Kuhlman 1989). Since this time, further MPs have been uncovered: MP-E
through MP-K (Geiser et al. 2005; Klaasen and Nelson 1996; Lepoint et al. 2005;
Leslie 1991; Nirenberg and O’Donnell 1998; Phan et al. 2004; Zeller et al. 2003).
6 DNA-Based Tools for the Detection of Fusarium spp. Pathogenic on Maize
Table 6.1 Biological species
(MP) in the Liseola section of
the G. fujikuroi species
complex (modified from
(Leslie and Summerell 2006)
MP
MP-A
MP-B
MP-C
MP-D
MP-E
MP-F
MP-G
MP-H
MP-I
MP-J
MP-K
Anamorph
Fusarium verticillioides
F. sacchari
F. fujikuroi
F. proliferatum
F. subglutinans
F. thapsinum
F. nygamai
F. circinatum
F. kunzum
F. gaditjirrii
F. xylarioides
115
Teleomorph
Gibberella moniliformis
G. sacchari
G. fujikuroi
G. intermedia
G. subglutinans
G. thapsina
G. nygamai
G. circinata
G. konza
G. gaditjirrii
G. xylarioides
In the meanwhile, the outcomes of sexual crosses have been gradually integrated
with morphological observations and DNA sequence data. The G. fujikuroi species
complex in particular has been subjected to various DNA-based phylogenetic
analyzes (see later section) (O’Donnell et al. 2000). Overall, the biological, morphological, phylogenetic approaches have produced largely congruent results, and
produced the current definition of 11 species (Table 6.1).
As alluded to above, current classifications have been largely founded upon and
refined by DNA sequence information, which does not rely on observations of the
morphology or sexual fertility of any given isolate. In the G. fujikuroi complex, a
number of DNA-based approaches has been deployed for this purpose, including
electrophoretic karyotyping, RAPD fingerprinting, RFLP genotyping, and DNA
sequence comparisons (Steenkamp et al. 1999, 2001; Voigt et al. 1995; Waalwijk
et al. 1996; Xu et al. 1995). Thus for example, Xu et al.’s electrophoretic karyotyping method was able to distinguish six MPs (A-F). Increasingly, unknown isolates
are assigned to a species on the basis of the DNA sequence within the ribosomal
DNA, calmodulin, b-tubulin, and EF-1 genes (Appel and Gordon 1996; Mirete
et al. 2004; Mulé et al. 2004, Steenkamp et al. 1999, 2001; Waalwijk et al. 1996).
The ribosomal gene family is composed of a tandem array of 18S, 5.8S, and 28S
genes, separated from one another by the internal transcribed spacer (ITS) and the
intergenic spacer (IGS) regions. As the sequence of the coding regions is well
conserved, universal primers can relatively easily be designed; in contrast, the ITS
and IGS regions are highly variable, and it is this sequence polymorphism which is
exploited for the discrimination between taxa.
6.4.2
Section Discolor
Section Discolor comprises 21 species, according to Gerlach and Niremberg
(1982), but only six according to Nelson et al. (Nelson et al. 1994). The species
fall into two major clades, one producing type A and the other type B trichothecenes. Here, we consider the maize pathogens F. graminearum and F. culmorum,
which are the main trichothecene B-producing species. While F. culmorum has a
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I. Visentin et al.
rather distinctive morphology (white or yellow mycelium; stout, thick-walled, and
curved macroconidia of width 4–7 mm and length 25–50 mm; abundant chlamydospores occurring singly, in chains, or in clumps), the species borders of F. graminearum have moved significantly in recent years. F. graminearum has been
conventionally recognized by its straight, moderately robust macroconidia produced in almost colorless sporodochia, by the absence of microconidia in the aerial
mycelium, and by the production of macroconidia and chlamydospores in vegetative mycelium. One subdivision of the species has been based on differences in the
ability to produce perithecia in culture (Burgess et al. 1975, Francis and Burgess
1977). This criterion correlates with different ecological behavior, since strains
belonging to group I (which do not produce perithecia in agar culture and occur in
arid areas) cause crown rot of wheat, while group II strains, later renamed F.
pseudograminearum, produce perithecia in culture, are more toxigenic (DON and
ZEA), and cause spikelet disease in wheat and cob rot in maize. Later, Miller et al.
recognized three chemotypes (able to produce nivalenol, DON, and other acetylated
derivatives to different levels) within the broader species concept of F. graminearum (Miller et al. 1991). O’Donnell et al. presented a phylogeny of F. graminearum based on six genes, which indicated a division into seven lineages (or
phylogenetic species) with distinct geographic origins. One of these lineages is the
producer of DON and ZEA in North America and northern Europe (O’Donnell et al.
1998). Ward et al. used sequence variation at eight toxin genes from a single cluster
to identify a phylogeny which was not congruent with those suggested by other
genes; the conclusion drawn was that the acquisition of the toxin genes preceded
speciation, and that a distinct genetic mechanism unrelated to recombination had
been responsible for the maintenance of chemotypes across the phylogenetic
species within the morphospecies F. graminearum (Ward et al. 2002).
6.5
DNA Sequence-Based Diagnosis of Fusarium spp.
Pathogenic On Maize: Species Assignment
The advent of PCR has opened the way to developing simple diagnostic assays
based on unique DNA sequence. Here, we review some of the assays which have
been developed to discriminate between the Fusarium species pathogenic on
maize – i.e., the major agents of pink ear rot (F. proliferatum, F. subglutinans
and F. verticillioides) and red ear rot (F. graminearum and F. culmorum).
6.5.1
Species-Diagnostic Primers for the Causal Agents
of Pink Ear Rot
The first published PCR primers diagnostic for F. moniliforme (i.e., F. verticillioides sensu Nirenberg 1976) were designed from the sequence of a heat shock
6 DNA-Based Tools for the Detection of Fusarium spp. Pathogenic on Maize
117
protein gene, within which a RAPD polymorphism had been identified (Murillo
et al. 1998). The Fus1-2 primer pair detected the presence of F. verticillioides DNA
in infected plants and soils. Möller et al. developed primers, specific for both
F. verticillioides (53-6F/R) and F. subglutinans (61-2F/R), based on sequences of
RAPD fragments, and were able to employ these for the analysis of infected maize
kernels (Möller et al. 1999). When the specificity of these primer pairs was tested
against a range of other Fusarium spp. and a selection of other fungal species,
53-6F/R specifically amplified from template of G. fujikuroi MP-A, and 61-2F/R
from MP-E. Template of F. culmorum, F. graminearum, or F. proliferatum amplified weakly and only at low annealing temperatures, and the amplicon size was not
as expected. Subsequently, Patino et al. developed the F. verticillioides-specific
PCR primer pair VERT1/2, based on the sequence of the ribosomal IGS (Patiño
et al. 2004). When tested against a panel of 54 F. verticillioides strains obtained
from a range of geographical origins and hosts, the assay proved unable to discriminate F. verticillioides from F. proliferatum isolates from Northern Italy (Visentin
et al. 2009). A further set of primer pairs were designed by Mulé et al. from the
sequence of the taxonomically informative calmodulin gene; these were specific
to F. verticillioides (VER1/2), F. subglutinans (SUB1/2), and F. proliferatum
(PRO1/2), and their discriminating ability was confirmed in an analysis of 150
maize isolates, mostly from Europe and USA (Mulé et al. 2004). A F. proliferatumspecific primer pair (Fp3F/4R) has also been designed, based on the IGS sequence
(Jurado et al. 2006). This assay was successfully validated by testing a range of
Fusarium species, commonly associated with cereals, as well as on other fungal
genera and plant material. As for the VERT1/2 assay, F. proliferatum could not
be always discriminated from isolates of F. verticillioides from Northern Italy
(Visentin et al. 2009). Very recently, the previously designed forward primer
VERT1 (Patiño et al. 2004) was used along with a newly developed reverse primer
VERT-R based on the intergenic spacer region (IGS) to detect F. verticillioides
(Sreenivasa et al. 2008). Finally, a new pair of primers designed on the ITS region
and to be used in combination with the ITS1 and ITS4 fungal universal primers was
described. Although the ITS region offers no full resolution of the genus Gibberella,
it may be very useful for the very practical and tedious task of distinguishing
unambiguously these two very similar species (Visentin et al. 2009, White et al.
1990). A full list of the Fusarium-specific primers described here is given in
Table 6.2.
6.5.2
Species-Diagnostic Primers for the Causal Agents
of Red Ear Rot
Several diagnostic PCR assays have been developed for the causal agents of red ear
rot, in particular F. graminearum and F. culmorum. The first of these to be
published involved the two primer pairs UBC85F/R and OPT18F/R, extracted
from informative RAPD profiles (Schilling et al. 1996). Both were tested against
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I. Visentin et al.
Table 6.2 Specific PCR assays for F. proliferatum, F. subglutinans and F. verticillioides
Primer pairs
Primer sequences
Specificity
Reference
Fus1
50 -cttggtcatgggccagtcaagac-30
F. moniliforme
Murillo et al. (1998)
Fus2
50 -cacagtcacatagcattgctagcc-30
53-6F
50 -tttacgaggcggcgatgggt-30
F. verticillioides
Möller et al. (1999)
53-6R
50 -ggccgtttacctggcttctt-30
61-2F
50 -ggccactcaagaggcgaaag-30
F. subglutinans
Möller et al. (1999)
61-2R
50 -gtcagaccagagcaatgggc-30
VERT1
50 -gtcagaatccatgccagaacg-30
F. verticillioides
Patiño et al. (2004)
VERT2
50 -cacccgcagcaatccatcag-30
VER1
50 -cttcctgcgatgtttctcc-30
F. verticillioides
Mulé et al. (2004)
VER2
50 -aattggccattggtattatatatcta-30
PRO1
50 -ctttccgccaagtttcttc-30
F. proliferatum
Mulé et al. (2004)
PRO2
50 -tgtcagtaactcgacgttgttg-30
SUB1
50 -ctgtcgctaacctctttatcca-30
F. subglutinans
Mulé et al. (2004)
SUB2
50 -cagtatggacgttggtattatatctaa-30
Fp3F
50 -cggccaccagaggatgtg-30
F. proliferatum
Jurado et al. (2006)
Fp4R
50 -caacacgaatcgcttcctgac-30
VERT1
50 -gtcagaatccatgccagaacg-30
F. verticillioides
Patiño et al. (2004)
VERT-R
50 -cgactcacggccaggaaacc-30
Sreenivasa et al. (2008)
verITS-F
50 -aaatcgcgttccccaaattga-30
F. verticillioides
White et al. (1990)
ITS4
50 -tcctccgcttattgatatgc-30
Visentin et al. (2009)
ITS1
50 -tccgtaggtgaacctgcgg-30
F. proliferatum
White et al. (1990)
proITS-R
50 -gcttgccgcaagggctcgc-30
Visentin et al. (2009)
a substantial collection of Fusarium spp. and other fungal pathogens associated
with red ear rot. The UBC85F/R primers selectively amplified DNA of all the
F. graminearum strains tested, but in some cases, also weakly amplified a fragment
from a template of F. culmorum. The OPT18F/R pair amplified as expected from
template of 65 out of 69 isolates of F.culmorum obtained from various countries
and continents. Using a similar approach (Nicholson et al., 1998) generated the four
primer pairs Fc01F/R (specific for F. culmorum), Fg16F/R and Fg16NF/R (F.
graminearum), and Fcg17F/R (both F. culmorum and F. graminearum). Fg16F/R
amplified selectively from 19 out of 19 isolates of F. graminearum, generating a
polymorphic amplicon. A 400 bp product was amplified from the majority of
isolates, but three isolates amplified a 470 bp product, one a 500 bp product, and
one a 360 bp product. Fg16NF/R generated a monomorphic 280 bp amplicon from
all the F. graminearum isolates, and the assay was completely specific. Fc01F/R
generated a 570 bp amplicon from 21 out of 21 isolates of F. culmorum, and did not
amplify from a template of F. graminearum. Fcg17F/R amplified a 340 bp fragment
from all strains of F. graminearum and F. culmorum. Jurado et al. developed an
assay for F. graminearum and F. culmorum based on the IGS sequence, and tested it
on a diverse set of Fusarium spp. strains commonly associated with cereals (Jurado
et al. 2005). The F. culmorum-specific primer pair (Fcu-F/R) amplified a ~ 200 bp
fragment from all F. culmorum samples, while the F. graminearum-specific Fgr-F/
R generated a ~ 500 bp amplicon from all but one of the F. graminearum strains
tested. A full list of the red ear rot specific assays described here is given in
Table 6.3.
6 DNA-Based Tools for the Detection of Fusarium spp. Pathogenic on Maize
Table 6.3 Specific PCR assays for F. graminearum and F. culmorum
Primer pairs
Primer sequences
Specificity
UBC85F
50 -gcagggtttgaatccgagac-30
F. graminearum
UBC85R
50 -agaatggagctaccaacggc-30
OPT18F
50 -gatgccagaccaagacgaag-30
F. culmorum
OPT18R
50 -gatgccagacgcactaagat-30
Fc01F
50 -atggtgaactcgtcgtggc-30
F. culmorum
FC01R
50 -cccttcttacgccaatctcg-30
Fg16F
50 -ctccggatatgttgcgtcaa-30
F. graminearum
Fg16R
50 -ggtaggtatccgacatggcaa-30
Fcg17F
50 -tcgatataccgtgcgatttcc-30
F. culmorum,
F. graminearum
Fcg17R
50 -tacagacaccgtcaggggg-30
Fg16NF
50 -acagatgacaagattcaggcaca-30
F. graminearum
Fg16NR
50 -ttc ttt gac atc tgt tca acc ca-30
Fcu-F
50 -gactatcattatgcttgcgagag-30
F. culmorum
Fgc-R
50 -ctctcatataccctccg-30
Fgr-F
50 -gttgatgggtaaaagtgtg-30
F. graminearum
Fgc-R
50 -ctctcatataccctccg-30
6.6
119
References
Schilling et al. (1996)
Schilling et al. (1996)
Nicholson et al. (1998)
Nicholson et al. (1998)
Nicholson et al. (1998)
Nicholson et al. (1998)
Jurado et al. (2005)
Jurado et al. (2005)
DNA Sequence-Based Diagnosis of Fusarium spp.
Pathogenic on Maize: Toxigenicity
The most problematical Fusarium spp. pathogens are those which are toxigenic.
Here, we describe available PCR-based methods for identifying and quantifying
isolates producing fumonisin and trichothecene from field samples.
6.6.1
Fumonisin-Producing Fusarium spp
Sensitive PCR-based methods have been developed to detect the toxigenic species,
and especially to identify nonproducing sub-populations or nontoxigenic strains
within the toxigenic species. Initially, DNA markers were used in conjunction with
phylogenetic methods to distinguish between groups of toxin producers and nonproducers. For example, Gonzalez-Jaèn et al. developed an IGS-RFLP assay which
could identify a polymorphism associated with toxigenic strains of F. verticillioides
(González-Jaén et al. 2004). Other authors have highlighted the presence of intraspecific polymorphism for such assays. The application of AFLP and IGS/EF-1a
sequence variation led to the definition of two F. verticillioides sub-groups, based
on a contrast between efficient producers of fumonisin (collected from maize), and
nontoxigenic strains (from Central and South American banana fruits) (Mirete et al.
2004; Moretti et al. 2004). The same nontoxigenic population was also exploited by
Patiño et al. to generate an IGS-RFLP assay diagnostic for toxigenicity (Patiño et al.
2006). The non-toxigenic isolates were crossable in vitro with MP-A testers
(corresponding to G. moniliformis), but showed only about 50% genetic similarity
120
I. Visentin et al.
with F. verticillioides strains isolated from maize, and a different chemotoxic
profile and virulence on the two hosts (banana and maize). In this case, it was
proposed that host specialization had driven the observed genetic drift, which will
probably turn into speciation. Several primer pairs were then developed to discriminate toxigenic from non-toxigenic isolates. One of these – diagnostic for
F. verticillioides fumonisin-producing strains – was based on sequence of the IGS
(Patiño et al. 2004). However, since only nonproducing strains from banana were
tested, and all these lack the complete FUM cluster (see below), an assay directed at
any of the fumonisin biosynthetic pathway genes would have equally allowed this
level of discrimination.
Because of the importance of the fumonisin-producing pathogens, some emphasis has been given to elucidating the biosynthetic and regulatory pathway of
mycotoxin production. All the fumonisin biosynthetic (FUM) genes characterized
to date have been located within a 42.5 kb region of the F. verticillioides genome, in
the so-called “FUM cluster” (Brown et al. 2007 Proctor et al. 2003). Gene clusters
in this context are distinct from gene families, which are also frequently clustered.
The former implies physical proximity, co-regulation, and participation in a common metabolic pathway. The latter, in addition, implies related sequence, as
individual members are thought to have evolved by localized duplication and that
subsequent divergence. The significance of gene clusters in this sense has long been
debated. One hypothesis holds that clustering is associated with gene co-regulation,
reminiscent of prokaryotic operons and regulons (Zhang et al. 2004). Alternatively,
they may represent an extended form of selfish genes, facilitating simultaneous
mobilization of a discrete biosynthetic function for horizontal transfer (Walton
2000). The FUM cluster consists of 16 co-regulated genes on chromosome I, now
designated FUM1 (previously named FUM5), FUM2 (previously FUM9), FUM3
(previously FUM12), FUM6-8, FUM10-11, FUM13-19 (Butchko et al. 2003; Proctor et al. 2003, 2006; Seo et al. 2001), and FUM21 (Brown et al. 2007). The role of
some of these genes has been deduced by deletion analysis and/or heterologous
expression. The deletion of either FUM1, FUM6, or FUM8 blocks the accumulation
of all fumonisins, indicating that all are required for fumonisin production (Proctor
et al. 1999; Seo et al. 2001). Their role in fumonisin biosynthesis has been inferred
from homology to genes of known function and from the analysis of deletion
mutants. Several PCR assays have thus been designed to target some of the genes
directly involved in mycotoxin biosynthesis, and these have been used in a quantitative mode to correlate the level of fumonisin with the abundance of particular
biosynthetic genes (i.e., of the toxigenic fungal strains). In particular, two assays
targeting FUM1, which encodes a polyketide synthase, have been applied to a range
of Fusarium spp. and other fungal genera. In both cases, the expected amplicon was
observed only in fumonisin-producing strains (F. verticillioides and F. proliferatum), but an amplicon of the correct size was also generated from template of the
normally non-producing species F. subglutinans and F. thapsinum. López-Errasquı́n
et al. have also observed a significant correlation between the expression level of
FUM1 and FUM19 and the production of fumonisin B1 (Lopez-Errasquin et al.
2007). Very recently, an additional qPCR test was developed, that targets a
6 DNA-Based Tools for the Detection of Fusarium spp. Pathogenic on Maize
121
Table 6.4 PCR assays for the discrimination of fumonisin-producing Fusarium strains
Primer pairs
Primer sequences
References
VERTF1
50 -gcgggaattcaaaagtggcc-30
Patiño et al. (2004)
VERTF2
50 -gagggcgcgaaacggatcgg-30
FUM5F
50 -gtcgagttgttgaccactgcg-30
Bluhm et al. (2002)
FUM5R
50 -cgtatcgtcagcatgatgtagc-30
FUM1for
50 -ccatcacagtgggacacagt-30
Bluhm et al. (2004)
FUM1rev
50 -cgtatcgtcagcatgatgtagc-30
PQF1-F
50 -gagccgagtcagcaaggatt-30
Lopez-Errasquin et al. (2007)
PQF1-R
50 -agggttcgtgagccaagga-30
PQF19-F
50 -atcagcatcggtaacgcttatga-30
Lopez-Errasquin et al. (2007)
PQF19-R
50 -catgtaagttgaggaagcccttgt-30
conserved sequence on the FUM1 gene and gives a good correlation between the
estimated total genomic DNA from fumonisin-producing Fusarium species, and
fumonisin content in maize kernels (Waalwijk et al. 2008a, b). A list of the primer
pairs diagnostic for fumonisin-producing Fusarium spp. reviewed here is given in
Table 6.4.
6.6.2
Trichothecene-Producing Fusarium spp
The trichothecene pathway is well explored, and several trichothecene biosynthetic
genes have been characterized (Desjardins et al. 1993). Bluhm et al. targeted the
gene TRI6 to produce two PCR assays diagnostic for trichothecene-producing
species. These assays were functional only from template of F. culmorum,
F. graminearum, or F. sporotrichioides, all of which are known to be good
producers of trichothecenes (Bluhm et al. 2002, 2004). Assays directed at a range
of other biosynthetic genes have been designed for the same purpose. One of these
targets was TRI5, encoding the catalyst of the isomerization and cyclization of
farnyl phosphate to trichodiene (Hohn and Beremand 1989), and this assay was able
to detect trichothecene-producing Fusarium spp. both from in vitro cultures and
from infected cereal samples (Niessen and Vogel 1998; Niessen et al. 2004). A
second assay exploited the trichodiene synthase family member TOX5, and this was
not only able to detect the presence of F. graminearum and F. culmorum DNA in
cereal samples (Niessen and Vogel 1998), but also its quantitative presence could
be correlated with the level of DON (Knoll et al. 2002a, b). Chemotype-specific PCR
assays were developed by Ward et al. based on the sequence of the TRI3 and TRI12
genes (Ward et al. 2002). Finally, an assay has recently been developed based on
TRI13, and used to explore the toxigenic potential of several Iranian isolates of
F. graminearum (Haratian et al. 2008). Several research groups are currently working
to establish quantitative PCR methods as a means of correlating the abundance of a
toxigenic pathogen in a cereal sample with the amount of trichothecenes present. The
necessary primer pairs target either one of the trichothecene biosynthetic genes
122
I. Visentin et al.
Table 6.5 PCR assays for the discrimination of trichothecene-producing Fusarium strains
Primer pairs
Primer sequences
References
Tri6F
50 -ctctttgatcgtgttgcgtc-30
Bluhm et al. (2002)
Tri6R
50 -cttgtgtatccgcctatagtgatc-30
Tri6for
50 -tgatttacatggaggccgaatctca-30
Bluhm et al. (2004)
Tri6rev
50 -ttcgaatgttggtgattcatagtcgtt-30
Tox5-1
50 -gctgctcatcactttgctcag-30
Niessen and Vogel (1998)
Tox5-2
50 -ctgatctggtcacgctcatc-30
Tri13F
50 -catcatgagacttgtkcrgtttggg-30
Haratian et al. (2008)
Tri13R
50 -ttgaaagctccaatgtcgtg-30
TMTrif
50 -cagcagmtrctcaaggtagaccc-30
Halstensen et al. (2006)
TMTrir
50 -aactgtayacraccatgccaac-30
Tr5F
50 -agcgactacaggcttccctc-30
Doohan et al. (1999)
Tr5R
50 -aaaccatccagttctccatctg-30
FGtubf
50 -ggtctcgacagcaatggtgtt-30
Reischer et al. (2004)
FGtubr
50 -gcttgtgtttttcgtggcagt-30
(Halstensen et al. 2006; Schnerr et al. 2002) or the gene encoding beta-tubulin
(Reischer et al. 2004). The PCR assays specific to trichothecene-producing Fusarium
spp. reviewed here are listed in Table 6.5.
6.7
Conclusion and Future Lines of Research
Species definition can be difficult in the fungi, because morphological variation
between sibling species is often lacking or difficult to recognize, and because many
species lack a known teleomorph. Phylogenetic analyses are therefore particularly
valuable to assign isolates to their correct species. We have discussed here a variety
of DNA-based tools which allow for a rapid and reliable diagnosis of Fusarium spp.
within the Liseola and Discolor sections, and for the detection and quantification of
toxin-producing isolates. PCR-based methods are relatively straightforward and
quick, but are not totally error-free. Their precision should increase as the informative loci from more isolates of different provenance are sequenced.
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Chapter 7
Molecular Detection and Identification
of Fusarium oxysporum
Ratul Saikia and Narendra Kadoo
Abstract Fusarium oxysporum is a ubiquitous inhabitant of soils worldwide and
causes diseases such as wilt, yellows, and damping-off in different plant species.
Rapid and reliable detection of the pathogen is essential for undertaking appropriate
and timely disease management measures. The time-consuming and laborious
classical detection methods are now being increasingly replaced by cultureindependent molecular detection techniques, which are much faster, more specific,
and sensitive. Molecular techniques like microarrays, whole genome sequencing,
DNA barcoding, metagenomics etc. can identify a large number of isolates in a
single assay. Some of the emerging tools will also allow complete analysis of
developmental processes that are characteristics of the fungus, including the
molecular nature of pathogenicity.
7.1
Introduction
Fusarium oxysporum Schlechtend. Fr. is an important asexual species complex and
is well represented among the soil borne fungi in every type of soil all over the
world (Burgess 1981). F. oxysporum includes morphologically indistinguishable
pathogenic, nonpathogenic, and even beneficial strains. The pathogenic strains
cause diseases such as vascular wilt, yellows, root rot, and damping-off in a wide
variety of economically important crops (Beckman and Roberts 1995), while the
R. Saikia
Biotechnology Division, North-East Institute of Science & Technology, Jorhat, 785006, Assam,
India
e-mail: rsaikia19@yahoo.com
N. Kadoo
PMB Group, Biochemical Sciences Division, National Chemical Laboratory, Pune 411008,
Maharashtra, India
e-mail: ny.kadoo@ncl.res.in
Both the authors have contributed equally to the manuscript.
Y. Gherbawy and K. Voigt (eds.), Molecular Identification of Fungi,
DOI 10.1007/978-3-642-05042-8_7, # Springer-Verlag Berlin Heidelberg 2010
131
132
R. Saikia and N. Kadoo
nonpathogenic strains are defined as the strains for which no host plants have been
identified (yet) (Lievens et al. 2008). As a species, F. oxysporum probably causes
more economic damage to agricultural crops than any other pathogen. In spite of
the broad host range of the species as a whole, individual strains usually infect only
a single or a few plant species. These individual fungal strains usually show a high
level of host specificity and, based on the plant species they can infect, they have
been classified into more than 120 formae speciales (Armstrong and Armstrong
1981); for example, F. oxysporum f.sp. ciceri causes wilt only in chickpea. However, some formae speciales such as F. oxysporum f.sp. radicis-cucumerinum, and
F. oxysporum f.sp. radicis-lycopersici have broader host ranges, which, apart from
infecting cucumber and tomato respectively, can cause root and stem rot on
multiple hosts from different plant families (Lievens et al. 2008). Isolates from a
particular forma specialis can be further subdivided into physiological races based
on cultivar specificity. In addition, based on the ability to form heterokaryons,
F. oxysporum strains have been grouped into vegetative compatibility groups (VCGs;
Puhalla 1985), and different formae speciales and races may contain multiple
VCGs (Katan 1999; Katan and Di Primo 1999). Thus, with regard to effective
management of the pathogen, identification below the species level is essential.
Identification of F. oxysporum pathotypes is traditionally based on the combination of diagnostic symptoms on the host and the presence of the fungus in the
affected tissues (Baayen et al. 2000). However, this classical approach is becoming
increasingly challenging because more than one forma specialis may infect a
particular host, along with nonpathogenic strains, which are common soil and
rhizosphere inhabitants (Edel et al. 2000). Genetic differences among F. oxysporum
formae speciales have been evaluated through the analyses of pathogenicity, VCG,
chromosomal features, ribosomal DNA (rDNA), mitochondrial DNA (mtDNA),
and other molecular markers (Jacobson and Gordon 1990; Puhalla 1985; Katan
1999; Appel and Gordon 1995; O’Donnell et al. 1998; Alves-Santos et al. 1999).
However, molecular discrimination of F. oxysporum is complicated by the observation that different isolates classified into a single forma specialis may have
independent evolutionary (polyphyletic) origins (O’Donnell et al. 1998; Baayen
et al. 2000; Skovgaard et al. 2001; Cramer et al. 2003), and that isolates that belong
to different formae speciales may share a common ancestor (monophyletic origin;
Kistler 1997).
Technological advances in molecular detection methods allow quick and accurate detection and quantification of plant pathogens and these are now being applied
to practical problems. The information resulting from such experiments could be
used to monitor the level of exposure of the crop to pathogen inoculum and to
improve disease control by allowing more rational decisions to be made about the
choice and use of fungicides and resistant cultivars. With all these approaches,
implementation of appropriate disease management measures requires timely
detection and reliable identification of the pathogen and its races. Early and reliable
detection is crucial for the containment of the disease and implementation of
disease control strategies when they are likely to be most effective. In recent
years, the increasing use of molecular methods in fungal diagnostics has emerged
7 Molecular Detection and Identification of Fusarium oxysporum
133
as a possible answer to the problems associated with existing phenotypic identification systems. Here we review the present scenario and emerging advances in
molecular identification of plant pathogenic F. oxysporum, and discuss how this
knowledge can help in managing the pathogen.
7.2
Earlier Efforts for Identification of Pathogenic Fusarium
oxysporum
Classically, plant pathogenic fungi were characterized by a series of morphological
criteria including cultural characteristics on growth media and diagnostic symptoms on the host along with the presence of the fungus in the affected tissues
(Baayen et al. 2000). However, accurate identification of fungi by visual examination of such morphological criteria is very difficult and erroneous. Moreover, these
methods have other major limitations such as, reliance on the ability of the fungus
to be cultured, time-consuming and laborious nature of identification process, and
the requirement for extensive taxonomical knowledge, which complicate timely
disease management decisions. Therefore, attempts are being made to replace these
methods with molecular identification techniques. As a result, in the last two
decades, molecular tools have had a major impact on the identification of plant
pathogens. Molecular techniques can avoid many of the drawbacks associated with
classical methods of pathogen identification and can also improve our understanding of pathogen detection in different conditions. In general, these techniques are
more specific, sensitive, and accurate than traditional methods, and do not demand
specialized taxonomical expertise. Today, a wide range of molecular techniques are
being applied to accurately identify F. oxysporum isolates (Table 7.1), of which
those based on detection of pathogen DNA or RNA are the most predominant.
7.2.1
Identification Using Anonymous Markers
Anonymous marker techniques like restriction fragment length polymorphism
(RFLP), random amplified polymorphic DNA (RAPD), amplified fragment length
polymorphism (AFLP), etc. have been successfully used for identification of
F. oxysporum isolates by several workers.
7.2.1.1
Restriction Fragment Length Polymorphism
Restriction Fragment Length Polymorphisms (RFLPs) have been extensively used
to characterize F. oxysporum isolates and VCGs (Flood et al. 1992; Manicom and
Baayen 1993; Fernandez et al. 1994; Mes et al. 1994; Appel and Gordon 1995;
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Table 7.1 Molecular techniques used for identification, detection, or genetic diversity analysis of some formae speciales of Fusarium oxysporum
Method of analysis
References
F. oxysporum forma
specialis
asparagi
Amplified Fragment Length Polymorphism (AFLP)
Baayen et al. (2000)
albedinis
DNA fingerprinting (DF), Restriction Fragment Length
Fernandez and Tantaoui (1994); Fernandez et al. (1995)
Polymorphism (RFLP), Random Amplified Polymorphic
DNA (RAPD), Vegetative Compatibility Grouping (VCG)
ciceri
RFLP, VCG, RAPD, IGS-RFLP, ISSR
Perez-Artes et al. (1995);
Honnareddy and Dubey (2006); Singh et al. (2006);
Bayraktar et al. (2008)
conglutinans
DF, isozyme analysis (ISA), Plasmid DNA profile (PDP),
Bosland and Williams (1987); Kistler et al. (1987, 1991);
RFLP, VCG
Kistler and Benny (1989); Hirota et al. (1992)
cubense
Electrophoretic karyotyping (EK), DF, ISA, RFLP, RAPD,
Miao (1990); Ploetz (1990); Kistler et al. (1991); Koenig et al.
VCG, AFLP
(1993); Boehm et al. (1994); Bentley et al. (1995);
O’Donnell et al. (1998); Baayen et al. (2000); Gerlach et al.
(2000); Groenewald et al. (2006)
cucumerinum
DF, RAPD
Namiki et al. (1994); Lievens et al. (2007)
cyclaminis
DF, RFLP, VCG
Woudt et al. (1995)
dianthi
RFLP, VCG, AFLP
Manicom et al. (1990); Manicom and Baayen (1993);
Baayen et al. (2000)
elaeidis
RFLP, VCG
Flood et al. (1992)
gladioli
DF, RAPD, VCG, AFLP
Mes et al. (1994), Baayen et al. (2000)
lini
AFLP, VCG
Baayen et al. (2000)
lycopersici
ISA, RAPD, RFLP, VCG, AFLP
Elias and Schneider (1991, 1992); Elias et al. (1993);
Baayen et al. (2000)
melonis
DF, RFLP, DNA sequence comparison (DSC), VCG
Jacobson and Gordon (1990); Namiki et al. (1994);
Appel and Gordon (1995)
niveum
EK, DF, RFLP, VCG
Kim et al. (1993); Namiki et al. (1994)
VCG, AFLP
RAPD
DF, RAPD, VCG
radicis-cucumerinum
radicis-lycopersici
raphani
RAPD
RFLP, VCG
DF, ISA, PLP, RFLP, VCG
tulipae
vasinfectum
VCG, AFLP
RAPD, RFLP, VCG, AFLP
Baayen et al. (2000)
Alves-Santos et al. (2002)
Whitehead et al. (1992); Bodker et al. (1993);
Grajal-Martin et al. (1993)
Lievens et al. (2007)
Katan et al. (1991)
Bosland and Williams (1987); Kistler et al. (1987,1991); Kistler
and Benny (1989); Hirota et al. (1992)
Baayen et al. (2000)
Fernandez et al. (1994b); Abd-Elsalam et al. (2002a, 2004);
Abo et al. (2005)
7 Molecular Detection and Identification of Fusarium oxysporum
opuntiarum
phaseoli
pisi
135
136
R. Saikia and N. Kadoo
Baayen et al. 1997; Kistler 1997). Baayen et al. (1998) screened isolates of
F. oxysporum from lily (F. oxysporum f.sp. lilii) for pathogenicity, vegetative
compatibility, and RFLP patterns, and compared these to reference isolates of the
formae speciales gladioli and tulipae. They found that the isolates from Europe and
United States shared unique RFLP patterns and belonged to the same VCG. RFLP
analysis of Fusarium isolates from carnation by Manicom et al. (1990) and Manicom and Baayen (1993) showed two major VCGs, each characterized by a distinct
RFLP pattern. Similarly, Fernandez et al. (1994) used RFLP analysis to identify
four ribosomal DNA (rDNA) and seven mitochondrial DNA (mtDNA) haplotypes
in F. oxysporum f.sp. vasinfectum, the causal organism of cotton wilt. Attitalla et al.
(2004) evaluated isozyme analysis, mtDNA-RFLP, and high performance liquid
chromatography (HPLC) to differentiate two morphologically indistinguishable
formae speciales of F. oxysporum, lycopersici, and radicis-lycopersici. Although
HPLC produced distinct profiles for nonpathogenic and pathogenic isolates, the
direct mtDNA-RFLP technique proved to be an efficient diagnostic tool for routine
differentiation of lycopersici and radicis-lycopersici isolates (Attitalla et al. 2004).
However, although RFLP has been successfully used in many studies to identify
Fusarium isolates, due to its labor-intensive nature, elaborate procedure, and the
need for high amount of DNA (Garcia-Mas et al. 2000), it is being replaced by
polymerase chain reaction (PCR) based techniques.
PCR allows rapid detection and identification of pathogens and overcomes most
of the limitations of classical approaches. It has revolutionized the detection of
pathogens and PCR-based methods are now widely used for identification of a
variety of pathogens because of its rapid, sensitive, and specific nature. Many PCRbased approaches have been reported for identification of F. oxysporum isolates and
the study of the genetic relationships among them. These fungi have been differentiated using either mycotoxigenic genes, ribosomal DNA, other genes, or unique
DNA bands from RAPD analysis (reviewed by Edwards et al. 2002).
7.2.1.2
Random Amplified Polymorphic DNA
Random amplified polymorphic DNA (RAPD) is a quick and cost-effective method
to detect pathogens and study the genetic similarity or diversity among pathogen
populations. The technique has been extensively used to analyze genetic diversity
among different F. oxysporum formae speciales, and races (Grajal-Martin et al. 1993;
Bentley et al. 1994; Kelly et al. 1994; Manulis et al. 1994; Wright et al. 1996).
Paavanen-Huhtala et al. (1999) analyzed 27 F. oxysporum isolates by RAPD and
isozyme patterns; however, all the isolates could only be distinguished from each
other by RAPD analysis. Mes et al. (1999) screened two races of F. oxysporum f.sp.
lycopersici for vegetative compatibility and characterized them using RAPD analysis,
and found that the RAPD profiles coincided with the vegetative compatibility groups.
The RAPD technique has been used to differentiate a collection of isolates into
races corresponding to pathogenicity tests in cotton (Assigbetse et al. 1994) and
basil (Chiocchetti et al. 1999; Chiocchetti 2001). Jimenez-Gasco et al. (2001)
7 Molecular Detection and Identification of Fusarium oxysporum
137
identified specific RAPD amplification profiles for F. oxysporum f.sp. ciceri races
0, 1B/C, 5, and 6. Using RAPD-generated DNA probes, Wang et al. (2001)
developed a sensitive and specific method for identifying F. oxysporum f.sp.
cucumerinum and F. oxysporum f.sp. luffae isolates. After RAPD analysis of 13
formae speciales of F. oxysporum, they selected specific DNA bands as probes and
developed forma specialis-specific probes for identification of F. oxysporum f.sp.
cucumerinum and F. oxysporum f.sp. luffae isolates by dot blot hybridization.
Lievens et al. (2007) developed a robust RAPD marker-based assay to specifically detect and identify the cucumber pathogens F. oxysporum f.sp. cucumerinum
and F. oxysporum f.sp. radicis-cucumerinum. Based on the phylogeny of translation
elongation factor-1a (TEF-1a), they found that F. oxysporum f.sp. cucumerinum
strains were genetically more diverse, while the F. oxysporum f.sp. radiciscucumerinum strains clustered in a separate clade. The developed markers were
implemented in an DNA array to enable parallel and sensitive detection and
identification of the pathogens in complex samples from diverse origins. However,
although the RAPD technique has been successfully used in many studies for
detection and identification of F. oxysporum isolates as well as to evaluate the
genetic diversity within and among pathogen populations, it suffers from wellknown limitations of poor reproducibility and inter-laboratory transferability.
7.2.1.3
Amplified Fragment Length Polymorphism
Amplified fragment length polymorphism (AFLP) has been used in many studies
for the analysis of fungal population structure (Majer et al. 1996; Gonzalez et al.
1998; DeScenzo et al. 1999; Purwantara et al. 2000; Zeller et al. 2000). Genetic
variation among pathogenic isolates of F. oxysporum was estimated using AFLP
markers by several workers (Baayen et al. 2000; Bao et al. 2002; Sivaramakrishan
et al. 2002; Groenewald et al. 2006; Stewart et al. 2006). Later, the utility,
reproducibility, and efficiency of AFLP technique led to its broader application in
the analysis of population diversity and identification of pathogens (Baayen et al.
2000; Abd-Elsalam et al. 2002a, b; Kiprop et al. 2002; Sivaramakrishan et al. 2002;
Abdel-Satar et al. 2003; Leslie et al. 2005; Gurjar et al. 2009). The technique was
used to examine genetic relationships among isolates of F. oxysporum f.sp.
vasinfectum by Abd-Elsalam et al. (2004) and Wang et al. (2006). Gurjar et al.
(2009) identified two F. oxysporum f.sp. ciceri races (1 and 2) based on unique
AFLP patterns. Sequence characterization of these race-specific AFLP products
revealed significant homologies with metabolically important fungal genes. However, as AFLP is relatively costly and has a rather complicated technical procedure,
it is being increasingly replaced by simpler PCR-based methods.
7.2.1.4
Simple Sequence Repeats
Simple sequence repeats (SSRs), also known as microsatellites, provide a powerful
tool for taxonomic and population genetics studies. They have also been used in
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R. Saikia and N. Kadoo
fungal studies because of the high resolution that they provide (Bogale et al. 2005,
2006; Bayraktar et al. 2008). van der Nest et al. (2000) used inter-simple sequence
repeat (ISSR) and SSR primers (random amplified microsatellites, RAMS) in PCR
to develop SSR markers for F. oxysporum. Barve et al. (2001) assessed the genetic
variability in F. oxysporum f.sp. ciceri (Foc) populations prevalent in India using 13
oligonucleotide probes and 11 restriction enzymes. Using the distribution of microsatellite repeats, it was found that races 1 and 4 were closely related as compared to
race 2, while race 3 of the pathogen was very distinct.
However, as these anonymous marker techniques have several disadvantages,
diagnostic DNA fragments identified with these approaches have often been converted into more simple and reliable molecular markers like sequence characterized
amplified region (SCAR) or sequence tagged sites (STS). This approach has proven
to be effective for the identification of several formae speciales and races of
F. oxysporum. For example, Kelly et al. (1998) developed an in planta PCR method
to detect isolates of race 5 of Foc in chickpea. The assay using RAPD-derived
SCAR markers specifically identified race 5 of the pathogen from infected chickpea
plants. Similarly, Jimenez-Gasco and Jimenez-Diaz (2003) sequenced previously
identified Foc specific RAPD markers and designed SCAR markers to identify Foc
and its four pathogenic races 0, 1A, 5, and 6. The assays were sensitive enough to
detect as low as 100 pg of fungal genomic DNA. Based on RAPD analysis, Shimazu
et al. (2005) developed three sets of STS markers for specific identification of three
races of F. oxysporum f.sp. lactucae. These markers were specific to F. oxysporum
f.sp. lactucae and did not amplify DNA from isolates of five other F. oxysporum
formae speciales as well as other plant pathogenic fungi, bacteria, or plant materials
examined in the study.
7.2.2
Identification Using Sequence-Specific Markers
Although the above-mentioned techniques have been successful in accurately
identifying the pathogens in many cases, the markers can be localized anywhere
in the pathogen genome and often little sequence data are available in public
databases for comparison with other sequences. Therefore, extensive screening
using a large collection of strains is necessary to validate the robustness of these
markers. Lievens et al. (2008) listed specific PCR primers for the detection and
identification of several formae speciales and races of F. oxysporum. Such markers
that are based on specific DNA sequences in the pathogen genomes could be used
for pathogen identification as well as for their phylogenetic studies.
7.2.2.1
ITS and IGS
The internal transcribed spacer (ITS) and intergenic spacer (IGS) regions of the
ribosomal RNA genes possess characteristics that allow pathogen identification
7 Molecular Detection and Identification of Fusarium oxysporum
139
(Ward 1994; Appel and Gordon 1995; Waalwijk et al. 1996; Edel et al. 2000; Bao
et al. 2002; Singh et al. 2006). Bateman et al. (1996) used PCR-RFLP of a
PCR product consisting of ITS1, 5.8S and ITS2 ribosomal DNAs, and eight
restriction enzymes to distinguish 18 Fusarium haplotypes, while Edel et al.
(1997) analyzed further into the 50 end of the 28S rDNA gene to distinguish five
Fusarium haplotypes. However, neither of these methods could distinguish among
F. crookwellense, F. culmorum, and F. graminearum, indicating that these formae
speciales might be more closely related. Indeed, Schilling et al. (1996) later found
that the DNA sequence of ITS1 region from F. culmorum and F. graminearum was
identical. Additionally, species-specific primers could not be designed due to minor
differences in the ITS2 region of the two Fusarium species. Mishra et al. (2003)
developed a fluorescent marker-based PCR assay for rapid and reliable identification of five toxigenic and pathogenic Fusarium species viz. F. oxysporum,
F. avenaceum, F. culmorum, F. equiseti, and F. sambucinum. The method was
based on PCR amplification of species-specific DNA fragments using fluorescent
oligonucleotide primers designed from ITS region of rDNA.
Similarly, Abd-Elsalam (2003) developed taxon-selective primers using ITS
sequences for quick identification of the Fusarium genus, while Abd-Elsalam
et al. (2006) identified F. oxysporum f.sp. vasinfectum (Fov) using specific primers
based on the 16S and 23S rRNA genes. Based on differences in ITS sequences of
Fusarium and Mycosphaerella spp., Zhang et al. (2005) developed species-specific
PCR assays for rapid and accurate detection of F. oxysporum f.sp. niveum and
Mycosphaerella melonis from diseased watermelon plants and infested soil. They
also developed real-time quantitative PCR assays to detect and monitor the pathogens directly in soil samples. Zambounis et al. (2007) used PCR-RFLP and realtime PCR for detection and quantification of Australian isolates of F. oxysporum
f.sp. vasinfectum. PCR-RFLP based on the rDNA-IGS region distinguished these
isolates from other formae speciales of F. oxysporum. Further, they identified
single-nucleotide polymorphisms (SNPs) in the 50 portion of the IGS region and
developed two specific real-time PCR assays based on these SNPs for absolute
quantification of genomic DNA from the isolates obtained from infected cotton
tissues as well as soil samples. Similarly, three Fusarium species from Dendrobium
were characterized by Latiffah et al. (2009) using PCR-RFLP of ITS in 5.8S rRNA
region. They found that isolates from the same species produced similar PCR-RFLP
patterns and UPGMA cluster analysis of the data clearly grouped F. oxysporum,
F. proliferatum, and F. solani into separate clusters. Likewise, Gurjar et al. (2009)
differentiated F. oxysporum f.sp. ciceri race 3 from the races 1, 2, and 4 based on
the polymorphisms obtained with ITS-RFLP and ISSR approaches.
7.2.2.2
Transposons
Mouyna et al. (1996) analyzed the South American populations of F. oxysporum
f.sp. elaeidis (an oil palm pathogen) and found that they had the palm transposon.
They also showed that the palm transposon was present in all the pathogenic
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R. Saikia and N. Kadoo
isolates, but was absent in all the nonpathogenic isolates, indicating that the
pathogenic populations may be marked by the transposon. Fernandez et al. (1998)
designed specific primers for detection of F. oxysporum f.sp. albedinis (the date
palm pathogen), based on the sequences of transposable element Fot1. They analyzed a large number of Fusarium isolates, including 286 F. oxysporum f.sp.
albedinis isolates, 17 other formae speciales, nonpathogenic F. oxysporum isolates,
and eight other Fusarium species and the specific primer amplified a 400-bp
fragment only in F. oxysporum f.sp. albedinis. A diagnostic PCR assay to detect
pathogenic F. oxysporum races causing wilt in carnation was developed by Chiocchetti et al. (1999). This strategy was based on the genetic characterization of strains
using different transposons and cloning and sequencing the regions flanking the
insertion sites of these elements, followed by construction of race-specific primers
for quick pathogen identification. Using a similar approach, Pasquali et al. (2007)
developed inter-retrotransposon sequence characterized amplified regions (IRSCAR) technique to differentiate F. oxysporum f.sp. lactucae race 1 isolates from
other F. oxysporum and F. oxysporum f.sp. lactucae isolates. Interestingly, the
robust RAPD marker-based assay developed by Lievens et al. (2007) to specifically
detect and identify the economically important cucumber pathogen F. oxysporum
f.sp. radicis-cucumerinum showed strong similarity with Folyt1, a transposable
element identified in the tomato wilt pathogen F. oxysporum f.sp. lycopersici.
7.2.2.3
Other Genes
Mule et al. (2004) developed PCR assays for rapid identification of F. oxysporum
and F. proliferatum in asparagus plants based on the calmodulin gene sequences,
while Hirano and Arie (2006) designed specific primer sets based on nucleotide
differences in endo-polygalacturonase (pg1) and exo-polygalacturonase (pgx4)
genes from F. oxysporum f.sp. lycopersici and radicis-lycopersici, infecting
tomato. A combination of amplifications from four primer sets allowed effective
differentiation of the isolates into formae speciales and races. A PCR-RFLP
technique based on TEF-1a gene sequences was designed by Bogale et al. (2007)
to distinguish Fusarium redolens and three formae speciales of F. oxysporum.
van der Does et al. (2008) found that, despite their polyphyletic origin, the
F. oxysporum f.sp. lycopersici isolates contained an identical genomic region of
at least 8 kb that was absent in other formae speciales as well as nonpathogenic
isolates, and comprised the genes SIX1, SIX2, and SHH1. They further found
that SIX3, which lies elsewhere on the same chromosome, was also unique to
F. oxysporum f.sp. lycopersici isolates.
Recently, five different approaches viz. gene-specific markers, sequence analysis
of TEF-1a, ITS-RFLP, ISSR, and AFLP were used distinguish four F. oxysporum
f.sp. ciceri (Foc) races, infecting chickpea (Gurjar et al. 2009). Unique AFLP
patterns identified the races 1 and 2, while race 4 was distinguished from other
races by the absence of amplification product of xylanase-3 gene in this race. The
Foc race 3 was differentiated from races 1, 2, and 4 based on the polymorphisms
7 Molecular Detection and Identification of Fusarium oxysporum
141
obtained with ITS-RFLP and ISSR approaches as well as amplification profiles
of Hop78 transposon, cutinase, and desaturase genes. However, phylogenetic
analysis of TEF-1a data from the four races revealed that race 3 was actually
Fusarium proliferatum and not F. oxysporum as has been considered till now
(Gurjar et al. 2009).
7.2.2.4
Multiplex PCR
Multiplex PCR allows simultaneous and sensitive detection of different DNA or
RNA targets in a single reaction. It can therefore, be designed to determine the
presence of more than one pathogen in plant material by selectively amplifying
specific sequences in two or more of them, or to detect related pathogens on
multiple hosts (Louws et al. 1999). Simultaneous identification of several plant
pathogens using multiplex PCR has been reported by Hamelin et al. (1996) and de
Haan et al. (2000). Demeke et al. (2005) developed a species-specific PCR assay
for identification of nine Fusarium species viz. avenaceum, acuminatum, crookwellense, culmorum, equiseti, graminearum, poae, pseudograminearum, and sporotrichioides in pure mycelial culture. Later, they could also simultaneously and
accurately identify F. culmorum, F. graminearum, and F. sporotrichioides using
multiplex PCR. If such specific primers are developed for common F. oxysporum
formae speciales or physiological races, it would greatly simplify their multiplexed
detection and identification for timely disease control. However, development of an
efficient multiplex PCR requires optimization of reaction conditions in order to
discriminate several amplicons per reaction (Elnifro et al. 2000).
7.2.3
Limitations of PCR-Based Techniques
Although PCR-based techniques are rapid, highly sensitive, and specific, they
might suffer from robustness (van der Wolf et al. 2001). The failure of PCR
amplification to correctly diagnose infected and noninfected plant material has
been reported in different comparative assays. Carry-over contamination of amplicons could be responsible for false-positive results, while the presence of inhibitor
components in sample extracts is the main reason for false negatives. Similarly,
PCR based techniques (except reverse transcriptase-PCR) can amplify the target
DNA sequences from both active and nonactive or dead pathogen cells/spores
(Malorny et al. 2003). Therefore, PCR might yield false positive results in some
cases. Another important limitation of PCR-based identification assays is that the
technique is not immediately quantitative. Although it is comparatively easy to
quantify the amount of a PCR product produced as a result of a successful PCR
amplification, it is difficult to estimate the amount of target DNA initially present at
the start of the reaction. This is because the reaction rate is exponential; as a result,
slight variations in the amplification procedure can generate different amounts of
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final product from the same amount of starting material. Although, target DNA can
be quantified using competitive PCR (Nicholson et al. 1998), this method is labor
intensive. However, many of these limitations could be overcome by using modern
techniques like real-time PCR and microarrays, which are increasingly being used
for routine pathogen identification.
7.3
Recent Techniques for Identification of Fusarium
oxysporum
Currently, the detection of plant pathogens is a changing, dynamic, and evolving
world where established protocols can be modified or optimized only months after
having been developed. Accurate and routine pathogen detection requires high
levels of specificity, sensitivity, reliability, and speed. In this context, specificity
can be defined as the capability to detect the pathogen in the absence of false
positives and negatives, while sensitivity relates to the lowest number of pathogens
reliably detected per assay or sample (Lopez et al. 2003). In addition, pathogen
quantification is also becoming important, since it serves as a basis for establishing
damage thresholds at which a pathogen causes disease, and action thresholds that
determine when measures should be taken to limit or prevent losses (Lievens et al.
2008). As F. oxysporum is known to survive and remain latent in soil for many
years, detection methods of high sensitivity, specificity, and reliability are required.
The battery of available techniques and probes for detection of plant pathogens has
increased considerably over the last few years. In addition to time benefits, there are
great advantages in terms of specificity, sensitivity, and reliability with these
techniques, as well as, they allow identification of the pathogen camouflaged by
other microorganisms. Some of such modern techniques currently used in identification of plant pathogens are discussed below.
7.3.1
Real-Time PCR
The real-time PCR technology provides escalating opportunities to identify phytopathogenic fungi and has been used in several studies for detection and identification of various formae speciales of F. oxysporum (Table 7.2). It can more accurately
quantify the extent of pathogen biomass in the host tissue and, with multiplex
formats, enables simultaneous detection of different pathogens (Lievens et al.
2003). The main advantage of real-time PCR assay over end-point quantitative
PCR is that the amplification products can be monitored in real time as they are
accumulated in the exponential phase (Schena et al. 2004), thus allowing precise
measurement of fungal DNA content in the reaction.
7 Molecular Detection and Identification of Fusarium oxysporum
143
Table 7.2 Some examples of real time-PCR assays developed for detection and identification of
Fusarium oxysporum formae speciales
F. oxysporum forma
Host plant
Chemistry
References
specialis
basilici
Ocimum basilicum
Taqman
Pasquali et al. (2006)
chrysanthemi
Argyranthemum
Taqman
Pasquali et al. (2004)
frutescens
chrysanthemi
Chrysanthemum
Taqman
Pasquali et al. (2004)
morifolium
cucumerinum
Cucumis sativus
SYBR Green I
Lievens et al. (2007)
radicis-cucumerinum
Cucumis sativus
SYBR Green I
Lievens et al. (2007)
tracheiphilum
Vigna unguiculata
Taqman
Pasquali et al. (2004)
tracheiphilum
Glycine max
Taqman
Pasquali et al. (2004)
vasinfectum
Gossypium spp.
SYBR Green I
Abd-Elsalam et al. (2006)
niveum
Citrullus lanatus
SYBR Green I
Zhang et al. (2005)
Pasquali et al. (2004) developed a real-time PCR assay based on TaqMan
chemistry to identify a new group of F. oxysporum f.sp. chrysanthemi isolates
highly pathogenic on Paris daisy. They successfully identified infected plants using
real-time PCR as early as the fifth day after artificial inoculation, although the
plants remained symptomless until the 13th day after inoculation. Zhang et al.
(2005) used real-time PCR to identify and quantify F. oxysporum f.sp. niveum
and Mycosphaerella melonis pathogens directly from soil samples. Similarly,
Abd-Elsalam et al. (2006) used real-time PCR based on the 16S and 23S rRNA
genes to detect F. oxysporum f.sp. vasinfectum (Fov) in cotton. The assay detected
as low as 200 fg of Fov genomic DNA in infected cotton roots, while no amplification was obtained from other plant structures such as stem and leaf. Lievens et al.
(2007) developed a robust RAPD marker-based assay to specifically detect and
identify the economically important cucumber pathogens F. oxysporum f.sp. cucumerinum and F. oxysporum f.sp. radicis-cucumerinum. They used the real-time
PCR assay to confirm that the selected RAPD markers for F. oxysporum f.sp.
cucumerinum and F. oxysporum f.sp. radicis-cucumerinum represented single
copy DNA sequences. Likewise, Zambounis et al. (2007) developed two specific
real-time PCR based assays based on the SNPs found in the 50 portion of the
rDNA-IGS regions for quantification of genomic DNA of Australian isolates of
F. oxysporum f.sp. vasinfectum from infected cotton tissues as well as soil samples.
However, like all other molecular methods based on DNA amplification, a major
drawback of the system is that it is unable to distinguish between viable and dead
propagules. Similarly, multiplexing in real-time PCR is limited by the number of
different fluorescent dyes available. In addition, the initial and running costs of a
real-time PCR system are several times more than a normal PCR system. However,
considering the many benefits of the real-time PCR technology compared to normal
PCR, the use of real-time PCR is still advantageous. Higgins et al. (2003) developed
a portable real-time PCR instrument for performing diagnostic assays directly in
the field. Such rapid real-time PCR diagnosis could result in taking appropriate
and timely control measures than possible with traditional methods of pathogen
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R. Saikia and N. Kadoo
identification. Therefore, the resulting losses due to diseases as well as the cost of
disease management could be greatly minimized.
7.3.2
Microarrays
Microarray holds promise for quick and accurate detection of plant pathogens. The
potential of microarray technology in the detection and identification of plant
pathogens is very high due to multiplex capabilities of the system. The application
of microarrays for detection of pathogens in various environments has enabled
parallel detection of multiple species in a high throughput format conducive to
automation (Small et al. 2001; Loy et al. 2002). For pathogenic fungi, microarray
analysis has a great potential to systematically and efficiently identify genes
required for infection (Lorenz 2002; Bryant et al. 2004). A Magnaporthe grisea
array is now commercially available from Agilent Technologies (http://www.
agilent.com/).
A molecular detection system based on DNA array technology was developed
by Lievens et al. (2003) for rapid and efficient detection of tomato vascular wilt
pathogens F. oxysporum f.sp. lycopersici, Verticillium albo-atrum, and V. dahliae.
The array was successfully used for sensitive detection of the tomato wilt pathogens from complex substrates like soil, plant tissues, and irrigation water as
well as samples collected from tomato growers. Similarly, microarray analysis of
F. oxysporum f.sp. vasinfectum genes expressed in planta (McFadden et al. 2006),
has revealed pathogenic genes in the cotton pathogen. The expression of this gene
was also positively correlated with vascular browning, which is a characteristic
symptom of Fusarium wilt infection (McFadden et al. 2006). Guldener et al. (2006)
reported the design and validation of the first Affymetrix GeneChip microarray
based on the entire genome of Fusarium graminearum. It has been shown to
efficiently detect genes from four other closely related species of Fusarium
graminearum. As the genomes of some formae speciales of F. oxysporum have
already been sequenced by the Broad Institute (http://www.broad.mit.edu/), microarray chips might become available for these and other formae speciales of
F. oxysporum in the near future.
Generally, one needs to analyze conserved genes when taxonomically comparing phyla, orders, families, or genera. However, less conserved genes must be used
when investigating species within a genus or taxonomic levels below the species
(Lévesque 2001), such as formae speciales and races. Considering this, Lievens
et al. (2007) developed a DNA array containing genus-, species- and forma
specialis-specific detector oligonucleotides for the detection and identification of
F. oxysporum f.sp. cucumerinum and F. oxysporum f.sp. radicis-cucumerinum. The
array utilized the rRNA gene cluster to derive genus- and species-specific oligonucleotides, whereas RAPD-derived SCAR markers were used to specifically identify
different formae speciales. Using such approach and taking into account the almost
unlimited expanding possibilities of DNA arrays, a comprehensive DNA array for
7 Molecular Detection and Identification of Fusarium oxysporum
145
the identification of all formae speciales (and possibly even races) of F. oxysporum
may ultimately be realized (Lievens et al. 2008).
7.3.3
Gene/Genome Sequencing
One of the most robust and informative techniques useful in fungal diagnosis is
nucleotide sequencing, where DNA sequence variations can be used to design
species-specific primers and/or probes. Sequences of the TEF-1a and the mitochondrial small subunit (mtSSU) ribosomal RNA genes have been valuable in distinguishing different species (Baayen et al. 2000, 2001; O’Donnell et al. 2000;
Skovgaard et al. 2001). Phylogenetic analysis of TEF-1a data by Gurjar et al.
(2009) from four F. oxysporum f.sp. ciceri races revealed that race 3 of the pathogen
was actually Fusarium proliferatum and not F. oxysporum as has been considered
till now. Similarly, DNA sequences of UTP-ammonia ligase, trichothecene 3-Oacetyltransferase, a putative reductase (O’Donnell et al. 2000), nitrate reductase and
phosphate permease (Skovgaard et al. 2001) have also been used successfully to
distinguish different Fusarium species.
Elucidation of full sequence of the genome of an organism can help in designing
the most accurate and sensitive method for its detection and identification. Based on
genome analysis, new specific sequences could be used to design microarray chips,
detection probes, or PCR primers for different pathogens. Using these, it is possible
to identify not only the formae speciales, but also individual races of a pathogen.
Genome sequencing efforts are currently in progress for several important species of
the Fusarium genus (F. circinatum, F. graminearum, F. oxysporum, F. proliferatum,
F. sporotrichioides, and F. verticillioides) (Table 7.3) and the genomes are available at Genomes OnLine Database (GOLD; http://www.genomesonline.org/
index2.htm). In case of F. oxysporum, the genome of f.sp. lycopersici strain
FGSC 4286 was sequenced at 6.8X coverage using the whole genome shotgun
(WGS) sequencing method and the draft sequence is now available. Automated
annotation of the draft sequence predicted over 17,000 protein-coding genes.
Further analysis of these genes can elucidate host-pathogen interactions and allow
the development of disease management approaches targeting important pathogenicity genes of the pathogens.
7.3.4
DNA Barcoding
DNA barcoding holds enormous potential for the rapid identification of organisms
at the species level. It is a taxonomic method that uses a short genetic marker in an
organism’s DNA to identify it as belonging to a particular species. It is emerging as
an important tool for the precise taxonomic identification of a wide range of species
and is effective at both identifying existing species and discovering newones.
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R. Saikia and N. Kadoo
Table 7.3 Status of genome sequencing projects of various Fusarium speciesa
Type
Genome
Sequencing centers Sequncing
Fusarium species/
strains
size
depth
F. circinatum FSP 34 Genome 50 Mb
Inqaba
10x
Biotechnologies
FABI
F. graminearum
Genome 36 Mb
Ceral Disease
N.A.
Laboratory
F. graminearum
Genome 36 Mb
Syngenta AG
N.A.
F. graminearum PH-1 Genome 36 Mb
Broad Institute
10x
IGGR
Genome 17,000
Broad Institute
6.8x
F. oxysporum f.sp.
lycopersici FGSC
ORFs
4286
F. proliferatum
Genome N.A.
Greenomics
N.A.
F. sporotrichioides
EST
N.A.
Univ of Oklahoma
N.A.
F. verticillioides
Genome 87 Mb
J. Craig Venter
N.A.
Institute USDA/
ARS
F. verticillioides 7600 Genome 46 Mb
Broad Institute
8x
Syngenta
a
Status as of August 31, 2009; N.A.: Not available
Sequencing
status
Complete
Incomplete
Incomplete
Complete and
Published
Incomplete
Incomplete
Incomplete
Complete
Incomplete
A 648-bp region of the mitochondrial cytochrome c oxidase subunit I (COI) gene
was initially proposed as a potential “DNA barcode” (Hebert et al. 2003). Using this
new standard, databases are being developed to facilitate rapid and accurate
identification of plant pathogens in general (Plant Pathogen Barcode, PPB; http://
www.plantpathogenbarcode.org/) and fungi in particular (All Fungi Barcoding,
http://www.allfungi.com/). Seifert et al. (2007) evaluated suitability of the COI
gene in fungi by analyzing 370 strains from 58 species of Penicillium subgenus
Penicillium and 12 allied species and found that the gene could be successfully used
for fungal barcoding. Strains from 38 out of 58 species formed cohesive assemblages with distinct COI sequences, and all cases of sequence sharing involved
known species complexes. However, there are reports that the COI gene does not
work well for most true fungi and some researchers feel that the most appropriate
gene for DNA barcoding of true fungi is the ITS region of the nuclear ribosomal
DNA (http://www.allfungi.com/).
Although DNA barcoding holds great promise for species identification, its use
in molecular phylogenetics is challenging. Hajibabaei et al. (2006) showed that
phylogenetic trees constructed from short DNA barcodes, although approximately
reflected accepted phylogenetic relationships, had low statistical support at many of
the internal nodes and could seriously misrepresent some of the branching patterns.
Hence, Min and Hickey (2007) assessed the effect of varying sequence length of
DNA barcodes for the classification of unknown specimens at the species level as
well as for phylogenetic reconstruction in fungi. They found that reducing the
length of the barcode had a profound effect on the accuracy of resulting phylogenetic trees; however, the short barcode sequences still identified the fungal species
accurately. They concluded that the standard short barcode sequences (~600 bp)
7 Molecular Detection and Identification of Fusarium oxysporum
147
were suitable for species identification, but not for inferring accurate phylogenetic
relationships among the fungi. Hence, it is possible that the standard DNA barcoding might accurately distinguish different Fusarium species; however, longer
barcodes would be necessary to precisely identify different formae speciales and
races of the F. oxysporum species complex.
7.4
7.4.1
Emerging Technologies for Pathogen Identification
Next-Generation Sequencing
The recently-developed “Next-Generation” sequencing platforms, such as 454
(Roche), Solexa (Illumina), and SOLiD (ABI), allow researchers to obtain several
million bp of sequences affordably in a single run in an unbiased manner. Among
these sequencing platforms, the 454 GS FLX instrument currently has the ability to
sequence 400–600 million bp per run (with 400–500 bp individual reads) using the
Titanium series reagents (http://www.454.com/). Due to its high accuracy, low cost,
and long reads compared to the Solexa and SOLiD systems, many researchers have
migrated toward the 454 sequencing platform for a variety of genome projects. As
these instruments have the potential of sequencing several microbial genomes in a
single run, it is very likely that the genomes of economically important plant
pathogens, including various Fusarium species, will be shortly available. Indeed,
genome sequencing projects of several Fusarium species are already in progress
(Table 7.3). Based on the analysis of these genomes, specific oligonucleotide
sequences could be used to design microarray chips, detection probes, or PCR
primers for high-throughput or multiplexed detection and identification of different
F. oxysporum strains. If the genomes of important F. oxysporum formae speciales,
and individual races become available, the pathogenic isolates could be detected
specifically even if camouflaged by other organisms.
7.4.2
Single-Nucleotide Polymorphisms
Detection and characterization of SNPs is also one of the promising post-genomics
research tools for pathogen identification. This new technology is pushing pathogen
identification to its ultimate limit-the single base pair difference. It is presumed that
many plant pathogenic races or formae speciales differ from their closest relatives
by only a few bases in different genes. The next-generation sequencing platforms
can rapidly carryout deep sequencing of microbial genomes, enabling quick discovery of SNPs in different pathogenic strains of the microbial species. This will
enable designing forma specialis or race-specific cleaved amplified polymorphic
sequence (CAPS) or derived cleaved amplified polymorphic sequence (dCAPS)
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markers for PCR-based identification. CAPS markers result from differential
restriction digestion of gene/allele specific PCR products based on the loss or
gain of restriction enzyme recognition sites due to the presence of SNPs or
insertion/deletion mutations. While in dCAPS analysis, a restriction enzyme recognition site that includes the SNP is introduced into the PCR product by a primer
containing one or more mismatches to template DNA (Neff et al. 1998). Zambounis
et al. (2007) discovered SNPs in a portion of the IGS region of rDNA flanking the
50 end and developed specific real-time PCR-based assays for absolute quantification of genomic DNA from the Australian Fusarium oxysporum f.sp. vasinfectum
isolates obtained from infected cotton tissues as well as soil samples.
7.4.3
Metagenomics
Another promising approach to large scale detection of microbes from diverse
samples is metagenomics. It is the study of genomic content of microbial organisms
directly in their natural environments, bypassing the need for isolation and culturing
of individual species (Chen and Pachter 2005). Hence, metagenomics enables
studies of organisms that are not culturable as well as studies of organisms in
their natural environment. Using the metagenomics approach, these new sequencing technologies enable researchers to quickly and affordably identify the organisms present in a complex sample (such as soil, irrigation water, or plant tissues)
without any prior knowledge. Such metagenomics approach to pathogen identification should facilitate quick identification and quantification of a range of pathogens
present in the sample and enable undertaking appropriate disease control strategies
well before the pathogen populations reach damage thresholds. The 454 GS FLX
System is very suitable for metagenomics as the system’s long reads help in
accurate identification of pathogenic strains present in the sample. Researchers
often use the platform for counting gene tags to analyze the relative abundance of
different microbial species in different samples.
7.5
Potential Limitations of Molecular Identification
Techniques
Currently, PCR, real-time PCR, and microarrays are the methods of choice for rapid
and accurate detection of plant pathogens. However, a major problem of PCR based
detection is that PCR could amplify DNA from both active and non-active or dead
pathogen cells/spores. Therefore, it may yield false positive results in some cases.
Similarly, false negatives can be attributed in standard PCR protocols due to the
presence of compounds that inhibit the polymerases, degradation of the target DNA
sequence, or reagent problems (Louws et al. 1999). Likewise, although microarray
7 Molecular Detection and Identification of Fusarium oxysporum
149
is the most suitable technique for multiplexed detection of many isolates of
F. oxysporum and other pathogens in a single assay, currently microarrays are
expensive for routine application. Moreover, additional work is needed to address
the challenges of working with environmental samples where contaminants may
interfere with DNA hybridization and affect the performance of microarrays.
Similarly, the lack of adequate sequence information can hamper the development
of reliable molecular diagnostic assays. Moreover, techniques like DNA barcoding
are presently unable to differentiate pathogenic strains from non-pathogenic ones
that belong to the same microbial species. Hence, if no molecular markers are
available to distinguish the pathogenic subspecies, pathogenicity test is the only
way to determine whether or not a given isolate is pathogenic on a specific crop or
variety.
Although technically feasible and potentially invaluable, large sequencing studies still face significant challenges. Foremost among the challenges is analyzing the
tremendous amounts of data generated (Nelson 2003). It is relatively easy to
characterize genes and genome of a well-studied and easily cultivated microbe;
however, it would be a daunting task to understand the genomics of unknown or
uncultured microbes or whole environmental genomes revealed by metagenomics
approaches. For example, Tringe et al. (2005) could assemble as many as 150,000
sequence reads into contiguous sequences spanning only 1% of a soil metagenome.
They estimated that 2–5 billion bp of sequence would be needed to completely
cover the metagenome of a Minnesota soil. Similarly, in mixed microbial communities like agricultural soils, it will be difficult to separate, assemble, and annotate
the genomes of a range of soil microflora. In addition, incorrect assembly of
contiguous genomes and the formation of chimeric inserts can create problems in
interpreting the data (Schloss and Handelsman 2005).
7.6
Conclusions and Future Prospects
Genomics research is generating fast-growing databases that can be used to design
molecular assays for simultaneous detection of a large number of pathogens,
coupled with novel platforms having unprecedented capabilities for multiplexing,
high throughput, and portability. As these new technologies gain wide acceptance,
routine detection, identification, and monitoring of plant pathogens should become
more common in plant pathology. Microarray chips are now being fabricated with
oligonucleotides that are either synthesized directly on a solid surface or are
microspotted. Similarly, the next generation sequencing technologies like 454
and SOLiD can sequence several microbial genomes in a single run.
If the complete DNA sequence of plant pathogens is revealed, oligonucleotides
specific for a pathogen can be designed and a single high-density microarray chip
could accommodate oligonucleotides specific to a large number of pathogens.
In the next few years, complete genome sequences of many pathogenic strains
of F. oxysporum are likely to become available and these will help to design
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PCR primers or probes very specific to the pathogen strains, enabling accurate
identification of the strains even if camouflaged by other pathogens. For example, if
each microarray chip contained oligonucleotides specific to each of the known
formae speciales and races of F oxysporum, it would be possible to have multiplex
detection of all these pathogens in one experiment even from complex substrates
like soil, plant tissues, and irrigation water. With such high-throughput technologies, integration of more strains into the detection systems of F. oxysporum should
become possible and identification of pathogens is likely to become an easier task.
However, these should be observed as management tools, to be used in combination
with the knowledge of the crop and understanding of the biology of different formae
speciales and ecology of the diseases. In this respect, the increasing availability
of full-genome sequences of many plant pathogens including formae speciales of
F. oxysporum is a welcome development.
With the availability of affordable and portable real-time PCR instruments
(Higgins et al. 2003) and simpler protocols, molecular-based diagnosis of crop
diseases is becoming a field reality. Routine diagnosis of many crop diseases is now
possible in one day or less using recent innovative technologies. This, coupled with
high throughput that reduces the cost per sample, should make these assays more
attractive for use in crop protection. A combination of DNA microarrays with other
genomic methods will certainly accelerate the efforts to characterize the function of
unknown stretches of fungal genomes. The resulting database will allow complete
analysis of developmental processes that are characteristics of the fungus, including
the molecular nature of pathogenicity. However, new molecular detection technologies that are portable, robust, sensitive, and cost effective need to be developed for
routine identification of plant pathogens directly in the field to undertake appropriate disease control measures as quickly as possible.
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Chapter 8
Molecular Chemotyping of Fusarium
graminearum, F. culmorum, and F. cerealis
Isolates From Finland and Russia
Tapani Yli-Mattila and Tatiana Gagkaeva
Abstract PCR assays that yield markers that are predictive of NIV versus DON
production or 3ADON versus 15ADON production were performed for 60 Fusarium
graminearum isolates, most of which were from Finland and Russia. None of the
F. graminearum isolates originating from Finland and north-western Russia produced any PCR fragment with DON and NIV specific primers, which indicates that
they have a 3ADON chemotype. All F. graminearum isolates from southern Russia
and most of the isolates from Asia and Germany produced fragments typical of the
15ADON chemotype. All F. culmorum isolates belonged to 3ADON chemotype,
while all F. cerealis isolates belonged to NIV chemotype. The highest DON levels
were found in the 3ADON molecular chemotype isolates of Finland, north-western
Russia, and central Russia. In the combined 3ADON molecular chemotype isolates,
DON production was clearly higher than in the combined 15DON chemotype
isolates.
8.1
Introduction
Fusarium head blight (FHB) caused by Fusarium graminearum (sexual state
Gibberella zeae) and related Fusarium species is among the most important fungal
disease of cereals worldwide (McMullen et al. 1997; Langseth et al. 1999; Bottalico
and Perrone 2002; Gagkaeva and Yli-Mattila 2004; Ward et al. 2008). FHB
T. Yli-Mattila
Laboratory of Plant Physiology and Molecular Biology, Department of Biology, University
of Turku, 20014 Turku, Finland
e-mail: tymat@utu.fi
T. Gagkaeva
Laboratory of Mycology and Phytopathology, All-Russian Institute of Plant Protection (VIZR),
196608 St. Petersburg-Pushkin, Russia
e-mail: t.gagkaeva@yahoo.com
Y. Gherbawy and K. Voigt (eds.), Molecular Identification of Fungi,
DOI 10.1007/978-3-642-05042-8_8, # Springer-Verlag Berlin Heidelberg 2010
159
160
T. Yli-Mattila and T. Gagkaeva
pathogens cause significant yield and quality losses and they pose a serious threat to
food safety, because they produce mycotoxins. The most important mycotoxins
are trichothecenes, such as deoxynivalenol (DON), nivalenol (NIV) and T-2, and
zearalenone (ZEN). Multilocus molecular phylogenetic analyses have resolved the
F. graminearum sensu lato as 13 phylogenetically distinct species (O’Donnell et al.
2000, 2004, 2008; Starkey et al. 2007; Yli-Mattila et al. 2009b). F. graminearum
sensu stricto is the dominant FHB pathogen in most parts of Europe and North
America (Láday et al. 2004; O’Donnell et al. 2000, 2004; Tóth et al. 2005;
Yli-Mattila et al. 2009c). Recently F. graminearum has been spreading northward
in Europe (e.g., Waalwijk et al. 2003; Nicholson et al. 2003) and has been replacing
the closely related F. culmorum, which produces less DON than F. graminearum
(Langseth et al. 1999; Jennings et al. 2004a; Jestoi et al. 2004, 2008). However,
in some recent studies, F. culmorum was still recovered more frequently than
F. graminearum in cereals e.g., in England, Wales, north-western Russia, and
Finland based on percent contamination levels (Shipilova and Gagkaeva 1992;
Jennings et al. 2004a, b).
In Finland, FHB (Fig. 8.1) was first reported in the 1930s as a problem in oats
(Rainio 1932). F. graminearum was reported in Finnish cereals as early as the
1960s (Ylimäki 1981), and subsequently in 1972 (Uoti and Ylimäki 1974); 1976–
1977 (Ylimäki et al. 1979); 1982–1984 (Rizzo 1993) and 1998 (Eskola et al. 2001;
Yli-Mattila et al. 2002). The highest DON levels have been found in oat
(Hietaniemi et al. 2008; Yli-Mattila et al. 2004a, b, 2008a, b, 2009a). High DON
levels have also been found in spring wheat and barley, especially in central and
western Finland, when harvesting has been delayed. The lowest levels have been
found in winter rye and wheat, which are harvested early. Only low levels of ZEN
Fig. 8.1 Symptoms on spring
wheat (cultivar Mahti) 4
weeks after artificial
inoculation in Finland
8 Molecular Chemotyping of Fusarium graminearum
161
have been found in Finnish field samples (Yli-Mattila et al. 2004a), although
F. graminearum and F. culmorum are the main producers of ZEN (Bottalico and
Perrone 2002; Jestoi et al. 2008).
Based on quantitative TaqMan real-time PCR (qPCR) analysis of DNA
recovered from cereal grains, F. graminearum is already more common than
F. culmorum in Finland and a highly significant correlation has been found between
F. graminearum DNA and DON in Finnish oat, barley, and spring wheat
(Yli-Mattila et al. 2008a, b), which is in agreement with the results obtained in
winter wheat in Sweden (Fredlund et al. 2008). In Finnish barley, F. culmorum also
seems to contribute to DON production. The highly significant correlation between
the level of F. graminearum/F. culmorum DNA and DON is in agreement with
previous results of Waalwijk et al. (2004) and Nicholson et al. (2003) in Europe and
Sarlin et al. (2006) in North America.
In Russia, FHB caused by F. graminearum was first reported at the end of
nineteenth century in the Far East region, where the environmental conditions are
favorable to FHB (Voronin 1890). This fungus has not been detected in Siberia and
the Ural regions, while in the southern Russia region (North Caucasus), where the
first outbreak was reported in 1933 (Pronicheva 1935), F.graminearum is the most
common causal agent of FHB. Since it was first detected in the North Caucasus
region, FHB has reached epidemic levels several times in southern Russia during
1960s, 80s, and 90s and caused reduction of cereal yields (Ivanchenko 1960,
Kirienkova 1992). In central Russia, where F. avenaceum tends to be the predominate cause of FHB, F. graminearum isolates have been found on the centralchernozem territory since 1980s (Selivanova et al. 1991). In the north-western
region of Russia, this pathogen was not found until 2003, but since then this
pathogen has become more common in this region (Gagkaeva et al. 2009).
There are three distinct subpopulations of F. graminearum in the European
part of Russia: southern, central, and north-western, which is adjacent to the Finnish
population. The distance from the north-western and Finnish population to the
southern population is ca. 2,000 km. Central population is located between them
and is about 1,000 km from both of them. European F. graminearum populations
are geographically separated from those in the Russian Far East and China by ca.
6,000 km (Fig. 8.2).
F. graminearum isolates can be divided into two main groups (chemotypes)
based on mycotoxin production and production profiles. One group produces DON
and its acetylated derivatives and the other group produces NIV and its acetylated
derivatives. The DON group can be further divided into 3ADON producers and
15ADON producers. The genetic basis of DON versus NIV production results from
differences in Tri7 and Tri13 genes. Chemotype-specific PCR primers (Ward et al.
2002; Jennings et al. 2004a, b; Starkey et al. 2007) and multilocus genotyping that
utilizes a suspension microarray (Ward et al. 2008) have been developed to predict
the chemical phenotype (chemotype) of F. graminearum isolates. The chemotypes
have also been called chemotype IA (producing 3ADON), IB (producing 15ADON)
and II (producing NIV) (Miller et al. 1991). Trichothecene chemotype differences
are apparently adaptive and trichothecene chemotype polymorphism has been
162
T. Yli-Mattila and T. Gagkaeva
Fig. 8.2 The origin (black circles) of Fusarium isolates. The origin (black spots) of F. graminearum isolates in Far East and southern and central Russia have been marked with arrows and
names. The three populations of F. graminearum in north-western Russia/Finland (A), southern
and central Russia (B) and Far East (C) have been marked with black circles
maintained through multiple speciation events by balancing selection (Ward et al.
2002). The 15ADON chemotype of F. graminearum is dominant in USA (Ward
et al. 2008), England, and Wales (Jennings et al. 2004a, b) based on molecular and
chemical analyses. Recent analyses of 3ADON populations in North America
revealed that they had higher average growth rates, produced significantly more
conidia, and accumulated significantly more trichothecene than isolates from sympatric 15ADON populations (Ward et al. 2008). NIV chemotype is relatively
common e.g., in UK (Jennings et al. 2004b) and in some parts of southern USA
(Gale et al. 2007).
The chemical structures of DON and NIV differ from one another only by the
presence or absence of a hydroxyl function at carbon atom 4 (C-4) of the core
trichothecene molecule; NIV has the C-4 hydroxyl and DON does not. The trichothecene biosynthetic gene Tri13 is responsible for this structural difference; the
Tri13 protein catalyzes the C-4 hydroxylation. In NIV-producing strains, Tri13 is
functional and the C-4 position is hydroxylated, whereas in DON-producing strains
the gene is non-functional due to multiple insertions and deletions in its coding
region, and the C-4 position is not hydroxylated (Lee et al. 2002, Brown et al.
2002). Another trichothecene biosynthetic gene, Tri7, is responsible for acetylation
of the C-4 hydroxyl and thereby is responsible for converting NIV to 4-acetylnivalenol (4-NIV). In DON-producing strains of F. graminearum, Tri7 is also nonfunctional due to multiple insertions and deletions (Lee et al. 2002; Brown et al.
2001). In at least some DON-producing strains, the nonfunctional Tri7 contains
multiple repetitions of 11-bp sequence which occur only once in the functional Tri7
of NIV producers (Lee et al. 2001).
8 Molecular Chemotyping of Fusarium graminearum
163
In northern Europe, most F. graminearum and F. culmorum isolates previously
studied possessed a 3ADON chemotype (Miller et al. 1991; Langseth et al. 1999;
Chandler et al. 2003; Jestoi et al. 2004, 2008) based on chemical and molecular
analysis, while in southern-European Russia the 15ADON chemotype was dominant (Leonov et al. 1990). In England and Sweden, the Tri7 gene of the trichothecene cluster was absent in all F. graminearum and F. culmorum isolates of the
3ADON chemotype (Chandler et al. 2003; Jennings et al. 2004a, b). In China also it
was absent in all F. asiaticum (former F. graminearum lineage 6) isolates of the
3ADON chemotype (Zhang et al. 2007). A more specific way to separate 3ADON
and 15ADON isolates is to use primers based on Tri3 gene (Ward et al. 2002,
Jennings et al. 2004b).
Genetic variation of Finnish and Russian F. graminearum isolates has been
studied previously by different molecular methods (Yli-Mattila et al. 2004b,
Gagkaeva and Yli-Mattila 2004) and by chemical analyses (Jestoi et al. 2004,
2008). In the present study, we reexamined most of these archived isolates as
well as some new isolates, for two chemotype-specific PCR markers (Lee et al.
2001, Waalwijk et al. 2003), pathogenicity assays to wheat seedlings, and for DON
and ZEN production in culture. The results were compared to those obtained with
the previously described multilocus genotyping assay (Yli-Mattila et al. 2009a).
8.2
8.2.1
Materials and Methods
Fusarium Isolates
Isolates used in this study are listed in Tables 8.1 and 8.2 together with their
geographic origin (Fig. 8.2), substrate, and results. Most isolates were obtained
from small cereals grains. Grain samples were collected in different regions of
Russia between 1998 and 2004, in Heilongjiang province (Harbin) of China in 1999
and in Germany in 1998. Six F. graminearum isolates from Finland were isolated
from grain, root, and stem base. Six additional Finnish F. graminearum isolates of
the years 2002 and 2003, used in molecular chemotyping, were obtained from grain
(Table 8.1). Every isolate was single-spore subcultured and identified by morphological methods (Gerlach and Nirenberg 1982, Marasas et al. 1984, Figs. 8.3 and
8.4). The identification of each F. graminearum isolate was confirmed by PCR with
species-specific primers Fg11f and Fg11r (Doohan et al. 1998, Waalwijk et al.
2003).
At present all isolates (except for 6 Finnish F. graminearum isolates 02–1, 02–3,
02–11, 03–26, 03–27 and 03–28) are stored in the Collection of Laboratory of
Mycology and Phytopathology, All-Russian Institute of Plant Protection (VIZR),
Russia and ARS Culture Collection (NRRL), Peoria, IL.
164
T. Yli-Mattila and T. Gagkaeva
Table 8.1 List of F. graminearum isolates used in mycotoxin (ng ml 1) and molecular chemotype
(GzTri7f1/r1 and Tri13f/r primers) analyses. Six Finnish isolates of the years 2002 and 2003 are
without NRRL number. Abbreviations: n.a. ¼ not analyzed, Ru ¼ Russia, CE ¼ central Russia,
FE ¼ Far East, NW ¼ north-western Russia, SE ¼ southern Russia
Origin (code for Finnish
Number
in NRRL isolates of the
years 2002 and 2003)
culture
collection
Host
45589
45590
Finland, Espoo
Finland, Jalasjärvi
45595
45602
Finland, Pori
Finland, Ylistaro
45845
45846
Finland, Isokyrö (02–06)
Finland, Marttila (02-05)
Finland, Isokyrö (02-11)
Finland, Isokyrö (02-01)
Finland, Isokyrö (02-03)
Central Finland (03-26)
Central Finland (03-27)
Eastern Finland (03-28)
Ru, CE, Bryansk
Ru, CE, Bryansk
Ru, CE, Bryansk
Ru, CE, Tula
Ru, FE, Kamen-Ribolov
Ru, FE, Kamen-Ribolov
Ru, FE, Kamen-Ribolov
Ru, FE, Kamen-Ribolov
Ru, FE, Kamen-Ribolov
Ru, FE, Kamen-Ribolov
Ru, FE, Kamen-Ribolov
Ru, FE, Kamen-Ribolov
Ru, FE, Kamen-Ribolov
Ru, FE, Khabarovsk
Ru, FE, Khabarovsk
Ru, FE, Khabarovsk
Ru, FE, Ussuriysk
Ru, FE, Ussuriysk
Ru, NW, Leningrad
Ru, NW, Leningrad
Ru, NW, Leningrad
Ru, NW, Leningrad
Ru, NW, Leningrad
Ru, NW, Leningrad
Ru, NW, Leningrad
Ru, SE, Krasnodar
Ru, SE, Krasnodar
Ru, SE, Krasnodar
Ru, SE, Krasnodar
Ru, SE, Krasnodar
Ru, SE, North Ossetia
Ru, SE, North Ossetia
Ru, SE, North Ossetia
Ru, SE, North Ossetia
Ru, SE, North Ossetia
Barley Root
Barley Stem
base
Wheat Root
Oat
Stem
base
Barley Grain
Barley Grain
Barley Grain
Wheat Grain
Wheat Grain
Oat
Grain
Oat
Grain
Oat
Grain
Wheat Grain
Wheat Grain
Wheat Grain
Wheat Grain
Wheat Grain
Wheat Grain
Wheat Grain
Wheat Grain
Wheat Grain
Wheat Grain
Wheat Grain
Wheat Grain
Wheat Grain
Wheat Grain
Wheat Grain
Wheat Grain
Wheat Grain
Wheat Grain
Wheat Grain
Barley Grain
Barley Grain
Barley Grain
Barley Grain
Barley Grain
Barley Grain
Wheat Grain
Wheat Grain
Wheat Grain
Wheat Grain
Wheat Grain
Wheat Grain
Wheat Grain
Wheat Grain
Wheat Grain
Wheat Grain
45633
45634
45635
45636
45574
45615
45616
45617
45630
45575
45599
45605
45614
45579
45577
45606
45618
45628
45611
45612
45622
45623
45624
45625
45637
45584
45585
45586
45591
45600
45578
45580
45581
45582
45583
Tissue
Year Toxins,
mg ml 1
Chemotypespecific
primers
DON ZEN
<4
1986 81
1986 138 251
GzTri7 Tri13
Suggested
chemotype
3ADON
3ADON
1986 399
1993 104
120
11480
3ADON
3ADON
2002
2002
2002
2002
2002
2003
2003
2003
2004
2004
2004
2004
1998
2003
2003
2001
2003
1998
1998
1998
2003
1998
1998
1998
2003
2002
2003
2003
2003
2003
2004
2004
2004
1998
1998
1997
1997
1997
1998
1998
1998
1998
1998
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
<4
28
188
<4
<4
107
27
25
741
795
237
<4
<4
251
<4
2510
43
2630
269
690
251
100
3550
245
1410
<4
<4
12880
<4
186
243
126
5010
126
3980
3ADON
3ADON
3ADON
3ADON
3ADON
3ADON
3ADON
3ADON
n.a.
n.a.
n.a.
n.a.
3ADON
3ADON
3ADON
3ADON
n.a.
15ADON
15ADON
15ADON
15ADON
15ADON
15ADON
15ADON
15ADON
n.a.
3ADON
3ADON
3ADON
3ADON
3ADON
3ADON
n.a.
15ADON
15ADON
15ADON
15ADON
15ADON
15ADON
15ADON
15ADON
15ADON
15ADON
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
17
<4
29
258
15
50
13
12
142
<4
<4
16
20
50
8
45
80
50
80
224
102
317
200
564
170
20
<4
166
<4
8
36
32
63
<4
87
n.a.
n.a.
n.a.
n.a.
n.a.
n.a
n.a.
n.a.
n.a.
þ
þ
þ
þ
þ
þ
þ
þ
n.a.
n.a.
þ
þ
þ
þ
n.a.
þ
þ
þ
þ
þ
þ
þ
þ
þ
þ
þ
þ
n.a.
n.a.
