pathogens
Article
Fungal Species Causing Maize Leaf Blight in Different
Agro-Ecologies in India
Vimla Singh 1, *, Dilip K. Lakshman 2, * , Daniel P. Roberts 2 , Adnan Ismaiel 2 , Alok Abhishek 3 , Shrvan Kumar 4
and Karambir S. Hooda 5
1
2
3
4
5
*
Citation: Singh, V.; Lakshman, D.K.;
Roberts, D.P.; Ismaiel, A.; Abhishek,
A.; Kumar, S.; Hooda, K.S. Fungal
Species Causing Maize Leaf Blight in
Different Agro-Ecologies in India.
Pathogens 2021, 10, 1621. https://
doi.org/10.3390/pathogens10121621
Academic Editor: Andrea Luvisi
Received: 9 November 2021
Accepted: 8 December 2021
Published: 14 December 2021
Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims in
Department of Botany and Plant Physiology, Chaudhary Charan Singh Haryana Agricultural University
Regional Research Station, Karnal 132001, India
Sustainable Agricultural Systems Laboratory, USDA-ARS, Beltsville, MD 20705, USA;
dan.roberts@usda.gov (D.P.R.); Ed.Ismaiel@usda.gov (A.I.)
ICAR-Indian Institute of Maize Research (Delhi Unit), Pusa Campus, New Delhi 110012, India;
alokproteome@gmail.com
Department of Mycology and Plant Pathology, Rajiv Gandhi South Campus, Banaras Hindu University,
Mirzapur 231001, India; shrvank@gmail.com
Germplasm Evaluation Division, National Bureau of Plant Genetic Resources, New Delhi 110012, India;
ks.hooda@icar.gov.in
Correspondence: vs.bot.cobsh@hau.ac.in (V.S.); Dilip.Lakshman@usda.gov (D.K.L.)
Abstract: Foliar diseases of maize cause severe economic losses in India and around the world.
The increasing severity of maize leaf blight (MLB) over the past ten years necessitates rigorous
identification and characterization of MLB-causing pathogens from different maize production zones
to ensure the success of resistance breeding programs and the selection of appropriate disease
management strategies. Although Bipolaris maydis is the primary pathogen causing MLB in India,
other related genera such as Curvularia, Drechslera, and Exserohilum, and a taxonomically distant
genus, Alternaria, are known to infect maize in other countries. To investigate the diversity of
pathogens associated with MLB in India, 350 symptomatic leaf samples were collected between 2016
and 2018, from 20 MLB hotspots in nine states representing six ecological zones where maize is grown
in India. Twenty representative fungal isolates causing MLB symptoms were characterized based on
cultural, pathogenic, and molecular variability. Internal Transcribed Spacer (ITS) and glyceraldehyde3-phosphate dehydrogenase (GADPH) gene sequence-based phylogenies showed that the majority
of isolates (13/20) were Bipolaris maydis. There were also two Curvularia papendorfii isolates, and one
isolate each of Bipolaris zeicola, Curvularia siddiquii, Curvularia sporobolicola, an unknown Curvularia
sp. isolate phylogenetically close to C. graminicola, and an Alternaria sp. isolate. The B. zeicola, the
aforesaid four Curvularia species, and the Alternaria sp. are the first reports of these fungi causing
MLB in India. Pathogenicity tests on maize plants showed that isolates identified as Curvularia spp.
and Alternaria sp. generally caused more severe MLB symptoms than those identified as Bipolaris spp.
The diversity of fungi causing MLB, types of lesions, and variation in disease severity by different
isolates described in this study provide baseline information for further investigations on MLB
disease distribution, diagnosis, and management in India.
published maps and institutional affiliations.
Keywords: leaf spot; foliar blight; foliar disease; fungal plant pathogen; pathogen identification;
cultural; morpho-molecular variability
Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
1. Introduction
This article is an open access article
Maize (Zea mays L.) is an important cereal crop in India and ranks third in production
after wheat and rice [1]. Maize has wide adaptability and is gaining popularity as evidenced
by its rising production and productivity [2]. Most of the produce in India is consumed
as food for humans, fodder for animals, and feed for poultry, apart from applications as
industrial raw materials. Among the 35 diseases affecting crop health, viz. seed rots and
distributed under the terms and
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Attribution (CC BY) license (https://
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4.0/).
Pathogens 2021, 10, 1621. https://doi.org/10.3390/pathogens10121621
https://www.mdpi.com/journal/pathogens
Pathogens 2021, 10, 1621
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seedling blights, root and stalk rots, foliar diseases, and ear rots, maize leaf blight (MLB)
caused by Bipolaris maydis [(Nisikado& Miyake) Shoem] is one of the major diseases of
maize [1,2]. This disease has been detected in almost all maize growing areas of India [3]
and is a constraint on crop improvement programs. In India, MLB occurs in the states
of Punjab, Haryana, Delhi, Uttar Pradesh, Bihar, Madhya Pradesh, Gujarat, Jammu and
Kashmir, Sikkim, Meghalaya, Rajasthan, Andhra Pradesh, and Maharashtra [3].
Bipolaris and related genera such as Curvularia, Dreschslera, and Exserohilum are ascomyceteous fungi known to infect maize [4], and belong to the Class Dothideomycetes,
Order Pleosporales, and Family Pleosporaceae. Although the name Cochliobolus (1934)
has been in the literature longer than the name Bipolaris (1959), it is not frequently used
in disease reports, and Bipolaris is widely applied in taxonomy [5]. The association of
the genus Bipolaris with plants from the family Poaceae is very common; however, species
of Bipolaris have been reported to infect 60 other host genera, either as saprophytes or
phytopathogens [6,7]. The spread of phytopathogenic species of the genus Bipolaris may
have occurred due to international trade [8].
Based on molecular phylogenetic analysis with the ITS1-5.8S-ITS2 region of rDNA
and partial sequence of the GAPDH (glyceraldehyde-3-phosphate dehydrogenase) gene [9],
Drechslera, Bipolaris, and Curvularia are distinct genera even though they share many
morphological similarities [4,9,10]. In addition, Bipolaris and Curvularia both have sexual
morphs in Cochliobolus [11]. In molecular analyses of ITS and GAPDH gene data, two major
clades, Cochliobolus Group-1 and Group-2 were clustered [12]. Similar results were obtained
from a combined analysis of ITS, GAPDH, TEF (translation elongation factor-1 alpha gene),
and LSU (28S nrRNA gene) sequence data [13]. Group-1 included the genus Bipolaris (type
species B. maydis), and Group-2 included the genus Curvularia, (type species C. lunata).
The fungus B. maydis ((Teleomorph: Cochliobolus heterostrophus (Drechsler) Drechsler)
exists as four different races infecting maize across the world, viz. race ‘T’, ‘O’ ‘C’ ‘S’ [14].
Race ‘T’ of B. maydis is highly virulent and was reported to cause the devastating ‘Southern
corn leaf blight’ epidemic in the USA during the 1970s, resulting in huge losses due to the
extremely susceptible response of Texas Male Sterile maize lines [6,15–18]. Although race
‘T’ has been reported on seeds of Phaseolus mungo, Vigna sinensis, and Paspalum scrobiculatum
from India [19], B. maydis race ‘O’ is the prevalent pathogen of maize in India and elsewhere
in the world [4,20,21]. Drechslera maydis (synonym of B. maydis) on maize was reported for
the first time in Punjab [22]. The occurrence of a pathotype resembling race ‘T’ in India on
maize hybrids 2310 and 2420 from Ludhiana was reported for the first time in 1978 [23].
Race C is the most virulent in maize cytoplasmic male sterile line C (c-cms), currently
reported only in China [20,24].
For over a decade, the severity of MLB on maize in the Indian subcontinent has been
increasing and the disease has spread to areas where it was not previously reported. A
remarkable variability in the range of symptoms has also been recorded. Due to this
variability in symptoms, it is very important to document the species of Bipolaris and
other associated genera infecting maize, and to precisely characterize the infecting species
complex. The rising incidence of Curvularia sp. on maize is also a concern for crop improvement programs [25]. The objectives of this study were (1) to examine the diversity of
Bipolaris species and associated fungal genera causing MLB across different agro-ecological
zones of India, (2) to provide correct morphological descriptions and identification of the
species/isolates for reference in order to device identification and management strategies,
and (3) to assess the virulence spectrum of common MLB pathogenic species. Knowledge
gained from this study will provide benchmark information necessary to accurately identify
MLB pathogens, breed for resistant cultivars, and improve disease management practices
in India.