þ
þ
þ
þ
þ
þ
þ
(continued)
8 Molecular Chemotyping of Fusarium graminearum
165
Table 8.1 (continued)
Origin (code for Finnish
Number
in NRRL isolates of the
years 2002 and 2003)
culture
collection
Host
Tissue
Year Toxins,
mg ml 1
45596
45607
45608
45609
45610
45619
45620
45621
45626
45627
45629
45631
45632
45576
45587
45588
45593
45594
45603
45604
45592
45597
45613
45601
45598
Ru, SE, North Ossetia
Ru, SE, North Ossetia
Ru, SE, North Ossetia
Ru, SE, North Ossetia
Ru, SE, North Ossetia
Ru, SE, North Ossetia
Ru, SE, North Ossetia
Ru, SE, North Ossetia
Ru, SE, North Ossetia
Ru, SE, North Ossetia
Ru, SE, North Ossetia
Ru, SE, North Ossetia
Ru, SE, North Ossetia
China, Harbin
China, Harbin
China, Harbin
China, Harbin
China, Harbin
China, Harbin
China, Harbin
Germany, Falkenhagen
Germany, Falkenhagen
Germany, Falkenhagen
Germany, Reinshof
Germany, Rocking
Wheat
wheat
wheat
wheat
wheat
Barley
Barley
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Grain
Grain
Grain
Grain
Grain
Grain
Grain
Grain
Grain
Grain
Grain
Grain
Grain
Grain
Grain
Grain
Grain
Grain
Grain
Grain
Grain
Grain
Grain
Grain
Grain
1998
2004
2004
2004
2004
2002
2002
2000
2004
2002
2002
2004
2004
1999
1999
1999
1999
1999
1998
1999
1998
1998
1998
1998
1998
8.2.2
DNA Extraction and PCR Chemotyping
DON
<4
<4
316
6
<4
8
24
21
10
<4
399
<4
32
12
<4
126
41
8
10
159
n.a.
<4
n.a.
<4
<4
ZEN
243
200
7080
1260
56
158
1200
200
64
76
<4
<4
23
562
1350
2510
1200
190
813
63
126
129
n.a.
295
447
Chemotypespecific
primers
Suggested
chemotype
GzTri7 Tri13
þ
þ
15ADON
þ
þ
15ADON
þ
15ADON
þ
þ
15ADON
þ
15ADON
þ
þ
15ADON
þ
þ
15ADON
þ
þ
15ADON
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
þ
þ
15ADON
3ADON
þ
15ADON
þ
15ADON
þ
þ
15ADON
þ
þ
15ADON
3ADON
þ
þ
15ADON
þ
þ
NIV
þ
15ADON
þ
þ
15ADON
þ
þ
15ADON
The chloroform-octanol method was used for DNA extraction as described by
Paavanen-Huhtala et al. (1999). Amplifications with chemotype-specific primers
GzTri7f1/r1 (Lee et al. 2001) and Tri13f/r (Waalwijk et al. 2003) were performed
for 60 F. graminearum isolates using a PTC-200 DNA Engine thermal cycler.
According to previous investigations NIV producers generate a PCR fragment of
162 with primers GzTri7f1/r1 and a PCR fragment of 415 bp with primers Tri13f/r,
while DON producers generate a PCR fragment of 162 bp plus a multiple of 11 bp
with primers GzTri7f1/r1 and a PCR fragment of 234 bp with primers Tri13f/r.
Amplifications were performed in 25-ml volumes containing Dynazyme reaction
buffer (Finnzymes, Espoo, Finland), 150 mM each of dNTP and 1–10 ng of fungal
DNA. The thermal cycler conditions used were as described by Lee et al. (2001),
except that annealing was performed at 52 C. PCR reactions were repeated at least
twice. PCR products from 23 isolates obtained with primers GzTrif1 and GzTrir1
were separated by electrophoresis in 2% MetaPhor agarose gel (FMC BioProducts,
Rockland, ME, USA) in order to measure the length of the PCR product.
166
T. Yli-Mattila and T. Gagkaeva
Table 8.2 F. culmorum, F. cerealis, and F. graminearum isolates and chemotypes identified by
MLGT analyses. Abbreviations: Ru ¼ Russia, CE ¼ central Russia, FE ¼ Far East, NW ¼
north-western Russia, SE ¼ southern Russia
NRRL
#
45592
45597
45598
45601
45613
45642
45726
45727
45752
45758
45759
45765
45766
45770
45771
45774
45775
45776
45777
45778
45783
45784
45788
45803
45804
45829
45830
45831
45850
45851
45852
45854
45855
45856
45858
45859
45861
45897
45898
Origin
Host
Germany, Falkenhagen
Germany, Falkenhagen
Germany, Rocking
Germany, Reinshof
Germany, Falkenhagen
Ru, FE, Khabarovsk
Ru, NW, Arhangelsk
Finland, Marttila
Finland, Martilla
Ru, CE, Moscow
Ru, CE, Moscow
China, Harbin
China, Harbin
China, Harbin
Ru, CE, Moscow
Ru, NW, Kaliningrad
China, Harbin
Ru, CE, Moscow
Ru, Ural region, Bashkiria
Ru, Ural, Bashkiria
Ru, SE, Rostov
Ru, SE, Rostov
Ru, SE, North Ossetia
Byelorussia
Ru, NW, Pskov
Kyrghyzstan
Kyrghyzstan
Ru, NW, Leningrad
Finland, Marttila
Finland, Marttila
Finland, Marttila
Finland, Marttila
Western Finland,
Etelä-Pohjanmaa
Southern Finland, Uusimaa
SW Finland, Satakunta
SW Finland, Varsinais-Suomi
Southern Finland, Uusimaa
Western Finland, Isokyrö
Finland, Marttila
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Solani
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Barley
Wheat
Wheat
Wheat
Wheat
Cirsium sp.
Cirsium sp.
Cirsium sp.
Wheat
Cirsium sp.
Cirsium sp.
Cirsium sp.
Cirsium sp.
Barley
Wheat
Wheat
Wheat
Oat
Tissue Year MLGT
identification
Grain 1998 graminearum
Grain 1998 graminearum
Grain 1998 graminearum
Grain 1998 graminearum
Grain 1998 graminearum
Ear
2006 cerealis
Potato 2002 culmorum
Grain 2004 culmorum
Grain 2004 culmorum
Grain 2005 culmorum
Grain 2005 culmorum
Grain 2003 cerealis
Grain 2003 cerealis
Grain 2003 cerealis
Grain 2004 culmorum
Grain 2006 culmorum
Grain 2003 cerealis
Grain 2005 culmorum
Root 2005 culmorum
Root 2005 culmorum
Leaf
2004 culmorum
Leaf
2004 culmorum
Leaf
2004 cerealis
Ear
2003 culmorum
Leaf
2004 culmorum
Stem 2005 culmorum
Stem 2005 culmorum
Stem 2005 culmorum
Grain 2002 culmorum
Grain 2002 culmorum
Grain 2002 culmorum
Grain 2003 culmorum
Grain 2003 culmorum
Barley
Oat
Wheat
Wheat
Barley
Barley
Grain
Grain
Grain
Grain
Grain
Grain
2003
2003
2003
2003
2001
2001
culmorum
culmorum
culmorum
culmorum
culmorum
culmorum
MLGT
chemotype
15ADON
NIV
15ADON
15ADON
15ADON
NIV
3ADON
3ADON
3ADON
3ADON
3ADON
NIV
NIV
NIV
3ADON
3ADON
NIV
3ADON
3ADON
3ADON
3ADON
3ADON
NIV
3ADON
3ADON
3ADON
3ADON
3ADON
3ADON
3ADON
3ADON
3ADON
3ADON
3ADON
3ADON
3ADON
3ADON
3ADON
3ADON
8 Molecular Chemotyping of Fusarium graminearum
167
Table 8.3 Gene sequences amplified by multiplex PCR and ASPE (allele-specific primer extension, Ward et al. 2008) probes used for MLGT analysis
Region
Size (bp)
Probe
Target
Reductase
702
RED-2
F. meridionale
RED-ce
F. cerealis
RED-cu
F. culmorum
RED-p
F. pseudograminearum
RED-3
F. boothi
RED-4
F. mesoamericanum
RED-9
F. brasilicum
Tri-101
911
AT-b
B-FHB clade
Fg complex
AT-g
F. austroamericanum
AT-1
AT-2
F. meridionale
AT-ce
F. cerealis
AT-cu
F. culmorum
AT-p
F. pseudoamericanum
AT-sp
Fusarium sp.
AT-3
F. boothi
AT-4
F. mesoamericanum
AT-5
F. acaciae-mearnsii
AT-6
F. asiaticum
AT-7
F. graminearum
AT-8
F. cortaderiae
EF
456
EF-g
Fg complex
F. mesoamericanum
EF-1
EF-L
F. lunulosporum
EF-sp
Fusarium sp.
EF-5
F. acaciae-mearnsii
EF-7
F. graminearum
EF-8
F. cortaderiae
MAT
1040
MAT-L
F. lunulosporum
MAT-6
F. asiaticum
MAT-9
F. brasilicum
Tri-3
912
T3-15ADON
15ADON
T3-3ADON
3ADON
T3-NIV
NIV
Tri-12
1163
T12-15ADON
15ADON
T12-3ADON
3ADON
T12-NIV
NIV
8.2.3
Multilocus Genotyping
The species and trichothecene chemotype composition of German F. graminearum
isolates and F. culmorum and F. cerealis isolates were investigated using multiplex
PCR with six primer pairs followed by a 37 probe version (Table 8.3) of six
gene sequences of the multilocus genotyping (MLGT) assay. The products of the
first PCR were used as templates in the multilocus genotyping assay. Multiplex
amplifications, allele-specific primer extensions, microsphere hybridization, and
168
T. Yli-Mattila and T. Gagkaeva
Fig. 8.3 Fusarium graminearum (left), F. cerealis (middle), and F. culmorum (right) conidia on
SNA medium after 2 weeks in the dark
Fig. 8.4 Fusarium graminearum (left), F. cerealis (middle) and F. culmorum (right) conidia on
SNA medium after two weeks in the dark
detection were performed as described by Ward et al. (2008). Hybridization and
detection were performed using a Luminex 100 flow cytometer.
8.2.4
Mycotoxin Analyses
A panel of 62 and 63 F. graminearum isolates was screened for DON and zearalenone (ZEN) production by indirect ELISA (enzyme linked immunosorbent
assay, Kononenko and Burkin 2002). Every isolate was cultivated for 7 days in a
small glass bottle (diameter 18 mm) with 1 ml PSA medium at 23 C. Then cultures
of isolates were extracted with 1 ml of acetonitrile: water (6:1) and extracts were
analyzed by ELISA, with detection limit 20 ng ml -1 of extract.
8.2.5
Pathogenicity Analysis
The pathogenicity of F. culmorum (45726, 45776, 45777, 45784, 45803),
F. graminearum (45618, 45633, 45702, 45710, 45720, 45744, 45827, 45636,
45638, 45713, 45762, 45799, 45832), and F. cerealis (45775, 45788, 45642) isolates
was examined according to the modified method of Chelkowski and Manka (1983).
8 Molecular Chemotyping of Fusarium graminearum
169
Surface sterilized grains of winter wheat (cv. Moscowskay 39) were kept for one day
in sterile water. Then healthy germinated grains were placed on the surface of the
fungal colony, which was grown for one week on potato sucrose agar (PSA). The
experiments were performed in 2 replicates, with 30 grains in three Petri dishes per
replicate. In controls, 50 grains in five Petri dishes were placed on the surface of PSA
medium in 2 replicates. The length of the seedlings and necrosis were estimated after
one week of incubation in darkness at 23 C. The length of every seedling was
measured and the mean of every isolate was compared to control. The symptoms
of necrosis on the seedlings were evaluated using a scale with classes: 0 ¼ healthy
seedlings, 1 ¼ small spots of necrosis on seedlings, 2 ¼ nearly 50% of the seedlings
covered by brown lesions, 3 ¼ more than 50% of the seedlings have brown lesions
or the seedlings are dead.
8.3
8.3.1
Results
Molecular Chemotype Determination with Tri7
and Tri13 Primer Pairs
When we analyzed the molecular chemotype results from the gel, we could find that
none of the six F. graminearum isolates originating from north-western region of
Russia and 12 isolates from Finland produced any PCR fragment with primers
GzTri7f1/r1 and Tri13f/r (Tables 8.1 and 8.4). According to Kimura et al. (2003);
Chandler et al. (2003) and Jennings et al. (2004a, b) the isolates which do not
produce any PCR fragment with GzTri7f1/r primers belong to the chemotype
3ADON. So, it was possible to divide the isolates into 3ADON and 15ADON
molecular chemotypes based on the presence or absence of amplicons, which in
previous studies (Lee et al. 2001; Waalwijk et al. 2003) were shown to be markers
for DON-producing isolates.
Most isolates of the suggested 15ADON molecular chemotype yielded the
DON-specific amplification fragment with GzTri7f1/r1 (31/34 isolates) and
Table 8.4 Frequency of PCR fragments produced by F. graminearum isolates with chemotypespecific primers GzTri7f1/r1 and Tri13f/r
Origin of isolates
n
% of isolates producing the PCR fragment, bp
GzTri7f1/r1
Tri13f/r
161
(161 + x11)
412
234
Finland
12
0
0
0
0
North-western Russia
6
0
0
0
0
Southern Russia
18
0
89
0
83
Far East of Russia
12
0
75
0
50
China
7
0
71
0
71
Germany
5
20
80
20
60
Total
60
170
T. Yli-Mattila and T. Gagkaeva
Tri13f/r primers (28/34 isolates). Six of the suggested 15ADON molecular chemotype isolates (NRRL 45579, 45577, 45585, 45581, 45582, and 45613) did not yield
an amplicon with the GzTri7f1/r1 primer pair but did yield an amplicon with the
Tri13f/r primer pair, while three isolates (NRRL 45608, 45610, and 45588) yielded
an amplicon only with the primer pair Tri13f/r (Table 8.1).
Most of the isolates from Asia (13/19 isolates), southern Russia (18/18 isolates), and Germany (4/5 isolates) produced fragments typical of the 15ADON
molecular chemotype by at least one of the two primer pairs. Only one isolate
(Germany, G.8-8) had an NIV molecular chemotype based on PCR products
(Tables 8.1 and 8.4).
The size of the PCR product obtained in 15ADON isolates with GzTri7f1/r1
primers was greatest in three isolates from North Ossetia collected in 1998 (206 bp).
In the rest of 15ADON molecular chemotype isolates, the size was 173-195 bp (2–6
copies of the 11 bp repetition) and the biggest 15ADON group (11/22 isolates) had
a PCR product of 184 bp. A single strain yielded an amplicon of 162 bp with
primers GzTrif1/ri, and this is indicative of NIV production. The size variation of
the PCR product between the 15ADON isolates was smaller than between the 50
isolates of Lee et al. (2001), who found 2–16 copies of the 11 bp repeat that occurs
within Tri7.
8.3.2
Multilocus Genotyping
The results of German F. graminearum isolates with MLGT assay were in accordance with the results obtained with molecular chemotype assays. All F. culmorum
isolates possessed the 3ADON molecular chemotype. In contrast, all six isolates of
F. cerealis possessed the NIV molecular chemotype (Table 8.2). The species
identifications of the isolates in Table 8.2 could also be confirmed by using the
MLGT assay.
8.3.3
DON and ZEN Production
There were differences in mycotoxin production between F. graminearum isolates
from different regions. Most F. graminearum isolates produced DON (47/62 isolates) and ZEN (51/63 isolates) (Table 8.1). The highest DON levels were produced
by isolates with the 3ADON molecular chemotype that were from Finland and
north-western Russia. Isolates from southern Russia with the 15ADON molecular
chemotype produced lower levels of DON. Among all isolates with the 3ADON
molecular chemotype, DON production was higher (154 39 ng ml 1) than
among all isolates with the 15ADON molecular chemotype (37 11 ng ml 1).
In contrast, there was no apparent difference in the levels of ZEN production
between isolates with the 3ADON and 15ADON markers (1159 723 ng ml 1
8 Molecular Chemotyping of Fusarium graminearum
171
Table 8.5 DON and ZEN production (mean SE) by F. graminearum isolates in 3ADON
and 15ADON chemotypes
Origin of isolates
Chemotype (n)
Toxin production, ng ml 1
DON
ZEN
Finland
3ADON (4)
180 74
2964 2839
851 546
North-western Russia
3ADON (6)
248 72
1831 808
Southern Russia
15ADON (18)
45 19
Far East of Russia
3ADON (4)
23 9
41 23
15ADON (8)
28 10
481 305
China
3ADON (2)
82
438
15ADON (5)
39 22
1055 399
254 93
<4
Germany
15ADON (2/3)
<4
129
NIV (1)
Total
50/51
Table 8.6 Pathogenicity of F. graminearum (15 ADON and 3 ADON chemotypes), F. culmorum
(3ADON chemotype), and F. cerealis (NIV chemotype) to seedlings of winter wheat cv. Moscovskay 39 as compared to controls
Necrosis,
Fusarium sp.
Chemotype
No. of
The length of seedlings as
score
compared to controls, %
isolates
F. graminearum
15 ADON
7
20.82 4.6
2.63 0.2
F. graminearum
3 ADON
6
11.93 2.6
2.94 0.05
F. culmorum
3 ADON
5
18.7 3.6
2.9 0.06
F. cerealis
NIV
3
27.8 5.6
2.6 0.3
Control
100
0
in 3ADON isolates and 1362 438 ng ml 1 in 15ADON isolates), except in
Russian Far East, where the isolates of the 15ADON chemotype produced clearly
more ZEN than the combined isolates of 3ADON chemotype (Table 8.5), while in
this area no clear difference was found in DON production between 3ADON and
15ADON isolates. The highest ZEN levels were produced by the F. graminearum
isolates from southern Russia and by one Finnish isolate from oats (Table 8.1).
8.3.4
Pathogenicity of Isolates
We analyzed the pathogenicity of isolates by determining their effect on seed
germination, growth, and disease symptoms in the moderate resistant wheat cultivar
Moscowskay 39. Seeds treated with all isolates of Fusarium resulted in significantly shorter seedlings than untreated, control seeds. In addition, large lesions
were observed on seedlings resulting from treated seeds but not on seedlings
resulting from untreated seeds (Table 8.6). F. graminearum isolates with 3ADON
marker inhibited seed germination and reduced seedling growth significantly more
than those with 15ADON marker. F. culmorum isolates with the 3ADON markers
172
T. Yli-Mattila and T. Gagkaeva
also reduced seed germination and seedling growth more than F. graminearum
isolates with 15ADON marker. The three F. cerealis isolates with NIV marker
reduced seed germination and seedling growth less than the F. graminearum and F.
culmorum isolates examined. The isolates examined exhibited a similar trend with
respect to necrotic lesions. Isolates of F. graminearum and F. culmorum with the
3ADON molecular chemotype caused larger necrotic lesions on seedlings than
isolates of F. graminearum with the 15ADON marker or isolates of F. cerealis
with the NIV marker.
8.4
Discussion
Although the 3ADON and 15ADON genetic markers of multilocus genotyping are
highly correlated with trichothecene production profiles, there is no evidence that
the genetic differences corresponding to the different PCR markers are the cause of
the chemotypes with different production profiles. The Tri3 protein catalyzes
acetylation of the C-15 hydroxyl, but Tri3 seems to be fully functional in both
3ADON and 15ADON producers. The Tri12 protein is an efflux pump that most
likely pumps trichothecenes out of the cells in which they are synthesized
(Desjardins 2006). So, it is not clear, how the genetic differences corresponding
to the markers at Tri3 and Tri12 could lead to the differences in 3ADON and
15ADON production. This is in contrast to the Tri7 and Tri13 markers, for which it
is quite clear that the genetic differences corresponding to the PCR markers directly
cause the difference in the trichothecene production profiles.
One F. graminearum strain from Far East has been shown to give a positive
signal with the 3ADON probe from the Tri12 gene and with the 15ADON probe
from the TRI3 gene suggesting that it may reflect recombination between isolates
with these two chemotypes (Yli-Mattila et al. 2009b). The result is similar to the
information of the article of Mirocha et al. (2003), according to whom Yoshizawa
and Morooka (1973) had found a 3,15ADON isolate of F. graminearum in wheat
and to the chromatographic analysis of one single-spore isolate from southern
Russia, which produced both 3ADON and 15ADON based on chemical chromatographic analysis (Leonov et al. 1988).
Kimura et al. (2003), Chandler et al. (2003) and Jennings et al. (2004a, b) have
shown that isolates, which do not produce any PCR fragment with GzTri7f1/r
primers belong to the chemotype 3ADON, because the Tri7 gene is deleted from
all 3ADON isolates. Based on the results of the present work it also seems that
isolates with the 3ADON molecular marker in most cases do not produce any PCR
fragment with primers Tri13f/r. The only exception was one Chinese isolate
(45603), which produced a PCR fragment with primers GzTri7f1/r and Tri13f/r.
Ji et al. (2007) have also found Chinese 3ADON isolates of F. asiaticum and
F. graminearum, which produced a PCR fragment with Tri13f/r primers.
8 Molecular Chemotyping of Fusarium graminearum
173
Forty-six of the 51 F. graminearum isolates tested with both the MLGT assay by
Yli-Mattila et al. (2009b) and chemotype specific primer pair GzTri7f1/r1 in the
present work produced concordant results. Ten isolates of Table 8.1 (45610, 45629,
45845, 45846, 02–01, 02–03, 02–11, 03–26, 03–27, 03–28) were not analyzed
by MLGT assay. Most of the 15ADON molecular chemotype isolates produced
the DON-specific amplification fragment both with GzTri7f1/r1 (31/34 isolates)
and Tri13f/r primers (25/34 isolates). Seven of the 15ADON molecular marker
chemotype isolates (isolates 45577, 45579, 45581, 45582, 45585, 45593, and
45613), which gave a positive result with GzTri7f1/r1 primers, did not produce the
DON-specific amplification product with primers Tri13f/r. Only one F. graminearum
isolate from China (isolate 45587), which gave a negative result with both primer
pairs and was identified as a 3ADON molecular chemotype isolate in the present
work, was later found to be a 15ADON molecular chemotype isolate based on MLGT
assay (Yli-Mattila et al. 2009b). In addition, isolates 45588 from China and 45608
from North Ossetia having the 15ADON molecular marker (based on MLGT analysis) gave a negative result with primer pair GzTri7f1/r1. The 26 isolates of 3ADON
chemotype (based on MLGT analysis) did not produce any amplification product,
except for two isolates from North Ossetia (isolate 45596) and China (isolate 45603),
which produced an amplification product both with Tri13f/r and GzTri7f/r primers.
The molecular chemotype and MLGT results of the present work and those of
Yli-Mattila et al. (2009b) are consistent with previous mycotoxin analyses of pure
cultures of Finnish FHB isolates on autoclaved rice (Jestoi et al. 2004, 2008) and
analyses of field samples (Yli-Mattila et al. 2008a, b), according to which Finnish
F. graminearum and F. culmorum isolates belong to 3ADON chemotype.
The idea that most 3ADON molecular chemotype isolates do not produce any
PCR fragment with GzTri7f1/r and Tri13f/r primers is in agreement with the results
of Waalwijk et al. (2003). According to Waalwijk et al. (2003) 26% of the Dutch
F. culmorum isolates and 14% of the Dutch F. graminearum isolates did not
produce any fragment with GzTri7f1/r primers, while 21% and 12% of the isolates
of the same species did not produce any fragment with Tri13 primers. This probably
means that ca. 20–25% of these Dutch F. culmorum and ca. 12–14% of the Dutch
F. graminearum isolates belonged to the 3ADON molecular chemotype.
Genotyping by chemotype-specific PCR may indicate only that mycotoxin gene
is present, but it does not guarantee that the mycotoxin is produced or predict the
levels of mycotoxin produced. According to the results of the present paper,
3ADON molecular genotypes produce usually more DON than 15ADON molecular
genotypes, which is in agreement with the results obtained in certain areas of North
America (Ward et al. 2008). According to Ward et al. (2008) and Yli-Mattila et al.
(2008b, 2009b), 3ADON molecular chemotype frequencies among F. graminearum
are increasing in certain areas of North America and Russian Far East, while in Russian
Far East a new 3ADON producing species of F. graminearum species complex,
Fusarium ussurianum, was recently found. In 1998 ten of 14 F. graminearum isolates
collected in Russian Far East and Harbin in China were of the 15ADON molecular
chemotype, while in 2006 twelve of 18 F. graminearum isolates had the 3ADON
molecular chemotype (Yli-Mattila et al. 2009b).
174
T. Yli-Mattila and T. Gagkaeva
3ADON molecular chemotype isolates of F. graminearum and F. culmorum
inhibited more strongly the growth of wheat seedlings and caused more necrotic
lesions than 15ADON molecular chemotype isolates of F. graminearum and NIV
isolates F. cerealis. This is in accordance with higher DON production of 3ADON
molecular chemotype isolates in the present work and previous investigations
(Ward et al. 2008) as compared to 15ADON molecular chemotype isolates. Only
3ADON molecular chemotype of F. graminearum was detected in the population of
north-western Russia, where F. graminearum was not found until 2003. This
population is probably related to the older 3ADON molecular chemotype population in Finland. Since, fitness is better (Ward et al. 2008) and 3ADON phytotoxicity
and pathogenic potential are higher in 3ADON molecular chemotype isolates as
compared to 15ADON molecular chemotype isolates, the increase of 3ADON
chemotype of F. graminearum on new cereal production areas may be dangerous
both for plant and mammal health.
Acknowledgments We are indebted to Drs. A. Burkin and G. Kononenko from Laboratory of
Mycotoxicology, All-Russian Institute for Veterinary Sanitation, Hygiene, and Ecology, Moscow,
Russia for performing mycotoxins analyses. The visits of Dr. T. Yli-Mattila to the All-Russian
Plant Protection Institute and the visits of Dr. T. Gagkaeva to the University of Turku were
supported financially by the Academy of Finland (no. 126917 and 131957) and the Nordic network
project New Emerging Mycotoxins and Secondary Metabolites in Toxigenic Fungi of Northern
Europe (project 090014), which is funded by the Nordic Research Board. The authors are grateful
to Drs. K. O’Donnell and T. Ward from USDA Research Institute in Peoria in USA for comments
on the previous version of the manuscript and to Dr. Robert Proctor from the same institute for
comments on the final version and for linguistic revision.
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Chapter 9
Molecular Characterization and Diagnosis
of Macrophomina phaseolina: A Charcoal
Rot Fungus
Bandamaravuri Kishore Babu, Ratul Saikia, and Dilip K. Arora
Abstract Macrophomina phaseolina is a global pathogen that inflicts losses on
many agriculturally important crops worldwide, particularly in warm and tropical
environments. Efforts to divide M. phaseolina into subspecies have been unsuccessful largely due to the extreme intraspecific variations in morphology and
pathogenecity. The failure to adequately identify and detect M. phaseolina using
conventional culture-based morphological techniques has led to the development of
nucleic acid-based molecular approaches. PCR-based methods are highly sensitive
and specific and have the potential to replace traditional technologies. Recently,
species-specific oligonucleotide primers and digoxigenin (DIG)-labeled probe were
designed at internal transcribed spacer (ITS) region for identification and detection
of M. phaseolina. Accurate diagnosis and early detection of pathogens is an
essential step in agriculture and environmental monitoring including plant disease
management. The main objective of this review is to outline various molecular tools
used for detection, identification, and characterization of M. phaseolina isolates.
We also emphasize the significance of advanced technique such as real-time
polymerase chain reaction (PCR) for qualitative and quantitative assays.
B.K. Babu
Environmental Microbiology Lab, Department of Environmental Engineering, Chosun University,
Gwang ju-501759, South Korea
e-mail: kishore_bandam@yahoo.co.in
B.K. Babu and D.K. Arora
National Bureau of Agriculturally Important Microorganisms (ICAR), Mau, Uttar Pradesh
275101, India
e-mail: aroradilip@yahoo.co.in
R. Saikia
Biotechnology Division, North-East Institute of Science & Technology (CSIR), Jorhat 785006,
Assam, India
e-mail: rsaikia19@yahoo.com
Y. Gherbawy and K. Voigt (eds.), Molecular Identification of Fungi,
DOI 10.1007/978-3-642-05042-8_9, # Springer-Verlag Berlin Heidelberg 2010
179
180
9.1
B.K. Babu et al.
Introduction
Macrophomina phaseolina (Tassi) Goid. is a primarily soilborne pathogen with
wide distribution, varied host range, greater longevity, and higher competitive
saprophytic ability (Chattanaver et al. 1988; Das 1988; Singh et al. 1988; Sobti
and Bansal 1988; Abbaiah and Satayanarayan 1990; Das and Sankar 1990; Osunlaja 1990; Singh et al. 1990; Srivastava and Singh 1990; Kaur and Mukhopadhyay
1992; Siddiqui and Mahmood 1992; Mukherjee 1993). About 500 plant diseases are
caused by the fungus (Su et al. 2001). The fungus is also associated with seeds and it
has been shown that infection leads to both pre- and postemergence mortality,
causing seed-to-seedling transmission of the pathogen (Pun et al. 1998). The
pathogen occurs both inter- and intracellularly. The amount of internal inoculum
is directly related with the degree of symptoms expressed (Sharma and Singh 2000).
The pathogen attacks the root system of the plants and causes dissolution of all
tissues except the xylem. Wilting followed by withering and death of aerial parts
are characteristic symptoms of the disease (Edmunds 1964). The infected roots
have abundant mycelia and sclerotia, but rarely pycnidia are produced on infected
roots (Knox-Davies 1967). Both pycnidiospores and sclerotia have been implicated
in the propagation of this fungus. The pathogen is plurivorus, causing ashy stem and
blight or charcoal rot; root and stem show destruction of the cortex. The fungus is
also the causal agent of the charcoal rot disease of many crops (Mihail 1992). In
some cases, as in histological sections of roots infected with M. phaseolina showed
destroyed cortical parenchyma, both giant cell and also cortical were invaded by
mycelia (Suárez et al. 1998). Inhibition of penetration through the outer cell wall of
the upper epidermis may be attributable to an osmophilic layer below the cell wall.
Disruption of the host cell walls and subsequent host cell death were preceded by
massive colonization of the host (Joye and Paul 1992).
In this chapter, we will provide up-to-date information for the detection and
identification of M. phaseolina. We will also discuss on molecular markers that
have detected a wide range of genetic variations among the isolates.
9.2
Classification and Nomenclature
Macrophomina phaseolina belongs to subdivision Duteromycotina, class Coelomycetes (Mihail 1992), order Sphaeropsidales, family Sphaerioidacease, and genus
Macrophomina. The genus Macrophomina contains only one species: phaseolina
(Sutton 1980).
The successive changes in nomenclature led to confusion in adopting the correct
name of Macrophomina. The monotypic genus Macrophomina was established by
Petrak (1923) as M. philippinensis. Subsequently, Ashby (1927) examined the type
material of this fungus, compared it with several other genera, and established
earlier binomial for the fungus as Macrophomina phaseoli Maubl. Consequently,
9 Molecular Characterization and Diagnosis of Macrophomina phaseolina
181
Ashby proposed the combination M. phaseoli (Maubl.) (Ashby) for M. phaseoli
Maubl. and relegated the synonym M. cajani P. Syd. and Butler, M. chorchori
Sawada, M. sesami Sewada, M. philippinensis Petrak, Sclerotium bataticola Taub.,
Rhizoctonia bataticola (Taub.) Butler, and Dothiorella cajani (P. Syd. and Butler)
Petrak and H. Syd. Goidanich (1947) reviewed the taxonomy of Macrophomina.
Petrak (1923) named this as M. phaseolina Tassi. in place of M. phaseoli Maubl.
From 1947 onwards, the two names i.e., M. phaseoli (Maubl.) (Ashby) and
M. phaseolina (Tassi.) Goid, became well established in psychopathological literature as the cause of charcoal rot of several important crop plants. After 1977, several
other names were suggested for the fungus and ultimately Macrophomina phaseolina
(Tassi.) Goid was accepted as the correct name (CMI description of pathogenic fungi
and bacteria no. 275). The sclerotial phase of M. phaseolina is known as R. bataticola
(Thakurji 1979; Punithalingam 1982).
9.3
Identification and Characterization
The biggest problem before mycologists/plant pathologists is to identify/detect
thousands of different isolates of this fungus from the cultures in infected roots,
soil, and seed lots. Identification and detection of M. phaseolina is very difficult
because the isolates are morphologically very similar. Different scientists have
adopted different methods to distinguish M. phaseolina isolates. Among the methods that are most applicable are (1) morphological and cultural characterization,
(2) biochemical methods, and (3) polymerase chain reaction (PCR) based molecular techniques.
9.3.1
Morphological and Cultural Characteristics
M. phaseolina forms black colonies on potato dextrose agar (PDA) medium, and
grows profusely at temperatures ranging from 15 to 40 C. However, the optimum
growth occurs at 30–35 C. Some of the isolates can be identified on the basis of
morphological characteristics and their thermophilic nature (Satto et al. 1999). The
shape of the sclerotia, in most cases, is irregular except for a few which are round to
oblong (Mandal et al. 1998). The mycelium is septate, 1.5–2.5 mm wide, hyaline at
first turning to honey or black color. Fructification consists of globose or subglobose pycnidium, which is formed only on infected plants and consists of 3–4 layers
of blackish-brown, thin-walled angular cells and sclerotia. Pycnidia can be detected
in epidermis. Sclerotia are black, and their size on infected plants as well as on
media is variable. Under laboratory conditions, sclerotium is hyaline to light brown
in color measuring 89 mm in diameter, whereas in soil it measures from 50 to
120 mm in diameter (Upadhayay et al. 2002).
182
B.K. Babu et al.
Insufficient morphological variability within the genus has led some workers to
partition this fungus on the basis of cultural characteristics (Reichert and Hellinger
1947). Chromogenicity, sporulation ability, and pycnidial size are also known to
diverge greatly (Crall 1948; Dhingra and Sinclair 1978; Pearson 1982). Traits with
less variability would be more useful when trying to group the isolates. Different
investigators have differentiated strains of this fungus on the basis of their ability to
utilize nitrate as a nitrogen source (Correll et al. 1986; Correll et al. 1987; Larkin
et al. 1988; Bayman and Cotty 1989). M. phaseolina have three types of growth
patterns, viz., dense, feathery, and restricted, on chlorate-containing minimal
medium (120 mM potassium chlorate). Earlier it was found that the utilization of
chlorate was used as a marker for identifying host-specific isolates in M. phaseolina
(Pearson et al. 1986; Cloud and Rupe 1991). Recent studies on the mechanism of
chlorate assimilation and genetic basis for chlorate sensitivity have found no
correlation with host specificity. It was also observed that chlorate-sensitive isolates
were distinct from chlorate-resistant isolates within a given host (Su et al. 2001;
Das et al. 2008). Therefore, the chlorate phenotype might not be useful for studying
host specialization in M. phaseolina.
9.3.2
Biochemical and Serological Characterization
Biochemical methods such as protein electrophoresis as well as fatty acid and
isozyme profiles have also been applied for the characterization and differentiation
of fungal taxa (Buth 1984; Faris et al. 1986). Immunological methods are highly
specific and sensitive, which may provide a possible solution for detection and
quantification of plant pathogenic fungi (Kitagawa et al. 1989; Eparvier and
Alabouvette 1994; Jamaux and Spire 1994) and are reliable as quantitative techniques for ecological studies (Balesdent et al. 1995). However, there are no considerable reports on the use of biochemical as well as serological techniques to detect
and quantify M. phaseolina. Srivastava and Arora (1997) have described a doubleantibody sandwich enzyme-linked immunosorbent assay (DAS-ELISA) technique
using polyclonal antisera raised from soluble mycelial protein, cell wall proteins,
and ribosomal proteins. Polyclonal antibodies that rose from soluble and cell wall
protein found no significant polymorphism within the isolates of M. phaseolina.
Ribosomal-specific antibodies detected in M. phaseolina at infected chickpea roots
and use of these ribosomal-specific antibodies for the detection of M. phaseolina
take place under some particular environmental conditions only. Therefore, this
technique was limited to taxonomic identification and detection of M. phaseolina.
9.3.3
Molecular Methods for Characterization of M. phaseolina
In recent years, there has been immense progress in the development of molecular
biological tools and technologies. These have been increasingly applied to the study
9 Molecular Characterization and Diagnosis of Macrophomina phaseolina
5.8S rRNA gene
18S
IGS region
28S
183
5.8S rRNA gene
ETS
28S
18S
Structural genes
Ribosomal RNA gene cluster
ITSregions
Primer ITS –1
5.8S rDNA
18S ribosomal RNA gene
28S ribosomal RNA gene
Primer ITS – 4
ITS –1 region
ITS – 2 region
Fig. 9.1 General Physical map of rDNA gene cluster in fungal genome: The complete repeat unit
is represented with genes location and spacer regions. ITS Internal transcribed spacers; IGS
Intergenic spacers. primers ITS-1 and ITS-4 are showing the specific binding position
of fungal plant pathogens (Leong and Holden 1989; Bridge and Arora 1998). The
DNA sequences that encode for RNAs have been extensively used to study the
taxonomic relationships and genetic variations in fungi (Bruns et al. 1992; Hibbert
1992). The ribosomal RNA gene cluster is found both in nucleus and mitochondria,
and consists of both highly conserved and variable regions (White et al. 1990).
The fungal nuclear rRNA genes are arranged as tandem repeats with several
hundred copies per genome. The conserved sequences found in the large subunit
and small subunit genes have been exploited to study the many relationships among
distantly related fungi (Gaudet et al. 1989; Bowman et al. 1992; Bruns et al. 1992).
The spacer regions between the subunits, called the internal transcribed spacers
(ITS), and between the genes clusters, called the intergenic spacers (IGS), are
considerably more variable than the subunit (Fig. 9.1). These genes have been
used widely for studies on the relationships among species within a single genus or
among interspecific populations (O’Donnel 1992; Molina et al. 1993; Li et al. 1994;
Buscot et al. 1996; Arora et al. 1996; Singh et al. 2006).
9.3.3.1
Molecular Tools Used for Characterization of M. phaseolina
Restriction Fragment Length Polymorphism
Though there are many examples of the use of restriction fragment length polymorphism (RFLP) of spacer regions for discriminating between closely related species
within a fungal genus, in the case of M. phaseolina the ITS region has shown no
variations among isolates in restriction patterns of DNA fragments amplified by
PCR covering the ITS region, 5.8S rRNA and part of 25S rRNA (Su et al. 2001;
Babu et al. 2007). However, Purkayastha et al. (2006) found some degree of
polymorphism in restriction patterns of the ITS region, including part of 25S
184
B.K. Babu et al.
rDNA, indicating the RFLP analysis was not suitable for detection of genetic
diversity of M. phaseolina.
PCR-Fingerprinting Techniques
Molecular fingerprinting techniques such as amplified fragment length polymorphism (AFLP), restriction fragment length polymorphism, random amplified polymorphic DNA (RAPD), and simple sequence repeats (SSR) have been used to
unveil genetic variability in this soilborne filamentous fungi. Various studies have
been devoted to the genetic diversity and pathogenic variability of M. phaseolina;
however, only a single species has been recognized in the genus Macrophomina,
but high levels of variation in pathogenecity have been observed (Mayek-Pe´rez
et al. 2001; Su et al. 2001). Jana et al. (2003) developed taxonomic markers for
population studies by using a single RAPD primer that distinguishes isolates of
M. phaseolina from soybean, sesame, ground nut, chickpea, cotton, common bean,
and 13 other hosts. The genetic diversity of M. phaseolina could favor its survival
and adaptation to variable environments because of significant morphological
(Mayek-Pe´rez et al. 1997), physiological (Mihail and Taylor 1995), pathogenic,
and genetic (Chase et al. 1994; Vandemark et al. 2000; Mayek-Pe´rez et al. 2001;
Pecina-Quintero et al. 2001; Su et al. 2001; Alvaro et al. 2003; Jana et al. 2003,
2005a, b) diversity. However, there is no clear evidence to suggest formae specialis,
or subspecies. Recently, sorghum isolates of Indian origin were distinguished on the
basis of chlorate sensitivity (Das et al. 2008). The correlation between genotype and
geographical or biological origin was obtained with single RAPD marker among
the Indian isolates of M. phaseolina collected from different hosts and various
agroclimatic zones (Babu et al. 2009a). The Unweighted Pair Group Method with
Arithmetic mean (UPGMA) dendrogram obtained by 10-mer random primer OPB08 separated 50 isolates physiological races has into 10 groups at 65–80% similarity
(Fig. 9.2). The 10 clusters correlated well with the geographical locations, with
exceptions for isolates obtained from Eastern Ghats (IV and X) and Western Ghats
(VIII and IX) and Western Ghats (Fig. 9.2). There was a segregation of isolates
from these two geographical locations into two clusters, thus distributing 10
genotypes into 8 geographical locations. The presence of two monomorphic
bands suggests that the isolates might have evolved from a common ancestor but
due to geographical isolation followed by natural selection and genetic drift they
might have segregated into subpopulations (Babu et al. 2009a). Similarly, ReyesFranco et al. (2006) reported significant variations among the pathotypes obtained
from different continents.
9.3.3.2
Diagnostic Tools Developed for Identification and Detection
Molecular methods have recently been described to resolve genetic variation
among the isolates of M. phaseolina (Das et al. 2008; Jana et al. 2005a, b;
9 Molecular Characterization and Diagnosis of Macrophomina phaseolina
mpK1
mpK2
mpK3
mpK8
mpK39
mpK5
mpK11
mpK18
mpK38
mpK40
mpK45
mpK32
mpK43
mpK9
mpK35
mpK36
mpK37
mpK6
mpK49
mpK50
mpK7
mpK14
mpK12
mpK13
mpK21
mpK23
mpK25
mpK19
mpK16
mpK44
mpK18
mpK42
mpK46
mpK47
mpK26
mpK27
mpK29
mpK30
mpK4
mpK17
mpK24
mpK41
mpK10
mpK20
mpK33
mpK15
mpK31
mpK34
mpK22
mpK28
0.6
0.7
0.8
0.9
I
Western Himalyas
II
Gangetic plain
III
Semi Arid zone
IV
Eastern Ghats. a.
V
Central High lands
Vl
Decean Plateau
Vlll
Wastern Ghats .a.
Vll
North East
lX
Wastern Ghats .b.
X
Eastern Ghats .b.
185
1.0
Fig. 9.2 UPGMA-SAHN clustering dendrogram constructed by the data obtained from the primer
OPB-8 in RAPD assay of Macrophomina phaseolina isolates labeled as 1–50 mpk. Geographical
clusters I to X. Scale in the dendrogram shows the genetic similarity coefficient calculated
according to Jaccard (1908).(Taken from Babu et al. 2009a)
Purkayastha et al. 2006). These techniques are useful for grouping of isolates rather
than their identification. Oligonucleotide-specific primers or probes targeting the
ITS region have been reported to selectively detect several agriculturally important
fungi such as Trichoderma, Hypocrea (Irina et al. 2005), Fusarium (Edel et al.
2000), Verticillium (Nazar et al. 1991), and Phytophthora (Lee et al. 1993). The
most interesting thing about Macrophomina is that it has only one species (Sutton
186
B.K. Babu et al.
1980) but thousands of isolates. However, the screening of the GenBank for ITS
sequences revealed the existence of very few sequences that showed some degree of
variation among the isolates. Sequence variation in the rRNA genes may allow the
use of these genes as targets for differential amplification.
PCR-Based Identification
ITS-RFLP of M. phaseolina could not detect variations within the different isolates
(Su et al. 2001, Babu et al. 2007) (Fig. 9.3). Sequencing and alignment of eight
isolates collected from different hosts and diverse ecological conditions, along with
two sequences from the GenBank, revealed various conserved and variable regions
in the ITS sequences. For a better understanding of these regions, the amplified ITS
sequence was virtually divided into five regions (Fig. 9.4). Region 4 (not depicted in
M 1 2 3 4 5
6 7
8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 M
Fig. 9.3 RFLP analysis of ITS region digested with HpaI showing similar restriction pattern with
different Macrophomina phaseolina isolates (Taken from Babu 2008)
Internal transcribed spacer 1
Internal transcribed spacer 2
AF 132795 :
U 97333 :
DQ359737 :
DQ359738 :
DQ359739 :
DQ359740 :
DQ359741 :
DQ359742 :
DQ359743 :
DQ359744 :
Region 1
110 bp
Region 2
Region 3
330 bp
Region 5
402 bp
Fig. 9.4 Development of specific oligonucleotide primers and probe: Alignment of ITS-1 and
ITS-2 sequences from eight isolates of Macrophomina phaseolina and two reference sequences
(AF132795 and U97333) from GenBank database. Nucleotides are shown as color bars (A-red,
G-yellow, T-blue and C-green). Regions 1, 2, 3 and 5 are completely aligned, 5.8S RNA gene is not
shown and the region 4 omitted because of the variability. Solid line rectangles indicate specific
nucleotide areas used for the development of specific oligonucleotide primers and the dashed ones
show the specific region used for probe designing. The position of the first nucleotide of region 1
and others are according to the reference sequence AF132795 (Taken from Babu et al. 2007)
9 Molecular Characterization and Diagnosis of Macrophomina phaseolina
187
Table 9.1 Species-specific oligonucleotides
Sl. No.
Primer/Probe
Sequence
1
MPKF1 (primer)
50 -CCG CCA GAG GAC TAT CAA AC-30
2
MPKR1(primer)
50 -CGT CCG AAG CGA GGT GTA TT-30
3
MPKH1 (probe)
50 -GCT CTG CTT GGT ATT GGG C-30
the figure) was deleted, as it contained sequences that showed variations among the
isolates of M. phaseolina. Further sequence alignment with other closely related
genera of soilborne fungi helped to identify two regions that were conserved among
Macrophomina isolates but exhibited a high degree of variability among isolates of
other genera. The two primers designed from these selected regions of ITS showed
specificity in the PCR assay. Optimization of the PCR conditions and validation of
primers yielded a specific 350-bp amplicon for M. phaseolina isolates. The absence
of the 350-bp product in other species of soilborne fungi, bacteria, and actinomycetes confirmed that the primers can be utilized to selectively and specifically
identify M. phaseolina. Thus PCR assays with primers MpKR1 and MpKF1
could be used to rapidly identify M. phaseolina.
Hybridization Probes
Further, species-specific oligonucleotide probe MpKH1 was also designed within
the ITS region (Table 9.1) (Babu et al. 2007). The DIG-labeled probe could detect
the target sequences at varying concentrations with little or no background. The
probe was also shown to be specific for M. phaseolina and no signals were obtained
with nonspecific target ITS sequences (Fig. 9.4). Though the probe would be a good
diagnostic tool for the detection within the PCR-amplified product of pure cultures,
in direct field detection with soil DNA it had shown false-positive signal and
nonspecific binding with closely related species (Babu 2008). Therefore, hybridization assays developed for M. phaseolina based on ITS region have been limited to
certain specific conditions.
9.4
Recent Developments in the Diagnostics of M. phaseolina
Previously, we demonstrated molecular identification and detection tools for
M. phaseolina (Babu et al. 2007) in which rDNA gene cluster had been selected
as a target for designing of specific primers and probe. Even though primers were
showing greater specificity, hybridization assay using DNA probe was not always
sensitive because of its small size (20 bp). Furthermore, like post-PCR analysis,
dot-blot techniques are very time-consuming and require additional skills. The
diagnostic technique has greatly improved by the introduction of real-time PCR
technology based on fluorescence detection and quantification during PCR
188
B.K. Babu et al.
amplification. Modern quantitative (qPCR) technology employing either nonspecific fluorogenic DNA-binding dyes, such as SYBR Green, or sequence-specific
fluorogenic hybridization probes, such as TaqMan (Cook and Schlitzer 1981;
Guiver et al. 2001) detection chemistry, has been described for a range of plant
pathogens (Falcao et al. 1993; Widjojoatmodjo et al. 1999; Arvanitidou et al. 2000;
Hao-Zhi and Ruey 2006) including assays for the detection both in the laboratory
(Doggett 2000; Stultz et al. 2001) and in the field (Spencer and Spencer 1997).
Therefore, recently we developed real-time qPCR assay to quantify M. phaseolina
abundance in soils and plants by using TaqMan and SYBR Green assay techniques.
The techniques were targeting on ~1 kb sequence characterized amplified region
(SCAR) of M. phaseolina, and two sets of specific primers were designed for SYBR
green (MpSyK) and TaqMan (MpTqK) assays. Both the assays were reproducible
and accurately quantified M. phaseolina population in soils and plant samples. No
cross hybridization and no increasing fluorescent signal exceeding the baseline
threshold were observed with the tested microbes, except when M. phaseolina DNA
was used as template. Limit of quantification (LOQ) of M. phaseolina DNA in
sclerotial suspension was calculated as 200 pg/ml equivalent to 1 ng, which is
equivalent to 2 104 CFU g–1 per soil. Further, we demonstrated the application
of a species-specific real-time qPCR assay useful for the detection of M. phaseolina
population in soil (Babu et al. 2009b).
9.5
Future Prospects
Sequence data in public databases are constantly increasing; as a result, integration
of more strains into detection systems of M. phaseolina will become possible, and
identification of this pathogen is likely to become an easier task which would also
help current detection and characterization methods. The resulting database will
allow the complete analysis of developmental processes that are characteristics of
the fungus, including the molecular nature of pathogenecity. Like some other
phytopathogenic fungi, in the next few years complete genome sequences might
be available for M. phaseolina also, and a combination of DNA microarrays with
other genomic methods will certainly accelerate the effort to characterize this
fungus. The escalating effect of biology, bioinformatics, and genomics may facilitate tracing out M. phaseolina genetic resources and their potential application in
disease management also.
9.6
Conclusion
In this review, an overview of our current knowledge regarding the biology of
M. phaseolina with emphasis on diagnosis is given. Although several attempts have
been made to examine the pathogenic and genetic variability of the species, further
9 Molecular Characterization and Diagnosis of Macrophomina phaseolina
189
work is needed to clarify, for example, the adaptability to multiple hosts and the
validity of species evolution in the genus Macrophomina. Similarly, our knowledge
on the PCR identification and hybridization assays for detection has been enhanced.
Therefore, further studies should be pursued to quantify the population of this
important plant pathogen in the field. Besides, diagnosis genes involved in the
pathogenesis and characterization of host-specific toxins would hasten efficient
breeding and the development of resistance traits.
Acknowledgment The work is supported by a Network Project, sponsored by Indian Council of
Agricultural Research (ICAR), Government of India, New Delhi. The authors are thankful to the
funding agency.
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among isolates of Macrophomina phaseolina using simplified AFLP technique and two
different methods of analysis. Mycologia 92:656–664
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Chapter 10
Molecular Diagnosis of Ochratoxigenic Fungi
Daniele Sartori, Marta Hiromi Taniwaki, Beatriz Iamanaka,
and Maria Helena Pelegrinelli Fungaro
Abstract Ochratoxin A (OTA) is one of the most abundant food-contaminating
mycotoxins. Its presence in several agricultural commodities has been considered a
problem worldwide. This toxin is mainly produced by two genera of fungi: Aspergillus and Penicillium. Ochratoxin A has nephrotoxic, immunosuppressive, and
carcinogenic effects; consequently, contamination with OTA presents a major risk
for human and animal health. Over the last 5 years, several studies have developed
PCR-based assays for identifying and quantifying OTA-producing fungi in food
samples. The main objective of these assays is to allow the detection of microorganisms capable of producing OTA, prior to ochratoxin production and accumulation. Several of these attempts will be reviewed and discussed in this chapter.
10.1
Introduction
Filamentous fungi can produce a vast variety of secondary metabolites and are rich
in genes that encode proteins involved in their biosynthesis (Khaldi et al. 2008). In
contrast to the primary metabolites that are common and of vital importance for all
living organisms, secondary metabolites are not necessary for survival and cellular
differentiation, and their synthesis is often limited to a single family, genus, species,
or even strain of fungus (Bennett and Ciegler 1983). The secondary metabolites
include mycotoxins, which are small organic molecules with diverse chemical
structures and biological activities. Mycotoxins are toxic compounds that are
occasionally very hazardous to animals and humans. The main source of mycotoxin
exposure is from consuming plant foods, which can be contaminated during
harvesting, transport, storage or manufacture, or even in the field (Smith and
D. Sartori, M.H. Taniwaki, B. Iamanaka, and M.H.P. Fungaro
Centro de Ciências Biológicas, Departamento de Biologia Geral, Universidade Estadual de
Londrina, Caixa Postal 6001, CEP 86051-970, Londrina-Paraná, Brazil
e-mail: fungaro@uel.br
Y. Gherbawy and K. Voigt (eds.), Molecular Identification of Fungi,
DOI 10.1007/978-3-642-05042-8_10, # Springer-Verlag Berlin Heidelberg 2010
195
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O
C
CH2
CH
OH
O
N
C
OH
O
O
H
H
CH3
CI
Fig. 10.1 The chemical structure of ochratoxin A
Henderson 1991). There is a risk to human health not only through the intake of
contaminated foods of vegetal source, but also through foods of animal origin due
to mycotoxin-contaminated animal feed ingested by animals. Due to the different
molecular structures of these mycotoxins, their influences on human and animal
health have a variety of effects; they may be neurotoxic, teratogenic, immunosuppressive, nephrotoxic, hepatotoxic, or carcinogenic (Geisen 1998). About 20 different mycotoxins are significant to human health (Geisen 1998; Bennett and Klich
2003), and demand exists for rapid and reliable techniques to detect mycotoxins and
mycotoxin producers (Russell and Paterson 2006).
Ochratoxins are a class of mycotoxins produced by some fungal species. There
are three types of ochratoxin — A, B, and C — but ochratoxin A (7-(L-b-phenylalanyl-carbonyl)-carboxyl-5-chloro-8-hydroxy-3,4-dihydro-3R-methyl isocumarin,
or OTA; Fig. 10.1) is the most toxigenic and is one of the most common food
mycotoxins. Although this toxin was described many years ago, it has only recently
begun to receive considerable attention (van der Merwe et al. 1965). As reviewed
by Petzinger and Weidenbach (2002), OTA-contaminated foods are abundant in
several countries. About 57% of approximately 6,500 food samples examined in
Europe contained amounts of OTA above the detection limit of 0.01 mg kg 1
(Wolff et al. 2000). The most important examples are grains, coffee beans, spices,
nuts, grapes, and figs (Bayman et al. 2002; Jorgensen and Jacobsen 2002; Battilani
et al. 2003; Taniwaki et al. 2003). OTA is not totally decomposed during most food
processing steps such as cooking, washing, and fermenting. Because of this, OTA
has also been detected in manufactured food products such as bread, beer, wine,
coffee, and chocolate (Jorgensen 1998; Visconti et al. 2001).
Kidneys are the main target organs of OTA. Nephrotoxic effects have been
demonstrated in all the mammalian species tested so far. For humans, there is
abundant circumstantial evidence connecting OTA ingestion with severe nephropathy (Mantle and McHugh 1993; Maaroufi et al. 1995; Wafa et al. 1998). The
carcinogenicity of OTA in rodents is also well established, although in humans a
correlation between cancer and exposure to OTA has not been proven directly.
Based on these facts, the International Agency for Research on Cancer (IARC
1993) classified OTA as a possible human carcinogen (group 2B) in 1993. More
10
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recent studies have documented significant effects of OTA on immune response.
According to Petzinger and Weidenbach (2002), these additional effects have
gained increased attention since it was observed that they may occur even at very
low concentrations of OTA.
Based on the risk that OTA presents to human health, the European Union has
imposed regulations on maximum levels of OTA in cereals and cereal products,
dried vine fruit, and all products derived from these items, as well as roasted and
soluble coffee. For dried vine fruits (raisins, currants, and sultanas), the maximum
tolerable level of OTA is set at 10 mg kg 1; the maximum level permitted in wines
and grapes is 2 mg kg 1. For raw cereal grains and all cereal-derived products for
direct human consumption, the maximum tolerable levels of OTA are 5 mg kg 1
and 3 mg kg 1, respectively. Finally, the maximum level of OTA in coffee is
5 mg kg 1 for both roasted coffee beans and ground coffee and 10 mg kg 1 for
instant coffee (Official Journal of The European Union, 2005). The European Union
is at present considering whether a maximum level for OTA should be established
in other foods, such as cocoa.
A particular species of fungus may produce several mycotoxins, but not all fungi
produce mycotoxins. In addition, the type and quantity of a certain mycotoxin are
associated with specific strains, while environmental conditions and available nutrients are determinants for the growth of the fungus and its mycotoxin production.
The economically most important OTA producers were recently reviewed by
Varga and Kozakiewicz (2006): Penicillium verrucosum in cereals (Lund and
Frisvad 2003); Aspergillus niger and A. carbonarius in grapes (Battilani and Pietri
2002); Aspergillus ochraceus, A. niger and A. carbonarius in coffee (Bucheli and
Taniwaki 2002; Taniwaki et al. 2003), and Aspergillus alliaceus in figs (Bayman
et al. 2002). However, recent advances in molecular biology and fungal metabolite
analysis resulted in the description of some important new OTA-producing species
by European researchers (Frisvad et al. 2004). Aspergillus westerdijkiae, which
closely resembles A. ochraceus, is now recognized as the main OTA producer in
coffee.
The severe consequences of OTA contamination demand efficient and costeffective methodologies for detecting OTA producers in food. In this chapter, we
present some of the relevant molecular approaches that have been used to detect and
quantify the main OTA producers in food.
10.1.1 Molecular Markers for the Detection of Ochratoxigenic
Fungi
The traditional schemes for the isolation and identification of ochratoxigenic fungi
from food samples are time-consuming and require a high knowledge of fungal
taxonomy. Even with taxonomic expertise, identification is commonly difficult in
some genera of fungi that contain a large number of closely related species. The
application of molecular biology techniques can help to overcome these problems
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because it can reduce the time for identification from days to hours and also allow
precise species identification. Polymerase chain reaction (PCR) is a technique that
was developed in 1985 for the in vitro amplification of specific segments of DNA
(Saiki et al. 1985; Mullis and Faloona 1987). This technique has allowed the precise
identification and fast detection of ochratoxigenic species without the need for
isolating pure cultures.
The selection of target sequence specific for a given mycotoxin-producing
fungus is a key process in the development of a PCR-based diagnostic assay.
These target sequences used for designing PCR primers may be didactically divided
into two groups: (a) anonymous DNA sequences and (b) functional genes (Carter
and Vetrie 2004). Anonymous DNA sequences are obtained from an unbiased
sample of genomic DNA and may or may not contain functional genes. Developing
markers from anonymous sequences requires comparative analyses between the
DNA profiles of related species generated from randomly amplified fragments by
random amplified polymorphic DNA (RAPD) or amplified fragment length polymorphism (AFLP) (Williams et al. 1990; Vos et al. 1995). Both methodologies have
proven to be powerful taxonomic instruments, especially at low taxonomic positions. The amplification patterns produced by RAPD and AFLP analysis allow
discrimination between species and distinct isolates of a single species. Polymorphisms are recognized by the presence or absence of amplified fragments at each
RAPD or AFLP locus. DNA bands that are exclusively present in all isolates of a
certain toxigenic species may be cloned and sequenced. Once an RAPD or AFLP
marker is sequenced, it can be converted into a robust PCR-based marker. Thus,
RAPD and AFLP have been applied successfully for revealing specific marker
sequences (Schmidt et al. 2003, 2004b; Fungaro et al. 2004a; Sartori et al. 2006).
Such sequences have been used to design species-specific primers that allow the
identification and detection of some ochratoxigenic species in food samples.
As mentioned above, the sequences of functional genes may also be used as
targets for PCR primers to detect mycotoxigenic fungi. However, in contrast to
other mycotoxins, the OTA biosynthetic pathway has not been well characterized in
any of the OTA-producing species; consequently, the genes that encode enzymes
involved in the biosynthesis of this secondary metabolite are poorly known.
Because of this, the several PCR-based assays developed during the last 5 years
have used genes that were not associated to mycotoxin biosynthesis: ribosomal
RNA, b-tubulin, and calmodulin genes (Perrone et al. 2004; Patiño et al. 2005;
Morello et al. 2007).
10.1.2 PCR-Detection and Quantification of Ochratoxigenic
Species with Sequences Not Associated to Mycotoxin
Biosynthesis
Ochratoxin A was discovered as a secondary metabolite of A. ochraceus strains,
which belongs to Aspergillus section Circumdati. Based on a polyphasic taxonomy,
10
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199
which takes into account all accessible phenotypic and genotypic data and integrates them in a consensus classification, 20 species are distinguished into Aspergillus section Circumdati. The taxonomy of this section remains in progress,
and Frisvad et al. (2004) recently proposed the division of A. ochraceus into two
species, A. ochraceus and A. westerdijkiae. Several species in the section Circumdati are able to produce OTA in culture medium, but the main culprit species for the
presence of OTA in food are A. ochraceus and A. westerdijkiae (Frisvad et al. 2004).
A. westerdijkiae and A. ochraceus are very similar, and several isolates previously identified as A. ochraceus are now recognized as A. westerdijkiae, including
the original OTA-producing strain (NRRL 3174). Amplification and sequencing of
the ITS1-5.8S-ITS2 region from several Brazilian strains of both species showed
specific nucleotide variations that distinguish A. westerdijkiae and A. ochraceus
(Fungaro et al. 2004b). In ITS1, all sequences of A. westerdijkiae differed from the
A. ochraceus sequences by possessing a C instead of a T at positions 76 and 80. In
addition, A. ochraceus has a deletion of a T at position 89. In ITS2, specific
nucleotides at position 494–495 (AT) characterized the strains of A. westerdijkiae,
compared to a TC at this position in A. ochraceus. Moreover, a T at position 487 is
deleted only in A. ochraceus strains. Similarly, Morello et al. (2007) detected 39
species-specific single nucleotide polymorphisms within the b-tubulin genes from
A. westerdijkiae and A. ochraceus, most of them (97.4%) in intronic regions.
Eleven nucleotide substitutions and one heptanucleotide insertion/deletion were
found in intron 3 (107 bp). Intron 4 (103 bp) was found to have six substitutions, one
pentanucleotide insertion/deletion, and one dinucleotide insertion/deletion. Seven
substitutions were found in intron 5 (87 bp).
The first report of a diagnostic PCR assay for A. ochraceus occurred in 2003
(Schmidt et al. 2003). The authors investigated the genetic relatedness among 70
strains with AFLP markers. A certain number of AFLP bands characteristic for
A. ochraceus were detected. Three of these bands were cloned and sequenced, after
which the sequences were used to design three primer pairs specific for A. ochraceus. The specificity of the primer pair OCA-V/OCA-R (Table 10.1) was tested
with DNA of several different target strains as well as the closely related Aspergillus and Penicillium spp. and DNA isolated from noninfected green coffee. However, this primer pair is able to amplify DNA sequence from both A. ochraceus and
A. westerdijkiae because it was developed previous to the division of formal
A. ochraceus species into the two species mentioned above.
Patiño et al. (2005) developed a specific PCR assay (OCRA1/OCRA2;
Table 10.1) for the detection of A. ochraceus on the basis of ITS sequence
comparison between several strains of Aspergillus species. The specificity of the
primer pair was tested on a number of Aspergillus, Penicillium, Cladosporium,
Botrytis, and Alternaria strains commonly associated with grapes, cereals, and
coffee. A single fragment of about 400 bp was only amplified from the genomic
DNA of A. ochraceus strains. No product was amplified from genomic DNA from
Aspergillus isolates other than A. ochraceus or from other genera. According to the
authors, the sensitivity of the PCR assay based on ITS sequences was higher (1 and
10 pg of DNA template per reaction) than one based on a single copy gene (0.1 and
Reference
Schmidt et al. (2003)
200
Patiño et al. (2005)
Dao et al. (2005)
Morello et al. (2007)
Sartori et al. (2006)
Patiño et al. (2005)
Dobson and
O’Callaghan (2004)
Mulè et al. (2006)
Schmidt et al. (2004a, b)
Atoui et al. (2007)
Fungaro et al. (2004a)
Selma et al. (2008)
Perrone et al. (2004)
Dobson and
O’Callaghan (2004)
Bogs et al. (2006)
Geisen et al. (2004)
D. Sartori et al.
Table 10.1 Primer sequences used for the detection of ochratoxin-A producing fungi
Species
Utility
Target region
Primer pair
A. ochraceus
Species-specific detection
AFLP marker
F50 ATACCACCGGGTCTAATGCA
R50 TGCCGACAGACCGAGTGGATT
A. ochraceus
Species-specific detection
rRNA gene
F50 CTTCCTTAGGGGTGGCACAGC
R50 GTTGCTTTTCAGCGTCGGCC
A. ochraceus
Species-specific detection
pks gene
F50 CATCCTGCCGCAACGCTCTATCTTTC
R50 CAATCACCCGAGGTCCAAGAGCCTCG
A. westerdijkiae
Species-specific detection
b-tubulin gene
F50 TGATACCTTGGCGCTTGTGACG
R50 CGGAAGCCTAAAAAATGAAGAG
and quantification
A. niger
Species-specific detection
RAPD marker
F50 CAGTCGTCCAGTACCCTAAC
R50 GAGCGAGGCTGATCTAAGTG
A. carbonarius
Species-specific detection
rRNA gene
F50 GCATCTCTGCCCCTCGG
R50 GGTTGGAGTTGTCGGCAG
A. carbonarius
Species-specific detection
pks gene
F50 TGGGTATGCGCGGGGTGAGGGTAT
R50 CCGTAGGCTTCGAAAAACTGACAC
A. carbonarius
Specie-specific detection
cmdA gene
F50 CCGATG GAGGTCATGACATGA
R50 AATGCGAACCGGATATTAACTTCTG
and quantification
A. carbonarius
Species-specific detection
AFLP marker
F50 GAATTCACCACACATCATAGC
R50 TTA ACTAGGATTTGGCATTGA AC
A. carbonarius
Specie-specific detection
pks gene
F50 AATATATCGACTATCTGGACGAGCG
and quantification
R50 CCCTCTAGCGTCTCCCGAAG
A. carbonarius
Species-specific detection
RAPD marker
F50 AGGCTAATGTTGATAACGGATGAT
R50 GCTGTCAGTATTGGACCTTAGAG
A. carbonarius
Species-specific detection
pks gene
F50 CCCTGATCCTCGTATGATAGCG-30
R50 CCGGCCTTAGATTTCTCTCACC-30
A. carbonarius
Species-specific detection
cmdA gene
F50 AAGCGAATCGATAGTCCACAAGAATAC
R50 TCTGGCAGAAGTTAATATCCGGTT
P. verrucosum
Species-specific detection
pks gene
F50 TGCACGACCGGGACAACATCA
R50 CCGTAGGCCTCCACAAAATCTG
P. nordicum
Species-specific detection
nrps gene
F50 AGTCTTCGCTGGGTGCTTCC
R50 CAGCACTTTTCCCTCCATCTATCC
P. nordicum
Species-specific detection
pks gene
F50 TACGGCCATCTTGAGCAACGGCACTGCC
R50 ATGCCTTTCTGGGTCCGATA
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Molecular Diagnosis of Ochratoxigenic Fungi
201
1 ng of DNA template per reaction). The authors did not mention the new species
A. westerdijkiae, and the primer pair presumably does not distinguish between
A. westerdijkiae and A. ochraceus.
Morello et al. (2007) further exploited the genetic variation found between the
b-tubulin gene sequences obtained from A. ochraceus and A. westerdijkiae with the
aim of developing primers specific for A. westerdijkiae. The primer pair Bt2Aw-F/
Bt2Aw-R was designed to specifically amplify A. westerdijkiae (Table 10.1).
A 347-bp amplicon was visualized in all A. westerdijkiae isolates, but no PCR
product was observed in A. ochraceus isolates. The Bt2Aw primers were successfully applied in detecting the 347-bp amplicon when using DNA collected from
coffee beans inoculated with A. westerdijkiae.
The ochratoxigenic species Aspergillus carbonarius and A. niger belong to
section Nigri, which is an important group of species in food mycology. As
discussed in Samson et al. (2007), black aspergilli are one of the more complex
groups in terms of classification and identification, and numerous taxonomic
schemes have been proposed. The differences between some species belonging to
section Nigri are very slight and their discrimination requires molecular analysis. A
total of 16 species are recognized in Aspergillus section Nigri: A. aculeatus,
A. brasiliensis, A. carbonarius, A. costaricaensis, A. ellipticus, A. ellipsoides,
A. japonicus, A. foetidus, A. homomorphus, A. heteromorphus, A. lacticoffeatus,
A. niger, A. piperis, A. sclerotioniger, A. tubingensis, and A. vadensis, with the
latter taxon recently described as a new species (Samson et al. 2004; de Vries et al.
2005). A. niger sensu stricto, A. tubingensis, A. foetidus and A. brasiliensis are
morphologically identical and collectively have been called the A. niger aggregate
(Parenicová et al. 2001). Although the taxa included in the A. niger aggregate are
morphologically indistinguishable, they differ in their ability to produce OTA and
other metabolites. The ability of species other than A. niger sensu stricto within
A. niger aggregate to produce OTA remain uncertain, probably due to the complexity
of species identification.
PCR-restriction fragment length polymorphism (RFLP) analysis of the ITS15.8S-ITS2 region allows the four A. niger aggregate taxa to be classified in two
patterns (N and T). A. foetidus and A. tubingensis are classified as type T, and
A. niger and A. brasiliensis are classified as type N by the Cabañes group (Accensi
et al. 1999; Accensi et al. 2001). According to these authors, all OTA-producing
strains were classified as pattern N, while none of the pattern T isolates produced
OTA. Ueno et al. (1991) described an A. foetidus isolate that is able to produce
OTA. However, according to Samson et al. (2004), no strains of A. foetidus sensu
stricto produce OTA. Consistent with this analysis, the strain CBS 618.78 of
A. foetidus that was described as an OTA producer was later shown to be A. niger
and not A. foetidus (Samson et al. 2004).
Although it was assumed for several years that A. tubingensis was not able to
produce OTA (Samson et al. 2004), two research groups recently found OTAproducing isolates of this species (Medina et al. 2005; Perrone et al. 2006). We have
analyzed several isolates within the A. niger aggregate (obtained from Brazilian
coffee beans and dried fruit from worldwide origin) in our own laboratory and
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D. Sartori et al.
found that only A. niger sensu stricto was an OTA producer; i.e., none of the
A. tubingensis or A. foetidus isolates analyzed was able to produce OTA (unpublished data). This situation demonstrates the importance of the development of
specific markers for the identification and detection of a particular ochratoxigenic
fungal species.
A specific PCR assay for the detection of A. carbonarius was developed by
Patiño et al. (2005) based on ITS sequences. The primer pair CAR1/CAR2 generated an amplicon of 420 bp exclusively from A. carbonarius genomic DNA
(Table 10.1). Schmidt et al. (2004b) used AFLP to detect specific markers for
A. carbonarius. A certain number of amplified fragments were found to be specific
to this species. The marker fragments were cloned, sequenced, and used to design a
specific primer pair to detect this species. The primer pairs A1B-fw/A1B-rv and
C1B-fw/C1B-rv amplify 189 bp and 351 bp fragments, respectively, in all A. carbonarius isolates tested (Table 10.1). Based on an alignment of calmodulin (cmdA)
gene sequences, Perrone et al. (2004) identified regions suitable to design specific
PCR primers for the detection of A. carbonarius. The primer pair CARBO1/
2 produced a PCR product of 371 bp with a sensitivity of about 12 pg when using
pure total genomic DNA. Although the PCR assay was useful in screening isolates
of black aspergilli from grapes, the authors did not use it to detect A. carbonarius
strains directly from sample materials.
Several strains representing closely related black aspergilli, i.e., A. carbonarius,
A. niger, and A. tubingensis, were analyzed by RAPD with the aim of developing
species-specific primers for the detection of A. carbonarius in coffee beans
(Fungaro et al. 2004a). A typical RAPD pattern is shown in Fig. 10.2. Some
Fig. 10.2 Amplification of polymorphic DNA from A. niger (lanes 1–6), A. tubingensis (lanes
7–18), and A. carbonarius (lanes 19–24) strains with the OPX7 random primer. The molecular
weight standard (M) is a 1-kb DNA ladder
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DNA bands were present in all A. carbonarius strains and absent in all strains of
A. niger and A. tubingensis. One of these bands was cloned and sequenced, and then
used to design a primer pair specific to A. carbonarius (OPX7809-F/OPX7809-R)
(Table 10.1). Using this primer-pair, the authors successfully detected an amplicon
of 809 bp when DNA from coffee beans infected with A. carbonarius strains was
used. No cross-reaction was observed with DNA from coffee beans infected with
closely related black aspergilli. Similarly, based on RAPD markers, Sartori et al.
(2006) developed specific primers to detect A. niger (Table 10.1). The primer pair
denoted OPX7372F/ OPX7372R generated an amplicon of 372 bp in all A. niger
stricto sensu isolates, and no amplification product was observed in reactions using
DNA from related species. This PCR assay was successfully applied in detecting
A. niger in coffee beans.
Brazil is the largest coffee bean producer and exporter in the world. Studies
concerning fungi with the potential for colonizing Brazilian coffee beans and
producing OTA showed that A. ochraceus (now A. westerdijkiae), A. carbonarius,
and A. niger are the major species in Brazilian coffee beans. Based on this
observation, our group developed a multiplex PCR assay that can detect these
three target fungi species directly from coffee bean samples (Sartori et al. 2006).
Multiplex PCR (m-PCR) is a procedure that allows the simultaneous amplification
of more than one target sequence in a single PCR reaction, decreasing the number
of reactions that must be performed to assess the possible presence of different
species in a food sample. Sartori et al. (2006) first analyzed the value of the m-PCR
assay with DNA obtained from coffee beans inoculated with these three species.
Figure 10.3a shows the amplification profiles from simultaneous use of the primer
pairs designed for A. westerdijkiae, A. carbonarius, and A. niger. Amplification
products of 260, 809, and 372 bp in a single PCR reaction confirmed the presence of
Fig. 10.3 (a) Amplification products obtained from DNA isolated from inoculated coffee beans.
Lane 1: DNA from coffee beans inoculated with A. ochraceus amplified with OCA V and OCA R
primers; lane 2: DNA from coffee beans inoculated with A. niger amplified with OPX7F372 and
OPX7R372 primers; lane 3: DNA from coffee beans inoculated with A. carbonarius amplified with
OPX7F809 and OPX7R809 primers; lane 4: multiplex PCR using DNA from coffee beans inoculated with A. ochraceus, A. niger, and A. carbonarius amplified with all three sets of primer pairs;
lane 5: negative control (DNA from coffee beans without fungal inoculation); lane 6: positive PCR
control (A. niger DNA amplified with the primers ITS1 and ITS4). (b) Multiplex PCR obtained
from naturally contaminated coffee beans. Lane 1: detection of A. niger; lane 2: no fungi detected;
lane 3: detection of A. niger; lane 4: detection of A. niger and A. ochraceus; lane 5: no fungi
detected; lane 6: detection of A. niger and A. ochraceus; lane 7: positive control of the multiplex
assay (DNA from coffee beans inoculated with A. carbonarius, A. niger and A. ochraceus).
Reproduced from Sartori et al. (2006) with permission)
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D. Sartori et al.
A. westerdijkiae, A. carbonarius, and A. niger, respectively. The usefulness of the
multiplex PCR assay was also analyzed in coffee bean samples collected on farms.
As shown in Fig. 10.3b, this methodology successfully allowed the detection of
amplification products from naturally occurring fungi in coffee beans.
Penicillium verrucosum has been commonly isolated from cereal crops and is
the principal OTA-producing fungus in cool, damp climatic regions (Pitt and
Hocking 1997). This species is morphologically very similar to the related species
P. nordicum, which is mainly isolated from proteinaceous foods like cheese and
fermented meat (Larsen et al. 2001; Castellá et al. 2002). P. nordicum is a high
OTA producer in vitro, but until now the ability of this species to produce OTA in
its natural environment has not been tested (Bogs et al. 2006).
Castellá et al. (2002) used RAPD, AFLP, and ITS sequencing to characterize two
groups of Penicillium OTA-producing strains that differed in their ability to produce
OTA, with group I containing mainly high-producing strains, and group II containing moderate to nonproducing strains. The strains from group I originate from foods,
such as cheese and meat products, while the strains from group II originate from
plants. The ribosomal ITS1-5.8S-ITS2 sequences were similar, except for two single
nucleotide exchanges in several strains of each group. Group I was recognized as P.
nordicum and Group II as P. verrucosum. The authors did not attempt to design
species-specific primers to detect either species of Penicillium.
Although conventional PCR is a valuable tool for detecting and monitoring
mycotoxigenic fungi, it is not appropriate to quantify a given fungus species in a
food sample. Small differences in reaction efficiency per cycle can result in a
substantial difference in the final product quantity, and so it is very difficult to
extrapolate the initial concentration of the template in the sample from the final
product (Hill 1996). Fortunately, the introduction of the real-time PCR technology
has increased the reliability of PCR results compared to those obtained by conventional methods, thus opening new avenues for quantifying ochratoxigenic fungi in
food. Real-time PCR is more sensitive than classical PCR and does not require gel
electrophoresis. The analysis can be concluded in less than 5 h. These attributes of
real-time PCR significantly reduce time and manual labor, making it appropriate for
large-scale analyses.
The use of fluorophores is common to most of these methods and is described in
detail by Boysen et al. (2000). By using real-time PCR it is possible to detect an
increase in fluorescence emission during the reaction which is proportional to the
initial copy number of the target sequence. The initial amount of template DNA is
inversely proportional to a parameter measured for each reaction, which is denoted
as the threshold cycle (Ct). The Ct value is the PCR cycle when the fluorescence
signal increases above the background threshold. The application of this method to
natural samples can provide an estimate of infection by a given species.
Because A. westerdijkiae consistently produces large amounts of OTA, Morello
et al. (2007) evaluated the potential of the real-time PCR approach for quantification of this species in coffee beans (Fig. 10.4). A real-time PCR standard curve was
obtained with a range of initial amounts of A. westerdijkiae total DNA (20; 10; 5;
1; 0.5 and 0.1 ng per reaction) showing a good correlation (r2 ¼ 0.982). Green
10
Molecular Diagnosis of Ochratoxigenic Fungi
205
1.2
1.1
A westerdijkiae 142
1
A ochraceus 14A
0.9
Blank
Fluorescence
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
5
10
15
20
25
Cycle
30
35
40
4
b
Fig. 10.4 Discrimination between A. westerdijkiae and A. ochraceus by (a) conventional PCR and
(b) real-time PCR. Reproduced from Morello et al. (2007) with permission
coffee beans were inoculated with 106 A. westerdijkiae conidia and incubated for
192 h at 28 C. DNA extraction and a colony forming unit (cfu) assay were
performed every 48 h. A high correlation was observed between the cfu data and
the fungal DNA content in the coffee beans (Fig. 10.5). The authors also assessed
the sensitivity of this method in order to detect A. westerdijkiae in coffee beans.
Serial dilutions (10 1–10 9) of DNA extracted from infected coffee beans after
48 h of incubation generated a positive signal at up to 10 5 dilution, showing that
less than 10 and more than 1 single copy of the A. westerdijkiae haploid genome can
be detected by this methodology. This value also indicated that less than 10 haploid
genomes could be detected per 0.1 g of coffee beans. Thus, the real-time PCR assay
was more than 100 times more sensitive than the cfu technique.
A quantitative real-time PCR assay was developed to detect and quantify
A. carbonarius in grapes as a possible tool for predicting potential ochratoxigenic
risk (Mulè et al. 2006). The species-specific primers and probes used by the authors
were derived from conserved regions of the A. carbonarius calmodulin gene.
The quantification of fungal genomic DNA in naturally contaminated grapes was
performed using the TaqMan signal versus spectrophotometrically measured DNA
quantities (log10) calibration curve with a linearity range from 50 to 5 10 4 ng of
DNA. A positive correlation (r2 ¼ 0.92) was found between A. carbonarius DNA
content and OTA concentration in naturally contaminated grape samples.
D. Sartori et al.
9
9
8
8
7
7
6
6
5
5
4
4
3
Log cfu/coffee bean
2
Log copy number/coffee bean
1
r = 0.859293
0
0
48
95
Time (hours)
144
3
2
1
0
192
Log copy number/coffee bean
Log cfu coffee bean
206
Fig. 10.5 Comparison of cfu data and the haploid genome copy number of A. westerdijkiae in
inoculated coffee beans. Reproduced from Morello et al. (2007) with permission
The sensitivity of the PCR method is crucial in the detection of foodborne
microorganisms. Unfortunately, there is no standard for reporting sensitivity.
Some authors refer to sensitivity as the minimum picograms of DNA that can be
detected (Bluhm et al. 2002; Schmidt et al. 2004a; Patiño et al. 2005), others refer to
it as the minimum percentage of infected grains in a sample (Schmidt et al. 2004a),
and more recently, the lowest detectable number of haploid genomes was also used
(Mulè et al. 2006). To eliminate confusion and uncertainties regarding sensitivity, a
single method for sensitivity calculation should be adopted. We suggest that the
number of haploid genomes per gram of sample is the most convenient metric with
which to indicate PCR sensitivity.
10.1.3 PCR-Based Detection and Quantification
of Ochratoxigenic Species with Biosynthetic
Pathway Genes
Various enzymes can be expected to catalyze key reactions in the formation of OTA
based on its structure. Some teams of researchers are currently looking for genes
related to OTA biosynthesis (Lebrihi et al. 2003; Geisen et al. 2004; Atoui et al.
2006; O’Callaghan et al. 2006; Bogs et al. 2006). A polyketide synthase is predicted
to be involved in OTA biosynthesis because the isocoumarin group of OTA is a
pentaketide likely to be formed from acetate and malonate via a polyketide synthesis pathway (O’Callaghan et al. 2003).
The diversity of polyketide synthase genes has been investigated in A. carbonarius
(Atoui et al. 2006). Two nonconserved sequences in the acyltransferase domain of
a polyketide synthase gene, denoted Ac12RL3, were used as a target sequence to
specifically detect A. carbonarius by PCR. The primer pair Ac12RL_OTAF/
10
Molecular Diagnosis of Ochratoxigenic Fungi
207
Ac12RL_OTAR (Table 10.1) generated a 141-bp PCR product in all A. carbonarius
isolates studied, while no other species gave a positive result with this PCR primer set
(Atoui et al. 2007). This specific primer pair was successfully employed to directly
quantify A. carbonarius in grape samples.
With the same objective, i.e., to quantify A. carbonarius in grape samples, Atoui
et al. (2006) used a specific primer pair (Ac12RL_OTAF/Ac12RL_OTAR)
(Table 10.1) that was designed from the acyltransferase (AT) domain of the
polyketide synthase sequence (Ac12RL3) to amplify a 141-bp PCR product.
Using real-time PCR conjugated with SYBR Green I dye, the authors found a
positive correlation (r2 ¼ 0.81) between A. carbonarius DNA content and OTA
concentration in 72 grape samples.
A real-time PCR system based on the otapksPN sequence was used to monitor the
growth and OTA production of P. nordicum in wheat (Geisen et al. 2004). A strong
correlation between the copy numbers of the otapksPN gene and cfu was observed.
Several analytical methods for the detection of OTA are available, and the level
of this mycotoxin can readily be measured very accurately in food. However, this
kind of analysis only returns a positive result once the toxins have been formed.
Similarly, several methods for the detection of ochratoxigenic species have been
described, but the presence of an ochratoxigenic fungus in a food sample does not
ultimately indicate the production OTA. The formation of OTA depends strongly
on environmental conditions such as substrate, water activity, pH, and temperature.
Based on these points, the measurement mycotoxin gene expression would allow
more meaningful monitoring of OTA in food; these genes are frequently expressed
some days prior to the mycotoxin production and thus would allow an early warning
(Schmidt-Heydt and Geisen 2007). According to some authors, the expression
analysis of key mycotoxin biosynthetic genes might be useful as Hazard Analysis
and Critical Control Point (HACCP) for the food industry (Geisen et al. 2004;
Niessen 2007).
The first relevant report of the cloning and characterization of putative polyketide
synthase gene (pks) from OTA-producing Aspergillus was provided by O’Callaghan
et al. (2003). These authors used a molecular strategy denoted “Suppression Subtractive Hybridization PCR-Based.” The predicted amino acid sequence of a 1.4-kb
clone shared 28–35% identity with acyltransferase regions from fungal polyketide
synthases found in the databases. Based on reverse transcription PCR studies, the
authors showed that this pks gene is expressed only under OTA-permissive conditions and only during the early stages of mycotoxin synthesis. A mutant in which
the pks gene has been interrupted was not able to synthesize OTA. The authors later
examined OTA production by A. ochraceus grown under different nutritional and
environmental conditions. Quantifications of pks transcript accumulation showed
that pks transcription is tightly linked to OTA production (O’Callaghan et al. 2006).
As reviewed by Niessen (2007), the University College Cork (Ireland) filed world
wide (WO 2004/072224) as well as European (EP 1592705A2) patent applications
based on Irish priority application (IE 20030095) based on O’Callaghan’s results.
The patent claims cover the use of the sequence for the purpose of detecting OTA
producers as well as its use for primer walking.
208
D. Sartori et al.
Geisen et al. (2004) used degenerate primers to detect and characterize a portion
of a polyketide synthase gene from Penicillium nordicum. All analyzed P. nordicum
strains possessed the fragment, whereas the closely related ochratoxigenic
P. verrucosum strains did not. An expression analysis of this gene demonstrated
that it is highly induced under OTA-producing conditions but only at low levels
under nonproducing conditions. In addition, a strong congruence between
otapksPN gene expression and OTA production in wheat was observed.
Microarray technology is suitable to analyze gene expression on a global level
and may be useful for detecting mycotoxigenic fungi before mycotoxins are
produced. For this purpose, the mRNA from a given sample is used to generate a
labeled sample, termed the “target,” which is hybridized with a large number of
DNA sequences that are immobilized on a solid surface in an ordered array.
Schmidt-Heydt and Geisen (2007) developed a microarray (DNA chip) that contains oligonucleotides homologous to genes from several fungal species that are
responsible for the biosynthesis of mycotoxins. Consequently, this microarray
covers most of the known relevant mycotoxin biosynthesis genes.
However, it is important to state that although this gene is really more expressed
by a positive strain under OTA-permissive conditions, no information is available
about the expression of this gene by OTA-nonproducing strains. A preliminary
investigation carried out by our group showed that the pks gene, described
by O’Callaghan et al. (2003), is in fact significantly more expressed by A. westerdijkiae when grown in OTA-permissive conditions than when grown in OTArestrictive conditions. However, when we cultivated two negative strains in
permissive conditions, the pks gene was expressed at levels similar to those of as
a positive strain, even though they did not produce OTA (unpublished data). This
probably occurs because other secondary metabolites require the function of the pks
gene. This observation stresses the importance of identifying genes that are differentially expressed between OTA-producing strains and OTA-nonproducing strains.
10.2
Conclusions
Over the last 5 years, several molecular assays for the identification and fast
detection of ochratoxigenic species without the need for isolating pure cultures
have been published. These assays include conventional PCR, real-time PCR, RT
real-time PCR, and microarray technology. Until now, they have been used in
research laboratories to detect putative mycotoxin-producing fungi in culture or
even in food samples to obtain information on the epidemiology and ecology of
ochratoxigenic species or to acquire basic information on gene expression. The use
of molecular assays in routine analyses in the food and feed industries remains a
challenge. Specificity, sensitivity and simplicity of analysis are all areas that must
be improved before these molecular assays become useful for practical applications. Furthermore, OTA biosynthesis is poorly understood relative to the synthesis
pathways of other economically important mycotoxins. Better knowledge of the
10
Molecular Diagnosis of Ochratoxigenic Fungi
209
genes involved in OTA biosynthesis is necessary to effectively predict the risk of
OTA production. Even so, we are optimistic that molecular technologies will be
useful for large-scale analyses in the near future, and will be regularly used as a
preventive approach to minimize ochratoxin entry into the food chain.
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Chapter 11
Molecular Barcoding of Microscopic Fungi
with Emphasis on the Mucoralean Genera
Mucor and Rhizopus
Youssuf Gherbawy, Claudia Kesselboth, Hesham Elhariry,
and Kerstin Hoffmann
Abstract A broad range of fungi were isolated from different geographic regions
and substrates and identified according to traditional and modern methods. A total
of 120 different isolates were assigned to the phyla, Basidiomycota with 8 isolates,
Ascomycota with 75 isolates, and “Zygomycota” with 37 isolates. Although morphological characters were able to differentiate the isolates to their phyla and in most
cases to the correct genera, a combination of several methods is always recommended because characterization and identification of unknown fungal isolates is
highly error-prone if relying on single methods. Sequence-based identification turned
out to be reliable for most Ascomycetes and Zygomycetes. But with the ongoing
questionable trend to rely on sequences as first source information for species
separation, the most serious problems are the annotation problems in public reference databases, the inconsistency of described taxa, and the available reference data.
11.1
Introduction and Background
The characterization and identification of organisms is fundamental in biological
life sciences. Each individual in general is regarded to be composed of numerous, if
not countless, characters. Every definable character could be used for descriptive
and comparative studies concerning all applied aspects of life. Such characters could
be features of morphology, biochemical composition, physiological characters,
Y. Gherbawy and C. Kesselboth
Botany Department, Faculty of Science, South Valley University, 83523 Qena, Egypt
K. Hoffmann
Institute of Microbiology, School of Biology and Pharmacy, University of Jena, Neugasse 25,
07743 Jena, Germany
e-mail: Hoffmann.Kerstin@uni-jena.de
H. Elhariry
Biological Sciences Department, Faculty of Science, Taif University, P.O. Box 888 Taif, Kingdom
of Saudi Arabia
Y. Gherbawy and K. Voigt (eds.), Molecular Identification of Fungi,
DOI 10.1007/978-3-642-05042-8_11, # Springer-Verlag Berlin Heidelberg 2010
213
214
Y. Gherbawy et al.
ecological properties, metabolic characteristics, or molecular features ranging from
mere nucleotide and amino acid sequences to structures, functions, and regulation.
Molecular data have several advantages over other characters because they are
not subjected to the highly subjective eye of an investigator if morphological
criteria are investigated. Also, they are independent from environmental or nutritional conditions influencing metabolism, cell composition, or cellular appearance.
Moreover, molecular data by means of nucleic acid sequences are quite easy to
access compared to chemotaxonomical criteria, which require cost-intensive laboratory equipment, as for performance of gas chromatography–mass spectrometry.
A major drawback is that chemotaxonomical markers are prone to external influences and physiological variability and therefore hard to reproduce. But a solely
single nucleotide sequence of a certain gene marker is not capable to designate an
organism to a species or reveal the actual features displayed by that organism. In the
end, a pure sequence is useless information without further data on the organism of
its origin, the locality of its isolation, and its preferred substrate. In this respect, the
identification of an organism must not depend on single methods; it should rather be
supported by a bunch of different criteria. Comparing and analysing all available
data gives insight into the biodiversity of the Earth and allows the reconstruction of
the evolutionary history of the organism. Well-supported taxonomic relationships
are necessary for the precise and reliable classification of new and unknown specimens. Consequently, the reconstruction of phylogenetic relationships works for
well-studied species only, if based solely on molecular information without knowledge of morphological, physiological, or ecological features. The exploration of
new specimens clearly depends on more than one criterion. Taxonomic systems
based on reconstructed phylogenetic relationships are essential for a sustainable
organisation of biological information and a deeper understanding of the evolution
and species diversification (Fenchel and Finlay 2006; Wheeler 2004). Identification
and classification of unknown specimens requires a broad sample of well-defined
and described reference specimens for comparison (Meyer and Paulay 2005; Hoffmann et al. 2009b). Storage of available information in public databases, and type
strains maintained and accessible from culture collections, as well as a consensus in
taxonomical classification through the scientific community, are indispensable for
precise assignments of species.
At the present time, the trend tends to rely mainly if not exclusively on molecular
data to identify biological specimens with the focus on so-called “DNA barcodes”,
a term created in 1993 (Arnot et al. 1993). The now well-established Consortium
for the Barcode of Life (CBOL, http://barcoding.si.edu) is aimed to coordinate the
research on DNA barcodes and to establish global standards with an open-access
database about species diversity.
The search for the universal barcode marker, which distinguishes all living
beings or at least large organismic groups is presently a subject of heavy scientific
debate. So far, the most promising barcodes for the identification of animals are
sequences of the mitochondrial cytochrome oxidase subunit I (CO1 or cox1)
(Hebert et al. 2003). cox1 has been successfully applied in various studies identifying a broad range of taxa (Hebert et al. 2004a, b; Johnson and Cicero 2004; Tavares
and Baker 2008). But cox1 shows also some applicational difficulties, for instance
11
Molecular Barcoding of Microscopic Fungi with Emphasis
215
in the differentiation of parapatric species which do not share a common ecological
habitat (Moritz and Cicero 2004; Aliabadian et al. 2009). Additional promising
sequences for metazoan phylogenetics target the small ribosomal subunit (16S
rDNA), the internal transcribed spacer (ITS), and the cytochrome b (cob) (Bradley
and Baker 2001; Helbig and Seibold 1999; Lemer et al. 2007; Park et al. 2007;
Vences et al. 2005). Although cox1 was also proven to be suitable for the identification of algae (Saunders 2005), it is not useful for land plants because of the high
intra– interspecific variability in the evolutionary rates of the mitochondrial DNA.
An applicable DNA barcode marker for land plants is still discussed. The nuclear
ITS region, the plastid trnHspbA intergenic spacer, and the rbcL gene were suggested by several authors (Chase et al. 2005; Kress et al. 2005; Kress and Erickson
2007; Newmaster et al. 2006). For fungi, cox1 is also proposed and was successfully
tested for Penicillium (Seifert et al. 2007). But, introns, which were reported
occasionally (Woo et al. 2003), or the lack of mitochondrial genomes arising
from missing mitochondria in anaerobic gut fungi (Yarlett et al. 1986), as well as
non-vertical inheritance of mitochondrial genes caused by parasexuality-driven
hyphal anastomoses over the species barrier, disqualifies cox1 as the universal
marker for fungi. However, alternative barcode markers like the widely used
internal transcribed spacer (ITS) region of the nuclear ribosomal DNA cluster are
in some cases insufficiently variable to reliably separate the species apart (Skouboe
et al. 1999). Because of their frequent lack of distinguishable morphological
characters, especially fungi necessitate a robust DNA-based identification system.
Although molecular identification is well-established for distinctive fungal groups,
a standardised protocol which is over-all applicable is still missing.
The aim of the present study is to elucidate common problems in barcoding
concerning the eukaryotic kingdom fungi with emphasis on Zygomycetes exemplified with the prominent genera Mucor and Rhizopus. Traditionally, four major
phyla are distinguished within the kingdom Fungi: Chytridiomycota, Zygomycota,
Ascomycota and Basidiomycota. But in recent years, it has become evident that this
traditional scheme does not reflect the phylogenetic relationships among fungi,
especially within the basal fungal lineages. Although the monophyletic phyla Ascoand Basidiomycota are well-characterised sister groups today and combined to the
subkingdom of the Dikarya, the classification of the basal fungal lineages is still in
flux (Sugiyama 1998; van de Peer et al. 2000; Berbee and Taylor 2001; James et al.
2006; Hibbett et al. 2007). Major chances in recent years were the establishment of
the phyla Glomeromycota (Schüßler et al. 2001), Blastocladiomycota (James et al.
2007), and Neocallimastigomycota (Hibbett et al. 2007) formerly embedded in
Zygomycota and Chytridiomycota. Both these phyla harbour several important
pathogens of plants, fungi, animals, and man, causing chytridiomycoses or zygomycoses. With a presumed 70% increase of zygomycotic infection diseases
between the years 1940 and 2000 (Roden et al. 2005), Zygomycetes are of growing
medical importance, especially for patients with immunocompromised systems and
diabetes mellitus, or for intravenous drug users (e.g. Greenberg et al. 2004; Metellus
et al. 2008; Nucci and Marr 2005; Ribes et al. 2000; Walsh et al. 2004). This
increase was notably significant even before the beginning of voriconazole prophylaxis and the treatment of aspergillosis infections in immunocompromised patients
216
Y. Gherbawy et al.
(Roden et al. 2005; Rogers 2008; Trifilio et al. 2007). Common zygomycotic
infections affect the rhino-orbito-cerebral tract, the respiratory tract, gastrointestinal
tract, or skin (Iwen et al. 2007; Roden et al. 2005). Species involved in mycoses
belong mainly to the order Mucorales and can be classified to the epidemiologically
and clinically important genera Rhizopus, Mucor, Lichtheimia (formerly Absidia),
Cunninghamella, Rhizomucor, and Apophysomyces (Diwakar et al. 2007; Iwen et al.
2007; de Hoog et al. 2000; Ribes et al. 2000). Because of the growing significance of
infections and their different sensibility to antifungal drugs, precise identification
down to species level is indispensable (Bal 2006; Cuenca-Estrella et al. 2006; Singh
et al. 2005). Comprehensive studies concerning clinically important fungi revealed
Rhizopus arrhizus (formerly R. oryzae), R. microsporus, and Mucor circinelloides
as the most frequent agents of mucormycoses (Alastruey-Izquierdo et al. 2009;
Alvarez et al. 2009). Each of these species has a different susceptibility to antifungals (Alastruey-Izquierdo et al. 2009; Almyroudis et al. 2007; Dannaoui et al.
2003). The possibility to identify clinically important Zygomycetes based on DNA
markers was successfully demonstrated in recent years (Iwen et al. 2005, 2007;
O’Donnell et al. 2001; Schwarz et al. 2006; Voigt et al. 1999; Voigt and Wöstemeyer
2001; White et al. 2006). We want to show the synergistic supplementation of
different easy-to-access data aiming at the identification of fungi with emphasis on
the mucoralean genera Mucor and Rhizopus. Although DNA markers usually allow
an easier (in theory) distinction of clinically important taxonomic groups, morphology is still essentially required for supporting the species designations and the
description of newly identified species (Alastruey-Izquierdo et al. 2010; Hoffmann
et al. 2007, 2009b).
11.2
Methodical Section
11.2.1 Isolation, Cultivation and Maintenance of Strains
A considerable number of soil and air-borne fungi were isolated from Saudi
Arabian fruits and soil, Germany, and Austria (Tables 11.1–11.4). Fungal isolates
were cultivated for maintenance and isolation of genomic DNA was done on MEX
solid media (30 gL 1 malt extract supplemented with 5 gL 1 yeast extract and
20 gL 1 agar). All strains with a FSU number are deposited at the Fungal Reference
Centre, University of Jena, and available upon request (www.prz.uni-jena.de).
11.2.2 Morphological Identification
Morphological identification was performed in following the guidelines of description keys commonly used for species identification and the therein recommended
11
Molecular Barcoding of Microscopic Fungi with Emphasis
217
Table 11.1 Basidiomycetes, isolated from Saudi Arabian fruits and soil. Because of lacking
morphological traits, a secure identification was not possible. Sequence BLAST results of ITS
sequences are given, but were not useful for correct species assignments. Taxonomical affiliations
for the best BLAST hits are indicated according to the taxonomy at NCBI. All BLAST results
belong to: Basidiomycota, Agaricomycotina, Agaricomycetes
FSU-no.
GenBank
ITS sequence
BLAST
Taxonomical affiliations
Acc.no.
BLAST results
identity (%)
6258/ 6280
GQ221186
Bjerkandera adusta 98–100
Polyporales, Coriolaceae
Thanatephorus
98–100
Cantharellales,
GQ221187
cucumeris
Ceratobasidiaceae
6263/
GQ221188
Phlebia radiata
98–100
Corticiales, Corticiaceae
6282
GQ221189
Sistotrema
99
Corticiales, Corticiaceae
6301/ 6404
GQ221190
brinkmannii
GQ221191
Lactarius
99
Russulales, Russulaceae
chrysorrheus
Coprinopsis
99
Agaricales,
cothurnata
Psathyrellaceae
Merulius
97–99
Corticiales, Corticiaceae
6291
GQ221192
tremellosus
Trametes versicolor 98–99
Polyporales, Coriolaceae
6418
GQ221193
T. ochracea
99
Polyporales, Coriolaceae
Tricholoma
99
Agaricales,
robustum
Tricholomataceae
Phellinus igniarius 98
Hymenochaetales,
Hymenochaetaceae
media and methods. For the identification of Zygomycetes the following keys were
used: Benjamin (1979), Ellis and Hesseltine (1965, 1966), Hesseltine and Ellis
(1961, 1964, 1966), Zycha et al. (1969), Schipper (1973, 1975, 1976, 1984, 1990),
Schipper and Stalpers (1984), and Alastruey-Izquierdo et al. (2010). Species of the
phyla Asco- and Basidiomycota were identified using Samson and Frisvad (2004),
Raper and Fennell (1965), Raper and Thom (1949), Leslie and Summerell (2006),
and Wollenweber and Reinking (1935). Some prominent morphological features
for differentiation are summarised in Figs. 11.1–11.3.
11.2.3 Extraction of Genomic DNA and PCR Amplification
Extraction of genomic DNA and PCR amplification of marker genes were done as
described elsewhere (Einax and Voigt 2003). The primers for amplification were
ITS1/4 for the internal transcribed spacer regions 1 and 2 (White et al. 1990), cmd5/6
for calmodulin fragments (Hong et al. 2005), and bt2a/b for beta-tubulin fragments
(Glass and Donaldson 1995). The amplicons were purified using the adsorption to
glass particles described by Vogelstein and Gillespie (1979). Purified fragments
were subjected to direct sequencing using the PCR primers as sequencing primers.
(6276, 6279)h
6408h
GQ221109, GQ221163, GQ221088
9292b
9320c
GQ221110
GQ221111
Aspergillus niger
var.niger
Aspergillus
sclerotiorum
Aspergillus ustus
Aureobasidium sp.
Bipolaris sp.
Botrytis sp.
Btub: A. niger var. niger [99%]
Cmd: A. niger var. niger, A. awamori [98%]
ITS: A. sclerotiorum, A. persii, A. bridgeri [99%]
Btub: A. sclerotiorum, A. persii [97–98%]
ITS: A. insuetus, A. ustus [99%]
Btub: A. insuetus, A. ustus [96–97%]
Cmd: A. insuetus, A. ustus [94–96%]
ITS: A. pullulans [100%]
ITS: B. heveae [99%]
A. niger var.
niger
A. sclerotiorum
A. ustus
A. pullulans
B. heveae
B. cinerea
Y. Gherbawy et al.
9297b
GQ221164–GQ221165, GQ221089–
GQ221090
GQ221108, GQ221162
218
Table 11.2 Ascomycetes, isolated in Saudi Arabia. Accepted identities based on considerations combined from morphological data and sequence BLAST
results of ITS, beta-tubulin or calmodulin sequences
Final
FSU-no.
GenBank Acc.no.
Identification based Identification verified by sequence BLAST,
identification
[BLAST identity]
on morphology
Acrostalagmus sp.
ITS: A. luteoalbus [99%]
A. luteoalbus
CK1
GQ221095
GQ221096 –GQ221104
Alternaria sp.
ITS (9285=9286=9289= 9306=9308=
Alternaria sp.
(9285, 9286,
9313=9314=9317=9641=9653 / 9315):
9306, 9308,
Alternaria sp. [99%]
9641, 9653)a,
9289b, (9313,
9314, 9315,
9317)c
9295d
Aspergillus
n.d.
A. candidus
candidus
9293d
GQ221105, GQ221159
Aspergillus sp.
ITS: Eurotium chevalieri, A. cristatus,
A. chevalieri
E. amstelodami, A. ruber [98%]
Btub: Eurotium chevalieri [100%]
GQ221106, GQ221160
Aspergillus flavus
ITS: A. flavus var. oryzae [99%]
A. flavus var.
9429f
var. oryzae
Btub: A. flavus var. oryzae [99%]
oryzae
GQ221107, GQ221161, GQ221087
Aspergillus
ITS (6405): A. fumigatus [100%]
A. fumigatus
(6264, 6405)x
Btub (6264): A. fumigatus [100%]
fumigatus
Cmd (6264): A. fumigatus [99%]
GQ221128
GQ221129
GQ221130–GQ221138,GQ221140,
GQ221141,GQ221175–GQ221176
Engyodontium sp.
Exserohilum sp.
Fusarium sp.
GQ221139, GQ221174
Fusarium oxysporum
GQ221142
GQ221177
Geotrichum candidum
var. citri-aurantii
n.d.
Paecilomyces sp.
Chaetomium sp.
GQ221124
GQ221125, GQ221172
GQ221126
GQ221127, GQ221173, GQ221092
Cochliobolus sp.
Cochliobolus sp.
Chaetomiaceae
Emericella
quadrilineata
8673g, 9639f
9310a
9299d
ITS: F. solani, F. oxysporum [99–100%]
Btub: F. solani, F. oxysporum [100%]
n.d.
ITS: Microsphaeropsis arundinis [100%]
Btub: P. variotii [97%]
C. globosum
Cochliobolus sp.
C. spicifer
C. kuwaitiensis
E.quadrilineata
E. sp.
E. rostratum
Fusarium sp.
F. oxysporum
G. candidum var.
citri-aurantii
M. arundinis
P. variotii
(continued)
219
9303a
9305a
(8671, 9302,
9427, 9428,
9643, 9298)a,
(9294,
9300)b,
6261e, 9296f,
9642g, (9301,
9304)j
9311d
GQ221120–GQ221123, GQ221091
ITS(6277=6296=6297=6300; 6289=6298=
6409=9640=9647): B. cinerea, B. fabae,
Sclerotinia sclerotiorum [99%]
Btub (6297=9640=9647; 6289=6298= 6409):
B. cinerea [99%, 95%]1
ITS (6295=6270=6290=6292): C. globosum
[100%]
Cmd (6270): C. globosum [99%]
ITS: C. kusanoi, Drechslera portulacae [94%]
ITS: C. spicifer [100%] Btub: C. sp. [90%]
ITS: Corynascus kuwaitiensis [99%]
ITS: E. quadrilineata, E. nidulans, Emericella
miyajii [100%]
Btub: E. miyajii, A. parvathecius, E.
quadrilineata [99–100%]
Cmd: E. quadrilineata
[100%]
ITS: E. album [96%]
ITS: Exserohilum rostratum [99%]
ITS: diverse Fusarium sp. [98–100%]
Btub (9298, 9304): diverse Fusarium sp.
[94–99%]2
Molecular Barcoding of Microscopic Fungi with Emphasis
GQ221112 –GQ221119, GQ221166–
GQ221171
11
(6277, 6296,
6297, 6298,
6300, 6409)h,
(9640, 9647)f,
6289x
(6270, 6290,
6292,
6295)h
9312c
9290e
9674a
9309a
Final
Identification verified by sequence BLAST,
identification
[BLAST identity]
GQ221143–GQ221146,GQ221178–
ITS: P. chrysogenum [100%]
P. chrysogenum
(6268, 6267,
GQ221181
Btub: P. chrysogenum
6406)h,
[98–100%]
6265x
GQ221147
Penicillium sp.
ITS: P. expansum [99%]
P. expansum
6269h
6293h, 6294x
GQ221148
Penicillium molle
ITS: diverse Penicillium sp. [100%]3
P. molle
(6278, 6281)h
GQ221149–GQ221150, GQ221182–
Penicillium sp.
ITS: P. commune, P. griseoroseum , P. solitum P. solitum var.
var. crustosum, P. italicum [99%]
crustosum
GQ221183, GQ221093–GQ221094
Btub: P. solitum var. crustosum [98–100%]
Cmd: P. solitum var. crustosum, P. hirsutum
var. allii [99%]
GQ221151
Pestalotiopsis sp.
ITS: P. clavispora, P. photiniae [100%]
Pestalotiopsis sp.
8674a
GQ221152
Cochliobolus sp.
ITS: Pseudocochliobolus verruculosus [100%] P. verruculosus
9307a
9646b
GQ221153
Cladosporium sp.
ITS: Retroconis fusiformis [100%]
R. fusiformis
(9425, 9426,
GQ221154–GQ221156, GQ221184–
Trichoderma sp.
ITS: diverse Trichoderma sp. [98–100%]
Trichoderma sp.
9431)a
GQ221185
Btub (9425, 9431): Trichoderma viride [93%]
GQ221157–GQ221158
Ulocladium sp.
ITS: diverse Ulocladium sp. [99%]
Ulocladium sp.
9287b, 9319c
1
No adequate reference sequence in database for Botrytis fabae, but morphological clearly B. cinerea
2All these Fusarium species belong to different species with 1–20% sequence differences based on an ITS1-5.8S rDNA-ITS2 alignment (data not shown)
3
No ITS sequence for Penicillium molle available
Substrates of isolation: (a) soil, (b) air, (c) wheat, (d) floor, (e) date palm, (f) guava, (g) apricot, (h) Calotropis procera, (j) banana, (x) unknown
Identification based
on morphology
Penicillium
chrysogenum
220
Table 11.2 (continued)
FSU-no.
GenBank Acc.no.
Y. Gherbawy et al.
11
Molecular Barcoding of Microscopic Fungi with Emphasis
221
Table 11.3 Zygomycetes, isolated in Saudi Arabia. Accepted identities based on considerations
combined from morphological data and sequence BLAST results of ITS sequences
Final
Identification verified
FSU-no.
GenBank Acc. Identification
identification
by sequence BLAST,
based on
no.
[BLAST identidy]
morphology
(6254, 9673)a, GQ221194–
Actinomucor
A. elegans [99%]
A. elegans
6256b
GQ221196
elegans
Mucor
(6257, 6259)a, GQ221197–
M. circinelloides
M. circinelloides
9637c
GQ221199
circinelloides
[99–100%]
f. griseof. griseocyanus
cyanus
GQ221200
Mucor hiemalis
Rhizomucor variabilis,
9654c
M. hiemalis
M. circinelloides,
M. hiemalis,
M. racemosus,
[98–99%]
9635a
GQ221201
Mucor varians
Rhizomucor variabilis,
M. varians
M. circinelloides,
M. hiemalis,
M. racemosus,
[98–99%]
GQ221202–
Rhizopus
R. arrhizus var. arrhizus R. arrhizus var.
(6255, 6262,
[100%]
arrhizus
GQ221207
arrhizus var.
9651,
arrhizus
9655)a,
9648d
(6253,
6266)x
Substrates of isolation: (a) Soil, (b) Date palm, (c) Poultry farm soil, (d) apricot, (x) Unknown
11.2.4 The Fungal Subphylum Mucoromycotina
Out of ten families of the order Mucorales (Mucoromycotina, “Zygomycota”)
species representatives for 26 genera were analysed on the basis of sequences of
the 18S rDNA, 28S rDNA, actin (act), and translation elongation factor 1alpha (tef).
The sequences were retrieved from Genbank (Table 11.5) and subjected to maximum parsimony, maximum likelihood, Bayesian inference, and distance based
phylogenetic reconstructions (Fig. 11.4).
11.2.5 Reconstruction of Multigene Phylogenetic Trees
Single alignments were carried out using ClustalX version 1.83 (Higgins and Sharp
1988, 1989; Thompson et al. 1997). The alignment consists of 41 taxa and 3,503
characters (1,215 characters for 18S rDNA, 389 characters for 28S rDNA, 807
characters for act, and 1,092 characters for tef). Bayesian inference with MrBayes
v3.0b4 (Huelsenbeck and Ronquist 2001; Ronquist and Huelsenbeck 2003) was
initiated from a random starting tree. Two runs with each four chains were
222
Y. Gherbawy et al.
Table 11.4 Zygomycetes, isolated from various substrates in Europe. Accepted identities based on considerations combined from morphological data and
sequence BLAST results of ITS sequences
Identification verified by
Identification based
FSU-no.
GenBank Acc.
Origin of isolation
Final identification
sequence BLAST, [BLAST
on morphology
(isolated by)
no.
identity]
Cunninghamella
FSU6521, 6526 diverse
C. echinulata
6510-6516,
GQ221208–
Waddenmeer, Vlieland, The
Cunninghamella sp.
echinulata
6521, 6526
GQ221209
Netherlands
[89–92%]
6250, 6520, 6523
GQ221210–
Lichtheimia
L. corymbifera [98–100%]
L. corymbifera
6250: human skin, Germany;
GQ221211,
corymbifera
6520: cow; 6523: dung of
GQ221217
pigeon, Innsbruck, Austria
6524
GQ221212
soil, Geisenheim, Germany
Mortierella alpina
M. alpina [100%]
M. alpina
M. circinelloides [99%]
6251, 6252, 6518
GQ221218–
Mucor circinelloides f.
M. circinelloides
6251, 6252: human ear, nail,
circinelloides
f. circinelloides
GQ221219,
Germany; 6518: Austria
GQ221213
6517
GQ221214
Snail, Austria
Mucor fragilis
M. fragilis [99%]
M. fragilis
6519, 6530
GQ221215,
6519: soil, Geisenheim,
Mucor hiemalis
M. hiemalis [99–100%]
M. hiemalis
GQ221220
Germany; 6530: human
sole of foot, Germany
6274
GQ221221
Human nail, Germany
Mucor plumbeus
M. plumbeus [98%]
M. plumbeus
6527
Soil, Innsbruck, Austria
Umbelopsis isabellina
n.d.
U. isabellina
6522, 6529
GQ221216,
6522: soil, Martell, Italy;
Zygorhynchus moelleri
Z. moelleri [99%]
Z. moelleri
GQ221222
6529: human nail,
Germany
11
Molecular Barcoding of Microscopic Fungi with Emphasis
223
Fig. 11.1 Light microscopic images of several easy-for-differentiation characters typically for the
fungal phyla. (a) regularly septated mycelium typical for Asco- and Basidiomycetes; (b) clamp
of basidiomycetes; (c) Perithecium, the sexual reproductive structure of some Ascomycetes
(Chaetomium sp.); (d) Zygospore, the sexual reproductive structure of Zygomycetes. Scale bar:
(a–b, d) 20 mm; (c) 100 mm
conducted for 5,000,000 generations with samples from every 5,000 generation.
After discarding the first 25% of the generated trees (burn-in) the consensus tree
was calculated using the halfcompat option. Posterior probabilities (in percent) at
the nodes represent node confidence values. The Bayesian inferred tree is presented
in Fig. 11.4. Distance analysis with distance measure Jukes-Cantor assuming
minimum evolution was done with PAUP* v4.0b10 (Swofford 1998); negative
branch lengths were prohibited. Bootstrap supports (BS) (Felsenstein 1985; 50%
majority rule) were obtained by 1,000 replicates and Jukes-Cantor distances. In
Maximum Parsimony, the starting tree was obtained by stepwise addition of the
sequences. The sequences were added on a simple basis and one tree was held at
each step. Tree-bisection-reconnection (TBR) was the branch-swapping algorithm.
Steepest descent was not in effect. “MulTrees” option was in effect. Two trees
were retained. The bootstrap support (BS) was calculated with fast-heuristic
search and 1,000 replicates. Maximum Likelihood was also carried out using a
heuristic search. The number of substitution types was 2 (HKY85 variant) as was
the transition/transversion ratio. Assumed nucleotide frequencies were empirical. A
molecular clock was not enforced. The starting branch lengths were obtained by the
Rogers–Swofford approximation method (Rogers and Swofford 1998). Using stepwise addition of the sequences and choosing as-is for the addition, the starting tree
was obtained. TBR was the branch-swapping algorithm. Steepest descent was not in
224
Y. Gherbawy et al.
a
c1
b1
b3
b2
c2
Fig. 11.2 Light microscopic images of asexual reproductive structures of zygomycetes. (a)
sporangium with endogenous mitospores (Mucor circinelloides); (b1) apophysate sporangium of
Rhizopus arrhizus; (b2) remaining columella after spore release of R. arrhizus; (b3) Sporangium
of R. arrhizus arising opposite rhizoids; (c) Sporangium and columella of Umbelopsis isabellina, a
fungus of the phylogenetic basal family Umbelopsidaceae (Fig. 11.4). Scale bar: (a–b) 20 mm;
(c) 10 mm
effect. “MulTrees” option was in effect. The bootstrap support (BS) was calculated
with fast-heuristic search and 100 replicates. Trees and Bootstrap supports of
parsimony, likelihood, and distance analyses supported the topology and branch
support from the Bayesian inference analyses, and are therefore not shown. BS
values equal or greater than 75% in all analyses are indicated as bold branches in
Fig. 11.4.
11.2.6 Analysis of the Internal Transcribed Spacer Regions
1 and 2 Including 5.8S rDNA
For several isolates of Rhizopus stolonifer, R. arrhizus, and Mucor circinelloides
ITS1-5.8S rDNA-ITS2 sequences were generated within this study and deposited in
GenBank as accession numbers AM933543-55, AM937531-2, GQ221197-99,
GQ221202-07, GQ221218-19, GQ221213. One sequence for Lichtheimia corymbifera was generated as outgroup taxon (AM937530). The following sequences
11
Molecular Barcoding of Microscopic Fungi with Emphasis
c
a2
a1
225
e1
b1
b2
e2
d
d1
Fig. 11.3 Light microscopic images of diverse asexual reproductive structures and conidia
observed in Ascomycetes. (a) phialides arising directly from the conidiogenous cell (a1 Aspergillus fumigatus, a2 Stachybotrys sp.); (b) or phialides arising from metulae (b1 Acrostalagmus
luteoalbus, b2 Penicillium sp.; c) polyblastic conidiogenesis of Botrytis cinerea; (d) conidiophores
arising from aggregated hyphae, the sporodochia of Fusarium sp., macro- and micoconidium (d1);
(e) septated conidia of Bipolaris heveae (e1) and Cochliobolus verruculosus (e2). Scale bars:
(a, b2) 10 mm; (b1, c, d1, e) 20 mm
226
Y. Gherbawy et al.
Table 11.5 Sequences retrieved from GenBank for the reconstruction of phylogenetic trees
(Fig. 11.4)
Strain
GenBank accession nos.
ACT
TEF
18S rDNA
28S rDNA
Absidia caeruleaNT
AJ287133
AF157226
AF113405
AF113443
Absidia glauca
AJ287135
X54730
AF157118
AF157172
Blakeslea trispora
AJ287143
AF157235
AF157124
AF157178
Chaetocladium brefeldii
AJ287144
AF157236
AF157125
AF157179
Chaetocladium jonesii
AJ287145
AF157237
AF157126
AF157180
Choanephora cucurbitarum
AJ287147
AF157239
AF157127
AF157181
Circinella umbellata
AJ287148
AF157240
AF157128
AF157182
Dichotomocladium elegans
AJ287153
AF157245
AF157131
AF157185
AJ287158
AF157250
AF157135
AF157189
Fennellomyces linderiT
Gilbertella persicaria
AJ287159
AF157251
AF157136
AF157190
Halteromyces radiatusT
AJ287161
AF157253
AF157138
AF157192
Lichtheimia corymbifera
AJ287134
AF157227
AF113407
AF113445
Lichtheimia hyalosporaT
AJ287132
AF157225
AF157117
AF157171
Lichtheimia ramosa
EU826377
EU826382
EU826361
EU826370
Mortierella alpina
EU736236
EU736263
EU736290
EU736317
Mortierella multidivaricata
AJ287168
AF157260
AF157144
AF157198
Mortierella verticillata
AJ287170
AF157262
AF157145
AF157199
Mucor circinelloides
AJ287173
AF157264
AF113427
AF113467
Mucor mucedo
AJ287176
AF157267
X89434
AF113470
AJ287177
AF157268
AF113430
AF113471
Mucor racemosusT
Mycotypha africanaIT
AJ287180
AF157271
AF157147
AF157201
Mycotypha microspora
AJ287181
AF157272
AF157148
AF157202
Parasitella parasitica
AJ287182
AF157273
AF157149
AF157203
AJ287183
AF157274
AF157150
AF157204
Phascolomyces articulosusT
Phycomyces blakesleeanus
AJ287184
AF157275
AF157151
AF157205
Protomycocladus faisalabadensis
AJ287189
AF157280
AF157156
AF157210
Radiomyces spectabilis
AJ287190
AF157281
AF157157
AF157211
Rhizomucor miehei
AJ287191
AF157282
AF113432
AF113473
Rhizomucor pusillus
AJ287192
AF157283
AF113433
AF113474
Rhizopus arrhizus
AJ287198
AF157289
AF113440
AF113481
Rhizopus stolonifer
AJ287199
AF157290
AF113441
AF113482
AJ287200
AF157291
AF113442
AF113483
Saksenaea vasiformisT
Spinellus fusiger
AJ287201
AF157292
AF157159
AF157213
Syncephalastrum monosporum
AJ287203
AF157294
AF157161
AF157215
Syncephalastrum racemosum
AJ287204
AF157295
X89437
AF113484
Thamnostylum piriforme
AJ287207
AF157298
AF157164
AF157218
AJ287208
AF157299
AF157165
AF157219
Thermomucor indicae-seudaticaeT
Umbelopsis isabellina
AJ287209
AF157300
AF157166
AF157220
Umbelopsis nana
AJ287210
AF157301
AF157167
AF157221
Umbelopsis ramanniana
AJ287166
AF157258
X89435
AF113463
AJ287212
AF157303
AF157169
AF157223
Zychaea mexicanaT
T-type strain; IT-isotype strain; NT-neotype strain
were retrieved from GenBank as references: AB113022 and AB113023 (R. stolonifer
var. stolonifer CBS150.83 and CBS609.82), DQ119009 (R. microsporus var.
chinensis, CBS631.82 type), DQ119011 (R. microsporus var. oligosporus CBS339.
62), DQ119014 (R. microsporus var. rhizopodiformis IP676.72), DQ119010
11
Molecular Barcoding of Microscopic Fungi with Emphasis
Mortierella multidivaricata
Mortierella verticillata
Mortierella alpina
Umbelopsis isabellina
100
Umbelopsis ramanniana
100
Umbelopsis nana
100
Phycomyces blakesleeanus
Spinellus fusiger
100
Thermomucor indicae-seudaticae
100
100
Rhizomucor miehei
100
Rhizomucor pusillus
Dichotomocladium elegans
100
100
100 Lichtheimia corymbifera
100
Lichtheimia hyalospora
100
Lichtheimia ramosa
Protomycocladus faisalabadensis
100 Syncephalastrum monosporum
99
Syncephalastrum racemosum
100
100
Fennellomyces linderi
100
Thamnostylum piriforme
97
Zychaea mexicana
100
100
Circinella umbellata
Phascolomyces articulosus
Saksenaea vasiformis
Radiomyces spectabilis
100
Halteromyces radiatus
100
Absidia caerulea
100
100
Absidia glauca
100
100
Rhizopus arrhizus
Rhizopus stolonifer
100 100
Mycotypha africana
Mycotypha microspora
Gilbertella persicaria
100
100
Blakeslea trispora
100 Choanephora cucurbitarum
100
Mucor mucedo
Mucor circinelloides
100
Chaetocladium brefeldii
100
100
Chaetocladium jonesii
73
Mucor racemosus
0.1 substitutions/ site 100
Parasitella parasitica
227
Mortierellales
Umbelopsidaceae
Phycomycetaceae
Mucoraceae
Syncephalastraceae
Lichtheimiaceae
Hoffmann et al., 2009
Syncephalastraceae
Mucoraceae
Syncephalastraceae
Radiomycetaceae
Absidiaceae (von Arx, 1982)
Hoffmann et al., 2007
Mucoraceae
Mycotyphaceae
Choanephoraceae
Mucoraceae
Fig. 11.4 Bayesian inferred phylogram based on aligned nucleotide sequences encoding actin,
translation elongation factor 1alpha, small and large subunit ribosomal RNA from 38 mucoralean
fungi with 3 species of the Mortierellales as outgroup (see Table 11.5). Family affiliations are
according to Kirk et al. (2008), Hoffmann et al. (2007, 2009b). Branch support values (posterior
probabilities) are given and branch support values equal or greater than 75% in all analyses are
indicated as bold branches
(R. microsporus var. mircrosporus IP1124.75), DQ641325 (R. caespitosus
CBS427.87), DQ641324 (R. homothallicus CBS336.62 type), DQ119031 (R. arrhizus
var. arrhizus CBS112.07 type), AY213687 (R. schipperae CBS138.95 type),
AB113016 (R. sexualis CBS336.39 type), DQ118991 (M. circinelloides f. circinelloides CBS195.68 neotype), AJ271061 (M. circinelloides f. lusitanicus CBS277.49),
and DQ118984 (Lichtheimia corymbifera CBS120805). Furthermore, appropriate
228
Y. Gherbawy et al.
sequences were retrieved from the genome projects of M. circinelloides f. lusitanicus
CBS277.49 (scaffold 3 and 12, as of March-29-2009; http://www.jgi.doe.gov) and
Rh. arrhizus var. arrhizus (supercontig 3.6 2078935-2079563 and 2042075-2042703,
as of March-29-2009; http://www.broad.mit.edu/annotation/genome/rhizopus_
oryzae). The phylogenetic analysis of the ITS sequences was based on the Bayesian inference and is shown in Fig. 11.5.
11.2.7 Random Amplified DNA Polymorphisms
Genomic DNA from several isolates of R. stolonifer, R. arrhizus, and M. circinelloides (Table 11.6) were amplified with the primers V6 (Lopandic et al. 1996) and
M13 (O’Donnell et al. 1999). The random amplified DNA polymorphism (RAPD)
profiles obtained were manually transferred into a binary data matrix (0 and 1 for
absence and presence of RAPD bands) and subjected to distance based UPGMA
analysis using PAUP* v4.0b10 (Swofford 1998). The combined matrices of both
RAPD analyses consist of 49 characters in the case of Mucor and 68 characters
for Rhizopus. RAPD analyses and corresponding trees are displayed in Figs. 11.6
and 11.7.
11.2.8 Sequence Similarity Matrices for Rhizopus and Mucor sp.
Sequence similarity matrices were generated from the alignments, which were also
used for the phylogenetic reconstructions. But it turned out that missing characters
need to be omitted, and thus the aligned DNA matrix needs to be shortened to equal
ends (Tables 11.7 and 11.8).
11.3
Results and Discussion
11.3.1 Diversity and Coarse Scale Identification of Fungal
Species Isolated From Saudi Arabian Soil and Fruits
A total of 120 different fungi were isolated, divided into Basidiomycota with
8 isolates, Ascomycota with 75 isolates out of 20 different genera with at least
26 species, and “Zygomycota” with 37 isolates belonging to 8 different genera and
13 species (Tables 11.1–11.4). Each phylum is characterised by specific features
allowing a relative rough and easy assignment of its species. Often no more than
a light microscope is necessary for the first rough identification. More or less
11
Molecular Barcoding of Microscopic Fungi with Emphasis
229
Lichtheimia corymbiferaCBS120805
Lichtheimia corymbiferaFSU6250
Rhizopus schipperae CBS138.95 T
R. caespitosus CBS427.87
99
100
R. homothallicus CBS336.62 T
100
R. microsporus var.microsporus IP1124.75
100
100
R. microsporus var. chinensis CBS631.82 T
R. microsporus var.oligosporus CBS339.62
R. microsporus var. rhizopodiformis IP676.72
R. arrhizus var. arrhizus CBS112.07 T
100
100 R. arrhizus var. arrhizus genome sc3.6 2078935-2079563
R. arrhizus var. arrhizus genome sc3.6 2042075-2042703
R. arrhizus TUR5
100 R. arrhizus TUR9
R. sexualis CBS336.39 T
R. stolonifer CBS150.83
100
R. stolonifer TUR1
100
R. stolonifer TUR6
R. stolonifer TUR7
R. stolonifer CBS609.82
100
Mucor circinelloides f. circinelloides CBS 195.68 NT
100 M. circinelloides f. circinelloides TUM1 AM933548
M. circinelloides f. circinelloides FSU6518
M. circinelloides f. circinelloides FSU6251
93
M. circinelloides f. circinelloides FSU6252
M. circinelloides f. griseo-cyanus FSU6257
M. circinelloides f. griseo-cyanus FSU6259
88
M. circinelloides f. griseo-cyanus FSU9637
M. circinelloides f. griseo-cyanus TUM3
100
M. circinelloides f. griseo-cyanus TUM10
M. circinelloides f. griseo-cyanus TUM15
M. circinelloides f. griseo-cyanus TUM6
M. circinelloides f. griseo-cyanus TUM12
M. circinelloides f. griseo-cyanus TUM7
M. circinelloides f. griseo-cyanus TUM14
M. circinelloides genomescaffold 3
100 M. circinelloides f. lusitanicus CSB277.49
0.1 substitutions/ site
M. circinelloides genome scaffold 12
Fig. 11.5 Bayesian inferred phylogram of aligned ITS sequences from different species and
subspecies of Mucor circinelloides and Rhizopus sp. Branch support values are Posterior Probabilities. Strain numbers are given. Type or neotype strains are indicated by “T” or “NT”
230
Y. Gherbawy et al.
Table 11.6 Rhizopus sp. and
Mucor circinelloides strains
isolated from different
substrates
Species
R. arrhizus
R. arrhizus
R. stolonifer
R. stolonifer
R. stolonifer
M. circinelloides
M. circinelloides
M. circinelloides
M. circinelloides
M. circinelloides
Isolation code
TUR5
TUR9-10
TUR1-4
TUR6
TUR7-8
TUM1-2
TUM3-4
TUM5-10
TUM11-14
TUM15
Substrate
Date
Soil
Apricot
Plum
Grape
Apricot
Date
Plum
Grape
Soil
R. stolonifer 1 (apricot)
R. stolonifer 2 (apricot)
R. stolonifer 3 (apricot)
R. stolonifer 4 (apricot)
R. stolonifer 7 (grape)
R. stolonifer 6 (grape)
R. stolonifer 8 (grape)
R. stolonifer 5 (date)
R. stolonifer 9 (soil)
R. stolonifer 10 (soil)
RAPD - M13
RAPD - V6
Fig. 11.6 RAPD analyses of several isolates of Rhizopus sp. from Saudi Arabia. The profiles of
two different primers, M13 and V6, were combined and subjected to distance based UPGMA
analysis. The combined matrix consists of 68 characters
regularly septated mycelia are typical for the hyphal growth of Asco- and Basidiomycota (Fig. 11.1a) in contrast to the nearly unseptated (but if septae are present,
than irregularly septated) mycelium of the “Zygomycota”. Eponymous for each
phylum are the sexual structures of reproduction, namely basidium, ascus
(Fig. 11.1c), and zygospore (Fig. 11.1d). For microscopic fungi with only a limited
number of distinctive, phylogenetic relevant morphological characters, the asexually developed mitospore- and their associated structures, possess great diagnostic
importance. Although the Basidiomycetes isolated within this study did not form
any distinctive features, e.g. anamorphic structures or even fruiting bodies in
culture, the occurrence of regularly septated mycelium with clamps was diagnostic
for dikaryotic mycelia of the Basidiomycetes (Fig. 11.1a, b). Because of the lack of
suitable morphological parameters, a continuing morphological identification was
not possible for any of the basidiomycetous isolates. A more detailed identification
was attempted using nucleotide sequence data of the nuclear ITS region. Three
11
Molecular Barcoding of Microscopic Fungi with Emphasis
231
M. circinelloides 15 (soil)
M. circinelloides 1 (apricot)
M. circinelloides 7 (plum)
M. circinelloides 8 (plum)
M. circinelloides 3 (date)
M. circinelloides 4 (date)
M. circinelloides 9 (plum)
M. circinelloides 10 (plum)
M. circinelloides 11 (grape)
M. circinelloides 12 (grape)
M. circinelloides 13 (grape)
M. circinelloides 14 (grape)
M. circinelloides 2 (apricot)
M. circinelloides 5 (plum)
M. circinelloides 6 (plum)
RAPD - M13
RAPD - V6
Fig. 11.7 RAPD analyses of several isolates of Mucor circinelloides from Saudi Arabia. The
profiles of two different primers, M13 and V6, were combined and subjected to distance based
UPGMA analysis. The combined matrix consists of 49 characters
isolates could be assigned to order and family level, and with good BLAST results
to the species level, namely Phlebia radiata and Merulius tremellosus. (Table 11.1).
For both species, the BLAST search was unequivocal for the genus level, but
because of the lack of reliable reference sequences, the species level delimitation
remains still somewhat uncertain. The other five isolates could not be assigned by
ITS to order or below-order level. As a result, neither ITS sequences nor morphological traits are sensitive enough to differentiate between the anamorphic stages of
basidiomycetes, if obvious distinctive features of the hyphae are missing. For that
purpose the development of alternative gene markers are mandatory.
Asco- and Zygomycetes differ in their type of mitospore formation. An
exogenous sporulation is typical for Ascomycetes but atypical for Zygomycetes.
The latter ones produce their mitospores endogenously within sporangia, sporangiola, and merosporangia. The sporangia in the order Mucorales are more or
less globose (to subglobose) with a distinctive columella of varying size and
shape (Fig. 11.2). The columella is synapomorphic for the Mucorales (Voigt
et al. 2009).
One of the most prominent exogenous spore disposals is the deliberation from
special conidiogenous cells, the phialides in Ascomycetes. Phialides arise either
directly from the conidiogenous cell (Fig. 11.3a) or from metulae (Fig. 11.3b).
Conidial disposal can also take part from polyblastic conidiogenous cells, which
arrange terminally on tree-like branches (Fig. 11.3c). Other ascomycetes bear their
conidiophores on aggregated hyphae, the sporodochia (Fig. 11.3d). The ascomycetous mitospores appear in various shapes, types, and cellular integrities. While the
232
Table 11.7 Sequence identity matrix of ITS sequences from different isolates of Rhizopus species
R. a.
R.
R.
R.
R.
R.
R. a.
genome
caespitosus homothallicus microsporus shipperae sexualis type
R. caespitosus
ID
R. homothallicus 76
ID
R. microsporus
73
77
ID
R. shipperae
63
61
59
ID
R. sexualis
45
44
48
44
ID
R. arrhizus type 69
70
67
64
47
ID
69
71
67
64
47
99
ID
R. arrhizus
genome
46
47
49
45
67
48
48
R. stolonifer
CBS150.83
R. stolonifer
43
45
47
42
60
46
46
isolate 1
46
47
49
45
66
48
48
R. stolonifer
isolates 6&7
67
68
65
62
48
97
98
R. arrhizus
isolates 5&9
R. st.
R. st.
CBS150.83 isolate 1
R. st.
R. a.
isolates 6&7 isolates 5&9
ID
84
ID
99
84
ID
48
46
48
ID
Y. Gherbawy et al.
11
M.c. f. g-c.
FSU6257
M.c. f. g-c.
FSU6259
M.c. f. g-c.
FSU9637
ID
99
ID
99
99
Molecular Barcoding of Microscopic Fungi with Emphasis
Table 11.8 Sequence identity matrix of ITS sequences from different isolates of Mucor circinelloides
M.c. f. c.
M. c. f. g-c. M. c. f. g-c.
M. c. f. l. M. c. f. c. M. c. f. c. M.c f. c..
genome
neotype
isolate 1
FSU6251 FSU6252 isolate 3
iso.6..//..15
ID
M. c. f. lusitanicus
genome
ID
M. c. f. circinelloides 95
NT
100
ID
M. c. f. circinelloides 96
isolate 1
97
98
ID
M. c. f. circinelloides 94
FSU6251
99
99
97
ID
M. c. f. circinelloides 95
FSU6252
M. c. f. griseo92
95
95
93
94
ID
cyanus isolate 3
M .c. f. g-c. iso.
91
94
94
92
93
98
ID
6,7,10,12,14,15
96
98
98
96
97
95
94
M. c. f. griseocyanus FSU6257
M. c. f. griseo96
99
99
96
98
96
94
cyanus FSU6259
96
98
98
96
96
95
95
M. c. f. griseocyanus FSU9637
ID
233
234
Y. Gherbawy et al.
mitospores of the ascomycetes can be uni- or multicellular, septated or unseptated
(Figs. 11.3d1 and e), the mitospores of the zygomycetes are always unicellular and
unseptated. On the basis of the anatomy of 75 ascomycete isolates, 74 (99%) could
be identified to genus level, but only 43 (57%) could be identified to species level.
From 64 species the ITS region, from 27 species the beta-tubulin gene, and from
8 species the calmodulin gene were sequenced. Those 99 sequences were subjected
to BLAST searches. In all cases an identification of the genus was possible. An
assignment to species level was possible for 56% of the ITS sequences, 82% for the
nucleotide sequences encoding beta-tubulin, and 100% for those encoding calmodulin. Consequently, the application of the ITS as barcode marker is ambivalent.
While ITS works nicely for molecular barcoding of the ascomycetous genera
Trichoderma, Hypocrea, or Trichophyton (Druzhinina et al. 2005; Summerbell
et al. 2007), it is not variable enough to distinguish between species in the genera
Penicillium (Skouboe et al. 1996, 1999) and Fusarium (possessing non-orthologous
copies of ITS2, O’Donnell and Cigelnik 1997; O’Donnell et al. 1998). In Aspergillus, the ITS is quite useful to separate different sections from each other but also not
useful to distinguish between species in Aspergillus (Balajee et al. 2007). Obviously, the species delimitations are narrower than in other genera. Alternative
barcode markers were evaluated and successfully applied. These are partial
sequences of the gene encoding translation elongation factor 1alpha (tef) for
Fusarium (Geiser et al. 2004) and the genes encoding beta-tubulin or calmodulin
for the most studied ascomycetous genera (Geiser et al. 2007; Hong et al. 2006;
Samson et al. 2004).
For Zygomycetes, the situation is somewhat different. Here the morphological
markers are discriminative enough to gain a proper above and below species-level
identification for all isolates. On the other hand, the ITS sequences facilitated a
proper identification of genera, but not of species. Only 80% zygomycetes could be
reliably identified down to the species level. The missing fifth (20%) of misapplied
classifications occurred because of (1) missing reference material (e.g. for M. varians
and M. circinelloides f. griseo-cyanus), or (2) morphologically problematic reference and type strains (FSU9654; M. hiemalis and Rhizomucor variabilis are
morphologically quite similar; see discussion in Hoffmann et al. 2009a). But by
carefully judging these possible problems, ITS possesses a high sensitivity and is a
very powerful tool for a rough classification of Zygomycetes, but tends to be more
precise in combination with phenotypic criteria. Thus, a single method of identification should always be supplemented with an additional support by different
unlinked nucleotide sequence barcode markers in combination with morphological
and physiological markers. Nevertheless, an advantage of ITS over others is that
the primers are universally applicable and the sequences are usually diverse
enough to distinguish between taxa down to the species level. A major drawback
of the ITS lies in its repetitive nature and in the resulting escape of single copies
from concerted evolution leading to different ITS sequence types in Zygomycetes
(Schwarz et al. 2006). However, a critical vision of all paralogs of the ITS increases
the quantity and the quality of the discriminating signal for zygomycete identification (Alastruey-Izquierdo et al. 2010).
11
Molecular Barcoding of Microscopic Fungi with Emphasis
235
In summary, apart from the choice of the right molecular barcode marker, the
most serious problems in the molecular identification are still caused by a lack in
the availability of suitable reference sequences (Hoffmann et al. 2009a) and their
annotation in the public data bases of the International Nucleotide Sequence
Database Collaboration (Nilsson et al. 2006). If sequence material is thought to
be the primary information source for identification of isolates as intended in the
various international barcode projects, an all-encompassing database of perfectly
described, annotated voucher specimens is indispensable. Such an effort for an
organised molecular identification of fungi was initiated by the creation of Mycobank at www.mycobank.org, an initiative of the Centraalbureau voor Schimmelcultures Utrecht in the Netherlands (Crous et al. 2004). Mycobank provides onward
links to DNA databases and nomenclatural novelties accessible in Mycobank,
IndexFungorum, GBIF, and other international biodiversity initiatives for the
realisation of a species bank that eventually links all databases of life.
11.3.2 Diversity and Morphological Identification
of the Mucoralean Genera Rhizopus and Mucor
Within the order Mucorales (Mucoromycotina) two prominent genera exist, namely
Rhizopus and Mucor. Whereas Rhizopus comprises closely related taxa (BS 100%
in Fig. 11.4; Voigt et al. 1999; Voigt and Wöstemeyer 2001), the genus Mucor
forms a highly polyphyletic group (Fig. 11.4; O’Donnell et al. 2001; Hoffmann
et al. 2009a; Voigt et al. 2009). Both genera harbour species of ubiquitous soil fungi
mainly living as saprobes. But under certain conditions some species could be
responsible not only for agricultural and food spoilage but also for mucormycoses
in humans and animals (Michailides and Spotts 1990; Ogawa et al. 1992; Ribes
et al. 2000; Voigt et al. 1999).
The genus Rhizopus EHRENBERG with its type R. stolonifer is characterised by
apophysate sporangia, stolons, and rhizoids. The sporangiophores arise mostly
opposite the rhizoids (Fig. 11.2b3; Ehrenberg 1820; Schipper 1984; Schipper and
Stalpers 1984). Traditional classification was mainly based on morphology (Zycha
et al. 1969). In a revision, the genus was divided into three groups: the R. arrhizus
(formerly R. oryzae) group, the R. microsporus group, and the R. stolonifer group
(Schipper 1984; Schipper and Stalpers (1984). R. arrhizus represents a single
species group; whereas the group of R. microsporus harbours its varieties, R. m.
var. microsporus, R. m. var. rhizopodiformis, R. m. var. oligosporus, R. m. var.
chinensis, and also R. homothallicus. The R. stolonifer group contained initially
two species, R. stolonifer and R. sexualis comprising the varieties R. s. var.
stolonifer, R. s. var. lyococcus, and R. s. var. sexualis and R. s. var. americanus,
respectively (Schipper and Stalpers 1984). But later the varieties were elevated
at the rank of species, e.g. R. americanus (Zheng et al. 2000) and R. lyococcus
(Liou et al. 2007). On the basis of 28S rDNA (LSU, D1/D2 region), the members
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of the R. lyococcus group can be clearly distinguished from the R. stolonifer group.
This is concordant with the appearance of recurved sporangiophores exclusively
found in the R. lyococcus group (Liou et al. 2007). In a monograph on the genus
Rhizopus morphological traits, growth temperature, mating behaviour, and molecular systematics were considered as the main descriptive characters (Zheng et al.
2007). The authors accepted ten species and seven varieties, but no groups.
The Dictionary of the Fungi (Kirk et al. 2008) and the database of IndexFungorum (www.indexfungorum.org; as of 31th August 2009) recognise nine to ten
species, respectively and eight varieties in the genus Rhizopus. Out of 155 entries in
IndexFungorum, six entries were re-classified in four other genera, twelve entries
were synonymous for R. stolonifer, and more than 70 entries were synonyms for
R. arrhizus var. arrhizus. From the latter species, the clinical isolate RA99-880
(FGSC9543; NRRL43880) was sequenced and published by the Broad Institute of
the Harvard University and the Massachusetts Institute of Technology (MIT). This
species was chosen as one important representative agent of mucormycoses in order
to gain knowledge on genes and their impact on pathobiology (www.broad.mit.
edu).
R. arrhizus differs from R. stolonifer by smaller sized and darker coloured
sporangia, by the ornamentation of the zygospores, and by its high thermotolerance allowing colonisation of warm-blooded animals including humans (Schipper
1984).
Within the present study, several isolates from fruits collected in Saudi Arabia
could be identified as members of the groups R. stolonifer and R. arrhizus.
Identification was performed on the basis of micromorphology and DNA polymorphisms generated by nucleotide sequences and DNA fingerprints (Figs. 11.5
and 11.6).
On the other hand, the genus Mucor FRESENIUS with its type M. mucedo is
characterised by the formation of non-apophysate sporangia (Fig. 11.2a) and the
lack of stolons and rhizoids (Fresenius 1850; Schipper 1975).
As the genus Mucor is highly polyphyletic ( O’Donnell et al. 2001; Voigt and
Wöstemeyer 2001), the number of accepted species varies between 50 and 75
(Kirk et al. 2008; www.indexfungorum.org; as of 31th August 2009). Out of
currently 700 entries in IndexFungorum, 116 entries were re-classified in forty
other genera and fifteen were synonyms for the type species M. mucedo. The
genome of M. circinelloides f. lusitanicus CBS 277.49 was sequenced by the
Joint Genome Institute (www.jgi.doe.gov). M. circinelloides is currently divided
into four formae with a total of 25 synonyms. The formae circinelloides,
lusitanicus, janssenii, and griseo-cyanus differ mainly in their colony colour,
sporangiospores, and appearance of the columellae (Schipper 1976). Differentiation between these formae still remains largely on morphological traits. Nucleotide sequence comparisons of the different formae are reported Sect. 11.3.5 of
this chapter.
M. circinelloides is not closely related to any other species of Mucor. Its closest
relatives are M. mucedo and M. racemosus as well as the facultative parasites
Parasitella and Chaetocladium (100% BS, Fig. 11.4).
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Molecular Barcoding of Microscopic Fungi with Emphasis
237
11.3.3 Phylogenetic Relevance of Morphological Markers
While the common morphological characteristics of both genera, Rhizopus and
Mucor, turned out to be very similar, only those of Rhizopus bear phylogenetic
relevance, which allows a secure assignment to the genus. The combination of the
criteria “stolons and rhizoids, apophysate sporangia, sporangiophores arising opposite the rhizoids” define a well-supported distinct evolutionary group, whereas the
appearance of “non-apophysate sporangia and the lack of stolons and rhizoids” is
not enough to describe the genus Mucor, because it matches also with the main
characteristics of many other genera polyphyletic in Mucor (Fig. 11.4). As outlined
in Sect. 11.3.1. the construction of an online platform linking all databases harbouring nucleotide sequences, as well as distinctive morphological and growth physiological criteria of the type strains from the core Mucoraceae, will help to revise the
genus delimitations towards a natural system reflected in a monophylogenetic
concept of the taxa.
11.3.4 Fine Scale Identification of Rhizopus Isolates Based
on Combined Morphological and Molecular Characters
Although various species of Rhizopus are morphologically very similar, there are
some phylogenetic applicable characters allowing affiliations to different species
complexes and species. Especially the complexity of rhizoids, length of sporangiophores, size of sporangia, appearance of zygospores, temperature range for growth,
and preferred substrates differentiate between the three species complexes (as
outlined in detail by Schipper and Stalpers 1984).
Thus, the species of Rhizopus isolated within this study were unequivocally
identified by the application of the morphological traits mentioned before. The
species designations were successfully supported by analyses of DNA sequence
(Tables 11.3–11.4).
11.3.5 Synergistic Application of DNA-Polymorphism
and DNA-Sequence Generating Tools
Based on RAPD analyses, the isolates of R. arrhizus differ largely from those of
R. stolonifer (Fig. 11.6). Two isolates of R. arrhizus from soil (samples 9 and 10)
were identical in their banding patterns but differed largely from isolate 5, which
was collected from a date fruit (Fig. 11.6). Nevertheless, the analysis of the ITS1
and 2 revealed no differences between the isolates from soil and date (Fig. 11.5,
Table 11.7). In a sequence identity matrix, these isolates of R. arrhizus show
highest similarities (97–98%) to the type of R. arrhizus CBS112.07 and to the
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strain RA99-880 used in the genome project (Table 11.7). R. arrhizus is the sister
group to R. microsporus complex with the species R. microsporus, R. caespitosus,
and R. homothallicus. R. schipperae appears basal to R. arrhizus / R. microsporus
supported by 99% PP (Fig. 11.5). According to sequence similarities and the
original description, R. schipperae belongs clearly to the R. microsporus complex
(Table 11.7; Weitzman et al. 1996). Sequence similarities within the R. microsporus complex range between 73–77% (except R. schipperae with ca. 60%) and
are around 62–71% to the group of R. arrhizus (Table 11.7). The R. microsporus
group and the R. arrhizus group are together the sister group to the R. stolonifer
group including R. sexualis (100% PP, Fig. 11.5; Schipper 1984; Schipper and
Stalpers 1984). RAPD analyses of different isolates from Saudi Arabian fruits show
clearly two distinctive groups, each with more or less similar banding patterns, but
on an average, the isolates collected from apricots show fewer bands than isolates
collected from grapes (Fig. 11.6). ITS-sequence similarities within the species R.
stolonifer are 84% between isolates from apricots and grapes, 84% between the
apricot isolate and strain CBS150.83, and 99% between the grape isolate and
CBS150.83 (Table 11.7). All isolates show similarities of 60–67% to R. sexualis.
The differences between R. sexualis and R. stolonifer are similarly compared to
those of R. microsporus versus R. arrhizus, thus indicating well-described and
supported taxonomic group affiliations. Species of the genus Rhizopus seem to
develop a certain host-specificity (Fig. 11.6). This is not the case in M. circinelloides
(Fig. 11.7).
Although there are obvious correlations between the analyses of ITS sequences
and RAPDs for Rhizopus isolates, there is no further correlation between these two
analyses of the different isolates of Mucor circinelloides. On the basis of the ITS
sequences, the isolates 6, 7, 10, 12, 14, and 15 are identical (data not shown, 100%)
with closest similarity to isolate 3 (98%, Table 11.8). But an unequivocal assignment to different formae could not be achieved. Although the two formae isolated
from Saudi Arabia were differentiated on the basis of the morphological criteria as
M. circinelloides f. circinelloides and M. circinelloides f. griseo-cyanus, there is no
reference sequence available from the latter forma. Both formae could be separated
by their different size of the sporangiospores and the shape of their columellae.
On the basis of ITS sequence overall similarities, only the forma lusitanicus is
clearly distinguishable from both other formae with 4–9% sequence dissimilarities
(Table 11.8). But the sequence of the neotype from M. circinelloides f. circinelloides CBS195.68 shows 98–99% sequence identity to M. circinelloides f. griseocyanus FSU6257, FSU6259, and FSU9637. This similarity is higher than that of
97% with the isolate FSU6251, which was identified as M. circinelloides f. circinelloides (Table 11.8). Isolates of M. circinelloides f. griseo-cyanus show sequence
dissimilarities between themselves ranging from 1–6% and sequence dissimilarities
from 1–8% to the isolates of M. circinelloides f. circinelloides. This high deviations
in sequence similarities is below forma-level and does therefore not facilitate a
sufficient differentiation between the two formae. But evaluating the sequence
alignment, few nucleotide positions occur that may help to tell the formae apart
(Fig. 11.8). Within the 550 basepair long ITS1-5.8S rDNA-ITS2 alignment, 15
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Molecular Barcoding of Microscopic Fungi with Emphasis
239
Fig. 11.8 ITS sequence alignment of several isolates of Mucor circinelloides. Alignment length is
550 base pairs. Alignment is cut to the positions with variable sites. Dots indicate invariant sites of
the sequences. Nucleotide sequence positions which are typical for the different formae are
highlighted in black. Formae are abbreviated as follows: “l” – lusitanicus; “gc”– griseo-cyanus;
“c”– circinelloides
nucleotide positions are obvious for M. circinelloides f. lusitanicus and clearly
separate this forma from M. circinelloides f. circinelloides and M. circinelloides f.
griseo-cyanus. These positions are position 5 (C for M. circinelloides f. lusitanicus
instead of T in the other formae = C/T), position 26 (C/T), position 44 (C/T), position
54 (T/C), position 171 (G/C), position 362 (gap/A), position 379 (T/A), position 380
(G/T), position 399 (G/T), position 400 (gap/A), position 401 (gap/T), position
404 (A/T), position 449 (gap/A), position 545 (C/T), and position 449 (gap/TC)
(Fig. 11.8). For differentiation of the other two formae griseo-cyanus and circinelloides, only few distinctive nucleotide positions exist. At position 86, a cytosine
is characteristic for M. circinelloides f. griseo-cyanus instead of a thymidine in
the other formae. An insert near the end of the alignment seems typically for
M. circinelloides f. griseo-cyanus, but is not present in all isolates of this formae.
M. circinelloides f. circinelloides show 3 characteristic nucleotide positions that
differentiate this form from the other forms. At position 100 a guanosine is localised
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Y. Gherbawy et al.
as a substitute for an adenosine. At position 367 is an inserted thymidine and at
position 382 a thymidine instead of a cytosine. Such specific nucleotide positions
within aligned sequences serve as markers, which differentiate between species
and subspecies when the whole sequence is not able to separate properly. Unlike
Rhizopus and its fruit-dependent ITS variances, there are no such differences within
the isolates and formae of M. circinelloides and their substrate collection.
Primer V6 shows no correlations between the origin of the isolate, e.g., with
similar patterns for isolates 3 & 4 (from date) and 9 &10 (from plum) (Fig. 11.7).
Dissimilar patterns were also observed, e.g., the isolated pairs 7 & 8, 9 & 10, and 5
& 6, which all originate from plums (Fig. 11.7). Even there are more bands for the
RAPD primer M13; there is also no correlation between origin and below-species
level designation possible. But primer M13 could differentiate between e.g. 3 & 4
(date) and 9 & 10 (plum). The similar RAPD patterns for both primers between the
pairs 3 & 4, 5 & 6, 9 & 10, 11 & 12, and 13 & 14 suggest that these species originate
from a common clonal line and do presumably belong to M. circinelloides f. griseocyanus (Fig. 11.7).Thus, the species of Rhizopus are more host-specific than the
isolates of Mucor circinelloides. Consequently, it can be argued that host specificity
may take part at the species level rather than at the below-species level. More
detailed information about the molecular identification of food- and fruitborne
Rhizopus and Mucor strains are published elsewhere (Gherbawy and Hussien
2009).
11.3.6 Evaluation of Potential Barcoding Methods and the Impact
of Extended Species Recognition
Species of the investigated genera Rhizopus and Mucor harbour important agents of
post harvest diseases and mucormycoses. A fast, accurate, cost-saving method to
unequivocally assign an unknown isolate to a species would be of great interest.
Although there are only few species, which cause mucormycoses (mainly Rhizopus
arrhizus and Mucor circinelloides), there exist different sensitivities against antifungals (Ribes et al. 2000; Dannaoui et al. 2003; Alastruey-Izquierdo et al. 2009).
Thus, profound studies on the geographic occurrence and diversity, genetic variability, and epidemiological significance of important fungal species are required.
DNA barcodes like ITS, IGS, 28S rDNA sequences and RAPDs already proved to
be useful markers to differentiate species and varieties for well-supported and wellstudied fungal groups (this study; Liou et al. 2007; Liu et al. 2008; Hoffmann et al.
2009a). However, molecular barcoding based on short standardised DNA regions is
neither a tool for phylogenetic reconstructions nor for taxonomical purposes.
Molecular barcoding solely provides means for the linkage of a sample specimen
to already existing taxonomical, systematic, and phylogenetic information. But a
non-negligible advantage of molecular barcoding is its ability for aiding ecologists
to gain insights into species diversity and identity of environmental samples, a goal
in well-timed pest control (Valentini et al. 2009).
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241
11.3.7 The Pressing Need for Reliable Species Identification
The present systematics of Zygomycetes suggests a more generalised lifestyle than
that in derived fungi. Host specificity is manifested already on species level,
whereas many derived fungi show broad host ranges on species level and small
host ranges on sub-species levels. For instance, the ascomycetous genus Fusarium
is well-studied because of its agricultural importance as causative agent of the head
blight of wheat as well as crown and stem rots causing immense yield losses and
mycotoxin envenomations in humans and animals after the consumption of infected
grains. Epidemiological studies revealed a very broad host range with different
formae speciales of Fusarium spp. based on their specificities to certain host plants
(Michielse and Rep 2009).
Probably because of the underestimation of the plant and animal damaging potential of zygomycetous fungi, the number of currently described species is most likely
undervalued. With a denser monitoring of their diversity and their epidemiology the
identification of a broader spectrum of species also defined by substrate specificity can
be predicted. In recent years several studies were published, reducing existing species
to the status of “synonyms” resulting in the aforementioned high number of synonyms
(e.g. Hoffmann et al. 2007, 2009a, b; Alastruey-Izquierdo et al. 2010; Zheng et al.
2007). For example, more than 70 synonyms were described for R. arrhizus (Zheng
et al. 2007; IndexFungorum). Few physiological and chemotaxonomical characters
not commonly used for the identification of Zygomycetes, such as differences in the
utilisation of carbon and nitrogen sources, the formation of specific compounds (cell
wall sugars, fatty acids etc.), or the quantity of sporulation, were not accepted by the
scientific community leading to a considerable reduction of the number of species by
Zycha (1935) and others. On the other hand, the ability to produce organic acids was
recently considered in species recognition, separating the R. arrhizus group once again
into R. arrhizus var. arrhizus and R. arrhizus var. delemar (Abe et al. 2003; Zheng
et al. 2007). Substrate specificities combined with established and accepted morphological and phylogenetic approaches could be a useful tool to differentiate and restore
already described species to accomplish a natural system of species, which does also
consider evolutionary distances in order to gain an increase in the objectivity of setting
species limitations. The resulting refinement in the definition of the phylogenetic
species concept (Taylor et al. 2000) allows a more reliable and precise identification
of a fungal specimen and is essential for comparative verifications of industrial,
environmental, or pathogenic strains (Ogawa et al. 1992; Hachmeister and Fung
1993; Voigt et al. 1999; Hageskal et al. 2006).
11.4
Conclusions
For the identification and the classification of specimens, a conscientious plan of the
approaches with careful judgement of the obtained data is mandatory and will lead
to sustainable results. The combination of different scientific expertise will solve
the puzzle of diverse characters.
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Y. Gherbawy et al.
With the concatenation of traditional with molecular approaches and its advantage of universal applicability, the identification of fungi will rapidly develop and
achieve a more precise delimitation of taxonomical groups than single criteria.
But what could be the contribution of the DNA barcodes? The database of the
Consortium for the Barcode of Life (http://www.barcoding.si.edu/) is also supposed
to help non-taxonomists in the assignment of an unknown specimen to a welldescribed voucher specimen based on short barcode sequences, which are easy to
obtain. These barcodes are thought of for the protection of the Earth’s biodiversity
which is preceded by the elucidation of the Earth’s biodiversity. Molecular barcodes are essential where no other opportunities for identification are possible, e.g.
missing discriminating data or under axenic conditions not cultivable specimens.
The protection of endangered life forms, and the control of pests and their vectors
are only few of the objectives examples supporting barcode research (CBOL, http://
barcoding.si.edu). But we should not forget that DNA barcodes were not designed
for the identification of new species. DNA barcodes are often not sufficient enough
for the exploration of new species and will probably fail (Aliabadian et al. 2009).
Nevertheless, with the ability to identify fungal species on the basis of sequence
information, a trend can be detected in disregarding characters other than DNA
sequences for the identification and the description of species. Trusting in a single
or few non-descriptive characters is a highly alarming trend. For instance, single
BLAST searches could be using inaccurate sequence data (Balajee et al. 2009;
Bridge et al. 2003). Although there are constant changes in the terminology of
fungal morphology and taxonomy, descriptive traditional characters are essential
and must not be neglected.
Furthermore, molecular, biochemical, ecological, and physiological parameters
can efficiently reveal morphologically identical species, cryptic species. The exploration of cryptic species is accelerating in recent years, for example in the dikaryomycotean genera Trichoderma (Gams and Bissett 1998), Fusarium (Baayen et al.
2000; O’Donnell 2000; O’Donnell et al. 2000), Armillaria (Pegler 2000), Aspergillus
(Geiser et al. 1998; Pringle et al. 2005), or Penicillium.
With the identification and the development of characters which are independent
from external influences, and therefore, less error-prone than other criteria, the
DNA markers are often preferred over morphological data. Because of the occasionally large intra-specific variability, the lack of sufficient distinctive characters,
or the dependence upon physiological parameters (Schipper 1973; Zycha et al.
1969), informative phenotypic data are often hard to obtain and to reproduce. But
without reliable morphological data, an assignment of molecular data to a specific
reference fungal specimen is not possible (Hoffmann et al. 2009a). Without reliable
reference strains and reference sequences a molecular identification is impossible.
With the ongoing trend to identifying fungal specimens using DNA barcodes, a
broad-ranged and well-defined taxonomic database is crucial (Meyer and Paulay
2005) because barcodes are only useful to assign unidentified specimens to already
known and described species. The same way, DNA markers can distinguish morphological cryptic species; molecular biologically cryptic species can be differentiated
11
Molecular Barcoding of Microscopic Fungi with Emphasis
243
by morphology. Therefore, the combination of phenotypic and molecular data is
highly recommended.
A gap located between the proposed total number of fungal species of at least
1.5 million (Hawksworth 1991; Kirk et al. 2001; Hawksworth 2001) and the number
described so far, which ranges between 72,000 and 120,000 (Hawksworth and
Rossman 1997; Hawksworth 2001), implies a large number of still undiscovered
and undescribed species. Once the problems of DNA barcoding, resulting from
insufficient sampling of voucher specimens, insufficient barcode markers (e.g.
paraloges), or bad taxonomy of voucher specimens because of misidentification or
because poly- or paraphyletic species are avoided, the large scaled molecular
identification of fungi will be a powerful and rapid procedure for the assessment
of the fungal organisms in the biosphere (Hebert et al. 2004a; Wiemers and Fiedler
2007; Funk and Omland 2003; Moritz and Cicero 2004).
Authors’ Contributions and Competing Interests The authors declare that they have no competing interests. CK is a graduate student and performed identification by traditional analyses as
well as sequencing of all fungi except the species related to the Rhizopus sp. – Mucor circinelloides part. YG and NG collected all Saudi Arabian fungal isolates and did all experiments related
to the Rhizopus sp. – Mucor circinelloides part, including identification, sequencing, and RAPD
analyses. YG provided inspiring ideas and contributed to the discussion of the results. KH
performed the phylogenetic analyses, coordinated the work, and wrote the manuscript.
Acknowledgements The authors wish to thank Martin Kirchmair (University of Innsbruck,
Austria) who kindly provided the zygomycetes strains FSU6510-6527 and Roman Schwarz
(Medizinisches Versorgungszentrum, Mönchengladbach, Germany) who kindly provided the
zygomycetes strains FSU6529, FSU6530, FSU6250-6252, FSU6274.
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Chapter 12
Advances in Detection and Identification
of Wood Rotting Fungi in Timber
and Standing Trees
Giovanni Nicolotti, Paolo Gonthier, and Fabio Guglielmo
Abstract Wood rotting fungi are reported as a major source of economic losses in
both timber production and wood in service, and one of the main causes of tree wind
throws and limb failures. Since the biology of these fungi is varied, their detection
and identification are important for the application of appropriate management
strategies and control measures. Following an overview of traditional and biochemical diagnostic techniques, whose usefulness is frequently limited either by their
reliance on the sporadically emerging and rarely visible fruit bodies, or by the need
of a preliminary isolation step, we discuss on DNA-based techniques that have been
developed to detect and early identify wood rotting fungi in timber and in standing
trees.
12.1
Introduction
Wood rotting fungi, also named decay fungi or rots, are the primary biotic decomposers of the wood because of their ability to break down lignified cell walls
(Blanchette 1991; Jasalavich et al. 2000). Except for few ascomycetes, all wood
attacking fungi are basidiomycetes primarily belonging to Agaricales, Hymenochaetales, Polyporales, and Russulales (Kirk et al. 2001). Based on their enzymatic
capabilities, the decay fungi are divided into brown rot fungi, which preferentially
attack and rapidly depolymerize cellulose and hemicelluloses, and white rot fungi,
which can progressively degrade both carbohydrates and lignin (Blanchette 1991;
Worrall et al. 1997). The structural deterioration of wood, determined by both types
of rots, is an essential process in carbon and nitrogen recycling of forest ecosystems,
G. Nicolotti, P. Gonthier, and F. Guglielmo
Di.Va.P.R.A., Department of Exploitation and Protection of the Agricultural and Forestry
Resources, Plant Pathology, University of Torino, via L. da Vinci 44, I-10095, Grugliasco (TO),
Italy
e-mail: giovanni.nicolotti@unito.it
Y. Gherbawy and K. Voigt (eds.), Molecular Identification of Fungi,
DOI 10.1007/978-3-642-05042-8_12, # Springer-Verlag Berlin Heidelberg 2010
251
252
G. Nicolotti et al.
but can represent a serious threat leading to considerable problems in the urban
context as well as in commercial forestry and plantations. In the urban environment,
wood decay fungi can have a negative impact on tree stability (Lonsdale 1999).
Furthermore, they are deemed to be responsible for most of damages of structural
wood in buildings (Schmidt 2007). In forests and plantations for timber production
and, to a lesser extent, in several fruit tree crops, root and butt rot diseases can cause
severe economic losses (Bahnweg et al. 2002; Utomo and Niepold 2000). At any
rate, timely detection and careful identification of wood rotting fungi are essential
to define the most appropriate management strategies and control measures. Moreover, effective identification methods may be basic tools for studies focused on
epidemiology, ecology, and biology of wood decay fungi. The late and occasional
occurrence of visible rot symptoms and signs, such as the emergence of fruit bodies,
can lead either to overlooking rot infections or to make identification of wood decay
fungi unfeasible. This relevant issue has led to the development of several alternative techniques to efficiently detect and identify wood rotting fungi.
Following a general overview of the problems and risks caused by rots in both
standing trees and wood in service, as well as of the most hazardous fungi involved,
this chapter is focused on methods for detection and identification of wood rotting
fungi. Recently developed diagnostic techniques are discussed in terms of
advances upon traditional methods, limits, and fields of application. Relevance is
given to DNA-based techniques allowing for early identification of rots directly
from wood.
12.2
Problems and Risks Related to Wood Rotting Fungi
12.2.1 Indoor Wood Rotting Fungi
Indoor wood decay fungi, also named house rots, figure prominently amongst the
economically most important wood inhabiting fungi (Schmidt 2007). Indeed, it has
been estimated that the cost for repairing damages caused by rots to timber used in
construction in 1977 in the UK amounted to £3 millions per week (Rayner and
Boddy 1988). The rise of wood moisture content, due to general building defects or
to the presence of permanent water vapor sources, can lead to environmental
conditions suitable for fungal infections. Based on the extent of the damage and
on the fungal species involved in the decay process, remedial treatments range from
expensive refurbishment methods to a more practical disposal of moisture sources
(Schmidt 2007). Not all indoor wood decay fungi are in fact problematic, and
the knowledge of their physiological requirements is important to develop environmentally friendly control strategies (Högberg and Land 2004; Schmidt 2007).
Identification of the house rots is therefore important for management purposes.
Several studies have been focused on the abundance, economic significance, and
biology of indoor wood inhabiting fungi (Bech-Andersen 1995; Gilbertson and
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253
Ryvarden 1987; Huckfeldt and Schmidt 2006; Jellison et al. 2004). Brown rot
basidiomycetes have been reported as the most common and hazardous indoor
wood decay fungi. Among them, the dry rot fungi Serpula lacrymans (Wulfen:Fr.)
and Meruliporia incrassata (Berk. & Curt.) are extremely destructive and among
the least controllable fungi in Europe and the USA, respectively, mainly due to their
ability to carry water and nutrients over long distances by means of strands (Jellison
et al. 2004; Schmidt 2007). In Germany, S. lacrymans is clearly differentiated from
other house rots as its presence requires considerably more rigorous and far-reaching
control measures (Schmidt 2007). Other hazardous brown rot species include the
cellar fungus Coniophora puteana (Schumach.) P. Karst., which proved to be able
to cause decay even in wood with low moisture content (Huckfeldt and Schmidt
2006); the white polypores Antrodia spp. and Oligoporus placenta (Fr.) Gilb. &
Ryvarden, mainly reported in the attic and upper floor; and the gill polypores
Gloeophyllum spp., described as common destroyers of window and roof timber,
with the ability to survive even at higher temperatures (Schmidt and Huckfeldt
2005). The Oak polypore, Donkioporia expansa (Desm.) Kotl. & Pouzar, has been
reported as one of the few white rot basidiomycetes leading to relevant damages to
indoor wood (Kleist and Seehann 1999).
12.2.2 Wood Rotting Fungi and Tree Stability
An accurate inspection of trees in public areas can be essential for correct tree
management plans aimed at preventing dangerous situations such as wind throws or
limb failures. Although main stems and root systems of standing trees are structurally optimized to withstand several times the average of the mechanical forces to
which they are subjected from their own weight and from loading by wind, rain, and
snow (Mattheck and Breloer 1995), the structural biological deterioration of wood
can increase the occurrence of mechanical failures. This may lead to severe
damages to properties and to personal injuries (Lonsdale 1999). Moreover, excessive pruning and root lesions, to which urban trees are frequently exposed, may
favor infections of wood rot fungi. A timely detection of hazardous trees is achieved
through a careful visual inspection of decay signs and structural weakness (Mattheck
and Breloer 1992). Although this method, complemented with instrumental analyses
(Habermehl et al. 1999; Müller et al. 2001; Nicolotti et al. 2003; Tomikawa et al.
1990), can allow detecting wood rot even at an incipient stage, it rarely enables the
diagnosis of the decay causative agent. Because the biology and ecology of
different rots are varied, the knowledge of the wood decay fungi involved in each
instance is important to predict, to some extent, the severity of the fungal infection
and, thus, to reliably assess potential risks of failure (Lonsdale 1999). Early
identification of the causative agent is then crucial for rapidly progressing decay
fungi that can turn a sound tree into a hazard in a short period of time.
Several comprehensive studies aimed at investigating and describing the most
common rots in landscape and urban trees (Bernicchia 2005; Erkkilä and Niemelä
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G. Nicolotti et al.
1986; Hickman and Perry 1997; Lonsdale 1999; Nicolotti et al. 2004a, b), as well as
their invasiveness in different host species (Deflorio et al. 2008; Schwarze and Baum
2000; Schwarze et al. 2004; Swiecki et al. 2005; Terho et al. 2007), have allowed
highlighting fungal taxa whose detection in a standing tree can be regarded as a
hazard. Most of these taxa are white rot basidiomycetes: several species of Ganoderma and Inonotus have been reported as very active root and butt rot fungi
potentially leading to extensive decay (Terho et al. 2007); Armillaria (Fr.:Fr.)
Staude species are known to be dangerous root rot fungi occurring with high
frequency even in urban environment (Guglielmo et al. 2008a); Phellinus spp. and
Perenniporia fraxinea (Bull.) Ryvarden are deemed to be widespread butt and stem
decay agents causing an intensive white rot (Bernicchia 2005; Nicolotti et al. 2004a, b;
Swiecki et al. 2005). Although rarely found in hardwoods of urban environment,
the brown rot Laetiporus sulphureus (Bull.) Murril is considered a hazardous root
decay agent (Bernicchia 2005; Nicolotti et al. 2004a, b). Finally, the ascomycete
Kretzschmaria deusta (Hoffm.) P.M.D. Martin has been recently proved to be strongly
invasive in living stems of different deciduous hosts (Deflorio et al. 2008).
12.2.3 Rot Diseases and Timber Production
Although root and butt rots represent one of the driving forces leading to spatial and
temporal diversification of forests, rot diseases figure amongst the most prominent
causes of cull in timber production, resulting in considerable economic losses
worldwide (Delatour 1980; Hansen and Goheen 2000). Indeed, in conifer stands
aimed at timber production, often characterized by intensive thinning and monoculture, rot frequency can amount up to 20% (Piri 1996). Since most of the rot fungi
can display host preference or specificity, and peculiar spreading and infection
biology, management practices and control measures to limit rot diseases in forests
are strongly dependent on precise and accurate identifications of the disease agent.
Several taxa within the Armillaria and Heterobasidion annosum (Fr.) Bref. species
complexes are deemed to be responsible for most of the root and butt rot diseases of
conifers and hardwoods in natural forest stands and plantations throughout the
northern temperate regions of the world (Chase and Ullrich 1988; Kile et al.
1991). As an example, taxa included in the Heterobadision annosum species
complex are reported to cause losses for more than €800 millions per year just in
Europe (Woodward et al. 1998). The complex genus Armillaria encompasses about
40 biological species of varying geographic distributions, host ranges and virulence
(Pegler 2000; Watling et al. 1991). Armillaria mellea (Vahl: Fries) Kummer and
A. ostoyae (Romagnesi) Herink. have been reported as aggressive rot pathogens,
whereas A. gallica Marxmuller and Romagnesi, A. cepistipes Velenovsky,
A. borealis Marxmuller and Korhonen, and A. tabescens (Scopoli: Fries) Emel
figure as secondary pathogens or weak parasites (Guillaumin et al. 1985; Kile et al.
1991; Wargo and Harrington 1991). Most of the Armillaria species are able to
spread over long distances by means of rhizomorphs despite absence of root
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Advances in Detection and Identification of Wood Rotting Fungi
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contacts between adjacent trees. Before forest stand regeneration, careful removal
of stumps or dying root systems is thus advisable to reduce fungal inoculum,
especially when aggressive pathogenic Armillaria species are detected.
Heterobasidion annosum sensu lato (s.l.) is a species complex including three
European species, namely, H. abietinum Niemelä & Korhonen, H. annosum sensu
stricto (s.s.), and H. parviporum Niemelä & Korhonen, and two North American
intersterility groups (ISGs), H. annosum ISG P (Am-P) and H. annosum ISG S
(Am-S). Each taxon within H. annosum s.l. is characterized by distinct host
specialization: H. abietinum, H. parviporum, and Am-S have been reported mostly
as butt rot agents on spruce or fir trees, whereas H. annosum s.s. and H. annosum
Am-P are associated with root rot and mortality of pines (Korhonen and Stenlid
1998). Primary infection occurs by means of airborne basidiospores on fresh stumps
or wounds, and secondary infection by vegetative spreading from stump to tree or
from tree to tree through root contacts. Treating fresh stumps with chemicals or
biotic competitors, as well as avoiding thinnings and clearcuttings in periods
of abundant sporulation, are important preventive control measures against this
pathogen (Gonthier et al. 2005; Möykkynen and Miina 2002; Nicolotti and
Gonthier 2005). The identification of H. annosum species infecting a stand can be
important for the selection of tree species to be used for reforestation (Hantula and
Vainio 2003).
Phellinus weirii (Murr.) Gilb. sensu lato and Inonotus tomentosus (Fr.) Teng
are reported as aggressive root rot pathogens that can cause extensive wood losses
and reduce productivity in conifer stands especially in North America (Germain
et al. 2002; Hansen and Goheen 2000). Finally, although further investigations
are needed, several species of Ganoderma, Phellinus, and Phlebia are responsible
for harmful root and butt rot diseases affecting hardwood plantation for timber
and biomass production in Asia (Lee 2000; Suhara et al. 2002; Utomo and
Niepold 2000).
12.2.4 Root and Butt Rot Diseases and Fruit Tree Plantations
Several root and basal stem rots have been reported as significant diseases in fruit
tree plantations, and decay agents are capable of surviving in the soil for several
years (Amenduni et al. 2001; Khairudin 1995). Curative measures are, in general,
expensive and not always effective, owing to the fact that visible disease symptoms
appear at a very late stage of infection (Utomo and Niepold 2000). Preventive
strategies based on the use of pathogen-free propagating materials and planting in
noninfested soils are the most appropriate control measures (Schena and Ippolito
2003). Detection and early identification tools are thus important to limit the spread
of these diseases in fruit tree plantations.
Rosellinia necatrix (Prill.) and A. mellea are dangerous root rot agents of fruit
and forest trees with a widely distribution throughout temperate regions (Anselmi
and Giorcelli 1990; Wargo and Harrington 1991). Basal stem rot caused by
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G. Nicolotti et al.
pathogenic Ganoderma spp. has been reported to severely reduce yearly harvest of
oil palm crops in Asia (Utomo and Niepold 2000).
12.3
Traditional Techniques of Identification
of Wood Rotting Fungi
12.3.1 Analysis of Fruit Bodies and Mycelial Strands
Conventional identification methods of wood decay fungi mostly rely on visual
analysis of fruit bodies. Dichotomous keys to species, available for several lignicolous basidiomycetes (Bernicchia 2005; Breitenbach and Kränzlin 1986; Hickman
and Perry 1997; Hjortstam et al. 1978), are based on macromorphology of the
basidioma and hymenophores, and on micromorphology of hyphal system, hymenial organs, and spores. Determination of fungal species through the use of these
keys often requires a deep mycological background. Simplified keys for the identification of several wood rotting fungi in urban and landscape trees proved to be
suitable for discrimination at the genus level (Intini et al. 2000; Lonsdale 1999;
Strouts and Winter 1994). Because aggressiveness and ability to overcome host
defenses can vary among different species within genera (Schwarze and Baum
2000), identification at a species level is often more useful for tree management
purpose. Recently, field keys based on macroscopic observations of basidiomata,
their longitudinal cross-sections, and color of spore print have been successfully
validated and they include the most important and widespread European wood rot
basidiomycetes in standing trees (Gonthier and Nicolotti 2007). Macroscopic and
microscopic analysis of fruit bodies, as well as of mycelial strands, can be successfully used to identify house rots (Bravery et al. 2003; Huckfeldt and Schmidt 2006).
Although this diagnostic method can be fast and reliable, it rarely allows for
early identification of wood rotting fungi. Indeed, fruit bodies and/or mycelial
strands of several wood decay fungi are rarely or sporadically visible and they
usually emerge at advanced stages of the fungal infection (Palfreyman et al. 1991;
Terho et al. 2007). This may represent a serious problem for several brown rots of
wood in service, which can rapidly and drastically reduce wood strength at incipient
stages, and for rapidly progressing root and butt rot agents of standing trees, which
can represent a serious hazard in the urban environment.
12.3.2 Analysis of Pure Fungal Cultures
Analysis of pure fungal cultures isolated from mycelium and/or decayed wood may
be used when no fruit bodies are available. Keys based on growth rate, microscopic
features, and enzymatic capabilities of mycelia have been published for the identification of several basidiomycetes at the species level (Lombard and Chamuris
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Advances in Detection and Identification of Wood Rotting Fungi
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1990; Nobles 1965; Stalpers 1978). Moreover, sexual or mating compatibility tests,
by means of pairing the unknown isolate with known haploid testers, may be
efficient diagnostic tools. A sexually compatible mating results in the production
of a genetic stable heterokaryotic mycelium, visible both by changes in culture
morphology or by microscopic observations for the presence of clamp connections
at some or most septa (Harrington et al. 1989; Ullrich and Anderson 1978). Mating
tests have been extensively used for the discrimination of species within Armillaria
and Heterobasidion annosum species complexes (Anderson 1986; Korhonen 1978).
Diagnostic methods based on pure culture analysis and tests are time-consuming
and often unsuited to distinguish between closely related species (Schmidt 2007).
Moreover, isolation of wood rotting fungi from environmental samples is often
impractical, despite the use of selective media, due to the presence of fast growing
fungal contaminants.
12.4
Biochemical Techniques
12.4.1 Protein-Based Techniques
Identification of wood decay fungi by means of analysis of their proteins includes
sodium dodecyl sulfate polyacrilamide gel electrophoresis (SDS-PAGE) and isozyme analysis. SDS-PAGE is based on the analysis of electrophoretic patterns of
whole cell proteins, after denaturation by means of chemical treatments. This
method has been used for the discrimination, at specific and subspecific levels, of
several indoor wood decay fungi (Palfreyman et al. 1991; Schmidt and Moreth
1995). Analysis of isozymes, which are proteins with multiple forms but with
similar or identical enzymatic properties, consists of an electrophoresis followed
by treatment with dye-forming substrate for the target enzyme. The resulting
isoenzymatic profiles can allow differentiation of closely related species. This
technique has been extensively used for studies on inter and intraspecific variability
within Armillaria and Heterobasidion annosum species complexes (Otrosina et al.
1992, 1993; Rizzo and Harrington 1993; Wahlstrom et al. 1991).
Both the above-described techniques require the isolation of pure fungal cultures
and a large amount of fungal tissues. Moreover, protein profiles can be highly
affected by factors related to environment and the stage of fungal development.
The procedure to develop systems yielding consistent results may then be work and
time-consuming.
12.4.2 Immunological Techniques
Immunological methods are based on the use of polyclonal antisera or monoclonal
antibodies obtained to specifically recognize antigens, such as proteins or
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polysaccharides, typical of the species to be identified. Several methods, such as
dot-blot immunoassay, enzyme-linked immunosorbent assay (ELISA), and electron
microscopy immunolabeling have been developed for detection and/or quantification of the most serious indoor wood decay fungi (Clausen 1997; Jellison and
Goodell 1988; Palfreyman et al. 2001). This technique proved to be useful to
early detect rots directly from extracts of wood, without the need of any prior
isolation and pure culturing step (Clausen and Kartal 2003). ELISA tests have been
successfully developed for rapid detection from wood samples of A. mellea and
A. ostoyae (Priestley et al. 1994) and pathogenic Ganoderma species on oil palm
(Utomo and Niepold 2000).
Although several immunological methods, such as ELISA, are promising techniques for screening a large number of samples, cross-reaction may occur with
nontarget organisms (Schmidt 2007). Further, sensitivity of immunological assays
can often be inhibited by wood extractives (Jellison and Goodell 1989).
12.5
DNA-Based Techniques
The great potential of DNA-based techniques, over traditional and biochemical
identification methods, relies on the chance to select diagnostic markers in coding
as well as noncoding DNA regions of the nuclear and mitochondrial genome.