Pathogens 2021, 10, 1621
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2. Results
2.1. Survey, Collection, and Maintenance of Fungal Isolates
A total of 350 symptomatic maize leaf samples showing maize leaf blight (MLB)like symptoms were collected from 20 hotspots representing six agro-ecological zones
under maize production during survey and surveillance visits during the Kharif seasons
(June–October) in 2016–2017 and 2017–2018 (Supplementary Material: Figure S1). The
six hotspots, viz. Godhra, Anand, Sukheri, Lakhawali, Mandya, and Mysore showed
variability in morphological and pathogenic profiles. However, in view of the sample size
and constraints of the resources available for this study, one candidate isolate was selected
from each of the 20 hotspots, viz. Pantnagar, Bajaura, Kangra, Patelnagar, Ludhiana, Pichola,
Banswara, Kota, Chittorgarh, Dungarpur, Amberi, Karnal, Dholi, Samastipur, Godhra,
Anand, Sukheri, Lakhawali, Mandya, and Mysore for phylogenetic analysis (Table 1).
Isolates were examined for typical characteristics of B. maydis which is the prevalent
species infecting maize in India, as reported by earlier workers [23,26–28]. Variability
in colony growth (slow, medium, or fast), color (light grey, dark grey, light black, or
black), texture (rough raised, rough appressed, smooth raised, smooth appressed with
or without zonation, and regular or irregular margins), conidial dimensions (7.6 µm to
19.3 µm × 3.1 µm to 6.1 µm), pathogenicity (mild to high) and disease severity (30 to 90%)
revealed that out of 20 hotspots surveyed, fungal isolates from 14 hotspots (Table 2) showed
typical morphological and pathogenic characteristics of Cochliobolus heterostrophus (Drechs.)
Drechs. (anamorph = Bipolaris maydis (Nisi-kado) Shoemaker; synonym = Helminthosporium
maydis Nisikado).
Table 1. Details of maize leaf blight causing isolates from Zea mays collected from different agro-ecological zones under
maize production.
S. No. $
New Code
Location
AEZ *
State
Latitude
Accession No.
Longitude
Soil Type
No. of
Samples
Collected
ITS
GAPDH
15
KX668613
OL519604
1
BmPhRj4
Pichola
(Udaipur)
WDR
Rajasthan
24◦ 36′ 48.00′′ N
73◦ 40′ 48.00′′ E
Sandy/clay
loam to
dessert loam
2
BmBjUa1
Bajaura
WHR
Uttaranchal
31◦ 50′ 54.2483′′ N
77◦ 9′ 51.6013′′ E
Sandy to
clay loam
23
KX668605
OL519605
3
BmBsRj4
Banswara
(Udaipur)
WDR
Rajasthan
23◦ 32′ 48.3252′′ N
74◦ 26′ 1.7880′′ E
Sandy/clay
loam to
dessert loam
11
KX668614
OL519606
4
BmDhBh3
Dholi
MGP
Bihar
25◦ 51′ 25.9951′′ N
85◦ 46′ 85.5895′′ E
Deep
loamy/silt/
clay loam
27
KX668619
OL519607
5
BmCgRj4
Chittorgarh
(Udaipur)
WDR
Rajasthan
24◦ 54′ 16.5716′′ N
74◦ 42′ 29.558′′ E
Sandy/clay
loam to
dessert loam
18
KX668617
OL519608
6
BmPnDl2
Patel
Nagar
TGP
Delhi
28◦ 39′ 8.7966′′ N
77◦ 11′ 29.9389′′ E
Alluvium
15
KX668610
OL519609
7
BmDnRj4
Dungarpur
(Udaipur)
WDR
Rajasthan
23◦ 50′ 16.5716′′ N
73◦ 50′ 29.558′′ E
Sandy/clay
loam to
dessert loam
19
KX668616
OL519610
8
BmKgUa1
Kangra
WHR
Uttaranchal
32◦ 5′ 59.2944′′ N
76◦ 16′ 8.7744′′ E
Shallow to
deep loam
21
KX668609
OL519611
29◦ 41′ 8.4944′′
76◦ 59′ 25.737′′
9
BmKrHr2
Karnal
TGP
Haryana
N
E
Sandy clay
20
KX668608
OL519612
23
KX668618
OL519614
34
KX668623
OL519613
10
BmKtRj4
Kota
(Udaipur)
WDR
Rajasthan
24◦ 10′ 16.5716′′ N
75◦ 52′ 29.558′′ E
Sandy/clay
loam to
dessert loam
11
BmLdPj2
Ludhiana
TGP
Punjab
30◦ 54′ 3.474′′ N
75◦ 51′ 26.1929′′ E
Deep
loamy/sandy/
clay loam
12
BmPtUa1
Pantnagar
WHR
Uttaranchal
29◦ 1′ 15.74′′ N
79◦ 29′ 23.06′′ E
Sandy clay
18
KX668604
OL519615
13
BmMyKa6
Mysore
SPHR
Karnataka
12◦ 31′ 25.4316′′ N
76◦ 53′ 40.8624′′ E
Light red
sandy loam
9
OK576634
OL519616
14
BmMdKa6
Mandya
SPHR
Karnataka
12◦ 31′ 25.4316′′ N
76◦ 53′ 40.8624′′ E
Light red
sandy loam
13
KX668606
OL502169
Pathogens 2021, 10, 1621
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Table 1. Cont.
Accession No.
ITS
GAPDH
Sandy loam
No. of
Samples
Collected
12
KX668621
OL502170
72◦ 56′ 56.1696′′ E
Sandy loam
12
KX668622
OL502171
11
KX668612
OL502172
S. No. $
New Code
Location
AEZ *
State
Latitude
Longitude
Soil Type
15
BmGdGj5
Godhra
GPHR
Gujarat
22◦ 46′ 24.9456′′ N
73◦ 36′ 49.9824′′ E
16
BmAdGj5
Anand
GPHR
Gujarat
22◦ 33′ 14.5044′′ N
17
BmLhRj4
Lakhawali
(Udaipur)
WDR
Rajasthan
24◦ 34′ 16.5716′′ N
73◦ 41′ 29.558′′ E
Sandy/clay
loam to
dessert loam
18
BmSkRj4
Sukher
(Udaipur)
WDR
Rajasthan
24◦ 34′ 16.5716′′ N
73◦ 41′ 29.558′′ E
Sandy/clay
loam to
dessert loam
16
KX668615
OL519603
19
BmSmBh3
Samastipur
MGP
Bihar
25◦ 51′ 46.6848′′ N
85◦ 46′ 51.7044′′ E
Deep
loamy/silt/
clay loam
18
KX668620
OL519617
20
BmAmRj4
Amberi
(Udaipur)
WDR
Rajasthan
26◦ 55′ 16.5716′′ N
73◦ 50′ 29.558′′ E
Sandy/clay
loam to
dessert loam
15
KX668611
**
* AEZ = Agro-ecological zone; WHR = Western Himalayan Region; TGP = Transgangetic Plains; MGP = Middle Gangetic Plains;
SPHR = Southern Plateau and Hill Region; WDR = Western Dry Region. ** GAPDH sequencing not done. $ Based on phylogeny, serial
numbers (SN) 1 to 13 were identified as Bipolaris maydis, SN 14 as B. zeicola, SN 15 and 16 as Curvularia papendorfii, SN 17 as C. sporobolicola,
SN 18 as C. siddiquii, SN 19 as Curvularia sp. (C. graminicola-like), and SN 20 as Alternaria sp.
Table 2. Cultural characteristics and pathogenic profiles of maize leaf blight (MLB)-causing isolates from Zea mays collected
from different agro-ecological zones under maize production on PDA at 27 ± 1 ◦ C.