Indeed, nucleotide sequence polymorphism of these regions can provide a large
amount of diagnostic characters suitable for identification of fungi at different
taxonomic levels independently of any factors related to environment and stage
of fungal development. Although DNA hybridization techniques combined with the
digestion of nuclear and mitochondrial DNA (nuc- and mt-DNA) by means of
restriction endonucleases proved to be powerful for identification of Armillaria at a
specific and subspecific rank (Jahnke et al. 1987; Anderson et al. 1989; Schulze
et al. 1995), this method is too time-consuming and expensive for routine diagnosis
of rots. Conversely, techniques based on polymerase chain reaction (PCR) are
valuable alternative identification tools for specific, sensitive, and rapid routine
diagnoses of wood decay fungi. As immunological methods, most PCR-based
methods allow fungal identification directly from wood, without the need of any
pure fungal culture isolation step. Following a brief overview of the protocols
developed to efficiently extract DNA from wood, we describe the most important
PCR-based methods used for identification of wood rotting fungi.
12.5.1 DNA Extraction from Wood
While starting from fungal mycelium easy and rapid methods of hyphal suspension
in sterile water followed by freezing and thawing steps may be suitable for PCR
amplification of fungal ribosomal DNA (rDNA) (Garbelotto et al. 1996; Harrington
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Advances in Detection and Identification of Wood Rotting Fungi
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and Wingfield 1995); when wood samples have to be tested, more elaborate protocols are necessary for efficiently extracting fungal DNA. Wood extractives, namely
polyphenols, tannins, resin acids, and polysaccharides, are known as potential PCR
inhibitors (Bahnweg et al. 1998). Further, in decayed wood, DNA molecules can be
subjected to partial degradation (Jasalavich et al. 2000). Efficient wood DNA
extraction is thus crucial for both reliability and sensitivity of PCR-based methods.
In a study focused on DNA isolation from recalcitrant materials, such as conifer
tree roots and bark, Bahnweg et al. (1998) developed a highly efficient cetyltrimethylammonium bromide (CTAB) protocol consisting of an early extraction or
precipitation of inhibiting components under conditions minimizing oxidation
reactions. Since this method is work- and time-consuming, and requires several
harmful reducing agents and organic solvents, it is unsuited to rapid routine
diagnostics. Other protocols, based on serial extractions with either CTAB or
SDS, and organic solvents (Jasalavich et al. 2000; Oh et al. 2003; Suhara et al.
2005; Vainio and Hantula 2000) efficiently provide amplifiable DNA from both
incipient and advanced decayed wood but still result in long procedures. Rapid and
organic solvent-free protocols consisting either of serial CTAB extractions (Råberg
et al. 2005) or CTAB extraction followed by a final DNA purification with
GENCLEAN Kit (Qbiogene, Carlsbad, CA, USA) (Allmér et al. 2006) or polyvinylpolypyrrolidone (PVPP) spin columns (Schena and Ippolito 2003) have
proven to be useful in extracting fungal DNA from wood. Finally, in a comparative
assay of different DNA extraction methods (Guglielmo 2005), a protocol entirely
based on a kit developed to extract DNA from “stool” (Qiagen, Valencia, CA,
USA) proved to be as efficient as the Bahnweg protocol for fungal DNA isolation
from wood of different tree species. Since this method is rapid and no harmful
reagent handling steps are necessary, it has been extensively and successfully used
for the validation of PCR-based diagnostic methods on wood samples collected
from different host tree species (Guglielmo et al. 2007, 2008b). Despite the cost,
DNA extraction kits are very useful for reliable and rapid routine diagnostics.
12.5.2 RAPD-PCR
Random amplified polymorphic DNA (RAPD) analysis consists of a PCR with an
arbitrary and short oligonucleotide which can prime the amplification of DNA
fragments when its complementary site occurs as reverted repeats in the genome
(Williams et al. 1990). DNA polymorphism among different individuals is thus
detected as the presence/absence of the amplicons that compose their RAPD profile.
Schmidt and Moreth (1998) proposed RAPD markers that may be useful to
distinguish S. lacrymans from other indoor decay fungi. Strain identification by
means of RAPD analysis was paramount to prove the different origins of several
C. puteana cultures that had been supposed to be strain Ebw15, an obligatory test
fungus used to evaluate the efficacy of wood preservatives according to the
European Standard EN113 (Göller and Rudolph 2003). RAPD analysis has been
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used to differentiate genotypes of Armillaria spp. in natural populations of different
geographical areas, providing markers for the distinction of both a single clone
(Smith et al. 1992) and a single species (Schulze et al. 1997). Finally, this method
has been extensively used to study the genetic variability among and within ISGs of
H. annosum (Garbelotto et al. 1993; Karjalainen 1996).
Although RAPD analysis is fast and easy to perform and does not require prior
information of the target DNA site, it can have limits of reproducibility. Moreover,
this technique should not be applied on DNA extracted from environmental samples, i.e., wood, potentially holding several different microorganisms.
12.5.3 PCR-RFLP
Restriction fragment length polymorphism (RFLP) analysis is based on the use of
restriction endonucleases, enzymes which recognize specific nucleotide sequences
(restriction sites) and consequently cut DNA at these or other points. Polymorphism
in these sites can thus be used to distinguish between different individuals. As stated
above, costly and elaborate Southern blotting and labeled probing techniques are
needed to detect RFLP of total nuc- and/or mt-DNA. Conversely, RFLP applied to
PCR-amplified DNA fragments can provide valuable diagnostic markers easily
detectable through a simple agarose gel electrophoresis. Since nuc- and mtrDNA loci include both conserved and variable domains (Hong et al. 2002;
White et al. 1990), they figure amongst the most popular DNA target sites for the
development of most of the DNA-based fungal diagnostic techniques, including
RFLP markers. Indeed, in the nuc-rDNA, internal transcribed spacers (ITSs) and
nontranscribed intergenic spacers (IGSs) display high inter and intraspecific variability, whereas ribosomal genes, such as large and small rDNA (nuc-LrDNA and
nuc-SrDNA), are more useful for identification at higher taxonomic levels (Bruns
and Shefferson 2004; Guerin-Laguette et al. 2002). Multicopy arrangement and
highly conserved priming sites, typical of both nuc- and mt-rDNA, allow DNA
amplification from virtually all fungi, even if the starting sample is lacking in
quantity or quality (Jasalavich et al. 2000; White et al. 1990).
Amplified ribosomal DNA restriction analysis of ITS (ARDRA-ITS) has proven
to be useful for the distinction of S. lacrymans from its closest relative Serpula
hymantioides (Fr.) P. Karst. (Schmidt and Moreth 1999). Digestion of an IGS
portion with a combination of restriction endonucleases allowed unambiguous
identification of pure cultures of several Armillaria species from Europe (Sierra
et al. 1999), North America (Harrington and Wingfield 1995; Sierra et al. 1999),
and Japan (Matsushita and Suzuki 2005). RFLP of PCR-amplified ITS and IGS has
been extensively used in several studies for the differentiation of H. annosum
species and ISGs both in Europe and North America (Garbelotto et al. 1993;
Gonthier et al. 2001; Kasuga and Mitchelson 2000; Kasuga et al. 1993). In a recent
study, the development of RFLP of nuc-rDNA amplified fragments allowed the
differentiation, within P. weirii complex, of P. weirii sensu stricto (s.s.) and
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Phellinus sulphurascens Pilat, two species differing in pathogenicity but mostly
undistinguishable by means of traditional methods (Lim et al. 2005). A wide
collection of RFLP profiles based on a 1,800–1,900-bp-long region, including the
ITS, allowed the differentiation among 48 out of 52 species of the European
polypores analyzed (Fischer and Wagner 1999). A similar study, but restricted to
RFLP analysis of ITS, has been performed to investigate wood inhabiting fungi in
Picea abies of unmanaged forests (Johannesson and Stenlid 1999).
PCR-RFLP has proved to be a valuable and reproducible method for fungal
identification at different taxonomic levels, but as RAPD markers when applied to
DNA extracted directly from wood it can lead to unreliable results. A cloning step
before the digestion of the amplified rDNA (Kennedy and Clipson 2003) can
overcome this limit but it makes the method longer and more complex.
12.5.4 T-RFLP
Terminal restriction fragment length polymorphism (T-RFLP) is an automated
version of PCR-RFLP. Fluorescently labeled primers are used in PCR and a highresolution capillary analyzer is used to investigate the digested fragments (Liu et al.
1997). In comparison to RFLP, only terminal digested fragments are detectable.
This technique is a high-throughput fingerprinting method often used in studies of
microbial communities (Edel-Hermann et al. 2004).
Through T-RFLP on ITS, Coniophora puteana has been detected directly from
artificially inoculated wood samples at early stages of colonization, when no
hyphae were visible at the microscope (Råberg et al. 2005). T-RFLP, visual fruit
body inspection, and analysis of pure fungal cultures have been simultaneously
employed to examine the composition and the abundance of wood inhabiting fungi
in woody debris of a Norway spruce stand (Allmér et al. 2006). Although the
number of fungal species detected by T-RFLP was lower than that obtained with the
other two methods, it allowed the detection of unculturable wood decay basidiomycetes (Lim et al. 2005).
Although few applications of this method have been reported so far for diagnosis
of wood rots, this technique is promising especially for rapid and simultaneous
investigation of several fungi.
12.5.5 Taxon-Specific Priming PCR
PCR with taxon-specific primers provides reliable tools for fungal diagnostics from
both pure culture and environmental samples. The specificity of this method relies
on the design of primers that anneal exclusively a complementary site unique for
the taxon to be detected. If DNA of the target species is present, taxon-specific
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oligonucleotides prime the amplification of DNA fragment of a peculiar size. As an
added benefit, the simultaneous application of taxon-specific primers in multiplex
PCR reactions can increase the diagnostic capacity of PCR without compromising
the specificity of the analysis (Elnifro et al. 2000). A simple agarose gel electrophoresis can allow the detection of taxon-specific amplicons.
Species-specific oligonucleotides were designed on ITS to identify S. lacrymans,
D. expansa, C. puteana, Antrodia vaillantii (DC.) Ryvarden, and Gloeophyllum
sepiarium (Wulfen) P. Karst. (Moreth and Schmidt 2000; Schmidt and Moreth
2000). This technique can be useful to easily and rapidly detect, directly from wood
samples, the economically most important basidiomycetes causing wood rot in
European buildings (Table 12.1).
PCRs with specific ITS primers have been developed to detect European Armillaria
species by Schulze et al. (1997) and Lochman et al. (2004). Further, primers
developed by Lochman et al. (2004) through a nested PCR method enable the
detection of Armillaria spp. directly from environmental samples, such as soil.
Attempts to design specific primers for each European Armillaria species are
reported in the study conducted by Sicoli et al. (2003) (Table 12.2).
A taxon-specific competitive priming (TSCP)-PCR, developed to identify in a
single reaction the two north American H. annosum ISGs, Am-P and Am-S, allowed
efficient typing of more than 500 fungal samples and to recover, first time in the field,
a well-established hybrid between the two ISGs (Garbelotto et al. 1996). A similar
approach has been used to study the abundance, potential dispersal range, and
habitat of European H. annosum species in pure and mixed forests (Gonthier et al.
2001, 2003). While taxon-specific primers designed on mt-LrDNA with partially
overlapping complementary sites allowed the distinction of H. parviporum and H.
abietinum, the simultaneous use of universal fungal primers on the same region
permitted the identification of the intronless H. annosum s.s. (Gonthier et al. 2003).
For more practical purposes, PCR with primers designed on ITS allowed detecting
both H. annosum s.s. and H. parviporum directly from increment cores of Norway
Table 12.1 PCR assays, with reverse taxon-specific primers designed on ITS region, for the
identification of indoor wood rotting fungi
Primer pairs Primer sequence (50 -30 ) Specificity/Amplicon size References
ITS1a
tccgtaggtgaacctgcgg
S. lacrymans/588 bp
Moreth and Schmidt (2000)
L
aatgttgtcttgcgacaacg
S. hymantioides/429 bp
Moreth and Schmidt (2000)
ITS1
tccgtaggtgaacctgcgg
H
tcccacaaccgaaacaaatc
C. puteana/633 bp
Moreth and Schmidt (2000)
ITS1
tccgtaggtgaacctgcgg
C
agtagcaagtaaggcataga
D. expansa/544 bp
Moreth and Schmidt (2000)
ITS1
tccgtaggtgaacctgcgg
D
tcgccaaaacgcttcacggt
ITS1
tccgtaggtgaacctgcgg
A. vaillantii/517 bp
Moreth and Schmidt (2000)
A
caccgataagccgactcatt
G. sepiarium/398 bp
Moreth and Schmidt (2000)
ITS1
tccgtaggtgaacctgcgg
G
gttaataaaaaccgggtgag
a
Universal forward primer designed by White et al. (1990)
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Table 12.2 PCR assays for the identification of important root and butt rot agents of forest trees
Primer pairs Primer sequence (50 -30 )
References
Specificity/Amplicon
DNA
target site
size
Schulze et al.
ARM-1
agggtatgtgcacgttcgac
Armillaria spp./660 bpa ITS
ARM-2
ggaaagctaagctcgcgcta
(1997)
AR-1
ctgacctgttaaagggtatgtgc
Armillaria spp./690–
ITS
Lochman et al.
AR-2
aagctgaatccttctacaaagtcaa
(2004)
724 bpb
IGS
Sicoli et al.
ATA1
ttgccttgaaccctgttataaggc A. tabescens/375–
ATA2
tgccaaaatcgttgcacgccgc
(2003)
381 bpb
A. mellea/631 bp
ITS
Sicoli et al.
AMEL3
ttgcttgcttacgagctaag
ITS4c
tcctccgcttattgatatgc
(2003)
A. mellea/364–387 bpb IGS
Sicoli et al.
AME1
aagaatcatgagatatcatcagt
AME2
ttagaaaatccgccttagaaac
(2003)
gcatcgatgaagaacgcagc
Armillaria spp./184 bp ITS
Guglielmo
ITS3c
et al. (2007)
Armi2R
aaacccccataatccaatcc
I. tomentosus/491 bp
ITS
Germain et al.
It-ITS-209-f gctaaatccactcttaacac
It-ITS-700-rc aggagccgaccacaaaagat
(2002)
PW164
gcttccatttttcttagg
P. weirii s.s./495 bp
ITS
Lim et al.
PW659
tcaaaagggcgtattaatg
(2005)
a
The size is referred to the amplicon obtained from A. ostoyae DNA extracts
b
Depending on the isolates or species considered, the size of amplicon varies between the reported
values
c
Universal primers designed by White et al. (1990)
spruce (Bahnweg et al. 2002), whereas primers designed on cloned DNA fragments
derived from random amplified microsatellites (RAMS) markers proved to be
suitable to distinguish H. annosum s.s. and H. parviporum (Hantula and Vainio
2003). A summary of taxon-specific priming PCRs developed for the identification
of H. annosum species is reported in Table 12.3.
Taxon-specific primers were designed on ITS region for two other important
root rot conifer pathogens, namely P. weirii s.s. and I. tomentosus (Germain et al.
2002; Lim et al. 2005) (Table 12.2), as well as for other significant hardwoods
pathogens, such as Ganoderma species causing the basal stem rot of oil palm
(Utomo et al. 2005); Phlebia brevispora Nakasone, involved in butt rot of Japanese
cypress (Suhara et al. 2005); and Phellinus noxius, a destructive pathogen of several
woody plants in Asia (Tsai et al. 2007).
Three multiplex PCRs based on 11 taxon-specific primers designed on either
nuc- or mt-rDNA regions allowed detecting several decay fungi, such as Armillaria
spp., Ganoderma spp., Inonotus spp., K. deusta, Laetiporus spp., P. fraxinea, and
Phellinus spp., reported as hazardous for tree stability in Europe and North America
(Guglielmo et al. 2007; Nicolotti et al. 2009). Two further multiplex PCR reactions
were developed to detect and identify at subgeneric levels the most hazardous wood
decay fungi belonging to Ganoderma, Phellinus, and Inonotus (Guglielmo et al.
2008b). These methods were validated in the field and proved to be highly sensitive,
allowing the detection of down to 10 1 pg of target DNA per 1 mg wood DNA
extracts (Guglielmo et al. 2007). A summary of these multiplex PCRs, with related
taxon-specific primers, is reported in Tables 12.4 and 12.5.
264
Table 12.3 TSCP-PCR and PCR assays developed for identification of H. annosum species
Primers combination and sequence (50 –30 )
Specificity/Amplicon size
Forward
Reverse
ITS1Fa (cttggtcatttagaggaagtaa)
ITS4
Fungi
H. annosum Am-P/518 bp
ITS P1 (gtcggtcgggttcttttgatc)
H. annosum Am-S/486 bp
ITS S1 (gccgcgtcttctcacaaact)
MLF (taaaaatttaaattagccataa)
Mito7 (gccaatttattttgctacc)
H. annosum s.s./230 bp
Mito5 (taagaccgctatawaccagac)
H. abietinum/195 bp
H. parviporum/185 bp
MLS (aaattagccatattttaaaag.)
EfaHaFor (ctatgtcgcggtacagcttg)
EfaHaRev (gcgaggayaagaagtaatcagca) H. annosum spp./169 bp
H. annosum Am-P/71 bp
EfaNAPFor (gtacatggtcactgtacgtagatgc)
H. annosum s.s./69 bp
EFAEuPFor (atggtcactgtacgtagatcatgc)
MJ-F (ggtcctgtctggctttgc)
MJ-R (ctgaagcacaccttgcca)
H. annosum s.s./100 bp
H. parviporum/350 bp
KJ-F (ccattaacggaaccgacgtg)
KJ-R (gtgcggctcattctacgctatc)
H. annosum spp./400 bp
HET-7 (cttctcacaaactcttcg)
HET-8 (caggtcccccacaatcg)
a
Universal primer designed by Gardes and Bruns (1993)
Target site
References
ITS
Garbelotto et al. (1996)
Mt-LrDNA
Garbelotto et al. (1998);
Gonthier et al. (2001,
2003)
Gonthier et al. (2007)
EFA
IGS
Unknown
ITS
Hantula and Vainio (2003)
Bahnweg et al. (2002)
G. Nicolotti et al.
Advances in Detection and Identification of Wood Rotting Fungi
265
Table 12.5 Multiplex PCR assays developed by Guglielmo et al. (2008b) for identification of hazardous wood rotting fungi within Ganoderma, Inonotus and
Phellinus
Multiplex PCR
Primers combination and sequence (50 -30 )
Specificity/ Amplicon size
Target site
Forward
Reverse
Mgano
ITS1-F
GadR (caggcaacaagtgcgctc)
G. adspersum, G. pfeifferi, G. applanatum (from North
ITS
America)/211 bp
GapR (gacacgcttcacaagctcc)
G. applanatum (from Europe)/200 bp
G. lucidum (from Europe)/193 bp
GlR (ttcacgaagccccgcaag)
G. resinaceum, G. lucidum (from North America)/178 bp
GrR (aagagcccgcttcacaacg)
Fomitiporia (P. punctatus, P. robustus)/258 bp
Nuc-LrDNA
Mhyme
25sF
FomR (cccagcccatgtatacaatag)
FuscR (cacactccgaagagtgcc)
Fuscoporia (P. contiguus, P. gilvus, P.torulosus)/ 225 bp
I. dryadeus/254 bp
IdryaR (accgacgcatacaacaaagg)
Inocutis (I. dryophilus)/265 bp
InocuR (cctcagtccccgacggt)
Inonotus s.s. (I. andersonii, I. hispidus, I. obliquus)/
InssR (gatgttgacccgtccgac)
214 bp
PhssR (ggcgctacattccctctg)
Phellinus s.s. (P. igniarius, P. tremulae, P. tuberculosus)/
173 bp
12
Table 12.4 Multiplex PCR assays developed by Guglielmo et al. (2007) for identification of important wood rotting fungi hazardous for tree stability
Specificity/Amplicon size
Target Site
Multiplex PCR
Primers combination and sequence (50 -30 )
Forward
Reverse
M1
ITS1F
ITS4
Fungi
ITS
Gano2R (tatagagtttgtgataaacgca)
Ganoderma spp./226–228 bp
Inonotus spp. and Phellinus spp./111 bp
Nuc-LrDNA
F115 (taagcgacccgtcttgaaac)
Hyme2R (tgcdccccctygcggag)
Hericium spp./199 bp
Nuc-LrDNA
M2
25sF (tggcgagagaccgatagc)
Heri2R (cagcccttgtccggcagt)
LaetR (ccgagcaaacgaatgcaa)
L. sulphureus/146 bp
Pleurotus spp./158 bp
Pleu2R (aaccaggaagtacgcctcac)
Armillaria spp./184 bp
ITS
ITS3
Armi2R (aaacccccataatccaatcc)
M3
ITS3
PerR (atctgcaaagaccggtaaggt)
P. fraxinea/152 bp
ITS
Schizophyllum spp./191 bp
Schi2R (ctccagcagacctccacttc)
Stereum spp./234–240 bp
Ste2R (gtcgcaacaagacgcactaa)
K. deusta/260 bp
Ustu2Rb (gctcatctctacaggcgagaa)
TraR (ttcatagtcttatggaaaccgc)
Trametes spp./220 bp
Mt-SrDNA
MS1a (cagcagtcaagaatattagtcaatg)
a
Universal primer designed by White et al. 1990
b
Primer designed by Nicolotti et al. (2009)
266
G. Nicolotti et al.
Taxon-specific priming PCR is the major tool for detection and identification of
wood rotting fungi. Indeed, this method is reproducible, specific, fast, easy to
perform, and useful for analysis of environmental samples. However, a preliminary
knowledge of the nucleotide sequence of target site is necessary, as well as a long
work on primer design and testing for specificity and possible cross-reactions with
other nontarget fungi.
12.5.6 Real-Time PCR
Real-time PCR combines the conventional PCR with the generation of a fluorescent
signal that depends on the amount of amplified DNA in each cycle. A detection
system allows the measurement of this signal throughout the reaction, providing a
real-time analysis and quantification of the specific DNA targets (Schmittgen
2001). The initial DNA amount of target DNA in the reaction can be related to a
cycle threshold (Ct), defined as the cycle number at which there is a statistically
significant increase of fluorescence. This method can thus be quantitative and does
not require a further electrophoretic run to detect the amplicon. The most popular
real-time PCR methods, such as Taq-man (Lee et al. 1993), Molecular beacons
(Tyagi and Kramer 1996) and Scorpion-PCR (Whitcombe et al. 1999), are based on
the use of a fluorescent reporter dye and a quencher linked to probes. These probes
are designed to be specific to a complementary site in the amplicon. Real-time PCR
has thus an increased specificity with respect to conventional PCR.
A multiplex real-time PCR assay was developed to monitor the dynamics of
Picea abies-H. annosum pathosystems (Hietala et al. 2003). In this study, real-time
PCR proved to be more effective than traditional methods in screening clone
resistance to the pathogen both under laboratory and field conditions. For diagnostic
purposes, real-time PCRs were developed for R. necatrix and Fuscoporia torulosa
(Pers.) T. Wagner & M. Fisch. (Campanile et al. 2008; Schena and Ippolito 2003).
Real-time PCR allowed detection of R. necatrix both in infected plants and in
contaminated soils with higher sensitivity than traditional isolation methods and
baiting systems, respectively.
Although real-time PCR methods are more rapid than conventional PCR and,
thus being more appropriate for routinely diagnostics, the need of costly machines
and reagents has limited so far their use in the field of diagnostics of wood rotting
fungi.
12.5.7 DNA Sequencing
As stated above, preliminary knowledge of nucleotide sequence of the target DNA
region is paramount for the development of efficient diagnostic tools, such as
12
Advances in Detection and Identification of Wood Rotting Fungi
267
taxon-specific primers and RFLP markers. Additionally, the DNA sequence itself
can also be used as a straightforward and powerful means of identification
potentially exploiting polymorphism not only at a restricted site but everywhere
in the DNA region considered. For this purpose, PCR product obtained from DNA
extracts of the unknown sample is subjected, tout court or after a cloning step, to a
sequencing reaction that leads, through high-resolution capillary analyzers, to a
chromatogram displaying the complete nucleotide sequence for the DNA fragment. The unknown sequence is then compared, through Basic Local Alignment
Search Tool (BLAST), to other sequences deposited in GenBank, which is an
annotated database of all available nucleotide and amino acid sequences (Altschul
et al. 1990). With the help of Expect (E) values, which report the significance of
matches, it is possible to detect species displaying the highest sequence similarity
with the unknown isolate. Large amounts of rDNA sequences, provided by several
taxonomic and phylogenetic studies (Chillali et al. 1998; Hong and Jung 2004; Ko
and Jung 1999; Larsson and Larsson 2003; Wagner and Fischer 2002), are
increasingly available in GenBank for most of wood decay fungal taxa. The
same is true for sequences of other nuc- and mt-DNA regions, such as ATP
synthase subunit 6 (ATP), calmodulin (CAM), elongation factor 1-a (EFA), and
glyceraldehyde 3-phosphate dehydrogenase (GPD) (Johannesson and Stenlid
2003; Linzer et al. 2008).
Direct sequencing of ITS combined with BLAST search has proved to be
effective and reliable for the identification of fungi directly from wood in construction (Högberg and Land 2004). The comprehensive database of ITS and ribosomal
genes sequences provided by Moreth and Schmidt (2005) for the most important
house rot species may be helpful to increase the chance of identification by means
of BLAST analysis.
Sequencing, after nested PCR, was helpful for the identification of H. annosum
species in forests (Gonthier et al. 2003). Interestingly, sequencing was also helpful
for the detection of an exotic root rot pathogen of forest trees in Italy (Gonthier et al.
2004). Sequence analysis of two nuclear loci and one mitochondrial locus showed
that individuals from an Italian stone pine stand belonged to H. annosum Am-P
(Gonthier et al. 2004). In a further study aimed at describing the patterns of invasion
of this exotic pathogen, Gonthier et al. (2007) proved, through sequencing of the
same loci, the occurrence of hybrids between North American and European
Heterobasidion species.
Finally, ITS sequencing of DNA extracted from both fruit bodies or decayed
wood is a method currently used to investigate the fungi associated to root and heart
rot of Acacia mangium (Glen et al. 2006).
Although sequencing is very powerful for the identification of wood decay
fungi, even directly from environmental samples after cloning, it appears too
expensive as a routine analysis method. Furthermore, since in some cases species
designation of the submitted organism in GenBank was wrong (Camacho et al.
1997; Redecker et al. 1999), a careful interpretation of the results from BLAST
search is necessary.
268
Table 12.6 Comparison of diagnostic techniques for wood rotting fungi in terms of preliminary requirements and main features
Diagnostic technique
Requirement of:
Specificity
Reproducibility
Cost
Fruit bodies
Isolation of
Mycological
background
pure cultures
Analysis of fruit bodies
Yes
No
Yes
High
Medium
Very low
Analysis of pure fungal cultures
No
Yes
Yes
Medium
Medium
Low
Protein-based techniques
No
Yes
No
High
Low
Medium
Immunological techniques
No
No
No
Medium
Medium
Medium
RAPD-PCR
No
Yes
No
High
Low
Low
No
High
High
Medium
PCR-RFLP
No
Yesa
T-RFLP
No
No
No
High
High
High
Taxon-specific priming PCR
No
No
No
High
High
Low
Real-Time PCR
No
No
No
High
High
High
DNA-sequencing
No
Yesa
No
High
High
High
Microarrays
No
No
No
High
High
High
a
Not required in case of preliminary cloning of PCR products
Time
required (days)
1–2
20–60
7–15
2–15
7–15
8–16
3–5
1–3
1–2
4–6
1–2
G. Nicolotti et al.
12
Advances in Detection and Identification of Wood Rotting Fungi
12.6
269
Conclusion and Perspectives
The introduction of DNA-based identification tools has overcome several limits of
traditional methods and protein-based methods, allowing for rapid fungal diagnosis
even in the absence of unequivocal rot signs and directly from wood without the
need of a time-consuming isolation step (Table 12.6). Through DNA-based techniques, identification of wood decay fungi can be performed at early stages of
fungal infection, making possible effective timely treatments against harmful house
rots and reducing risks of tree failures in urban environment. Further, most DNAbased techniques provide straightforward diagnostic characters easy to interpret,
independently of factors related to environment and stage of fungal development.
Advances in DNA-based phytodiagnostics are mainly addressed to the development of rapid methods allowing samples to be simultaneously screened for a large
number of pathogens (Mumford et al. 2006). Multiplex taxon-specific PCRs have
already allowed successful identification of several wood decay fungal species in a
few assays (Guglielmo et al. 2007, 2008b). A more powerful tool for parallel testing
of many targets in a single reaction is provided by microarrays, which are based on
specific hybridization events between nucleic acid in a sample and known nucleic
acid probes linked to a solid phase. A basic array method, the hybridization of
immobilized sequence-specific oligonucleotide probes with PCR amplified fungal
rDNA (SSOP) , has already been proved to be a valuable and sensitive tool for
simultaneous detection of decay fungi involved in the deterioration of wood
products in service (Oh et al. 2003).
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Chapter 13
Molecular Diversity and Identification
of Endophytic Fungi
Liang-Dong Guo
Abstract Endophytes are organisms inhabiting the living plant organs at some
time in their life, without causing apparent harm to the host. Endophytic fungi,
which have been widely studied in various geographical and climatic zones, are
ubiquitous and occur within all examined plants including a broad range of host
orders, families, genera, and species in diverse ecosystems. DNA fingerprinting and
sequencing techniques employed in the population genetic diversity and in the
detection and identification of endophytic fungi are summarized in this chapter.
13.1
Introduction
The term “endophyte,” originally introduced by De Bary (1866), refers to any
organisms occurring within plant tissues, distinct from the epiphytes that live on
plant surfaces. Carroll (1986) defines endophytes as mutualists, those fungi that
colonize aerial parts of living plant tissues and do not cause symptoms of disease.
Pathogenic and mycorrhizal fungi are excluded from this definition. Petrini (1991)
considers that endophytes are organisms inhabiting the living plant organs at some
time in their life, without causing apparent harm to the host. Therefore, latent
pathogens known to live symptomlessly inside the host tissues and organisms that
have an epiphytic phase in their life cycle are also endophytes. This latter definition
is broad enough to include virtually any microbes and vascular plants that colonize
the living internal tissues of plants (Bills 1996; Stone et al. 2000; Schulz and Boyle
2005, 2006). However, mycologists have come to employ this term “endophyte” (or
endophytic fungi and fungal endophyte) only for those fungi that colonize a plant
L.‐D. Guo
Systematic Mycology & Lichenology Laboratory, Institute of Microbiology, Chinese Academy
of Sciences, Beijing 100101, China
e-mail: guold@sun.im.ac.cn
Y. Gherbawy and K. Voigt (eds.), Molecular Identification of Fungi,
DOI 10.1007/978-3-642-05042-8_13, # Springer-Verlag Berlin Heidelberg 2010
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without causing visible disease symptoms at any specific moment (Petrini 1991;
Wilson 1995; Stone et al. 2000; Schulz and Boyle 2005).
Endophytic fungi, which have been widely studied in various geographical and
climatic zones, are ubiquitous and occur within all examined plants including a
broad range of host orders, families, genera, and species in diverse ecosystems
(Petrini 1991; Wilson 1995; Stone et al. 2000; Guo 2001; Schulz and Boyle 2005;
Li et al. 2007; Sun and Guo 2007; Wei et al. 2007; Guo et al. 2008; Sun et al. 2008).
Most endophytic fungi are members of the Ascomycota or their mitosporic fungi
but can also include some taxa of the Basidiomycota, Zygomycota, and Oomycota
(Zheng and Jiang 1995; Sinclair and Cerkauskas 1996). Because the plant tissues
are multilayered and spatially and temporally diverse microbial habitats, they
support a rich and varied endophytic mycobiota that form specialized association
with various plant species and tissues. Consequently, an accepted estimate of 1.5
million fungal species exists on earth primarily based on the ratios of vascular
plants to fungal species at 1:6, but endophytic fungi have not been seriously taken
into account in the estimation (Hawksworth 1991). Furthermore, Petrini (1991)
suggests that there should be more than 1 million species of endophytic fungi
remaining to be discovered and described in the world based on the ratios of
vascular plants to fungal species at 1:4–5.
In the survey of endophytic fungal diversity, many techniques have been used;
traditional cultivation-dependent techniques, however, have been routinely
employed in previous studies. In the cultivation-dependent methods, living plant
tissues are subjected to a serial process of surface sterilization in order to remove all
organisms from the surface of plant tissues. Only internal fungi are isolated by
means of the incubation of the plant samples onto nutrient plates. The cultivationdependent techniques have generally involved three basic steps: (1) surface sterilization of plant tissues to kill any fungi on the host surface, (2) isolation of
endophytic fungi growing out from samples placed onto nutrient agar, and
(3) identification of the endophytic fungi based on morphological characteristics
in culture. The advantage of the cultivation-dependent method is that this technique
is effective for rapid recovery of a large number of endophytic fungal species from
plant tissues. However, the study of endophytes is a method-dependent process.
Endophytic fungal communities obtained from plants are directly affected by
surface sterilization techniques and incubation conditions, and whether the isolates
sporulate. Therefore, there are limitations in the cultural isolation techniques: (1) It
is rather laborious and time intensive and is not suitable to compare large numbers
of samples; (2) The large number of sterile isolates poses a special problem,
because they cannot be identified to any taxonomic category, while various methods have been used to promote sporulation of isolates in order to overcome the
shortcomings of some isolates failing to sporulate in culture (Taylor et al. 1999;
Guo et al. 1998, 2000, 2008); (3) Some fungi may be missed as a result of failure to
grow or some grow slowly and are easily outcompeted by fast-growing species in
artificial conditions. In order to overcome the potential technical bias, cultivationindependent approaches, e.g., molecular techniques, to analyze endophytic fungal
communities of plants are needed.
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Molecular techniques have been successfully used in the detection and identification of mycorrhizal fungi in roots and soils (Gardes et al. 1991; Simon et al. 1993;
Clapp et al. 1995; Chelius and Triplett 1999; Tedersoo et al. 2008); pathogenic
fungi directly from within plant tissues (Schesser et al. 1991; Mills et al. 1992;
Moukhamedov et al. 1994; Beck and Ligon 1995; Bates et al. 2001; Atkins et al.
2003, 2004); and fungi in Iceman’s grass clothing (Rollo et al. 1995), bamboos
(Zhang et al. 1997), and glacial ice strata (Ma et al. 1997). In this chapter, molecular
techniques, i.e., DNA fingerprinting and sequencing methods, employed in the
population genetic diversity and in the detection and identification of endophytic
fungi, excluding mycorrhizal fungi, are briefly summarized.
13.2
Molecular Fingerprinting for Endophytic Fungal
Population
DNA fingerprinting techniques, such as restriction fragment length polymorphism
(RFLP), terminal-RFLP (T-RFLP), random amplified polymorphic DNA (RAPD),
simple sequence repeat (SSR) or inter-SSR (ISSR), amplified fragment length
polymorphism (AFLP), denaturing gradient gel electrophoresis (DGGE), temperature gradient gel electrophoresis (TGGE), and single-stranded conformation polymorphism (SSCP), are well established and have been successfully applied to
assess the population genetic diversity and fungal communities in natural environment (Gardes et al. 1991; Simon et al. 1993; Chambers et al. 1999; Smit et al. 1999;
Tooley et al. 2000; van Elsas et al. 2000; Bock et al. 2002; Klamer et al. 2002;
Anderson et al. 2003; Huai et al. 2003; Jansa et al. 2003; Anderson and Cairney
2004; Liang et al. 2004, 2005). These techniques have recently been adopted and
applied to assess the population structure and community of endophytic fungi.
13.2.1 RAPD and RFLP Techniques
The RAPD technique is used to investigate the genotypic diversity in populations of
an endophytic fungus Rhabdocline parkeri isolated from Douglas fir growing in
various habitats (McCutcheon and Carroll 1993). A significantly lower number of
R. parkeri genotypes per unit foliage have been isolated from trees within a
20-year-old managed stand and from an isolated tree than from old growth trees.
Therefore, the variation of genetic diversity of R. parkeri populations is ascribed to
differences in tree age and access to inoculum. Furthermore, the genotypes of an
endophytic fungus Discula umbrinella are related to host origin on the basis of the
analysis of 30 strains isolated from beech, chestnut, and oak assessed by RAPD
markers (Hämmerli et al. 1992). The population structure of an endophytic fungus
Phialocephala fortinii has been studied at a primary succession site on a glacier
forefront using RAPD markers, and 23 genets of P. fortinii were detected in 34
strains in 1 year, and 10 genets were found in 49 strains in the next year, but none of
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the genets was isolated in both years (Jumpponen 1999). Further studies show that
there are recombination, gene, and genotype flow in P. fortinii population based on
the analysis of single-locus RFLP markers (Grünig et al. 2003). In addition, all
strains of endophytic Phyllosticta species isolated from different tropical tree
species in India have been identified as species Phyllosticta capitalensis using
ITS-RFLP markers (Pandey et al. 2003).
13.2.2 SSR and AFLP Techniques
SSR or ISSR technique, which is originally used to measure genetic diversity of
plants and animals (Zietkiewicz et al. 1994), has been applied in studies of fungi
(Hantula et al. 1996; Hantula and Müller 1997; Liang et al. 2005). In endophyte
studies, Groppe et al. (1995) have analyzed the genetic diversity of an endophytic
fungus Epichloe¨ typhina isolated from tissues of Bromus erectus using a microsatellite-containing locus as molecular markers. Further, Groppe and Boller (1997)
have developed specific primer pairs flanking a microsatellite-containing locus and
successfully detected a rDNA fragment of endophytic Epichloe¨ species from
infected tissues of B. erectus, but no fragments were generated from total DNA
isolated from uninfected plant material or unrelated fungi isolated from the same
grass. Further studies have shown that there are high levels of polymorphism
between Neotyphodium and Epichloe¨ species and low levels of polymorphism
within Neotyphodium coenophialum and N. lolii based on the analysis of polymorphic SSR markers, and these markers can be used to identify endophytic fungi
Neotyphodium and Epichloe¨ and to evaluate intraspecific population genetic diversity (De Jong et al. 2003).
Four different morphotypes of an endophytic fungus Sphaeropsis sapinea have
been isolated from the natural and exotic Pinus spp. in the Southern Hemisphere
(Burgess et al. 2001). Of these morphotypes, the putative I is found to be identical to
Botryosphaeria obtusa, the other remaining three are clearly distinguished using
polymorphic SSR markers. Endophytic fungi P. fortinii and type I of a nonsporulating mycelium, which have the same allozyme phenotype, were differentiated on
the basis of ISSR analysis (Grünig et al. 2001). Furthermore, 21 genets were
detected in 144 P. fortinii strains isolated from roots of Norway spruce (Picea
abies) collected within a plot (3 3 m2) of a 40-year-old plantation using ISSR
markers (Grünig et al. 2002). Further population genetic studies suggest that the
endophytic fungus P. fortinii population has high genetic diversity and should be
considered cryptic species in the same forest site and even in the same root
fragment in Europe (Grünig et al. 2004, 2006, 2007, 2008).
The relationship between endophytic population genotypes and hosts, age, and
geographic origin has been investigated on the basis of the SSR analysis. A high
genetic diversity in an endophytic fungus Alternaria alternata population isolated
from Pinus tabulaeformis in Beijing was detected and no relationship between
genotypes of A. alternata and host tissue ages (Guo et al. 2004) was found.
Similarly, the genotypes of an endophytic fungus Guignardia mangiferae do not
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correspond either to the host or to the geographic origin (Rodrigues et al. 2004), and
there is no host specificity for isolates of an endophytic fungus Lasiodiplodia
theobromae, although there is very high gene flow between populations from
different hosts based on the SSR analysis (Mohali et al. 2005).
AFLP markers were used to analyze the genetic polymorphism existing in two
natural populations of an endophytic fungus Epichloe¨ festucae in semiarid natural
grasslands in western Spain, and most genetic variation detected was found to occur
within populations, with only a moderate amount of genetic differentiation between
populations, and nonrecombinant asexual reproduction predominated in both populations (Garcı́a et al. 2002).
The SSR (or ISSR) technique is comparatively cheap, fast, and easy to perform. It
is similar to RAPD analysis, but longer primers (ca. 18 nucleotides) are used and the
conditions (e.g., annealing temperature) during amplification are more stringent.
Furthermore, genomic regions containing microsatellites evolve and mutate more
rapidly than other areas of genome. This is due to slipped-strand mispairing during
replication, with the slippage rate depending on the length of the repeat (Levinson
and Gutman 1987; Burgess et al. 2001). Therefore, the use of higher annealing
temperatures and longer nucleotide primers results in highly reproducible SSR
markers that are much more robust than the RAPD markers used previously (Roberts
et al. 2000; Peever et al. 2002; Liang et al. 2005). The SSR markers are also more
powerful than the RFLP profiles generated from rDNA in revealing genetic variation
among a set of closely related isolates (Adachi et al. 1993; Aradhya et al. 2001).
Thus, SSR (ISSR) technique combines most of the benefits of RAPD and microsatellite analyzes, and is ideal for studies of genetic variation of endophyte population.
There are arguments against using SSR (ISSR) techniques, as compared to AFLP
and RAPD, in population genetic studies. Although microsatellite alleles are considered to be codominant markers, differences in alleles are measured solely on the
basis of size. There is therefore the possibility of single-point mutations within the
flanking sequence that do not result in a change in the fragment length. Furthermore,
fragments from different genomic regions can co-migrate because they are of the
same size. It is possible that different indels could result in fragments of the same
size that have different sequences. In addition, markers may not be independent,
because of genetic linkage or being alternative alleles at the same locus. In an
asexual fungus, however, meiotic segregation of markers cannot occur, and although
co-migration may occur, this does not negate the usefulness of this approach. Thus, a
dominant marker system is suitable for assessing haploid, asexual populations
without overestimating variation due to co-segregation (Bock et al. 2002).
13.2.3 DGGE Technique
The DGGE technique, which is capable of separating closely related sequences
by their differential mobilities in a gradient of denaturants, has been effectively
used to estimate the diversity of prokaryotes and eukaryotes in natural samples
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(Dı́ez et al. 2001; Dar et al. 2005; Countway et al. 2005; Jeewon and Hyde
2006). This technique has recently been successfully applied to document fungal
communities (Kowalchuk et al. 1997; Vainio and Hantula 2000; May et al. 2001;
Nikolcheva et al. 2003). In endophyte studies, Duong et al. (2006) used DGGE
coupled with sequence analysis of partial 18S rRNA gene to assess endophytic
fungal diversity in living leaves of Magnolia liliifera collected from Thailand. A
total of 14 operational taxonomic units were recovered, and the DGGE could be
used to detect known and abundant fungi (Xylariales, Hypocreales, and Pleosporales) as well as unknown endophytic fungi (Mycosphaerellales, Dothideales,
Helotiales, and Rhytismatales). Similarly, the composition and relative abundance
of endophytic fungi were assessed by DGGE analysis of 18S rRNA gene fragments
amplified from total community DNA extracted from roots of potato Solanum
tuberosum (Götz et al. 2006). Dominant bands in DGGE correspond to Verticillium
dahliae, Cylindrocarpon destructans, and Colletotrichum coccodes, as the most
frequently isolated species by traditional cultural method. Therefore, differences in
the relative abundance of endophytic fungi colonizing the roots of T4-lysozyme
producing potatoes and the parental line can be detected by DGGE methods.
DGGE is a suitable method that can be applied to estimate fungal diversity by
excising and sequencing bands, thereby obtaining taxonomic information for
members of the community via database searches and phylogenetic analysis
(Anderson and Cairney 2004; Duong et al. 2006). Simultaneously, the techniques
can be used in conjunction with DNA oligonucleotide probes to increase the
specificity of the analysis (Stephen et al. 1998). Despite the advantages of
DGGE, there are also disadvantages. In general, shorter fragments (<500 bp) of
DNA result in better resolution between bands in a profile, thereby limiting the
taxonomic information to properly identify taxa at the genus or species level (May
et al. 2001; Duong et al. 2006), although some larger products have also been used
successfully in a few cases (Ranjard et al. 2000). Moreover, even the most sensitive
staining methods are often not sensitive enough to detect all the diversity present
within a sample, particularly for the less dominant members of the fungal community (Anderson and Cairney 2004). In addition, in some cases single bands on a gel
have been shown to comprise more than a single sequence type (Schmalenberger
and Tebbe 2003). Further studies should consider primers that are more universal
for fungi and give better phylogenetic resolution at generic or species level.
13.3
Molecular Sequencing for Endophytic Fungal Community
Molecular fingerprinting techniques are inadequate for the analysis of fungal communities from environmental samples where several different fungi may be simultaneously present and where their identities unknown. However, molecular
sequencing techniques have been successfully employed for fungal identification
and phylogenies based on the sequence analyses of coding genes, e.g., cytochrome
c oxidase 1 (CO1) gene, beta-tubulin 2 gene (tub2), and 18S, 28S and 5.8S genes of
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Molecular Diversity and Identification of Endophytic Fungi
283
rDNA and noncoding internal transcribed spacer (ITS) regions of rDNA. Because
most coding genes are highly conserved, they have been successfully used to assess
phylogenetic relationships at higher taxonomic levels. The CO1, tub2, and ITS
regions benefit from a fast rate of evolution, resulting in greater sequence variation
between closely related species. These region sequences therefore generally provide greater lower taxonomic resolution at genus and species level. Molecular
sequencing techniques have recently been successfully used in the detection and
identification of endophytic fungi based on phylogenetic analysis and sequence
similarity comparison.
13.3.1 Identification of Endophytic Fungi
The endophytic fungal community of roots of healthy conifers Douglas-fir (Pseudotsuga menziesii) and ponderosa pine (Pinus ponderosa) has been surveyed in the
dry forests on the eastern slope of the Cascade Mountains in Washington, USA
(Hoff et al. 2004). A total of 27 fungal genera were isolated and identified using a
combination of morphological and molecular (ITS region sequences) methods.
Fourteen genera were isolated from ponderosa pine, and nine genera from
Douglas-fir. Most of the fungi isolated are ascomycetes and zygomycetes, and a
few are basidiomycetes. Of these, endophytic fungi Byssochlamys nivea, Umbelopsis spp., and Mucor sp. are the most frequently recovered fungi from ponderosa
pine and Douglas-fir. Similarly, a new endophytic fungus Pestalotiopsis hainanensis isolated from healthy branches of Podocarpus macrophyllus in tropical China
was identified by a combination of morphological characteristics and ITS and tub2
sequence analyses (Liu et al. 2007).
Based on ITS rDNA sequence similarity (95%) to operationally designate
species boundaries, a total of 277 fungal species were recovered from 1,403
endophytic strains isolated from common plants in arctic, boreal, temperate, and
tropical localities, which represent phylogenetically diverse plant taxa (Arnold and
Lutzoni 2007). Similarly, a total of 439 isolates representing 24 morphotaxa were
isolated from asymptomatic foliage of loblolly pine (Pinus taeda) in North
Carolina, USA. Sequence data from ITS region for 150 isolates revealed 59 distinct
ITS genotypes that represent 24 and 37 unique groups based on 90% and 95%
sequence similarity, respectively (Arnold et al. 2007).
In some studies not only the ITS region but also 18S and 28S rDNA fragments
have been employed in the identification of endophytic fungi at various taxonomic
levels. Diversity of endophytic fungi isolated from bamboos Phyllostachy and Sasa
species were studied based on the analyses of 18S rDNA gene and ITS region
sequences, and 71 representative strains were placed into Sordariomycetes and
Dothideomycetes. Of these, fungi Xylariales is the dominant group within bamboos
and several rDNA gene sequences are not similar to any current sequence in the
database and might be novel species or genera (Morakotkarn et al. 2007). Similarly,
a total of 47 distinct genotype groups based on 90% ITS sequence similarity were
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L.-D. Guo
obtained from 280 representative strains isolated from healthy photosynthetic tissues
of three plant species (Huperzia selago, Picea mariana, and Dryas integrifolia) in
northern and southern boreal forests and arctic tundra (Higgins et al. 2007). Further
phylogenetic analyses of combined data from 18S and 28S rDNA show that these
different genotypic endophytic fungi represent Dothideomycetes, Sordariomycetes,
Chaetothyriomycetidae, Leotiomycetes, and Pezizomycetes of Ascomycota.
13.3.2 Identification of Nonsporulating Endophytic Fungi
In traditional cultivation-dependent process of endophytic studies, endophytic isolates can be identified only on the basis of morphological characteristics if they
sporulate on the media. Despite the development of various methods to promote
sporulation, e.g., by growing them on modifications of artificial media and under
various incubation conditions (Guo et al. 1998, 2000; Taylor et al. 1999), the
number of isolates that do not sporulate ranges from 4.5– 54% of the total isolates
(Petrini et al. 1982, Espinosa-Garcia and Langenheim 1990; Johnson and Whitney
1992; Fisher et al. 1993; Guo et al. 2000, 2008; Photita et al. 2001; Cannon and
Simmons 2002; Kumaresan and Suryanarayanan 2002; Wang and Guo 2007; Sun
et al. 2008). Since conventional classification of fungi relies heavily on reproductive structures, these nonsporulating strains cannot be provided with taxonomic
names. In order to appreciate the considerable diversity of these mycelia sterilia in
culture, they are generally categorized as “morphotype” on the basis of similar
cultural characters (Taylor et al. 1999; Guo et al. 2000, 2003; Arnold et al. 2001;
Wang et al. 2005). Arrangement of taxa into different morphotypes, however, does
not reflect species phylogeny, because morphotypes are not real taxonomic entities
(Lacap et al. 2003; Guo et al. 2000; 2003; Wang et al. 2005). Molecular methods are
therefore required for the identification and understanding of the diversity of these
endophytic mycelia sterilia.
In our survey of endophytic fungi from fronds of Livistona chinensis in Hong
Kong, a large number of isolates (16.5% of total isolates) do not sporulate,
remaining as mycelia sterilia (Guo et al. 2000). These nonsporulating isolates
were grouped into 19 morphotypes on the basis of their cultural morphology.
Furthermore, nine morphotypes were identified to genus level (Diaporthe, Mycosphaerella, and Xylaria), five to family level (Pleosporaceae and Clypeosphaeriaceae), and the other five to ordinal level (Xylariales) on the basis of ITS sequence
similarity comparisons and phylogenetic analyses. Similarly, in our another study
of endophytic fungi of P. tabulaeformis in two distinct climatic sites of Liaoning
province of China, a large number of isolates (11% of total isolates) remained as
mycelia sterilia (Wang and Guo 2007). These nonsporulating isolates were grouped
into 74 morphotypes according to their cultural morphology, and were further
divided into 64 taxa on the basis of ITS sequence analyses. Of these morphotypes,
five are Basidiomycota and 69 are Ascomycota, and then two morphotypes were
identified as Fusarium sporotrichioides and Schizophyllum commune, respectively.
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Molecular Diversity and Identification of Endophytic Fungi
285
Twenty-two morphotypes were identified to generic level, seven to family
(Lophiostomataceae and Valsaceae) level, and four to ordinal (Helotiales and
Pezizales) level (Wang et al. 2005).
Fifty-nine of morphologically unidentifiable strains isolated from healthy stems
and pods of cacao (Theobroma cacao) trees in natural forest ecosystems and
agroecosystems in Latin America and West Africa were identified on the basis of
the sequence analyses of 28S rDNA (Crozier et al. 2006). The majority of the
isolates tested belong to Basidiomycota, particularly to corticoid and polyporoid
taxa. Some isolates come from rarely isolated genera, such as Byssomerulius, whilst
the most commonly isolated basidiomycetous endophyte is a member of the
cosmopolitan genus Coprinellus of Agaricales.
In our recent study of endophytic fungi of 20 lichen species in four sites of
China, a total of 340 isolates (17.9% of total isolates) did not produce any spores
and were divided into 51 morphotypes according to similar cultural characteristics.
These morphotypes were placed into 42 taxa, including Atheliales and Agaricales
of Basiodiomycota and Coniochaetales, Hypocreales, Pezizales, Pleosporales, Sordariales, and Xylariales of Ascomycota on the basis of ITS sequence analyses
(W.C. Li and L.D. Guo, unpublished data).
13.3.3 Identification of White Morphotype Strains
In our investigation of endophyte diversity from P. tabulaeformis at Dongling
Mountain mixed woodland, the Beijing Forest Ecosystem Research Station of the
Chinese Academy of Sciences in China (Guo et al. 2008), the sterile mycelia were
divided into different morphotypes on the basis of similar cultural characteristics.
Although some sterile isolates having similar cultural characters were grouped into
the same morphotype, these isolates might be distantly related taxa. Therefore, an
attempt was carried out to establish whether the isolates included in the same
morphotype were of the same fungal origin. A total of 18 sterile strains grouped
in the white morphotype were selected to evaluate the fungal origins of different
isolates using ITS sequence analyses (Guo et al. 2003). Molecular identification
showed that five strains belonged to species of Rhytismataceae, and the other 13
strains were identified to Rosellinia, Entoleuca, and Nemania of Xylariaceae
(Fig. 13.1). Our results indicate that strains grouped into white morphotype have
different fungal origins.
13.3.4 Detection and Identification of Endophytic Fungi
Within Plant Tissues
Because of the limitations of traditional isolation techniques, it is highly probable
that some or even numerous endophytic fungi are never isolated. This may be
286
L.-D. Guo
Fig. 13.1 One of 1,720 equally parsimonious trees generated from the ITS (ITS1, 5.8S and ITS2)
sequences of 48 taxa showing the relationships of 13 white morphotype strains with reference taxa.
The tree rooted with Amphisphaeria umbrina, Discostroma tosta, and Lepteutypa cupressi (Tree
length ¼ 1703, Consistency index ¼ 0.437, Homoplasy index ¼ 0.563, Retention index ¼ 0.66,
Rescaled consistency index ¼ 0.289). Bootstrap values greater than or equal to 50% (1,000
replicates) are shown at branches. Asterisks indicate the branches that collapse in the strict
consensus tree
13
Molecular Diversity and Identification of Endophytic Fungi
287
because some endophytic fungi cannot grow on the artificial media. Most of the
endophytic fungi isolated are also usually ascomycetes or their anamorphs. It is not
clear whether this is because isolation techniques preclude other fungi, or whether
only ascomycetes or their anamorphs constitute the endophytic fungal community.
In order to overcome the potential technical bias, molecular techniques have been
employed in the detection and identification of endophytic fungi including culturable and nonculturable fungi from the hosts. The molecular study generally
includes five steps: (1) The total genomic DNA (including fungi and plants) is
extracted from sterile plant tissues; (2) DNA fragments (e.g., ITS, 28S and 18S
rDNA) are amplified from total DNA with fungal primers; (3) Polymerase chain
reaction (PCR) products (bands) are separated by DGGE or are cloned into plasmids (e.g., pGEM-T vector); (4) Different single clones are screened using DNA
fingerprinting techniques (e.g., RFLP and SSCP) and different DGGE bands are
excised; (5) Representative clones and DGGE bands are sequenced and theoretically identified into various taxonomic levels on the basis of phylogenetic analysis
and sequence similarity comparison.
Endophytic fungal community of Marram grass (Ammophila arenaria) roots
were analyzed using DGGE with subsequent cloning and sequencing to identify the
fungi by amplification of partial 18S rDNA gene (Kowalchuk et al. 1997). Some
ITS fragments amplified from Picea foliages were identified as endophytic fungi
isolated from the same plant tissues using a cultivation-dependent method (Camacho
et al. 1997). In our study, fungal ITS regions were amplified directly from total
genomic DNA extracted from fronds of Livistona chinensis. A total of five different
cloned sequences of fungi were obtained; of these four cloned sequences were
identified as Glomerella (anamorph Colletotrichum), Mycosphaerella (anamorph
Cladosporium), and Herpotrichiellaceae of Ascomycetes, and the other one cloned
sequence belonged to Basidiomycetes which is not found using traditional cultivation-dependent method (Guo et al. 2001). The variation in endophytic fungal
diversity closely associated with roots, stems, and leaves of common reed (Phragmites australis) from two dry and two flooded sites at Lake Constance in Germany
were investigated on the basis of ITS sequence analysis (Wirsel et al. 2001). Most
isolates were Ascomycetes, and some were Basidiomycetes. The result indicates
that there are differences in distribution of endophytic fungi between dry and
flooded sites. Similarly, the differences in the composition and relative abundance
of endophytic fungi colonizing the roots of T4-lysozyme producing potatoes and
the parental line were detected by amplified 18S rRNA gene fragments from total
community DNA extracted from roots of potato Solanum tuberosum (Götz et al.
2006).
In the detection of endophytic fungi of Heterosmilax japonica tissues, a broad
spectrum of fungal ITS sequences was directly amplified from genomic DNA
extracted from host tissues (Gao et al. 2005). Of these fungal sequences some
were identified as Aureobasidium, Botryosphaeria, Cladosporium, Glomerella,
Mycosphaerella, Phomopsis, and Guignardia, the others (e.g., YJ4-61, YJ4-9 and
YJ4-70) were significantly similar to some uncultured environmental samples and
were not specifically affiliated with any currently documented fungal sequences in
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the NBCI GenBank database. Endophytic fungal rDNA fragments (28S and ITS)
were amplified from surface sterilized needles from 12 Pinus taeda trees in North
Carolina, USA (Arnold et al. 2007). Phylogenetic analyses of 28S rDNA indicate
that cloned endophytic fungi are distributed across multiple lineages of Ascomycota and Basidiomycota. Further identification of cloned endophytic fungi based on
ITS sequence analyses shows that there are at least four unique fungal species
within Basidiomycota and at least nine fungal species within Ascomycota. Ascomycetous endophytic fungi are primarily Dothideomycetes and Leotiomycetes,
which are commonly isolated from P. taeda using traditional cultural methods,
but no Sordariomycetes were recovered from cloned endophytic sequences,
despite the prevalence of this lineage among cultural endophytes. The results of
some previous studies show that the diversity of endophytic fungi detected with
molecular methods differs from that found using traditional cultivation-dependent
methods.
Although molecular techniques insight into diversity of endophytic fungi, there
is disadvantage in the identification of endophyte morphotypes based on ITS
sequence analysis. There is no criterion to delimit species boundary of ITS
sequence divergence. This is because, although some endophytic fungi have high
similarity in the ITS sequences and cluster together with high bootstrap support
with reference taxa, there is still insufficient information at present to determine
whether the terminal clades include one or more species in the phylogenetic
analysis. For most of the taxa included in the DNA sequence analyses, the level
of interspecific and intraspecific variations is still variable. Different levels of
variations have been reported in the different taxa in previous studies. A relatively
low substitution rate was reported in ITS sequences of several Armillaria species
(0.5%) from the Northern Hemisphere (Anderson and Stasovski 1992) and among
Sclerotium species (Carbone and Kohn 1993). On the contrary, there is a relatively
low level of homology (76.1%) between weakly virulent and highly virulent
isolates of Leptosphaeria maculans, while the ITS sequences differ in only four
nucleotide positions within the highly virulent isolates and in two nucleotide
positions within the weakly virulent isolates (Morales et al. 1993). Similarly,
there is great divergence among three ITS types of Fusarium sambucinum (4.6–15%),
while the divergence is extremely low (0–2.3%) within each type (O’Donnell
1992). Significantly, Arnold et al. (2007) have constructed well-supported phylogenies based on a ca. 600 bp of the 28S rDNA for 72 Ascomycota and Basidiomycota, 145 cultured endophytic fungi, and 33 environmental PCR samples. The result
shows that ITS genotype groups based on 90% sequence similarity are concordant
with 28S rDNA-delimited species. However, at present there appears to be absence
of definite criteria for interspecific and intraspecific level of nucleotide divergence
in ITS region sequences of fungi.
There are some limitations of the detection and identification of endophytic
fungi directly from within plant tissues using molecular techniques. Firstly, as only
sparse hyphae may exist within the plant tissues, some fungal DNA may be lost
during the DNA extraction process, thus only a minor fraction of fungal DNA is
included in the total DNA extracted from plant tissues. Secondly, there are
13
Molecular Diversity and Identification of Endophytic Fungi
289
inhibitors that may interfere with the PCR amplification in the DNA solution.
Thirdly, the universal primers may not completely match with some fungal template
DNA. In addition, it is important to take into consideration that surface sterilization may not have denaturized the DNA of epiphytes, although sodium hypochlorite
is relatively effective for this purpose. Therefore, it is likely to be difficult to
amplify all endophytic fungal DNA fragments from the total DNA samples.
Another limitation is the limited number of sequences, i.e., less than 1%, of the
estimated 1.5 million fungal species presented in NBCI GenBank and EMBL database, although there is daily increase in fungal DNA sequences in public databases
(Vilgalys 2003). In addition, misidentifications of named published sequences, of
which ca. 20% of the named sequences may be attributed to incorrectly named
organisms, may represent another problem restricting the feasibility of sequencebased identification of endophytic fungi (Vilgalys 2003; Hawksworth 2004).
13.4
Conclusions
Molecular fingerprinting techniques are powerful tools in the detection of population genetic structure and diversity of endophytic fungi. Further development of
these markers to allow detection of endophytes in planta will considerably enhance
their value, and will permit the sensitive detection of endophyte incidence in plant
populations. Molecular sequencing techniques offer an effective method for the
identification of endophytic fungi, particularly for nonsporulating isolates, and for
the detection of the viable but nonculturable fungi by directly amplified rDNA
fragments from plant tissues.
PCR-based molecular techniques are conventional PCR employed in the detection and identification of endophytic fungi in previous studies. These conventional
PCR can identify endophytic fungi specifically, but it cannot be used to quantify
endophytic fungal biomass within plant tissues. However, real-time PCR can detect
small quantities of DNA in environmental samples and has been successfully used
to determine the population density of some fungal species such as Pyrenophora sp.
(Bates et al. 2001), Plectosphaerella cucumerina and Paecilomyces lilacinus
(Atkins et al. 2003, 2004), and Hirsutella rhossiliensis (Zhang et al. 2006).
DNA barcoding systems employ a short, effective, standardized gene region to
identify species (Hebert et al. 2003; Blaxter 2003; Savolainen et al. 2005; Seifert
et al. 2007; Craig et al. 2008). To date, this technique has been extensively used in
the animal kingdom with a 648-bp region of the CO1 gene (Smith et al. 2005; Ward
et al. 2005; Hajibabaei et al. 2006). DNA barcodes were first employed in the
identification of fungi Penicillium species using CO1 gene (Seifert et al. 2007) and
ectomycorrhizal fungi in a Tasmanian wet sclerophyll forest by ITS regions
(Tedersoo et al. 2008). With the improvement of molecular techniques, e.g.,
DNA fingerprinting, DNA sequencing, real-time PCR, and DNA barcoding, they
will become routine, accurate, rapid, and sensitive techniques in the detection,
identification, and quantification of endophytic fungal diversity in future.
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L.-D. Guo
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Chapter 14
Molecular Identification of Anaerobic
Rumen Fungi
Martin Eckart, Katerina Fliegerová, Kerstin Hoffmann, and Kerstin Voigt
Abstract Anaerobic fungi are phylogenetically unique and form a separate group,
the Neocallimastigomycota, among the chitinous fungi. Until now six genera are
described within that phylum, namely the monocentric genera Neocallimastix,
Caecomyces and Piromyces as well as the polycentric genera Anaeromyces,
Cyllamyces and Orpinomyces. This chapter gives a brief survey of the fascinating
world of anaerobic rumen fungi, their phylogeny, and identification. The golden
standards of molecular identification as well as promising alternatives will be
discussed.
14.1
Introduction
The physiology of the microbial community is fundamental for understanding the
processes of anaerobic decomposition of plant material, and has an economic
relevance for mankind. The distribution of organisms within the rumen is essential
for our understanding of the biochemistry of cellulose degradation (Hungate 1966).
A major part of organisms within the rumen fluid encompasses bacteria and
flagellates, but fresh and undigested plant material is rapidly colonised by anaerobic
fungi. It is now generally known that the degradation of herbal carbohydrates by
rumen fungi accelerates the digestion by downsizing the plant tissue particles.
Those particles are subsequently more easily decomposed by bacteria and protozoa.
The effectiveness of digestion is an important contributor to the health of animals in
husbandry (Wulff 2001).
M. Eckart, K. Hoffmann, and K. Voigt
Institute of Microbiology, School of Biology and Pharmacy, University of Jena, Neugasse 25,
07743 Jena, Germany
e-mail: martin.eckart@uni-jena.de
K. Fliegerová
Department of Biological Basis of Food Quality and Safety, Institute of Animal Physiology and
Genetics, Czech Academy of Sciences, v.v.i., Vı́deňská 1083, 14220 Prague 4, Czech Republic
Y. Gherbawy and K. Voigt (eds.), Molecular Identification of Fungi,
DOI 10.1007/978-3-642-05042-8_14, # Springer-Verlag Berlin Heidelberg 2010
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Because of the economic and scientific interest in this topic, it is not surprising
that the first description of “flagellated organisms” living within the rumen was
given at the beginning of the twentieth century. But, astonishingly it needed more
than 60 years to discover these organisms to be fungi living without any oxygen.
The anaerobic environment is mandatory for the ecosystem rumen. It determines the
mode of life of microorganisms residing there. Besides being well-known prokaryotes, anaerobic fungi are important producers of short-chain fatty acids, which are
an essential source of nutrition for herbivores. Such a unique occupation of a special
ecologic niche by a group of heterotrophic, hyphal, and chitin containing eukaryotes
inevitably raises the question about the relationships of these fungi. Today, this
group is well supported by morphological and molecular data and accepted as the
Neocallimastigales (Li et al. 1993). Although the final position within the kingdom
Fungi is still unclear, it turned out to be a monophyletic group, as a basal lineage
besides or within the phylum Chytridiomycota, and is now recognised as phylum
(James et al. 2006). While a flagellated phase through the life cycle of chytridiomycetes is a case sui generis proved for Chytridiales, Rhizophydiales, Spizellomycetales, Blastocladiales, and Neocallimastigales, the rumen fungi are characterised
by another unique attribute inside the kingdom Fungi: they live in anaerobiosis.
Until now, only several species of gut fungi have been described, probably because
of the problematic cultivation and maintenance of these organisms and high morphological variability depending on growth conditions. Extensive studies of a broad
range of ruminants and application of modern methods in molecular biology will
probably bring deeper insights in microbial communities and species relationships.
This survey gives a brief overview of the historical background and of modern
trends in species recognition of this interesting fungal group.
14.2
Historical Background and the Discovery
of Rumen Fungi
Decisive for the terminology of anaerobic gut fungi was a flagellated organism
observed within the rumen of herbivores by Liebetanz (1910). This organism was
named Callimastix frontalis (Braune 1913) because of its high morphological
similarity to Callimastix cyclopis (order Blastocladiales) (Weissenberg 1912), a
flagellated parasite of Cyclops. Braune first described the multi-flagellated zoospores seen in Fig. 14.1, but did not recognise them as a stage of a fungal life cycle
and misclassified this organism as parasite. The given name C. frontalis led to a
number of mis-assignments of parasitic flagellates within this genus. Ultrastructural
examinations of C. frontalis by Vavra and Joyón (1966) resulted in the establishment of the new genus Neocallimastix. But unfortunately, the authors did not
recognise this organism as a fungus and still considered it as zooflagellate. Eight
years later, Whisler et al. (1974) assumed that organisms of the genus Neocallimastix are actually motile spores of an alternate life cycle of Coelomomyces
psorophorae – a blastocladialean fungus – and declared the herbivores as
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299
Fig. 14.1 First description of Callimastix as a flagellate parasite. Front view, side view, and
cleavage with aequitorial layer (Braune 1913)
alternative hosts along with mosquitoes. Orpin (1977) first suggested that these
anaerobic organisms living in the rumen actually might be fungi and his assumption
was based on the recognition of chitin in the cell walls and on the morphological
description of the thallus of different Neocallimastix species (Orpin 1974, 1975,
1976). Orpin’s findings were in contrast to the general belief of microbiologists
that no obligate anaerobic fungi can exist and therefore fungal colonies growing
in anoxic tubes were discarded as oxygen contaminations (van der Giezen
2002). However, none of these scientists provided a taxonomic definition for
Neocallimastix. It was Heath et al. (1983) who linked Neocallimastix to the
chytridiomycetes by setting up the new family Neocallimastigaceae within the
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order Spizellomycetales (phylum Chytridiomycota). The lack of multiple morphological characters has always been and still is a handicap for identifying these
organisms within the gut fungi.
14.3
Traditional and Current Systematics
Their incapability of locomotion and their appearance resulted in the erroneous
classification of fungi as plants before the twentieth century. An own kingdom
Fungi was recommended only in 1969 by Whittaker (1969). The Chytridiomycetes,
besides the Oomycetes and Hyphochytriomycetes, were the only group of flagellated
organisms that shared the class-characteristic cell-wall polymers (Bartnicki-Garcia
1970) and lysine synthetic pathway (Vogel 1964) of the Eumycota, comprising
Zygo-, Asco- and Basidiomycetes at that time. In the 1980s, taxonomy and phylogeny of Chytridiomycetes were based on the thallus development, discharge of
zoospores, the size, ultrastructural complexity, and organisation of zoospores, as
well as number and length of flagella. Furthermore, characteristics like mono- and
polycentric development as well as the release of zoospores via diffusion or via
papillae affected the taxonomy and phylogeny of these basal fungi (Barr 1978).
The anaerobic gut fungi, as a special group of the flagellated fungi, often
changed their taxonomic position within the Chytridiomycetes. Because of their
late discovery and the unusual physiological character, especially the obligate
anaerobiosis, the rumen fungi were placed into different taxonomic groups over
time, first into the subdivision Mastigomycotina (Ainsworth 1966), and later into
the division Mastigomycota (Alexopoulos and Mims 1979). Within the Mastigomycotina the following zoosporic fungi were accepted: Chytridiomycetes, Hyphochytridiomycetes, Plasmodiophoromycetes, and Oomycetes. The basis for this
classification built the zoospore with one or two flagellae as an asexual propagative
spore. The class Chytridiomycetes traditionally contained the four orders Chytridiales, Harpochytriales, Blastocladiales, and Monoblepharidales. Some studies
mentioned the order Harpochytriales, now known as a synonym of the group
Chytridiales (Kirk et al. 2008). Development of molecular genetic methods such
as polymerase chain reaction (PCR), cloning, and automated sequencing enabled to
generate data for diverse analyses. Traditional phylogeny based on the short-handed
phenotypic markers such as morphology, physiology, and biochemistry is now
complemented by statistically supported evolutionary analyses, which allowed
re-evaluation and re-classification of the whole kingdom Fungi including also the
young taxonomic group covering anaerobic fungi. Molecular-biological analysis of
gut fungi performed by Li et al. (1993) resulted in the establishment of an
own order, the Neocallimastigales, with only one family: Neocallimastigaceae.
Recently, Hibbett et al. (2007) postulated a separate phylum for this group, the
Neocallimastigomycota, adapted from the paraphyletic origin of the chytridiomycete fungi concluded by James et al. (2006). An informal supertree based on several
analyses showed a close relationship to the chytridiomycetes (Hibbett et al. 2007).
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Table 14.1 The systematics of the chytridiomycetes based on traditional and modern classification schemes
Traditional system
Modern system
domain Eukaryota
domain Eukaryota
kingdom Fungi (Linnaeus 1753) Nees 1817
kingdom Fungi (Linnaeus 1753) Nees 1817
phylum Chytridiomycota von Arx 1967
phylum Chytridiomycota von Arx 1967
class Chytridiomycetes (de Bary 1863)
class Chytridiomycetes (de Bary 1863) Sparrow
Sparrow 1958
1958
order Chytridiales Cohn 1879
order Chytridiales Cohn 1879
order Spizellomycetales Barr 1980
order Spizellomycetales Barr 1980
order Blastocladiales Fitzpatrick 1930
order Rhizophydiales Letcher 2006
order Monoblepharidales Sparrow 1942
order Neocallimastigales Li et al. 1993
class Monoblepharidomycetes Powell 2007
order Monoblepharidales Sparrow 1942
phylum Neocallimastigomycota Powell 2007
class Neocallimastigomycetes Powell 2007
order Neocallimastigales Li et al. 1993
phylum Blastocladiomycota James et al. 2006
class Blastocladiomycetes James et al. 2006
order Blastocladiales Fitzpatrick 1930
However, new phylogenetic approaches display the chytridiomycetes again as
monophyletic group (Ebersberger et al. 2010). Therefore, the separate phylum
Neocallimastigomycota seems to be redundant. A comparison of both classical
taxonomy, based on morphology and physiology, and modern systematic methods,
based on up-to-date molecular-genetic techniques, is shown in Table 14.1.
At present, the family Neocallimastigaceae comprises six genera1 (Adl et al.
2005): Anaeromyces (Breton et al. 1990), Caecomyces (Gold et al. 1988), Cyllamyces (Ozkose et al. 2001), Neocallimastix (Vavra and Joyon ex Heath 1983),
Orpinomyces (Barr et al. 1989), and Piromyces (Gold et al. 1988). An overview
of the six taxonomic groups within the family Neocallimastigaceae is shown in
Table 14.2.
14.4
Phylogeny
Traditional phylogenetic results supported by molecular-genetic data can redraw
evolutionary hypothesis and consequently the affinity of organisms to taxonomic
groups. Like phenotypic characterisations, molecular phylogenetics should never
be based just on one character. Comparisons or combinations of morphological and
genetic characters lead to stable and well supported evolutionary hypotheses and
with this strengths and weaknesses of genetic markers become obvious. A marker
of high diagnostic value has to be unique to a species or even to a strain and at the
1
http://indexfungorum.org/Names/familyrecord.asp?strRecordID=81063
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M. Eckart et al.
Table 14.2 Survey of the species from the anaerobic chytrids
Genus
Species
Author
Neocallimastix
frontalis
(RA Braune) Vavra and Joyón 1966 ex IB Heath et al.
(1983)
hurleyensis
Theodorou and Webb (1991)
joyonii
Breton, Gaillard, Bernalier, Bonnemoy and Fonty (1988)
patriciarum
Orpin and Munn (1986)
variabilis
Ho and Barr (1993)
Anaeromyces
elegans
Ho (1993)
mucronatus
Breton et al. (1990)
Caecomyces
communis
Gold et al. (1988)
equi
Gold (1988)
sympodialis
Chen, Tsai and Chien (2007)
Cyllamyces
aberensis
Ozkose et al. (2001)
Orpinomyces
bovis
Barr et al. (1989)
intercalaris
Ho et al. (1994)
(Breton, Bernalier, Bonnemoy, Fonty, Gaillard and Gouet)
joyonii1
Li, Heath and Cheng (1990))
Piromyces
citronii
Gaillard, Breton, Dusser and Julliand (1995)
communis
Gold, Heath, and Bauchop (1988)
dumbonicus
Li (1990)
mae
Li (1990)
minutus
Ho (1993)
polycephalus
Chen, Chien and Hseu (2002)
rhizinflatus
Breton, Dusser, Gaillard, Guillot, Millet and Prensier (1991)
spiralis
Ho (1993)
1
Basionym, current name: Neocallimastix joyonii Breton, Bernalier, Bonnemoy, Fonty, B. Gaillard
& Gouet 1989
same time ubiquitous for all taxa. The more various the set taxonomic groups is, the
more conserved the marker has to be. On the other hand, clustering on lower level,
starting with the family, requires more variable data to distinguish between species
or even strains (outlined in Fig. 14.2).
Clustering methods use differences between partitions of given data to rebuild
cladistic relationships. To get quality estimation such as bootstrap proportions (BTs
or BP), checking the robustness of a set of data (Felsenstein 1985) is required.
Highly conserved data lead to stable reconstructions in early branches caused
by low clade stability supports. An example is given in Fig. 14.2. There is no
possibility to distinguish between taxon2 and taxon3 based on identical sequence
data. This exemplary marker is not adequate for molecular diagnostics on a lower
taxonomic level such as genus or species. We demonstrate these problems with an
analysis based on real data in Fig. 14.3. The gene encoding actin is highly conserved in eukaryotes. The coding sequence divergence between plant and non-plant
actin genes shows only 15% or less variability (Hightower and Meagher 1986).
Therefore, this marker demonstrates perfectly the relationship between anaerobic
and aerobic chytridiomycetes, with the zygomycetous order Mucorales as outgroup
(Fig. 14.3). Varieties of species level cannot be determined with actin data, as this
marker lacks molecular diagnostics possibilities.
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303
Fig. 14.2 Schematic illustration of problems occurring during the application of single phylogenetic markers. The master sequence should be ATTGCTAAGCGA; the (recent) taxa show
modified sequences. Changes compared to the consensus sequences are colour-coded in red.
Occurring problems are obvious: a stable backbone with statistical support is only possible with
data that are not highly diverse. However, differentiation at higher branches requires variable
sequences. To combine these datasets, several approaches like supermatrix or supertree methods
can be applied
Nevertheless, highly variable data could result in an unstable reconstruction of
early branches caused by “long-branch-attraction” (Bergsten 2005). Although high
variable data could help measure distances between the closest neighbours and
other taxa on lower taxonomic levels, the variability of the data could lead to false
positive congruence, such as analogy instead of homology. An example is shown in
Fig. 14.4. The high variability of the internal transcribed spacer (ITS) sequences of
chytridiomycetes allow to distinguish even between strains, but alternative ways to
cluster these data decrease the robustness of the data set. One problem is the
differentiation of homologous and paralogous markers. Homology is not a problem
if orthologous genes are involved, but paralogous genes can lead to misinterpreted
results, similar to the comparison of “apples and oranges”. One example would be
the eukaryotic translation elongation factor 1-a (EF-1a) with more than one copy
within the genomes of fungi (see fungal genomes published by the JGI at http://
genome.jgi-psf.org/). False positive results in phylogenetic analysis based on alignments of paralogous genes are not always obvious as shown in Fig. 14.5.
14.5
Predicted Impact of Molecular Markers on Future
Identification and Phylogeny
Based on the theory of evolution, highly conserved genes of diverse taxonomic
groups could be amplified by the combination of PCR techniques and universal
oligonucleotides (primers). The most commonly used DNA region for moleculargenetic phylogeny is the highly repetitive cluster of the nuclear ribosomal DNA
(rDNA). The nucleotide sequences of the nuclear small (SSU) and large (LSU)
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M. Eckart et al.
Fig. 14.3 Phylogeny of the Neocallimastigomycota and other chytridiomycetes based on a Maximum Likelihood analysis of actin sequences from 24 taxa
with a total of 903 aligned characters (unpublished sequences). (methodical informations: GAMMA þ P-Invar model with RAxML 7.0.4 GTR-CAT (rapid
hill-climbing bootstrapping method (Stamatakis 2006, 2008)), 10,000 rapid bootstrap inferences before a thorough ML search; final ML Optimization
Likelihood: – 4676.139464)
14
Molecular Identification of Anaerobic Rumen Fungi
Fig. 14.4 Phylogeny of the Neocallimastigomycota and other chytridiomycetes based on a Maximum Likelihood analysis of ITS sequences from 49 taxa with
a total of 1,161 aligned characters (unpublished sequences). (methodical informations: GAMMA þ P-Invar model with RAxML 7.0.4 GTR-CAT,
(Stamatakis 2006, 2008), 10,000 rapid bootstrap inferences before a thorough ML search. Final ML Optimization Likelihood: – 17766.020153)
305
306
M. Eckart et al.
Fig. 14.5 Phylogeny of the Neocallimastigomycota and other chytridiomycetes based on a Maximum Likelihood analysis of tef sequences from 21 taxa with a
total of 1,377 aligned characters (unpublished sequences). Included paralogous copies disturb the correct species assignments. (methodical informations:
GAMMA þ P-Invar model with RAxML 7.0.4 GTR-CAT (Stamatakis 2006, 2008), 10,000 rapid bootstrap inferences before a thorough ML search. Final ML
Optimization Likelihood: – 5723.672908)
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307
subunits are separated by the non-coding DNA sequences of the internal transcribed
spacer (ITS) 1 and 2 and the non-transcribed intergenic spacer (IGS). Lacking a
sufficient evolutionary pressure, the non-coding regions allow the separation of
organisms down to the levels of species and strains. Using the flanking conserved
sequences of 18S (SSU) and 28S (LSU) rDNA, these regions can easily be
amplified with universal primers. Unfortunately, the ITS regions are not single
copy regions. Although the ribosomal DNA cluster follows concerted evolution
(Arnheim 1983), the intra-specific variability among organisms cannot be denied.
Usage of this region as molecular barcode marker is therefore questionable, especially if there is no reliable and supporting approach for species identification based
on e.g. morphology (Nilsson et al. 2008). Moreover, the variability of the ITS
region is sometimes not high enough to separate at the level of species as shown
for the fungal genus Penicillium (Skouboe et al. 1996, 1999). This experience
enforced the search and establishment of alternative genetic markers like the introncontaining protein coding genes actin (act), eukaryotic translation elongation factor
1-a (tef), or beta-tubulin (btub). A profound base for this approach requires reference
strains, which need to be morphologically and genetically well characterised, and also
the subsequent completion of the published results and sequence submissions.
First efforts to identify the anaerobic gut fungi by molecular genetic methods
were done by Doré and Stahl (1991) and Bowman et al. (1992). Their approaches
relied on partial 18S rDNA sequences for including the anaerobic fungi into the
chytridiomycetes, but the authors did not separate the species within the genera
(Doré and Stahl 1991; Bowman et al. 1992).
Trying to clarify the phylogenetic relationships within the order Neocallimastigales using sequence analysis (ITS1) combined with morphological features,
ultrastructures and mitotic characters have led to seperation of the order Neocallimastigales (Li et al. 1993). Isozyme analyses or DNA hybridisation has also been
used with the aim to clarify identification of anaerobic gut fungi and to increase the
level of specificity (Ho et al. 1994).
A fast and easy method for the differentiation of polycentric anaerobic fungi is
available by (RFLP) analysis of ITS spacer and/or fragments of ribosomal large
subunit (28S rDNA) digested by proper endonucleases. However, the ribosomal
small subunit (18S rDNA) turned out to be too conservative to get a well resolved
DNA polymorphism, and therefor is not very suitable for this type of analysis
(Fliegerová et al. 2006).
Methods of molecular biology are very promising, but “old-fashioned” taxonomy is still substantiated despite many discrepancies. The classical approach of
Neocallimastigales identification is based on their morphological characters. Thallus shape (filamentous or bulbous), zoosporangial development (monocentric or
polycentric), and number of flagella per zoospore (uni- or polyflagellated) are
decisive for genus differentiations, while the ultrastructure of the zoospore is
determinative for species. (Heath et al. 1983; Orpin and Munn 1986; Munn et al.
1988; Webb and Theodorou 1991). Unfortunately, characters observable by light
microscopy vary with culture conditions and are highly pleomorphic (Brookman
et al. 2000). Moreover, the cultures often fail to produce important structures
308
M. Eckart et al.
(sporangia and zoospores) making identification even more problematic. Also the
differentiation of species using ultrastructural features of the zoospores is questionable, because ultrastructure depends not only on the age of microorganisms but also
on the method and quality of their preparation (Ho and Barr 1995).
14.6
Molecular Identification and DNA Barcoding
One of the important characteristics of anaerobic fungi is their flagellated stage in life
cycle. However, flagellated zoospores, can be found also in other aquatic fungi, like
the Blastocladiomycota and the Chytridiomycota sensu stricto and also in some
protists, e.g., the stramenopiles and among those the oomycetes, which are derived
brown algae. The flagellae of these organisms caused the mis-applications of taxonomic and phylogenetic assignments as it happened to Braune with Neocallimastix
(1913). The elucidation of morphological characters is valuable and indispensable,
but has to be supported by techniques of molecular genetics because the pleomorphic
shape of fungi leads to complications in their identification. Therefore, molecular
information becomes more and more important as a primary source for species
recognition. Now, 90 years after the discovery of the anaerobic rumen fungi, molecular phylogenetic studies confirmed their relationship to the kingdom Fungi (Förster
et al. 1990; Bowman et al. 1992). The choice of molecular genetic markers in the
kingdom Fungi, respectively the phylum Chytridiomycota, is clearly arranged.
Today, state of the art comprises seven markers for fungal phylogeny that provides
data over the complete spectrum of the kingdom: 18S rDNA, 28S rDNA, ITS1 and
ITS2 including the 5.8S rDNA, rpb1, rpb2, tef, and beta-tubulin. In special cases
like pathogenic species or organisms of industrial importance, some additional
markers exhibiting a higher specificity were developed. Such markers encompass
not only genes encoding calmodulin, Mcm7 (MS456), and Tsr1 (MS277) (Aguileta
et al. 2008; Schmitt et al. 2009) but also physiological properties such as toxins or
extrolite profiles, which are well established, for example, the ascomycetous genus
Penicillium (Samson and Frisvad 2004).
To find the most useful marker for “tagging” all forms of life is the aim of many
current projects involved in “DNA barcoding”. DNA barcoding is an approach to
identify any organism based on sequence analysis of selected genomic regions.
Access to these regions should be as universal as possible, comparable, reproducible, and relatively easy to accomplish. Barcoding is thought to serve not only the
identification or verification of known specimens but also to contribute in the
discovery of new, undescribed species. Although DNA barcoding already proved
to be a very useful tool for the discovery of cryptic species, which are by definition
not differentiable by morphological features (Hebert et al. 2004), barcoding is
nevertheless error-prone. Depending on the method used, DNA barcoding turned
out to be not always sufficient for species recognition (Brower 2006; DeSalle
et al. 2005; Whitworth et al. 2007). One of the major problems in all barcoding
14
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309
a
b
Phylum
Ascomycota
Basidiomycota
environmental samples
Glomeromycota
Microsporidia
unclassified fungi
Fungi incertae sedis
Zoopagomycotina
Entomophthoromycotina
Kickxellomycotina
Mucoromycotina
unkown
Chytridiomycota
Neocallimastigomycota
Blastocladiomycota
CoS
1,124,132
197,974
41,955
11,698
5,676
5,107
5,092
32
439
276
3,948
397
1,683
465
134
Fig. 14.6 Schematic illustration and number of nucleotide sequences provided by the International Nucleotide Sequence Database Collaboration. (e.g., Genbank). (a) Percentages of the
number of fungal sequences provided in GenBank. The graph shows the total number of submitted
sequences within the kingdom Fungi. The subparts describe the single phyla based on the
taxonomy provided by the TaxBrowser at NCBI. The group Dikarya is represented by approximately 96% of all available sequences. The number of sequences that were generated of environmental samples is higher than that of all other phyla with the exception of the Dikarya. The
Neocallimastigomycota represent with 465 sequences the second smallest group of fungal organisms represented as nucleotide sequences within GenBank. (b) Survey of the nucleotide sequences
provided by the International Nucleotide Sequence Database Collaboration (as of May 1st, 2009)
approaches is still the question which molecular tool should be used, since every
further step in species identification is based on it.
In animal systems, the mitochondrial cox1 is widely applied (Hebert et al. 2003),
although its sufficiency is already questioned (Goetze 2003). With a slower evolutionary rate of this cytochrome c oxidase, this marker is not applicable for flowering
plants (Kress et al. 2005).
One of the most discussed marker in fungal taxonomy and phylogenetics is still
the ITS region with all its afore mentioned advantages and disadvantages (see Sect. 5).
310
M. Eckart et al.
Nevertheless, provided sequence data usable for species identification for anaerobic
gut fungi are restricted, e.g., only 163 “ITS” tagged sequences are assigned to the
order Neocallimastigales (465 nucleotide sequences in summary, compare Fig. 14.6),
with only 17 sequences assigned to full taxon names. Because of missing mitochondria in anaerobic fungi (hydrogenosomes instead), mitochondrial based barcode
markers are out of question (Bullerwell and Lang 2005). The need for a complete barcoding database, as always demanded (Ekrem 2007), is obvious. But another major
drawback is the data deposited in such a barcode database. An adequate number
of well-defined reference specimens are a prerequisite for species identification
and especially for species discovery. Such references should encompass all possible variances within defined species boundaries, e.g., geographically based variations (DeSalle et al. 2005; Meyer and Paulay 2005).
Originally thought to be a fast, cheap, and easy-to-access method for the
assignment of “unknown” to “known” specimens, molecular barcoding should be
used with caution. On the one hand, supplementing a barcode marker with additional information about e.g., morphology, biogeography, or even more molecular
data will miss the aim of a single easy-to-use marker for species assignment. But on
the other hand, supplementing data is necessary as a specimen cannot be identified
or described with certainty by one molecular attribute (Brower 2006; Will et al.
2005). Storing new data in a database is always tied with responsibility of the
submitter. Open-access to such databases is necessary but at the same time prone to
errors and losing its value as shown by GenBank at the NCBI (Bridge et al. 2003).
14.7
Conclusion and Future Line of Research
According to the efforts of Aguileta et al. (2008) and Schmitt et al. (2009) more
alterantive barcoding markers need to be established and validated in order to get a
reliable identification which is in concordance with morphological and ultrastructural
characters. The increase of the complexity of research on anaerobic rumen fungi in
their composite ecosystems requires a common platform for strain and data shared
among the scientific community. It is necessary to gain a certain homogeneity and
common use of reference and type strains including reference sequences of barcode
markers and other characters suitable for a reliable identification of anaerobic rumen
fungi. This is a fundamental for cultivation-independent detection in the natural
ecosystems and habitats of anaerobic fungi as performed by Fliegerová et al. (2010).
Acknowledgments The authors express their gratitude to L. Jay Yanke (Agriculture and AgriFood Canada, Lethbridge Research Centre, Lethbridge, AB, Canada) for providing Neocallimastix
frontalis strain SR4. This project was a component of the institutional research plan (AV OZ 5045
0515) of the Institute of Animal Physiology and Genetics, Academy of Sciences of the Czech
Republic in Prague. The czech team was supported by The National Agency for Agriculture
Research (project no. QI92A286/2008), The german team was supported by the Deutsche Forschungsgemeinschaft (project no. Vo 772/7-1), which is part of a bilateral grant between the Czech
Science Foundation and the Deutsche Forschungsgemeinschaft.
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Part II
Human Pathological and Clinical Aspects
Chapter 15
New Approaches in Fungal DNA Preparation
from Whole Blood and Subsequent Pathogen
Detection Via Multiplex PCR
Roland P.H. Schmitz, Raimund Eck, and Marc Lehmann
Abstract Sepsis is a life-threatening disease that results from excessive host
responses to microbial infections. Fungal pathogens mainly contribute to lethal
outcomes and high treatment budgets. Numerous trials revealed that the mortality
rates of septic patients could be reduced if appropriate anti-infective approaches are
promptly initiated. This demands a forthwith identification of the causative pathogen(s) and antibiotic resistances. However, standard procedures (e.g., blood cultures) deliver first results after 2–3 days. Facing the time-to-result for cultural
pathogen detection, culture independent nucleic acid amplification techniques
(NAT) are increasingly desirable to deliver a reliable basis for a targeted antibiotic
regimen within the first decisive hours of the disease.
Crucial steps in the detection of pathogens within whole blood concern cell lysis
and the disproportion of pathogen and human background DNA Standard analytical
methods applied and current developments in sepsis diagnostics are reviewed. New
tools are introduced which accelerate the clinical investigation course and improve
the sensitivity as well as the quality of NAT-based genus and species detections.
15.1
Introduction: Fungi as Sepsis Causative Pathogens
Life-threatening fungal and bacterial infections and their outcomes – sepsis and
consecutive organ failure – are frequent complications of hospitalized patients, with
an increasing number of 18 million new sepsis cases each year worldwide and with
a mortality rate of 30–50% (Slade et al. 2003). Sepsis results from the hosts
response to fungal and bacterial (and protozoan) infections, whereas a malfunction
of the defence and repair system is responsible for the development of organ
dysfunctions and at last multiorgan failure.
R.P.H. Schmitz, R. Eck, and M. Lehmann
SIRS-Lab GmbH, Winzerlaer Str. 2, 07745 Jena, Germany
e-mail: schmitz@sirs-lab.com
Y. Gherbawy and K. Voigt (eds.), Molecular Identification of Fungi,
DOI 10.1007/978-3-642-05042-8_15, # Springer-Verlag Berlin Heidelberg 2010
317
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In Germany, about 60,000 out of 1,54,000 patients die from severe sepsis, which
therefore is one of the most frequent causes of death in intensive care units (ICU).
The incidence of sepsis has risen due to the use of invasive devices, aging of the
population, and the higher incidence of immunosuppressive conditions such as
chemotherapy for cancer and acquired immunodeficiency syndrome (AIDS) (Martin et al. 2003). About 30% of the intensive medicine budget is expended for the
treatment of those patients (Reinhart et al. 2006). On average, the treatment of
candidaemia amounts to about US $44,536 for each patient, mainly attributed to
prolonged hospitalization (Pfaller et al. 2005), whereas treatment of sepsis costs
only US $22,000 per patient in the USA (US $16.7 billion spent each year for sepsis
care; Angus and Wax 2001), which marks the discrepancies in care expenses of
septical infections caused by fungal and bacterial pathogens.
From the 1970s to 1990s, septical infections in Germany were attributed mainly
to Gram-negative bacterial species, whereas currently Gram-positives, fungi, and
multi-infections are rising (Bauer et al. 2006; Karlowsky et al. 2004; Martin et al.
2003). The incidence of fungal species in septical infections was determined to be
mainly contributed by Candida spp. (Fig. 15.1), especially C. albicans, with prominent findings in several clinical studies: compared to bacterial sepsis causative
pathogens, the incidence of fungal species was quite significant with Candida spp.
Fig. 15.1 Frequencies of
fungal sepsis causative
pathogens as determined in 11
clinical studies. Individual
species were designated only
in a part of the studies, which
accounts for their percentage
distribution as individual
species or fungi/Candida sp.
The boxplot data were
calculated using R (R
Development Core Team,
2007). The data were taken
from: Bodmann and Vogel
(2001); Cockerill et al.
(1997); Focht and Adam
(2004); Fridkin and Gaynes
(1999); Geerdes et al. (1992);
Geffers et al. (2004); Jones
et al. (2004); Karlowsky et al.
(2004); Kübler et al. (2004);
Styers et al. (2006); Vincent
et al. (2006); R: A language
and environment for
statistical computing. R
Foundation for Statistical
Computing (2007) Vienna,
Austria, ISBN 3-900051-07-0
15
New Approaches in Fungal DNA Preparation from Whole Blood
319
10%, Aspergillus spp. 5–15%, and Fusarium spp. < 2% (Richardson and Kokki
1999; Vincent et al. 1998; Duthie and Denning 1995; Gamis et al. 1991).
Candida albicans was then identified to be the fifth and seventh frequent
causative pathogen of nosocomial infections in Germany and the USA, respectively
(Geffers et al. 2004; Fridkin and Gaynes 1999), while candidaemia in general
accounts for the fourth frequent nosocomial infection affecting the blood circuit
(Liu et al. 2006; Gudlaugsson et al. 2003; Pappas et al. 2003). The spectrum of
nosocomial fungal pathogens in particular comprises mainly yeasts – first of all
C. albicans (>50%), followed by non-C. albicans Candida spp. (~45%, e.g.,
C. glabrata, C. krusei, C. parapsilosis, C. tropicalis) as well as molds (2–5%,
e.g., Aspergillus spp.). The lethality of nosocomial C. albicans infections was
quoted to be 22–40% (Gudlaugsson et al. 2003; Nolla-Salas et al. 1997; Fraser
et al. 1992; Wey et al. 1988).
The incidence of sepsis and the number of sepsis-related deaths were increasing
in the USA, although the overall mortality rate among patients with sepsis was
declining: the rate of sepsis due to fungal organisms increased by 207% between
1979 and 2000 (with Gram-positive bacteria becoming the predominant pathogens
after 1987) (Martin and Mannino 2003). Candidaemia occurrence was proven to be
associated with an extraordinary high mortality rate among critically ill patients: in
fungal infections the patients mortality was >60% (85% and 45.2% in medical and
surgical patients, respectively) (Charles et al. 2003). Causing identical clinical
syndromes in severe sepsis/septic shock, the mortality of patients with bacterial
infections was only determined to be 30–50%. About 70% of all fungal infections
were diagnosed post mortem (Schmidt et al. 1991).
15.2
Sepsis Diagnostics: An Overview of Current Methods
Given the high mortality rates from patients suffering from candidaemia, there is an
obvious need for more accurate and rapid identification strategies. Early detection
of systemic fungal infection and prompt and adequate antibiosis in the first few
hours of infection are the crucial steps for an effective sepsis therapy (GarnachoMontero et al. 2003; Fine et al. 2002; Ibrahim et al. 2000). Epidemiological data
confirm that a doubling of mortality is the consequence of inadequate therapies
(Vallés et al. 2003) (Fig. 15.2) and an increase of mortality of more than ~7% per
hour is proven in cases of delayed adequate (directed) antibiotic treatment in case of
sepsis, irrespective of the causative pathogen (Iregui et al. 2002). Unsurprisingly, an
increase of mortality has also been proven for delayed empirical (nondirected)
therapies in cases of systemic candidiasis (Morrell et al. 2005).
Diagnosis of invasive fungal infections (IFI) is generally based on direct
pathogen detection in body fluids and in aseptically withdrawn samples of the
skin, lung, liver, and CNS biopsy, respectively, via growth cultures. A histological
proof within inflamed tissue is also accepted (Ascioglu et al. 2002). However,
the conventional identification of pathogenic fungi in clinical microbiology
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R.P.H. Schmitz et al.
Fig. 15.2 Reduction of mortality by adequate antibiotic therapy
laboratories bases on phenotypic features and physiological tests and remains a
significant problem in general. The clinical symptoms are difficult to interpret and
the findings of noninvasive methods (e.g., computed tomographic scanning and
X-ray) are not specific (Richardson and Kokki 1999). Deep-tissue sample cultures
from infections with focal lesions are frequently negative (Vincent et al. 1998;
Duthie and Denning 1995). Direct microscopy and histopathological examination
are rapid, but they do not always allow identification of the infecting agent to the
species level (Richardson and Kokki 1999; Vincent et al. 1998).
Even though monoclonal antibody-based enzyme-linked immunosorbent assays
(ELISAs) for circulating Aspergillus and Candida antigens (e.g., Cand-Tec1 latex
agglutination assay, Ramco Laboratories, Houston, Texas) are somewhat specific,
they lack sensitivity (Richardson and Kokki 1999). Furthermore, the detection of
Candida sp. antibodies may also be attributed to a mucocutanous infection and is no
proof for an invasion, and antibody production may fail to appear in case of
immunocompromised patients.
b-D-glucan, a component of the fungal cell wall, has become a diagnostic
parameter for IFIs (Alam et al. 2007; Odabasi et al. 2004). The available assays
use saccharide-specific antibodies or limulus amebocyte lysates (LAL) of the
horseshoe crab, which is used for years for endotoxin detection to measure the
non-Candida-specific 1,3-b-D-glucan level. The concentration of 1,3-b-D-glucan in
plasma of patients with IFI was markedly increased. However, the LAL-based
assays from Japan (e.g., Fungitec-G1; Lü et al. 2007) or USA (e.g., Glucatell1),
are still not validated for the sole diagnosis of IFIs. They cannot be applied to
differentiate aspergillosis from yeast fungus infection, are soonest to be used 3 days
postoperatively, and deliver different assay-specific results.
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D-arabinitol, a further putative target metabolite and exclusive fungal metabolic
product is not produced by C. glabrata and C. krusei and is therefore of restricted
diagnostic relevance for fungi in general (Walsh et al. 1995). Fungal serum mannan
acts as an early antigen marker for candidaemia (Fujita et al. 2006). The Platelia1
Candida Antigen EIA (Bio-Rad; sensitivity 42%, specificity 98%) may be tested
negative in patients with anti-mannan antibodies. Therefore, determination of the
anti-mannan antibody concentration is recommended. The sensitivity of the combined assay increases to 76%, the specificity to 93% (Sendid et al. 2003). Fungal
serum mannan and at least fungal enolase tests (Yeo and Wong 2002) might at least
be promising for the early detection of invasive candidiasis, but show short serum
half-times and the latter affords complex measurement techniques.
In general, antibodies directed against fungal targets are of epidemiological
value but antigenic extracts are not yet standardized. The proteins are first seen in
a late stadium within the course of the disease and are in general of limited use in
immunosuppressed patients. Serological test may in general contribute to IFI
diagnostics but have to be assessed by further cultural and clinical data or combined
even with current molecular diagnostics (Yeo and Wong 2002).
While clinical manifestations of inflammations are elusive, some biochemical
parameters indicate early stages of fungal or bacterial infections. The presence of
three biomarkers was proven in systemic infections: C-reactive protein (CRP),
procalcitonin (PCT), and D-dimer. None of them, however, functions as single
independent criterion for sepsis (De La Rosa et al. 2008).
CRP, an acute-phase protein that plays a significant role within the complement
pathway, binds to several polysaccharides present in all classes of sepsis causative
pathogens. Secretion of CRP starts within several hours of the stimulus peaking
between 36 and 50 h. After disappearance of the stimulus, CRP falls rapidly with a
half-life of 19 h, but it can remain elevated, even for very long periods, if the
underlying cause of the elevation persists. Only interventions affecting the inflammatory process responsible for the acute phase reaction can change the CRP level.
Changes may be very helpful in diagnosis as well as in monitoring response to
therapy, as CRP levels are only determined by the rate of synthesis (Povoa 2002).
PCT is a 116-amino acid prohormone proven to be a useful marker in sepsis and
sepsis-like conditions (e.g., severe burns and mechanical trauma), and also in some
infections of nonbacterial causation as systemic fungal infection (Becker et al.
2004). Serum levels of PCT are frequently increased in sepsis patients, sometimes
attaining levels several thousand-fold normal, and these high levels often persist for
a long period of time. Moreover, the levels often correlate positively with the
severity of the condition and mortality (Pettila et al. 2002; Meisner et al. 1999).
A good correlation was found between the serum PCT level and the Sepsis-Related
Organ Failure Assessment (SOFA) score, although no correlation was found
between the latter and the CRP level (Endo et al. 2008). It has been argued that
the PCT serum level may be useful in aiding the diagnosis of sepsis and the
discrimination between the specific phases of the disease.
Activation of the coagulation cascade is a common and early phenomenon in the
development of sepsis, and this fact supports the use of anticoagulant treatments
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as potentially useful interventions (Levi and Ten Cate 1999). Anticoagulation
releases degradation products containing D-dimers whereas a finding of more than
500 ng of D-dimer per milliliter is considered abnormal, and such levels are present
in virtually all patients with sepsis (Opal and Esmon 2003).
However, none of these potential biochemical test parameters which gain information on the status of inflammation and altered along with the development of
sepsis, especially parameters regarding the host-response on invasive infections,
pathogen cell components, or at least metabolic by-products, do permit access to a
directed therapy of the disease. This exclusively demands the identification of the
causative agent and putative antibiotic resistances which it exhibits.
Various commercial cultural systems that are able to identify sepsis causative
pathogens within 4–72 h have been developed. Although correct identification of
clinically relevant yeast strains can be achieved with these systems, incomplete or
incorrect identifications may occur when certain new and emerging yeast strains
are tested (Espinel-Ingroff et al. 1998). The gold standard technique blood culture,
which is the routine method in clinical microbiology laboratories to demonstrate
the presence of pathogens in patients suspected of systemic infections, exhibits
some drawbacks due to the patient’s antibiotic treatment prior to sample withdrawal, a low abundance of causative agents in the blood samples, and frequently
noncultivable organisms. The blood culture remains negative in 80–90% of all
sepsis incidents and takes a period of usually 24–72 h to obtain results, whereas a
sample can be reliably declared negative within up to 7 days. The culture-based
phenotypic identification of Candida species from clinical materials, for example,
requires at least another day to obtain pure cultures. The results then become the
basis for further microbial diagnostics, e.g., species differentiation, biochemical
typing, and/or generation of antifungal or antibacterial susceptibility profiles,
which are also laborious and time-consuming although the methods are in part
automated.
15.3
Fate of Antimycosis
The time-to-result of blood cultures is too long to initiate an effective sepsis
therapy. Therefore, broad spectrum antibiotics are given simultaneously or prior
to blood withdrawal without trusted microbiological findings which enhances the
broadening of multi-resistant organisms and downsizes the efforts of later
taken blood cultures (Chastre 2008; de Kraker and van de Sande-Bruinsma 2007;
Weinstein 2003). Therapy is usually administered indirectly early in the clinical
course of blood stream infections (BSI) and prior to reporting of positive blood
culture results. With respect to antimicrobial management, the most important
information provided by the clinical microbiology laboratory appeared to be the
reporting of positive blood culture and Gram stain results. Antimicrobial susceptibility testing data did not appear to have a comparatively important impact on
antimicrobial management among patients with BSI (Munson et al. 2003).
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In general, considerable adverse effects have to be faced when antimycotics are
given (e.g., Amphotericin B). Crucial factors for the prognosis of patients with
systemic mycoses therefore are again start and accuracy of the antimycotic. Additionally, several human fungal pathogens are characterized by high rates of intrinsic
resistance. Therefore, identification of fungal pathogens to the species level rather
than antifungal drug susceptibility testing is presently the most important step in
selection of adequate antifungal agents (Rex and Pfaller 2002). As expected, IFIs
have become an important cause of morbidity and mortality among immunocompromised patients, many of whom are undergoing long-term treatment with antifungal agents.
Although there is little evidence of emerging resistance in e.g., Candida albicans
(Pfaller et al. 2005), long-term treatment may lead to an increase of non-C. albicans
strains (Marr 2004), Aspergillus terreus, and Zygomycetes infections (Wingard
2005; Kauffman 2004). Some Candida species are problematic in this respect
notwithstanding: C. glabrata, C. rugosa, and C. guilliermondi display low susceptibilities to fluconazole, an otherwise effective, inexpensive broad spectrum antibiotic with excellent penetration and oral absorption properties (this resistance may
also come along with voriconazol resistance), and C. krusei, which is innately
resistant like Aspergillus spp. and other molds (Pfaller et al. 2005; Pappas et al.
2003).
In general, candidiasis and aspergillosis are the most common IFIs in patients
receiving immunosuppressive treatment, e.g., chemotherapy for cancer or organ
transplantation, or in immunodeficient patients, such as patients with AIDS (Ellis
et al. 2001; Dasbach et al. 2000; Coleman et al. 1998; Barnes et al. 1996), and in
addition to the increasing incidence of IFIs, the number of fungal species which
must be considered as potential fungal pathogens has also increased during the last
few decades.
15.4
Pathogen Detection by Nucleic Acids Amplification
Techniques (NAT)
Nucleic acid amplification techniques (NAT, e.g., polymerase chain reaction, PCR)
allow a more rapid target and resistance detection within several hours, even from
whole blood, compared to culture-based methods. Free fungal and bacterial DNAs, as
well as DNA from adherent, phagocytosed, and free intact and nonintact pathogens,
are detected while blood cultures contribute only in the presence of viable and
metabolic active cells. However, the high sensitivity is decreased by factors such as
high fractions of salts, hemin, and other blood ingredients, most of which can be
effectively removed by affinity chromatography steps during sample preparation.
Foremost human bulk DNA, co-isolated with microbial pathogen nucleic acids from
the addressed sample material (e.g., whole blood), is additionally the cause for a
minute pathogen to human DNA ratio, increased cross-reactivities with primers, and
significantly reduced overall analytical assay sensitivities (Handschur et al. 2009).
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In recent years, numerous nucleic acid-based methods have been developed to
improve the diagnosis of mycotic infections and the identification of pathogenic
fungi (Mikami 2008; Gottfredsson et al. 1998; Reiss et al. 1998; Walsh and
Chanock 1998). Prompt and accurate detection and identification of yeast species
are important due to the fact that the virulence of Candida isolates for example
differs according to the species level, with C. albicans being most virulent, followed
by C. tropicalis (Wingard 1995). Therefore, protocols have been published for the
detection and identification of mainly yeast pathogens, including species or group
discrimination with specific (Yong et al. 2008; Flahaut et al. 1998; Kobayashi et al.
1999; Skladny et al. 1999; Mannarelli and Kurtzman 1998; Reichard et al. 1997) or
panfungal (broad-range) PCR primers (Inácio et al. 2008; van Burik et al. 1998).
Probes and restriction fragment length polymorphisms have been described in a
number of studies to identify unique ribosomal DNA (rDNA) sequences (Evertsson
et al. 2000; Kauffman et al. 2000; Loeffler et al. 2000; Martin et al. 2000; Turin et al.
2000; Turenne et al. 1999; Velegraki et al. 1999; Kappe et al. 1998) and as a matter
of fact, primers were directed against targets within the rDNA in several approaches
(Evertsson et al. 2000; Wahyuningsih et al. 2000; Elie et al. 1998).
The identification of PCR products was done by gel or capillary electrophoresis
(De Baere et al. 2002; Chen et al. 2000; Turenne et al. 1999), PCR amplicon
restriction fragment length polymorphism analysis (Fujita and Hashimoto 2000),
single-strand conformational polymorphism (Li and Bai 2007), Southern blot
hybridization (microarray) assays with oligonucleotide probes (Spiess et al. 2007;
Wiesinger-Mayr et al. 2007; Hebart et al. 2000; Shin et al. 1999; Flahaut et al.
1998; Einsele et al. 1997), and random amplification of polymorphic DNA analysis
(Stefan et al. 1997). Furthermore, a number of PCR-enzyme immunoassays (EIAs)
has been developed (Badiee et al. 2007; Wellinghausen et al. 2004; Lindsley et al.
2001; Elie et al. 1998; Loeffler et al. 1998; Shin et al. 1997; Fujita et al. 1995).
One study showed the applicability of PCR-EIA for the resolution of discrepancies in phenotype-based identification between different institutions (Coignard et al.
2004). Real-time PCR assays have been described for the quantitative detection of
either Candida or Aspergillus species in serum (Challier et al. 2004; White et al.
2003; Costa et al. 2001) or other specimen types (White et al. 2004) and Diaz and
Fell (2004) applied the Luminex technology for the detection of pathogenic yeasts
of the genus Trichosporon. The latter assay combines flow cytometry and nucleotide hybridization via fluorescent beads covalently bound to species-specific capture
probes. Upon hybridization, the beads bearing the target amplicons are classified
by their spectral addresses with a 635-nm laser. Quantitation of the hybridized
biotinylated amplicon is based on fluorescence detection with a 532-nm laser.
Although most of these published PCR-based methods have been useful for the
identification of fungal species, they either identify only one species at a time or
require a probe hybridization procedure that incurs time and expense. An economically more efficient approach would be the application of protocols capable
of identifying broad panels of relevant species in a highly parallel fashion (PalkaSantini et al. 2009; Louie et al. 2008). Additionally, the protocols exclude an
optimized procedure for the lysis of fungal cells within the sample material, e.g.,
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325
whole blood or serum, which is a crucial step in nucleic acid detection, and mostly
relies on in-house techniques for cell disruption. Beyond any attempts for standardization, the extraction methods for pathogen DNA, i.e., the combination of cell
lysis and DNA isolation protocols, produce markedly differing yields of fungal (and
bacterial) DNA and thus can significantly affect the results of NAT methods for the
respective species (Metwally et al. 2008; Fredricks et al. 2005).
Anyway, mechanical impact has been regarded as the most efficient lysis
method for fungal cells (Wong et al. 2007; Müller et al. 1998). Further studies
described enzymatic/thermal lysis protocols as superior to mechanical impact
(Lugert et al. 2006), but the experience should be argued to be mainly attributed
to the mechanical device used and its effective power, lysis matrix, sample to headspace volume ratio within the lysis tubes, and the protocol (device settings) applied.
It has to be considered that the lastly cited studies on cell lysis were done with pure
fungal cells devoid of human cell material, which significantly affects the lysis of
the target cells, but the results of Fredricks et al. (2005), which likewise support
mechanical lysis, were obtained from spiked clinical samples, a technique which
should basically be recommended for assay development.
However, the mechanical devices of the last generation (e.g., FastPrep1-24, MP
Biomedicals, Solon, OH, USA), which disrupt cells in periods of several seconds to
few minutes while executing figure-8 vertical, angular motions, seem to guarantee
for the first time acceptable efficiencies for standardized disruptions of designated
rigid pathogen cells within high-volume (i.e., 2 mL) clinical samples. The cells
are ground mostly between glass or ceramic bead sand mixtures of particle sizes
between 0.1 and 2.5 mm in diameter. Higher head-space volumes over the sample/
bead-matrix suspension support the lysis efficiency, an effect which is obviously
noticed in tubes of 15 mL total volume (suspension to head-space volume 2:1).
Although mechanical lysis is described as an inexpensive technique, the rotating
equipment which ensures sufficient efficiency, has to be regarded as initially quite
cost-intensive. Additionally, a DNA extraction method is indispensable for a PCRbased assay and both manual and automated protocols are forthcoming (Loeffler
et al. 2002) – the latter often high priced.
A recently launched diagnostic PCR-linked tool bases on a selective lysis of
(human) blood cells by chaotropic buffers and quantitative degradation of human
nucleic acids via chaotroph-resistant DNase (Horz et al. 2008). The enzyme is
subsequently heat-inactivated and bacterial pathogen cells are lyzed in a second
step to gain their genomic DNA for NAT detection purposes. It has to be questioned
if this initially smartly appearing two-step lysis procedure is actually a drawback of
the analytical approach, since sublethally affected pathogen cells (e.g., due to
antibiotic treatment or impact of the immune system) and Gram-negative thin-walled
cells may be disrupted within the first lysis step and lose their genomic (target)
DNA (Horz et al. 2008). However, the tool may preferably be suited for rigid cell
types, but its applicability for the detection of yeast cells, which has been declared
to be covered with the assay panel, has not yet been proven in clinical studies.
A new multiplex PCR-based assay (VYOO1, SIRS-Lab GmbH, Jena) was
launched recently and compensates the above mentioned drawbacks by combining
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an efficient bead-based mechanical lysis protocol with an extended multiplex PCR
detection step (Sachse et al. 2009; Horz et al. 2008). The launched assay includes a
unique pretreatment tool which specifically concentrates fungal and bacterial DNA by
affinity chromatography and removes human background DNA, the cause for a
minute fungal plus bacterial to human DNA ratio within the addressed sample
material (e.g., EDTA whole blood). A truncated DNA-binding protein recognizes
unmethylated XpYpCpGpXpY motifs within the DNA which are significantly less
frequent in humans than in yeast (and bacterial) DNA (Pinarbasi et al. 1996; Wilkinson et al. 1995). An earlier study described different methylation grades between the
mycelia and yeast forms of C. albicans and outlined an overall lower methylation of
fungal DNA compared to DNA from higher eukaryotes (Russell et al. 1987).
However, the enrichment of pathogen DNA significantly increases the sensitivity
of the chosen downstream detection method by at least one order of magnitude
(Sachse et al. 2009). The standard (as compared to real-time PCR/qPCR assays)
multiplex PCR detects an optimized panel of six fungal (A. fumigatus, C. albicans,
C. glabrata, C. krusei, C. parapsilosis, and C. tropicalis) (and 34 bacterial) species
that cause life-threatening infections and comprise 99% of sepsis-causative pathogens (as confirmed by the frequencies of pathogens via meta-analysis of 11 clinical
studies, see above legend to Fig. 15.1), as well as a set of important antibiotic
resistances (e.g., methicillin, vancomycin, b-lactamase). The test has been designed
for the examination of the generated amplicons by gel-electrophoresis or hybridization methodologies. The latter is demanded for increased sensitivities and result
verification. However, using amplicon-specific DNA length markers, the amplicon
identification works straightforward and allows for results within 8 h – an important
benefit in sepsis diagnostics compared to assays which rely on preculturing of viable
cells (i.e., blood culture) (Lau et al. 2008) (Fig. 15.3).
The crucial step in pathogen detection from whole blood is the low abundance of
pathogen cells within the circuit. A high percentage of bacteraemia gained positive
blood cultures from blood samples possessing less than 10 cfu of pathogen cells per
Fig. 15.3 Time course of the detection of fungal causative pathogens with VYOO1
15
New Approaches in Fungal DNA Preparation from Whole Blood
327
mL (Kreger et al. 1980). Sine qua non for a new NAT-based assay is therefore a
sensitivity which enters this analytical range to compete with the standard techniques in the lab and with the medical tradition which has to be persuaded for the
effectiveness of nucleic acid based assay systems. C. albicans, for example, was
detected in EDTA whole blood after spiking, using the new multiplex PCR tool and
gelelectrophoretic amplicon detection with a sensitivity of <20 cfu/mL, a level
which was attained previously only by qPCR-based techniques (Lehmann et al.
2008) requiring high-priced analytical devices and confined by restricted numbers
of detectable targets due to the available wavelength-specific fluorescence dyes (e.
g., 6-carboxy-fluorescein/FAM) and/or fluorescence channels of the qPCR device
used. Their number is in fact growing with the state of the art, but to achieve a still
limited but increased multiplex applicability fluorescence detection (e.g., via dual
fluorescence resonance energy transfer probes targeting species-specific internal
transcribed spacer (ITS) regions of PCR amplicons (Dunyach et al. 2008; Mancini
et al. 2008)), is combined with error-prone melting point analyzes and done with a
high workload (Schrenzel 2007).
The progress of the new standard multiplex procedure has in part to be attributed
to the high sample volume of 5 mL whole blood which can be applied, regardless of
the benefits of the usage of 15 mL centrifugation vials within the lysis step (see
above). The importance of the blood volume cultured or processed in NAT-based
methods has been discussed long ago (Arpi et al. 1989); however, the implications
of reduced sample volumes has been accepted for the qPCR evaluation due to the
always aspired miniaturization of assay layouts.
The innovative part of the new multiplex PCR assay, however, remains the
protein-based pathogen-DNA affinity chromatography step which is additionally
sold as an assay-independent pretreatment tool (LOOXSTER1), which may substantially enhance even home-brew NAT-based assays, and the unmatched ultrahigh multiplex assay for the simultaneous detection of fungal (and bacterial)
pathogens within one working day.
15.5
Conclusion and Future Line of Research
In recent years, a broad spectrum of PCR-based methods for the detection of sepsis
causative fungal pathogens has been developed and some of them might be suitable
to support and expedite clinical findings and strengthen a directed and restricted
antibiotic therapy. A standardization, however, is not yet in sight. At present, only
sparse information is available on potential cost benefits for application of molecular diagnosis versus conventional detection of bloodstream infections (Falagas and
Panayotis 2008) but it has to be assumed, that the high initial and running costs will
be outweighed by the increased assay sensitivity and reduced time-to-result.
The assays are in part compromised by their exquisite sensitivities responsible for
nucleic acid trace detection already present in associated consumables or introduced
via applying routine sample withdrawal techniques causing false-positive results.
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R.P.H. Schmitz et al.
Origin and clinical significance of those “false-positive” samples are often ambiguous and might belong to yet unbeknown host-pathogen interactions (Schrenzel
2007). Positive NAT-related findings therefore have to be correlated with other
clinical observations and diagnostic tests by clinicians and should not be the sole
reason for any therapeutical consequences. It should be remembered that three
decades ago culture-positive bacteraemia was reported after tooth brushing (Berger
et al. 1974), which indicates the range of risk factors that obtain false-positives and
the difficulties in distinguishing them from true-positives, a problem which might
also be assigned to fungaemia in general. The usage of broad-range primers should
be consciously balanced in favor of particular species detections. The amplification
method itself, e.g., loop-mediated isothermal amplification (LAMP), ligase chain
reaction, nucleic acid sequence-based amplification (NASBA), self-sustained
sequence replication (3SR), strand displacement amplification (SDA), transcription-mediated amplification (TMA), or cycling probe technology (CPT), as listed
by Schrenzel (2007), may in part significantly alter and improve the sensitivity of
the invented verification procedure – the NAT itself will only be as suitable as the
associated total DNA release and isolation protocols are – and of course, the
approach of getting rid of bulk DNA and polymerase inhibitors. What is required
are combined multitarget assay systems with proven clinical utility and that offer
high negative predictive values with notwithstanding high analytical sensitivities
and low detection thresholds.
Further approaches in test development should focus on standardization and
ongoing shortening of the clinical course, e.g., via automation of test flows. Coated
magnetic bead particles, e.g., for covalent binding of proteins and antibodies (e.g.,
for affinity chromatography), capture of biotinylated biomolecules (e.g., for hybridization techniques), DNA separation, or immunological applications (e.g.,
enzyme-linked immunosorbent assays, ELISA), are already used in many applications, since centrifugation is not required due to the separation of the beads, sized
from 50 nm to approximately 3 mm in diameter, from aqueous phases with magnets.
Time-consuming DNA-sedimentations and redilutions are circumvented.
The combination of multiplex PCR with microarrays on chips in part placed at the
bottom of reaction vials (e.g., ArrayTube1 system, Clondiag, Jena, Germany)
represents a currently tedious and laborious but forward-looking development. A
new gold standard for the detection of fungal pathogens, however, not yet found, will
for sure be nucleic acid based as announced by the current diagnostic achievements.
Acknowledgments The work was supported by grants from the Thuringian Ministry of Economy,
Technology and Labour (TMWTA 2007 FE 0255).
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Chapter 16
Classification of Yeasts of the Genus
Malassezia by Sequencing of the ITS
and D1/D2 Regions of DNA
Lidia Pérez-Pérez, Manuel Pereiro, and Jaime Toribio
Abstract Yeasts of the genus Malassezia are known commensals of human beings
and warm-blooded animals. Currently, they are considered emergent pathogen
yeasts and have been described as causative agents of systemic opportunistic
infections. An accurate identification of Malassezia spp. is of relevance to determine the role each species plays in the development of cutaneous and systemic
infections. The taxonomy of Malassezia spp. has been a matter of discussion since
the creation of the genus by Baillon in 1889. The recent development of molecular
techniques has improved the classification of this genus, allowing a more accurate
differentiation among different species. The taxonomic status is still under expansion, some new species have been appended recently and more will be probably
added in the near future. However, descriptions of new species should be done in a
standardized manner, including phenotypic and molecular features.
We describe the current classification of Malassezia spp. yeasts based on the study
and sequencing of ITS and D1/D2 gene of the rDNA and highlight the importance
of these regions of the DNA as an easy tool for the identification of this genus.
16.1
Introduction
Malassezia spp. is a common member of the skin flora which can become a
pathogenic element after changes in the cutaneous microclimate. It has been
implicated in the ethiopathogenic mechanisms of different skin diseases. Yeasts
of the genus Malassezia have been classically identified by physiological tests
L. Pérez-Pérez
Department of Dermatology, University Hospital Complex of Vigo, C/Porriño 5, 36209 Vigo,
Spain
e-mail: lidiacomba@yahoo.es
M. Pereiro and J. Toribio
Department of Dermatology, Laboratory of Mycology, Faculty of Medicine, University Hospital
Complex of Santiago de Compostela, C/ San Francisco S/N, 15706 Santiago de Compostela, Spain
Y. Gherbawy and K. Voigt (eds.), Molecular Identification of Fungi,
DOI 10.1007/978-3-642-05042-8_16, # Springer-Verlag Berlin Heidelberg 2010
337
338
L. Pérez-Pérez et al.
(Kaneko et al. 2007), which allow the identification of some but not all the Malassezia species recognized nowadays. The development of a range of molecular
techniques based on the study of particular genes has been a definite step in the
pathway of fungal identification (Gupta et al. 2004a; Canteros et al. 2007). They
provide a more accurate identification, detecting slight differences and are also a
very useful tool in the study of the taxonomy of the genus. They are also of great
value in the understanding of the phylogenetic relationships and the analysis of the
specific genetic variation of the species. The taxonomy and classification of the
genus Malassezia are currently being updated and they will be probably enlarged
with some other species in the near future. We present the classification of Malassezia spp. according to the sequencing of the D1/D2 domain and ITS regions of DNA
and discuss the value of the novel molecular techniques as identification tools.
16.2
Description of the Article
16.2.1 Clinical Relevance of the Genus Malassezia
Over the last few years, the implication of different yeasts in the development of
many diseases in humans has become very relevant, particularly in some subgroups
such as immunocompromised patients who may suffer from life-threatening widespread and severe infections. Malassezia spp. is a known commensal of warmblooded animals (including bears, monkeys, pigs, elephants, birds, horses, dogs,
goats, sheep, cows, etc) and humans, mainly colonizing areas with a high density of
sebaceous glands (scalp, face, ears, back, and chest). However, it can become a
pathogenic agent under certain circumstances (Fig.16.1) such as high temperature
and relative humidity, seborrhoeic constitution, hyperhidrosis, AIDS (Acquired
Immunodeficiency Syndrome), hematological malignancy, organ transplants, intravascular devices, antitumoral therapy, corticoids, and broad spectrum antibiotics
(Gupta et al. 2000, 2004b).
The most common disease related to Malassezia spp. is pityriasis versicolor
(Okuda et al. 1998; Crespo-Erchiga et al. 1999; Pereiro-Miguens 1999; Crespo et al.
2000a; Prohic and Ozegovic 2006; Krisanty et al. 2009) (Fig.16.2), which clinically
manifests as multiple brownish, pinkish or whitish plaques with a mild desquamation that usually appear on areas rich in sebaceous glands. Some studies have
suggested that M. globosa is the main causative agent of pityriasis versicolor
(Crespo et al. 2000a); however, others have found M. furfur and M. sympodialis
to be the most common species isolated in patients with this disease (Krisanty et al.
2009). Malassezia spp. may also play a role in the development of a number of skin
diseases including pityriasis capitis, folliculitis, atopic dermatitis (Sugita et al.
2001, 2003b; Sandström et al. 2005) (Fig.16.3), seborrhoeic dermatitis (Gaitanis
et al. 2006b; Prohic 2009), seborrhoeic blepharitis, confluent and reticulate papillomatosis (Gougerot and Carteaud syndrome) (Fig.16.4), transient acantholytic
dermatosis, acne, psoriasis (Paulino et al. 2006; Ashbee 2006) (Fig.16.4), nodular
16
Classification of Yeasts of the Genus Malassezia by Sequencing of the ITS
339
Fig. 16.1 Factors that can contribute to the pathogenic transformation of Malassezia spp
Fig. 16.2 (a) Typical clinical appearance of pityriasis versicolor, with whitish macules on a male
patient’s back. (b) A typical presentation of pityriasis versicolor, with atrophic patches and
coexisting foliculitis on a female patient’s back
hair infections, and onychomycosis (Gupta et al. 2004b). Midgley demonstrated
that 72.5% of patients with seborrhoeic dermatitis showed precipitating antibodies
to M. globosa (Midgley 2000). Crespo et al established that M. restricta and M
globosa were the most common species isolated from 75 patients with seborrehoeic
dermatitis (Crespo et al. 2000a). Folliculitis due to Malassezia spp. is a chronic
process characterized by the presence of small pruritic follicular papules and
pustules mainly distributed on the trunk and upper extremities. The role of Malassezia spp. in the development of atopic dermatitis is controversial. Some authorities
have suggested that these yeasts might act as allergens mainly in those patients with
lesions on their face and neck (Faergemann 1999). Confluent and reticulated
340
L. Pérez-Pérez et al.
Fig. 16.3 Atopic eczema on a
male patient’s forearm
Fig. 16.4 (a) Clinical appearance of reticulate papillomatosis of Gougerot and Carteaud on a male
patient’s back. (b) Typical plaques of psoriasis on a male patient’s back
papillomatosis is an uncommon disorder clinically characterized by greyish to
brownish papules on the trunk or abdomen. The relevance of the identification of
Malassezia yeasts in patients with this condition and also in patients with psoriasis
is yet unknown. Malassezia spp. has also been suggested to play a role in fungal nail
disease (Midgley 2000) and has also been identified as the causative agent for
different severe extracutaneous diseases (Gueho et al. 1987), particularly in patients
with underlying diseases or predisposing factors, such as pneumonia, mastitis,
sinusitis, malignant otitis externa, abscesses, meningitis (Ashbee 2007), catheterrelated fungaemia (Juncosa Morros et al. 2002), and peritonitis (Aspı́roz et al.
1997). M. furfur and to a lesser extent M. pachydermatis have been implicated in
the development of severe systemic disease in neonates. Malassezia spp. can also
cause many skin diseases in animals such as otitis externa (Crespo et al. 2000b;
Hirai et al. 2004), dermatitis (Cabañes et al. 2005), alopecia, ulcerous lesions,
pruritus, and liquenification (Chen and Hill 2005).
16
Classification of Yeasts of the Genus Malassezia by Sequencing of the ITS
341
16.2.2 The Diagnosis of the Genus Malassezia
The identification of the genus Malassezia and the differentiation among species
have been classically made on the basis of phenotypical and physiological features
(Table 16.1) such as the morphology of the colonies, size and shape of the cells
(Fig.16.5), and nutritional requirements (Guillot et al. 1996; Kaneko et al. 2007).
The macroscopic appearance of the colonies varies among the species. The colonies
are generally small, creamy to yellowish in color, with a smooth or rough surface
(Fig.16.6) and are composed of rounded, cylindrical or oval cells (Gueho et al.
1996). A characteristic physiological feature of these yeasts is their lipid-dependency, which may vary among the species. The lipid-dependent species need long
chain fatty acids to grow; meanwhile those non lipid-dependent species may grow
in common culture media containing short chain fatty acids. Except for M. pachydermatis, yeasts of the genus Malassezia are all lipid-dependent. However, different authors have described isolates of M. pachydermatis, phenotypically identified
as lipid-dependent, this fact still being a matter of controversy. (Cafarchia et al.
2007). Some authorities have suggested it would be the result of a process of
differentiation or adaptation to a particular host. The lipid-dependent species are
usually isolated from human skin whereas M. pachydermatis has been isolated
mainly from birds and mammals. The former have been associated with several
diseases and the latter causes chronic dermatitis and otitis externa in animals and
also nosocomial infection in humans (Cafarchia et al. 2007). Other physiological
features comprise the catalase reaction, assimilation of different polyethilenesorbitane esters (Tween 20, 40, 60, 80), enzymatic activity (esterase, esterase–lipase,
N-phosphohydrolase, acid phosphatase, alkaline phosphatase, phospholipase
(Cafarchia et al. 2008)), and tolerance to temperature. Guillot et al developed a
physiologic algorithm for the identification of Malassezia species based on lipid
assimilation and other phenotypic features (Guillot et al. 1996). Kaneko et al.
developed a culture-based system for the identification of Malassezia species
which allowed an easy identification of nine different species (particularly
M. furfur, M. globosa and M. restricta) with a rate of concordance with molecular
analysis of 98.1% (Kaneko et al. 2007). The atypical assimilation of Tween 80 has
been recently found to be of interest for the identification of M. furfur (González
et al. 2009).
These physiological tests, however, present some limitations and difficulties:
they are time-consuming, their results are variable, and sometimes display an
inadequate taxonomic value. The classical methods do not allow a certain identification of all the species and thus are not enough for classification purposes.
16.2.3 Current State of the Classification of Malassezia spp.
Until 1990, only three species of Malassezia were recognized, M. furfur
(Robin) Baillon, M. pachydermatis (Weidman) Dodge, and M. sympodialis
342
L. Pérez-Pérez et al.
Table 16.1 Physiological characteristics of the main Malassezia species: 1 ¼ M. furfur; 2 ¼ M. pachydermatis; 3 ¼ M. sympodialis; 4 ¼ M. globosa;
5 ¼ M. obtusa; 6 ¼ M. restricta; 7 ¼ M. slooffiae; 8 ¼ M. dermatis; 9 ¼ M. nana; 10 ¼ M. japonica; 11 ¼ M. yamatoensis. (Guillot et al. 1996; Hirai et al.
2004; Sugita et al. 2003b)
Features
1
2
3
4
5
6
7
8
9
10
11
Culture in Sabouraud medium at 32 C
+
(no lipid supplementation)
Culture in Dixon medium at 40 C
+
+
+
+
+
+/
Catalase reaction
+
+/
+
+
+
+
+
+
+
+
+/
Lipid assimilation:
+/
+
+
+
+
+
+/
+/
– Tween 20 (10%)
+
+
+
+/
+
+
– Tween 40 or 60 (0.5%)
+
+
+
NTb
– Tween 80 (0.1%)
+
Va
– Cremophor EL
Esculine hydrolisis
V
+
+
NT
NT
NT
+
+
NT
+
+
NT
NT
Precipitate in Dixon medium
a
V-variable
b
NT-not tested
16
Classification of Yeasts of the Genus Malassezia by Sequencing of the ITS
343
Fig. 16.5 Shape of Malassezia globosa cells
Fig. 16.6 Small, whitish and
creamy colonies of
Malassezia pachydermatis
(Simmons and Guého) (Gupta et al. 2000). In 1996, Guého et al updated the genus
Malassezia according to morphologic, ultrastructural, physiologic, and molecular
criteria and established a new classification comprising seven well-defined
species (Gueho et al. 1996). Recently, on the basis of genetic studies of a number
of different isolates from humans and animals, four new species have been suggested or proposed: M. dermatis (Sugita et al. 2002), M. nana (Hirai et al. 2004),
M. japonica (Sugita et al. 2003b), and M. yamatoensis (Sugita et al. 2004)
(Table 16.2). Nell et al. isolated a new species from horses, M. equi, which has
not been formally recognized (Nell et al. 2002), as its description was not provided
and there is not any type specimen currently available. Cabañes et al recently
described two new lipid-dependent species named Malassezia caprae sp. nov. and
Malassezia equina sp. nov., isolated from healthy goats and horses, respectively
(Cabañes et al 2007). These species seem to be closely related to M. sympodialis,
M. Dermatis, and M. nana. M. equina, M. caprae, M. Nana, and M. pachydermatis
are associated with animals; the remaining species are part of the normal human
flora and are also associated with human pathologies (González et al. 2009).
Several molecular techniques have been introduced recently in the field of
mycology for the study and identification of fungi. Those applied to study the
genus Malassezia include RADP (Random amplification of polymorphic DNA)
344
Table 16.2 Currently
accepted and proposed
Malassezia species
L. Pérez-Pérez et al.
Malassezia species
M furfur
M. pachydermatis
M. sympodialis
M globosa
M. slooffiae
M. obtusa
M. restricta
M. dermatis
M. japonica
M. nana
M. yamatoensis
M. caprae sp nov
M. equina sp nov
Author, year
(Robin) Baillon (1889)
(Weidman) Dodge (1935)
Simmons and Guého (1990)
Midgley et al. (1996)
Guillot et al. (1996)
Gueho et al. (1996)
Gueho et al. (1996)
Sugita et al. (2002)
Sugita et al. (2003)
Hirai et al. (2004)
Sugita et al. (2004)
Cabañes et al. (2007)
Cabañes et al. (2007)
(Castellá et al. 2005; Hossain et al. 2007), PFGE (pulsed-field gel electrophoresis)
(Boekhout et al. 1998), sequencing of the chitin synthase 2 gene (Kano et al. 1999),
sequencing of the large subunit of mitochondrial rRNA (Yamada et al. 2003), AFLP
(Amplified Length polymorphisms) (Gupta et al. 2004a), PCR of the LSU of the
rRNA and digestion with restriction enzymes (Guillot et al. 2000), multiplex-real
time PCR (Paulino et al. 2008), PCR-REA (Polymerase Chain Reaction and Restriction Enzyme Analysis) (Giusiano et al. 2003), DGGE (denaturing gradient gel
electrophoresis) (Theelen et al. 2001), RFLP (restriction fragment polymorphisms)
(Mirhendi et al. 2005), sequencing of the LSU of the rDNA or the ITS region (Sugita
et al. 2003a; Cafarchia et al. 2007). The most recent method developed for the
identification of Malassezia spp. is a bead suspension array that uses species and
group specific probes analyzed by flow cytometry (Dı́az et al. 2006). Cafarchia et al
suggested the use of multilocus sequencing for the identification of and differentiation among species or genotypes which are phenotypically difficult to characterize
(Cafarchia et al. 2007). Gaitanis et al published recently an interesting and detailed
review on the methodology for Malassezia typing, distinguishing two main groups of
techniques: those focused on targeted PCR amplifications of selected sequences and
subsequent search of mutations and random PCR-amplification of polymorphic DNA
or redundant sequences within the genome (Gaitanis et al. 2009). Most of these
methods are expensive and time consuming. In contrast, PCR techniques are easy to
perform and provide a rapid identification of Malassezia species (Affes et al. 2008).
Sequencing of the D1/D2 domain and the ITS regions (Gaitanis et al. 2006a;
Makimura et al. 2000) of the DNA is a useful and accurate procedure for the
identification and classification of different fungi (Abliz et al. 2004; León-Mateos
et al. 2006). The rDNA genes of Malassezia spp. are constituted by the 5S, 5.8S,
18S (small), and 26S (large) subunits (Fig.16.7). There are other two regions
inserted between the subunits: the ITS region (Internal Transcriber Spacer) and
the IGS region (Intergenic Spacer). Both of them are divided into two subregions.
The D1/D2 region of the DNA which encodes for the ribosomal large subunit
(LSUrDNA) is located in the 50 end of the large subunit (26S) of the ribosomal
16
Classification of Yeasts of the Genus Malassezia by Sequencing of the ITS
345
Fig. 16.7 Structure of the rDNA gene of Malassezia spp
DNA (Sugita et al. 2003a). These regions are highly conserved in a particular
species and vary among different species. rDNA is a multicopy gene that includes
several regions not encoding for proteins: ITS 1, ITS 2, and IGS, which are highly
conserved regions.
The D1/D2 region of the DNA encoding for the ribosomal large subunit
(LSUrDNA) is currently considered very useful for the identification of the vast
majority of fungi of medical relevance (Kurtzman and Robnett 1997; Fell et al.
2000). Most of the species can be identified by analysis of the D1/D2 domain. In
fact, no other genetic region with a higher ability to discriminate species has been
described to date (Abliz et al 2004). However, the study of closely related species or
strains requires sequencing of the ITS region (Cabañes et al. 2005).
The sequencing of the ITS regions and D1/D2 domain and subsequent studies of
the sequences obtained showed that the phylogenetic trees constructed with the ITS
region sequencing matched those obtained with D1/D2 domain sequencing (Gupta
et al. 2004a). This method allows an accurate identification and differentiation of
the current Malassezia species, which appear in the trees grouped in different
clusters. Small differences among strains from the same species can be found
sometimes and thus a particular species can be considered in terms of a “species
complex.”
Our group (Laboratory of Mycology, Department of Dermatology, Faculty of
Medicine, Santiago de Compostela) conducted studies on the D1/D2 and ITS
regions of isolates from different species of Malassezia, in an attempt to analyze
their phylogenetic relations (unpublished data). We studied a total of 28 strains
from six different species of the genus Malassezia (M. pachydermatis, M. sympodialis, M. furfur, M. restricta, M. globosa, M. sloffiae) (Table 16.3). These isolates
were collected from dogs, pigs, healthy subjects, and patients with pytiriasis
versicolor and were part of a 63-strain collection previously used by our group to
carry out a study on the LSU and ITS regions (unpublished data).
The strains were cultured in Saboraud and modified Dixon’s media supplemented with cyclohemixida and chloramfenicol following standard procedures and
were first identified on the basis of their phenotypic and physiological features.
DNA extraction was subsequently performed as described by Hillis (Hillis et al.
1996), after digestion of the cellular wall. The ITS region and D1/D2 domain were
amplified by PCR using respectively the fungal oligonucleotides (ITS-5, ITS-2,
ITS-3, ITS-4) and (NL-1, NL-2, NL-3, NL-4) (Table 16.4) synthesized by Sigma
346
Table 16.3 Details of the
strains sequenced in our study
L. Pérez-Pérez et al.
Origin
Animal, pig
Animal, pig
Animal, dog
Animal, dog
Animal, dog
Animal, dog
Animal, dog
Animal, dog
Animal, dog
Animal, dog
Animal, dog
Animal, dog
Animal, pig
Animal, pig
Animal, pig
Animal, pig
Animal, pig
Animal, pig
Human
Human
Human
Animal, pig
Animal, pig
Human
Human
Human
Human
Animal, pig
Strain
M. furfur 26
M. furfur 28
M. pachydermatis 4
M. pachydermatis 6
M. pachydermatis 10
M. pachydermatis 34LD
M. pachydermatis 21
M. pachydermatis 75LD
M. pachydermatis 13LD
M. pachydermatis 11
M. pachydermatis 75
M. pachydermatis 107LD
M. sympodialis 12A
M. sympodialis 13A
M. sympodialis 20
M. sympodialis 21
M. sympodialis 22A
M. sympodialis 25A
M. sympodialis 01022043
M. sympodialis 043943B
M. sympodialis 039371A
M. sympodialis 17A
M. sympodialis 32A
M. sympodialis CBS 7222
M. globosa 01034998
M. globosa 010425748
M. restricta VCA 585
M. slooffiae 3A
Code
MFU01
MFU02
MPA03
MPA04
MPA05
MPA06
MPA07
MPA08
MPA09
MPA10
MPA11
MPA12
MSY13
MSY14
MSY15
MSY16
MSY17
MSY18
MSY19
MSY20
MSY21
MSY22
MSY23
MSY24
MGL25
MGL26
MRE27
MSL28
Table 16.4 Primers used for the amplification of the D1/D2 domain and the ITS regions of
Malassezia spp
Tm ( C)
Region
Primer
Sequence (50 –30 )
D1/D2
NL-1
gca tat caa taa gcg gag gaa aag
650 33
NL-4 m
ggt ccg tgt ttc aag acg
610 79
ITS
ITS1
tcc gta ggt gaa ccg cgc
65
ITS5
gga agt aaa gtc gta aca agg
63
ITS2
gct gcg ttc ttc atc gat gc
62
ITS3
gca tcg atg aag aac gca gc
62
ITS4
tcc tcc gct tat tga tat gc
58
Genosys labs (Sigma Genosys Ltd, Sigma-Aldrich House, Haverhill, UK). These
primers had already been successfully used in previous studies of these regions
(Hirai et al. 2002; Sugita et al. 2002, 2003a; Martin and Rygiewicz 2005; Cabañes
et al. 2005). We extracted a number of sequences of different Malassezia species
from the Genbank database (Table 16.5) with comparative purposes and to study
their phylogeny.
16
Classification of Yeasts of the Genus Malassezia by Sequencing of the ITS
347
Table 16.5 Sequences extracted from the GenBank database and their accession numbers
Species
Strain
D1/D2 domain
ITS region
accession number
accesion number
M. sympodialis
WBC2
AY 387254
–
LMB3
AY 387268
–
KEB1
AY 387271
–
JF05
AY 387276
–
98F
AY 387291
–
MA231
AY 743609
AY743648
MA80.CBS9967
AY 743618
AY743647
MA125
AY 743619
AY743646
MA73.CBS9968
AY 743627
AY743640
MA 477
AY 743628
AY743639
MA88CBS9986
–
AY743645
MA419
–
AY743653
M. pachydermatis
GENOTYPE A
DQ915500
–
GENOTYPE B
DQ915501
–
GENOTYPE C1
DQ915502
–
CBS1879
AY387235
–
CBS1919
AY387236
–
CBS1885
AY387237
–
CBS1884
AY387238
–
CBS1879
AY743605
AY743637
AFTOL-ID856
AY745724
–
CBS1879
AJ249952
–
CBS1879
–
AB118941
IFM52772
–
AB118939
IFM52748
–
AB118940
IFM52755
–
AB118937
M. furfur
CBS1878
AY743602
AY743634
CBS7019
AY743603
AY743635
CBS1878
AY387196
–
M. yamatoensis
M9985
AB12563
AB125261
M9986
AB12564
M. japonica
CBS9431
EF140672
M9976
AB105199
AB105199
M. slooffiae
CBS7956
AY743606
AY743633
AJ249956
–
TV1
AY387249
–
M. globosa
CBS7966
AJ249951
–
AY387228
–
AY743604
AY743630
M. restricta
CBS7877
AJ249950
–
AY387239
–
AY743607
AY743636
M. obtusa
CBS7876
AY743629
AY743631
CBS7968
AY387234
–
M. dermatis
M9927
AB070361
AB070356
M9930
AB070364
–
348
L. Pérez-Pérez et al.
The sequences obtained were analyzed with the software DNAsis, CLC Free
Workbench v. 4.0.2 and MEGA version 3.1 (Kumar et al 2004).The clustal alignment of our sequences and those extracted from the GenBank database was
performed with the software CLC Free Workbench v.4.0.2. Subsequent comparative studies of the sequences obtained were conducted to analyze inter and intraspecies dissimilarities. The MEGA package, version 3.1, was used to perform a
maximum parsimony analysis with 1,000 bootstrap replicates.
The molecular phylogenetic trees of the ITS and D1/D2 regions of the 26s rRNA
gene sequences were constructed with MEGA v3.1 using the maximum parsimony
method.
The D1/D2 domain tree in Fig. 16.8 shows four well-defined phylogenetic clusters: cluster I comprises M. sympodialis strains, which seem to be closely related
to M. dermatis strains and display intraspecies diversity. Strains of M. sympodialis
from animals and humans tend to appear grouped in the tree. Cluster II includes
M. obtusa, M. yamatoensis, M. Japonica, and M. furfur. M. yamatoensis and
M. japonica are both from human origin and appear classified within the same
subcluster. All the M. pachydermatis strains were isolated from animals (dogs) and
are grouped in cluster III. The vast majority of our strains are grouped together,
closely related to those from the GenBank database. Cluster IV includes M. globosa,
M. Restricta, and M. slooffiae, which are clearly separated into three independent
subgroups.
The phylogenetic tree constructed with the sequences of the ITS region of our
strains and those selected from the GenBank database is shown in Fig. 16.9. As it
occurs with the tree obtained with the D1/D2 domain sequences, four main clusters
are identified: cluster I includes M. sympodialis, M. Dermatis, and M. yamatoensis;
cluster II comprises all the strains of M. pachydermatis, which seem to share a
common root with M. sympodialis. All of them appear grouped together. Cluster III
includes strains of M. japonica, M. Obtusa, and M. furfur. M. slooffiae, M. Globosa,
and M. restricta constitute cluster IV.
The phylogenetic relationships displayed in the trees constructed with the
sequences of ITS and D1/D2 regions are very similar.
16.3
Conclusions and Future Line of Investigation
The molecular methods have provided strong evidence to support the current
classification of Malassezia spp. and have contributed much to improve the understanding and knowledge of the genus (Gaitanis et al. 2009). However, they present
some limitations. Firstly, they need specific equipment and trained staff and are
expensive in comparison to the classical methods of identification. Moreover, on
clinical grounds, for most routine clinical mycology laboratories there is little need
to speciate the isolates recovered from skin samples. Although it is of epidemiological interest to determine the species of Malassezia associated with particular
16
Classification of Yeasts of the Genus Malassezia by Sequencing of the ITS
Fig. 16.8 D1/D2
phylogenetic tree (See text).
The numbers at branch points
represent the percentages of
1,000 bootstrapped datasets
that supported the specific
internal branches
349
Msy AY743627
Msy AY387276
Mder AB070361
99 Mder AB070364
MSY24
Msy AY387268
MSY20
Msy AY387254
2 MSY16
Msy AY743628
37
MSY15
MSY21
Cluster I
Msy AY387271
Msy AY387291
96 Msy AY743619
34
27
Msy AY743618
Msy AY743609
MSY14
35 24 MSY17
MSY22
MSY13
99
MSY19
MSY23
MSY18
43
99 Mob AY387234
Mob AY743629
99 Myam AB12563
Myam AB12564
38
96
Mjap EF140672
Cluster II
99 Mjap AB105199
MFU02
91
MFU01
Mfu AY743602
86
Mfu AY743603
Mfu AY387196
68 MPA05
60 MPA03
MPA10
Mpa DQ915502
MPA09
Mpa DQ915501
MPA12
Mpa AY387237
MPA08
98
MPA04
Cluster III
MPA07
MPA11
MPA06
Mpa AY387238
Mpa AY743605
46
Mpa AJ249952
Mpa DQ915500
84
Mpa AY387235
Mpa AY745724
Mpa AY387236
Mgl AY387228
MGL26
99
Mgl AJ249951
MGL25
Mgl AY743604
Mre AY743607
40
Cluster IV
99 MRE27
Mre AJ249950
Mre AY387239
Msl AY743606
31
Msl AY387249
99 Msl AJ249956
MSL28
5
350
L. Pérez-Pérez et al.
Fig. 16.9 ITS phylogenetic tree (See text). The numbers at branch points represent the percentages
of 1,000 bootstrapped datasets that supported the specific internal branches
16
Classification of Yeasts of the Genus Malassezia by Sequencing of the ITS
351
diseases, this is beyond the scope of most laboratories in a routine clinical setting
and thus, most of these methods are used in laboratories for only investigative
purposes. Because of the time it takes to culture Malassezia and the realization that
no single medium can reliably recover all the species, several groups have developed methods for the molecular analysis of fungus directly from the skin without
prior culture (Ashbee 2007) or from a range of commercial media used in microbiology laboratories (Pryce et al. 2006). This would be an interesting alternative, as it
shortens the identification process and makes it easier.
Anyway, the results obtained by molecular methods should be carefully interpreted under the light of the classical phenotypic methods of identification and
clinical findings, as the molecular classification is based on genetic sequences that
encode proteins and these are not directly related to the phenotypic characteristics
of the species. The current available analyzes study highly conserved regions of the
nuclear DNA encoding for the ribosomal subunits. Differences among the
sequences obtained seem to overlap with clear phenotypic differences observed
among the species. The dissimilarities found in these regions may affect the
intergenic spaces, which do not encode for protein (intron) or the spaces encoding
for a particular subunit. Intergenic spaces are of high value, as they include
transcription regulating regions. Along the evolution of the species, these spaces
tend to shorten due to deletions in the sequences and thus it is relatively common to
find differences. However, it can be difficult to establish whether these differences
merit to be considered a different species or are simply variations of a particular
species. The regions encoding for functional proteins (exon) tend to remain conserved and therefore significant differences in them are more difficult to observe. It
would also be of interest to analyze in future studies whether the differences among
these two regions (intron and exon) are concordant.
We tried to compare sequences of the ITS region and the D1/D2 domain of the
same strain, as we thought the comparison between these two regions of the DNA
would be stronger. It was not possible to do so with all the strains, as many of them
do not have sequences available for both regions in the GenBank database. We
consider it would be of interest to enlarge in the future the databases with strains
which were sequenced in both the ITS and D1/D2 domain, in order to compare this
two regions properly and analyze their relationships.
ITS region and D1/D2 domain are much conserved. Small differences between
them are of high relevance, particularly in the D1/D2 domain, as it is more
conserved than the ITS region. We consider of interest the classification of the
different species on the basis of the sequences of both regions. Some species
showed high diversity in the phylogenetic trees, thus suggesting that the existence
of close and different species not yet identified might be a strong possibility. We
observed that M pachydermatis and M sympodialis particularly showed higher
genetic diversity in the regions we studied and we suggest it would be interesting
to run a larger study on these species, as some of the strains currently included may
be recognized as new species in the future.
A deeper knowledge of all the Malassezia species and their biology is not only
necessary to fully understand the mechanism of many skin diseases, but also to
352
L. Pérez-Pérez et al.
improve and complement the different treatment options currently available for
these disorders.
Uploading new sequences of different species of Malassezia in the GenBank
database is of great interest in enlarging the number of sequences available for
studies in the near future. Larger investigations correlating the molecular dissimilarities among species and their phenotypical and biological characteristics are the
key to fully understand the real meaning of the findings in the molecular methods
and their impact in the daily routine.
Acknowledgments
We are very grateful to
l
l
l
l
Dr. Carmen Paredes Suárez (Dermatology Unit; Hospital Virxe da Xunqueira, Cee, Spain),
who kindly provided her personal data on the restriction enzyme analysis of the ITS region.
Dr Álvaro León Mateos (Department of Dermatology; Hospital POVISA, Vigo, Spain) for his
advise on the writing of this manuscript.
Dr. Margarita Garau and Dr Amalia del Palacio (Department of Microbiology; Hospital 12 de
Octubre, Madrid, Spain), for providing some of the strains for our study.
Dr. Gillian Midgley (Department of Medical Mycology, St John’s Institute of Dermatology, St
Thomas’ Hospital, London, UK) for her disinterested contribution to the understanding of the
genus Malassezia.
This study was supported by the grant PGIDT01PX120810PR from the Local Government of
Galicia, Spain.
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Chapter 17
DNA-Based Detection of Human Pathogenic
Fungi: Dermatophytes, Opportunists,
and Causative Agents of Deep Mycoses
Lorenza Putignani, Silvia D’Arezzo, Maria Grazia Paglia, and Paolo Visca
Abstract The affordability of modern molecular biology tools and the availability
of whole genome sequences have brought substantial improvement in research
on pathogenic fungi and diagnosis of fungal infection. Molecular methods have
resolved many critical aspects of mycological diagnosis by (1) providing specieslevel identification of fungi through sequencing of suitable taxonomic markers; (2)
shortening of the time required for microbiological confirmation of life-threatening
fungal infections; and (3) tracing the molecular epidemiology of fungal diseases.
Nucleic acids-based methods are less subjective than microscopy- or culture-based
methods and unaffected by fungal growth conditions, thus capable of discriminating between phenotypically undistinguishable species. This chapter focuses on the
contribution of DNA-based techniques to the identification of clinically important
fungi such as Aspergillus, Blastomyces, Candida, Coccidioides, Cryptococcus,
Dematiaceous fungi, Fusarium, Histoplasma, Trichosporon, Zygomycetes, and
Dermatophytes. Because of their excellent performances, molecular assays are
being increasingly adopted by clinical laboratories to complement conventional
methods, providing new diagnostic capabilities.
L. Putignani
Microbiology Unit, Children’s Hospital, Healthcare and Research Institute Bambino Gesù, Piazza
Sant’Onofrio 4, 00165 Rome, Italy
S. D’Arezzo and M. G. Paglia
National Institute for Infectious Diseases “Lazzaro Spallanzani” I.R.C.C.S, Via Portuense 292,
00149 Rome, Italy
P. Visca
National Institute for Infectious Diseases “Lazzaro Spallanzani” I.R.C.C.S, Via Portuense 292,
00149 Rome, Italy
Department of Biology, University of Roma Tre, Viale Marconi 446, 00146 Rome, Italy
e-mail: visca@uniroma3.it
Y. Gherbawy and K. Voigt (eds.), Molecular Identification of Fungi,
DOI 10.1007/978-3-642-05042-8_17, # Springer-Verlag Berlin Heidelberg 2010
357
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17.1
L. Putignani et al.
Introduction
Fungal pathogens are currently rivaling their bacterial counterparts as emerging
agents of nosocomial and community-acquired infections, posing a particular risk to
patients under sustained immunosuppression. Deep mycoses and systemic mycotic
infections have gained importance as potentially life-threatening opportunistic
infections. This is due to the increasing number of immunocompromised individuals
or the underlying risk factors, such as AIDS and cancer patients, organ transplant
recipients, and patients under intensive care or predisposing concomitant treatments
such as steroid, immunosuppressive, antineoplastic, and antibiotic chemotherapy.
Indeed, the progress in transplant medicine and the therapy of hematological
malignancies are counteracted by the threat of invasive or disseminated fungal
infections (IFI), mainly triggered by species belonging to genus Candida and
Aspergillus (Kontoyiannis and Bodey 2002; Pfaller and Diekema 2007). However,
cutaneous fungi are also becoming emerging agents of hematogenously
disseminated infections in the immunosuppressed host with severe or fatal prognosis
(Cornely 2008).
Recently, a substantial progress in fungal classification and identification has
been achieved by means of molecular studies aimed at (1) tracing of evolutionary
link between groups at higher taxonomic ranks through phylogenetic investigation;
(2) improving taxonomy, mostly at the level of genera and species; (3) developing
diagnostic applications for new defined taxonomic units; and (4) improving the
epidemiological tools to monitor outbreaks and transmission routes of infection to
subspecific entities (Yeo and Wong 2002). These broad aims have been achieved by
optimizing techniques (Guarro et al. 1999) based on highly performing molecular
targets, which serve as evolutionary clocks for phylogenetic studies (Yeo and
Wong, 2002). One such target is the group of genes encoding the nuclear ribosomal
RNA (rRNA). The main reasons for the success of the ribosomal DNA (rDNA) as
an evolutionary marker is that its sequences encode for multiple-copy loci, whose
repeated copies in tandem are synchronized by concerted evolution, and it is
therefore reasonably treated as a single locus (Guarro et al. 1999). Furthermore,
ribosomes are present in all organisms, with a common evolutionary origin. Parts of
the molecule are highly conserved (van de Peer et al. 1996; van de Peer et al. 1997)
and serve as reference points for evolutionary divergence studies. The 5.8S, 18S,
and 25–28S rRNA genes (or rDNAs) are transcribed as a 35S to 40S precursors,
along with internal and external transcribed spacers (ITS and ETS, respectively),
which are spliced out of the transcript (Guarro et al. 1999) (Fig. 17.1). The
conserved regions alternate with divergent domains (D1 and D2) and highly
variable regions (ITS) (Hassouna et al. 1984) (Fig. 17.1). Between each cluster,
there is a nontranscribed or intergenic spacer (NTS or IGS) that serves to separate
the repeats from one another along the chromosome (Fig. 17.1). A 5S rRNA gene
takes a variable position and transcription direction depending on the fungal group
(Fig. 17.1). The total length of one DNA repeat is between 7.7 and 24 Kb
(Hibbett 1992). For phylogeny of filamentous fungi, the 18S rDNA (also called
17
DNA-Based Detection of Human Pathogenic Fungi
359
Fig. 17.1 Schematic drawing of the physical organization of the fungal ribosomal rRNA gene
cluster. All cluster components are included in the representation. SSU, small subunit (18S rRNA
gene); LSU, large subunit (25–28S rRNA gene); D1 and D2 regions are the highly divergent
regions of the LSU rRNA gene, shown as black boxes. ITS1, ITS2, and ETS1, ETS2 represent,
respectively, intergenic and extragenic spacers, shown as dark grey boxes. Intergenic spacers
(IGS1 and IGS2), between each cluster are nontranscribed regions which separate rRNA clusters
from one another along the chromosome
the small-subunit, SSU) is most often used either as full-length sequence or as
subdomain of ca. 600 bp (Bruns et al. 1992). The divergent domains of the 25–28S
(also called the large-subunit, LSU) rDNA are very informative and allow comparisons from high taxonomic levels down to the species level, although only a limited
number of variable positions are present (Guého et al. 1993). In the 18S rRNA gene,
the variable domains mostly provide insufficient information for diagnostic purposes (de Hoog and Gerrits van den Ende 1998), and large parts of the molecule
must be sequenced to obtain the resolution required for species identification
(de Hoog and Gerrits van den Ende 1992). In contrast, the 5.8S rDNA is too
small and has the least variability. The 5S molecule has mainly been used to infer
relationships at the order level, where differences could be traced back to the
secondary structure of the molecule (Walker and Doolittle 1982). The ITS regions
are much more variable, and sequences can be aligned with confidence only
between closely related taxa. These regions have been extensively used to assess
intraspecies differentiation (Kurtzman and Robnett 1991, 1998; Kurtzman and Fell
1998; Lott et al. 1998; Iwen 2003; Hinrikson et al. 2005). In yeasts, the D1 and D2
variable regions of the 25–28S rDNA have been extensively used for species-level
identification (Sandhu et al. 1995; Sanguinetti et al. 2007; Linton et al. 2007;
Putignani et al. 2008b) (Fig. 17.1). A region encompassing the D2 domain has
also been exploited to produce a commercial sequencing kit based on the interrogation of libraries of fungal D2 rDNA sequences (MicroSeq D2 LSU rDNA
Fungal Identification Kit, Applied Biosystems). The MicroSeq system is composed of PCR and cycle sequencing modules, identification and analysis software,
and a D2 sequence library (Hall et al. 2003, 2004). Also mitochondrial targets,
considered as “multicopy” loci because of the multiplicity of mitochondria
per cell, have been exploited as molecular tools for the classification and identification of molds and yeasts (Guarro et al. 1999; Wang et al. 2000; Yeo and
Wong 2002; Yamada et al. 2004). Introns of several protein-encoding genes,
such as the b-tubulin (Tsai et al. 1994), actin (Cox et al. 1995), chitin synthase
(Bowen et al. 1992), acetyl coenzyme A synthase (Birch et al. 1992), glyceraldehyde-3-phosphate dehydrogenase (Harmsen et al. 1992), lignin peroxidase (Naidu
et al. 1990), or orotidine 50 -monophosphate decarboxylase (Radford 1993) genes,
can also provide information at the species level. Recently, repetitive genome
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sequences (rep) have also been exploited as taxonomical tools for identification of
Aspergillus spp. (Healy et al. 2004; Hansen et al. 2008) and Candida spp. (Wise
et al. 2007) or for genomic fingerprinting (rep-PCR) assays adapted to an automated platform (DiversiLab system, Biomerieux).
Amongst clinically relevant fungi, there are three main groups quite different
from one another and classified according to their biological characteristics. One
group is composed of dimorphic saprobes, which include soil-borne fungi that
have developed the ability to switch from a yeast to a hyphal morphology to
adapt to the hostile environment of the human body (Guarro et al. 1999).
The dimorphic pathogens (e.g., Histoplasma capsulatum, Coccidioides immitis,
Blastomyces dermatitidis, Paracoccidioides brasiliensis, Sporothrix schenckii,
Penicillium marneffei) are incorporated in the Ascomycota and belong to the
Plectomycetes group, a class of the supraordinal systematics defined according to
the asci arrangement (Müller and von Arx 1973). The second group, which is the
most numerous, consists of opportunistic saprobes, which cause opportunistic
mycoses in individuals whose immune system is deficient or artificially suppressed (Kendrick 1992). This group includes Aspergillus, Fusarium, Rhizopus
and Mucor genera, dematiaceous fungi, yeasts (Candida, Cryptococcus, Trichosporon), and zygomycetes. The third large group refers to dermatophytes, a group
of obligate parasites, which attack the human skin, nails, and hair and are
therefore mainly related to superficial mycoses (Kendrick 1992). This group
includes Epidermophyton, Trichophyton, and Microsporum genera. From a taxonomical view point, the pathogenic and opportunistic fungi are distributed among
three major phyla of the Kingdom Fungi: Ascomycota, Basidiomycota, and
Zygomycota (Guarro et al. 1999). Recently, a new comprehensive phylogenetic
classification of the Kingdom Fungi has been proposed, with reference to recent
molecular phylogenetic analyses, and supported by several members of the
fungal taxonomic community (Hibbett et al. 2007). Subkingdoms Dikarya and
Basal Fungi include the main phyla of medical relevance. The dermatophytes are
not a particular phylum but rather a short-hand label for the group of the three
fungal genera Epidermophyton, Trichophyton, and Microsporum, all belonging
to Ascomycota phylum (Fig. 17.2). Generally, the large fungal Phylum Glomeromycota are plant symbionts, Chytridiomycota and Neocallimastigomycota are
animal pathogens, while Blastocladiomycota are algal pathogens (Hibbett et al.
2007) (Fig. 17.2).
Apart from the taxonomic reevaluation, the teleomorph or anamorph relationship
(sexual and asexual reproductive stages, respectively) within the phyla Ascomycota
and Basidiomycota must also be taken into account for correct identification and
proper description of medically important fungi, especially in laboratory reports to
the clinical staff. Therefore, the species names reported hereafter will usually refer to
the anamomorph nomenclature or, alternatively, to the teleomorph name when
commonly used in practice. However, nomenclature interconversion from teleomorph to anamorph can be promptly achieved by interrogation of dedicated internet-based taxonomy browsers (e.g., http://www.doctorfungus.org/imageban/help.
htm; http://www.ncbi.nlm.-nih.gov/Taxonomy/Browser/wwwtax.cgi).
17
DNA-Based Detection of Human Pathogenic Fungi
361
Fig. 17.2 Schematic phylogeny and classification of fungal human pathogens within the Basal
Fungi and Dikarya Subkingdoms. The pathogenic and opportunistic human fungi are distributed
among the three major phyla Ascomycota, Basidiomycota, and Zygomycota of the Kingdom
Fungi. Subkingdom Dikarya include both Ascomycota and Basidiomycota (dark grey), while
Zygomycota (pale grey) belong to the Basal Fungi despite a pending resolution of relationships
among clades that still affect its definitive taxonomic location. The phylum Glomeromycota
includes important plant symbionts; Chytridiomycota and Neocallimastigomycota animal pathogens, while Blastocladiomycota algal pathogens. The group of dermatophytes belong to the
Ascomycota phylum. The branch lengths are not proportional to genetic distances. Modified
from Hibbett et al. (2007)
From a clinical perspective, early and accurate diagnosis of fungal infections is
crucial to avoid the extensive clinical use of empirical antifungal therapy, which is
the primary cause for the emergence of antifungal resistance (Yeo and Wong 2002).
It must be pointed out that a major drawback to the successful treatment of IFIs is
the lack of sensitive and specific methods for early diagnosis. Standard approaches
to the laboratory diagnosis of IFIs include (1) direct microscopic visualization for
the presence of organisms in freshly obtained body fluids, (2) detection of specific
antibodies, (3) histopathologic demonstration of fungi within tissue sections, and
(4) classical cultivation of the causative fungus with its subsequent macroscopic
and biochemical identification. These approaches are not sensitive enough and/or
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specific to the diagnosis of IFI, which requires invasive procedures to obtain the
necessary quantity of specimens. Moreover, the diagnosis of IFI can be biased by
improper samplings, not representative of the real agent and site of the infection,
as well known for invasive pulmonary aspergillosis (Kappe and Rimek 1999).
Furthermore, phenotypic identification of fungi requires complicated algorithms
and time-consuming procedures, not always correctly interpretable in daily
diagnostic routine without dedicated mycologists. Among the culture-independent
methods, detection of a specific host antibody response is attractive because such
tests can be performed rapidly and do not require invasive sampling procedures.
However, presence of host antibodies does not always correlate with the presence of
invasive mycosis, especially in patients whose humoral response is impeded by
immunosuppressive drugs and/or serious underlying disease. Detection of macromolecular antigens generally requires a relatively large fungal burden, which may
limit the sensitivity of these assays. Nonetheless, several examples of successful
antigen detection systems exist, and some of these are widely used in the clinical
mycology laboratory. Alternatives to standard culture and serologic diagnostic
methods include amplification and detection of specific fungal DNA sequences
and the detection and quantitation of specific fungal metabolome and proteome
products. In this scenario, the diagnosis of IFIs remains a challenge because clinical
symptoms are not pathognomonic, and searching for mycotic agents is delayed
unless a high index of clinical suspicion is applied and a differential diagnosis
provided.
This chapter will address recent advances in the DNA-based diagnosis of
relevant or emerging fungal pathogens, with special attention to the IFIs, which
represent an important cause of morbidity and mortality in both the developed and
developing world. Progresses in advanced molecular methods for diagnosis and
epidemiological typing of pathogenic fungi are becoming fundamental for early
treatment of patients, controlling fungal clearance, and counteracting resistance to
antifungal therapy.
17.2
DNA Manipulations
Specimen handling and preparation have a significant impact on the performance of
molecular diagnostic tests for fungal detection. The sample preparation method
should release intracellular DNA from the fungal cell wall, concentrate DNA
targets that may be present in very small amounts, and eliminate contaminants,
potential inhibitors, and other extraneous materials without degrading the target
DNA. The availability of an easy-to-perform DNA extraction procedure, providing
pure DNA devoid of PCR inhibitors, would be ideal for any PCR-based diagnostic
test. Simple cytolytic procedures for DNA extraction, e.g., thermolysis, although
used in some protocols (Putignani et al. 2008a, b) cannot be applied to all fungi. For
instance, filamentous fungi have strong cell walls which are often resistant to
traditional DNA extraction procedures. Fungal nucleases, polysaccharides, and
17
DNA-Based Detection of Human Pathogenic Fungi
363
pigments also contribute to difficulties in purifying DNA from filamentous fungi
(Hope et al. 2005). There are a multitude of nucleic acids extraction techniques
(Griffiths et al. 2006). The preferable method represents a compromise between
efficiency, purification yields, and transferability to the laboratory routine. DNA
may be extracted using in-house methods, commercial kits, and automated commercial techniques. Mechanical destruction with glass beads and freeze–thaw steps
with liquid nitrogen or a heat-alkali treatment have successfully been applied
(Hopfer et al. 1993; Löffler et al. 1997; Griffin et al. 2002). DNA extraction
following enzymatic digestion of the fungal wall is another effective method
(Williamson et al. 2000). However, many of these in house-methods are not suited
for the clinical microbiology laboratory, where many samples are simultaneously
processed. Moreover, the use of toxic chemicals such as phenol–chloroform mixtures further limits the use of in house-methods in the clinical routine (Griffiths
et al. 2006). The use of commercial kits (e.g., QIAmp Tissue, Qiagen; GeneReleaser, BioVentures; Puregene D 6000, Gentra; Dynabeads DNA DIRECT, Dynal; and
DNAzol, Molecular Research Center) shortens the extraction procedure, but the
efficiency of extraction of fungal DNA can vary considerably between commercial
kits (Griffiths et al. 2006; Löffler et al. 1997). Automated commercial techniques
(e.g., MagNA Pure LC; Roche Diagnostics) are better suited for routine clinical
laboratories (Costa et al. 2002). High-speed cell disruption (HSCD) incorporating
chaotropic reagents and lysing matrices provides rapid lysis of cells and high yields
of DNA from medically important yeasts (e.g., Candida albicans, Cryptococcus
neoformans, Trichosporon beigelii) and filamentous fungi (e.g., Aspergillus spp.
and Fusarium solani) (Müller et al. 1998). Concerted efforts are focused on the
optimization of DNA extraction methods from yeasts, particularly from blood
samples in cases of candidemia (Metwally et al. 2008a, b). Although the quality
of samples can affect the recovery of nucleic acids (Bougnoux et al. 1999; Fredricks
et al. 2005; Metwally et al. 2008a, b bis), yeast DNA has successfully been
extracted and purified from different clinical samples, including whole blood
(Buchman et al. 1990), serum and plasma (Kan 1993; Bougnoux et al. 1999;
Metwally et al. 2008a, b, bis), bronchoalveolar lavage fluid (Klingspor and Jalal
2006), and cerebrospinal fluid (CSF) (Ralph and Hussain 1996), using a variety of
home-made and commercial kits protocols.
Sample contamination should also be considered as a major problem in molecular diagnosis because of the extremely high sensitivity of all nucleic acids
amplification techniques. Fungal spores, such as conidia from Aspergillus spp.
and other molds, might be present in the air. Thus, airborne spore inoculation
during the DNA extraction process could potentially lead to false-positive results,
especially if panfungal primers are applied (Löffler et al. 1999). However, the risk
of contamination is not higher in fungal PCR assays than in other diagnostic PCRs
if general precautions are taken. In order to control naturally arising DNA from
airborne sources (e.g., fungal spores) negative controls should be included during
each DNA extraction procedure. Negative controls consist of sterile water or blood
from healthy individuals, and should be subjected to all preparation steps in parallel
with the extracted samples (Sarkar and Sommer 1990; Löffler et al. 1999).
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The development of semi-automated platforms that comprise nucleic acids
extraction and product detection through a series of linked instruments have
produced substantial implementation of molecular testing within the routine of
the clinical diagnostic laboratory, strongly reducing the risk of sample contamination. The absence of post-PCR processing after amplification step, as for the
on-chip platforms and the real-time PCR-based procedures, has offered many
practical advantages over the use of traditional detection methods by facilitating
sample processing and minimizing DNA shedding in the laboratory environment
(Löffler et al. 1999).
17.3
Panfungal Assays
For clinical diagnostic purposes, the broad-range detection of pathogenic fungi in
clinical samples is as important as the ability to identify the specific pathogen(s).
The common approach involves the application of broad-ranging panfungal primers
with postamplification analysis for species determination (Table 17.1). Panfungal
primers are directed toward conserved regions, usually within multicopy genes,
which flank sequences containing species specific polymorphisms that can be
defined in postamplification analysis (Chen et al. 2002). Depending on the assay,
a diverse range of fungal genera and species can be identified, including species of
Aspergillus, Candida, Cryptococcus, Fusarium, Trichosporon, Rhizopus spp., etc.
(Makimura et al. 1994; van Burik et al. 1998; Hendolin et al. 2000; Klingspor and
Jalal, 2006; Lau et al. 2007; Schabereiter-Gurtner et al. 2007; Spiess et al. 2007;
Zeng et al. 2007) (summarized in Table 17.1). The multicopy ribosomal gene
complex is a useful target for these assays for reasons of sensitivity (multicopy
target), high sequence conservation of 5.8S, 18S, and 25–28S rDNA regions (for
panfungal primers), and high variability of its intervening ITS regions (for species
specific probes) with high interspecies and low intraspecies heterogeneity
(Lott et al. 1998; Iwen 2003; Hinrikson et al. 2005). Panfungal assays are potentially able to detect all fungal pathogens, but require additional tests for specieslevel identification. The most common approaches for species differentiation rely
upon differences in restriction enzyme digestion patterns of amplicons, or their
hybridization with species-specific probes (Hopfer et al. 1993; Sandhu et al. 1995;
Einsele et al. 1997; Elie et al. 1998; Martin et al. 2000). Other methods, such as
differences in PCR product sizes following electrophoresis, amplicon sequencing,
or single-stranded conformational polymorphism analysis, have been applied
(Walsh et al. 1995; Henry et al. 2000; Chen et al. 2002; Iwen 2003; Gupta et al.
2004; Iwen et al. 2004). Detection of amplicons can also be achieved by means of
hybridization with enzyme-labeled oligonucleotide probe, eventually in microtiter plate-based enzyme immunoassay (Elie et al. 1998; Löffler et al. 1998;
Wahyuningsih et al. 2000), or fluorogenic probes (Guiver et al. 2001; Maaroufi
et al. 2003; Selvarangan et al. 2003), or by Southern blotting (Sandhu et al. 1995;
Einsele et al. 1997; van Burik et al. 1998; Evertsson et al. 2000). The use of a
17
Specificity
References
Einsele et al. (1997)
Walsh et al. (1995)
18S rRNA
18S rRNA
Blood
Culture
28S rRNA
Cervical swab, nail and Real Time
horny skin scraping,
serum, blood, urine
28S rRNA
Blood
PCR
Southern blot
28S rRNA
Respiratory (BAL)
and tissues
Blood, respiratory,
tissue
Skin, nail, wound, urine,
blood, respiratory,
tissue
Fresh and formalinfixed, paraffinembedded tissue
Real Time
FRET
Real Time
TaqMan
Aspergillus spp., Candida spp.
Aspergillus spp., Candida spp.,
Cryptococcus neoformans,
Pseudallescheria boydii, Rhizopus
arrhizus
Aspergillus spp., Candida spp.
Absidia spp., Mucor spp., Rhizopus spp.,
Rhizomucor spp.
Aspergillus spp., Candida spp.,
Cryptococcus spp., Mucor spp.,
Penicillium spp., Pichia spp.,
Microsporum spp., Trichophyton spp.,
Scopulariopsis spp.
Aspergillus spp., Candida spp.,
C. neoformans
Rhizopus spp., Mucor spp., Rhizomucor
spp.
Aspergillus spp., Candida spp.
PCR
ELISA
Aspergillus spp.,Candida spp.
Badiee et al. (2007)
PCR
Sequencing
Lau et al. (2007)
PCR
Multiplex liquid
hybridization
and sequencing
Candida spp., Cryptococcus spp.,
Trichosporon spp., Aspergillus spp.,
Fusarium spp., Scedosporium spp.,
Exophiala spp., Exserohilum spp.,
Apophysomyces spp., Actinomucor
spp., Rhizopus spp.
Aspergillus spp., Candida spp.,
C. neoformans
28S rRNA
ITS
ITS1
Southern blot
Ethidium bromide
staining
TaqMan and
sequencing
Van Burik et al. (1998)
Machouart et al. (2006)
Vollmer et al. (2008)
Evertsson et al. (2000)
Kasai et al. (2008)
Basková et al. (2007)
Hendolin et al. (2000)
(continued)
365
ITS1-5.8S
Tissues
rRNA-ITS2
PCR
PCR-RFLP
DNA-Based Detection of Human Pathogenic Fungi
Table 17.1 Main DNA-based wide-broad range and panfungal assays
Target DNA
Method
Detection method
Specimen
18S rRNA
Blood
PCR
Southern blot
Ethidium bromide
18S rRNA
Culture
PCR-SSCPa
staining
Method
Detection method
Specificity
References
INNO-LiPA
Enzyme
immunoassay
Microarray
hybridization
Aspergillus spp., Candida spp.,
Cryptococcus spp.
Aspergillus spp., Candida spp., Fusarium
spp., Mucor racemosus, Rhizopus
microsporus, Scedosporium
prolificans, Trichosporon asahii
Aspergillus spp., Candida spp.,
Epidermophiton floccosum,
Microsporum spp., Trichophiton spp.
Aspergillus spp., Candida spp.,
Cryptococcus spp.
Martin et al. (2000)
Multiplex-PCR
ITS2
Culture
PCR
ITS2
Culture
Repetitive
sequences
Cytochrome b
Culture
Reverse
line blot
hybridization
Rep-PCR
Microfluidics chip
Culture and tissues
Real Time
Spiess et al. (2007)
Turenne et al. (1999)
Playford et al. (2006)
TaqMan
Coccidioides spp., Blastomyces
Pounder et al. (2006)
dermatitidis, Histoplasma capsulatum
Hata et al. (2008)
Absidia spp., Apophysomyces spp.,
Cunninghamella spp., Mucor spp,
Rhizopus spp, Saksenaea spp.
Aspergillus spp., Candida spp.
Klingspor and Jalal (2006)
Melting point
Aspergillus spp., Candida spp.
FRET
Chemiluminescence Aspergillus spp., Candida spp.,
Cryptococcus spp.
Schabereiter-Gurtner et al.
(2007)
Zeng et al. (2007)
L. Putignani et al.
Blood, respiratory, bile, Real Time
drainage, urine,
pleura, CSF, biopsy
ITS2
Blood, respiratory,
Real time
tissues
ITS1/ITS2
Blood, respiratory
PCR-reverse
line blot
(BAL), tissue, CSF,
(RLB)
skin
a
Single-strand conformational polymorphism
18S rRNA
Fluorescent
capillary
electrophoresis
Enzyme
immunoassay
366
Table 17.1 (continued)
Target DNA
Specimen
ITS1-5.8S
Culture
rRNA-ITS2
18S rRNA,
Blood, tissues and
5.8S, ITS1
respiratory (BAL)
17
DNA-Based Detection of Human Pathogenic Fungi
367
panfungal PCR followed by hybridization with species-specific probes is a practical
solution to the problem of fungal detection.
17.4
Aspergillus spp.
Aspergillus spp. are filamentous, cosmopolitan, ubiquitous fungi which can cause
life-threatening infections, especially in immunocompromised patients. Aspergillus
spp. are commonly isolated from the soil, plant debris, and the indoor environment,
including hospitals (Latgé 1999). The genus Aspergillus includes over 185 species.
Nearly 20 species have been reported as causative agents of opportunistic infections
in humans. A. fumigatus is the most frequently isolated species in the clinical
setting. Other common species associated with infection are A. flavus, A. niger,
and A. terreus, while A. nidulans, A. versicolor, A. candidus, A. oryzae, A. sydowii,
and A. clavatus have been rarely documented (Patterson 2005). Aspergillosis
includes a large spectrum of fungal diseases which primarily affect the lung. The
transmission of fungal spores to the human host is via inhalation (Zmeili and
Soubani 2007). Aspergillus spp. may cause a variety of pulmonary diseases,
depending on immune status and the presence of underlying lung disease. These
manifestations range from hypersensitivity reactions (allergic bronchopulmunary
aspergillosis, ABPA) to noninvasive colonization of previously damaged tissue
(pulmonary aspergilloma) to acute or chronic limited invasive disease (chronic
necrotizing pulmonary aspergillosis) to rapidly progressive invasive disease (invasive aspergillosis) (Patterson 2005; Zmeili and Soubani 2007). Invasive aspergillosis is an often fatal infection that occurs in severely immunosuppressed patients,
and is characterized by invasion of blood vessels and organ dissemination, resulting
in significant morbidity and mortality (Kontoyiannis et al. 2002).
Risk factors for invasive aspergillosis are severe neutropenia, hematopoietic
stem cell and solid organ transplantation, prolonged and high-dose corticosteroid
therapy, hematological malignancy, cytotoxic therapy, AIDS, and chronic granulomatous disease (Segal and Walsh 2006; Zmeili and Soubani 2007). The incidence of
life threatening invasive Aspergillus infections has been increasing with the growing
number of transplant patients and patients with leukemia, lymphoma, and other
malignancies. Incidence rates of invasive Aspergillus infection are about 17–26% in
lung transplant patients, 5–24% in acute leukemia patients, 5–15% in allogenic bone
marrow transplant patients, 2–13% in heart transplant patients, and 1–3% in lymphoma patients (Patterson et al. 2000; Kontoyiannis et al. 2002).