SN$
Isolate
Size of Conidia (µm) and Septations *
Length (µm)
Width (µm)
No. of
Septa
Radial
Growth (in
mm) **
Disease
Score
***
Incubation
Period (in h)
∞
Colony
Texture #
Colour of
Colony **
Disease
Index β
(PDI)
1
BmPhRj4
9.8 (6.54–17.86)
3.4 (2.25–4.63)
2.7 (2–5)
47.5 (++)
1.5
72 (Type-I)
Rr/Nz/Irm
Light black
30 (MV)
2
BmBjUa1
16.9 (10.68–20.84)
4.1 (3.72–4.45)
7.1 (5–8)
58.5 (++)
2.6
72 (Type-II)
Rr/Nz/Rm
Black
52 (MoV)
46 (MV)
3
BmBsRj4
12.7 (7.79–22.78)
4.9 (4.36–5.26)
4.7 (3–6)
71.4 (+++)
2.3
48 (Type-III)
Sap/Nz/Rm
Black
4
BmDhBh3
14.4 (11.91–16.66)
4.5 (3.91–5.43)
3.7 (3–5)
51.1 (++)
3.7
72 (Type-I)
Rap/Nz/Rm
Black
74 (HV)
5
BmCgRj4
14.8 (9.26–20.96)
4.3 (2.48–4.78)
4.2 (2–9)
72.3 (+++)
2.9
48 (Type-II)
Rr/Nz/Rm
Light black
58 (MoV)
6
BmPnDl2
19.3 (13.27–21.36)
5.0 (3.91–5.73)
4.3 (3–7)
68.8 (++)
2.7
72 (Type-III)
Rr/Z/Irm
Black
54 (MoV)
7
BmDnRj4
11.1 (6.52–14.94)
4.7 (3.63–5.51)
3.0 (2–5)
69.0 (++)
1.9
48 (Type-II)
Sap/Nz/Rm
Light grey
38 (MV)
8
BmKgUa1
10.1 (7.34–15.43)
4.5 (3.89–5.46)
3.1 (2–6)
63.4 (++)
2.4
76 (Type-II)
Sap/Nz/Rm
Dark grey
48 (MV)
9
BmKrHr2
15.1 (19.25–11.03)
4.4 (4.19–4.93)
6.1 (4–7)
74.3 (+++)
3.5
48 (Type-I)
Sap/Nz/Rm
Dark grey
70 (HV)
10
BmKtRj4
13.0 (8.92–19.4)
3.9 (2.54–5.22)
3.7 (2–5)
54.3 (++)
1.7
96 (Type-III)
Sap/Nz/Rm
Black
34 (MV)
11
BmLdPj2
14.3 (8.78–23.57)
4.4 (2.55–5.77)
5.1 (3–6)
37.4 (+)
4.3
72 (Type-II)
Rr/Nz/Irm
Dark grey
86 (HV)
12
BmPtUa1
14.7 (11.89–17.74)
4.9 (4.23–5.43)
4.1 (3–4)
45.5 (++)
3.2
72 (Type-II)
Rr/Nz/Rm
Dark grey
64 (MoV)
13
BmMyKa6
13.1 (10.77–17.03)
3.8 (2.46–4.78)
4.1 (3–4)
78.9 (+++)
2.7
72 (Type-IV)
Sap/Z/Rm
Light grey
54 (MoV)
14
BmMdKa6
11.6 (6.88–15.32)
3.6 (4.12–5.36)
3.8 (4–2)
81.8 (+++)
1.7
72 (Type-I)
Sap/Z/Rm
Light grey
34 (MV)
15
BmGdGj5
7.6 (6.83–9.77)
3.1 (3.61–4.52)
1.0 (1–3)
79.3 (+++)
3.3
48 (Type-I)
Rr/Nz/Rm
Black
66 (MoV)
16
BmAdGj5
12.1 (8.23–15.98)
4.3 (3.84–5.86)
3.0 (2–9)
51.6 (++)
4.5
72 (Type-VI)
Rap/Nz/Rm
Black
90 (HV)
17
BmLhRj4
17.2 (10.33–23.13)
3.7 (2.44–4.57)
5.0 (4–8)
59.3 (++)
3.7
72 (Type-III)
Rr/Z/Irm
Dark grey
74 (HV)
18
BmSkRj4
16.8 (9.78–20.11)
3.1 (2.98–4.91)
3.0 (2–8)
37.7 (+)
3.6
72 (Type-V)
Sap/Nz/Rm
Dark grey
72 (HV)
19
BmSmBh3
7.8 (6.12–10.11)
6.1 (4.21–7.93)
2.0 (2–6)
42.6 (++)
4.3
76 (Type-V)
Sap/Z/Rm
Dark grey
86 (HV)
BmAmRj4
18.6 (7.33–21.67)
5.8 (3.22–8.44)
6.0 (4–8)
67.3 (++)
4.1
72 (Type-IV)
Rr/Nz/Irm
Black
82 (HV)
6.2
1.2
2.0
1.28
1.1
20
CD at 5%
* Range is given in parentheses. ** Radial growth was recorded 10 days after inoculation (DAI) and expressed as an average of 3 replications;
(+) = Slow growth (30–40 mm), (++) = Medium growth (40–70 mm), (+++) = Fast growth (70–90 mm). # Rr = rough raised, Z = Zonation,
Nz = no zonation, Rm = regular margin, Rap = rough appressed, Irm = irregular margin; Sap = smooth appressed, Sr = smooth raised.
*** Disease score expressed as an average of 10 replications using a rating scale of 1–5 (Payak and Sharma, 1983). β PDI (Percent Disease
Index) expressed as an average of 10 replications using the formula PDI = sum of all ratings/maximum disease rating × 100; PDI > 70–
100%—highly virulent (HV), PDI > 50–69%—Moderate virulence (MoV), PDI > 20–49%—Mild virulence (MV). ∞ Symptoms: Type-I, Small,
dot–like yellowish necrotic lesions scattered away from midrib; Type-II, Dot–like, tan–colored lesions scattered profusely on the leaf surface;
Type-III, Elongated, nearly long strip, tan–colored lesions restricted by veins; Type-IV, Long, narrow tan–colored linear lesions; Type-V:
Circular lesions that were larger than the Type I lesions with purplish margins; Type-VI: Very large necrotic lesions along the length of leaf
margins or parallel to midrib. $ Based on phylogeny, serial numbers (SN) 1 to 13 were identified as Bipolaris maydis, SN 14 as B. zeicola, SN
15 and 16 as Curvularia papendorfiii, SN 17 as C. sporobolicola, SN 18 as C. siddiquii, SN 19 as Curvularia sp. (C. graminicola–like), and SN 20 as
Alternaria sp.
Pathogens 2021, 10, 1621
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2.2. Phylogenetic Analyses
The final ITS alignment file had thirty taxa and 483 characters of which 84 were parsimony informative representing 17% of the total characters. The GADPH file had 23 taxa
and 512 characters of which 118 were parsimony informative representing 23% of the total
characters. For both files, reference sequences representing mostly sequences of ex-type
cultures of Bipolaris or Curvularia species were obtained from GenBank and were included
in Supplementary Material (Table S1). The phylogenetic trees obtained with Bayseian
analyses had essentially identical topology to the trees obtained by maximum likelihood
(ML). Therefore, for each locus, only one ML tree was selected for this publication, but the
posterior probability (PP) support for the branches from the Bayesian trees is reflected on
the maximum likelihood tree branches. The maximum likelihood tree shown in Figure 1A
based on GAPDH sequence data reveals that three taxa under study formed a highly
supported subclade (A) with a sequence of ex-type culture B. maydis. As a matter of fact,
there were 10 additional isolates with identical sequences to taxa in clade A which were
not included in the analysis due to the tree size. In other words, 13 of 20 isolates were
identified as B. maydis. The tree based on ITS sequence data (Figure 1B) was congruent
with the GAPDH tree and revealed the same clade (A) within a large all Bipolaris species
clade. One isolate (BmMdKa6) had identical sequence to the ex-type culture of B. zeicola and
they together formed a highly supported (BS = 97%; PP = 0.98) subclade B (Figure 1A). This
subclade was sister to the B. maydis subclade with BS support of 100% and PP of 1. Similar
to subclade A, isolate BmMdKa6 was also identified as B. zeicola in the ITS tree (subclade B;
Figure 1B). In brief, among the 20 isolates identified morphologically and pathologically
as fungi causing MLB, 13 isolates (viz. BmPhRj4, BmBjUa1, BmBsRj4, BmDhBh3, BmCgRj4,
BmPnDl2, BmDnRj4, BmKgUa1, BmKrHr2, BmKtRj4, BmLdPj2, BmPtUa1, and BmMyKa6)
representing 13 hotspots were identified as B. maydis and one isolate (BmMdKa6) was
identified as B. zeicola, based on phylogenetic trees of two loci, GAPDH, and ITS.
The remaining taxa in the tree were Curvularia sp. isolates and they formed three main
supported clades C, D, and E. (Figure 1A). Clades C, D, and E had a polytomy relationship
to each other and to Bipolaris clades B and A. (Figure 1A). Within clade E, isolates BmAdGj5
and BmGdGj5 and ex-type culture of C. papendorfii had identical sequences, and together
they formed a highly supported subclade (BS = 98% and PP = 0.99 subclade). Isolate
BmLhRj4 had an identical sequence to an ex-type culture of C. sporobolicola, and together
they formed a highly supported subclade. Isolate BmSkRj4 formed a subclade with two
isolates of C. siddiquii, with high support (BS = 0.99 and PP = 1). In the ITS tree, however,
the isolates that fell into clade E (BmLhRj4, BmGdGj5, BmAdGj5, and BmSkRj4) formed a
highly supported clade with C. lunata and they all had identical ITS sequences. Clearly,
phylogeny based on ITS sequence data appears to be unsuccessful in resolving Curvularia
isolates to the species level like the GAPDH tree. Isolate BmSmBh3 (Figure 1A) formed a
clade with the sequence of the unidentified species of Curvularia (Accession No. KU552166).
The species C. graminicola was shown to be the closest relative to them (Clade D, Figure 1A).
Therefore, this unidentified species remained ambiguous, needs additional markers-based
phylogeny for clarity, and was named C. graminicola-like fungus for this report. In the ITS
tree, isolate BmSmBh3 fell into the large Curvularia clade but did not form a clade with a
sequence of any known species of Curvularia.
The isolate BmAmRj4 did not fall into the Bipolaris or Curvularia clades but formed a
clade with the ex-type culture of Alternaria alternata in the ITS tree (Figure 1B). The two
sequences had 100% homology. However, we could not obtain the GAPDH sequence for
this isolate, and thus it was excluded from the phylogenetic analyses based on GAPDH. In
summary, in addition to the 14 isolates of B. maydis and B. zeicola that were causative agents
for MLB, we identified two isolates of C. papendorfii, and one isolate each of C. siddiquii, C.
sporobolicola, a C. graminicola-like fungus, and an Alternaria sp. as MLB causing fungi in
India.
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2.3. Morphological Characterization of Fungal sp. Causing Maize Leaf Blight
The 20 candidate fungal isolates maintained on Potato Dextrose Agar (PDA) plates
showed striking variability in culture morphology and conidial dimensions (Table 2;
Figure 2A). The length and width of conidia of different isolates varied between 7.6 µm
(BmgGdGj5, Godhra) to 19.3 µm (BmPnDl12, Patel Nagar) and 6.1 µm to 3.1 µm (BmSmBh3,
Samastipur and BmgGdGj5, Godhra or BmSkRj4, Sukher), respectively. The isolate BmPnDl12 (Patel Nagar) had the largest sized conidia with mean length of 19.3 µm and width
of 5.0 µm and BmgGdGj5 (Godhra) had the smallest conidia, 7.6 µm × 3.1 µm. The conidial
dimensions of the rest of the 18 isolates were in the order BmAmRj4 (Amberi) > BmLhrj5
(Lakhawali) > BmBjUa1 (Bajaura) > BmSkRj4 (Sukher) > BmKrHr2 (Karnal) > BmCgRj4
(Chittorgarh) > BmPtUa1 (Pantnagar) > BmDhBh3 (Dholi) > BmLdPj2 (Ludhiana) > BmMyKa6 (Mysore) > BmKtRj4 (Kota) > BmBsRj4 (Banswara) > BmAdGj5 (Anand) > BmMdKa6
(Mandya) > BmDnRj4 (Dungarpur) > BmKgUa1 (Kangra) > BmPhRj4 (Pichola) > BmSmBh3
(Samastipur) (Table 2).
H7C8
H N8
100/1
H2
100/1
. H R DN
97/0.98
H4 2
. S D JG
. OMDAJGDD ICMP 6149
90/1
C. richardiae BRIP 4371
91/1
Cochiiobolus lunatus CBS 730.96
C. inaequalis CBS 102.42
C. spicifera CBS 274.52
C. BM HDID JG
93/1
100/1
807
C. sp. BRIP61674
H9H C
93/0.96
H3C8
. NKJMJ JGD JG
98/0.99
74/-
807
H
H
. K K I JMADD
H9F8
0.99/1
. ND
DLPDD
9
.
C. siddiquii CBS196.62
7RM IJKCJM
C
OJHDJD
N
0.050
(A)
Figure 1. Cont.
64
BS 137271
Clade A
B. maydis
+ 10 more isolates
FIP532
Clade B
Pathogens 2021, 10, 1621
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KX668615 BmSkRj4
.H J P
99/1
87/1
CBS 730.96
2
Bm
F
2
Bm
F
2
Bm3D8F
. OL BAN CBS 274.52
-/0.99
2
. J AM
Bm9I D
H O CBS 102.42
. PN BKH ICMP 6149
C. richardiae BRIP 4371
-/0.98
C. graminicola BRIP 23186a
C. siddiquii CBS 142.78
88/0.99
C. papendorfii CBS 308.67
CI. sporobolicola BRIP 23040b
97/1 KX668606 BmMdKa6
83/1
-/1
B . zeicola FIP 532
B. zeae BRIP 115121soP
B. eleusines CBS 274.91
B. sorokiniana CBS 110.14
88/1
B. salviniae CBS 308.90
95/1
B. cynodontis CBS109894
B. oryzae MFLUCC 10-0715
B. yamadae CBS 202.29
B. maydis CBS 137271
KX668614 BmBsRj4
KX668613 BmPhRj4
KX668609 BmKgUa1
97/1
Clade A
B. maydis
+ 10 more isolates
KX668611 BmAmRj4
Alternaria alternara CBS 916.96
Pyrenophora chaetomioid DAOM 208989
0.050
(B)
Figure 1. (A). Maximum likelihood tree obtained by MEGA X derived from glyceraldehyde 3-phosphate dehydrogenase
(GAPDH) sequence data of 20 fungal isolates causing maize leaf blight (MLB) within reference sequences obtained from
Pathogens 2021, 10, 1621
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GenBank. The bootstrap values ≥ 70% and posterior probabilities ≥ 0.95 from Bayesian analysis are indicated above
the branches, respectively. The scale bar refers to the number of nucleotide substitutions per site. The tree is rooted to
Pyrenophora chaetomiodes. The leaf names in bold letters refer to isolates used in this investigation. (B). Maximum likelihood
tree obtained by MEGA X derived from internal transcribed spacer (ITS) sequence data of 20 fungal isolates causing
maize leaf blight (MLB) within reference sequences obtained from GenBank. The bootstrap values ≥ 70% and posterior
probabilities ≥ 0.95 from Bayesian analysis are indicated above the branches, respectively. The scale bar refers to number
of nucleotide substitutions per site. The tree is rooted to Pyrenophora chaetomiodes. The leaf names in bold letters refer to
isolates used in this investigation.
(A)
(B)
Figure 2. Cont.
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(C)
Figure 2. (A). Conidial morphology of various fungi. Panels a to m, culture of Bipolaris maydis isolates (Bar = 20 µm)
(BmPhRj4, BmBjUa1, BmBsRj4, BmDhBh3, BmCgRj4, BmPnDl2, BmDnRj4, BmKgUa1, BmKrHr2, BmKtRj4, BmLdPj2, BmPtUa1,
Pathogens 2021, 10, 1621
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and BmMyKa6); panel n, B. zeicola (BmMdKa6); panels o & p, Curvularia papendorfii (BmGdGj5 and BmAdGj5); panel q,
C. sporobolicola (BmLhRj4); panel r, C. siddiquii (BmSkRj4); panel s, C. graminicola–like (BmSmBh3); panel t, Alternaria sp.