17.4.1 Laboratory Diagnosis
Given that invasive Aspergillus infections are associated with high crude and
attributable mortality rates, early, rapid, and accurate diagnosis is important in
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order to guide the selection of appropriate antifungal therapy and thus improve
patient outcomes, as well as for epidemiological purposes. Earlier detection of
infection permits prompt initiation of antifungal therapy with greater likelihood for
improved survival and reduced morbidity. Moreover, diagnostic tests with a high
negative predictive value may allow expensive and potentially toxic antifungal
drugs to be withheld (Hope et al. 2005). The traditional diagnostics include
microscopy, culture on agar media, antigenemia, and search for antibodies. All of
them are limited either by poor sensitivity, narrow temporal window for fungal
detection, complex interpretation and high levels of nonspecific reactions. Positive
culture of Aspergillus spp., although indicative, is not a substantial proof of
infection. Furthermore, culture-based phenotypic identification techniques are
slow and prone to misidentification (Reiss and Morrison 1993). The “gold standard” investigation remains microbiological and/or histological evidence of tissue
invasion, which is not always achievable (Bretagne and Costa 2005).
The detection of galactomannan has been included into the routine practise for
diagnosis of invasive aspergillosis (Hope et al. 2005). There are two commercial
assays for the detection of galactomannan: the latex agglutination test (e.g., Pastorex Aspergillus; Sanofi Diagnostics Pasteur) and a double-antibody sandwich
enzyme immunoassay (e.g., Bio-Rad Platelia1 Aspergillus EIA, Bio-Rad Laboratories). However, the growth phase, microenvironment, host immune status, and
pathology may all influence galactomannan release and hence the results of immunological tests (Latgé et al. 1994). Furthermore, cross reactivity with other filamentous fungi, bacteria, drugs, and cotton swabs have been documented (Kappe and
Schulze-Berge 1993; Hashiguchi et al. 1994; Swanink et al. 1997; Dalle et al. 2002;
Mennink-Kersten et al. 2004).
17.4.2 Molecular Detection
The application of PCR technology to molecular diagnostics holds great promise
for the early identification of Aspergillus spp. (Williamson and Leeming 1999;
Klingspor and Loeffler 2009). DNA-based assays rapidly detect the presence of
fungal DNA in blood and other sterile body fluids with high sensitivity and
specificity (Williamson and Leeming 1999), particularly since parts of the fungal
genome, especially multicopy gene targets, were identified and sequenced
(Buchheidt and Hummel 2005). For early detection of Aspergillus spp. in clinical
samples, several groups have succeeded in defining target gene sequences, practicable primers, and effective DNA extraction methods. Technical difficulties, such
as differentiation and specification of the amplicons, have also been overcome by
different approaches (e.g., species-specific oligonucleotide probes and PCR
ELISA). A variety of PCR protocols for human samples have been published,
including panfungal PCR assays (Table 17.1) and methods that detect one species
or genus (Table 17.2). Using different primer sets, PCR has been recommended by
several studies as a useful tool in establishing the diagnosis of invasive aspergillosis
Culture
PCR-SSCP
ITS1-5.8S rRNA-ITS2
Culture
PCR
ITS2
Culture and
tissue
Blood
Culture
PCR
Blood culture
Real Time
PCR
Real-Time
Septifast
References
Aspergillus spp.
A. fumigatus
Aspergillus spp.
Makimura et al. (1994)
Löffler et al. (2000)
Kami et al. (2001)
A. fumigatus, A. flavus, A. glaucus, A. niger,
A. terreus
A. fumigatus, A. flavus, A. nidulans, A. niger,
A. ochraceus, A. terreus, A. ustus,
A. versicolor
A. fumigatus, A. flavus, A. terreus, A. nidulans,
A. niger
Aspergillus spp.
A. fumigatus
A. fumigatus
Sanguinetti et al. (2003)
A. fumigatus, A. flavus, A. terreus, A. niger,
A. ustus, A. nidulans
A. fumigatus, A. flavus, A. terreus, A. niger,
A. nidulans
A. fumigatus
Henry et al. (2000)
A. fumigatus, A. flavus, A. terreus, A. niger,
A. nidulans, A. ustus, A. versicolor
A. fumigatus, A. flavus, A. terreus, A. niger
A. fumigatus, A. flavus, A. terreus, A. niger
De Aguirre et al. (2004)
TaqMan
Ethidium
bromide
staining
Melting curve A. fumigatus
Halliday et al. (2005)
Melchers et al. (1994)
Pham et al. (2003)
Challier et al. (2004)
Spreadbury et al. (1993)
Rath and Ansorg (2000)
Zhao et al. (2001)
Faber et al. (2009)
Logotheti et al. (2009)
Mancini et al. (2008)
(continued)
369
18S rRNA
ITS1-5.8S rRNA-ITS2 and
aspergillopepsin 1st and
4th exon
ITS
Silver
staining
Ethidium
bromide
staining
ELISA
Specificity
DNA-Based Detection of Human Pathogenic Fungi
ITS1-5.8S rRNA-ITS2
17
Table 17.2 Main DNA-based assays for Aspergillus spp. identification
Target DNA
Specimen
Method
Detection
method
18S rRNA
Respiratory
PCR
Southern blot
18S rRNA
Blood
Real Time
FRET
18S rRNA
Blood and
Real Time
TaqMan
plasma
18S rRNA
Respiratory
Real Time
TaqMan
(BAL)
Real Time
TaqMan
18S rRNA
Blood, CSF,
ascitic
fluid, tissue
18S rRNA
Respiratory
PCR-RFLP
Southern blot
(BAL)
5.8S rRNA
Serum
Real Time
TaqMan
28S rRNA
Serum
Real Time
TaqMan
26S-ITS
Respiratory
PCR
Southern blot
(BAL)
ITS1-5.8S rRNA-ITS2
Culture
PCR
Sequencing
Specimen
Mitochondrial tRNA
Respiratory
(BAL)
Mitochondrial tRNA
Respiratory
(BAL)
Mitochondrial tRNA
Tissues
Mitochondrial tRNA
Blood and
serum
Mitochondrial tRNA
Serum
Mitochondrial tRNA
Respiratory
(BAL) and
tissues
Mitochondrial cytochrome b Respiratory
(BAL) and
blood
IgE-binding protein
Blood and
urine
FKS
Blood and
serum
Repetitive sequences
Culture
Repetitive sequences
Culture
Method
PCR
Detection
Specificity
method
Southern blot A. fumigatus, A. flavus, A. terreus, A. niger
Bretagne et al. (1995)
PCR
Southern blot A. fumigatus, A. flavus, A. terreus, A. niger
Raad et al. (2002)
PCR
Real Time
Sequencing
TaqMan
Aspergillus spp.
A. fumigatus
Rickerts et al. (2006)
Costa et al. (2001)
Real Time
Real Time
FRET
FRET
A. fumigatu, A. flavus
A. fumigatus
Costa et al. (2002)
Rantakokko-Jalava et al.
(2003)
Real Time
FRET
A. fumigatus
Spiess et al. (2003)
PCR
Southern blot A. fumigatus
Reddy et al. (1993)
Real Time
TaqMan
Rep-PCR
Microfluidics A. fumigatus, A. flavus, A. terreus
chip
Microfluidics A. fumigatus, A. flavus, A. terreus, A. niger,
chip
A. ochraceus, A, candidus, A. sydowii,
A. versicolor, A. nidulans
Rep-PCR
A. fumigatus
References
370
Table 17.2 (continued)
Target DNA
Costa et al. (2001)
Healy et al. (2004)
Hansen et al. (2008)
L. Putignani et al.
17
DNA-Based Detection of Human Pathogenic Fungi
371
(Spreadbury et al. 1993; Tang et al. 1993; Melchers et al. 1994; Skladny et al.
1999). However, the lack of standardization of technical issues continues to represent a considerable barrier for the widespread application of PCR in the diagnosis of
invasive aspergillosis (Bretagne 2003; Hope et al. 2005; Mengoli et al. 2009).
PCR assays may be applied to broncho alveolar lavage (BAL) specimens,
blood fractions (serum, plasma, whole blood) and tissues, including paraffinembedded thin sections (Hope et al. 2005). Initial studies focused on detection
of DNA in BAL samples (Spreadbury et al. 1993; Makimura et al. 1994; Melchers
et al. 1994; Bretagne et al. 1995; Raad et al. 2002) (Table 17.2). With few
exceptions, the rate of positivity was attained in 35% of the samples (Bretagne
2003). However, the inhaled Aspergillus spores or conidia, which are ubiquitous
in the air, could lead to false-positive reactions. In fact, Aspergillus hyphae are
often present in the air and could transiently colonize the respiratory tract of
noninfected individuals or even contaminate the amplification mixture. The PCR
performed on BAL cannot differentiate between infecting and colonizing fungi in
the oropharyngeal and bronchoalveolar space of patients (Bretagne and Costa
2005). On the other hand, some authors have highlighted the potential value of
a negative result to exclude a diagnosis of aspergillosis (Raad et al. 2002).
Therefore, a negative PCR test result in a patient with a suspected infection
suggests that the patient does not have invasive pulmonary aspergillosis, and
most likely does not have organism colonization. Given the high rate of positivity
and the difficulties in interpreting PCR positive results in bronchial specimens,
several studies have switched to blood samples, reporting a high positive predictive value (>95%) (Reddy et al. 1993). The use of PCR technology with serum or
plasma has several advantages over the use of BAL samples. First, assuming
appropriate handling of the specimen, false-positive results do not occur from
specimen contamination. Second, taking blood sample is considerably easier than
obtaining BAL (Einsele et al. 1997). Compared to ELISA, however, PCR positivity seems to occur later than galactomannan detection (Bretagne et al. 1998).
Therefore, the combined use of PCR and ELISA should result in a definitive
diagnosis aspergillosis, even in the absence of obvious clinical signs (Bretagne
et al. 1998). The optimal blood fraction for the detection of Aspergillus DNA
remains unknown. One study, using quantitative PCR (qPCR), suggested that the
yield of DNA from serum, plasma, and white cells was similar (Costa et al. 2002),
while another demonstrated that the PCR signal from whole blood was superior to
that from plasma (Löffler et al. 2000). Serum has the advantage of enabling
concomitant antigen testing (Costa et al. 2002), and does not require the addition
of anticoagulants (e.g., sodium citrate, edetic acid, or heparin) that may inhibit
PCR. An important study has recently focused on the diagnostic applicability of
serial blood and serum samples to diagnose IA in neutropenic patients by means
of real-time quantitative PCR combined with galactomannan quantification
(Cuenca-Estrella et al. 2009). Furthermore, a previous report (Suarez et al.
2008) had shown that real-time PCR assays, performed by using DNA extracted
from large serum volumes, may actually represent a robust and early diagnostic
tool for IA in patients under hematologic surveillance.
372
L. Putignani et al.
A variety of in-house and commercial PCR-based assays have been developed
for the identification of Aspergillus species (Table 17.2). The mitochondrial tRNA
genes and the (apo)cytochrome b have been used as PCR targets (Wang et al. 2000)
(Table 17.2). The rep-PCR assay (DiversiLab Aspergillus system) enables rapid
and accurate Aspergillus spp. identification (Healy et al. 2004; Hansen et al. 2008).
This approach takes advantage of the fact that there are repetitive elements interspersed throughout the fungal genome that, when amplified by PCR, give highly
discriminatory reproducible profiles within Aspergillus spp. The method has been
developed as a user-friendly kit, and the automated detection and analysis provides
readily interpretable reports (Hansen et al. 2008). Moreover, rep-PCR based identification is in full agreement with the ITS region sequence-based identification
(Healy et al. 2004). The MicroSeq D2 LSU rDNA Fungal Identification Kit
(Applied Biosystems) has allowed the identification of filamentous fungi, including
Aspergillus spp., by exploiting the D2 LSU diversity region (Hall et al. 2004). Some
of the newer assays are successfully using the real-time PCR technology, either the
Light Cycler or TaqMan technology, both combining amplification with simultaneous amplicon detection (Table 17.2). The method applies to DNA extracted from
both blood and BALs. One of the main advantages of the real-time PCR is the
possibility of avoiding false positive results due to contamination with previously
amplified products. Contamination is reduced because the reaction tubes need not
be opened following amplification. Moreover, real-time PCR techniques can also
include the systematic use of uracyl-N-glycosylase. The sensitive and specific
quantification of the fungal burden seems to be of clinical relevance, since the
assessment of the individual fungal burden may possibly allow therapeutic monitoring (Costa et al. 2001). To achieve an improved, specific, sensitive, and rapid
method for quantification of the A. fumigatus fungal load in clinical samples, Spiess
et al. (2003) established a LightCycler PCR assay to test blood and BAL samples.
An optimal pair of primers and hybridization probes derived from the sequence of
the A. fumigatus mitochondrial cytochrome b gene was selected (Spiess et al. 2003).
Two new TaqMan-based PCR assays for a fungal species, one targeting a single
copy gene and the other a mitochondrial gene have been developed (Costa et al.
2001). To diagnose invasive mold infection from serum samples a quantitative realtime PCR assay targeting the 5.8S rRNA gene was designed (Pham et al. 2003).
This assay distinguishes invasive infections caused by Aspergillus spp. from those
caused by Fusarium spp., and Scedosporium spp. (Pham et al. 2003). Recently,
Vollmer et al. (2008) developed a broad-range 28S rDNA real-time PCR assay for
the rapid detection of fungal pathogens in various clinical specimens (e.g., serum,
urine, and EDTA-supplemented blood). The assay allows the simultaneous detection
of and discrimination between genera of pathogenic fungi, including Aspergillus,
Candida, Cryptococcus, Mucor, Penicillium, Pichia, Microsporum, Trichophyton,
and Scopulariopsis (Vollmer et al. 2008). A rapid real-time PCR assay has recently
been designed which exploits regions of the 18S rRNA locus to simultaneously detect
the common A. fumigatus, A. flavus, A. terreus, and A. niger species by a differential
melting point analysis (Faber et al. 2009). Concomitantly, the multiplex PCR assay
described by Logotheti et al. (2009), has provided a similar panel for simultaneous
17
DNA-Based Detection of Human Pathogenic Fungi
373
identification (A. fumigatus, A. flavus, A. terreus, and A. niger) with an easier multiplexPCR system based on a combined ITS1-5.8S rRNA-ITS2 and aspergillopepsin first
and fourth exon primer set.
Recently, the real-time PCR assay based on ITS variability has been adapted to
semiautomated platforms (Light Cycler SeptiFast, Roche) significantly reducing
diagnostic turnaround time, particularly for the diagnosis of A. fumigatus, a typical
slow-growing filamentous fungus (Mancini et al. 2008).
17.5
Blastomyces dermatitidis
B. dermatitidis is a thermally dimorphic fungus and a probable saprobe of the soil. It
is rarely isolated as a natural habitat, specifically inhabiting decaying wood material. Isolation from the environment is most likely when the sample contains soil
and is rich in organic material. It is endemic in North America with highest
incidence of infection in Mississippi, Ohio, and the Missouri valleys (Pappas
2004). African type B. dermatitidis strains isolated from cases in Africa also
exist. It was demonstrated that African type strains are not identical to the North
American strains. These two groups most probably constitute distinct types of
B. dermatitidis showing geographic and serologic diversity (McCullough et al.
2000). The sexual state (teleomorph) of B. dermatitidis belongs to the family
Onygenaceae and is referred to as Ajellomyces dermatitidis. B. dermatitidis is the
only species included in the genus Blastomyces and is the causative agent of
blastomycosis (Pappas 2004). Cutaneous and disseminated blastomycosis are the
two clinical forms of the disease. Blastomycosis is generally acquired by inhalation,
and initially presents with a pulmonary infection which may later disseminate to
other organs. Primary cutaneous infection due to direct inoculation of the fungus
into the skin is also likely. Hematogenous spread of the organism results in
infection of skin, bones, kidneys, and male urogenital system. Reactivation blastomycosis and subclinical, self-limiting infections have been defined (Farr et al. 1992;
Mounts and Deepe 1998). Although B. dermatitidis is a pathogenic fungus and
blastomycosis occurs mainly in immunocompetent hosts, it may also infect immunocompromised patients, indicating that B. dermatitidis has now emerged as an
opportunistic pathogen (Pappas 2004).
17.5.1 Laboratory Diagnosis
The morphology of the fungus is mold-like at 25 C and yeast-like at 37 C. At 25 C,
septate hyaline hyphae and unbranched short conidiophores are observed. In rich
medium or in infected tissue sections the fungus appears as budding yeast cells.
Conversion of the mold phase to the yeast phase for definitive identification is
rarely performed now (Kauffman 2006). Diagnosis is often achieved by detection
374
L. Putignani et al.
of specific antibodies, which are usually absent at presentation of symptoms, and
which can be impaired in immunocompromised patients (Yeo and Wong 2002).
17.5.2 Molecular Detection
Since therapy and prognosis depend on early and specific diagnosis, there has been
considerable interest in molecular detection of B. dermatitidis. Specific DNA
probes have successfully been used for identification of B. dermatitidis isolates
through different hybridization assays (Stockman et al. 1993; Sandhu et al. 1995;
Lindsley et al. 2001). A sensitivity of 95% and a specificity of 100% with
B. dermatitidis yeast cells were obtained by using two oligonucleotide pairs complementary to the 18S and 28S rDNA (Hayden et al. 2001). A nested PCR assay was
established targeting the gene encoding the species-specific B. dermatitidis adhesin
(BAD), formerly called WI-1 (Bialek et al. 2003). This assay was specific and the
detection limit of 0.1 fg target DNA was comparable to the 18S rDNA PCR (Bialek
et al. 2005a, b). The 18S rDNA PCR is routinely used as a screening assay, and
when positive, the specific nested PCR is added to confirm the diagnosis
(Table 17.3). More recently, the automated rep-PCR (DiversiLab system) has
been used to identify B. dermatitidis, Coccidioides, and H. capsulatum isolates,
providing excellent performance for the identification of B. dermatitidis isolates, all
of which had very similar fingerprint patterns (Pounder et al. 2006).
17.6
Candida spp.
Candida is a complex genus comprising 163 anamorphic species with teleomorphs
in at least 13 genera (Kurtzman and Fell 1998). Some of these genera, such as Pichia
(Peterson and Kurtzman 1991) or Debaryomyces (Kurtzman and Robnett 1991,
1994) seem to be polyphyletic. Until few years ago, only a few pathogenic species
of Candida were known, namely C. albicans, C. parapsilosis, Candida krusei,
C. tropicalis, Candida lusitaniae, Candida dubliniensis, and Candida glabrata.
However, in recent years the number of species related to human infections has
increased considerably (Hazen 1995; D’Antonio et al. 1998; Sullivan and Coleman
1998; Trofa et al. 2008). Now nearly 20 species have been identified for being
associated with human infection (Hazen 1996). Candida spp. can either colonize or
infect nearly every body surface. The various forms of candidiasis are the most
frequent causes of fungal infection in man, and can present with extremely diverse
clinical manifestations. Candida spp. can produce infections in otherwise healthy
individuals, as well as in individuals with impaired immune function. Candidiasis
may be superficial (cutaneous), local (mucocutaneous, affecting mouth and vagina),
deep-seated (involving central nervous system, respiratory and urinary tract,
cardiac, ocular, peritoneum, and vasculature affections) and disseminated as
17
DNA-Based Detection of Human Pathogenic Fungi
375
systemic syndrome (candidemia), arisen from hematogenous spread from the primarily infected site. Systemic candidiasis is a complicate disease affecting individuals with reduced immune function or any other type of weakening of their
defences. Almost any organ of the body may be involved, after beginning as an
episode of candidemia, during which Candida can be isolated from blood. From a
clinical standpoint, systemic candidiasis may differ into four forms: (1) the catheterrelated candidemia, due to infection of a vascular catheter; (2) the acute
disseminated candidiasis in which candidemia is present and may apparently spread
to one or more organs; (3) the chronic disseminated candidiasis or hepatosplenic
candidiasis, occurring after prolonged episodes of bone marrow dysfunction and
neutropenia that occur during treatment for leukemia; (4) the deep organ candidiasis, in which any organ may be affected, either alone or in combination. When
Candida disseminates, multiple organs are usually involved, with the kidney, brain,
myocardium, and eye being the most common. As an aid to earlier diagnosis,
considerable attention has been focused on the detection of Candida antigens.
Despite the appearance of a large number of reports on the serologic diagnosis of
disseminated candidiasis, controversies remain regarding the value of various
serodiagnostic procedures. Problems with the older diagnostic tests have been
reviewed in detail (Edwards 1991). Among severely immunosuppressed patients,
almost all patients with candidemia have disseminated disease. The problem is
compounded by the absence of positive blood cultures in many patients with
disseminated disease. In these cases, a positive blood culture for Candida cannot
be underestimated but verified by repeated sampling. However, interpretation of the
ensuing resultion of the candidemia should be made with the recognition that 50%
of the patients with disseminated candidiasis would not have positive blood
cultures especially when concomitant bacterimia exists (Hockey et al. 1982; Geha
and Roberts 1994). Promptness in correct fungal identification is therefore crucial
in laboratory diagnosis to overcome limits arising from both serological and
culture tests.
Candida infections are the most frequent cause of IFIs worldwide (Pfaller and
Diekema 2007). In the United States, Candida spp. are the fourth most common
cause of nosocomial bloodstream infection (Pfaller and Diekema 2007). C. albicans
remains by far the most common species causing invasive candidiasis worldwide
although the frequency of other species, including Candida tropicalis, Candida
parapsilosis, Candida glabrata, and Candida krusei, has been steadily increasing
over the last 10 years (Pfaller and Diekema 2007). The burden of invasive candidiasis remains substantial; after a decline in mortality throughout the early to mid
1990s, mortality rates have leveled off in recent years (Pfaller and Diekema 2007).
There are a large number of well-characterized risk factors for invasive candidiasis,
including (1) exposure to broad-spectrum antibiotics (Pfaller and Diekema 2007),
(2) duration and degree of chemotherapy (Karabinis et al. 1988), (3) mucosal
colonization (Pfaller and Diekema 2007), (4) indwelling vascular catheter
(Diekema and Pfaller 2004), (5) total parenteral nutrition and severity of illness
(Ostrosky-Zeichner 2003), (6) neutropenia (Prentice et al. 2000), (7) prior
surgery (especially gastrointestinal) (Blumberg et al. 2001), (8) renal failure or
376
L. Putignani et al.
Table 17.3 Main DNA-based assays for identification of medically important fungi other than Candida, Aspergillus and Cryptococcus spp.
Target DNA
Specimen
Method
Detection method
Specificity
References
18S rRNA
Tissues and blood
PCR
Sequencing
H. capsulatum
Bialek et al. (2001)
B. dermatitidis
Bialek et al. (2003)
18S rRNA
Tissue
PCR
Sequencing
Rhizomucor spp.
Bialek et al. (2005a, b)
18S rRNA
Tissues
PCR
Sequencing
18S rRNA
Culture
PCR
Ethidium bromide staining
Trichosporon spp.
Sugita et al. (1998)
Cunninghamella spp.
Kasai et al. (2008)
28S rRNA
Plasma, respiratory (BAL)
Real Time
FRET
and tissues
Fusarium spp.
Mishra et al. (2003)
ITS
Culture
PCR
Fuorescence
Rhizopus spp.
Nagao et al. (2005)
ITS
Tissues and serum
PCR
Ethidium bromide staining
Fonsecaea pedrosoi
Miyagi et al. (2008)
ITS
Culture
PCR
Sequencing
ITS
Culture
Real Time
FRET
H. capsulatum
Martagon-Villamil et al. (2003)
Trichosporon spp.
Sugita et al. (1999)
ITS
Culture
PCR
Sequencing
Trichosporon asahii
Sugita et al. (2001)
ITS
Serum
PCR
Ethidium bromide staining
ITS2
Respiratory and tissue
Real Time
FRET
Coccidioides spp.
Binnicker et al. (2007)
Trichosporon asahii
Mekha et al. (2007)
IGS1
Serum
Real Time
TaqMan
Trichosporon spp.
Rodriguez-Tudela et al. (2005)
IGS1
Culture
PCR
Sequencing
H. capsulatum
Guedes et al. (2003)
M antigen
Culture
PCR
Ethidium bromide staining
H. capsulatum
Bracca et al. (2003)
H antigen
Blood and tissues
PCR
Ethidium bromide staining
Hc100
Tissues
PCR
Ethidium bromide staining
H. capsulatum
Bialek et al. (2002a)
Coccidioides posadasii
Bialek et al. (2004)
Ag2/PRA
Tissues
Real Time
FRET
Coccidioides posadasii
Bialek et al. 2004
Ag2/PRA
Tissues
PCR
Sequencing
WI-1
Tissues
PCR
Sequencing
B. dermatitidis
Bialek et al. 2003
17
DNA-Based Detection of Human Pathogenic Fungi
377
hemodialysis (Blumberg et al. 2001), (9) bone marrow and solid-organ transplantation (Rüping et al. 2008), (10) recurrent or persistent gastrointestinal perforation
(Eggimann et al. 1999), and (11) preterm delivery depending on gestational age and
after birth intubation practices (Saiman et al. 2000; Wang et al. 2008).
17.6.1 Laboratory Diagnosis
The challenging diagnosis of Candida infections reflects the complexity of the
diseases sustained by these species. Traditional microbiological techniques
for diagnosis of invasive candidiasis often fail to detect Candida spp. as blood
cultures are often negative or become positive too late. Efforts to develop reliable
diagnostic tests have stimulated the development of several serological methods for
the diagnosis of Candida infection. However, antibody detection in patients
with candidiasis is of limited usefulness for three reasons: (1) colonization by
Candida spp. of the gastrointestinal tract or other sites can elicit antibody responses
in uninfected individuals; (2) immunocompromised patients may not mount
detectable antibody responses even when they have deep Candida infections; (3)
development of a significant antibody titer occurs too late during infection.
Morphologically, Candida spp. are thin walled and ovoid unicellular organisms
(blastospores). Budding yeasts and pseudohyphae appear as Gram-positive.
Candida organisms form smooth, creamy white, glistening colonies. Preliminary
identification relies on Germ tube test, despite the fact that both false-positive and
false-negative germ formation may occur (Sheppard et al. 2008). Traditional
identification procedures are based on metabolic tests rather than on morphological
characteristics (Wadlin et al. 1999). Because of variation in pathogenicity of
individual species, accurate identification at the species level is highly recommended in clinical practice (Bishop et al. 2008; Sivakumar et al. 2009). In blood
cultures, the growth kinetics may differ between Candida spp.: 1–3 days are
necessary for C. albicans, C. parapsilosis, and C. tropicalis in standard medium,
while growth of C. krusei and C. glabrata may take longer (Prevost and Bannister
1981). While candidemia would seem to be a key element of invasive candidiasis,
retrospective studies have shown that blood cultures are positive in less than 50%
of patients with autopsy-proven invasive candidiasis. (Rodriguez et al. 1996).
Candiduria is common, especially in hospitalized patients having urinary catheters
(Chen et al. 2008). However, neither the absolute colony count nor the presence
or absence of white blood cells is pathognomonic (Navarro et al. 1997). It is
particularly frequent to find Candida spp. in the respiratory tract of severely ill
patients, but clinically relevant candidal pneumonia is quite rare and the presence of
Candida spp. in the sputum has only a loose association with pneumonia
(Rodriguez et al. 2000). Detection of Candida in CSF should always be regarded
as pathognomonic of central nervous system (CNS) candidiasis.
Despite intense and long-lasting efforts, no serological test has yet been shown
to have clinical applicability. Very recently, a test employing Candida cytoplasmic
378
L. Putignani et al.
antigens has been developed to measure circulating IgG, IgM, and IgA antibodies
against C. albicans (Prince et al. 2008). Unlike the conventional antibody detection
tests, the direct detection of Candida spp. antigens has been shown to have potential
as an early diagnostic test. The Cand-Tec latex agglutination test (Ramco Laboratories,) was used as the first commercially available antigen detection test (Lemieux
et al. 1990). However, the specificity and sensitivity of the Cand-Tec assay varied
among reports (Phillips et al. 1990), and this test per se cannot establish a diagnosis
of candidiasis. An alternative strategy is the detection of circulating b-(1-3)-Dglucan, a main cell wall component of Candida. High concentrations of b-(1-3)-Dglucan have been detected in patients with invasive candidiasis (Miyazaki et al.
1995a, b), and a commercial test is available (Fungitec G-test; Seikagaku Corporation). The detection of mannan antigenemia (mannanemia) for the immunodiagnosis of systemic candidiasis is widely used in patients with candidiasis, since positive
mannan result may correlate with invasive candidiasis (Yeo and Wong 2002).
Furthermore, correlation has been demonstrated between mannanemia and tissue
invasion by Candida spp. in patients with candidemia, while mannanemia was less
likely to be positive in patients with transient or central venous catheter-related
candidemia (Girmenia et al. 1997). Two assays employing the anti-mamman EBCA1 monoclonal antibody are marketed as the Pastorex Candida latex agglutination
test (Bio-Rad) and the Platelia Candida Antigen test (a double-sandwich enzyme
immunoassay by Bio-Rad) (Sendid et al. 1999). Although the specificities of these
two assays are similar, the EIA is more sensitive than the latex agglutination test
(Sendid et al. 1999). Despite the attempt to improve the immunodiagnostic detection of mannan, most assays, like the Pastorex latex agglutination test, still lack
sensitivity due to the rapid serum clearance of the antigen.
17.6.2 Molecular Detection
The increasing incidence of Candida infections in immunocompromised patients
(Cornely 2008) has focused attention on the exploitation of nucleic acids based
techniques to set rapid and accurate diagnosis of IFI, independently from immunological-related markers. Nucleic acid hybridization and amplification methods
provide both high detection rates and identification of Candida at the species
level. This is increasingly important with the widespread use of antifungal therapy,
and the problem of species-dependent resistance to antifungal agents in the genus
Candida (Pfaller and Diekema 2004). Targets that are used in molecular diagnostic
tests for Candida infections include both single and multicopy genes of nuclear
and mitochondrial origin (Table 17.4). Among single copy genes of nuclear origin,
actin, chitin synthase, cytochrome P450, and cytochrome P-450 lanosterol14a-demethylase (L1A1) have been exploited to detect Candida spp. by standard
and nested-PCR from a wide set of clinical specimens including blood, serum,
BAL, and body fluids (Kan 1993; Burgener-Kairuz et al. 1994; Chryssanthou et al.
1994; Jordan 1994) (Table 17.4). Species-specific restriction fragment length
Method
PCR
Chitin synthase
cytochrome P450
Blood
Serum
PCR
PCR
cytochrome P-450
lanosterol-14ademethylase (L1A1)
L1A1
Blood, deep pus, peritoneal fluid, PCR
pleural fluid, CSF, bile, urine,
BAL
BAL, blood
PCR-RFLP
L1A1
Blood
PCR-RFLP
18S rRNA
Culture
PCR-RFLP
HSP90
Swabs, urines, peritoneal fluid,
pus, blood, serum
Blood
PCR-RFLP
ITS
18S rRNA
ITS
Serum
Serum
Serum
PCR-EIA
PCR
PCR
25–28S rRNA
LSU D2/D1
ITS1-5.8S-ITS2,
25–28S rRNA
LSU D2
Repetitive sequences
25–28S rRNA
LSU D2
Culture
EO3,duplicated
mitochondrial region
Detection method
Hybridization with
radiolabeled probe
Southern blotting
Ethidium bromide
staining
Southern blotting
Specificity
Candida spp.
References
Kan (1993)
Candida spp.
Candida albicans
Jordan (1994)
Chryssanthou et al. (1994)
Candida spp.
Burgener-Kairuz et al. (1994)
Candida spp.
Morace et al. (1997)
Candida spp.
Morace et al. (1999)
Candida spp.
Hopfer et al. (1993)
C. albicans
Crampin and Matthews (1993)
C. albicans
Miyakawa et al. (1993)
Candida spp.
Candida spp.
Candida spp.
Burnie et al. (1997)
Einsele et al. (1997)
Bougnoux et al. (1999)
PCR
Ethidium bromide
staining/Southern
blotting
Ethidium bromide
staining
Ethidium bromide
staining
Hybridization with
radiolabeled probe
Ethidium bromide
staining/Southern
blotting
Enzyme immunoassay
Southern blotting
Ethidium bromide
staining
Sequencing
Candida spp.
Linton et al. (2007)
Culture
PCR
Sequencing
Candida spp.
Sanguinetti et al. (2007)
Culture
Culture
Rep-PCR
PCR
Microfluidics chip
Sequencing
Candida spp.
Wise et al. (2007)
Hall et al. (2003)
PCR
(continued)
379
Specimen
Serum
DNA-Based Detection of Human Pathogenic Fungi
Target DNA
Actin
17
Table 17.4 Main DNA-based assays for identification of Candida spp
Specimen
Culture
Method
PCR
Detection method
Sequencing
Blood culture
PCR
ITS1 and ITS2
Blood culture
Multiplex-PCR
EF3, CDC3, HIS3
microsatellite
M13 minisatellite
Culture
Real-Time
Ethidium bromide
Candida spp.
staining
Candida spp.
Ethidium bromide
staining
Primer fluoro-labeling C. albicans
Culture
PCR
ITS2
25-28S rRNA
LSU D2/D1
ITS
Culture
Culture
PCR
LAMP
Blood culture
Real-Time
Septifast
ITS2
RNA subunit of RNase P
ITS2
ITS2
18S rRNA
Blood culture
Blood
Blood
Culture
Blood culture
Real-Time
Real-Time
Real-Time
Real-Time
Real-Time
Melting curve
TaqMan
TaqMan
TaqMan
TaqMan
ITS1 and ITS2
18S rRNA gene
Serum
Culture
Real-Time
Real-Time
Melting curve
Melting curve
Ethidium bromide
staining
Pyrosequencing
LAMP amplicon DIGlabeling
Melting curve
Specificity
Candida spp.
References
Putignani et al. (2008a, b)
Li et al. (2003)
Chang et al. (2001)
Beretta et al. (2006)
C. albicans
Bartie et al. (2001)
Candida spp.
Candida spp.
Boyanton et al. (2008)
Inácio et al. (2008)
C. albicans,
C. tropicalis,
C. parapsilosis,
C. krusei,
C. glabrata
Candida spp.
Candida spp.
Candida spp.
Candida spp.
FLC-sensitive species
(C. albicans,
C. tropicalis,
C. parapsilosis,
C. dubliniensis) and
FLC-resistant
(C. glabrata,
C. krusei)
Candida spp.
Candida spp.
Mancini et al. (2008)
Selvarangan et al. (2003)
Innings et al. (2007)
Maaroufi et al. (2003)
Guiver et al. (2001)
Metwally et al. (2007)
Dunyach et al. (2008)
White et al. (2004)
L. Putignani et al.
Target DNA
25–28S rRNA
LSU D2
ITS1 and ITS2
380
Table 17.4 (continued)
17
DNA-Based Detection of Human Pathogenic Fungi
381
polymorphisms (RFLPs) have been identified in the L1A1 locus, making possible
the identification of Candida species directly from DNA extracted from BAL and
blood, even though traditional blood cultures and antigen detection assays were
negative (Morace et al. 1997, 1999). Also HSP90 and ribosomal DNA RFLPs
patterns have been exploited to perform identification of C. albicans and Candida
spp. from clinical specimens (Crampin and Matthews 1993; Hopfer et al. 1993).
Single-strand conformational polymorphisms of the 18S rDNA have provided
differential profiles for Candida spp. and several yeast and mold species (Walsh
et al. 1995).
Methods targeting multicopy genes offer lower detection limit in terms of
number of fungal genomes. Among multicopy genes, mitochondrial DNA has
been used in the PCR-based detection of C. albicans (Miyakawa et al. 1992) and
Candida spp. (Yokoyama et al. 2000). However, the variability of mitochondrial
DNA among different strains may be a limiting factor. Other studies have targeted
the multicopy rDNA gene cluster with universal primer sets, in order to maximize
sensitivity and specificity (Sandhu et al. 1995; Martin et al. 2000, Putignani et al.
2008a, b). As already discussed, the ribosomal genes contain conserved sequences
that are common to all fungi (Figure 17.1), and which can be used to screen for yeast
presence (Burnie et al. 1997; Einsele et al. 1997), while the variable ITS and LSU
D2 sequences can be exploited for species identification (Linton et al. 2007;
Sanguinetti et al. 2007; Putignani et al. 2008a, b). Indeed, the commercial MicroSeq
D2 LSU rDNA Fungal Identification Kit can easily be applied to yeast identification
(Hall et al. 2003). Since non-albicans Candida spp. are increasing in importance
(Bille et al. 2005; Tavanti et al. 2005), broad-range diagnostic approaches capable of
identifying a large number of Candida species are required (Table 17.4). The huge
amount of sequencing data generated for the ribosomal 25–28S rDNA target have
recently allowed molecular mycologists to compare between DNA-based identification procedures and classical diagnostic methods using large cohorts of patients
and yeast isolates (Linton et al. 2007; Sanguinetti et al. 2007). New technologies,
such as the pyrosequencing-based method, have recently been developed to perform
identification of Candida spp. (Boyanton et al. 2008). Moreover, an innovative
technique alternative to the PCR and based on isothermal DNA amplification, is
providing highly performing identification of Candida (Inácio et al. 2008).
Repeated genome regions, dispersed through the fungal genomes, have also been
considered to assess inter and intraspecies variability within the genus Candida.
A real-time PCR study performed by using EF3, CDC3, and HIS3 microsatellite
sequences provided an interesting example of genotyping clustering for cases of
candidaemia in an intensive care unit (Beretta et al. 2006). Also a minisatellitespecific M13 primer was exploited to assess a mixed population of C. albicans
strains in the oral microflora of patients affected by chronic hyperplastic candidosis
(CHC) (Bartie et al. 2001). More recently, the DiversiLab rep-PCR-based system
made it possible to identify and differentiate clinical isolates of Candida spp. (Wise
et al. 2007). Most of the questions raised on the value of PCR assays for invasive
aspergillosis apply also to disseminated candidosis (Bretagne and Costa 2005).
The aim of several reports using PCR assays (Table 17.4) is to demonstrate the
382
L. Putignani et al.
superiority of PCR assays over blood cultures. The latter are known to be poorly (ca.
50%) sensitive, as previously discussed. A likely explanation is the low burden of
circulating yeasts makes unlikely their sampling from blood. Therefore, the amplification of Candida DNA from blood raises the question whether the DNA comes
from living Candida or it is naked DNA from lysed cells. If the aim of PCR assays is
to improve the detection of viable Candida cells, this should be related to the
sensitivity of blood culture, usually comprised between 1 and 150 CFU/mL (Einsele
et al. 1997). With currently used DNA extraction kits, the input blood volume is
usually 200 mL. Thus, in order to obtain a PCR-positive result, at least ten Candida
cells must be present in the 200 mL tested (i.e., 50 cells/mL), since only 1/10th of the
extracted material is loaded in the PCR reaction. Under these conditions, a blood
culture performed with 10 mL of blood is expected to turn positive unless the
Candida fails to grow because of antifungal treatment. If the amplified DNA
comes from circulating nacked DNA, as suggested by the better yield reported for
serum than for blood (Burnie et al. 1997; Bougnoux et al. 1999), the sensitivity using
multicopy genes as a target could reach higher sensitivity than 50 Candida cells/mL,
probably below one Candida genome/mL assuming that the target is > 50 copies
per cell, as in case of the rDNA. Indeed, the sensitivity of the real-time PCR (Light
Cycler) system targeting the ITS was estimated ca. 1 cell/mL (White et al. 2003).
However, the meaning of such a finding is less clear than a positive blood culture,
especially in heavily colonized patients, as seen in ICUs, or patient under antifungal
therapy. Another potential limit is the need to detect several Candida species, at
least the five or six main species encountered in blood cultures (Tortorano et al.
2004). Thus, a good method should distinguish between most of the Candida spp.
which are sensitive to fluconazole, and C. glabrata and C. krusei whose sensitivity is
variable or null. Detection of anonymous yeasts in a pathological sample, without
the knowledge of the involved species, cannot direct antifungal therapy until yeast
identification. Therefore, to overpass the traditional culture on agar media, a realtime PCR assay should enable to detect and identify every Candida spp. even in
polymicrobial association. The generation of new real-time PCR instruments which
can simultaneously use up to four fluorogenic probes (as in the Light Cycler
SeptiFast system) is a substantial advance in this direction. Another option is to
associate PCR assays with a DNA-chip technology as in the rep-PCR DiversiLab
system. As for Aspergillus, the use of real-time PCR should improve the reproducibility of the PCR tests and make comparison of the results from several studies
feasible. The current assays are methodologically heterogeneous (Table 17.4).
Recently, panfungal-primer based assays (Table 17.1) have also been applied to
solve emerging clinical issues, as the detection of invasive candidosis in renal
transplant recipients (Badiee et al. 2007) (Table 17.1).
17.7
Coccidioides spp.
Coccidioides immitis and Coccidiodes posadasii, the only species included in the
genus Coccidioides, are dimorphic fungi found in soil particularly in warm and dry
areas with low rain fall, high summer temperatures, and low altitude. The two
17
DNA-Based Detection of Human Pathogenic Fungi
383
species are morphologically identical but genetically and epidemiologically distinct
(Fisher et al. 2001, 2002). C. immitis is geographically limited to California’s San
Joaquin valley region, whereas C. posadasii is found in the southwest of the United
States, Mexico, and South America. Imported cases are observed following travel
to endemic areas (Cairns et al. 2000). The two species co-exist in the southwest of
the United States and Mexico. Coccidioides spp. are causative agent of coccidioidomycosis in humans. Coccidioidomycosis is a true systemic mycoses (Galgiani
1999), acquired by inhalation, and initially presents with a pulmonary infection
which may later disseminate to other organs and systems. Airway coccidioidomycosis involving the endotracheal and endobronchial tissues may develop (Polesky
et al. 1999). The clinical picture has a remarkably wide spectrum. The infection
remains as an acute and self-limiting respiratory infection in most exposed individuals, but it can progress to a chronic and sometimes fatal disease in others.
Spontaneous healing is observed in ca. 95% of the otherwise healthy individuals.
Clinical presentations of coccidioidal infection are acute pneumonia, chronic
progressive pneumonia, pulmonary nodules and cavities, extrapulmonary nonmeningeal disease, and meningitis (Chiller et al. 2003). Due to the true pathogenic
nature of the fungus, coccidioidomycosis affects otherwise healthy, immunocompetent humans, although it may also affect immunocompromised patients, such as
AIDS patients and organ transplant recipients (Medoff et al. 1992; Blair and Logan
2001). In fact, concurrent risk factors are HIV infection, organ transplant, hematologic malignancy and pregnancy (Powell et al. 1983). Coccidioidomycosis is a
common cause of community-acquired pneumonia (CAP) in disease-endemic
areas. However, because Coccidioides spp. testing among CAP patients is infrequent, reportable-disease data, which rely on positive diagnostic test results, greatly
underestimate the true disease prevalence (Chang et al. 2008).
17.7.1 Laboratory Diagnosis
The diagnosis of coccidioidal infection can be traditionally made in three ways: (1)
identification of coccidioidal spherules in a cytology or biopsy specimen, (2)
culture from any body fluid that is positive for Coccidioides spp., or (3) a serologic
test that is positive for the Coccidioides spp. Since Coccidioides does not colonize
humans, the finding of spherules in tissue, sputum, bronchoalveolar lavage fluid, or
other body fluid or a positive culture from any location in the body is pathognomonic of coccidioidal infection. For the safe isolation of Coccidioides spp., the
laboratory should maintain a biological safety level 2 or 3. Serodiagnosis can be
used to detect coccidioidal infection. Early immune response is characterized by the
presence of IgM, which can be detected by a tube precipitin method, immunodiffusion, latex agglutination, or enzyme immunoassay (EIA). Latex agglutination and
EIA are highly sensitive but are associated with false-positive results (Pappagianis
2001). These qualitative tests provide positive or negative results but no quantitative information. By comparison, complement fixation provides a quantitative titer
that reflects the intensity of the immune response (Galgiani 1992).
384
L. Putignani et al.
17.7.2 Molecular Detection
Identification of coccidioidal elements in tissue sections can be very difficult or
impossible (Kaufman et al. 1998). A successful approach to C. immitis detection in
paraffin-embedded tissue sections is in situ hybridization. Hayden et al. (Hayden
et al. 2001) described a set of oligonucleotide probes which identify and differentiate yeast like organisms in tissue sections. The C. immitis-specific probe had a
sensitivity of 94.3%, a 100% specificity, and a positive predictive value of 100%.
However, identification by this method is limited to cases with microscopically
visible fungal elements. Stockman et al. (1993) showed a commercially available
acridinium ester-labeled chemiluminescent DNA probe targeting the ribosomal
RNA of Coccidioides spp. to be sensitive and 100% specific. A total of 164 strains
from related and unrelated fungal species were tested to define specificity, and no
cross-reaction was detected. The probe was developed for detection on spherule in
tissue samples. Fixation in formaldehyde reduces efficiency of this excellent and
widely used identification system (Gromadzki and Chaturvedi 2000). Nested PCR
and a real-time PCR assays were recently developed to target the genus-specific
antigen2/proline rich antigen of Coccidioides spp. (Bialek et al. 2004) (Table 17.3).
Melting curve analysis by LightCycler and sequencing of the 526-bp product of the
first PCR correctly identified all strains as C. posadasii. In addition, specific DNA
was amplified by the conventional nested PCR from three microscopically spherulepositive paraffin-embedded tissue samples whereas 20 human samples positive for
other dimorphic fungi remained negative (Bialek et al. 2004). Another LightCycler
assay, targeting the ITS2 locus, allows identification of Coccidioides spp. from
various respiratory specimens (Binnicker et al. 2007). Finally, a rep-PCR assay,
binding to multiple noncoding, repetitive sequences interspersed throughout the
genome, was exploited to test different Coccidiodes spp. (Pounder et al. 2006)
(Table 17.3). Distinction between C. inmitis and C. posadasii species was assessed
by designing appropriate coupled primers amplifying nucleotides 660.313–661.032
of C. immitis contig 2.2 (AAEC02000002, (http://www.broad.mit.edu/annotation/
fungi/coccidioides_immitis/). This test discriminates C. posadasii from C. immitis
for a 86-bp deletion (Umeyama et al. 2006).
17.8
Cryptococcus neoformans
Although more than 30 species are included in the genus Cryptococcus, only two of
them are pathogenic: Cryptococcus neoformans and Cryptococcus gattii (KwonChung et al. 2002). In the environment, C. neoformans is primarily found associated with fecal excretions from certain birds, such as pigeons, and in tree hollows.
For years, C. gattii was found primarily in tropical and subtropical regions. It has
been associated primarily with eucalyptus trees, which were considered its primary
niche (Hull and Heitman 2002). These species were previously classified as three
17
DNA-Based Detection of Human Pathogenic Fungi
385
varieties: C. neoformans var neoformans, C. neoformans var grubii, and C. neoformans var gattii (Franzot et al. 1999), which were classified into five capsular
serotypes: A, D, and the hybrid diploid AD belonging to the C. neoformans, with
serotype A named C. neoformans var grubii, and serotype D named C. neoformans
var neoformans; and serotype B and C classified as C. gattii (Franzot et al. 1999)
and eight molecular genotypes (VNI through VNIV for C. neoformans and VGI
through VGIV for C. gattii) (Meyer et al. 2003). Principal predisposing factors for
cryptococcosis are HIV infection, treatment with corticosteroids, solid organ transplantation with immunosuppressive therapies, malignancies, CD4+ T-cell lymphopenia, connective tissue diseases or immunologic diseases, diabetes mellitus,
chronic pulmonary diseases or lung cancer, renal failure or peritoneal dialysis,
cirrhosis and pregnancy (Perfect and Casadevall 2002). Before the HIV epidemic,
cryptococcal infection was an uncommon systemic fungal infection that occurred
primarily in patients who had impaired immunity (Mitchell and Perfect 1995).
However, during the past two decades of the HIV epidemic, the incidence of
cryptococcosis increased dramatically. Before the development of the “highly
active antiretroviral therapy” (HAART), cryptococcal infection was regarded as
the major cause for morbidity and mortality in HIV-infected patients with CD4
lymphocyte counts < 100 cells/mL. However, in the HAART era, the incidence of
cryptococcosis decreased significantly in HIV patients, although remaining constant in non-HIV individuals (Friedman et al. 2005). A recent clinical syndrome
associated with HAART-driven immune reconstitution in HIV patients is “the
immune reconstitution inflammatory syndrome” (IRIS). IRIS has been reported to
occur in 30–35% of HIV patients with a history of cryptococcosis in whom HAART
was initiated (Perfect and Casadevall 2002). Patients infected with HIV who have
cryptococcal meningitis and IRIS have a greater fungal burden, as indicated by
higher CSF antigen titer and the presence of disseminated infection or fungemia.
Nevertheless, cryptococci are hardly culturable from these patients, and molecular
diagnosis is recommended (Putignani et al. 2008a, b). Similar to patients infected
with HIV, those who have undergone solid organ transplantation and having higher
cryptococcal antigen titers with disseminated disease are more likely to develop
IRIS after initiation of antifungal therapy (Singh et al. 2005). Cryptococcosis is the
third most common invasive fungal infection after candidiasis and aspergillosis in
patients undergoing solid organ transplantation (Vilchez et al. 2002). The CNS and
respiratory tract are the most plagued organs by C. neoformans and C. gattii
infections.
17.8.1 Laboratory Diagnosis
Traditionally, diagnosis of cryptococcosis depends on Cryptococcus culture or on the
demonstration of encapsulated yeasts in India ink-stained pathological samples.
Direct microscopy and culture are specific but the sensitivity is poor (50–80%)
(Snow et al. 1975). Although culture remains the “gold standard” for diagnosis, it
386
L. Putignani et al.
is cumbersome, labor intensive, and time consuming because of the slow growth of
cryptococci. On the other hand, negative cultures may occur despite positive India ink
examinations because of nonviable yeast cells that may have prolonged persistence at
the infection site (Putignani et al. 2008a, b). Serology is an indirect and adjunct or
complementary procedure to support clinical diagnosis, especially when the patient is
on treatment. Antigen detection still represents the fastest and simplest diagnostic
tool. Detection of cryptococcal capsular polysaccharide antigen in serum or body
fluids has performed robustly for many years. The main component of the C. neoformans capsular polysaccharide is a glucuronoxylomannan (GXM). Antigenic structures intrinsic to the GXM allow the distinction between serotypes. An important tool
in the diagnosis of cryptococcosis is the latex particle agglutination test (LAT, e.g.,
Cryptococcus-Antigen Latex-Agglutination System; CALAS, Meridian Bioscience
Inc.), which uses latex particles coated with an anti-GXM antibody to detect capsular
polysaccharide antigen in serum or CSF. LAT is the most commonly used serological
method due to its simplicity in performance (Hamilton et al. 1991; Kiska et al. 1994),
although suffering from false positivity and difficulty of interpretation in borderline
cases (Whittier et al. 1994; Millon et al. 1995). Enzyme immunoassay (EIA, e.g.,
PREMIER Cryptococcal Antigen Kit; Meridian Bioscience) is another serological
tool for detection of capsular polysaccharide antigens of C. neoformans in CSF. This
is a rapid test that provides visual and numeric result in less than an hour without
pre-treatment of the specimen (Saha et al. 2008).
17.8.2 Molecular Detection
Various DNA extraction procedures have been published for efficient disruption of
cryptococcal cells, including enzyme digestion or glass beads (Tanaka et al. 1996),
and a number of PCR assays have successfully been applied to diagnose cryptococcal disease starting from a variety of clinical specimens, such as blood, liquor,
secretions, cutaneous scrapings, bronchial alveolar aspirate, and urine. These PCR
assays use primers targeting the 18S, 28S, or the ITS and 5.8S rDNA, eventually
coupled with species-specific probes (Mitchell et al. 1994; Sandhu et al. 1995;
Prariyachatigul et al. 1996; Rappelli et al. 1998; Kano et al. 2001; Bialek et al.
2002b; Iyer and Banker 2002; Takahashi et al. 2003; Pagano et al. 2004; Paschoal
et al. 2004; Putignani et al. 2008a, b) (Table 17.5). Unique primers named CN4,
CN5, and CN6, have been developed to amplify the 5.8S and ITS regions of
C. neoformans rDNA, and used with different clinical specimens (Mitchell et al.
1994). Rappelli et al. (1998) set up a nested PCR assay on the ITS region of
C. neoformans directly in CSF specimens, followed by visual detection in agarose
gels (Rappelli et al. 1998). This method was improved by Paschoal et al. (2004),
who shortened the time for C. neoformans detection and identification from
CSF samples by entailing just a single step for the amplification. The results
demonstrated that PCR had the highest sensitivity rate (92.9%), superior to
culture (85.7%) and to India ink test (76.8%) (Paschoal et al. 2004). Rapid cycling
17
DNA-Based Detection of Human Pathogenic Fungi
387
Table 17.5 Main DNA-based assays for identification of C. neoformans
Target DNA Specimen
Method
Detection method
References
18S rRNA
Tissues
PCR
Sequencing
Bialek et al. (2002b)
18S rRNA
Tissues
Real Time
Real time (FRET)
Bialek et al. (2002b)
18S rRNA
CSF
PCR
Southern
Prariyachatigul et al. (1996)
hybridization
18S rRNA
Culture
PCR
Ethidium bromide
Mitchell et al. (1994)
staining
ITS2
CSF
PCR
Ethidium bromide
Rappelli et al. (1998)
staining
ITS2
Lymph node PCR
Ethidium bromide
Putignani et al. (2008a, b)
aspirate
staining
ITS2
Respiratory PCR
Sequencing
Takahashi et al. (2003)
(BAL)
Culture
PCR
Sequencing
Putignani et al. (2008a, b)
25–28S
rRNA
LSU D2
ITS5.8S
CSF
PCR
Ethidium bromide
Paschoal et al. (2004)
rRNA
staining
CAP59
Tissues
PCR
Ethidium bromide
Kano et al. (2001)
staining
Ethidium bromide
Tanaka et al. (1996)
URA5
Respiratory PCR
and
staining
tissues
real-time PCR protocols further simplified the diagnostic laboratory workflow and
reduced the possibility of product contaminations (Bialek et al. 2002b; Bergman
et al. 2007). Bialek et al. (2002b) established two PCR protocols targeting the 18S
rRNA gene of C. neoformans. One protocol was designed as a nested PCR to be
performed in conventional thermal cyclers. However, to minimize the event of
false-positive results, amplicons should be sequenced for an unambiguous species
identification. The other protocol was designed as a quantitative single-round
PCR adapted to LightCycler technology (Bialek et al. 2002b) which avoids
amplicon verification by means of Southern blotting or DNA sequencing. Once
DNA is extracted from suitable specimens and reaction mixtures are completed, the
results of sensitive and quantitative PCR are available within 60 min (Bialek et al.
2002b). A simple PCR-based method for C. neoformans serotyping strains, which
uses a set of four primers for the laccase (LAC1) gene has recently been developed
(Ito-Kuwa et al. 2007). This primer combination differentiates serotypes A, D, B,
and C. Further differentiation between serotypes AD and D requires the use of a
primer pair to the capsule (CAP64) gene. When multiplex PCR is performed with
all of the above six primers, the five serotypes generate distinct fingerprints
composed of two to five fragments. Genotype-based differentiation of the
C. neoformans serotypes can further be achieved by combining PCR-RFLP analysis
of the CAP10 and CAP59 genes (Raimondi et al. 2007). A reverse line blot
hybridization panfungal assay for identification of C. neoformans isolates is also
available (Zeng et al. 2007) (Table 17.1).
388
17.9
L. Putignani et al.
Dematiaceous Fungi
Chromoblastomycosis, mycetoma, and phaeohyphomycosis are fungal infections
caused by dematiaceous (darkly-pigmented) fungi, a group of organism usually
found in the soil (Revankar et al. 2002). Chromoblastomycosis, a chronic infection
of skin and subcutaneous tissues, is most commonly seen in tropical areas with most
cases caused by Fonsecaea pedrosoi followed by Fonsecaea compacta, Phialophora
verrucosa, Cladophialophora carrionii, and Rhinocladiella aquaspersa (Revankar
et al. 2002, Sanche et al. 2003). Infection typically occurs via traumatic implantation
in exposed surfaces of the legs (Milam and Fenske 1989). Mycetoma, also known as
Madura’s foot, is also a chronic infection of cutaneous and subcutaneous tissues,
caused by Madurella mycetomatis, Madurella grisea, Curvularia lunata, Exophiala
jeanselmei, and Leptosphaeria senegalensis (Sanche et al. 2003). Chromoblastomycosis and mycetoma are considered types of phaeohyphomycoses, which can also
include corneal, systemic infections, and fulminant disseminated disease (Revankar
et al. 2002; Sanche et al. 2003). Over 100 species have been implicated in phaeohyphomycoses (Revankar et al. 2002). Genera associated with pneumonia include
Ochroconis, Exophiala, and Chaetomium (Revankar et al. 2004) while Scedosporium
(e.g., S. prolificans) and, to a lesser extent, Bipolaris and Wangiella produce
disseminated disease (Revankar et al. 2002, 2004). Genera associated with CNS
infection include Cladophialophora (e.g., C. bantiana), Ramichloridium (e.g.,
R. mackenzei), and Ochroconis (Kantarcioglu and de Hoog 2004; Revankar et al.
2004; Revankar 2006). In contrast to other IFIs, underlying immunodeficiency is not a
prerequisite for phaeohyphomycoses, although some immune dysfunction is associated with disseminated disease (Revankar et al. 2002). Mortality rates are high
regardless of the patient’s immune status; however, recovery from neutropenia is
considered critical for patients with S. prolificans infection (Revankar et al. 2002). No
risk factors have been identified in many patients (Kantarcioglu and de Hoog 2004;
Revankar et al. 2004). However, CNS disease is generally correlated to cellular
immune dysfunction while disseminated disease to malignancy, neutropenia,
HSCT, solid organ transplant (SOT), HIV, and catheterism (Cornely 2008).
17.9.1 Laboratory Diagnosis
Classical methods are based on 20% potassium hydroxide microscopy, histopathological confirmation of sclerotic cells by periodic acid-Schiff stain, culture on
Sabouraud’s glucose agar, slide culture method, and observation of conidia by
scanning electron microscopic examination (Hospenthal 1995).
17.9.2 Molecular Detection
DNA-based techniques have recently been employed to identify the causative
agents of chromoblastomycosis (Vidal et al. 2004; Piepenbring et al. 2007;
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Chowdhary et al. 2008; Miyagi et al. 2008). PCR of the ITS and direct sequence
analysis of the amplicon, coupled with classical detection methods proved effective
in identification of the causative agent of chromoblastomycosis as Fonsecaea
pedrosoi (Miyagi et al. 2008). By means of 18S rDNA sequencing and GenBank
database homology searches, a rare case of chromoblastomycosis in a renal transplant recipient caused by a nonsporulating fungal isolate belonging to genus
Rhytidhysteron was successfully diagnosed (Chowdhary et al. 2008).
17.10
Fusarium spp.
Fusariosis is a life-threatening mycosis in immunocompromised hosts (Lionakis
and Kontoyiannis 2004). Fusarium spp. are angiotropic and angioinvasive molds
that produce hemorrhagic infarction and low tissue perfusion, resulting in tissue
necrosis (Lionakis and Kontoyiannis 2004). More than 50 species of Fusarium have
been identified but only a few are pathogenic in humans (Lionakis and Kontoyiannis 2004). These include F. solani (causes ~ 50% of cases), Fusarium oxysporum,
Fusarium moniliforme, Fusarium verticillioides, Fusarium dimerum, and Fusarium
proliferatum (Lionakis and Kontoyiannis 2004). In terms of global occurrence,
fusariosis is most common in the United States (50–80% of all fusariosis cases),
followed by France, Italy, and Brazil (Torres et al. 2003). Invasive fusariosis has
emerged in many tertiary-care cancer centers as the second most common invasive
mold infection (after invasive aspergillosis) in severely immunocompromised
patients (Lionakis and Kontoyiannis 2004). A steady rise in the number of cases
of fusariosis in hematopoietic stem cell transplant recipients has been observed
since the late 1980s (Nucci et al. 2004). More than 90% of cases of fusariosis have
been reported in neutropenic patients with hematologic malignancies (Lionakis and
Kontoyiannis 2004) and autologous bone marrow transplant recipients (Boutati and
Anaissie 1997). Because the clinical presentation of fusariosis is rather unspecific,
differentiation from invasive aspergillosis can be challenging (Torres et al. 2003;
Lionakis and Kontoyiannis 2004).
17.10.1
Laboratory Diagnosis
Fusarium spp. grow easily and rapidly in most mycological media. Although the
genus Fusarium can be identified by the production of hyaline, banana-shaped,
multicellular macroconidia with a foot cell at the base, interpretation of the growth
of Fusarium spp. from different biological materials depends on the clinical
context. The clinician and the microbiologist must be cautious, because Fusarium
spp. may contaminate laboratory specimens and pseudo-outbreaks of fusariosis
may occur (Grigis et al. 2000). In support of infection are the isolation of several
colonies from the same specimen or of the same fungus from different specimens of
the same patient, the site of isolation, and, most importantly, a positive direct
examination of the biological material. Histopathology is therefore recommended
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for a confirmatory diagnosis of fusariosis. In tissues, the hyphae of Fusarium are
similar to those of Aspergillus spp. (hyaline and septate filaments). However,
adventitious sporulation may be present in tissue, and the finding of both hyphae
and yeast-like structures is highly suggestive of fusariosis in the high-risk population. In the absence of microbial growth, distinguishing fusariosis from other
hyalohyphomycoses may be difficult and requires the use of molecular techniques.
17.10.2
Molecular Detection
A fluorescent-based PCR assay which allows rapid and reliable identification of five
toxigenic and pathogenic Fusarium spp., namely Fusarium avenaceum, F. culmorum, F. equiseti, F. Oxysporum, and F. sambucinum has been developed (Mishra
et al. 2003). This method is based on amplification of species-specific ITS using
fluorescent oligonucleotide primers, which were designed on sequence divergence
within the rDNA. Besides providing an accurate, reliable, and rapid identification of
these Fusarium spp., it reduces the potential for exposure to carcinogenic chemicals
as it substitutes ethidium bromide staining of amplicons with the use of fluorescent
dyes (Mishra et al. 2003). Molecular diagnosis of the toxigenic Fusarium spp. has
recently been developed in a PCR assays for genes involved in the toxin biosynthesis (Mulè et al. 2005). The method allows early detection of toxin-producing
Fusarium spp, and reveals which particular toxin may be present in a feed product
(Mulè et al. 2005). A DNA microarray was assembled to detect and identify DNA
from 14 fungal pathogens including F. oxysporum and F. solani in blood, BAL, and
tissue samples from high-risk patients. The assay combines multiplex PCR and
consecutive DNA microarray hybridization. PCR primers and capture probes were
derived from unique sequences of the 18S, 5.8S, and ITS1 regions of the fungal
rRNA genes. Hybridization with genomic DNA of fungal species resulted in
species-specific hybridization patterns (Spiess et al. 2007).
17.11
Histoplasma capsulatum
H. capsulatum is a dimorphic fungus that, although worldwide distributed, is more
prevalent in certain regions of north and central America (Wheat and Kauffman
2003). Manifestations of histoplasmosis range from asymptomatic to severe and
fatal disease, depending on the immune status and the magnitude of exposure
(Wheat and Kauffman 2003). Disseminated disease occurs in approximately 10%
of all infections (Wheat and Kauffman 2003). CNS involvement is the presenting
manifestation in 5–10% of disseminated disease cases (Wheat and Kauffman 2003).
Although histoplasmosis is relatively uncommon among transplant patients, outbreaks of the disease have been reported in transplant centers with incidence rates
of ca. 2% (Freifeld et al. 2005). While immunocompetent adults with disseminated
histoplasmosis typically have a chronic progressive course of the disease, those
who are severely immunosuppressed can have an acute course with fatal outcome.
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17.11.1
391
Laboratory Diagnosis
Since the clinical picture of histoplasmosis strongly mimics those of tuberculosis
and some other lung diseases, it is not possible to confirm a diagnosis of pulmonary
histoplasmosis on the sole basis of the clinical symptoms (Bracca et al. 2003).
Confirmatory diagnosis requires culture, fungal stain of tissue or body fluids, and
tests for antibodies and antigens, depending on the extent and severity of infection
(Wheat 2003).
Microscopic identification of Histoplasma in May-Grünwald-Giemsa-stained
slides is an acceptable approach, but an experienced operator is needed to obtain
reliable results. The fungus can be cultured from different clinical samples such as
blood, bone marrow, respiratory secretions, or localized skin lesions (Wheat 2003).
Isolation of the organism from cultures provides the strongest evidence for infection with H. capsulatum, but has some limitations. First, growth of H. capsulatum in
culture is slow, requiring up to 4 weeks, causing undesirable delay in the diagnosis
and therapy. Second, invasive procedures might be required to obtain specimens for
culture. Bone marrow cultures yield the highest frequency of positive isolations
(70–90%), while respiratory specimens yield positive results less frequently
(50–90%). Third, cultures are negative in most patients with mild forms of histoplasmosis, limiting its use for diagnosis in mild cases. Cultures are positive
primarily in patients with disseminated or chronic pulmonary histoplasmosis, but
even in these patients cultures can be falsely negative in about 20% of disseminated
histoplasmosis and 50% of chronic pulmonary diseases (Wheat 2003). Serological
methods are faster than culture, but they can lead to false-positive results because
the titer of specific antibodies against Histoplasma remains high for months or
years after the primary infection (Bullok 1995). In addition, cross-reactivity against
P. brasiliensis can give false positive results (Raman et al. 1990). On the other
hand, false-negative results due to low antibody titers can be observed in immunocompromised patients with active infection (Wheat et al. 1992). An alternative is
the detection of H. capsulatum antigen in body fluids (Gomez et al. 1997). Although
this method is more sensitive than serum antibody detection assays, cross-reactivity
against antigens of other pathogenic fungi remains a problem (Wheat et al. 2002).
17.11.2
Molecular Detection
A variety of PCR and DNA probes have been applied to the detection of
H. capsulatum DNA in tissues and body fluids (Sandhu et al. 1995; Bialek et al.
2005a; Rickerts et al. 2002; Bracca et al. 2003; Martagon-Villamil et al. 2003). A
seminested PCR for the diagnosis of histoplasmosis that amplifies a portion of the
H. capsulatum H antigen gene has been developed. This assay is sensitive and
specific, being able to detect genomic material corresponding to less than ten yeast
cells without cross-reaction against other bacterial or fungal pathogens (Bracca
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L. Putignani et al.
et al. 2003). The real-time PCR assay for H. capsulatum can be used for the confirmation of culture isolates suspected to be H. capsulatum, and potentially to test clinical
specimens directly (Martagon-Villamil et al. 2003). A rep-PCR assay, targeting
multiple noncoding, repetitive sequences (generally 30–500 bp) interspersed throughout the fungal genome, was exploited to differentiate isolates of H. capsulatum,
according to the procedure previously described for B. dermatitidis (Pounder et al.
2006) (Table 17.3).
17.12
Trichosporon spp.
Trichosporonosis is a relatively uncommon opportunistic fungal infection in
immunocompromised individuals, often resulting in fatal outcome (Girmenia
et al. 2005). The taxonomy of the yeasts that causes trichosporonosis has recently
been revised. It is now widely accepted that the previously named T. beigelii
consists actually of six species: Trichosporon asahii, Trichosporon asteroides,
Trichosporon cutaneum, Trichosporon inkin, Trichosporon mucoides, and Trichosporon ovoides. Geotrichum capitatum, originally included in genus Trichosporon, has been classified as Blastoschizomyces capitatus, whose Dipodascus
capitatus is the teleomorph stage. B. capitatus is also a common cause of
trichosporonosis (Girmenia et al. 2005) and has recently been characterized as
an outbreak agent (Ersoz et al. 2004). Case reports of invasive trichosporonosis
have frequently been reported, and Trichosporon and Blastoschizomyces are
currently considered the second most common yeasts causing disseminated infections after Candida spp. (Chagas-Neto et al. 2008). Trichosporonosis is an acute,
febrile, severe infection with dissemination to multiple deep organs, associated
with up to 64% mortality (Chagas-Neto et al. 2008). While any immunocompromised patient can develop trichosporonosis, the risk is highest for those with
hematologic malignancies, followed by neutropenia, peritoneal dialysis, solid
tumor, SOT, burns, and prosthetic cardiac valve (Girmenia et al. 2005). Incidence
rates of 0.4% and 0.5%, respectively, for infections due to Trichosporon spp. and
G. capitatum have been reported in patients with leukemia (Girmenia et al. 2005).
Trichosporon spp. are resistant to echinocandins, as demonstrated by breakthrough trichosporonosis in immunocompromised patients treated with caspofungin or micafungin (Cornely 2008). Trichosporon infection should be suspected in
immunocompromised patients who are being treated with echinocandins and
develop signs of septicemia or local infection.
17.12.1
Laboratory Diagnosis
A firm diagnosis of deep-seated trichosporonosis should result from histological
examination of tissue samples obtained by biopsy and culture of living Trichosporon cells. However, invasive examinations, such as biopsy, cannot repeatedly be
17
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393
performed in patients with severe underlying diseases, and even though the detection of causative fungi in the blood is clinically valuable, the results of blood
cultures usually become available after a long time. Patients with disseminated
trichosporonosis may test positive for the GXM antigen (Melcher et al. 1991) or
(1 ! 3)-b-D-glucan (Miyazaki et al. 1995a, b). However, patients with other
mycoses also test positive in these assays, and therefore the specificity of these
tests is unsatisfactory (Miyazaki et al. 1995a, b).
17.12.2
Molecular Detection
Sugita et al. (1999) developed an accurate identification system for all the species in
the genus Trichosporon, including the six medically relevant species, based on
comparative sequence analysis of the ITS regions. Furthermore, the same authors
described a nested PCR assay for species-specific detection of T. asahii, which is
the major causative agent for deep-seated infection (Sugita et al. 2001) (Table 17.3).
Recently, DNA-based procedures for the identification of Trichosporon have been
stepped up by the sequence analysis of the rRNA ITS1, which better distinguishes
between sibling species (Table 17.3). Quantification of Trichosporon spp. in clinical samples is of great clinical significance. A quantitative real-time PCR assay to
detect T. asahii DNA from the blood sample of thichosporonosis patients was
recently developed (Mekha et al. 2007). The specific primer/probe system was
capable of detecting T. asahii DNA in all samples from trichosporonosis patients,
showing higher sensitivity than polysaccharide antigen detection (Table 17.3).
17.13
Zygomycetes
Zygomycosis is an increasingly important IFI caused by emerging pathogens
belonging to the Zygomycetes class, which can be subdivided into two
orders: Mucorales and Entomophthorales (Ribes et al. 2000). The most common
species of Mucorales causing angioinvasive zygomycosis are Rhizopus arrhizus
(syn. Rhizopus oryzae), Rhizopus microsporus var. rhizopodiformis, and Rhizomucor pusillus. Other causative species include Absidia corymbifera, Mucor spp., and
Cunninghamella bertholletiae (Chayakulkeeree et al. 2006). Human disease is most
commonly caused by Mucorales, which are characterized by rapidly evolving
course, tissue destruction, and invasion of blood vessels (Chayakulkeeree et al.
2006). Mycoses caused by Entomophthorales are more indolent and chronically
progressive (Chayakulkeeree et al. 2006). The most common types of infection are
sinus, pulmonary, and cutaneous; disseminated disease is reported in approximately
one-fourth of patients (Roden et al. 2005). Iron overload predisposes to zygomycosis (Gonzalez et al. 2002). Mucorales are distributed worldwide, while Entomophthorales are generally limited to the tropics and subtropics (Gonzalez et al.
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L. Putignani et al.
2002). Notably, there has been a steady increase in reported cases of zygomycosis
over the last 60 years (Roden et al. 2005). Diabetic patients, particularly those
with ketoacidosis, are highly susceptible to zygomycosis (Chayakulkeeree et al.
2006). Other risk factors are neutropenia, corticosteroid use, HSCT, SOT, HIV,
drug use, skin or soft tissue breakdown (e.g., burn, traumatic inoculation, surgical
wounds), prematurity, malnourishment, malignancy, and long-term prophylaxis
with voriconazole.
17.13.1
Laboratory Diagnosis
The traditional diagnosis of zygomycosis is based upon identification of broad,
ribbon-like, pauciseptate hyphae by histopathology, or the use of macroscopic and
microscopic morphology analysis following fungal culture (Gonzalez et al. 2002).
Histopathology determinations suffer from subjectivity that is dependent upon the
experience of the reader. In addition, tissue processing, fixation, and staining may
require several days (Frater et al. 2001). When culture is used, the distinctive hyphal
elements of zygomycetes are difficult to distinguish from those of other filamentous
fungi, especially at early growth stages. Although the zygomycetes grow quite
rapidly on solid media, sporulation and identification may still take several days. In
addition, when a zygomycetous infection is not specifically suspected at the time of
specimen submission, tissues may undergo extensive processing prior to culture,
which ruptures the pauciseptate hyphae. It is therefore not unusual to have negative
fungal culture results when histopathology results suggest the presence of zygomycosis (Kontoyiannis et al. 2000).
17.13.2
Molecular Detection
DNA-based molecular techniques have an enormous potential for rapidly and
accurately identifying the agents of zygomycoses. A molecular approach for the
detection of Zygomycete molds may increase sensitivity and rapid diagnosis,
resulting in earlier, directed therapy. Several reports describe utilization of universal fungal primers from the 18S rDNA or the ITS region for PCR amplification,
followed by amplicon sequencing (Kobayashi et al. 2004; Schwarz et al. 2006) or
hybridization to specific probes (Einsele et al. 1997, Rickerts et al. 2001). Also a
seminested PCR assay targeting the 18S rDNA of Zygomycetes, followed by
sequencing of the amplified product has been developed, providing sufficient
sensitivity for fungal detection in paraffin-embedded tissues (Bialek et al. 2005a)
(Table 17.3). A multiplex PCR method designed to yield different sized PCR
products from the ITS region, whose length and combination correlates with four
Rhizopus spp., provided detection of DNA from paraffin-embedded tissues and
blood taken from a single patient (Nagao et al. 2005). Another assay uses a mixture
of four genus-specific sense primers coupled with one degenerate antisense primer
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395
from the 18S rDNA to detect the four major genera within the Mucorales. RFLP of
the amplicon makes possible species-level identification (Machouart et al. 2006).
Kontoyiannis et al. (2005) used sequence-based identification to characterize the
distribution of the various genera among clinical isolates of Zygomycetes. ITS
sequencing identified the genus in almost all of their isolates (Kontoyiannis et al.
2005). They also showed that the results of ITS sequencing were > 20% discordant
with those of morphological identification, and that most of the morphologically
misidentified Zygomycetes isolates belonged to Rhizopus spp. (Kontoyiannis et al.
2005). More recent studies reported the use of real-time PCR assays for detection
of infections caused by Zygomycetes. One study utilized a conserved region of
the zygomycete cytochrome b gene as target (Hata et al. 2008). The second study
was aimed at identifying the most common species of Zygomycetes causing
human disease, using the 28S rRNA gene as target. The first assay (qPCR-1) detects
Rhizopus, Mucor, and Rhizomucor spp. and the second assay (qPCR-2) detects
Cunninghamella spp. Both assays utilize fluorescence resonance energy transfer
(FRET) hybridization probes for detection of species within the genera (Kasai et al.
2008).
17.14
Dermatophytes
The dermatophytes are a group of closely related fungi that have the ability to
invade the stratum corneum of the epidermis and keratinized tissues (keratinophilic
fungi), such as the skin, nail, and hair of humans and animals. Many dermatophytes
are saprophytic soil fungi (geophilic), without any pathogenic feature for humans
and animals and other only animals (zoophilic). Because zoophilic dermatophytes,
through zoonotic transmission, infect humans only rarely and geophilic dermatophytes are infrequent cause of human disease, we will mainly focus on anthropophilic dermatophytes. These fungi cause dermathophytoses at most skin sites,
although the feet, groin, scalp, and nails are most commonly affected. There are
three genera of pathogenic anthropophilic dermatophytes, Trichophyton, Microsporum, and Epidermophyton. The last genus is represented by the single species
Epidermophyton floccosum. Most of the 39 dermatophyte species are parasitic,
causing disease in either humans and animals with mechanisms of narrow host
range of adaptation (Hay 1995). The taxonomy of these fungi is complicated by the
fact that most clinical isolates are imperfect fungi, organisms that do not produce
sexual structures in culture. It is important for these fungi the strain differentiation
within the same species to understand spreading of infections and relapse, quite
frequent after apparently successful treatment (Abdel-Rahman 2008). Anthropophilic dermatophytes are the most common cause of human dermatophytosis
(generally referred as ringworm or tinea corporis) as well as tinea pedis or
tinea cruris, all of them belonging to the so-called superficial fungal infections
(Kanbe 2008). Dermatomycoses are generally restricted to the cutaneous and the
nonliving corneum layers due to host defense responses to the invading fungi in
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L. Putignani et al.
immunopotent individuals (Ogawa et al. 1998). In immunocompromised individuals, infection may progress to deep cutaneous and subcutaneous sites (Kanbe
2008). Dermatophytes are the most common causes of skin disease in tropical
countries. Trichophyton rubrum is probably the most prevalent agent of dermatophytosis throughout the world (Veer et al. 2007).
17.14.1
Laboratory Diagnosis
The morphological similarity, variability, and polymorphism of dermatophytes
have meant that species identification for dermatophytes is time consuming and
requires significant expertise. Furthermore, the application of chemotherapy has
also contributed to the occasional modification and alteration of the morphological
features of dermatophytes, resulting in atypical colonial growth and appearance and
complicating laboratory identification procedures based on phenotypic features.
17.14.2
Molecular Detection
Molecular analyzes of dermatophyte genomes would clear several problems in the
traditional morphology-based taxonomy (Kanbe 2008). With these expectations,
many investigators have focused their research on the nucleic acids of dermatophytes. The G + C content of chromosomal DNA isolated from species belonging
to genera, Trichophyton, Microsporum, and Epidermophyton is 48.7–50.3%, a
narrow range when compared with the 48–61% range reported in the single genus
Aspergillus. This indicates a genetic homogeneity among dermatophytes as opposite to their phenotypic and ecological variation (Davidson et al. 1980). Subsequently many investigators have focused on mitochondrial DNA (mtDNA) and
rDNA of dermatophytes to determine the phylogenetic relationships among dermatophytic species. These data have widely contributed to the development of molecular techniques for the identification and epidemiology of dermatophytes, as
reviewed by Kanbe (2008), Blanz et al. (2000) and Kac (2000). PCR and PCRRFLP-based techniques made it possible to identify dermatophytes to species level,
and to discriminate between isolates at the strain level (Makimura et al. 1999;
Gräser et al. 2000; Liu et al. 2002). DNA samples obtained from fungal cultures or
clinical specimens can be amplified by three primer sets targeting the 18S rDNA
and ITS regions (TR1/TR2 and B2F/B4R for 18S rDNA and ITS1/ITS2 for ITS
regions), yielding species-specific products from the ITS regions of Trichophyton,
Microsporum, or Candida species (Turin et al. 2000). PCR-RFLP targeting both the
ITS and NTS regions provides a valuable tool for species identification of dermatophytes (Jackson et al. 1999). The ITS is amplified with a universal primer set for
17 common dermatophyte species, and further RFLP with MvaI allows to discriminate between the majority of the dermatophytes at the species level, except for
the sibling species of T. rubrum/Trichophyton soudanense and Trichophyton
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quinkeanum/Trichophyton schoenlenii. On the basis of RFLP profiles of the NTS
region, T. rubrum can be subdivided into 14 types (Jackson et al. 1999). Similarly,
Mochizuki et al. (2003) described the identification of T. tonsurans by PCR-RFLP
targeting the ITS region, and MvaI or HinfI digestion. The RFLP profile obtained
with MvaI was distinctive of T. tonsurans and different from that of other dermatophyte species (Mochizuki et al. 2003). Recently, Yoshida et al. (2006) reported on
a PCR-based identification of T. tonsurans, in which the T. tonsurans genomic
DNA was amplified by primers specific to the ITS1 region of this fungus. This
method was able to discriminate T. tonsurans from other fungal species involved in
dermatophytosis using only a single PCR amplification step (Yoshida et al. 2006).
Real-time PCR with LightCycler has been combined with RFLP for the rapid
detection/identification of isolates of dermatophytes and other pathogenic fungi in
clinical specimens. Dermatophytes were distinguished from nondermatophytes
using the LightCycler melting points. However, restriction enzyme digestion of
the PCR product was necessary for discrimination between dermatophyte species
(Gutzmer et al. 2006). Some other genes such as chitin synthase I gene (CHS1) or
DNA topoisomerase II gene (TOP2) have also been used as a target for species
identification of dermatophytes (Kano et al. 1999; Kanbe et al. 2003).
17.15
Conclusion and Perspectives
Phenotype-based mycological diagnosis relying upon conventional microbiology
and histopathology is time consuming, labor intensive, and often does not warrant
sufficient sensitivity and specificity. Phenotype-based identification intrinsically
suffers from the variable nature of phenotypic characteristics, which are influenced
by culture conditions and subjective interpretation. These issues pose the need,
among clinical mycologists, for faster, easier, and more proficient diagnostic tools
for fungal infections. DNA-based methods have largely satisfied these needs
because of their objective nature, rapidity, broad range of detection (panfungal
tests), applicability to a variety of specimen types, capability to provide results that
are unaffected by growth conditions, and high discriminatory power, thereby
ensuring identification of fungi that would be indistinguishable according to phenotypic traits.
Our review of the current literature on DNA-based methods for fungal identification has highlighted the utility of such methods in clinical practice. In many
instances, the simple PCR and sequencing of conserved regions of the fungal
genome provides species-level identification with reasonable confidence for both
molds and yeasts, including those species which escape identification by conventional techniques or commercially available kits. Furthermore, molecular assays are
becoming the only suitable diagnostic approach to early detection of fungal cells
(i.e., of their DNA) at low infecting concentrations and in the absence of serological
evidence, as in case of immunocompromised patients (White et al. 2006; Badiee
et al. 2009). Early diagnosis will allow clinicians to combat fungal infection at an
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early stage through choice-specific and effective treatment, avoiding empirical
therapy and development of resistance to antimycotic drugs. In this scenario, it is
expected that ongoing progress in molecular biology will continue to have a
positive impact on medical mycology.
There are many issues, however, that need to be addressed in the future. First, the
direct identification of fungal DNA extracted from pathological samples still poses
some problem, and most molecular identification methods require preliminary
isolation fungi as pure cultures. Second, the percentage of sequence homology
required to define fungal species or genera should be clearly established by the
scientific community for the main phylogenetic markers, e.g., the rRNA genes.
Third, interrogation of public databases of rRNA genes can provide dubious
identities because of the presence of uncontrolled entries. If fungal cultures are
unavailable, uncertain, or spurious, DNA-based identifications cannot be verified
through appropriate phenotypic testing, and the molecular epidemiology of infectious fungi will be difficult to trace. Fourth, the reliability of the current DNA-based
identification assays ought to be assessed in the coming years with well-designed
prospective studies and regular quality controls. Rigorous testing of molecular
assays for the diagnosis of fungal disease through multicenter proficiency studies
and external validation from certifying institutions (e.g., USFDA) will be unavoidable steps. Lastly, the clinical meaning of a positive PCR should be test interpreted
in the light of our knowledge of the clearance kinetics of fungal DNA in the infected
patient; this would help in distinguishing between colonized individuals and
infected patients.
Simplification and/or standardization of methods for DNA extraction and detection are likely to facilitate the introduction of molecular technology to routine
clinical laboratories (De Marco et al. 2007). But technical problems still need to
be solved, primarily the risk of contamination. Nonetheless, the approach of using
primers that target multicopy genes is likely to provide the high degrees of
sensitivity that are needed for initial diagnosis of severe fungal infection.
Automated DNA extraction, real-time PCR techniques, and the development of
controlled sequence databases are likely to improve reliability of the current DNAbased identification assays. The usage of close real-time PCR systems (e.g., Light
Cycler SeptiFast) in the current diagnostic protocols and the development of
repPCR-based methods (e.g., DiversiLab) for further routine evaluation are partly
overcoming contamination issues. At the same time, these commercial systems
provide ready-to-use instruments and reagents that render molecular diagnosis
affordable even in non specialized laboratories. New advanced molecular
approaches based on mass spectrometry (e.g., MALDI-ToF, Matrix-assisted laser
description ionization-time of flight-mass spectrometry) are currently under setting
for the rapid detection and identification of fungi in clinical microbiology laboratories. They could open new horizons for the fast and reliable management of
fungal infections in high risk patients.
Acknowledgments This work was supported by Grants from: Ricerca Corrente, Bambino Gesù
Hospital Health Care and Research Institute RC 200702P002153 to L.P.; Ricerca Corrente 2008,
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399
INMI “Lazzaro Spallanzani” to P.V.; ISPESL, Ricerca Finalizzata PMS/40/06 to P.V. We
acknowledge with great respect the work of very many researchers that has contributed to improve
molecular diagnosis of mycoses, and that for reasons of space we were not able to directly
reference here.
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Chapter 18
Applications of Loop-Mediated Isothermal
Amplificaton Methods (LAMP) for Identification
and Diagnosis of Mycotic Diseases:
Paracoccidioidomycosis and Ochroconis
gallopava infection
Ayako Sano and Eiko Nakagawa Itano
Abstract Loop-mediated isothermal amplification (LAMP) methods are now useful for the detection of a specific gene in infectious diseases, genetic diseases, and/
or genetic disorders in the large number of medical fields, and it was recently
introduced to fungal investigation. It is characterized by the use of four different
primers specifically designed to recognize six distinct regions of the target gene,
and the reaction process proceeds at a constant temperature using strand displacement reaction. Quickness and simplicity is the advantage of the method. Amplification and detection of gene can be completed in a single step, by incubating the
mixture of samples, primers, DNA polymerase with strand displacement activity
and substrates at a constant temperature. The method was applied to two fungal
infections; paracoccidioidomycosis (PCM), a deep mycosis caused by Paracoccidioides brasiliensis and Ochroconis gallopava infection. For PCM a combination
of F3, B3, FIP, and BIP primers designed from the partial sequence of P. brasiliensis gp43 gene was used. The PCR products amplified by the primer set; F3 and
B3 showed species specificity for P. brasiliensis and the detection limit of the PCR
was 100 fg of fungal genomic DNA. The specific DNA banding pattern of P. brasiliensis was detected in the clinical and nine-banded armadillo derived isolates,
paraffin-embedded tissue sample or sputum from PCM patient. LAMP method was
used also for the identification of O. gallopava by using species-specific primer sets
based on the D1/D2 domain of the LSU rDNA sequence. The method successfully
detected the gene from both fungal DNA derived from brains and spleens of
A. Sano
Medical Mycology Research Center, Chiba University, 1-8-1, Inohana, Chuo-ku, 260-8673
Chiba, Japan
e-mail: aya1@faculty.chiba-u.jp
E.N. Itano
Department of Pathological Science, CCB, State University of Londrina, P.O. Box 6001,
86051-970 Londrina, Paraná, Brazil
e-mail: itanoeiko@hotmail.com
Y. Gherbawy and K. Voigt (eds.), Molecular Identification of Fungi,
DOI 10.1007/978-3-642-05042-8_18, # Springer-Verlag Berlin Heidelberg 2010
417
418
A. Sano and E.N. Itano
experimentally-infected mice with O. gallopava and environmental isolates. In
conclusion, LAMP method for PCM and O. gallopava seemed to be useful for
identification, diagnosis or retrospective study with advantage in the quickness and
simplicity procedure, but require strictly-controlled environments.
18.1
Introduction
The gold standard for diagnosis of fungal infections is detection, isolation and
identification of the patogenic fungi from clinical specimen; such as skin scrapings,
hair and nail, mouth and vaginal swabs, blood, cerebrospinal fluid, urine, sputa and
respiratory tract secretion, pus, ocular specimen, and organ biopsy. However, there
are many complicated problems in clinical laboratories.
First of all, the most important procedure is avoiding laboratory infections
caused by highly pathogenic fungal species, such as Coccidioides immitis,
C. posadasii, Histoplasma capsulatum, Blastomyces dermatitidis, Paracoccidioides brasiliensis and Penicillium marneffei. In general, highly pathogenic
fungal species are not recommended to isolate clinical laboratories in general
(Larone 1995). Furthermore, a fungal infection, caused by Ochroconis gallopava,
which requires to be differentiated from highly pathogenic bird flu or SARS
(Ohori et al. 2006), is also recommended to diagnose without culturing to avoid
the viral laboratorial infections.
The lower rate of isolation of the causative agents seems to be caused by short
incubation periods for the isolation of fungi from clinical material. Visualization
of fungal sprouts from clinical materials takes a longer time than those of bacteria.
It takes at least 48 h in pathogenic yeasts, 4–7 days in common pathogenic
filamentous fungi; dermatophytes, Aspergillus spp., zygomycetes, and others,
almost 10–14 days in dematiaceous fungi, and 3 weeks or more in particular fungal
species, especially P. brasiliensis, of course, it should not try to isolate in general
laboratories. But most laboratories could not keep incubating more than 1 week.
Therefore, the isolation rate of filamentous fungal pathogens seems to be very low
compared to pathogenic yeasts.
Followed by difficulties in isolations of fungal pathogens, there is a serious
problem with identification. Expert skills for identification based on morphological
and physiological characteristics are strongly required. The procedures are highly
time-consuming to prepare photogenic samples and to evaluate special morphologiclal and physiological characteristics (Ohori et al. 2006). Furthermore, clinical
isolates sometimes lacked characteristic appearances such as textures and colors of
colonies, conidiogenesis, mating and physiological abilities (Uno et al. 2001).
Diagnosis for fungal infections is able to be confirmed on the basis of combinations of clinical findings, diagnositic imagings, serological tests, immunological
18
Applications of Loop-Mediated Isothermal Amplificaton Methods
419
tests, cytological and histopathological findings without the fungal isolate (Ishikawa
et al. 2008).