(BmAmRj4). (B). Cultural variations among various fungi. Panels a to m, culture of Bipolaris maydis isolates (BmPhRj4,
BmBjUa1, BmBsRj4, BmDhBh3, BmCgRj4, BmPnDl2, BmDnRj4, BmKgUa1, BmKrHr2, BmKtRj4, BmLdPj2, BmPtUa1, and
BmMyKa6); panel n, B. zeicola (BmMdKa6); panels o & p, Curvularia papendorfii (BmGdGj5 and BmAdGj5); panel q, C. sporobolicola (BmLhRj4); panel r, C. siddiquii (BmSkRj4); panel s, C. graminicola–like (BmSmBh3); panel t, Alternaria sp. (BmAmRj4).
(C). Symptoms of maize leaf blight (MLB) caused by various fungi. Panels a to m, symptoms caused by Bipolaris maydis
isolates (BmPhRj4, BmBjUa1, BmBsRj4, BmDhBh3, BmCgRj4, BmPnDl2, BmDnRj4, BmKgUa1, BmKrHr2, BmKtRj4, BmLdPj2,
BmPtUa1, and BmMyKa6); panel n, B. zeicola (BmMdKa6); panels o & p, Curvularia papendorfii (BmGdGj5 and BmAdGj5); panel
q, C. sporobolicola (BmLhRj4); panel r, C. siddiquii (BmSkRj4); panel s, C. graminicola–like (BmSmBh3); panel t, Alternaria sp.
(BmAmRj4); u & v are mock–inoculated control and uninoculated samples, respectively.
The number of septa of various isolates ranged between one to three (BmgGdGj5,
Godhra isolate) to five to eight (BmBjUa1, Bajaura isolate) (Table 2; Figure 2A). For the rest
of the isolates, it was in the order BmAmRj4 (Amberi) = BmLhRj4 (Lakhawali) > BmKrHr2
(Karnal) > BmMdKa6 (Mandya) > BmPnDl12 (Patel Nagar) > BmBsRj4 (Banswara) =
BmLdPj2 (Ludhiana) > BmDhBh3 (Dholi) > BmPtUa1 (Pantnagar) = BmMyKa6 (Mysore) >
BmCgRj4 (Chittorgarh) > BmAdGj5 (Anand) > BmSkRj4 (Sukher) > BmSmBh3 (Samastipur)
> BmKtRj4 (Kota) = BmDnRj4 (Dungarpur) = BmPhRj4 (Pichola) (Table 2).
Various cultural characteristics like radial growth, colony texture, color, and diameter
revealed that the isolates from Banswara, Chittorgarh, Patel Nagar, Dungarpur, Kangra,
Karnal, Godhra, Mandya, and Mysore had fast radial growth on PDA, whereas isolates from
Pichola, Bajaura, Dholi, Kota, Pantnagar, Amberi, Lakhawali, and Samastipur were medium
growing and isolates from Ludhiana and Sukher were slow growing. The isolate BmMdKa6
(Mandya) had the fastest radial growth, whereas BmLdPj2 had the slowest growth. Colony
colors were light black (BmPhRj4 and BCgRj4); light grey (BmDnRj4, BmMdKa6, BmMyKa6);
dark grey (BmKgUA1, BmKrHr2, BmBmLdPj2, BmPtUa1, BmLhRj4, BmSkRj4, BmSmBh3) and
black (BmBjUa1, BmBsRj4, BmDhBh3, BmPnDl12, BmKtRj4, BmGdGj5, BmAmRj4, BmAdGj5)
(Figure 2B).
The culture morphology of C. papendorfii showed a rough surface with irregular
margins and no zonation, conidial dimensions 7.6 µm × 3.1 µm to 16.9 µm × 4.1 µm, and
one or more septa (Table 2) which falls into Group-2 (Table S2); whereas B. zeicola showed
smooth appressed surface with regular margins and zonation, conidial dimensions 7.8 µm
× 6.1 µm to 13.1 µm × 3.8 µm slightly larger than C. papendorfii, and 3 to 4 septa (Table 2)
formed Group-5 (Table S2). The C. papendorfii isolate from Godhra showed a rough raised
surface while the Anand isolate showed a rough appressed surface with no zonation and
smooth margins. The conidial size was also very small, with 1 to 2 septa, and ranged from
7.6 to 12.1 µm × 3.1 to 4.3 µm. Ecologically both B. zeicola and C. papendorfii prevailed in
different parts of the plateau and hill regions which are at high altitudes with cool and
moist climates close to the sea (C. papendorfii from the western part having sandy loam
soil and B. zeicola from the southern part of the plateau and hill region having laterite
soils). Isolates from Lakhawali, Sukher, and Anand showed variable morpho–pathogenic
profiles and represented different groups being different species in the genus Curvularia.
The conidia of the C. sporobolicola (Lakhawali) isolate were slightly curved with 2 to 3 septa,
conidial size ranging from 17.2 µm × 3.7 µm, forming a rough colony with zonation and
irregular margins. However, the C. siddiquii (Sukher) isolate had conidial sizes smaller
than the C. sporobolicola isolate (i.e., 16.8 µm × 3.1 µm in size) with a slight curvature,
3 to 4 septa, smooth appressed colony, no zonation, and rough margins. The conidial
morphology of C. papendorfii was oval or obpyriform with 1–3 septa. The C. graminicola–like
sp. (Samastipur) isolate produced sickle-shaped conidia with 2 to 3 septa, ranging in size
from 7.8 to 6.1 µm and 2.6 µm average diameter. Alternaria sp. was also isolated from
maize in some regions from the Amberi hotspot in Rajasthan.
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2.4. Pathogenic Variability of Fungal Isolates on Zea mays c.v. DHM 117
Koch’s postulates experiments were performed for all 20 isolates, and all were positive
for causing MLB disease. The MLB symptoms appeared as small yellowish necrotic spots
3 to 4 days after inoculation of the test plants, Zea mays c.v. DHM 117. Necrotic spots
coalesced with the progression of the disease resulting in blight symptoms. The severity
of the disease differed between the isolates (Figure 2C). In general, isolates identified
molecularly as Curvularia spp. (SN 15 to 19, Table 2) and Alternaria sp. (SN20, Table 2)
caused more severe disease with scores of 3.3 to 4.5 and an average score of 3.91, than
isolates identified as B. maydis (SN 1 to 13, Table 2) or B. zeicola (SN 14, Table 2), with scores
of 1.5 to 4.3 and an average score of 2.65. The type of lesions on the leaves differed, and
thus, we categorized them into Types I to VI (Table 2). The type of lesions was overlapping
between the isolates identified as Bipolaris spp. and those identified as Curvularia spp.
The isolates BmPhRj4, BmDhBh3, BmKrHr2, BmGdGj5, and BmMdKa6 produced Type-I
symptoms but mild and moderate to severe virulence within 48 to 72 h after inoculation.
The isolates BmBjUa1, BmCgRj4, BmDnRj4, BmKgUa1, BmLdPj2, and BmPtUa1 showed
Type-II symptoms with 48 to 76 h incubation period and moderate to severe virulence.
Type-III symptoms were shown by isolates BmBsRj4, BmPnDl2, BmKtRj4, and BmLhRj4
with 48 to 96 h incubation period and mild and moderate to severe virulence. Type-IV
symptoms were observed in isolates BmAmRj4 and BmMyKa6 with an incubation period of
72 h and severe virulence. Isolates BmSkRj4 and BmSmBh3 showed Type-V symptoms with
a 72 to 76 h incubation period and severe virulence. Type-VI symptoms were expressed by
isolate BmAdGj5 with a 72 h incubation period and severe virulence.
The colony texture of isolates correlated with their pathogenic characteristics resulting
in the categorization of the isolates into six groups (Table S1; Figure S3). Group-1, represented 64 samples (18.28%) of the total population examined, and had rough colonies with
no zonation and irregular margins as shown by isolates BmPhRj4, BmAmRj4, and BmLdPj2.