Detections of 1.3-beta-D-glucan, galactomannan, and D-arabinitol from sera are
faster than other methods, and are also useful for diagnosis of some fungal infections (Christensson et al. 1999; Kelaher 2006), however, it is impossible to estimate
the species of the causative agent.
Isolation and identification, and detection of a species-specific gene by molecular biological methods from clinical materials are able to confirm the causative
agent in the species level (Borman et al. 2008).
Following the developments of molecular biological techniques in these two
decades, molecular biological data for identification of fungal species based on
ribosomal DNA (rDNA) sequences became common, such as for P. brasiliensis
identification (Motoyama et al. 2000). Although internal transcribed spacer 1 region
of rDNA sequence (ITS 1 rDNA) is treated as a barcode gene for identification and
taxonomical classification of fungi (Druzhinina 2005), there were some difficulty to
confirm the fungal species based on the gene sequences. Therefore, selection of
species-specific genes, beside the ITS 1 rDNA may add value to targets.
Detections of species-specific genes derived from causative agents in clinical
materials by polymerase chain reactions (PCR) have been reported in many
mycotic diseases (Reiss et al. 2000; Balajee et al. 2007). But, it still takes at least
several hours to obtain the results and sometimes should be requested to confirm the
sequences of the amplified genes. Therefore, rapid and accurate diagnostic methods
based on molecular biolgical techniques have been waited for.
Notomi et al. in 2000 reported a new method, the so called loop-mediated
isothermal amplification (LAMP) method to detect specific gene from a DNA
virus within a few hours. The method has been applied in the field of microbiology
for detection and identification of Mycobacterium sp. (Iwamoto et al. 2003),
hepatitis B virus (Nagamine and Watanabe 2001; Nagamine et al. 2002), highly
pathogenic bird flu (Imai et al. 2007) and many other pathogens reaching to more
than 200 reports up to the end of November 2008.
On the other hand, the technique has not been successful in applying fungal
infections. Personal communications suggested that the LAMP methods are useful
for opportunistic fungal infection in the early times; however, our opinion is that the
LAMP methods for Candida spp., Aspergillus spp., and other opportunistic fungal
species may not be reliable because of the difficulties to judge the real pathogen or
environmental contaminant. We would like to suggest that the application of the
LAMP methods to mycotic diseases should be limited to the highly pathogenic
fungal species out of endemic areas, and/or to rare species, for example Cryptococcus gattii (Lucas et al. 2009), although a LAMP method for identification of
Candida spp. was reported by Inácio et al (2008).
The present chapter describes the principle of LAMP method, detections of
specific gene from P. brasiliensis categorized as one of the highly pathogenic
fungi (Endo et al. 2004), and of O. gallopava required to be differentiated from
highly pathogenic bird flu or SARS (Ohori et al. 2006).
420
A. Sano and E.N. Itano
FIP
5’ F1c F2
3’
F3
3’
F3 Primer 5’
F3c F2c F1c Targer DNA B1 B2 B3
3’
5’
5’
3’
B1c B2c B3c
F3 F2 F1
5’
3’
B3 B3 primer
3’
B2
5’
B1c
BIP
Fig. 18.1 Design 4 types of primers based on the following six distinct regions of the target gene:
the F3c, F2c and F1c regions at the 30 side and the B1, B2 and B3 regions at the 50 side. FIP:
Forward Inner Primer (FIP) consists of the F2 region (at the 30 end) that is complementary to the
F2c region, and the same sequence as the F1c region at the 50 end. F3 Primer: Forward Outer
Primer consists of the F3 region that is complementary to the F3c region. BIP: Backward Inner
Primer (BIP) consists of the B2 region (at the 30 end) that is complementary to the B2c region,
and the same sequence as the B1c region at the 50 end. B3 Primer: Backward Outer Primer consists
of the B3 region that is complementary to the B3c region (http://loopamp.eiken.co.jp/e/lamp/
primer.html)
18.2
The Principle of LAMP Method
18.2.1 About LAMP Method (http://loopamp.eiken.co.jp/e/
lamp/index.html)
LAMP method which stands for LAMP is a simple, rapid, specific and cost-effective
nucleic acid amplification method solely developed by Eiken Chemical Co., Ltd. It
is characterized by the use of four different primers specifically designed to recognize six distinct regions on the target gene and the reaction process that proceeds at a
constant temperature using strand displacement reaction (Fig. 18.1).
Amplification and detection of genes can be completed in a single step, by
incubating the mixture of samples, primers, DNA polymerase with strand displacement activity and substrates at a constant temperature (about 65 C). It provides high
amplification efficiency, with DNA being amplified 109–1010 times in 15–60 min.
Because of its high specificity, the presence of amplified product can indicate the
presence of the target gene.
18.2.2 Primers
LAMP method uses four primer sets; F3, B3, FIP and BIP selected from six distinct
regions of the target gene (http://loopamp.eiken.co.jp/e/lamp/primer.html). The
most important primer set is F3 and B3. The primers should be selected from
specific genes or gene sequences based on species specific PCR and confirmed after
18
Applications of Loop-Mediated Isothermal Amplificaton Methods
421
testing with intra species diversity and a huge numbers of related pathogenic fungal
species.
Therefore, enormous numbers of trials and errors are latent until the final primers
are confirmed. Furthermore, the primers should completely differentiate the fungal
genes from host ones.
Although, special software to design LAMP primers- PrimerExplore is available
in the website (http://primerexplorer.jp/e/), it seemed to be useful as reference hints
for base composition, GC contents, secondary structures and Tm value on designing
primers based on our experience.
18.2.3 Basic Principle
The target gene (DNA template as example) and the reagents are incubated at a
constant temperature between 60–65 C. The reaction steps are available at the
website (http://loopamp.eiken.co.jp/e/lamp/principle.html).
18.2.4 Cautions
LAMP method is highly sensitive. We experienced many faults of contamination of
the genes. Once contamination of the target gene occurs, all reactions become
positive, even in a negative control using distilled water as a template. Therefore,
extremely careful procedures are requested. Reagents, pipets, plastic pipet tips,
safety cabinet, and hands. The samples should be handled separately from the
reagents. The positive control for the target gene should be done separately.
This is one of the reasons why some fungal species common in normal human
flora or in environments are not recommended to use the LAMP method. Selection
of the target fungal species is also important. The fungal species should be rare in
laboratorial environment.
18.3
Applications of LAMP Method for Identifications
of P. brasiliensis and or/Diagnosis for
Paracoccidioidomycosis (PCM)
18.3.1 Backgrounds for P. brasiliensis
P. brasiliensis is considered to belong to the family Onygenaceae (Order Onygenales, Ascomycota), in the same group as Blastomyces dermatitidis, Coccidioides
immitis, Histoplasma capsulatum, and Lacazia loboi (Bagagli et al. 2008). The
422
A. Sano and E.N. Itano
fungal species is treated as one of the highly pahogenic fungi categorized as
biosafety level 3 as the same as C. immitis, C. posadasii, H. capsulatum, B.
dermatitidis and Penicillium marneffei (Kamei et al. 2003) On the other hand, the
identification and diagnosis of the above fungal infections with nonculture method
seems to be very important to avoid laboratory infection (Kamei et al. 2003,
Umeyama et al. 2006).
P. brasiliensis is the causative agent for paracoccidioidomycosis (PCM) endemic
in Latin American countries. This fungus invades the lungs, lymph nodes, skin,
mucosa, liver, spleen and various other organs of humans and dogs. In humans, the
disease is characterized by two clinical forms: the acute or juvenile form (AF) and
more frequently chronic or adult form (CF). The AF is prevalent in children and
young people and presents a more severe and rapid clinical evolution with the
involvement of multiple organs and adenomegaly, hepatosplenomegaly, digestive
disorders, osteo-articular involvement and muco-cutaneous lesions. The CF occurs
mainly in adult males and has multiple forms, ranging from benign and localized
(unifocal) to severe and disseminated (multifocal) disease that involves skin,
mucous membranes, pulmonary and lymph node manifestations (Restrepo 1985;
Franco 1987; Kwon-Chung and Bennett 1992; Brummer et al. 1993; Ono et al.
2003; Ricci et al. 2004).
The probable natural habitat of P. brasiliensis is soil as saprophytic form. In fact,
isolations from soil or soil related products, from the feces of both frugivorous bats
(Artibeus lituratus) and a penguin (Pygoscelis adeliae) were reported. Interestingly,
the natural reservoir of P. brasiliensis seems to be the nine-banded armadillo
(Dasypus novemcinctus) because of repeated isolation of the fungal species from
various endemic areas of paracoccidioidomycosis with high incidences showing, as
the same genetic profiles as clinical isolates. Furthermore, detection of P. brasiliensis gene from the internal organs of wild animals that died in traffic accidents;
guinea pig (Cavia aperea), porcupine (Sphiggurus spinosus), grison (Gallictis
vittata) and raccoon (Procyon cancrivoros) suggested that the mycosis invades
not only humans but also many mammal species, and is one of zoonotic mycosis
(Bagagli et al. 2008).
The characteristics of P. brasiliensis is temperature-dependent dimorphism; a
mycelial form at ambient temperature, and multiple budding yeast form in host
tissue or at temperatures above 35–37 C in certain culture media (Restrepo 1985;
Franco 1987; Franco et al. 1989; Kwon-Chung and Bennett 1992; Brummer et al.
1993). (Fig. 18.2).
The important characteristics of P. brasiliensis are a multiple-nuclei microorganism (Imai et al. 2000), and a haploid microorganism except for gp43, encoding
the major antigen of P. brasiliensis; 43 kDa glycoprotein appeared as only one
allele (Almeida et al. 2007). The mature or during maturation of yeast cells that
have multiple nuclei, suggested that any P. brasiliensis gene may easily be amplified because of multiple copies at least. It suggested that selection of the target gene
is free from sticking on ribosomal RNA genes having tandem repeats (Kobayashi
2006) from clinical materials.
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Applications of Loop-Mediated Isothermal Amplificaton Methods
423
Fig. 18.2 (a) Upper; colony
of P. brasiliensis cultured on
Sabouraud dextrose agar
plate, lower; on potato
dextrose agar plate at 25 C
for 8 weeks, (b) cerebriform
yeast-like colony on 1%
dextrose added brain heart
infusion agar slant cultured at
35 C for 7 days (left; ninebanded armadillo derived
isolate, right; clinical isolate),
(c) whip wheel like
appearance in a infected
lymphonode tissue (Dr.
Nakajima Y, Matsushita
Memorial Hospital, Osaka,
Japan), (d) aleurioconidia
cultured on potato dextrose
agar at 25 C for 8 weeks, (e)
clamydospores cultured on
potato dextrose agar at 25 C
for 8 weeks, (f) mycelial to
yeast form conversion
process cultured on potato
dextrose agar at 25 C for
2 weeks and cultured at 35 C
for 3 days, (g) multiple
budding yeast cells consisted
of big mother cells, daughter
and grand daughter cells
Genetic data of P. brasiliensis have progressed in the twenty first century. More
than 5,000 sequences of P. brasiliensis are released into the GenBank database
(http://www.ncbi.nlm.nih.gov/sites/entrez).
Based on multiple gene analysis, P. brasiliensis was separated into three different phylogenetic species; S1 (species 1 from Brazil, Argentina, Paraguay, Peru and
Venezuela), PS2 (phylogenetic species 2 from Brazil and Venezuela) and PS3
(phylogenetic species 3 from Colombia) (Matute et al. 2006a, b, 2007).
Whole genome sequences on three strains of P. brasiliensis (Pb01, Pb03 and
Pb18) were released in the BROAD Institute (http://www.broad.mit.edu/annotation/
genome/paracoccidioides_brasiliensis/MultiHome.html). According to Carrero et al.
2008, isolate Pb01 might be a new Paracoccidioides species because of its diversity of
gene profiles compared to other P. brasiliensis isolates, and was named as P. lutzii
(Teixeira et al. 2009).
Among various genes, the gp43 is the most important gene because of its
diagnostic value (Puccia et al. 2008). We have also been trying to detect gp43 from
paraffin embedded tissue samples and blood (Sano et al. 2001; Itano et al. 2002).
424
A. Sano and E.N. Itano
The gene encodes the major fungal antigen; 43 kDa glycoprotein, which is a
dominant P. brasiliensis antigen, and has been used for serological test in endemic
areas (Miura et al. 2001; Camargo 2008).
Approximately 300 sequences of gp43 were released in the GenBank database at
the end of August 2009. The gene homologies among the majority of P. brasiliensis
isolates is more than 96% in, except for Pb01 and its related isolates identity
(Teixeira et al. 2009, Takayama et al. 2009). According to Takayama et al., the
LAMP band pattern of P. lutzii was different from those of P. brasiliensis.
18.3.2 LAMP Method for Identifications of P. brasiliensis
18.3.2.1
P. brasiliensis Isolates and Reference Species
Twenty-two clinical and seven nine-banded armadillo (Dasypus novemcinctus)
derived P. brasiliensis isolates were tested.
As an advanced notice, our method might limit to detect S1 phylogenetic type
of P. brasiliensis since we have not tested the isolates belonging to PS2 and PS3
proposed by Matute et al. 2006a and b. Furthermore, there is an uncertainty to
detect gp43 in atypical isolate P. brasiliensis strain Pb01 and its related isolates
(Carrero et al. 2008; Takayama et al. 2009), and has just been named as the new
species P. lutzii (Teixeira et al. 2009).
Isolates of Coccidioides immitis sensu lato (IFM 50993, identified as C. posadasii based on multiple gene analysis by Sano et al. 2006), Histoplasma capsulatum
(IFM 41329), Blastomyces dermatitidis (IFM 41316), Sporothrix schenckii (IFM
47068), Penicillium marneffei (IFM41708), Candida albicans (IFM 5740), and
Cryptococcus neoformans (IFM 5830) were used as negative controls (Table 18.1).
18.3.2.2
Extraction of DNA
Isolates of P. brasiliensis were evaluated. Yeast-form cells harvested on 1.0%
glucose added DifcoTM brain heart infusion agar (Becton Dickinson Microbiology
Systems, Sparks, MD, USA) slants at 35 C for 7 days were used. Approximately
5 108 yeast-form cells were suspended in distilled water (DW) and washed three
times with DW, and homogenized in a 1.5 mL volume plastic homogenizer. DNA
was extracted with the Gen Toru Kun for the yeast (Dr. GenTLETM for yeast) kit
(TAKARA BIO INC., Ohtsu, Shiga, Japan).
Isolates of C. posadasii H. capsulatum, B. dermatitidis, S. schenckii, P. marneffei, Ca.albicans, and Cr. neoformans were cultured on potato dextrose agar (Becton
Dickinson Microbiology Systems) at 25 C for 7–60 days.
The fungal cells of C. posadasii were fixed with 70% ethanol overnight, and
the DNA was extracted by the kit (Dr. GenTLETM for yeast, TAKARA BIO INC.).
The final concentrations of DNA were adjusted from 10 to 20 ng/mL.
Country
(City)
Source
(Remarks)
Phylogenetic
speciesa
Accession no.
(gp43)
Pb-9
Pb-18
Bt-2
Bt-3
Bt-4
Bt-7
Bt-9
B1183
PbLev
B339
Brazil
Brazil
Brazil (Botucatu, São Paulo)
Brazil (Botucatu, São Paulo)
Brazil (Botucatu, São Paulo)
Brazil (Botucatu, São Paulo)
Brazil (Botucatu, São Paulo)
Brazil
Brazil
Brazil
Human patient
Human patient
Human patient
Human patient
Human patient
Human patient
Human patient
Human patient
Human patient
Human patient
S1
S1
S1
S1
S1
S1
S1
ND
S1
S1
AB047690
AB047691
AB304676
AB304677
AB047693
AB304678
AB047694
ND
AB304680
AB304681
Recife
Pb-HM-AOK
Hachisuga
WAG
Tateishi
Bt-1
Pb-267
Pb-265
Recife-Pb-HC
P-25
P-30
UMK
Tatu
PRT1
PRT2
D3LY1
D4S1
Brazil (Recife)
Japan (Tokyo)b
Japan (Fukuoka)b
Japan (Osaka)c
Japan (Ibaragi)b
Brazil (Botucatu, São Paulo)
Brazil
Brazil
Brazil (Recife)
Costa Rica (San Jose)
Costa Rica (San Jose)
Japan (Chiba)b
Brazil (Botucatu, São Paulo)
Brazil (Botucatu, São Paulo)
Brazil (Botucatu, São Paulo)
Brazil (Botucatu, São Paulo)
Brazil (Botucatu, São Paulo)
Human patient
Human patient
Human patient
Human patient
Human patient
Human patient
Mutant of Pb-9
Mutant of Pb-9
Human patient
Human patient
Human patient
Human patient
Armadillo
Armadillo
Armadillo
Armadillo
Armadillo
S1
S1
S1
S1
S1
S1
S1
S1
S1
ND
ND
S1
S1
S1
S1
S1
S1
AB304682
AB047695
AB304682
AB047696
AB304684
AB304685
AB047692
AB304686
AB047699
AB047698
AB304688
AB047697
AB047700
AB047701
AB047702
AB047813
AB047704
(continued)
425
Strain
Applications of Loop-Mediated Isothermal Amplificaton Methods
(=CBS 372.73, =ATCC 32069)
IFM 41631
IFM 41632
IFM 41633
IFM 46215
IFM 46240
IFM 46464
IFM 46465
IFM 46466
IFM 46467
IFM 46468
IFM 46470
IFM 46930
IFM 46463
IFM 47183
IFM 47185
IFM 47195
IFM 47217
18
Table 18.1 Isolates
IFM
Number
Paracoccidioides brasiliensis
IFM 41620
IFM 41621
IFM 41622
IFM 41623
IFM 41624
IFM 41625
IFM 41626
IFM 41628
IFM 41629
IFM 41630
Country
(City)
Brazil (Botucatu, São Paulo)
Brazil (Botucatu, São Paulo)
Source
(Remarks)
Armadillo
Armadillo
Phylogenetic
speciesa
S1
S1
Accession no.
(gp43)
AB047703
AB047705
Coccidioides immitis sensu lato
(C. posadasii)
IFM 50993
USA
Human patient
–
–
Histoplasma capsulatum
IFM 41329
USA
Human patient
–
–
USA
Human patient
–
–
Sporothrix schenkii
IFM 47068
Japan
Human patient
–
–
Penicillium marneffei
IFM 41708
China
Bamboo rat
–
–
Candida albicans
IFM 5740
Japan
Human patient
–
–
Blastomyces dermatitidis
IFM 41316
(=ATCC 26199)
Strain
D4S9
D4LIV1
A. Sano and E.N. Itano
Cryptococcus nenformans
sensu lato
IFM 5830
Japan
Human patient
–
–
IFM Institute of Food Microbiology, Chiba University, the former name of the Medical Mycology Researc Center, and deposited as the official abbreviation
of the world culture collection of pathogenic fungi and actinomycetes
a
Phylogenetic species was estimated from gp43 sequence
b
The patient was infected in Brazil
c
The patient was infected in Paraguay
ND Not determined
426
Table 18.1 (continued)
IFM
Number
IFM 47228
IFM 47247
18
Applications of Loop-Mediated Isothermal Amplificaton Methods
427
DNA extracted from a paraffin-embedded tissue sample of PCM and an ethanolfixed sputum sample was extracted with a DEXPAT kit (TAKARA BIO INC.) and
was also used in the LAMP assay.
18.3.2.3
Detection of gp43 by PCR
A total volume of 25 mL was used for all PCR reactions. Fifty nanograms per
milliliter of DNA extracts were added to 2.5 mL of Ex TaqTM buffer in the kit (Ex
TaqTM, TAKARA BIO INC.) containing 4.5 mM MgSO4, 2 mL (2.5 mM each)
dNTP mixture in the kit (ExTaqTM, TAKARA BIO INC.), 2 mL each 10 pM primer
set of F3 50 -TCA CGT CGC ATC TCA CAT TG-30 encoding from 391st to 410th
and B3 50 -AAG CGC CTT GTC CAA ATA GTC GA-30 designed from the
complementary sequence from 718th to 740th correspondent to gp43 sequence at
GenBank U26160 and 0.0625 mL (5 units/mL) TaKaRa Ex TaqTM polymerase in the
kit (Ex TaqTM, TAKARA BIO INC.). Reaction mixtures were subjected to denaturation at 94 C for 1 min, followed by 30 cycles of amplification at 94 C for 1 min,
50 C for 1 min, and 72 C for 2 min and a final extension at 72 C for 10 min, in a
PCR Thermal Cycler MP (TAKARA BIO INC.). PCR products were separated by
electrophoresis on 1.0% agarose gels in TAE buffer (40 mM Tris-base, 20 mM
acetic acid, 1 mM EDTA), stained with ethidium bromide, and visualized by UV
transillumination. DNA strands obtained from the PCR were processed for direct
sequencing with ABI Prism 3,100 (Applied Biosystems, Foster City, CA., USA) to
confirm the sequence of gp43 (Sano et al. 1998–1999).
18.3.2.4
LAMP Method for gp43
Briefly, the LAMP method used in the present study detects the gp43 gene with a
combination of F3, B3, FIP, and BIP primers designed from the partial sequence of
gp43 (GenBank accession number U26160) by a registration system primer designing website (FUJITSU Ltd., Tokyo, Japan: “LAMP PIMER EXPLORER” website
in “Netlaboratory” homepage http://venus.netlaboratory.com/partner/lamp/index.
html). These primers recognize a partial sequence of gp43.
The primer sequences were as follows: F3, used in the species specific forward
primer; B3, used in the species-specific reverse one; FIP, 50 -TGG CTC CAG CAA
TAG CCA CCC GTC AAG CAG GAT CAG CAA T-30 designed from the forward
sequence of 425th to 445th and the complementary sequence of 464th to 485th; and
BIP: 50 -CAT GTC AGG ATC CCG ATC GGG CCT TGT ACA TAT GGC TCT
CCC T-30 designed by the forward sequence from 648th to 668th and the complementary sequence from 691st to 712th. The annealing sites of the primers are shown
in Fig. 18.3.
One micro liter of 10 ng/mL DNA template and 40 pmol each of the FIP and BIP
primers and 5 pmol each of the F3 and B3 primers were mixed with 12.5 mL of
2 reaction mix in the kit (Loop AMP, Eiken Chemical Co., Ltd., Tokyo, Japan) in a
428
A. Sano and E.N. Itano
1981
1
391
F3 Primer
(391–410)f
FIP Primer
(425–445)f
+(485–464)c
BIP Primer
(648–668)f
+(712–691)c
740
B3 Primer
(740–718)c
Fig. 18.3 Primer map for the LAMP method of detecting gp43 from P. brasiliensis
final volume of 23.0 mL. DNA mixtures were incubated at 63 C for 60 min. The
reaction was stopped by heating the mixture at 80 C for 2 min to inactivate the
enzyme of LAMP amplification. Detection limits of the LAMP method were
evaluated with serial dilutions of DNA from isolate IFM 46930.
As the positive control attached with the kit and a negative control consisted
of DW and other fungal DNAs, C. immitis, H. capsulatum, B. dermatitidis,
S. schenckii, P. marneffei, C. albicans, and Cr. neoformans were used. In addition,
DNAs extracted from a paraffin-embedded tissue sample, and an ethanol-fixed
sputum were reacted at 63 C for 60 and 120 min.
In addition, time-dependent increases in levels of DNA products by LAMP were
monitored by real-time-PCR (Rotor-Gene, RG2000, NIPPN/Techno Cluster, Inc.,
Tokyo, Japan) for as long as 70 min at 63 C with P. brasiliensis isolates IFM 41630
and IFM 46215.
18.4
Results
The PCR products amplified with the primer set; F3 and B3 showed species specificity for P. brasiliensis. The detection limit of the PCR was 100 fg of fungal genomic
DNA (data not shown). Other related species, such as C. posadasiis (not shown),
H. capsulatum, and B. dermatitidis or important pathogenic fungi; S. schenckii,
P. marneffei, Ca. albicans, and Cr. neoformans were negative (Fig. 18.4).
All partial sequences of gp43 consisted of 339 bps and were correspondent to
their accession numbers, except for isolate IFM 41628 (not done).
The specific DNA banding pattern of P. brasiliensis was detected in the clinical
and nine-banded armadillo derived isolates by LAMP. No DNA band was observed
in negative control isolates of C. posadasii, H. capsulatum, B. dermatitidis,
S. schenckii, P. marneffei, C. albicans, and Cr. neoformans (Fig. 18.5). The
detection limit of LAMP for gp43 was also 100 fg of fungal genomic DNA.
The incubation procedure at 63 C for 60 min was not sufficient for detection of
gp43 from DNA extracted from paraffin-embedded tissue sample or sputum
infected with PCM (data not shown). The DNA from a paraffin-embedded tissue
and sputum from different patients yielded the same ladder band yielded by fungal
DNAs via LAMP at 63 C for 120 min (Fig. 18.6a, b).
18
Applications of Loop-Mediated Isothermal Amplificaton Methods
bps
429
bps
1000
1000
500
500
M 1 2
3 4 5
6 7 8 9 10 11 12 13 14 15 16 17 18 M
Fig. 18.4 Amplification of the gp43 gene by PCR with primers F3 and B3. All DNA derived from
P. brasiliensis isolates (line 1–11) were uniformly positive. 12: Ca. albicans, 13: H. capsulatum,
14: B. dermatitidis, 15: P. marneffei, 16: S. schenckii, 17: Cr. neoformans, and 18: C. immitis
(C. posadasii) were negative
bps
bps
1000
1000
500
500
M 1 2
3 4 5
6 7 8 9 10 11 12 13 14 15 16 17 18 M
Fig. 18.5 Amplification of the gp43 gene by the LAMP methods. All DNA derived from
P. brasiliensis isolates (line 1–11) were uniformly positive. 12: Ca. albicans, 13: H. capsulatum,
14: B. dermatitidis, 15: P. marneffei, 16: S. schenckii, 17: Cr. neoformans, and 18: C. immitis 18:
C. immitis (C. posadasii) were negative
The LAMP reaction reached a plateau after incubation at 63 C for 45 min, so
far, as monitored by real time- PCR (Fig. 18.7). The positive control provided
with the kit reached a plateau at 15 min, and the negative one did not show
increase of fluorescence level. DNAs from other fungal species did not increase
the fluorescence level (data not shown). The LAMP reaction of DNA from isolate
IFM 46215 reached a plateau at 63 C for 45 min and those of IFM 41622 was
50 min.
430
A. Sano and E.N. Itano
Fig. 18.6 (a) Amplification
of the gp43 from paraffin
embedded tissue sample
by the LAMP methods.
M: Marker, 2: DNA from the
paraffin embedded tissue
sample. 3 and 4: Fungal DNA
of P. brasiliensis. (b) Those
from sputa. M: marker,
2: DNA from the sputum, 3
and 4: Fungal DNA of
P. brasiliensis
bps
a
bps
1000
b
1000
M
1
2
3
M
M
1
2
3
35
30
Fluorescence
25
20
15
Positive control
P. brasiliensis (IFM 41622)
P. brasiliensis (IFM 46215)
Negative control (DW)
10
5
0
0
10
20
30
Minutes
40
50
60
Cycle
Fig. 18.7 LAMP reaction monitored by real-time-PCR. The negative control with other fungal
DNAs, C. immitis (C. posadasii), H. capsulatum, B. dermatitidis, S. schenckii, P. marneffei, Ca.
albicans, and Cr. neoformans were as the same as DW
18.5
Comments and Opinions
The LAMP method provides for more rapid detection of gp43 than nested PCR.
LAMP required only 3 h from DNA extraction to identification, whereas nested
PCR required 12 h when we tested.
18
Applications of Loop-Mediated Isothermal Amplificaton Methods
431
LAMP methods are also advantageous because it can be applied to clinical
material, such as paraffin-embedded tissue and sputum samples for retrospective
study (Endo et al. 2004; Tatibana et al. 2009). Even in clinical samples, the time
required for diagnosis was less than 4 h.
The LAMP method is not only convenient for identification of P. brasiliensis,
but also for diagnosis of PCM, especially for identification of P. brasiliensis and
diagnosis of PCM outside of the endemic areas, such as European countries and
Japan. Patients in endemic areas are sometimes misdiagnosed as having a malignant
tumor because of a shadow on the chest X-ray and granulomatous inflammation of
infected tissue. Therefore, most PCM of patients in Japan are being diagnosed on
the basis of histopathological findings (Endo et al. 2004). The LAMP method could
be applied for PCM diagnosis in such cases without isolation of the fungus.
Application of real-time-PCR to the LAMP method should shorten the time for
obtaining the results within a couple of hours, because electrophoresis is not required.
While analysis of LAMP amplification products by agarose gel electrophoresis takes
approximately 3 h, LAMP in connection with real-time-PCR takes only 2 h.
According to the manufacturer’s protocol, LAMP products can be detected by
optical density under UV light. However, we do not recommend this method. Some
of pseudo reactions showing smear-like amplification products also became positive. Furthermore, we do not have any experience to react as a smear-like amplification in the real-time PCR method. Uncertainty of the reaction also could not be
removed. Therefore, LAMP products should be visualized by agarose gel electrophoresis.
In addition, the reaction does not require a special thermo cycler system.
A styrofoam box with warm water like that of a hot coffee temperature is one
sign of a good apparatus. It suggested that the method is useful in field hospitals.
This method will be important for detecting specific genes in highly pathogenic
or rare emerging fungal infections which require care and time-consuming culturing procedures.
However, because of extremely higher sensitivities to detecting genes by the
LAMP methods, it should be meaningless to apply the LAMP methods to Candida
species that exist as common fungal flora in oral or body surface, to Aspergillus
species and/or to other causative agents for the emerging fungal infections habitat
popular in soil or environments. It should be impossible to judge the results whether
it is environmental contaminations or real infectious propague. In addition, we
would like to avoid to give a comment on the report by Inácio et al (2008).
18.6
LAMP Method for Identifications of O. gallopava
We also applied the LAMP method to detection of the species-specific gene of
O. gallopava; a species of dematiaceous fungi recognized as a causative agent of
zoonotic and emerging fungal infections. The fungal specie shows excellent growth
at 42 C (Fig. 18.8a), and is able to grow up to 45 C or more.
432
A. Sano and E.N. Itano
Fig. 18.8 (a) Colonies of
O. gallopava cultured on
potato dextrose agar plate at
25, 37 and 42 C for 8 days,
(b and c) clavate conidia
under microscopy, x400
It affects the central nervous system and respiratory tracts of humans, birds and
cats and is required to be differentiated from SARS and highly pathogenic bird flu.
Clavate conidia (Fig. 18.8b and c) are virulent to experimentally infected mice
(Ohori et al. 2006; Yarita et al. 2007).
We designed O. gallopava species-specific primer sets to aid in its identification by the LAMP method based on the D1/D2 domain of the LSU rDNA
sequence.
The primer set for O. gallopava was designed based on the sequence of D1/D2
LSU rDNA of O. gallopava (accession number AB125281 in GenBank) with a
comparison of 21 species of dematiaceous fungi obtained from the present study
and from 108 sequences in GenBank database. The primer sequences were as
follows: OgF3: 50 -AGG GAG TCT CGG GTT AAG GG-30 encoding from the
391st to the 410th, and OgB3: 50 -CAT TCC CTT CGT CTT TGT CC-30
corresponding to the complementary sequence from the 718th to the 740th of
AB125281 and were species-specific for O. gallopava (Fig. 18.9). FIP; 50 -ACT
CGA CTC GTC GAA GGG GCA GAG GGT GAG AGT CCC GT-30 designed by
the forward sequence of 425th to 445th and the complementary sequence of 464th
to 485th, and BIP; 50 -ACT GGC CAG AGA CCG ATA GCG TGA CTC TCT TTT
18
Applications of Loop-Mediated Isothermal Amplificaton Methods
433
bps
bps
1000
1000
500
500
M
1
2
3
4
5
6
7
8
9
10 11 12 13
M
Fig. 18.9 Species specific PCR for O. gallopava. M: Marker, 1–10: O. gallopava, 11: O. gamsii,
12: and 13: O. tsawytschae. The related species such as O. constricta, O. humicola, Alternaria
alternata, Arthrobotrys javanica, Bipolaris sp., Bipolaris specifera, Cladophialophora bantiana,
C. carrionii, Curvularia geniculata, Cu. lunata var. lunata, Cu. senegalensis, Exophiala alcalophiala, E. dermatitidis, E. jeanselmei, E. moniliae, E. spinifera, Fonsecaea pedrosoi, Phialophora
verrucosa, Rhinocladiella atrovirens, Scolecobasidium terreum were negative
bps
bps
1000
1000
500
500
M
1
2
3
4
5
6
7
8
9
10 11 12 13
M
Fig. 18.10 Species specific loop mediated isothermal amplification method (LAMP) for O.
gallopava. M: Marker, 1–10: O. gallopava, 11: O. gamsii, 12: and 13: O. tsawytschae. The related
species such as O. constricta, O. humicola, Alternaria alternata, Arthrobotrys javanica, Bipolaris
sp., Bipolaris specifera, Cladophialophora bantiana, C. carrionii, Curvularia geniculata, Cu.
lunata var. lunata, Cu. senegalensis, Exophiala alcalophiala, E. dermatitidis, E. jeanselmei,
E. moniliae, E. spinifera, Fonsecaea pedrosoi, Phialophora verrucosa, Rhinocladiella atrovirens,
Scolecobasidium terreum were negative
CAA AGT GC-30 designed by the forward sequence from 648th to 668th and the
complementary sequence from 691 st to 712 nd of AB125281.
The LAMP method successfully detected the gene from both the fungal DNA
derived from experimentally infected brains and spleens of mice and environmental
434
A. Sano and E.N. Itano
bps
bps
1000
1000
500
500
M
1
2
3
4
5
6
7
8
9
10 11 12 13
M
Fig. 18.11 Detection of O. gallopava gene from the experimentally infected brains and spleens of
mice by LAMP method. M: Marker, 1–5: brain tissue of mice infected with O. gallopava. 6: blank,
7–11: spleen tissue of mice infected with O. gallopava. 12 and 13: negative control DNA from
demateaceous fungi
bps
Fig. 18.12 DNA pattern by
loop madiated isothermal
amplification method
(LAMP) specific for
O. gallopava using 20 pg
of fungal DNA. M: Marker,
1 and 6: a clinical isolate,
2–5: hot spring isolates,
7: a negative control using
distilled water for a template
bps
1000
1000
500
500
M
1
2
3 4
5
6 7 M
isolates (Fig. 18.10–18.12),which will help to differentiate O. gallopava infection
from other important avian zoonoses (Ohori et al. 2006; Yarita et al. 2007).
18.7
Conclusion and Future Line of Research
In conclusion, LAMP method for PCM and O. gallopava seemed to be useful for
fungal identification, diagnosis or retrospective study with advantage in the quickness and simplicity procedure, but require strictly controlled environments. It could
be applicable for clinical identification of fungi and diagnosis of fungal
18
Applications of Loop-Mediated Isothermal Amplificaton Methods
435
diseases caused by level 3 biohazards, such as coccidioidomycosis, histoplasmosis,
blastomycosis, and infection of Penicillium marneffei, which generally require care
and time consuming culturing procedures, and causative agent for emerging fungal
infections.
Acknowledgments We thank Drs. Kazuko Nishimura, Makoto Miyaji, Shigeo Endo, Akira
Ohori, Tsuyoshi Igarashi, Koji Yokoyama, Masashi Yamaguchi, Yoko Takahashi, Katsuhiko
Kamei, Marcello Franco, Giannina Ricci, Berenice Tatibana, Ms. Kyoko Yarita and Mr. Takashi
Komori for their cooperation.
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Chapter 19
Identification of the Genus Absidia (Mucorales,
Zygomycetes): A Comprehensive Taxonomic
Revision
Kerstin Hoffmann
Abstract This brief review intends to survey and evaluate the present knowledge
about the genus Absidia Tiegh. sensu lato regarding the traditional and current
position within the order Mucorales (Mucoromycotina, Zygomycetes), nomenclatural changes and the taxonomical rearrangements of the prevalent species. Species
grouped within Absidia possess some very promising industrial and medical application possibilities e.g., as mediators of biotransformations, producers of antimicrobial and wound healing stimulators. But some species are also causatives of
severe and frequent fatal mucormycoses. Using traditional and modern methods of
species determination had uncovered a trichotomous genera separation, namely
Absidia sensu stricto, Lichtheimia, and Lentamyces, belonging to distinct families,
the Absidiaceae, Lichtheimiaceae and “Lentamycetaceae” (NN), respectively. The
existing medical and industrial aspects necessitate a fast and secure identification of
a prominent species. Within this survey, morphological criteria and molecular
markers were proposed for clear distinction of Absidia sensu lato.
19.1
The Genus Absidia: Current State of the
Art – A Brief Survey
The order Mucorales within the proposed subphylum Mucoromycotina (Hibbett
et al. 2007) comprises ubiquitous soil fungi mainly living as saprobes, but also
facultative parasites on other fungi or plants and opportunistic pathogens causing
mucormycoses in human and animals (Ribes et al. 2000; Thirion-Delalande et al.
2005). One of these causative organisms is the genus Absidia causing rhino-cerebral
K. Hoffmann
Institute of Microbiology, School of Biology and Pharmacy, University of Jena, Neugasse, 25,
07743 Jena, Germany
e-mail: Hoffmann.Kerstin@uni-jena.de
Y. Gherbawy and K. Voigt (eds.), Molecular Identification of Fungi,
DOI 10.1007/978-3-642-05042-8_19, # Springer-Verlag Berlin Heidelberg 2010
439
440
K. Hoffmann
mycoses, primary cutaneous, pulmonary or gastrointestinal lesions which occur
sometimes in humans showing debilitating conditions like diabetes, burn wounds,
immunosuppression, or traumata (Gonzalez et al. 2002; Ribes et al. 2000). Since
opportunism of Absidia species is pronounced by growth maxima above body
temperature, thermotolerant species enjoy physiological advantages over mesophilic ones. Not only due to its opportunism is the genus Absidia of recurrent
interest but also due to some interesting biotechnological applications. For instance,
microbial biotransformations are an important tool for pharmaceutical, economical
purposes or even biodegradation of environmental pollutants (Chen et al. 2007;
Demirci et al. 2004; Guiraud et al. 2008).
To describe and classify species of the genus Absidia was therefore the main
objective of several mycologists and taxonomists. The genus was described in
1876 by van Tieghem and augmented by reputable taxonomists like Bainier
(1882, 1889), Hagem (1908), and Lendner (1907, 1908, 1924). Comprehensive
morphological and physiological investigations of Absidia species were accomplished especially by Hesseltine, Ellis and Schipper (Hesseltine and Ellis 1961,
1964, 1966; Ellis and Hesseltine 1965, 1966; Schipper 1990). Molecular aspects
have led to a renewal of species differentiation and were included in recent
years, allowing for a reliable discrimination at species and genus level. Combined with differences in growth temperature as well as morphological distinctions, the genus Absidia was previously distinguished in Absidia sensu stricto
encompassing the mesophilic species and in Lichtheimia comprising the thermotolerant species, which were summarized into a distinct family, the Mycocladaceae (orthographically erroneously pronounced as “Mycocladiaceae,” Hoffmann
et al. 2007) and revised in the Lichtheimiaceae (Hoffmann et al. 2009b). For potential
mycoparasitic species, a third genus, Lentamyces, was erected (Hoffmann and Voigt
2008). A detailed chronological summary of important accepted species and genera is
given in Table 19.1 with family affiliation, type strain specification and MycoBank
number (www.mycobank.org; Crous et al. 2004; Robert et al. 2005).
19.2
The Traditional Genus Absidia: Morphological Aspects
Nomenclatural designation of Absidia (Etym.: absis, arcus) started as early as 1876
with the genus description by van Tieghem. He characterized this genus by (1)
arcuated stolons with rhizoids, (2) rhizoids not opposite the sporangiophores, (3)
sporangiophores arising from the elevated parts of the stolons, (4) apophysate and
pyriform sporangia with deliquescent walls, and (5) zygospores surrounded by
appendages originating from the suspensors (van Tieghem 1876).
The assignment of species to the genus Absidia sensu lato is mainly based on
traditional morphological criteria and growth parameters. In so doing, the last
species identified so far is a thermotolerant variety of A. idahoensis (A. idahoensis
var. thermophila, Chen and Zheng 1998).
19
Identification of the Genus Absidia
441
Table 19.1 Major species traditionally placed within Absidia sensu lato and currently accepted
within the genera Absidia sensu stricto, Lichtheimia, and Lentamyces
Year Species
Type strain
MycoBank
no.
Absidia TIEGH. 1876, MB20001, type species: A. repens TIEGH., family Absidiaceae MB81973
1876 A. repens TIEGH.
CBS115583 (IT) MB223578
NRRL1315 (NT) MB351936
1889 A. caerulea BAINIER
NRRL2797 (T)
MB224063
1907 A. spinosa var. spinosa LENDN.
1908 A. cylindrospora HAGEM var. cylindrospora
NRRL1317 (T)
MB427391
NRRL1328 (T)
MB221208
1908 A. glauca HAGEM
NRRL2800 (T)
MB252572
1930 A. heterospora Y. LING
NRRL2793 (T)
MB252285
1936 A. fusca LINNEM.
1958 A. spinosa var. azygospora BOEDIJN
NRRL2841 (T)
MB346488
NRRL2632 (T)
MB292052
1959 A. cuneospora G.F. ORR & PLUNKETT
1961 A. cylindrospora var. rhizomorpha HESSELT. & J.J. ELLIS NRRL2771 (T)
MB348992
NRRL2770 (T)
MB325715
1962 A. pseudocylindrospora HESSELT. & J.J. ELLIS
NRRL1807 (T)
MB325709
1964 A. anomala HESSELT. & J.J. ELLIS
NRRL3060 (T)
MB353238
1964 A. cylindrospora var. nigra HESSELT. & J.J. ELLIS
1964 A. spinosa var. biappendiculata RALL & SOLHEIM
NRRL3033 (T)
MB348993
NRRL2968 (T)
MB325710
1965 A. californica J.J. ELLIS & HESSELT.
CBS697.68 (T)
MB325712
1968 A. macrospora VÁNOVÁ
Lichtheimia VUILL. 1903, MB20308, type species: L. corymbifera (COHN) VUILL., family
Lichtheimiaceae MB508680
NRRL2981 (NT) MB416447
1903 L. corymbifera (COHN 1884) VUILL.
NRRL1309 (NT) MB416448
1903 L. ramosa (ZOPF 1890) VUILL.
2009 L. hyalospora (SAITO 1906) K. HOFFM, G. WALTHER & K. VOIGT NRRL2916 (NT) MB512830
2009 L. ornata (A.K. Sarbhoy 1965) A. ALASTRUEY-IZQUIERDO & NRRL10293 (IT) –
G. WALTHER
–
2010 L. sphaerocystis A. ALASTRUEY-IZQUIERDO & G. WALTHER CBS420.70 (T)
Lentamyces K. HOFFM. & K. VOIGT 2008, MB511979, type species: L. parricida (RENNER &
MUSKAT ex HESSELT. & J.J. ELLIS) K. HOFFM. & K. VOIGT
2008 L. parricida (RENNER & MUSKAT ex HESSELT. & J.J. ELLIS NRRL2409 (T)
MB511980
1964) K. HOFFM. & K. VOIGT
NRRL2806 (T)
MB511981
2008 L. zychae (HESSELT. & J.J. ELLIS 1966) K. HOFFM. &
K. VOIGT
NT Neotype; IT Isotype; T type; NRRL Northern Regional Research Laboratories, strain collection
of the National Center of Agricultural Utilization Research Peoria, IL, USA; CBS Centraalbureau
voor Schimmelcultures Utrecht, The Netherlands
Although the first species described possess appendaged suspensors of their
zygospores, several species lacking appendages were described in the following
years, and due to further differences in morphology and physiology (especially
sporangiophore branching, stolon, rhizoid and zygospore appearance, as well as
growth temperature) ten different generic names were proposed over the years
1888–2008 in order to delimitate Absidia-like species from unequivocal designation to Absidia: Tieghemella BERL. & DE TONI (1888), Mycocladus BEAUVERIE
(1900), Proabsidia VUILL (1903), Lichtheimia VUILL (1903), Pseudoabsidia [as
“Pseudo-Absidia”] BAINIER (1903), Protoabsidia NAUMOV (1935), Gongronella
RIBALDI (1952), Chlamydoabsidia HESSELT. & J.J. ELLIS (1966), Siepmannia
KWAŚNA & NIRENBERG (2008a, b) and Lentamyces K. HOFFM. & K. VOIGT (2008).
442
K. Hoffmann
The genera Absidia, Tieghemella, and Proabsidia are now considered as synonyms for species with zygospores surrounded by appendages from the suspensors
whereas, Lichtheimia, Mycocladus, Pseudoabsidia, and Protoabsidia were
assigned to Absidia species lacking such appendages (Hesseltine and Ellis 1964;
Schipper 1990).
The genus Gongronella, which is based on Absidia butleri LENDN., shows an
apophysis, nonpyriform sporangia with reduced columellae, and zygospore suspensors devoid of appendages (Ribaldi 1952).
Based on morphology, the genus Chlamydoabsidia is obviously nested within
Absidia sensu stricto but developing unique multiseptate, pigmented aerial chlamydospores (Hesseltine and Ellis 1966). Most recently the species with warty
exospore of their Mucor-like zygospores were separated in the genus Lentamyces,
which was first invalidly (then correctly) described as Siepmannia the same year
(Hoffmann and Voigt 2008; Kwaśna and Nirenberg 2008a, b).
19.3
The Impact of Molecular Data: The Genus Absidia
sensu lato is Distinguished in at Least Three
Nonrelated Genera
Support of its morphological and physiological evidence by molecular based
phylogenetic analyzes has led to a wide acceptance of the polyphyly of Absidia
in recent years (Voigt et al. 1999; Voigt and Wöstemeyer 2001; O’Donnell et al.
2001; Kwaśna et al. 2006). This phylogenetic interpretation approximates a natural
system contradicting the nomenclatural inflation of Absidia and its allied genera
around the turn of the nineteenth century.
In order to prove and support the relationship of the described species to a
specific genus within this study, molecular data was analyzed in a multigene
phylogeny and supplemented with morphological and physiological data (here
especially parameters of growth temperature). An alignment of the combined
ribosomal DNA sequences (18S rDNA, 28S rDNA) and nucleotide sequences
coding for actin (act) and translation elongation factor 1 alpha (tef) was subjected
to a Bayesian inference (Fig. 19.1).
Since their morphology-based description, the genera Gongronella and
Chlamydoabsidia are considered as independent Absidia-like genera, but they are
still somehow related to Absidia morphologically and also on the molecular level,
with Chlamydoabsidia nested within the genus and Gongronella closely related to
the Absidia core group (Voigt et al. 1999; O’Donnell et al. 2001; Voigt and
Wöstemeyer 2001; Hoffmann and Voigt 2008; Fig. 19.1).
The classification currently accepted assigns Absidia-like taxa to three different
genera and is supported by molecular phylogenies, morphological and physiological studies: (1) Absidia sensu stricto (syn. Tieghemella, Proabsidia), (2) Lentamyces
and (3) Lichtheimia (syn. Mycocladus, Pseudoabsidia, Protoabsidia).
19
Identification of the Genus Absidia
443
Mortierella multidivaricata
Mortierella verticillata
Mortierella alpina
Umbelopsis isabellina
Umbelopsis nana
Umbelopsis ramanniana
Lentamyces parricida
Lentamyces zychae
Phycomyces blakesleeanus
Spinellus fusiger
Radiomyces spectabilis
Saksenaea vasiformis
Thermomucor indicae-seudaticae
Rhizomucor miehei
Rhizomucor pusillus
Dichotomocladium elegans
93
Lichtheimia corymbifera
Lichtheimia ramosa
L. hyalospora
L. hyalospora
Rhizopus oryzae
93
Rhizopus stolonifer
Mycotypha africana
Mycotypha microspora
Blakeslea trispora
Choanephora cucurbitarum
99
Chaetocladium brefeldii
Mucor racemosus
Parasitella parasitica
Gongronella butleri
Hesseltinella vesiculosa
Cunninghamella bertholletiae
Cunninghamella echinulata
Halteromyces radiatus
Absidia spinosa
Absidia psychrophilia
Absidia repens
98
Absidia glauca
Chlamydoabsidia padenii
Absidia macrospora
Absidia californica
0.1 substitutions / site
Absidia caerulea
Fig. 19.1 Phylogeny of inferred by Bayesian analysis from a combined analysis of aligned
nucleotide sequences coding for actin, translation elongation factor 1alpha, small (18S) and
large (28S) subunit rRNA (see Table 19.3). Posterior Probabilities (PP) are given above the
branches with dots indicating 100%
444
K. Hoffmann
19.3.1 The Genus Absidia TIEGH. sensu stricto Deserves
a Separate Family, the Absidiaceae V. ARX
As already mentioned, the genus Absidia sensu stricto harbors mesophilic species
with the optimum and maximum temperatures for growth around 30 C and 37 C
respectively. Along with their common pyriform, multispored sporangia, they form
columellae with species specific apical projections (Hoffmann et al. 2007). Furthermore, the asexually produced sporangiospores are species-specifically globose to
cylindrical. As outlined in detail by Schipper (1990), Absidia could be divided into
several groups distinguishable by their spores. This distinction is of taxonomical
importance, since it is also present in molecular phylogenetic analyzes. (Kwaśna
et al. 2006; Hoffmann et al. 2007, 2009a; Hoffmann and Voigt 2008). Within
these analyzes three well supported clades are obvious: A. caerulea, A. californica,
A. glauca, and A. macrospora with globose sporangiospores (temperature for growth
and sporulation at 15–30 C, no growth at 34–37 C). A. anomala, A. cylindrospora,
A. pseudocylindrospora, A. psychrophilia, A. repens, and A. spinosa possess oval
to cylindrical spores (growth and sporulation at 15–34 C, no growth at 30–37 C), and
A. cuneospora shows conical shaped spores and represents an intermediate species
positioned between the other two groups (Schipper 1990; Hoffmann et al. 2007;
missing data for A. cuneospora in Fig. 19.1).
Species within these clades, especially A. caerulea and A. glauca, offer some
pharmaceutical important properties as biomimetic models to test the metabolism
of xenobiotics like steroids and saponins in mammalia (Brezezowska et al. 1996;
Huszcza and Dmochowska-Gladysz 2003; Chen et al. 2007). Both species are also
potentially chitosan producers, useable in the food processing industry as well as
medical applications since chitosan seems to possess antimicrobial and woundhealing stimulating activities (Abdel-Fattah et al. 1984; Muzzarelli et al. 1994;
Rungsardthong et al. 2006; Dai et al. 2009). Some species were also extensively
studied for applications in environmental detoxifications like A. cylindrospora and
A. fusca, which are able to degrade polycyclic aromatic hydrocarbons (Guiraud
et al. 2008).
All species belonging to the genus Absidia sensu stricto could now be summarized in the family Absidiaceae, which was erected by von Arx (1982). Although von
Arx included fourteen genera within the Absidiaceae, only six are accepted here,
namely Absidia, Chlamydoabsidia, Cunninghamella, Gongronella, Halteromyces,
and Hesseltinella. Even though, there are only a few studies including all affected
genera in one analysis, the close relationships between some of these genera was
repeatedly demonstrated. Based on 18S and 28S rDNA sequences, Absidia, Chlamydoabsidia and Cunninghamella are well supported sister taxa (100% BS, Voigt
et al. 1999). Based on the combined coding sequences of act and tef, Absidia,
Chlamydoabsidia, Cunninghamella, Hesseltinella and Halteromyces are in close
vicinity (without high support values, Voigt and Wöstemeyer 2001) but high
support values for this clade (additionally including Gongronella, 100% BS) are
presented by O’Donnell et al. 2001, in an analysis of combined tef and rDNA
19
Identification of the Genus Absidia
445
sequences. Except of Chlamydoabsidia (which is always nested within Absidia), all
genera are slightly distinct from the core Absidia, but are related within one
monophyletic clade (Fig. 19.1, 100% posterior probability (PP)). On the morphological level, the main distinctions could be found in the shape of the sporangia
(e.g., pyriform for Absidia, dumbbell-shaped for Halteromyces), number of spores
produced within each sporangia (e.g., few or uni-spored [Cunninghamella] or
multispored [Halteromyces, Absidia]), and zygospore appearance (with [Absidia]
or without appendages on the suspensors [Cunninghamella, Gongronella]). All of
these characteristics seem not to be systematically important in family description,
a finding which was also proven for other families within the order Mucorales
(Voigt et al. 2009), and in the past, these morphological criteria have led to
systematic classifications, not sustainable in the era of molecular phylogenetics
(e.g., Absidiaceae comprised fourteen genera from which only six are phylogenetically related; compare von Arx 1982 and O’Donnell et al. 2001; Voigt and
Wöstemeyer 2001). Although Absidiaceae is treated as a synonym of the highly
polyphyletic family Mucoraceae (Kirk et al. 2008), in accordance to Voigt et al.
(2009) a restoration of the monophyletic Absidiaceae is highly recommended here.
19.3.2 The Genus Lichtheimia (COHN) VUILL. and Its Family
Lichtheimiaceae K. HOFFM., G. WALTHER and K. VOIGT
Lichtheimia corymbifera (formerly: Absidia corymbifera) is a common causative
agent of mucormycoses and was described as Mucor corymbifer by Cohn 1884.
Mycoses caused by other species belonging to this genus were not reported
yet, which is, in all likelihood, a problem of proper identification as well as taxonomical knowledge. Morphological and physiological separation between the species of
Lichtheimia depends on differences in the growth temperature, in the giant cell and
partly in the sporangiospore morphology (Hoffmann et al. 2007, 2009a; AlastrueyIzquierdo et al. 2010), and with optima for growth around 37 C all species should
be capable to colonize endothermic organisms under appropriate conditions. With the
growing awareness for the need to differentiate between single species in fungal
infections, it was essential to discriminate Lichtheimia from Absidia species, because
species of the mesophilic genus Absidia are known to be harmless and do not cause
systemic infections in human and warm-blooded animals. Furthermore, the assignment of all known former thermotolerant Absidia species to the genus Lichtheimia
is essential for the establishment of a natural monophylum-based system.
Lichtheimia is distinguished from Absidia not only on the molecular level, but
also on the basis of morphological and growth-physiological differences. Since
comprehensive analyses including as many genera as possible, thermotolerant
species were clearly distinct from mesophilic Absidia species (Voigt et al. 1999,
2009; O’Donnell et al. 2001; Voigt and Wöstemeyer 2001; Hoffmann et al. 2007;
Hoffmann and Voigt 2008). Due to zygospores lacking appendaged suspensors and
growth temperatures with optima and maxima above 37 C, a separation of these
446
K. Hoffmann
species within the subgenus Mycocladus was proposed by Hesseltine and Ellis
(1964) and was accepted by Schipper (1990). This subgenus was based on the type
taxon M. verticillatus BEAUVERIE (Beauverie 1900). Mycocladus was also described
as independent genus (Mirza et al. 1979; Vánová 1991). Based on physiological,
phylogenetic and morphological analyses the (sub-)genus Mycocladus was reclassified in the new family Mycocladaceae [as “Mycocladiaceae”], K. HOFFM., DISCHER
& K. VOIGT emphasizing its phylogenetic distinctness from species designated to
Absidia (Hoffmann et al. 2007). But in the course of a critical reexamination of all
available literature references, especially the years around the turn of the century
(1882–1904), the correct assignment of Mycocladus verticillatus as type taxon for
nonappendaged zygospore suspensors was rejected. Furthermore, on the morphological level Mycocladus verticillatus seems to be a coculture of at least two
different species (Beauverie 1900; Hoffmann et al. 2009b).
The first rough-walled zygospores with unadorned suspensors and equatorial
ridges within the genus Absidia were described in 1903 by Bainier for the species
Pseudoabsidia vulgaris [as “Pseudo-Absidia”], based on Absidia dubia BAINIER
1882 (Bainier 1882, 1903). His error of assigning a wrong epithet was corrected
the same year by Sydow, proposing Pseudabsidia dubia (BAINIER) SYDOW (Sydow
1903). The species was later transferred to Lichtheimia, a genus named in honor of
the mycologist Lichtheim, professor at the University of Bern, Switzerland (Vuillemin 1903, 1904). Within the same publication issue of the Bulletin de Socie´te´
Mycologique de France where Bainier described Pseudoabsidia (page 155), Vuillemin proposed the genus Lichtheimia (page 126). He recognized Mucor corymbifer COHN as type of Lichtheimia. The appearance of nonappendaged and naked
zygospores in L. corymbifera was described separately (Vuillemin 1904).
The original description of Lichtheimia VUILL. and its type L. corymbifera
represents the new family Lichtheimiaceae K. HOFFM., G. WALTHER & K. VOIGT
which harbors the species L. corymbifera (COHN) VUILL., L. ramosa (ZOPF) VUILL.,
L. ornata (A.K. SARBHOY) A. ALASTRUEY-IZQUIERDO & G. WALTHER, L. hyalospora
(SAITO) K. HOFFM., WALTHER & K. VOIGT and L. sphaerocystis A. ALASTRUEY-IZQUIERDO
& G. WALTHER.
19.3.3 The Genus Lentamyces and a Required Excursus
to Siepmannia: Species Boundaries
The genus Lentamyces K. HOFFM. & K. VOIGT comprises homothallic and potentially
mycoparasitic species producing warty zygospores lacking appendaged suspensors
(Hoffmann and Voigt 2008). This genus is composed of currently two species with
the potentially mycoparasitic L. zychae and the mycoparasitic L. parricida.
L. zychae was originally described to be mycoparasitic on other Mucorales (Zycha
1935), but could never be confirmed as causative agent of mycoparasitic reactions
on other mucoralean hosts in recent confrontation experiments using the type strain
NRRL2806 (Table 19.1; Hoffmann and Voigt 2008). But for L. parricida a wide
19
Identification of the Genus Absidia
447
variety of potential mucoralean hosts are experimentally confirmed (Schipper 1990;
Hoffmann and Voigt 2008). Apart from the varying potential for mycoparasitic
abilities, both species show morphological and physiological characteristics of
mycoparasitic fungi such as slowly developing colonies with thin mycelia, and
abundant sucker-like branches in the substrate mycelium of single cultures but
vigorously growing hyphae in cocultures with other mucoralean fungi. L. zychae
and L. parricida form a monophyletic group (100% PP) which is closely related to
the Phycomycetaceae (Voigt et al. 2009). The Lentamyces clade may represent the
next to the last family, the putative “Lentamycetaceae,” at the base of the order
Mucorales (Fig. 19.1). Their homothallic and facultative parasitic nature turns this
basal lineage of mucoralean fungi into an interesting subject to study the evolution
of fungal communication directly at the level of radiation and diversification of
mucoralean fungi (Hoffmann et al. 2007; Hoffmann and Voigt 2008). In 2008 both
species were classified into the genus Siepmannia as S. parricida and S. zychae. The
genus was amended by two new species, S. pineti and S. lariceti. The authors
described S. pineti as morphologically similar to Fennellomyces linderi and
S. lariceti similar to Mucor circinelloides but with micromorphological features
of different size (Kwaśna and Nirenberg 2008a). Nevertheless, judging by the
presented descriptions and photographs, S. pineti seems more like a species of the
genus Circinella: developing structures typical for Circinella like circinate sporangiophores terminating in globose to dorsiventrally flattened sporangia with a
persistent wall. F. linderi would occasionally develop a subsporangial vesicle, not
described for Siepmannia. S. lariceti seems with all likelihood representing a
species of Mucor, as stated by Kwaśna and Nirenberg. On the contrary, neither
L. parricida nor L. zychae produce circinate nor sympodially branched sporangiophores as described for Siepmannia. The sporangia are always globose to subpyriform, apophysate surrounded with a deliquescent sporangial wall (Hesseltine and
Ellis 1964, 1966).
Although species of Siepmannia are described to be mycotrophic, no hint for
potential mycoparasitism was reported (Kwaśna and Nirenberg 2008a). Parasitic
interactions, e.g., between L. parricida and one of its host Zygorhynchus moelleri,
was successfully demonstrated by Hoffmann and Voigt 2008. A typical morphological feature of Lentamyces is the abundant sucker-like substrate mycelium and
the homothallic formed globose zygospores with a warty exospore. No such typical
mycelium was pictured for S. lariceti and S. pineti. The zygospores of S. lariceti are
globose to ellipsoid and not as large and warty as those of Lentamyces. The only
criteria which have Siepmannia and Lentamyces in common are of physiological
nature, e.g., a low maximum temperature for growth and a restricted growth, which
is stimulated in the presence of other fungi (potential hosts in the case of Lentamyces)
(Kwaśna and Nirenberg 2008a; Hesseltine and Ellis 1964, 1966; Hoffmann and Voigt
2008). However, physiological criteria may vary among isolates and species and their
relevance as synapomorphic characters is limited (Voigt et al. 2009).
In a further step, the authors generated species-specific restriction patterns
of digested ITS sequences. They used the enzymes AluI, HhaI, DdeI, HaeIII,
HincII, HinfI, HpaII, Sau3AI, and TaqI, which clearly differentiated S. pineti
448
K. Hoffmann
from S. lariceti and F. linderi as well as S. lariceti from M. circinelloides (Kwaśna
and Nirenberg 2008a) Nevertheless, they did not say anything about the restriction
patterns of L. parricida and L. zychae. Repeating these restriction experiments with
all species of Lentamyces and Siepmannia in theoretical in silico RFLP analyses
using BioEdit v.7.0.9.0 (Hall 1999) resulted in highly variable restriction fragment
length polymorphisms among the strains (Table 19.2). Neither Siepmannia nor
Lentamyces show similar restriction sites to each other or to Mucor circinelloides
or Fennellomyces linderi. Based on the present characteristics, it could not be stated
whether Lentamyces and Siepmannia share a common generic designation or
represent distinct taxa.
The molecular phylogenetic analysis presented by Kwaśna and Nirenberg
(2008a) was done on ITS1-5.8S rDNA-ITS2 sequences and lacks reference and
type species. The fusion of both genera within Siepmannia neglects obvious
morphological and molecular distinctions and does not doubtlessly justify a combination of the genus Siepmannia with L. zychae and L. parricida. The relationship
between Siepmannia and Lentamyces has to be proven by further investigations
Table 19.2 Theoretical in silico RFLP analyses of species belonging to the genera Lentamyces
and Siepmannia as well as Mucor circinelloides and Fennellomyces linderi. Bold indicated
restriction sites are similar in Siepmannia but are not present in Lentamyces, M. circinelloides or
F. linderi
Species and
Length of
Restriction sites for different enzymes
GenBank
ITS1AluI HhaI DdeI HaeIII HincII HinfI HpaII Sau3AI TaqI
accession
5.8S-ITS2
number
[bp]
S. pineti
630
241 –
–
473
–
339 151
25
168
AJ748134
249
347 381
272
291
499 557
509
S. lariceti
402; first
547 –
–
466
–
340 –
272
291
178 bp
AJ748857
are missing
348
L. parricida
545
–
–
–
406
–
267 309
198
90
AY944884
275 472
100
217
L. zychae
594
444 –
–
–
–
10
331
222
119
EF030529
289 512
241
297
544
L. zychae
594
444 –
–
422
–
10
331
222
119
AJ968561
289 343
241
297 512
544 560
M. circinelloides 556
129 337 78
147
122
308
237
256
AJ878535
142 457
316
314
533
F. linderi
669
467
34
354
283
72
AJ878536
211
601
302
482
656
360
19
Identification of the Genus Absidia
449
in the context of extended multilocus phylogenetic analyzes on a taxon set
which comprehensively represents the Mucorales as a whole as demonstrated by
O’Donnell et al. (2001) and Voigt and Wöstemeyer (2001).
Furthermore, the first descriptions of the genus Siepmannia as well as the new
combinations of S. zychae and S. parricida were not in accordance with the articles
37.1, 33.4 and 43.1 of the ICBN (McNeill et al. 2006). Although a validation was
made the same year (Kwaśna and Nirenberg 2008b), the genus Lentamyces for the
species L. parricida and L. zychae was validly published before (Hoffmann and
Voigt 2008). The final phylogenetic position of the genus Siepmannia and its
relation to Lentamyces requires further investigations; even a combination in one
family is possible.
19.4
Morphological and Molecular Differentiation of Affected
Species Belonging to Absidia sensu lato
Although the traditional approach of comparative morphology for species differentiation is quite easy to perform, some if not most of the existing descriptions keys
are now outdated. The more the data gained, the more changes in taxonomical designations were performed as a consequence of varying interrelationships. The increase
of importance of molecular data combined with a broad range of analytical tools
allows improvements in statistically supported phylogenetic relationships at all taxonomical levels. Natural relationships among species could not predict and be fully
resolved on the basis of morphology alone but by comparative molecular phylogenetics as well, and therefore, in order to assign an organism to its natural affiliation,
morphology should be supplemented with additional and independent data.
In the following a synoptic key to the affected genera and species of Absidia
sensu lato is given, which extends the detailed descriptions given by Ellis and
Hesseltine (1965, 1966), Hesseltine and Ellis (1961, 1964, 1966), Zycha et al.
(1969), Schipper (1990) and Alastruey-Izquierdo et al. (2010). In addition short
signature consensus sequences and PCR-restriction fragment length polymorphisms
of the ribosomal ITS1-5.8S rDNA-ITS2 region are proposed for genus separation.
19.5
Synoptic key to Genera and Species
1a. thermotolerant, temperature optimum and maximum above 34 C, growth
above 37 C, rapidly growing, sporangiophores often without subsporangial
septum, non parasitic on other Mucorales, zygospores without appendaged
suspensors ........................................................................... genus Lichtheimia
1b. not thermotolerant, temperature maximum above 30 C, no growth above 37 C,
rapidly growing, sporangiophores with subsporangial septum, non parasitic on
other Mucorales, zygospores with appendaged suspensors ....... genus Absidia
450
K. Hoffmann
1c. not thermotolerant, temperature maximum below 30 C, slowly growing, sporangiophores with subsporangial septum, potentially parasitic on other Mucorales, homothallic, warty zygospores without appendaged suspensors ..............
............................................................................................... genus Lentamyces
19.5.1 The Genus Lichtheimia (VUILL. 1903; Lichtheimiaceae
K. HOFFM., G. WALTHER & K. VOIGT 2009):
This Key Is Originally Published in Alastruey-Izquierdo
et al. (2010)
1a. Sporangia dark brown or dark grey to black; colony diameter after 72 h at
43 C < 2 mm; mature sporangiospores rough and/or > 6.5 mm in their longest extension ................................................................................................. 2
1b. Sporangia light brownish grey; colony diameter after 72 h at 43 C > 14 mm;
mature sporangiospores smooth and < 6.5 mm in their longest extension .....3
2a. Giant-cells consistently globose, 60–150 mm in diameter ....L. sphaerocystis
2b. Giant-cells (if present) more hypha-like, irregularly swollen, simple to
strongly branched, never consistently globose ...................... L. hyalospora[1]
2ba. Mature sporangiospores small (< 5.5 mm), rough, and brownish ..................
......................................................... small-spored variants of L. hyalospora[1]
2bb. Mature sporangiospores larger (on the majority > 5.5 mm), smooth or rough,
hyaline or brownish ........................large-spored variants of L. hyalospora[1]
3a. Colony diameter after 72 h at 43 C > 40 mm, spores ellipsoidal to cylindrical
or subglobose to broadly ellipsoidal ................................................L. ramosa
3b. Colony diameter after 72 h at 43 C < 27 mm, spores never consistently
ellipsoidal to cylindrical ................................................................................ 4
4a. Densely branched giant-cells, 380–760 ( 900) 320–660 ( 770) mm, present in 2-week-old YEA cultures ....................................................... L. ornata
4b. Giant-cells absent from 2-week-old YEA cultures .................L. corymbifera
[1]
L. hyalospora is now a synonym of L. blakesleeana (Alastruey-Izquierdo et al.
2010). L. hyalospora was originally seperated from L. blakesleeana by the formation of larger and unusual hyaline mitospores. A prospective new separation of both
species in varieties or formae could not be excluded.
19.5.2 The Genus Absidia (Tiegh. 1876; Absidiaceae Arx 1982)
1a. all sporangia pyriform, apophysate, with prominent columella, columellae
often with apical projection, without chlamydospores ................ 2 (Absidia)
1b. dark-colored chlamydospores within aerial hyphae ........................................
................................................................................. Chlamydoabsidia padenii
19
Identification of the Genus Absidia
451
2a. sporangiophores circinate and arising individually, sporangia mutant .......
........................................................................A. reflexa (uncertain species)
2b. sporangiophores not bent ........................................................................... 3
3a. sporangiospores smooth ............................................................................. 4
3b. sporangiospores roughened to echinulate ..... A. scabra (uncertain species)
4a. sporangiospores spherical, heterothallic .................................................... 5
4b. sporangiospores spherical, homothallic ........A. septata (uncertain species)
4c. sporangiospores throughout not spherical, heterothallic or homothallic ......8
5a. all sporangiospores spherical 2.5–5.5 mm ................................................. 6
5b. all sporangiospores spherical up to 8.9 mm ......................... A. macrospora
6a. young mycelium violet ............................................................. A. caerulea
6b. young mycelium of different color ............................................................ 7
7a. sporangiophores single or in whorls, often two; young mycelium strain
specifically colored (white, green, brown) .................................. A. glauca
7b. sporangiophores single or in abundant whorls, mostly more than two; young
mycelium green to grey .........................................................A. californica
8a. sporangiospores more or less cylindrical, species homothallic ................. 9
8b. sporangiospores diverse (oval, cylindrical, globose, conical, irregular),
species heterothallic ................................................................................. 10
9a. young cultures violet or reddish ............................................... A. anomala
9b. young cultures white, never violet or reddish, if suspensors typically
unequal in size then appendages originate from the larger one .....................
.................................................................................... A. spinosa var. spinosa
9c. zygospore suspensors equal in size, appendages originating from both
suspensors ................................................A. spinosa var. biappendiculata
9d. similar to variety spinosa but abundant azygospores with up to 3 spores on
one suspensor ...................................................A. spinosa var. azygospora
10a. abundant secondary sporangia in older cultures, sporangiospores oval to
short cylindrical ............................................................................A. repens
10b. no secondary sporangia, sporangiospores conical or clearly cylindrical ....11
11a. sporangiospores conspicuously conical ................................A. cuneospora
11b. sporangiospores diverse, irregularly shaped, globose and cylindricalellipsoidal, columellae without distinct apical projections .... A. heterospora
11c. sporangiospores regularly cylindrical ...................................................... 12
12a. young colonies on PDA white, older colonies greyish-brown, sporangiophores
in whorls (1–4), zygospores with unequal suspensors .....................................
.................................................................A. cylindrospora var. cylindrospora
12aa. appears similar to A. pseudocylindrospora but older colonies on PDA
medium of dark brownish grey color, no mating with A. cylindrospora ....
.......................................................................... A. cylindrospora var. nigra
12ab. colonies on PDA light greyish brown; on Czapek-agar forming rhizomorph-like hyphae, no mating with A. cylindrospora ................................
..............................................................A. cylindrospora var. rhizomorpha
12b. similar to A. cylindrospora, but older colonies blackish brown pigmented,
sporangiophores in whorls up to six ...............................................A. fusca
452
K. Hoffmann
12c. similar to A. cylindrospora, young colonies grey, zygospores with equal
suspensors ............................................................. A. pseudocylindrospora
12d. young colonies brownish, temperature optimum between 15–20 C, no
growth at 30 C .................................................................. A. psychrophilia
19.5.3 The Genus Lentamyces (K. HOFFM. and K. VOIGT 2008)
1a on MEX mycelium not higher than 3 mm, thin, slow growing, brownish,
facultative parasitic on other Mucorales, abundant zygospores, sporangiospores
cylindrical 1.6–2.5 mm 1.9–3.3 mm ..................................................L. parricida
1b not parasitic on other Mucorales, rare zygospores, sporangiospores cylindrical
1.2–2.2 mm 1.6–3.3 mm ........................................................................L. zychae
19.6
Some Remarks to Uncertain Species
Among the literature species epithets exist which are only once encountered and
described. The species are not available in any culture collection and, if there was
no mistake in the observations described, could be presumed as lost. Therefore,
A. scabra, A. septata and A. reflexa still remain within the genus Absidia until
they are rediscovered because the passed down morphological descriptions match
those of Absidia. Except for the roughened to echinulate sporangiospores and
missing septae beneath the sporangium, A. scabra COCCONI resembles the characteristics of A. caerulea (Cocconi 1899; Ellis and Hesseltine 1965). The description of
A. septata TIEGH. is also nearly identical with those of A. caerulea but differs in the
presence of homothallically formed zygospores which were definitively illustrated
(van Tieghem 1876; Ellis and Hesseltine 1965). A. reflexa TIEGH. described by van
Tieghem (1876) shows obvious circinate sporangiophores which is not typical for
Absidia (Ellis and Hesseltine 1965). Until a rediscovery and without a profound
phylogenetic study, a clear designation to any species or genera remains uncertain.
Because they lacked sufficient diagnoses or absence in appropriate strain collections
the following taxa were not considered here: A. aegyptiacum SATORY, MEYER & TAWFIK
1939; A. capillata TIEGH. 1876; A. clavata B.S. MEHROTRA & NAND 1967; A. fassatiae
VÁNOVÁ 1971; A. griseola H. NAGAN. & HIRAHARA 1970; A. inflata J.H. MIRZA, S.M.
KHAN, S. BEGUM & SHAGUFTA 1979; A. narayanai SUBRAHAMANYAM 1990; A. robusta
RACIBORSKI 1899; A. tuneta RENNER & MUSKAT 1958; A. ushtrina S.C. ARARWAL 1974.
19.7
Molecular Key to the Genera
The augmentation of generally easy-to-access morphological data with molecular
characteristics will support the current concepts of species relationships to specific
genera. Sequences of the nuclear internal transcribed spacer (ITS) region already
19
Identification of the Genus Absidia
5` GGCACRGTTGTTTCAGTATC
3`
5` CCGGWGRGKACGCCTG
3`
5` GGTACGYCTGTTTCAGTATCATT 3`
18S rDNA
453
Lichtheimia
Lentamyces
Absidia
ITS1
5.8S rDNA
5` GGAAGGATCATTACTGAGAGG
3`
5` CGGAAGGATCATTAMTGTTTWTG 3`
5` TGCGGAAGGATCATTARAAATG 3`
Lichtheimia
Lentamyces
Absidia
5` GATCTGAAATCAACTGAGAYYAC 3`
5` GYCTGAAATCAGGTGGGATTAC 3`
5` TTGATCTGAAATCAGRYGGGA
3`
ITS2
28S rDNA
5` ATGGATCTCTTGGTTCTCGCA 3`
5` CGGATCTCTTGGTTCTCGCA
3`
5` TGGATCTCTCGGCTTTCGTATC 3`
Fig. 19.2 Schematic illustration of the nuclear ribosomal DNA cluster including internal transcribed spacer regions (ITS) 1 and 2 with short signature sequences to differentiate between the
genera Absidia sensu stricto, Lentamyces and Lichtheimia. Signature sequences are located at the
18S rDNA – ITS1 boundary, at the 50 and 30 end of the 5.8S rDNA, and at the 50 end of the 28S
rDNA. Positions of the signature sequences could slightly vary
…C TCGAG…
Lentamyces …GAGCT C…
Lichtheimia ramosa AY944897
18S rDNA
ITS1
Absidia
5.8S rDNA
ITS2
28S rDNA
…TCG CGA…
…AGC GCT…
Fig. 19.3 Schematic illustration of the nuclear ribosomal DNA cluster including internal transcribed spacer regions (ITS) 1 and 2 with unique restriction sites useful for the discrimination of
the genera Absidia sensu stricto, Lentamyces and Lichtheimia. Species in the genus Absidia sensu
stricto possess a unique restriction site for the enzyme Bsp68I (NruI, recognizing the motif
TCGCGA) near the 50 end of the 5.8S rDNA, cutting ITS sequences (between 500–700 bp) in
two fragments nearly about the same size. In the middle of the ITS1 sequence (around position
100) is a XhoI restriction site located (recognizing the motif CTCGAG), unique for the genus
Lentamyces. With the exception AY944897 both sequence motifs occur not within sequences of
the genus Lichtheimia
proved to be useful for species designation and phylogenetic analyzes concerning
members of the genera Absidia, Lentamyces and Lichtheimia (Machouart et al.
2006; Schwarz et al. 2006; Hoffmann et al. 2007, 2009a). Several ITS sequences
available from GenBank (www.ncbi.nlm.nih.gov; listed in the methodical Sect. 9.3.)
were analyzed for short sequence fragments useful to differentiate between genera
(Fig. 19.2). Signature sequences are located at the nuclear 18S ribosomal DNA –
ITS1 boundary, at the 50 and at the 30 end of the 5.8S rDNA, and at the 50 end of the
28S rDNA. Positions of the signature sequences could slightly vary.
Furthermore, restriction site analyzes of the sequenced PCR products revealed
unique sites potentially useful for differentiation of the genera (Fig. 19.3). Within
Absidia sensu stricto the enzyme Bsp68I (TCG CGA) cuts the total ITS sequences
within the 5.8S rDNA region in two fragments nearly about the same size. There is
no Bsp68I restriction site within the analyzed sequences of species belonging to the
454
K. Hoffmann
genera Lentamyces or Lichtheimia (or Siepmannia). A unique recognition site for
the enzyme XhoI is present within Lentamyces (but not within Siepmannia), nearly
half cutting ITS1 (around position 100 of the total ITS1-5.8S rDNA-ITS2
sequence). Absidia and Lichtheimia show no XhoI restriction site with one exception. The ITS1 region of Lichtheimia ramosa (AY944897) is restricted by XhoI
after two-thirds (Fig. 19.3).
19.8
Combining Morphological and Molecular Characters:
An Example
Bearing in mind that the name of a type strain is intrinsically tied to its morphological features, a molecular-based identification should not neglect a profound check on
morphology. One example is illustrated by Absidia repens. This species is characterized by the presence of uniquely formed secondary sporangia beneath typical
Absidia-like sporangia. A. repens is one of the few species with available sequences
from different geographical populations. In Fig. 19.4. an alignment of three isolates
is displayed. Two isolates are from America (A) and the isotype is from Europe (E).
Both American isolates are similar to each other with 95% identity but differ
considerably from the European isolate (52% identity). As already outlined in detail
by Hoffmann et al. 2009a, information on the geographical origin could solve
differences within isolates caused by geographically-based species deviation and
will eventually support the erection of new formae, varieties or even species. Such
a cryptic species with no obvious morphological differences is A. repens, but a
separation in two distinct species requires a more profound investigation of the
already described isolates. A synonym of A. repens, namely A. japonica, was
isolated in Japan and may easily represent a distinct cryptic species.
19.9
Methodological Section
19.9.1 Media for Cultivation
Media for cultivation, mentioned in the description keys were PDA (see DSMZ
medium 129), Czapek-Agar (see DSMZ medium 130) and MEX (3% malt extract
supplemented with 0.5% yeast extract); YEA (yeast extract, Difco, Alphen a/d Rijn,
The Netherlands); MEA (malt extract, Difco).
19.9.2 Methods for Strain Maintenance, Cultivation,
and Sequence Analyses
Methods for strain maintenance, cultivation, and sequence analyses were
previously described by Hoffmann et al. (2007) and Hoffmann and Voigt (2008).
19
Identification of the Genus Absidia
455
CBS101.32(A)1 -------------------------------------------------- 50
KAS3611 (A) 1 -------------------------------------------------- 50
CBS115583(E)1 GAAATGCTGGGAAGCCTCCGGGAGGACCTAACTTTTTTCTACTGGTCCCT 50
CBS101.32
KAS3611
CBS115583
51 -------------------------------------------------- 100
51 -------------------------------------------------- 100
51 TGTTTTTTTAGGGGGTTGCTTGGGAAGGGATTCGTTTCTTCCCTTGATGT 100
CBS101.32 101 -----AAAATGCGGCCGGTTCTCTTTCGGGAGGATTGGTCAACAGATTTA 150
KAS3611
101 -----AAAATGCGGCTGGCTCTCTTT--GGAGGGTTGGTCAACAGATTTA 150
CBS115583 101 TTGGGGGAATTTTATTATTCCCCCTTCATGGGAAAGTTTTACTACTTTCC 150
CBS101.32 151 ATTCTGTGCACTGTTTTTAATTGGGGGTTTTCTTGAAAAAGGGAGCCTCC 200
KAS3611
151 ATTCTGTGCACTGTTTTTAATTGGGGGTTTTCTTGAAAAAGGGAGCCTCC 200
CBS115583 151 CCTTCTCCCACCCTGGGTAAA-GCCCTTTTTCCTTTGGGAGAATCCGGTT 200
CBS101.32 201 TGCCCTGG-GTATTGCTCTTTTTCCTTTGGGAAGAAATCAGCTTGCCCTA 250
KAS3611
201 TGCCCTGG-GTATTGCTCTTTTTCCTTTGGGAAGAAATCAGCTTGCCCTA 250
CBS115583 201 TGCCCAGTTGAATTCCCCTTCTTTCATAGGGGGGGGG-----TTTTCAAG 250
CBS101.32 251 TTAATATACTATTCTGACTGAACTAAAACAGAAAATTGTTTAACACATAA 300
KAS3611
251 TTAATATACTATTCTGACTGAACTAAAACAGAAAATTGTTTAACATATAA 300
CBS115583 251 TTTATATACTATTTTGACTGAACTAAA-CAGAAA-TTGTTTAACACTTAA 300
CBS101.32 301 ACAACTTTCAGCAATGGATCTCTCGGCTTTCGTATCGATGAAGAACGCAG 350
KAS3611
301 ACAACTTTCAGCAATGGATCTCTCGGCTTTCGTATCGATGAAGAACGCAG 350
CBS115583 301 ACAACTTTCAGCAATGGATCTCTCGGCTTTCGTATCGATGAAGAACGCAG 350
CBS101.32 351 CAAATCGCGATATGTAGTGTGATCTGCCTATAGTGAATCATCAAATCTTT 400
KAS3611
351 CAAATCGCGATATGTAGTGTGATCTGCCTATAGTGAATCATCAAATCTTT 400
CBS115583 351 CAAATCGCGATATGTAGTGTGATCTGCCTATAGTGAATCATCAAATCTTT 400
CBS101.32 401 GAACGCATCTTGCACCCTTGGGTATTCCTGAGGGTACGCCTGTTTCAGTA 450
KAS3611
401 GAACGCATCTTGCACCCTTGGGTATTCCTGAGGGTACGCCTGTTTCAGTA 450
CBS115583 401 GAACGCATCTTGCACCCTTGGGTATTCCTGAGGGTACCCCTGTTTCAGTA 450
CBS101.32 451 TCATTTTAACTTCATCTCCTTTCGAGGGGTTTG----------AAAAAAT 500
KAS3611
451 TCATTTTAACTTCATCTCCTTTCGAGGG-TTTG----------AAAAAAT 500
CBS115583 451 TCATTTTTATCTTCTTTCCCGTCCTTAGGTTGGTGGGGAAGGGGAAAAAT 500
CBS101.32 501 CACTACTGGCCATTGAGTACCTTTGT------GTATTTCTCGGCTGAAAT 550
KAS3611
501 CACTACTGGCCATTGAGTACTTTATT------GTGCTTCTCGGCTGAAAT 550
CBS115583 501 CAC-ACTCGCC-TAGAGTACTAGTTTAGACCGGTGCTTCTTGGCTGAAAT 550
CBS101.32 601 AATCT-TATGGTTTCCCTTATGACTGGGGGCAATTACCCTTTGGTAGAAT 600
KAS3611
601 AATTT-TATGGTTTCCCTTATGACTGGGGGCAATTACCCTTTGGTAGAAT 600
CBS115583 601 TATTGATACAGTTTTCCCTTTGACTTTAAAGGGGTACCCTTTGGTAGCCT 600
CBS101.32 651 TTATTTTTTACAAAAGAAAAAATTGAAGCCAGTCTAGAAGCTATACCGTC 650
KAS3611
651 TCATTTTTTACAAAAGAAACAATTGAAGCCAGTCTAGAAGTCATACCTTC 650
CBS115583 651 TTC----------------------------------------------- 650
CBS101.32 701 GAAAGACAACCCCAAAAA 718
KAS3611
701 --------ACCCCAAAAA 718
CBS115583 701 ------------------ 718
Fig. 19.4 Alignment of sequenced ITS1-5.8S rDNA-ITS2 regions from three different isolates of
Absidia repens. CBS101.32 and KAS3611 were isolated in America (A). The isotype of the
species is of European origin (E). The European isolate differs primarily by a major indel
(insertion/deletion) within ITS1 as well as unambiguously aligned regions within ITS1 and ITS2
of the American strains
456
K. Hoffmann
Bayesian inference was done using MrBayes v3.1.2 (Huelsenbeck and Ronquist
2001; Ronquist and Huelsenbeck 2003). The alignment consists of combined
sequences of partial 18S rDNA (1202 characters), partial 28S rDNA (389 characters), partial sequences coding for act (807 characters) and tef (1092 characters).
Table 19.3 Species and GenBank accession numbers studied in the Bayesian inference (Fig. 19.1)
Species
GenBank accession numbers
act
tef
18S rDNA
28S rDNA
Absidia caerulea
EU736223
EU736245
EU736272
EU736299
A. californica
EU736224
EU736247
EU736274
EU736301
A. glauca
EU736225
EU736248
EU736275
EU736302
A. macrospora
AY944760
EU736249
EU736276
EU736303
A. psychrophilia
AY944762
EU736252
EU736279
EU736306
A. repens
AJ287136
AF157228
AF113410
AF113448
A. spinosa
EU736227
EU736253
EU736280
EU736307
Blakeslea trispora
AJ287143
AF157235
AF157124
AF157178
Chaetocladium brefeldii
AJ287144
AF157236
AF157125
AF157179
Chlamydoabsidia padenii
AJ287146
AF157238
AF113415
AF113453
Choanephora cucurbitarum
AJ287147
AF157239
AF157127
AF157181
Cunninghamella bertholletiae
AJ287151
AF157243
AF113421
AF113459
C. echinulata
AJ287152
AF157244
AF157130
AF157184
Dichotomocladium elegans
AJ287153
AF157245
AF157131
AF157185
Gongronella butleri
AJ287160
AF157252
AF157137
AF157191
Halteromyces radiatus
AJ287161
AF157253
AF157138
AF157192
Hesseltinella vesiculosa
AJ287163
AF157255
AF157140
AF157194
Lentamyces parricida
AY944761
EU736250
EU736277
EU736304
L. zychae
EU736228
EU736255
EU736282
EU736309
Lichtheimia corymbifera
AJ287134
AF157227
AF113407
AF113445
L. hyalospora
AJ287132
AF157225
AF157117
AF157171
L. hyalospora
EF030531
EU826384
EU826360
EU826368
EU826377a
EU826382a
EU826361a
EU826370a
L. ramosaa
Mortierella alpina
EU736236
EU736263
EU736290
EU736317
M. multidivaricata
AJ287168
AF157260
AF157144
AF157198
M. verticillata
AJ287170
AF157262
AF157145
AF157199
Mucor racemosus
AJ287177
AF157268
AF113430
AF113471
Mycotypha africana
AJ287180
AF157271
AF157147
AF157201
M. microspora
AJ287181
AF157272
AF157148
AF157202
Parasitella parasitica
AJ287182
AF157273
AF157149
AF157203
Phycomyces blakesleeanus
AJ287184
AF157275
AF157151
AF157205
Radiomyces spectabilis
AJ287190
AF157281
AF157157
AF157211
Rhizomucor miehei
AJ287191
AF157282
AF113432
AF113473
R. pusillus
AJ287192
AF157283
AF113433
AF113474
Rhizopus oryzae
AJ287198
AF157289
AF113440
AF113481
R. stolonifer
AJ287199
AF157290
AF113441
AF113482
Saksenaea vasiformis
AJ287200
AF157291
AF113442
AF113483
Spinellus fusiger
AJ287201
AF157292
AF157159
AF157213
Thermomucor indicae-seudaticae
AJ287208
AF157299
AF157165
AF157219
Umbelopsis isabellina
AJ287209
AF157300
AF157166
AF157220
U. nana
AJ287210
AF157301
AF157167
AF157221
U. ramanniana
AJ287166
AF157258
X89435
AF113463
a
described as Absidia idahoensis var. thermophila (Chen and Zheng 1998); sequences generated in
this study
19
Identification of the Genus Absidia
457
Forty-two taxa were included, using three species of Mortierella as outgroup
(Table 19.3). Starting from a random tree, two runs, each with four chains, were
conducted for 5,000,000 generations. Thousand trees were sampled per run. The
consensus tree was calculated using the halfcompat option with a 25% burn-in. The
node confidence values (posterior probabilities, in percent) are shown above
the branches in Fig. 19.1.
19.9.3 PCR-RFLP and Sequence Analysis
ITS sequences were retrieved from GenBank (www.ncbi.nlm.nih.gov). Sequences
for the genus Lichtheimia: L. blakesleeana (AY944892-4, EF030530), L. corymbifera/ramosa (DQ118984, DQ118982, AY944895, AY944897, AY944896); genus
Lentamyces: L. parricida (AY944884/5), L. zychae (EF030529/AJ968561); genus
Absidia sensu stricto: A. californica (AY944872/3), A. caerulea (AY944866-71),
A. macrospora (AY944882/3), A. glauca (AY944875-81), A. spinosa (AY944886-8),
A. repens (EF030527/8, AY944890/1, AJ877962, FJ849793), A. pseudocylindrospora (EF030525/6); A. anomala (EF030523), A. cylindrospora (AY944889),
A. psychrophilia (AY944874), A. cuneospora (EF030524); genus Siepmannia:
S. pineti (AJ748134), S. lariceti (AJ748857); Mucor circinelloides (AJ878535);
Fennellomyces linderi (AJ878536). In silico restriction analysis as well as calculation
of sequence similarities was done using BioEdit v.7.0.9.0 (Hall 1999).
Acknowledgments This work was supported by a grant of the Deutsche Forschungsgemeinschaft
(VO 772/9-1) and by the Thüringer Ministerium für Wissenschaft, Forschung und Kunst. The
author wishes to express her gratitude to Kerstin Voigt (University of Jena, Germany) and Grit
Walther (CBS, Centraalbureau voor Schimmelcultures Utrecht, The Netherlands) for critically
reading the manuscript and valuable advices, to Keith A. Seifert (Eastern Cereal and Oilseed
Research Centre, Agriculture and Agri-Food Ottawa, Ontario, Canada) for kindly providing a
culture and sequence information of Absidia repens KAS3611, to Ru-yong Zheng (Key Laboratory of Systematic Mycology and Lichenology, Institute of Microbiology, Chinese Academy of
Sciences, Beijing, China) for providing Absidia idahoensis var. thermophila strain AS 3.4808 and
to Gisela Baumbach for excellent assistance in strain maintenance.
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Chapter 20
Molecular Characters of Zygomycetous Fungi
Xiao-yong Liu and Kerstin Voigt
Abstract The traditional Zygomycota has recently been considered polyphyletic
as evidenced by a lot of molecular phylogenetic analyses. As a result, it has been
distributed into a new phylum and four pending subphyla. Before the taxonomic
status for these four subphyla could be determined, the term “zygomycetous fungi”
is used for those members traditionally included in the classical phylum Zygomycota. Most current molecular characters of zygomycetous fungi have revealed that
there is an obvious conflict between the traditional morphology-based classification
scheme and recent DNA-based phylogenies. Except for the notable adjustments at
the phylum and subphylum level, major changes at the order level can be observed
for Amoebidiales, Basidiobolales, Eccrinales, Entomophthorales, Geosiphonales
and Mortierellales. With respect to families, studies on the order Mucorales have
suggested an unnatural feature for its traditional family-level classification scheme.
Some genera such as Absidia, Cunninghamella and Rhizopus have also been
intensively investigated by molecular methods. Genes encoding glucoamylases,
polygalacturonases, fumaric acids and polyunsaturated fatty acids, have been
intensively studied for industrial purposes. Another important area is the study of
the clinical relevance of zygomycetous fungi as pathogens. The poor sensitivity of
histological practices, the difficult pure cultivation, and the inaccurate susceptibility
and serological tests, have led to the development of highly sensitive and specific
molecular techniques, such as microsatellite, oligonucleotide probes, microarrays
of gene markers and their expression, fluorescent capillary electrophoresis, realtime PCR (polymerase chain reaction), PCR-RFLP (PCR-restriction fragment
X-y. Liu
Key Laboratory of Systematic Mycology and Lichenology, Institute of Microbiology, Chinese
Academy of Sciences, No. 1 Beichen West Road, Chaoyang District, Beijing 100101, P. R. China
e-mail: liuxiaoyong@im.ac.cn
K. Voigt
Institute of Microbiology, School of Biology and Pharmacy, University of Jena, Neugasse 25,
07743 Jena, Germany
e-mail: kerstin.voigt@uni-jena.de
Y. Gherbawy and K. Voigt (eds.), Molecular Identification of Fungi,
DOI 10.1007/978-3-642-05042-8_20, # Springer-Verlag Berlin Heidelberg 2010
461
462
X-y. Liu and K. Voigt
length polymorphism), RAPD (randomly amplified polymorphic DNA), PFGE
(Pulsed Field Gel Electrophoresis), and direct sequencing of PCR products, but
these methods are not widely available and are reserved primarily for research
purposes. New techniques in the molecular identification of zygomycetous fungi
need to be further developed and validated. So far, there are only five genome
projects relevant to zygomycetous fungi, including Mortierella verticillata, Mucor
circinelloides, Phycomyces blakesleeanus, Rhizopus arrhizus, and Smittium culisetae. More genome projects about industrially, agriculturally, medically and
environmentally important zygomycetous fungi are hopeful to provide a better
understanding of their natural status in the whole organismic system in the world
and their potential to benefit the human being.
20.1
Introduction
The phylum Zygomycota in the kingdom Fungi was first proposed by Moreau
(1954), but it is invalid and consequently illegal because of a lack of Latin diagnosis
or description, which is mandatory for descriptions on or after 1 January 1935
according to the International Code of Botanical Nomenclature (McNeill et al.
2006). Nevertheless, the name Zygomycota has still been recognized by most
investigators for more than a semicentury and its members have been gradually
increasing until the prosperity of molecular phylogenetic studies triggered by the
proposal of universal primers for different rRNA genes and spacers in the early
1990s (White et al. 1990).
Recently, the majority of molecular evidences strongly suggested that the
traditional Zygomycota is not monophyletic (Tanabe et al. 2005; James et al.
2006), though its monophyletic feature was supported by the result of analyzing
the sequences of genes rpb1 and rpb2 (Liu et al. 2006). In the most recent
classification of the kingdom Fungi in light of numerous molecular phylogenetic
studies, the widely accepted phylum Zygomycota was temporarily rejected and the
taxa that have formerly been placed in it were distributed into five parts, including
the phylum Glomeromycota and four subphyla of uncertain position (incertae
sedis), namely Entomophthoromycotina, Kickxellomycotina, Mucoromycotina,
and Zoopagomycotina (Hibbett et al. 2007). A three-protein phylogeny, shown in
Fig. 20.1, demonstrates the phylogenetic positions of the former three subphyla
with the exception of the Zoopagomycotina based on concatenation of translation
elongation factor 1alpha, actin and beta tubulin amino acid sequences shown in
Table 20.1. The notable taxonomic change of dispersing Zygomycota into different
clades reflects to a great extent the current progress on molecular systematics of this
basal fungal phylum, even though significant questions are left behind, such as the
pending attribution of the four subphyla mentioned above in the kingdom of Fungi.
As compared with the molecular polyphyletic trait of the classical phylum
Zygomycota, its diversity in ecological distribution was also well known for a
long period of time, ever since the very beginning of the establishment of this
20
Molecular Characters of Zygomycetous Fungi
463
Fig. 20.1 Concatenated phylogenetic analysis based on a total of 1,262 aligned amino acid
characters comprising 500 characters of the translation elongation factor 1 alpha (TEF), 323
characters of actin (ACT) and 439 characters of beta-tubulin (BTUB) from sixty five taxa
(Table 20.1). Single alignments were carried out using ClustalX version 1.83 (Higgins and
Sharp 1988, 1989; Thompson et al. 1997). Neighbor-joining with distance measure mean character
464
X-y. Liu and K. Voigt
phylum. Mucorales and Kickxellales are saprobes, the order Entomophthorales
comprises obligate parasites of insects, Dimargaritales and Zoopagales are obligate
parasites of microorganisms, Asellariales and Harpellales are endocommensals in
crustacean guts, and the species of the order Endogonales are ectomycorrhizae.
Taking into account the ecological diversity and the molecular polyphyly as well as
the invalid naming for the phylum rank, the organisms that have long been included
in the traditional Zygomycota refer to zygomycetous fungi in this chapter. That
term is far from a new name but is widely accepted by lots of investigators. Here the
range of zygomycetous fungi will exclude what is now classified as Glomeromycota, which is a phylum of proven acceptance in the kingdom of Fungi (Schübler
et al. 2001). Furthermore, the Eccrinales and the Amoebidiales will be excluded
from the zygomycetous fungi sensu stricto. Both orders were considered as members of Trichomycetes and now have moved on to a protistan class, the Mesomycetozoea (Cafaro 2005). An extra point worth noticing here targets the Microsporidia,
for which zygomycete origin was suggested (Keeling et al. 2000; Keeling 2003)
besides the fact that this group will not be included into the zygomycetous fungi in
this chapter because of the many evidences revealing its protistan and nonfungal
origin influencing its nomenclatural status (Forget et al. 2002; Gill and Fast 2006; Liu
et al. 2006).
The morphological taxonomy of zygomycetous fungi was extensively investigated
during the last 50 years by some experts (Benjamin 1959, 1966, 1979; Hesseltine and
Ellis 1973; O’Donnell 1979; Benny 1982; Lichtwardt 1986; Humber 1989; Benny
et al. 2001) and intensively probed by more mycologists with a certain genus as
research interests: Absidia (Hesseltine and Ellis 1964); Cunninghamella (Zheng and
Chen 2001); Mortierella (Gams 1977); Mucor (Schipper 1973, 1975, 1976, 1978);
Rhizopus (Zheng et al. 2007) etc. These studies circumscribe large genera if compared
with genera within the derived fungi, the Asco- and Basidiomycota. For more details
on numerous other genera and higher ranks in the zygomycetous fungi as well, it is
worth to visit the open website www.zygomycetes.org by Gerald L. Benny which
provides a great diversity and a wonderful overview about the zygomycetes.
Looking back into the history, besides morphology, many other molecular and
chemical traits such as sterols, fatty acids, nucleic acids, and proteins, were also
applied for the identification and the classification of zygomycetous fungi. An
investigation of sterol composition of zygomycetous fungi suggested that orders
can be distinguished by different sterol chemotypes (Weete and Gandhi 1997).
Excitingly, six new ergosterols from a marine zygomycetous fungus were found,
providing an evidence for the importance to study on organisms in its endemic
habitat (Wang et al. 2008). Regarding fatty acids, there are a few studies, which
<
Fig. 20.1 (continued) difference was conducted with PAUP*v4.0b10 (Swofford 1998); negative
branch lengths were prohibited. Bootstrap supports (BS) (Felsenstein 1985; 50% majority rule)
were obtained by 1,000 bootstrap replicates of a neighbor-joining search using mean character
differences as distance measure as implemented in PAUP*v4.0b10. The tree was rooted to the
elongation factor Tu and to the cytoskeletal proteins FtsZ (homologous to tubulin) and MreB
(homologous to actin), the latter two first discovered in the thermophilic eubacterium Thermotoga
maritima (van den Ent et al. 2001), facilitating deep-level phylogenies beyond the divergence of
prokaryotes and eukaryotes. Names printed in red colour indicate taxa designated to the zygomycetes
20
Molecular Characters of Zygomycetous Fungi
465
Table 20.1 Protein sequences retrieved from the International Nucleotide Sequence Database
Collaboration and genome projects (see footnotes) with corresponding accession numbers for the
corresponding nucleotide sequences. The aligned amino acid sequences were subjected to distance
based phylogenetic analyses shown in Fig. 20.1
Genus
GenBank acc. nos.
ACT
TEF
BTUB
Acanthamoeba
V00002
AY582829
AY582853
Acrasis
–
AF190771
AF276945
Allomyces
Unpublished
Unpublished
AY131269
Anaeromyces
Unpublished
Unpublished
Unpublished
Aphanomyces
–
EF370041
EF370043
Arabidopsis
U41998
X16430
M20405
Aspergillus
M22869
AB007770
M17519
Basidiobolus
–
DQ282610
AF162060
e_gw1.2.331.1
estExt_40375
estExt_C_90068
Batrachochytriuma
Bigelowiella
EF455788
AY729489
EF455767
Bombyx
X05185
D13338
X74951
Candida
X16377
M29934
M19398
Capsaspora
AY724689
DQ403163
–
Catenaria
Unpublished
Unpublished
AY944844
Chytriomyces
AY582841
AY582823
AY944845
Coemansia
–
DQ282615
AY944833
Conidiobolus
–
DQ275337
AF162058
Coprinus
AB034637
AY881026
AB000116
Corallochytrium
AY582844
X55973
AY582850
Dictyostelium
X03283
DQ282609
AF030823
Drosophila
AB003910
X06869
M20419
Encephalitozoon
AF031701
NC_003231
AF297876
Entamoeba
M19871
M92073
AF247192
Entomophthora
EF434860
ABB84538
AY944832
Gallus
X00182
L00677
M11442
Giardia
L29032
D14342
X06748
Glugea
–
D84253
AF162084
Glycine
J01298
X56856
M21296
Harpochytrium
–
AF450113
AF162079
Histoplasma
U17498
U14100
M28359
Homo
M10277
X03558
X00734
Hydra
XP_002154696
D79977
XM_002161824
Leishmania
L16961
XM_001682206
AF345947
Lichtheimia
AJ287134
AF157227
L47261
Ministeria
AY582846
AY582825
AY582851
Monoblepharis
–
AF450112
AY944851
Monosiga
AY026072
AY026073
AY026071
Mortierella
AJ287170
AF157262
AF162071
estExt_C_40513
estExt_C_40175
gw1.3.598.1
Mucora
Naegleria
AF101729
DQ295229
X81050
Neoparamoeba
EU089662
FJ807261
–
Neurospora
U78026
D45837
M13630
Nosema
AF031702
AY452734
AY138803
Nuclearia
AY582845
AY582827
AY582852
Orpinomyces
Unpublished
Unpublished
Unpublished
Oryza
X16280
AF030517
X79367
(continued)
466
X-y. Liu and K. Voigt
Table 20.1 (continued)
Genus
ACT
Phycomycesa
estExt_Genewise
1.C_340013
Physarum
X07792
Phytophthora
M59715
Plasmodiophora
AM411664
Pythium
X76725
Reticulomyxa
AJ132374
RO3G_14002.3
Rhizopusb
Saccharomyces
L00026
Schizophyllum
AF156157
Smittium
AY582840
Sphaeroforma
AJ780965
Stephanopogon
EF455777
Suillus
AF155931
Trichoderma
X75421
Trichomonas
U63124
Trypanosoma
M20310
Umbelopsis
AJ287166
Zea
J01238
Thermotoga
NP_228398
a
Genome projects at http://genome.jgi-psf.org/
b
Genome project at http://www.broadinstitute.org
GenBank acc. nos.
TEF
e_gw1.2.294.1
AF016243
AJ249839
AM411655
DQ911417
EU810334
RO3G_15351.3
M10992
X94913
AY582822
DQ403164
FJ807246
AY883429
Z23012
–
U10562
AF157258
D45408
M27479
BTUB
estExt_20134
M20191
U22050
AM411665
AF218256
X96477
RO3G_06151.3
V01296
X63372
AY944829
–
EF455757
AY112730
Z15054
L05468
K02836
AF162073
X52878
U65944
were reviewed by Kock and Botha (1998) and Frisvad et al. (2008). Because of the
inconsistent quality throughout the zygomycetous fungi, no studies on fatty acids at
higher taxonomic levels, from phylum to family, have been reported so far. But it is
the very inconsistence that makes fatty acids so useful in lower rank’s taxonomy.
Therefore at or below genus level applying comparatively few numbers of isolates
as representatives, fatty acids were proven to be a potential marker for identification
and classification as different genera, subgenera, or even species that can exhibit
distinctive profiles (Amano et al. 1992; Blomquist et al. 1992; Weete et al. 1998;
Weete and Gandhi 1999; Batrakov et al. 2002, 2004). Moving on to the nucleotide
and protein aspects, there are far more papers than on the previously mentioned
characters. Using “Zygomycota” as inquiry, more than 5,000 references for literature can nowadays be retrieved from the National Center for Biotechnology Information (www.ncbi.nlm.nih.gov) alone. This article will make an effort to give a
sketchy review from such a considerably large number of publications on nucleic
acids as well as proteins.
20.2
Molecular Characters for Classifying Zygomycetous Fungi
It usually tends to be called molecular phylogeny or equivalents when DNA
data are used to identify and classify organisms because they are believed to
contain original, genetic and evolutionary information. Most current DNA data
20
Molecular Characters of Zygomycetous Fungi
467
Table 20.2 Comparison of traditional Zygomycota and current zygomycetous fungi
Hawksworth et al. (1995)
Kirk et al. (2001)
Hibbett et al. (2007)
ZYGOMYCOTA
ZYGOMYCOTA
GLOMEROMYCOTA
Zygomycetes
Zygomycetes
Glomeromycetes
1. Geosiphonales
1. Glomales
2. Glomales
1. Glomerales
SUBPHYLA INCERTAE SEDIS
Entomophthoromycotina
2. Entomophthorales
3. Entomophthorales
1. Entomophthorales
Basidiobolaceae
4. Basidiobolales
3. Endogonales
Mortierellaceae
4. Mucorales
5. Endogonales
6. Mortierellales
7. Mucorales
Mucoromycotina
1. Endogonales
2. Mortierellales
3. Mucorales
5. Zoopagales
8. Zoopagales
Zoopagomycotina
1. Zoopagales
6. Dimargaritales
7. Kickxellales
9. Dimargaritales
10. Kickxellales
Kickxellomycotina
1. Dimargaritales
2. Kickxellales
Trichomycetes
1. Asellariales
2. Harpellales
3. Amoebidiales
4. Eccrinales
Trichomycetes
1. Asellariales
2. Harpellales
3. Asellariales
4. Harpellales
3. Eccrinales
from zygomycetous fungi have revealed that there is obviously a conflict between
traditional morphology-based classification scheme and recent DNA-based phylogenetic one. Above the level of orders this inconsistence has led to a distribution of
traditional Zygomycota among five clades, including Glomeromycota, Mucoromycotina, Kickxellomycotina, Entomophthoromycotina, and Zoopagomycotina (Hibbett
et al. 2007).
From the comparison of the current zygomycetous fungi with the last two
editions of Ainsworth and Bisby’s Dictionary of the Fungi (Table 20.2), four
major points of status changes at the order level can be observed.
20.2.1 Amoebidiales and Eccrinales
Eccrinales and Amoebidiales, sharing ecological niche — the arthropod gut with
other orders of the class Trichomycetes, were thought to be members of this class
(Lichtwardt 1986). At the same time there were lots of opposites concerning its
affinity with Trichomycetes based on the lack of a septal pore and associated plug,
the presence of dictyosomes (Moss 1999), the lack of chitin in their cell wall
(Trotter and Whisler 1965), and the distant relationships in rDNA phylogenies
(Benny and O’Donnell 2000; Ustinova et al. 2000; Mendoza et al. 2002; Cafaro
2005). Therefore they are now excluded from the zygomycetous fungi. However,
both of the remaining orders of the former Trichomycetes, the Asellariales and the
468
X-y. Liu and K. Voigt
Harpellales still remain among the zygomycetous fungi. Zygospores were reported
in species of the Asellariales (Valle and Cafaro 2008). The Harpellales is phylogenetically closely related to the Kickxellales (Benny and O’Donnell 2000) and
classified now to the Kickxellomycotina (Hibbett et al. 2007).
20.2.2 Basidiobolales
Basidiobolus was originally placed in the family Basidiobolaceae of the order
Entomophthorales, then raised as a separate order Basidiobolales (Cavalier-Smith
1998) and later adopted (Kirk et al. 2001), and end up now as not being placed
in any higher taxa. Why is that? Basidiobolus is currently the only genus of
nonzoospore forming fungi known to have a nucleus-associated organelle that
contain microtubules, suggesting a potential affinity between Basidiobolus and
Chytridiomycota, although the structure of the microtubules is somewhat different
(McKerracher and Heath 1985). In the phylogeny based on SSU rDNA, Basidiobolus did form a clade with many chytrids (James et al. 2000), whereas it was
grouped with some Zygomycetes in phylogenies of alpha-tubulin and beta-tubulin
and SSU rDNA (Nagahama et al. 1995; Jensen et al. 1998; Keeling et al. 2000;
Keeling 2003) and nested in a clade consisting of major zygomycetous fungi in a
stronger phylogeny of six genes (James et al. 2006). Based on ACT-BTUB-TEF
protein phylogenies Basidiobolus appears to be paraphyletic to the Entomophthoromycotina, but with no statistical branch (BS) support (Fig. 20.1). Ultra structural
and molecular characteristics congruously suggested that Basidiobolus might be a
transitional organism between chytrids and zygomycetous fungi.
20.2.3 Geosiphonales
Geosiphon was initially only given an unassigned zygomycete position as a genus
(Hawksworth et al. 1995), then became a member of Geomycetes (Ascomycota)
(Cavalier-Smith 1998), and later returned to Zygomycetes but with a certain
position of a separate order Geosiphonales (Kirk et al. 2001; Schübler et al.
2001). In the current classification it is once more apart from the zygomycetous
fungi and belongs to the Glomeromycota only reaching a level of family Geosiphonaceae (Hibbett et al. 2007; CABI_BioScience and Research 2008). The reason
for these remarkable changes in position is that Geosiphon is associated with
cyanobacteria, so different from its related taxa in Glomeromycota, which are all
symbionts of arbuscular mycorrhiza. This time it will be expected to stay more
stably because a series of papers about the Glomeromycota always revealed a
monophyly for the genus Geosiphon and other members of Glomeromycota as a
whole, even if a polyphyletic feature among them has also been discovered on the
basis of data from ribosomal RNA and some protein genes (Schübler et al. 2001;
Schübler 2002; Redecker and Raab 2006; Walker et al. 2007).
20
Molecular Characters of Zygomycetous Fungi
469
20.2.4 Mortierellales
Mortierellales was established by Cavalier-Smith (1998) based on a traditional
family Mortierellaceae in Mucorales, and this elevation in taxonomic status has
been supported by different molecular data including act, EF-1 alpha, and SSUITS-LSU rRNA genes (Gehrig et al. 1996; Voigt and Wöstemeyer 2001; Lutzoni
et al. 2004; Kwasna et al. 2006). While Hibbett et al. (2007) proposed the phylogenetic alliance of the Mortierellales with the Mucorales unified in the Mucoromycotina, Voigt et al. (2009) discovered a more derived phylogenetic relationship
between the Mortierellales and the Endogonales, which deserves the erection of a
new subphylum, the Mortierellomycotina ined.
20.2.5 Mucorales
In regard to families, the most remarkable studies are about the classification within
the order Mucorales. The artificial or unnatural feature of the traditional familylevel classification schemes for this order has been presented according to the
analyses of SSU, LSU rDNA, EF-1 alpha, and actin gene sequences (O’Donnell
et al. 2001; Voigt and Wöstemeyer 2001). Another gene, rpb1, was also proposed as
an alternative marker for Mucorales phylogenetic studies (Tanabe et al. 2004). As a
consequence of these data, G. L. Benny later integrated almost all families of
Mucorales, except Umbelopsidaceae, into a single family Mucoraceae sensu lato
(http://www.zygomycetes.org/), which was considered plausible (White et al.
2006). However, the recognition of families in ancient fungal lineages such as
mucoralean and other terrestrial fungi is rather tedious. For a rough estimation of
the origin and the radiation of mucoralean and allied fungi the following minimum
ages for the divergence of major clades may be used: (1) 1,000 million years for
the radiation of the major eukaryotic clades fungi, Metazoa and plants (Simon et al.
1993; Hightower and Meagher 1986), (2) the split of the Metazoa from the fungi
944–965 million years ago and (3) the divergence of Asco- and Basidiomycota
452–500 million years ago including (4) 440 million years for basidiomycete radiation and (5) 240 million years for radiation of the Pezizomycotina (for (2)–(5) see
Berbee and Taylor 2001; Taylor and Berbee 2006). The standard procedure for
molecular clocks is to plot averaged distances against time (Li and Graur 1999;
Wang et al. 1999). Now exploiting the molecular clock-like and linear evolution of
actin (Hightower and Meagher 1986; Berbee and Taylor 2001; Taylor and Berbee
2006) and other protein-coding genes commonly used for the assessment of evolutionary distances and phylogenetic trees (see Fig. 20.1 in this chapter; Fig. 2 in
Voigt and Wöstemeyer 2001), the Mucorales may have already originated in the
Late Cambrian, approximately 530 million years ago, and the origin of the Mortierellales dates to the Mid Devonian, 360 million years ago. Consequently, the
origin of the Mortierellales coincides with the manifestation the arbuscular endomycorrhizal fungi (Glomeromycota) 353–462 million years ago (Simon et al. 1993;
470
X-y. Liu and K. Voigt
Redecker et al 2000), whereas the Mucorales diverged as basal fungal lineage,
possibly before the appearance of the first land plants, 360–480 million years ago
(Simon et al. 1993; Hightower and Meagher 1986; Kenrick and Crane 1997; Berbee
and Taylor 2001; Taylor and Berbee 2006). These data qualify the Mucorales as one
of the earliest groups of recent land fungi on Earth, emerging before the availability
of terrestrial plants as carbon source. Support of that estimation is gained by the
putative localization of the radiation of the true fungi in the Early Paleozoic era,
about 650–700 million years ago, which agrees well with previous estimates
(Margulis 1981; Berbee and Taylor 2001; Taylor and Berbee 2006). It has to be
emphasized that those rough calculations gained minimum ages, which fit well with
fossil records (e.g., Redecker et al. 2000). Since fossil records define the time point
of the manifestation of a certain taxon, the minimum ages may be underestimated.
The suggestion of the ancient divergence between Glomeromycota from the Dikaryomycota (Asco- and Basidiomycota) 600 million years ago according to Redecker
et al. (2000) strengthens that hypothesis. Therefore, it can be concluded that the
Mucorales are more heterogenous and justify more than just two families. An
attempt to revise the family structure of the Mucorales based on four-locus phylogenies is shown in Chaps. 11 (Fig. 11.4) and 19 (Fig. 19.1).
Besides these significant shifts about subphyla, orders and families resulted from
modern molecular phylogenetic studies; there are some more emphases on different
genera of zygomycetous fungi.
20.2.5.1
Absidia
Absidia spp. are filamentous fungi that are cosmopolitan and ubiquitous in nature as
common environmental contaminants. They are found in plant debris and soil, as
well as being isolated from foods and indoor air environment. They often cause
food spoilage. It can transform steroids and produce rennin-like components,
whereas some species are opportunistic human pathogens. Absidia is characterized
by the branched and grouped sporangiophores carrying pyriform and relatively
small sporangia, and arising on stolons from points between the rhizoids, but not
opposite the rhizoids as in Rhizopus. Zygospores are formed on opposed, more or
less equal suspensors adorned with several appendages. Absidia was divided into
two parts: the subgenus Absidia in which the zygospores are surrounded by
suspensor appendages and the subgenus Mycocladus in which suspensor appendages are not produced (Hesseltine and Ellis 1964). On investigating the phylogenetic relationships between 16 Absidia species based on act and ITS1-5.8S-ITS2
rDNA sequences, a trichotomy relevant to mesophilic, thermotolerant, and mycoparasitic groups was reconstructed, which is concordant with the morphology of the
zygospores (Hoffmann et al. 2007). Furthermore based on the phylogenetic coherence of mesophilic and thermotolerant Absidia species, as well as other distinct
characteristics in morphology, the two groups were separated into two distinct
genera and placed in different family, Absidia (Absidiaceae) for the mesophilic
species and Mycocladus (as “Mycocladiaceae,” but orthographically correct
20
Molecular Characters of Zygomycetous Fungi
471
Mycocladaceae) for the thermotolerant species A. corymbifera, A. blakesleeana and
A. hyalospora (Hoffmann et al. 2007). But the type of species of Mycocladus,
M. verticillatus Beauverie was discovered to be a coculture between a mesophylic
and a mycoparasitic species of the former Absidia, and thus, not congeneric with the
other species of Mycocladus. Therefore, a new family was established for the
thermotolerant Absidia spp., the Lichtheimiaceae typified with Lichtheimia corymbifera (Cohn) Vuill. (Hoffmann et al. 2009b). For a more detailed review on the
classification and the identification of Absidia see Chap. 19.
20.2.5.2
Actinomucor
Actinomucor has been used in the fermentation of sufu (Chinese cheese). Only
two species, viz. A. elegans and A. taiwanensis, are generally accepted in this
small genus. The former is widespread and has already been found in many
countries, while the latter has been reported from China only. According to ITS
rDNA and EF-1 alpha sequence data, A. taiwanensis was reduced to varietal rank
under A. elegans as A. elegans var. meitauzae because A. taiwanensis is the same
fungus as Mucor meitauzae which was published in 1937, before A. taiwanensis
(Zheng and Liu 2005).
20.2.5.3
Cunninghamella
Cunninghamella is a filamentous fungus found in soil, plant material, animal material,
cheese, and Brazil nuts. In addition to being a common contaminant, it is an opportunistic fungus causing infections in immunocompromised hosts. Cunninghamella can
transform pantoprazole and amoxapine and can also produce gamma-linolenic acid,
chitin and chitosan. Classification of Cunninghamella has been based principally on
morphology of the sporangial and zygosporic states, maximum growth temperature,
mating compatibility and zygospore formation. In addition, ITS rDNA sequences has
been used as an important reference for species and variety delimitation, leading to the
recognition of 12 species and three varieties within the genus (Liu et al. 2001).
20.2.5.4
Pilaira
All members of Pilobolaceae are coprophilous and produce phototropic, almost
unbranched sporangiophores, which arise directly from substrate and terminate in
dark hemispheric columellate sporangia with persistent, cutinized walls. The genus
Pilaira is characterized by the absence of trophocysts and subsporangial swellings,
which are present in both Pilobolus and Utharomyces. Multigene phylogenetic
analyses supported the presence of trophocysts and subsporangial swellings as
synapomorphic characters by the separation of Pilaira from the core Pilobolaceae
sensus stricto (Voigt et al. 2009). Nine of the ten species documented by Index
472
X-y. Liu and K. Voigt
Fungorum of CABI Bioscience seem to be unique and have only been recorded
once in literature, while P. anomala is ubiquitous in Europe and America and has
been reported many times (Zheng and Liu 2009). Morphological studies have been
conducted with all the available strains: six and 15 respectively from China and
NRRL, resulting in recognition of five taxa including two new species and one new
combination (Zheng and Liu 2009). Molecular phylogeny of 21 worldwide available strains of Pilaira, including two new species recently proposed from China,
was reconstructed by using ITS rDNA and pyrG gene sequences (Liu et al. In
press). The two loci displayed different phylogenetic histories. Besides some
complete or partial concordances with morphology, several disagreements were
found suggesting that this genus is dynamic in lineage splitting.
20.2.5.5
Rhizomucor
The genus Rhizomucor is ubiquitous and commonly found in soil, compost heaps,
decaying fruit and vegetables. It produces highly efficient enzymes for flax retting,
milk clotting and lignocellulose degeneration. It is often associated with animal
diseases. As for human being, most species of Rhizomucor are opportunistic agents
causing zygomycosis. For successful treatments, it is critical to quickly and accurately identify the pathogen and then promptly and precisely apply antimycotics.
Morphologically, Rhizomucor is distinguished from Mucor by the presence of
stolons and rhizoids. Rhizomucor hitherto comprises six species and one variety
belonging to two groups by virtue of the maximum growth temperature, i.e., the
thermophilic and the mesophilic species. All these taxa can be well delimitated by
distinct characteristics besides the maximum growth temperature, and the key to the
species and varieties of Rhizomucor were provided by Zheng and Jiang (1995).
It seems very easy to distinguish Rhizomucor taxa from one another according to
numerous, stable, reliable and distinct morphological and physiochemical features.
However, the practical determinations of Rhizomucor species based on morphological
observations and sometimes physiochemical tests involve limitations, frequently
resulting in inaccurate identifications (Lukács et al. 2004). Moreover recent
molecular data have brought forth some new questions. The comparison of
morphology-based and DNA-based identifications suggested that some prior
reports concerning R. pusillus based on traditional methods might even represent
other zygomycetous fungi, such as Rhizopus and Mucor (Iwen et al. 2005;
Kontoyiannis et al. 2005). Different genes have shown different phylogenies
for the members of Rhizomucor. Nuclear SSU rDNA sequence data have
revealed that Rhizomucor were polyphyletic, with the thermophilic R. miehei
and R. pusillus being a sister group of the clade of Absidia corymbifera, and the
mesophilic R. variabilis being nested within the clade of seven species of Mucor
(Voigt et al. 1999). The LSU rDNA sequences demonstrated another phylogenetic relationship between Rhizomucor spp. and other members of Mucorales,
i.e., R. miehei and R. pusillus related next to Syncephalastrum racemosum rather
than A. corymbifera, and R. variabilis formed a clade with two species of Mucor
20
Molecular Characters of Zygomycetous Fungi
473
instead of seven. Exhaustive ITS1-5.8S-ITS2 phylogenies and identity matrices
revealed a close relationship between R. variabilis and M. hiemalis (Hoffmann
et al. 2009a). The combined data of SSU, LSU rDNA and EF-1 alpha sequences
showed that the species R. pusillus related more closely to Thermomucor
indicae-seudaticae than to S. racemosum or A. corymbifera (O’Donnell et al.
2001). Beside these questions about R. miehei, R. pusillus and R. variabilis, the
recognition of R. tauricus as a distinct species was doubted by some investigators based on isoenzyme patterns, ITS-RFLP, and RAPD (Vágvölgyi et al. 1999;
Vastag et al. 2000). In order to solve the problems met in morphological and
physiochemical identification, molecular relationships based on cox1, cox2,
cox3, pyrG, and SSU+ITS1+5.8 S+ITS2 rDNA sequences, were analyzed with
a result of dichotomy relevant to mesophilic and thermophilic groups (Liu and
Zheng 2008).
20.2.5.6
Rhizopus
Members of Rhizopus are important as agents of food fermentation, agricultural and
food spoilage, human mucormycosis, and industrial and medical biotechnology.
They may occur as saprobes on plant debris, soil, and dung, or as air contaminants.
Rhizopus is characterized by apophysate sporangia, stolons on aerial mycelia, and
rhizoids developed from stolons and opposite sporangiophores. Rhizopus was
divided into two groups (R. microsporus Group and R. stolonifer Group) and one
species (R. oryzae Went & Prins. Geerl.) according to anamorphic morphology and
growth temperature (Schipper 1984; Schipper and Stalpers 1984). A recent monographic study of this genus based on morphology, maximum growth temperature,
mating compatibility, and molecular systematics has been conducted in which a
total of 17 taxa including ten species and seven varieties were recognized from a
global collection (Zheng et al. 2007). Concerning molecular studies on this genus,
some taxa have been involved for aiming at the resolution of high-level phylogeny
(Voigt et al. 1999; O’Donnell et al. 2001; Schwarz et al. 2006). ITS, 18S and 28S
rDNA sequences were used to investigate the molecular phylogeny of this genus
(Abe et al. 2003, 2006; Hoffmann et al. 2009a). For a more detailed review on the
molecular ITS-based identification of Rhizopus and allied genera see Chap. 11. ITS
rDNA and pyrG were also applied to support most of the morphological treatments
made recently, including the rejection of the level of group between genus and
species (Liu et al. 2007; Zheng et al. 2007). On the basis of nuclear ribosomal DNA
sequence and pyrG data, the distant relationship between the two varieties of
R. stolonifer, i.e., var. lyococcus and var. stolonifer, was observed but treated
differently: not reclassifying these two taxa (Abe et al. 2006), modifying the
taxonomical scheme of Schipper et al. with a new combination R. lyococcus
(Liou et al. 2007), or R. lyococcus being recognized as a synonym of R. reflexus
(Liu et al. 2007; Zheng et al. 2007). As for those varieties within R. arrhizus and
R. microsporus, IGS rDNA, especially the short tandem repeat motifs, was found to
be very useful for variety delimitation (Liu et al. 2008). The fumaric–malic acid
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X-y. Liu and K. Voigt
producer group of R. arrhizae was raised to a species level as R. delemar, differing
from the lactic acid producer group and confirmed by analyses of ITS rDNA, lactate
dehydrogenase B, actin, translation elongation factor-1alpha and AFLP (Amplified
Fragment Length Polymorphism) (Abe et al. 2007).
Thus, it is obvious that molecular studies mostly paid attention to those issues
that have long been questioned by traditional methods and actually addressed many,
if not all. Therefore the molecular data were proven to be a very important part of
the characters of zygomycetous fungi, not a separate and independent aspect.
Among these molecular markers, genes and spacers of ribosomal RNA are most
investigated, due to their universal primers, suitable fragment length and moderate
variation speed.
20.3
Molecular Characters in Industrial Zygomycetous Fungi
It is well-known that there are many products from zygomycetous fungi playing an
important role in industry, such as glucoamylase, polygalacturonase, fumaric acid
and polyunsaturated fatty acids (PUFAs). In addition to identification and classification, this article will also touch on topics of molecular characters in industrial fields.
20.3.1 Glucoamylase
Glucoamylase from Rhizopus arrhizus has long been of considerable importance to
the fermentation and food industries for saccharification of starch/amylopectin to
alcohol. Many commercial glucoamylase enzyme preparations are derived from
Rhizopus owing to their nearly complete conversion of starch to glucose. Glucoamylase has been isolated and characterized from a number of Rhizopus species
(Mertens and Skory 2007a, b).
20.3.2 Polygalacturonase
Flax has widely been used in textiles, high quality papers and composites. Retting is
one of the greatest problems in flax fiber production. Water-retting and dew-retting
were used in the past but are discarded nowadays due to different disadvantages
such as pollution and weather dependency. Alternative ideas for retting have been
developed, such as chemical retting using chelating agents and enzymatic retting
using suitable enzyme mixtures. The latter technique results in cleaner fibers of
higher and more consistent quality. The retting efficiency varied considerably
between different organisms. Rhizopus oryzae (=R. arrhizus) produced extracellular enzymes that could independently degrade the middle lamella. This zygomycete
20
Molecular Characters of Zygomycetous Fungi
475
is an ideal model system for studying the mechanisms of enzymatic retting of flax.
An extracellular polygalacturonase is probably the key component in the retting
system of R. oryzae. It was purified and characterized. The purified enzyme has a
molecular mass of 37,436 Da from mass spectrometric determination, an isoelectric
point of 8.4, and has nonmethylated polygalacturonic acid as its preferred substrate.
Peptide sequences indicate that the enzyme belongs to family 28, in similarity with
other polygalacturonases. It contains, however an N-terminal sequence absent in
other fungal pectinases, but present in an enzyme from the phytopathogenic bacterium Ralstonia solanacearum (Zhang et al. 2005). Besides R. oryzae, other wellknown zygomycetous fungus producing flax-retting enzymes is Rhizomucor pusillus
(Henriksson et al. 1999).
20.3.3 Fumaric Acids
Fumaric acid is a naturally occurring organic acid. Many microorganisms produce
fumaric acid in small amounts, as it is a key intermediate in the citrate cycle.
Currently, fumaric acid is produced chemically from maleic anhydride. However,
as petroleum prices are rising rather quickly, maleic anhydride as a, petroleum
derivative has increased in price as well. This situation has caused a renewed
interest in the fumaric acid production by fermentation. Zygomycetous fungi,
including Rhizopus, Mucor, Cunninghamella, and Circinella species, are wellknown for their organic acid-producing capability and have been used in fermentation processes for fumaric acid production (Roa Engel et al. 2008). Among these
strains, R. arrhizus is the best-producing one. According to the analyses of, ITS
rDNA, lactate dehydrogenase B, actin, translation elongation factor-1alpha, genomewide AFLP, and organic acid production as well, R. arrhizus var. delemar
(=R. delemar) was thought to be the proper name for R. arrhizus fumaric–malic
acid producers (Abe et al. 2007). To date there is no report about the sequencing,
cloning and characterization of enzymes relevant to metabolic pathways of fumaric
acid.
20.3.4 Polyunsaturated Fatty Acids
Polyunsaturated fatty acids play important roles as structural components of membrane phospholipids and as precursors of the eicosanoids of signaling molecules.
All mammals synthesize such eicosanoids, which are involved in inflammatory
responses, reproductive function, immune responses and regulation of blood pressure. Arachidonic acid (AA; 20:4n 6), as a representative n 6 PUFA, is the most
abundant 20-carbon PUFA in humans; and it not only exhibits various regulation
effects and physiological activities but also plays important roles in infant nutrition.
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X-y. Liu and K. Voigt
Eicosapentaenoic acid (EPA; 20:5n 3), as a representative n 3 PUFA, is beneficial for cardiovascular diseases and decreases platelet aggregation and blood
pressure. The distinct functions of the two families make the ratio in the diet of
n 6 and n 3 PUFAs important for inflammatory responses and cardiovascular
health. Mortierella alpina 1S-4 can produce EPA through the n 3 PUFA biosynthetic pathway and AA through the n 6 PUFA biosynthetic pathway. Therefore,
this fungus is a good model for analyzing a fatty acid desaturation system from
both fundamental and applied viewpoints. The genes encoding o3-desaturase, the
D9-desaturases, D12-desaturases, D6-desaturases and D5-desaturases involved in
20-carbon PUFA biosynthesis have been cloned from M. alpina 1S-4 (Sakuradani
et al. 1999a, b, c, 2005; Sakuradani and Shimizu 2003).
20.4
Molecular Characters in Medical Zygomycetous Fungi
Another important area of studies on zygomycetous fungi is medicine. Zygomycosis is a rare and opportunistic infection caused by fungi belonging to zygomycetous fungi. This type of invasive infections, both superficial and angioinvasive, is
major medical complications in immunocompromised patients. Zygomycosis is
frequently lethal if it is not detected early and treated only with high doses of
amphotericin B, which is currently the main effective therapy for zygomycosis
fungi but limited by severe nephrotoxic side effects. Mortality rates may be as high
as 80% in infected transplant recipients. The recent rise in AIDS, cancer, diabetes,
leukemia, lymphoma, solid organ or bone marrow transplants, immunosuppressive
therapy, and broad-spectrum antimicrobial drugs, has increased the number of
immunosupprimised and immunocompromised patients. Although Aspergillus
and Candida are generally two most commonly infected agents in such patients,
zygomycosis has increased significantly over the past decade. Zygomycetous fungi
are now listed by hospitals as microorganisms responsible for frequent emerging
infections (Chayakulkeeree et al. 2006).
Due to its acute and rapid development, the prompt and precise identification of
a pathogen becomes very crucial for appropriate and efficient treatments to
decrease its mortality. Zygomycosis can be subdivided into mucoromycosis and
entomophthoromycosis which are caused by members of the order Mucorales and
Entomophthorales, respectively. Pathogenic Mucorales comprises the following ten
genera: Absidia, Apophysomyces, Cokeromyces, Cunninghamella, Mortierella,
Mucor, Rhizomucr, Rhizopus, Saksenaea, and Syncephalastrum. Among these,
Absidia, Mucor, Rhizomucor, and Rhizopus are four most common isolated pathogens. Medical Entomophthorales only includes Conidiobolus and Basidiobolus.
Histopathological examination of the tissues typically shows characteristic broad,
hyaline, ribbon-like, wide-angled branching, pauciseptate irregular fungal hyphae
(mucoromycosis), or shows broad fungal hyphae with sparsely found septum
surrounded by eosinophilic granular material (entomophthoromycosis). Their morphological characteristics are so reduced that it is impossible to distinguish them
20
Molecular Characters of Zygomycetous Fungi
477
only by histopathological examination. It is quite easy to differentiate them by
sporangia and other reproductive features after pure cultivation. However, it has not
been widely adopted to diagnose agents through detailed morphological characteristics due to notorious difficulties in axenic culture from clinical specimens because
hyphal elements may be rare in tissue specimens and they can lose their viability
during the tissue homogenization prior to culturing. In addition, Antifungal susceptibility and serological tests usually cannot get accurate and consistent endpoints
and consequently are not available for routine use.
The poor sensitivity of histological practices, the difficult pure cultivation, and
the inaccurate susceptibility and serological tests, have led to the development
of highly sensitive and specific molecular techniques, such as microsatellite, oligonucleotide probes, array, fluorescent capillary electrophoresis, real-time PCR,
PCR-restriction fragment length polymorphism (PCR-RFLP), random amplified
polymorphic DNA (RAPD), pulsed field gel electrophoresis (PFGE), and direct
sequencing of PCR products. These methods targeted either a single gene or a
whole genome.
20.4.1 SSU/LSU rDNA
Numerous targets within the fungal genome have been evaluated, with much of the
current work using areas within the ribosomal RNA gene (rDNA) complex, especially SSU and LSU rDNA. A molecular database for 42 isolates representing all
clinically important zygomycetous fungi was constructed from the SSU and
LSU rDNA. And 13 taxon-specific PCR primers were designed for those taxa
most commonly encountered in infections, according to the aligned LSU rDNA
sequences, which was suggested to have the potential to be used in the PCR assay
for rapid and accurate identification of the etiological zygomycoses (Voigt et al.
1999). A case, in which proven invasive infection caused by Cunninghamella
bertholletiae was confirmed by a pan-fungal PCR assay using conserved primers
binding to SSU rDNA and a specific biotin-labeled probe, was reported. However,
because of the relatively high conservation of SSU rDNA, the probe can detect
DNA not only from C. bertholletiae but also from Absidia glauca, C. elegans and
C. polymorpha (Rickerts et al. 2001). Other cases caused by C. bertholletiae,
however, were also reported not by simple probes but through direct DNA sequencing of the PCR products from serial serum samples (Kobayashi et al. 2004; Makoto
2004). A set of oligonucleotide probes based on SSU rDNA sequencing for the
detection of common airborne or pathogenic fungi at the genus and species levels,
including some zygomycetous organisms, was developed (Wu et al. 2003). The
MicroSeq D2 large-subunit ribosomal DNA sequencing kit was used to detect
filamentous fungi, but did not obtain a high rate of accurate identification among
the zygomycetous fungi, and consequently suggested an additional work to determine which gene or combination of genes is needed for complete separation of
genera and species (Hall et al. 2004). Additionally, a review paper highlighted the
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X-y. Liu and K. Voigt
discordance between conventional phenotypic characterization and identification
using this kit (Greenberg et al. 2004).
20.4.2 ITS rDNA
The ITS rDNA has also been widely used as targets to detect and identify human
fungal pathogens. It plays a critical role in the development of functional rRNA,
with sequence variations among species showing promise as signature regions for
molecular assays. A rapid identification of fungi was recommended by using the
ITS2 rDNA region and an automated fluorescent capillary electrophoresis system,
which was thought to be a promising tool for the rapid diagnosis of invasive fungal
infections, including zygomycosis (Turenne et al. 1999). The whole ITS rDNA was
used as the basis of multiplex PCR by which human pathogenic Rhizopus species
was genetically identified and detected (Nagao et al. 2005) and as the basis of an
oligonucleotide array, which was developed to identify species of clinically important filamentous or dimorphic fungi (Hsiao et al. 2005). The multiplex ITS-PCR
method provided a rapid, simple, and reliable alternative to conventional methods
to identify common clinical fungal isolates, based on the testing pathogenic fungi
directly from cultures with 100% sensitivity and specificity (Luo and Mitchell
2002). PCR-RFLP method, another molecular biology tool concerning ITS
rDNA, was developed to identify the main Mucorales belonging to the genera
Absidia, Mucor, Rhizopus, and Rhizomucor involved in human pathology at
genus and species level (Machouart et al. 2006). The analysis of ITS rDNA
sequences was validated as a reliable technique for identification of zygomycetous
fungi to the species level by using 54 strains belonging to 16 species, including the
most common pathogenic Rhizopus, Absidia, Mucor, and Rhizomucor (Schwarz
et al. 2006; Hoffmann et al. 2009a). Among the genus Cunninghamella, C.
bertholletiae has long been considered the only agent in human diseases, but
recently Cunninghamella echinulata has been identified as another agent based
on the result of the ITS rDNA sequences of isolates of C. bertholletiae, which are
highly homological and are distinct from those of C. echinulata (Liu et al. 2001;
Lemmer et al. 2002). However, it is also mentioned that the number of organisms,
which could be amplified directly from mycelial fragments is relatively low, only
about 50% (Luo and Mitchell 2002).
20.4.3 Cytochrome b Gene
Besides different regions and spacers of ribosomal RNA genes, other genes are also
occasionally used to differentiate zygomycetous pathogens. For example, real-time
PCR assay was developed by using probes binding to a 167-bp conserved region of
the multicopy zygomycete cytochrome b gene, to detect species of the genera
Absidia, Apophysomyces, Cunninghamella, Mucor, Rhizopus, and Saksenaea in
20
Molecular Characters of Zygomycetous Fungi
479
culture and tissue samples. Based on the high sensitivity and specificity from
various materials, it is concluded that the real-time PCR assay was useful for the
rapid and accurate detection of zygomycetous fungi (Hata et al. 2008).
20.4.4 Whole-Genome Fingerprinting and Genotyping
The microsatellite DNA fingerprinting confirmed the proposal of the new pathogen
of C. echinulata (Lemmer et al. 2002) and the interstrain polymorphism of Apophysomyces elegans was examined by using microsatellite primers with the results
of two groups according to their patterns (Chakrabarti et al. 2003).
RAPD (Randomly Amplified Polymorphic DNA) analysis is also able to provide
reproducible markers for strain identification. RAPD analysis of Rhizomucor strains
showed R. miehei to be genetically more homogeneous than the diverse R. pusillus.
RAPD markers described in these works could be utilized in further studies to
identify clinical and environmental isolates of R. miehei and R. pusillus and to
check the accuracy of the original species identifications (Vastag et al. 2000). The
intraspecies variability of Rhizopus stolonifer and R. oryzae (=R. arrhizus) species
was also examined by the RAPD method (Vágvölgyi et al. 2004). Although only a
few R. oryzae strains were involved in that study, the RAPD analysis appeared to
support the unity of the species R. oryzae, which was established with the incorporation of about 30 strains originally described as independent species.
PFGE (Pulsed Field Gel Electrophoresis) is also a versatile tool for molecular
typing and to reveal the genetic variability at species and intraspecies levels. The
electrophoretic karyotypes of A. glauca strains, have been revealed by rotating field
gel electrophoresis and the sexually compatible strains of the mating type pair A.
glauca showed considerable differences in their electrophoretic karyotype (Kayser
and Wöstemeyer 1991); While those of Mucor circinelloides f. lusitanicus strains
were generated by contour-clamped homogeneous electric field gel-electrophoresis
and most showed polymorphisms with a different main karyotype pattern correlated
with each mating type. (Dı́az-Mı́nguez et al. 1999). Further possiblities to elucidate
fingerprints and genotypes are AFLP (Amplified Fragment Length Polymorphism),
RFLP (Restriction Fragment Length Polymorphism), PCR-RFLP and microsatellite
PCR (Vastag et al. 2000; Vágvölgyi et al 2004).
20.4.5 Carbon Assimilation Profiles
In addition to the methods for investigating different genes and whole genome,
carbon assimilation profiles are sometime adopted to determine agents of zygomycosis. Fifty seven strains belonging to 15 species and varieties of zygomycetous
fungi, including the genera Rhizopus, Absidia, Mucor, and Rhizomucor, was tested
for intraspecies and interspecies variability based on their carbon assimilation
profiles. It was concluded that the clustering of isolates based on their carbon
480
X-y. Liu and K. Voigt
assimilation profiles was in accordance with DNA-based phylogeny of zygomycetous fungi and the carbon assimilation profiles allowed precise and accurate identification of most zygomycetous fungi to the species level (Schwarz et al. 2007).
Except the previously reviewed published studies, there are also many researches
in which most infections are identified just as zygomycosis without any species
determination (Ribes et al. 2000; Eucker et al. 2001). Nevertheless, the direct DNA
sequencing of the PCR products obtained from pan-fungal primers remains the
most reliable way to precisely identify zygomycetous fungi, even to a species level.
But molecular techniques for detection of zygomycetous fungi by PCR or other
methods are not widely available and are reserved primarily for research purposes.
New techniques in the molecular identification of zygomycetous fungi need to be
further developed and validated before they are used in clinical practice.
20.5
Genome Projects for Zygomycetous Fungi
The genome projects relevant to zygomycetous fungi are far less than those for
Ascomycota and Basidiomycota, with a total of five species, namely Mortierella verticillata, Mucor circinelloides, Phycomyces blakesleeanus, Rhizopus oryzae (=Rhizopus arrizus), and Smittium culisetae (Table 20.3). The R. oryzae genome is the first
zygomycetous fungus to be sequenced and now has been assembled, annotated,
mapped, and released to public. Its mitochondrial sequence was assembled separately from the genomic one (www.broad.mit.edu/annotation/genome/rhizopus_oryzae/MultiHome.html). Mitochondrial genome of another strain of R. oryzae has
also been accomplished (www.ncbi.nlm.nih.gov/sites/entrez?db=genomeprj&cmd
=Retrieve &dopt=Overview&list_uids=13352; Seif et al. 2005). The mitochondrial
genomes of two other zygomycetous fungi are also determined (Seif et al. 2005),
that is, M. verticillata for which the genome sequencing is in progress (www.broad.
mit.edu/node/575), and S. culisetae. The M. circinelloides genome assembly was
completed and is prerelease annotating (mucorgen.um.es/), while the genome of P.
blakesleeanus was released (genome.jgi-psf.org/Phybl1/Phybl1.home.html).
Table 20.3 Genome statistics for zygomycetous fungi (N/A, not available)
Taxa
Isolates
Nuclei
Mitochondrion
Sizes (Mb) GC (%) Genes Sizes (kb) GC (%) Genes
Mortierella
NRRL 6337
N/A
N/A
N/A 58.745
27.9
54
verticillata
Mucor
CBS 277.49
36.05
N/A
N/A N/A
N/A
N/A
circinelloides
Phycomyces
N/A
55.9
N/A
14792 N/A
N/A
N/A
blakesleeanus
Rhizopus oryzae
RA 99–880
46.09
35.6
17713 61.76
26.36
19
DAOM 148428 N/A
N/A
N/A 54.178
26.2
51
Smittium culisetae 18–3
N/A
N/A
N/A 58.654
18.5
61
20
Molecular Characters of Zygomycetous Fungi
481
These zygomycetous fungi which have been selected as material for genome
programs are all of certain importance. For example, Mucor circinelloides is a
model system for Agrobacterium tumefaciens-mediated transformation (Nyilasi
et al. 2005); Phycomyces blakesleeanus is also a model system not only for sensory
physiology, but also for the regulation of the biosynthesis of the pigment betacarotene in fungi as well; And Rhizopus oryzae (=R. arrhizus) is the most important
and representative agent of mucormycosis.
20.6
Prospect
Zygomycetous fungi are usually distinguished mainly on numerous morphological
traits. When the circumscription of certain taxa was controversial, other characters
were called on as an auxiliary measure, including molecular ones. The morphological characters are undoubtedly the core of taxonomy of zygomycetous fungi either
the past, the present or the future. On the other hand, further works on molecular
characters of the zygomycetous fungi will expectably continue to increase, especially for those fungi that play a crucial role in medicine, agriculture and industry.
To resolve the pending phylogenetic relationships among zygomycetous fungi
based on more loci and more comprehensive samplings, will continue to be an
important research advance at higher ranks like phylum, class and family. Meanwhile, at relatively low levels such as genus and species, on the basis of evaluation
of suitable molecular markers, thoroughly and rationally integrating morphological
and molecular characters for the identification and classification of zygomycetous
fungi and even all cellular organisms is definitely an unchangeable trend, as already
taken on in the effort to establish a worldwide organism barcode system (International Barcode of Life at www.dnabarcoding.org, and Consortium for the Barcode
of Life at barcoding.si.edu). Alternative genes, such as the single copy genes Mcm7
(MS456) and Tsr1 (MS277) useful for both phylogenetics and systematics
(Aguileta et al. 2008, Schmitt et al. 2009) will circumvent designation problems
triggered by paralogies of multicopied protein-coding genes or highly repetitive
ribosomal DNA and revolutionize the molecular identification of fungi and the
zygomycetes. It is most likely in the near future to establish a worldwide collaborative system for fungal identification serving all fungal research communities and
individuals, on the basis of tremendous web resources, such as Assembling the
Fungal Tree of Life (aftol.org), Barcode of Life Data Systems (www.barcodinglife.
org), GenBank (www.ncbi.nlm.nih.gov), Global Biodiversity Information Faculty
(www.gbif.org), Index Fungorum (www.indexfungorum.org), MycoBank (www.
mycobank.org), etc. With the spurt in sequencing technology, more and more
important zygomycetous fungi are hopeful of next candidates for genome projects,
following the five completed representatives. The genome projects about some
industrially, agriculturally, medically and environmentally important zygomycetous fungi are bound to provide a better understanding for their natural status in the
whole organism system in the world and their potential to serve the human being.
482
X-y. Liu and K. Voigt
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Index
A
Absidia, 464, 470–474, 478, 479
A. aegyptiacum, 452
A. anomala, 444, 451, 457
A. caerulea, 444, 451, 452, 457
A. californica, 444, 451, 457
A. capillata, 452
A. clavata, 452
A. corymbifera, 445
A. cuneospora, 444, 451, 457
A. cylindrospora, 444, 451, 452, 457
A. cylindrospora var. cylindrospora,
441, 451
A. cylindrospora var. nigra, 441, 451
A. cylindrospora var. rhizomorpha,
441, 451
A. dubia, 446
A. fassatiae, 452
A. fusca, 444, 451
A. glauca, 444, 451, 457
A. griseola, 452
A. heterospora, 451
A. idahoensis var. thermophila, 440
A. inflata, 452
A. macrospora, 444, 451, 457
A. narayanai, 452
A. pseudocylindrospora, 444, 451, 452
A. psychrophilia, 444, 452, 457
A. reflexa, 451, 452
A. repens, 444, 451, 454, 455, 457
A. robusta, 452
A. scabra, 451, 452
A. septata, 451, 452
A. spinosa, 444, 457
A. spinosa var. azygospora, 441, 451
A. spinosa var. biappendiculata,
441, 451
A. spinosa var. spinosa, 441, 451
A. tuneta, 452
A. ushtrina, 452
description, 440
distinction, 444, 445
mesophilic species, 440, 444
molecular aspects, 440
molecular key, 452–454
morphological aspects, 440–442
phylogenetic analyses, 442, 444, 453
phylogeny, 442
physiological aspects, 440, 442, 445
polyphyly, 442
sensu lato, 440–442
sensu stricto, 440–442, 444–445,
453, 457
synoptic key, 450–452
thermotolerant species, 440,
445, 449
Absidiaceae, 444–445, 450–452
Abundance, underestimated, 71
Acid
arachidonic acid, 475
eicosapentaenoic acid (EPA), 476
fatty acids, 464, 466, 474–476
fumaric acids, 475
organic acid, 475
Actin, MreB, 463
Actinomucor, 471
489
490
Albuginales, 39
Albuginomycetidae, 37
Albugo candida, 37, 41
All Fungi Barcoding, 146
Alternative host plants, 73
Amplified fragment length polymorphism
(AFLP), 40, 113, 134, 137, 198–200, 202,
204, 279–281
Anamorphs, 287
Ancient DNA, 35
Anisogramma anomala, 16
Antimycotics
amphotericin B, 476
nephrotoxic side effects, 476
Antrodia spp., 253
Antrodia vaillantii, 262
Arabidopsis thaliana, 70
Archaeophytes, 5
Armillaria spp., 254, 255, 257, 258, 260,
262, 263, 265
A. borealis, 254
A. cepistipes, 254
A. gallica, 254
A. mellea, 25, 254, 255, 258, 263
A. ostoyae, 254, 258, 263
A. tabescens, 254, 263
Ascomycota, 215, 228
Aspergillus, 198, 199, 201, 207, 319, 320,
323, 324
A. alliaceus, 197
A. carbonarius, 197, 200–207
A. fumigatus, 326
A. niger, 197, 200–204
A. ochraceus, 197–201, 203, 205, 207
A. section Circumdati, 198–199
A. westerdijkiae, 197, 199–201,
203–206
laboratory diagnosis, 367–368
molecular detection, 368–373
Atopic dermatitis, 338, 339
B
Bait tests, 60
Barcoding, 42, 72, 481
Basal fungal lineages, 215
Basidiobolus, Basidiobolaceae, 467, 468
Basidiomycota, 215, 217, 228
Index
Batrachochytrium dendrobatidis, 13
Bayesian inference, 442, 456
Biosynthetic pathway
20-carbon PUFA biosynthesis, 476
n-3 PUFA biosynthetic pathway, 476
n-6 PUFA biosynthetic pathway, 475, 476
Blastocladiomycota, 215
Blastomyces dermatitidis
laboratory diagnosis, 373–374
molecular detection, 374
Blood
culture, 322, 323, 326, 327
whole, 317–328
Blood stream infection (BSI), 322, 327
therapy, 322
Blumeria graminis, 11
Botryosphaeria, 25
Buffon’s law, 7
C
Calmodulin gene, 140
Cambrian, 467
Candida, 318–324
C. albicans, 318, 319, 323, 324, 326, 327
C. glabrata, 319, 321, 323, 326
C. krusei, 319, 321, 323, 326
C. parapsilosis, 319, 326
C. tropicalis, 319, 324, 326
laboratory diagnosis, 377–378
molecular detection, 378–382
Candidaemia, 318–319, 321
Carbon assimilation profiles, 479–480
Ceratocystis fagacearum, 13, 16
Cerotelium, 9
Characteristics
barcode, 481
biochemical, 213
chemotaxonomical, 241
diagnostic importance, 230
ecological, 214
growth temperature, 471–473
isoenzyme patterns, 473
mating compatibility, 471, 473
mesophilic, 470, 472, 473
metabolic, 214
molecular, 214, 227, 461–481
morphological, 213, 215, 227, 230, 464,
467, 470–473, 477, 481
Index
phylogenetic relevance, 221, 223, 237
physiological, 213, 241
synapomorphic, 471
thermophilic, 464, 472, 473
thermotolerant, 470, 471
zygospore, 468, 470, 471
Charcoal rot, 108, 181
Chasmothecial appendage, 85, 86, 88, 89
Chemotype
3ADON chemotype, 161–167, 169–174
15ADON chemotype, 161–167, 169–174
molecular chemotype, 164, 169, 170, 173
NIV chemotype, 160–162, 165–167,
170–172, 174
Chickpea, 80–83
China, 161, 163, 165, 166, 169, 171, 173
Chlamydoabsidia, 441, 442, 444, 445, 450
Chromatography, affinity, 323, 326–328
Chytridiomycota, 215
Chytrids, 468
Ciborinia camelliae, 11
Cicer arietinum, 80
Circinella, 447
Cladosporium, 7
C. subtilissimum, 8
Classification
DNA-based, 467, 472, 480
morphology-based, 467, 472
traditional, 467
Cleaved amplified polymorphic sequence
(CAPS), 147
Clinical specimens
BAL, 371, 372, 378, 390
blood, 363, 368, 371, 372, 375, 377,
378, 381, 382, 386, 390, 391,
393, 394
CSF, 363, 385, 386
serum, 371, 372, 378, 382, 386, 391
serum, plasma, 363, 371
skin, 360, 373, 388, 391, 394, 395
tissue, 361, 367, 368, 371, 373, 378, 383,
384, 388, 390–392, 394
urine, 372, 386
Coccidioides spp.
laboratory diagnosis, 383
molecular detection, 384
Cochliobolus carbonum, 9
Coleosporium helianthi, 10
491
Compatibility
mating, 471
tests, 257
Confluent and reticulate papillomatosis,
338, 339
Coniophora puteana, 253, 261
cox2, 37, 38, 41
C-reactive protein (CRP), 321
Cronartium
C. occidentale, 20
C. quercuum f.sp. fusiforme, 16
C. ribicola, 18, 19
Cryphonectria parasitica, 24
Cryptococcus neoformans
laboratory diagnosis, 385–386
molecular detection, 386–387
Cultivation-dependent method, 278, 287
Culture collections, 214
Cunninghamella, 444, 445, 464, 471,
475–478
Cutinase gene, 141
Cytochrome c oxidase subunit I (COI), 146
D
D-arabinitol, 321
D1/D2 domain, phylogenetic trees, 345,
348, 351
D-dimer, 321, 322
Dematiaceous
laboratory diagnosis, 388
molecular detection, 388–389
Denaturing gradient gel electrophoresis
(DGGE), 279, 281–282, 287
Deoxynivalenol (DON), 160
Derived cleaved amplified polymorphic
sequence (dCAPS), 147, 148
Dermatophytes
laboratory diagnosis, 396
molecular detection, 396–397
Devonian, 469
b-D-glucan, 320
Diagnostic tools, 184–187
Dictyosome, 467
Dikarya, 215
Dikaryomycota
Ascomycota, 468, 480
Basidiomycota, 464, 469, 470, 480
492
Dimorphic, 360, 373, 382, 384, 390
Dimorphic ascospores, 83
Discula destructiva, 15
Divergence
of Asco- and Basidiomycota, 469
of Metazoa and fungi, 469
Diversity
ecological, 462, 464, 467
global biodiversity information faculty,
481
DNA, 303, 307–310, 317–328
array, 100, 137, 144
background, 326
extraction, 68, 165
fingerprinting, 279–282, 287, 289
human background, 326
hybridization, 307
manipulations, 362–364
methylation, 326
microarray, 324, 328
nuclear ribosomal, 303
polymorphism, 307
rDNA, 467–475, 477–478
ribosomal, 468, 473, 474, 477, 478, 481
DNA barcodes, 80, 89, 145–147, 149, 214,
215, 240, 242
alternative barcode markers, 215
barcode markers in combination, 234
beta-tubulin, 234
calmodulin, 234
Consortium for the Barcode of Life
(CBOL), 214
cox1, 214–215
cytochrome b (cob), 215
IGS, 240
internal transcribed spacer (ITS), 215,
217–222, 224–228, 239–240
16S rDNA, 215
28S rDNA, 221, 235, 240
translation elongation factor 1 alpha, 221,
227, 234
universal barcode marker, 214
Donkioporia expansa, 253
E
Ecological importance, 72
Electrophoresis
fluorescent capillary, 477, 478
Index
pulsed field gel electrophoresis (PFGE),
462, 477, 479
Endocommensal, 464
Endocronartium harknessii, 21
Endomycorrhiza, arbuscular, 468, 469
Endophyte, 277, 278, 280–282, 285,
288, 289
Endophytic fungi, 277–289
Endo-polygalacturonase gene (pgI), 140
Entoleuca mammata, 13
Entomophthoromycotina
arbuscular endomycorrhiza, 468, 469
Entomophthorales, 464, 467, 468,
476, 484
Enzyme-linked immunosorbent assay
(ELISA), 62, 168, 258
Erysiphales, 84
Erysiphe
E. pisi, 85, 86
E. trifolii, 81, 85–89
Evolution
actin, 462–464, 469, 471, 474, 475
EF-1 alpha, 469, 471, 473
linear, 469
tubulin, 462–464, 468
Exaptation, 14
F
Fahrenholz’s rule, 11
Fatty acids
n-3 PUFA, 476
n-6 PUFA, 475, 476
polyunsaturated, 474–476
PUFA, 474–476
Fennellomyces linderi, 447, 448, 457
Filamentous fungi, 195
Fingerprinting
amplified fragment length polymorphism
(AFLP), 474, 475, 479
microsatellite PCR, 477, 479
PCR-RFLP, 477–479
pulsed field gel electrophoresis (PFGE),
462, 479
restriction fragment length polymorphism
(RFLP), 477, 479
whole-genome, 479
Finland, 159–174
Forestry, 252
Index
Fruit bodies, 252, 256, 267, 268
Fumonisins
biosynthesis, 120
effects, 109
F. nygamai, 108, 115
F. proliferatum, 108, 111, 114–118
F. verticillioides, 108, 111, 114–120
structure, 108
toxic action, 108–110
Fungi, Dikaryomycota, 470
Fusarium head blight (FHB), 159
Fusarium oxysporum
formae speciales, 132, 134, 136–145,
147, 150
Fusarium spp., 93–102, 185, 319
biological species concept, 113, 115
F. asiaticum, 163, 167, 172
F. avenaceum, 161
F. cerealis, 159–174
F. culmorum, 159–174
F. graminearum, 159–174
F. ussurianum, 173
laboratory diagnosis, 389–390
molecular detection, 390
morphological species concept, 113–115
phylogenetic species concept, 113–116,
119
Fuscoporia torulosa, 266
G
Ganoderma spp., 255, 256, 258, 263, 265
Gene, 302, 303, 308
Ac12RL3 gene, 206, 207
actin, 462–463, 469, 471, 474, 475
actin (act), 302, 304, 307
beta-tubulin (btub), 307, 308
cytochrome, 478–479
D5-desaturase, 476
D9-desaturase, 476
D12-desaturase, 476
encoding o3-desaturase, 476
GenBank, 465, 466, 481
lactate dehydrogenase B, 475
orthologous, 303
otapksPN gene, 207, 208
paralogous, 303
pks gene, 200, 207–208
protein coding, 307
493
repetitive, 303
single copy, 303, 307, 481
translation elongation factor (tef),
303, 307
translation elongation factor-1alpha,
474, 475
Genome
analysis, 145
mitochondrial, 480
Mucor, 462, 464, 465, 471, 472, 476,
478–480
Phycomyces, 462, 466, 480, 481
Rhizopus, 462, 464, 466, 470, 472–476,
478–481
sequencing, 145–147
Genomes OnLine Database (GOLD), 145
Genomics, 68–71
Genotyping
microsatellite PCR, 477, 479
PCR-RFLP, 477–479
pulsed field gel electrophoresis (PFGE),
462, 477, 479
randomly amplified polymorphic DNA
(RAPD), 462, 473, 477, 479
restriction fragment length polymorphism
(RFLP), 473, 477–479
whole-genome, 479
Geosiphonales, Geosiphon, 468
Germany, 163, 165, 166, 169–171
Gloeophyllum spp., 253
Gloeophyllum sepiarium, 262
Glomeromycota, 215
Glomeromycota, Geosiphonales, 467, 468
Glucoamylase, 474
Gongronella, 441, 442, 444, 445
Gougerot and Carteaud syndrome, 338, 340
gp43, 422–424, 427–430
Graminicolous downy mildews, 37, 39
Group I introns, 81–84, 89
Gymnosporangium fuscum, 23
H
Halteromyces, 444, 445
Herbarium specimens, 42
Hesseltinella, 444
Heterobasidion annosum sensu lato (s.l.),
254, 255, 257, 260, 262–264, 267
H. abietinum, 255, 262, 264
494
H. annosum sensu stricto (s.s.), 255,
262–264
H. parviporum, 255, 262–264
High performance liquid chromatography
(HPLC), 136
Histoplasma capsulatum
laboratory diagnosis, 391
molecular detection, 391–392
Holocene, 3, 5
Homogocene, 3–27
Hyaloperonospora, 39
Hybridization probes, 187, 188
Hypertrophies, 53, 60
Hypocrea, 185
I
Identification, 56, 62
of Aspergillus, 368–369, 372
barcode, 481
of Blastomyces dermatitidis, 373, 374
of Candida, 374, 376
of chromoblastomyces, 388–389
of Coccidioides, 383, 384
of Cryptococcus neoformans, 387
of dermatophytes, 396, 397
of filamentous fungi, 372
of Fusarium, 389, 390
of Histoplasma, 390, 391
of molds and yeasts, 359
morphological, 464, 472, 473, 477, 481
phenotype-based identification, 397
physiochemical, 472, 473
preliminary identification, 377
species identification, 359, 381,
396, 397
of Trichosporon, 393
of yeasts, 359
of Zygomycetes, 394
Immunological test methods, 62
Infection
fungal, 471, 476–478, 480
invasive fungal infections (IFI),
319–321, 323
nosocomial, 319
zygomycosis, 472, 476, 478, 480
Inonotus spp., 254, 263, 265
I. tomentosus, 255
Intergenic spacer (IGS), 138–139
Index
Internal transcribed spacer (ITS), 41–44,
80–83, 85–89, 138–139
Inter-simple sequence repeat (ISSR), 137,
279–281
Intraspecific phylogeny, 58
Invasive/disseminated fungal infections
(IFI)
angioinvasive moulds, 389
angioinvasive zygomycosis, 393
cryptococcosis, 385
diagnosis of IFI, 361–362
diagnosis of invasive aspergillosis,
368, 371
invasive aspergillosis, 367, 389
invasive candidiasis, 375
invasive candidosis, 382
invasive fusariosis, 389
invasive mold infection, 372, 389
invasive pulmonary aspergillosis,
362, 371
invasive trichosporonosis, 392
limited invasive disease, 367
progressive invasive disease, 367
risk factors for invasive aspergillosis, 367
Isozyme, 134, 136
analysis, 39, 257, 307
iSSR, 41
ITS regions, phylogenetic trees, 345,
348, 351
K
Kickxellomycotina
Harpellales, 464, 467, 468
Kickxellales, 464, 467, 468
Kretzschmaria deusta, 254
Kuehneola, 9
L
Laetiporus sulphureus, 254
Large-subunit, D2, 477
Lens culinaris, 80
Lentamyces
L. parricida, 446–449, 452, 457
L. zychae, 446–449, 452, 457
morphological aspects, 447, 448
mycoparasitism, 447
physiological aspects, 447
Index
RFLP, in silico, 448
sucker-like substrate mycelium, 447
Lentil, 80, 81, 84–89
Lichtheimia
discrimination from Absidia, 453
L. corymbifera, 445, 446, 450
L. hyalospora, 446, 450
L. ornata, 446, 450
L. ramosa, 446, 450, 454, 457
L. sphaerocystis, 446, 450
morphological aspects, 445
physiological aspects, 445
Lichtheimiaceae, 440, 445–446, 450
Lichtheimiaceae, Lichtheimia, 471
Life cycle, 51–73
Ligniera, 71
Loop-mediated isothermal amplification
(LAMP) methods, 417–435
LOOXSTER1, 327
Lophodermium pinastri, 22
LSU, large-subunit, 477
Lysis
mechanical, 325, 326
pathogen cells, 325
M
Macrophomina phaseolina
biochemical and serological
characterization, 182
clasification and nomenclature, 180–181
identification and characterization, 181
morphological and cultural
characteristics, 181
Maize, mycotoxins, 108, 111
Malassezia spp
identification, 337, 338, 340, 341,
344, 345
M. caprae, 343
M. dermatis, 341–343, 348
M. equi, 343
M. equina, 343
M. furfur, 338, 340–342, 345, 348
M. globosa, 338, 339, 341–343, 345, 348
M. japonica, 342, 343, 348
M. nana, 342, 343
molecular techniques, 338, 343
M. pachydermatis, 340–343, 345,
348, 351
495
M. restricta, 339, 341, 342, 345, 348
M. sloffiae, 345
M. sympodialis, 338, 341–343, 348, 351
M. yamatoensis, 342, 343, 348
phenotypical and physiological features,
341
rDNA genes, 344
Melampsora
M. hypericorum, 9, 10
M. larici-populina, 21
M. medusae, 20, 21
M. occidentalis, 20
Melampsora x columbiana, 21
Meruliporia incrassata, 253
Mesomycetozoea, Eccrinales, 464
Metagenomics, 148, 149
Metazoa, 469
Microarrays, 70, 142, 144–145, 147–150,
268, 269, 461
Microcyclus ulei, 26
Minimum ages, 469, 470
Molecular
actin, 462–464, 469, 474, 475
chemotype, 164, 169, 170, 173
clocks, 469
data available, 71
detection, 131–150
lactate dehydrogenase B, 474, 475
tools, restriction fragment length
polymorphism, 183–184
translation elongation factor-1alpha,
462–464, 474, 475
Molecular assays, amplicon size, PCR and
sequencing
fluorescence-based PCR, 395
FRET probes, 395
in-house and commercial PCR, 372
LAMP, 380
multiplex PCR, 372, 373, 387, 390, 394
nested PCR, 374, 378, 384, 386, 387, 393
panfungal PCR, 367, 368
PCR and cryptococcosi, 386
PCR direct on BAL, 371
PCR ELISA, 368, 371
PCR-RFLP, 387, 396, 397
PCR serotyping, 387
PCR vs. blood cultures, 382
qPCR, 371, 395
496
quantitative real time, 371, 393
real time, 371–373, 384, 393, 395
rep-PCR, 360, 372, 374, 381, 384, 392
seminested PCR, 391, 394
Molecular basis of plasmodiophorid
infection, 69
Monitoring, 60
Monophyletic, 39
origin, 132
Morphological characters, 36
Morphology
subsporangial swelling, 471
trophocyst, 471
Morphotypes, 280, 284–286, 288
Mortierellomycotinained
Endogonales, 469
Mortierellales, 469
Mucor, 213–243
M. circinelloides, 216, 221, 222, 224,
226, 229–231, 233, 236, 238–240,
447, 448, 457
M. circinelloides f. circinelloides, 222,
227, 233, 238, 239
M. circinelloides f. griseo-cyanus, 221,
233, 234, 238–240
M. circinelloides f. janssenii, 236
M. circinelloides f. lusitanicus, 227, 228,
233, 236, 238, 239
M. corymbifer, 445
M. mucedo, 226, 236
M. racemosus, 221, 226, 236
polyphyletic, 235–237
Mucorales
Absidia, 470–472, 476, 478
Actinomucor, 471
Cunninghamella, 471, 476, 478
facultative parasites, 439, 447, 452
Lichtheimiaceae, 471
Mucor, 471, 472, 476, 478
mycoparasitic species, 440, 446
opportunistic pathogens, 439
Pilaira, 471–472
Pilobolaceae, 471
Rhizomucor, 472–473, 476, 478
Rhizopus, 470, 472–474, 476, 478
saprobes, 439
Umbelopsidaceae, 469
Mucormycoses, 216, 235, 236, 240, 439, 445
Index
Mucoromycotina
Mucorales, 469, 476
Multilocus genotyping (MLGT), 161, 163,
167–168, 170, 172
Multiplex PCR, 141
Multiplex polymerase chain reaction
(m-PCR), 203–204
Mycocladaceae, 446
Mycocladiaceae, 470
Mycocladus, 470–471
Mycocladus verticillatus, 446
Mycorrhiza
ectomycorrhiza, 464
endomycorrhiza, 469
Mycosphaerella
M. fijiensis, 4
M. musicola, 4
M. populicola, 22
Mycotoxins, 195–198, 207–208
N
Necrosis, 169, 171
Neocallimastigomycota, 215
Neolithic, 3, 5, 6, 17
Neophytes, 5
Next-generation sequencing, 147
Nivalenol (NIV), 160
NIV chemotype, 160–162, 165–167,
170–172, 174
Non-sporulating endophytic fungi,
284–285, 289
Nucleic acid amplification technique
(NAT), 323–328
Nucleic-acid-based detection methods,
63–68
O
Obligate intracellular parasites, 52
Ochratoxigenic fungi, 195–209
Ochratoxin A (OTA)
biosynthetic pathway genes, 206–208
chemical structure, 196
effects, 196–197
molecular marker, 197–198
PCR detection and quantification,
198–208
producer, 197
Index
regulations, 197
Ochroconis gallopava, 417–435
Oligonucleotide, 303
microsatellite, 477
universal, 303
Oligoporus placenta, 253
On-site PCR, 68
Oospore ornamentation, 39
Ophiostoma, 16
O. novo-ulmi, 17
O. ulmi, 17
Opportunistic, 358, 360, 361, 367, 373, 392
Origin
of Mortierellales, 469
of Mucorales, 469
P
Paleozoic, 470
Panfungal assays, 364–367
Paracoccidioides
P. brasiliensis, 418, 419, 421–431
P. lutzii, 423, 424
Paracoccidioidomycosis, 417–435
Parasites
obligate, 464
Pathogen, 470, 472, 476–479
Pathogenicity, 132, 136, 149, 150, 163,
168–169, 171–172
Pathogen release hypothesis, 8–10
Pathway, biosynthetic pathway, 476
Patients
immunocompromised, 476
immunosupprimised, 476
PCR chemotyping, 165–167
PCR-fingerprinting techniques
ITS, 183, 185–187
ITS-RFLP, 186
Penicillium, 199, 204
P. nordicum, 200, 204, 207, 208
P. verrucosum, 197, 200, 204, 208
Perenniporia fraxinea, 254
Peridiopsora, 9
Peronospora
P. farinosa, 37
P. sparsa, 43
Phacidium infestans, 22
Phagomyxa, 57
497
Phagomyxids, 52, 57, 71, 72
Phakopsora, 9
Phakopsora
P. meibomiae, 9
P. pachyrhizi, 9
Phellinus spp., 254, 255, 263, 265
P. noxius, 263
P. sulphurascens, 261
P. weirii, 255
Phenotypic characters, 39
Phlebia spp., 255, 263
Phylogenetic analysis, parsimony
analysis, 87
Phylogenetic marker
actin (act), 442–444, 456
ribosomal DNA, 442, 444, 448, 449,
453–456
translation elongation factor 1 alpha (tef),
442–444, 456
Phylogenetics, 462, 465–466, 469, 472, 481
coherence, 470
molecular, 462, 470, 481
multigene, 471
Phylogeny
actin, 462–464
DNA-based, 466–468, 470, 472, 473,
480, 481
Fungal Tree of Life, 481
molecular, 466, 472, 473
multigene, 471
phylogenetic analyses, 360
phylogenetic classification, 360
phylogenetic investigation, 358
phylogenetic markers, 398
phylogenetic relationships, 396
phylogenetic studies, 358
protein, 462–466, 468, 481
rpb1, 462, 469
rpb2, 462
Phytomyxea, 56, 57
Phytophthora, 4, 15, 25, 40, 44
P. cinnamomi, 25
P. infestans, 4
P. lateralis, 15
Pilaira, 471–472
Pink ear rot
F. proliferatum, 111, 116, 117
F. subglutinans, 111, 116, 117
498
F. verticillioides, 111, 116, 117
infection, 111
inoculum, 111
Pityriasis capitis, 338
Pityriasis versicolor, 338, 339
Plant diseases, 59, 63
Plant Pathogen Barcode, 146
Plasmodiophora brassicae, 52, 55–57,
59–63, 70–72
Plasmodiophorids, 51–73
Plasmopara
P. halstedii, 37, 40–44
P. viticola, 41, 43
Podosphaera leucotricha, 23
Polygalacturonase, 474–475
Polymerase chain reaction (PCR), 80, 82,
83, 86, 136–143, 145, 147, 148, 150,
258–259, 323–325, 327, 419, 421,
427–431, 433, 477–480
amplified fragment length polymorphism
(AFLP), 479
DNA sequencing, 266–267
group specific, 98–100
microsatellite PCR, 479
multiplex, 317–328
nested PCR, 262, 267
PCR-RFLP, 477–479
qPCR, 326, 327
random amplified polymorphic DNA
(RAPD), 259–261, 268
random amplified satellites (RAMS), 263
RAPD, 477, 479
real-time, 324, 326, 477–479
real-time PCR, 266
restriction fragment length polymorphism
(RFLP), 260–261
sequence specific oligonucleotide probe
(SSOP), 269
species specific, 96–98
taxon-specific PCR, 261–269
terminal restriction fragment length
polymorphism (T-RFLP), 261
Polymerase chain reaction (PCR) assay,
198–209
Polymyxa, 57, 58, 62
P. betae, 57–59, 62, 63, 67
P. graminis, 57–59, 62, 63, 69–71
Polyphyly, 464
Index
Population structure, 137
Post harvest diseases, 240
Powdery mildew, 84–86, 89
Powdery scab, 59, 61
Primer, 303
universal, 303, 307
Proabsidia, 441, 442
Procalcitonin (PCT), 321
Projects, genome, 465–466, 480–481
Proteome, 70
Protoabsidia, 441, 442
Pseudoabsidia, 441, 442, 446
Psoriasis, 338, 340
Public databases, 214, 235
Puccinia
P. carthami, 26
P. helianthi, 10
P. irrequiseta, 9
P. jaceae var. diffusa, 9
P. psidii, 11, 18, 21
P. tanaceti, 9
Pucciniastrum corni, 15
Pythiales, 38, 39
Q
qPCR, 161
Quantitative real time PCR, 205
R
Radiation
basidiomycete radiation, 469
pezizomycotina radiation, 469
Random amplified polymorphic DNA
(RAPD), 40, 133, 134, 136–137, 198,
200, 202–204, 228, 279–281
Real-time PCR, 139, 142–144, 148, 150,
204–205, 207
Real -time PCR technology
SYBR Green, 188
TaqMan, 188
Red ear rot
colonization, 112, 113
DON, 112, 113
F. acuminatum, 111
F. avenaceum, 111
F. chlamydosporum, 111
F. culmorum, 111, 113, 116–119
Index
F. equiseti, 111
F. graminearum, 111–113, 117–119
F. heterosporum, 111
F. poae, 111
F. semitectum, 111
F. sporotrichioides, 121
infection, 112
inoculum, 112, 113
symptoms, 109
Reference material, 234
Relationships, 467, 469, 470, 472, 473, 481
Relevance
clinical, 461
Resting spores, 55, 56, 60, 62, 67–69
Restriction fragment length polymorphism
(RFLP), 39, 133–136, 279–281,
287, 307
Rhizina undulata, 25
Rhizomorphs, 254
Rhizomucor, 472–473, 475, 476, 478, 479
Rhizopus, 213–243
R. americanus, 235
R. arrhizus, 216, 224, 226, 228, 230, 232,
235–238, 240, 241
R. arrhizus var. arrhizus, 221, 228,
236, 241
R. arrhizus var. delemar, 241
R. caespitosus, 227, 232, 238
R. homothallicus, 227, 232, 235, 238
R. lyococcus, 235, 236
R. microsporus, 216, 232, 235, 238
R. microsporus var. chinensis, 226
R. microsporus var. microsporus,
227, 235
R. microsporus var. oligosporus, 226
R. microsporus var. rhizopodiformis, 226
R. schipperae, 227, 238
R. sexualis, 227, 232, 235, 238
R. stolonifer, 224, 226, 228, 230, 232,
235–238
R. stolonifer var. americanus, 235, 237
R. stolonifer var. lyococcus, 235
R. stolonifer var. sexualis, 235
R. stolonifer var. stolonifer, 226, 235
Rhynchosporium secalis, 13
Rhytisma americanum, 22
Ribosomal DNA (rDNA), 303, 307
cluster, 303, 307
499
intergenic spacer (IGS), 307
ITS, 469, 471–475, 478
large subunit (LSU), 303, 307
LSU, 469, 472, 473, 477–478
18S, 307, 308
28S, 307, 308
small subunit (SSU), 307
SSU, 468, 469, 472, 473, 477–478
variability, 307
Rosellinia necatrix, 255
S
Saprobe, 464, 473
Sclerotinia
S. sclerotiorum, 81–84, 89
S. trifoliorum, 80–84, 89
Seborrhoeic dermatitis, 338, 339
Section Discolor
chemotypes, 116
F. culmorum, 115
F. graminearum, 115, 116
F. pseudograminearum, 116
morphology, 116
Section Liseola
F. anthophilum, 114
F. moniliforme, 114
F. proliferatum, 114, 115
F. subglutinans, 114, 115
mating populations, 114, 115
phylogenetic analyses, 122
Seiridium, 16
Sepsis, 326, 327
causative pathogen, 317–319, 326
therapy, 319–322
Sequence-based classification, 41
Sequence characterized amplified region
(SCAR), 138, 140
Sequence tagged sites (STS), 138
454 Sequencing, 147
Sequencing, direct, 477, 480
Serpula lacrymans, 13, 253
Siepmannia
RFLP, restriction patterns, 447, 448
S. lariceti, 447, 448, 457
S. parricida, 447, 449
S. pineti, 447, 457
S. zychae, 447, 449
500
Simple sequence repeats (SSRs), 137–138,
279–281
Single nucleotide polymorphic sites
(SNPs), 82
Single-nucleotide polymorphisms (SNPs),
42, 139, 143, 147, 148
Sirococcus clavigignenti-juglandacearum, 15
SNPs. See Single nucleotide polymorphism
Sodium dodecyl sulfate polyacrilamide gel
electrophoresis (SDS-PAGE), 257
Solexa, 147
SOLiD, 147, 149
Sorosphaera, 53
S. veronicae, 57, 61, 69
S. viticola, 61, 69
Species specific PCR
calmodulin, 115, 117
F. culmorum, 116–118, 121, 122
F. graminearum, 110, 116–119, 121
F. proliferatum, 108, 111, 116–118
F. subglutinans, 115–118
F. verticillioides, 108, 116–120
IGS, 117–119
ITS, 117, 118
Species-specific primers, 63, 163
specimens, unknown, 214
Sphaeropsis sapinea, 13
Spongospora subterranea, 57, 59–62, 69
18S rDNA, 37, 38, 41
28S rDNA, 37, 41
Stegophora ulmea, 22
Stem rot, 80–84
Sterile mycelia, 284, 285
Straminipila, 36
Suspensor, appendages, 470
Systematics
Index Fungorum, 481
Index Fungorum of CABI Bioscience,
471–472
molecular, 462, 473
MycoBank, 481
Index
Technology, sequencing, 481
Tens rule, 6, 22–24
Tieghemella, 441, 442
Timber, 251–269
Toxin-specific PCR
EF-1a, 119
F. culmorum, 121
F. graminearum, 121
F. sporotrichioides, 110, 121
FUM cluster, 120
fumonisins, 108–109, 119–121
F. verticillioides, 108, 119, 120
IGS-RFLP, 119
TRI cluster, 121
Transcriptome analysis, 70
Transformation, Agrobacterium
tumefaciens-mediated, 481
Translation elongation factor-1a gene
(TEF-la), 137
Transposons, 139–140
Tree stability, 252–254, 263, 265
Tri7, 161–165, 169–170, 172, 173
Tri13, 161, 162, 164, 165, 169–170,
172, 173
Trichoderma, 185
Trichomycetes
Asellariales, 464, 467, 468
Trichophyton rubrum, 13
Trichosporon spp.
laboratory diagnosis, 392–393
molecular detection, 393
Trichothecenes
DON, 109, 110, 121
F. acuminatum, 110
F. culmorum, 110, 121
F. equiseti, 110
F. graminearum, 110, 121
F. sporotrichioides, 110, 121
structure, 109, 110
T-2, 109, 110
toxic action, 110
Tubulin, FtsZ, 464
T
Taphrina, 14
Taxonomic concept, 36
Taxonomic position, 56
Taxonomy, 358, 360, 392, 395, 396
U
Universal primers, 462, 474
Uredinales, 11
Uromyces heterogeneus, 23
Index
501
V
Z
Vegetative compatibility groups (VCGs),
132–134, 136
Venturia, 10, 14
V. inaequalis, 13, 23
V. inopina, 10
V. populina, 10
Verticillium, 185
Virus transmission, 59, 61–63, 67
VYOO1, 325, 326
Zearalenone (ZEN), 160
Zoopagomycotina
Dimargaritales, 464
Zoopagales, 464
Zygomycetes, 215–217, 221–224, 231, 234,
241, 464, 468, 474, 478, 481
laboratory diagnosis, 394
molecular detection, 394–395
Zygomycetous fungi, 461–481
Zygomycosis
antimycotics, 472
entomophthoromycosis, 476
mucormycosis, 473, 481
Zygomycota, 215, 221, 228, 230
Basidiobolales, 468
Entomophthoromycotina, 462, 467,
468
Kickxellomycotina, 462, 467, 468
Mortierellales, 469
Mortierellomycotinained, 469
Mucoromycotina, 462
Zoopagomycotina, 462, 467
Zygospore, 468, 470, 471
W
White blister rusts, 37, 39, 44
Wood rotting fungi, 251–269
brown rot, 251, 253, 254, 256
butt rot, 252, 254–256, 263
indoor wood decay fungi, 252–253,
257, 258
root rot, 254, 255, 263, 267
white rot, 251, 253, 254
X
Xylanase-3 gene, 140