The isolates of this group had mild to moderate virulence, an incubation period of 72 h on
the host, and disease severity of 1.5 to 4.3 on the rating scale; the highest virulence being
recorded was for BmLdPj2. Group-2 with 71 samples (20.28%), had rough colonies with
no zonation and regular margins, as shown by isolates BmBjUa1, BmCgRj4, BmPtUa1, and
BmGdGj5, had moderate virulence, an incubation period of 48 to 72 h and disease severity of
2.6 to 3.3. Group-3 with 26 samples (7.42%) had rough colonies with zonation and irregular
margins, as shown by BmPnDl12 and BmLhRj4, which had moderate to high virulence, an
incubation period of 72 h, and disease severity of 2.7 to 3.7. Group-4 with 110 samples
(31.42%), had smooth appressed colonies with no zonation and regular margins, as shown
by isolates BmBsRj4, BmDnRj4, BmKgUa1, BmKrHr2, BmKtRj4, and BmSmBh3, had mild
to high virulence, an incubation period of 48 to 96 h and disease severity of 1.9 to 3.6.
Group-5 with 40 samples (11.42%) had smooth appressed colonies with zonation and
regular margins, as shown by isolates BmMdKa6, BmMyKa6, and BmSmBh3 had mild to
high virulence, an incubation period of 72 to76 h, and disease severity of 1.7 to 4.3. Finally,
Group-6 with 39 samples (11.14%) had rough appressed colonies with no zonation and
regular margins and high virulence, a 72 h incubation period, and disease rating of 3.7
to 4.5.
Based on the expression of symptoms (Type-I to -VI, Figure 2C), the isolates were
categorized into six groups. The morphological and pathological variations of B. maydis
isolates were distributed among all six groups, whereas Curvularia isolates were distributed
from Group-2 to Group-6, and Alternaria sp. came under Group-1 (Table S1). B. maydis
was the dominant pathogenic species out of the total population of MLB collected across
20 hotspots in six maize production zones being identified in 72.85% of the 350 disease
samples collected, followed by Curvularia species being identified in 20.28% of the samples.
A few instances of B. zeicola (3.71%), C. papendorfii (3.42%), and Alternaria sp. (3.14%)
were also detected from the MLB samples. Mixed infection of B. maydis, C. papendorfii,
and Alternaria sp. were noticed from the same leaf in Mysore (Karnataka state), Amberi
(Rajasthan state), and Anand (Gujarat state) (data not shown).
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Visually the symptoms of B. maydis could be differentiated from B. zeicola in having
oval lesions (4 to 5 mm × 7 to 9 mm) which later elongated and coalesced into larger
irregular necrotic lesions along the mid rib (9 to 12 cm), whereas B. zeicola produced circular
to oval dot–like yellowish necrotic lesions (2 mm × 3 mm) which did not coalesce with the
progression of the disease (Figure 2C). The lesions increased in circumference but remained
distinct, increasing in size up to 1.2 cm × 2.5 cm. However, for both the B. maydis and
B. zeicola isolates, no lesions could be observed on husks and leaf sheaths, and no wilting
was observed in the diseased plants in field observations as well as in the greenhouse
inoculation experiments. This may serve as a preliminary indication that the isolates
of B. maydis observed in our survey belong to race type “O” (20). B. maydis showed an
extensive distribution across all maize cropping zones.
The C. papendorfii isolates formed very minute dot-like, yellowish necrotic spots more
profuse than symptoms caused by B. zeicola the lesions showing irregular purplish brown
margins (3 mm × 5 mm) which remained discrete and showed no coalescence with progression in size of spots, whereas C. sporobolicola and C. siddiquii formed tan colored streaks
on the leaves. While C. sporobolicola showed coalescence of streaks to form large necrotic
streaks on the leaf (Figure 2A, plate q), the C. siddiquii isolate formed elongated mosaic-like
streaks which remained discrete and did not coalesce. Symptoms of C. graminicola were
close to C. papendorfii; however, the lesions were smaller than those formed by C. papendorfii
with no purplish margins, and coalescence with the progression of the symptoms was
observed. The C. papendorfii and B. zeicola isolates were weakly to moderately pathogenic
on maize in the plateau and hill regions of India. Another pathogen, Alternaria sp. was
detected to cause MLB in India. Symptoms of Alternaria were visible as discrete oval to
irregularly elongated, yellow necrotic spots (1.3 cm × 2.7 cm to 2.5 cm × 3.7 cm), discrete
and larger in size than with B. maydis, C. papendorfii, and B. zeicola. With disease progression,
lesions coalesced up to 2.7 cm × 3.4 cm in size, but not as large irregular elongations. Symptoms of Curvularia sp. generally were scattered 3 to 5 mm × 6 to 7 mm lesions, visible as
mosaic patterns on the leaf lamina, which coalesced to form necrotic regions on leaves.
3. Discussion
Maize leaf blight (MLB) is listed as a major biotic stress on maize in India, and every
year monitoring visits are undertaken to survey the disease-prone areas to examine yield
losses due to the disease [1,2]. Precise characterization of the species infecting the maize
crop is needed for developing effective strategies to manage the economic losses. In the
global climate change scenario, it is very important to examine the trends in yield losses and
the severity of MLB on the crop within different cropping zones. In the current investigation,
for molecular identification of fungi obtained from MLB samples, we depended primarily
on the section of the GAPDH gene, which has been regarded as the best single marker for
delineating species of the genus Bipolaris [29]. Additionally, we used phylogeny based
on ITS to further support of the results. B. maydis was identified in 13 of 20 hotspots
surveyed. This observation supports B. maydis as the dominant MLB pathogen in India [3].
However, B. zeicola was present in one hotspot. These two species were the only Bioplaris
species detected in our relatively small sample size for characterizations. Our results are in
agreement with the survey in China where they found that these two species accounted
for about 97% of Bipolaris species causing diseases in maize [20]. In Yunnan, Sichuan,
and Shaanxi Provinces of China, B. zeicola isolates were reported to produce long, narrow
linear lesions [8,20,30,31]. However, the pathogenicity of the Indian isolate of B. zeicola is
slightly different from the Chinese isolates. Isolates of B. maydis from different hotspots
across six maize production zones of India showed mainly Type-I, -II, and -III symptoms
(Table 2; Figure 2C). Therefore, elongated, necrotic lesions were the typical symptoms
caused by B. maydis, as reported in previous studies [3,28]. Although the association of B.
zeicola (synonym B. carbonum) in healthy maize seeds [32] and on healthy rice leaves [33] in
India were noted earlier, the reports lacked pathogenicity data of the respective organisms.
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B. zeicola is also reported to be a pathogen of rice and maize in China [34] and a pathogen
of rice in Pakistan [35].
Of the four reported races of B. maydis viz. O, T, C, and S [14,36], lesions of race O were
tan in color with buff to brown borders. They began as small, diamond-shaped lesions
and sometimes elongated within the veins to become larger and rectangular. However,
race O lesions were contained within the leaves. Lesion size ranges from 2 to 6 mm × 2 to
22 mm. Lesions produced by race T were oval and larger than those produced by race O
and isolates of race T commonly affected husks and leaf sheaths. Lesions caused by race
C were necrotic and found to be about 5 mm long. They also tended to cause wilt [14].
While it is beyond the scope of this study, based on symptomatology we conclude that
the B. maydis isolates observed in our survey belong to race O. Race O was also found
to be the predominant pathogen of maize in India by other workers [27,37]. Studies on
the virulence of B. maydis and B. zeicola isolates revealed that both are adapted to distinct
ecological conditions [31,38,39]. It was reported that race 3 of B. zeicola with narrow linear
lesions on the leaves of mature maize plants may have been a mountain ecotype, favoring
high humidity and cool temperatures at high elevations for infection. However, in our
study B. zeicola produced dot-like, spherical lesions.
In recent years variations in MLB symptoms on maize have been noticed in India.
This points towards the likely establishment of other species/races also infecting maize.
In substantiation, we report for the first time that along with B. zeicola, four Curvularia
pathogens (C. papendorfii, C. sporobolicola, C. siddiquii, C. graminicola–like fungus), and
Alternaria sp. are pathogens causing MLB disease in India. Earlier, a leaf spot disease of
maize caused by C. clavata and maize leaf spot caused by C. geniculata were recorded in
India [25,40]. The presence of C. papendorfii in rice soil [41] has been documented from
India but the report lacked any pathogenicity data for the organism. However, the presence
of four Curvularia species in five out of 20 molecularly identified pathogens raises concern
that Curvularia is an emerging threat to maize in India. C. sporobolicola was shown to be a
pathogen of the grass Sporobolus australasicus in Australia [42] and C. siddiquii a pathogen
of Pennisetum americanum in India [43], C. graminicola was isolated from Aristida ingrata
(Poaceae) in Australia [44], and a taxonomically close relative of the fungus (Curvularia sp.
BRIP 61674) was found to be a pathogen of Oryza spp. in Australia [45]. Furthermore, C.
papendorfii (synonym: B. papendorfii) was shown to be a pathogen of maize in China [46].
Alternaria species including A. tenuissima, A. alternata, and A. burnsii were shown to cause
disease in maize [47,48]. Migration of these pathogenic fungal species to maize may have
happened from adjacent sugarcane or rice fields or due to secondary inoculum developed
on previous crops in the rotation schedule, which necessitates further investigations.
Previous investigations on the characterization of maize pathogens from MLB disease
prone maize production zones indicated the presence of the disease caused by B. maydis
in all the maize production zones, especially in Kharif maize [3,28]. C. papendorfii and B.
zeicola were characterized by Godhra and Mandya hotspots which were in the plateau and
hill region. In addition to the widely distributed B. maydis and minor reports of B. zeicola,
some other Bipolaris species such as B. sorokiniana have also been reported in other countries
as harmful pathogens of maize [4,49,50]. Interestingly, B. sorokiniana that causes wheat
root rot and leaf spot was the dominant species infecting wheat in India [51]. Therefore,
the chance establishment of this species on maize, particularly in traditional wheat–maize
rotations is probable. B. sorokiniana has been reported from maize fields under wheat–maize
rotation in Sichuan [20]. Here it is worth mentioning that reports of B. sorokiniana as a
dominant species infecting wheat in India can be an emerging threat to maize because the
crop cycle of spring maize has some overlap with the wheat season. Similarly, B. sacchari a
pathogen of sugarcane in India [43], was also reported as a pathogen of maize in China [52].
Recently, a new sheath spot disease of maize caused by Waitea circinata var. prodigus has
been reported from eastern India [53]. Therefore, regular monitoring in maize fields for the
possible presence of new or emerging pathogens along with B. maydis, B. zeicola, Curvularia
Pathogens 2021, 10, 1621
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spp., and Alternaria sp. (this report) are necessary to document various fungi causing MLB
in India.
Our studies on pathogenicity supported previous reports, however, severity varied for
different isolates. Although isolates of B. zeicola, C. papendorfii, C. sporobolicola, C. siddiquii,
and C. graminicola–like pathogens showed weak, moderate to severe virulence on maize,
their occurrence is a concern for the Western and Southern Plateau and Hill region. Their
incidence may rise in the future with changing environments. Hence, it is essential to
test the virulence on maize lines and to establish the lines showing severe infection for
advisories to avoid huge maize losses. We suggest a more rigorous screening of maize
germplasm under simulating epiphytotic conditions to examine the pathogenicity of
species of Bipolaris, Curvularia, and Alternaria at high altitudes and cold regimes. The race
diversity of B. maydis, B. zeicola, Curvularia spp., and Alternaria sp. on maize also needs to
be investigated to avoid complications of possible mixed infection.
Taken together, we explored the species diversity of fungi causing MLB in maize
production zones of India based on cultural morphology and symptoms on the host. We
found that B. maydis was the dominant species infecting maize in all geographical locations
surveyed. The isolates of B. maydis also showed a variation in symptoms on Zea mays
c.v. DHM 117. The B. zeicola, C. papendorfii, C. sporobolicola, C. siddiquii, C. graminicola–like
fungus, and Alternaria sp. are six new species we identified to cause MLB in India. Of these
C. sporobolicola, C. siddiquii, C. graminicola–like fungus are probably the first worldwide
reported as pathogens of maize. The symptoms of the four Carvularia species and the
Alternaria sp. recorded on maize in India were more severe than the dominant species
B. maydis probably due to more rigorous crop management strategies against the target
species. These species recorded in the study reported here were occasionally able to cause
mixed infections in the field but were distinguished by pure culture isolations and symptom
expressions on test plants. These findings may contribute greatly to the understanding of
the species diversity in the maize production zones of India and aid in the diagnosis of
MLB pathogens and management.
4. Materials and Methods
4.1. Collection and Maintenance of Isolates
Maize leaves showing characteristic maize leaf blight (MLB)–like symptoms (n = 350)
were collected from maize fields across the different agro-climatic zones of India covering
the states of Uttaranchal, Himachal Pradesh, Karnataka, Haryana, Delhi, Rajasthan, Bihar,
Gujarat, and Punjab (Figure S1). Surveys were undertaken in disease prone areas to collect
different fungal isolates from maize showing leaf spots and blights (Table 1). Symptomatic
samples were thoroughly washed in sterile water and 1–2 mm bits of infected leaf tissue
showing lesions were cut and surface sterilized using 2% sodium hypochlorite for 5 min,
washed with sterile water, and blotted dry. The sterilized bits were then transferred
aseptically into Petri plates containing PDA These plates were incubated at 25 ± 1 ◦ C in a
BOD Incubator (REMI Cl-10, Mumbai, India). Pure cultures of isolates were established
by single spore isolation and examined under a light microscope (Olympus BX-53, Tokyo,
Japan) to study characteristic features. The fungal isolates were maintained at standard
storage conditions on PDA slants for further studies. From a total of 350 samples analyzed,
20 fungal isolates representing candidate isolates for each location surveyed were further
examined to assess the MLB causing fungal species diversity.
4.2. Fungal DNA Extraction, Amplification, Sequencing and Phylogenetic Analysis
Growth plugs (10 mm diameter) from actively growing 7-day-old cultures of 20 fungal
isolates (Table 1) maintained on PDA were inoculated into 100 mL of potato dextrose broth
media in Erlenmeyer flasks and incubated at 25 ◦ C in a BOD incubator, with shaking at
100 rpm. Mycelia were harvested with a sterile Whatman No. 4 filter disk and Buchner
funnel attached to a vacuum flask. Then, mycelia were washed with sterile distilled water,
Pathogens 2021, 10, 1621
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blotted dry between layers of tissue paper, wrapped in aluminum foil, frozen in liquid
nitrogen, and stored at −80 ◦ C until needed.
Genomic DNA was extracted using the Cetyltrimethylammonium bromide (CTAB)
method [54]. DNA concentrations were determined using a Pico-drop Spectrophotometer
(Pico-drop Ltd., Cambridge, UK), and the concentration adjusted to 200 ng/µL. DNA
solutions were stored at −80 ◦ C until used.
PCR was performed to amplify the internal transcribed region of the rRNA gene
using primers ITS1 and ITS4 [55]. The PCR mixture (50 µL) contained 10 µL of 5× PCR
Go TaqFlexi buffer (Promega Corp., supplied by Pragati Biomedical, New Delhi, India),
0.2 mM dNTPs, 0.2 µM of each primer, and 1.25 units of Taq Polymerase GoTaq Flexi
(Promega Corp., Pvt. Ltd., Mumbai, India). Reaction mixtures in PCR vials were placed in
a thermocycler (CT-100 Bio-Rad, Gurugram, India). The program used for amplification
consisted of an initial 2 min denaturation at 94 ◦ C, followed by 35 cycles of 1 min denaturation at 94 ◦ C, 1 min annealing at 55 ◦ C, and 1 min extension at 72 ◦ C. The program
was concluded with a 10 min extension at 72 ◦ C. PCR amplification was checked by gel
electrophoresis on 1% agarose gels stained with ethidium bromide. PCR products of 439 to
587 bp were excised from the gel and cleaned using the Wizard® SV Gel and PCR Clean–Up
System (Promega Corp., Madison, WI, USA). Cleaned PCR products were sequenced using
an ABI 3730 XL Sequencer (Xcleris Labs Pvt. Ltd., Ahmedabad, India).and the BigDye
Terminator cycle sequencing kit (Applied Biosystems, Foster City, CA, USA). Products were
analyzed directly on a 3730 XL DNA sequencer (Applied Biosystems). Both DNA strands
were sequenced with primers ITS1 and ITS4 in separate reactions. PCR for amplification of
GAPDH was performed as described for ITS above except that the annealing temperature
used was 52 ◦ C and the primers were GPD-1 and GPD-2 (12). All sequences were submitted
to GenBank (Table 1) and subjected to the Basic Local Alignment Search Tool (BLAST)
available at http://blast.ncbi.nlm.nih.gov/Blast.cgi (accessed on 12 October 2021).
4.3. Phylogenetic Analysis
ITS sequences for 20 isolates under study plus additional sequences of reference strains
obtained from GenBank (Table S1) were aligned using MEGA X [56] and then manually
adjusted if needed in Mesquite [57]. Ends of the alignment were cut to make the analysis
on common regions for all the taxa. Phylogeny trees derived from ITS sequences were
constructed using maximum likelihood with substitution model K2 + g obtained by MEGA.
Support for the branches was obtained with bootstrap, 500 replicates. Phylogeny trees were
also obtained with Mrbayes (3.2.7a) [58]. The Bayesian analysis used the DNA substitution
model of Kimara 2 parameter (K2 + G, nst = 2) with gamma distribution determined using
MEGA X. Four chains and 1,000,000 Markov chain–Monte Carlo generations were run, and
the current tree was saved to a file every 1000 generations. The stability of likelihood scores
was confirmed with the plot of likelihood score versus generation number in Microsoft
Excel. 25% of the initial trees were discarded as the burn–in phase. Posterior probabilities
of above 95 were considered significant support for the clades. The maximum likelihood
and the Bayesian trees were rooted to Pyrenophora chaetomioides.
GADPH trees of the twelve GenBank accessions (Table S1) and the 19 isolates under
investigation were also obtained with two methods, maximum likelihood with MEGA X
and Bayesian, as described for ITS. The models used for both trees were K2 + G, obtained
with MEGA X. Character status of the data was obtained with MEGA X.
4.4. Cultural and Morphological Variation
Single-spore-purified fungal cultures from maize leaf spots were maintained on PDA
in 100 mm × 15 mm sterile polystyrene Petri plates (Fisher Scientific, Thane, India). For
observations of morphological variability, 5 mm plugs of the seven-day-old culture of
the isolates were placed in the center of the PDA plates and incubated at 27 ± 1 ◦ C in a
BOD incubator with alternate light and dark for 12 h daily. Observations were recorded
in triplicate. Morphometric variations in the size of conidia and number of septa were
Pathogens 2021, 10, 1621
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examined at 100× magnification with the BX-53 microscope fitted with a camera and
imaging software. The length and width of conidia as well as the number of septa were
observed microscopically and compared with the identification key of Manamgoda et al.,
2014 [4]; measurements being taken using Biovis Image Plus Software with advanced image
analysis and image processing tools (developed by Expert Vision Labs, Mumbai, India).
Averages of 10 conidia in a microscopic field are presented in Table 2. The observations on
colony color and texture were recorded for 10 days after inoculation (DAI) from the top
and bottom sides of the culture plates. The isolates were designated to different groups
based on cultural characteristics. Observations on radial growth patterns were recorded at
24 h intervals and the final growth at 10 DAI is presented in Table 2. Average radial growth
was recorded, and the cultures were assigned as fast (+++), medium (++), and slow (+)
groups (Table 2).
4.5. Pathogenic Variability
Large-scale growth of inoculum was done on sorghum grains [59]. Sorghum grains
were thoroughly washed in tap water, sterilized in 2 % sodium hypochlorite for 5 min,
and soaked overnight in distilled water. Excess water from the soaked grains was drained
off through several layers of cheesecloth, the grains dispensed into aliquots of 100 g each
in 250 mL Erlenmeyer flasks, and autoclaved at 120 ◦ C for 40 min. The sorghum grains
were inoculated with bits (5 mm diameter) of actively growing culture of each of the fungal
isolates. Cultures were shaken after every two days and incubated for 10 to 15 days at
28 ◦ C. Colonized sorghum grains were dried under shade for 7 to 10 days and powdered.
Simultaneously, seeds were planted in 20 inch-diameter pots in a sterilized soil mixture
containing vermiculite, coco peat, and sand (2:2:1) in four replications of six pots each.
The Koch’s Postulates test [60] for pathogenicity of the 20 fungal isolates was conducted on the susceptible maize inbred line DHM117 in the greenhouse under controlled
conditions (28 ± 2 ◦ C temperature, relative humidity 85%, and 16 h photoperiod). Inoculation of maize seedlings was done using powdered sorghum grains. Twelve seedlings
in six pots were inoculated twice viz., at the seven–leaf stage and eight days after the first
inoculation, with a small pinch of inoculum (about 100 mg) applied in the leaf whorl as
per standard techniques for disease resistance screening [61] (Figure S2). Twelve control
plants were treated with sterilized healthy sorghum seed powder only. Pots were covered
with polythene bags to maintain the desired humidity. The plants were observed daily, and
disease scoring was done up to 20 days after inoculation. The inoculation experiment was
performed a total of three times. Disease scoring was done using the rating scale of Payak
and Sharma [58], which is based upon the severity of the infected leaves after 20 days of
inoculation (1 to 5 rating scale) (Figure S2B).
1.
2.
3.
4.
5.
Very mild infection, as 1 to 2 or more scattered lesions on lower leaves of the host.
Moderate infection showing few lesions on lower leaves only of the host.
Moderate infection, with abundant lesions on lower leaves, spreading up to middle
leaves and extending to upper leaves of the host.
Severe infection showing abundant lesions on lower and middle leaves, extending to
upper leaves of the host.
Intense severity with abundant lesions on almost all the leaves showing premature
drying or necrosis of infected leaf tissue.
Pathogens from the diseased leaf spots following inoculations were reisolated and
observed to have similar morphology of the respective fungal inoculum.
4.6. Statistical Analysis
The data from cultural, morphological, and pathogenic variability was analyzed
statistically to derive significance by SAS Ver 10.0. (SAS Institute, Cary, NC, USA), with
desired statistic estimates such as Means, Standard Error (SE), Standard Deviation (SD),
Pathogens 2021, 10, 1621
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and Coefficient of Variation (CV). Percent Disease Index (PDI) was calculated based on an
average of 10 replications using the formula:
PDI = (Sum of all the ratings/maximum disease rating) × 100.
PDI > 70–100%—highly virulent (HV); PDI > 50–69%—Moderate virulence (MoV);
PDI > 20–49%—Mild virulence (MV).
Supplementary Materials: The following are available online at https://www.mdpi.com/article/
10.3390/pathogens10121621/s1, Figure S1, Hotspot locations covered under survey and surveillance
for monitoring maize leaf blight symptoms, Figure S2A, Inoculation of fungal isolates to the leaf
whorl in test plants, Zea mays at 7–leaf stage to examine the symptoms and pathogenicity; Figure S2B, Disease rating scale of Payak and Sharma [59], Figure S3, Distribution of morphological and
pathogenic variability in the total population of fungal species sampled from 6 maize production
zones of India; Table S1: Description of fungal species, strain numbers, hosts, counties, and GenBank
accessions of ITS and GAPDH used as references in the study. Table S2, Distribution of morphological
and pathogenic variability in the total population of maize leaf blight isolates sampled from six maize
production zones of India.
Author Contributions: Conceptualization, V.S.; methodology, V.S.; software, A.I.; validation, A.I.;
formal analysis, D.K.L.; investigation, V.S.; resources, K.S.H.; data curation, A.A. and S.K.; writing—
original draft preparation, V.S.; writing—review and editing, D.P.R.; supervision, D.K.L.; funding
acquisition, K.S.H. All authors have read and agreed to the published version of the manuscript.
Funding: This research was supported by DST/KIRAN, India, Grant Number: SR/WOS-A/LS221/2018(G), and USDA-ARS base fund project 8042 21220 181 000 D.
Data Availability Statement: The datasets generated during and/or analyzed during the current
study can be find in the main text and the Supplementary Materials.
Acknowledgments: We are grateful to ICAR-Indian Institute of Maize Research, Delhi/Ludhiana
(Punjab) Unit for extending facilities for this work and CCS HAU Regional Research Station, Karnal
(Haryana) for supporting pathogenicity tests. We are also grateful to all of the other Regional Research
Stations at hotspots of the disease for supporting our research.
Conflicts of Interest: The authors declare no conflict of interest in this work. All forms of financial support are duly acknowledged in the contribution. This work does not involve any human
participants or animals. All authors have offered their consent to submission.
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