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Frontiers in Microbiology 01 frontiersin.org
Whole-genome sequencing of
marine water-derived Curvularia
verruculosa KHW-7: a pioneering
study
PayalBaranda
1†, ShaikhulIslam
2†, AshishModi
1, HarshMistry
1,
SamiAlObaid
3, MohammadJavedAnsari
4,
VirendraKumarYadav
1, AshishPatel
1
*, MadhviJoshi
5*,
DipakKumarSahoo
6* and HimanshuBariya
1
*
1 Department of Life Sciences, Hemchandracharya North Gujarat University, Patan, India, 2 Plant
Pathology Division, Bangladesh Wheat and Maize Research Institute, Nashipur, Bangladesh,
3 Department of Botany and Microbiology, College of Science, King Saud University, Riyadh, Saudi
Arabia, 4 Department of Botany, Hindu College Moradabad (Mahatma Jyotiba Phule Rohilkhand
University Bareilly), Uttar Pradesh, India, 5 Gujarat Biotechnology Research Centre (GBRC),
Gandhinagar, India, 6 Department of Veterinary Clinical Sciences, College of Veterinary Medicine, Iowa
State University, Ames, IA, United States
Marine microorganisms are renowned for being a rich source of new
secondary metabolites that are significant to humans. The fungi strain KHW-
7 was isolated from the seawater collected from the Gulf of Khambhat,
India, and identified as Curvularia verruculosa KHW-7. On a next-generation
sequencing platform, C. verruculosa KHW-7’s whole-genome sequencing
(WGS) and gene annotation were carried out using several bioinformatic
methods. The 31.59 MB genome size, 52.3% GC, and 158 bp mean read length
were discovered using WGS. This genome also contained 9,745 protein-
coding genes, including 852 secreted proteins and 2048 transmembrane
proteins. The antiSMASH algorithm used to analyze genomes found 25
secondary metabolite biosynthetic gene clusters (BGCs) that are abundant
in terpene, non-ribosomal peptide synthetase (NRPS), and polyketides type
1 (T1PKS). To our knowledge, this is the first whole-genome sequence report
of C. verruculosa. The WGS analysis of C. verruculosa KHW-7 indicated that
this marine-derived fungus could be an efficient generator of bioactive
secondary metabolites and an important industrial enzyme, both of which
demand further investigation and development.
KEYWORDS
Curvularia verruculosa KHW-7, whole-genome sequencing, secondary metabolites,
marine microorganism, functional genomics
Introduction
Curvularia is a genus of fungi that includes several species, many of which are plant
pathogens. is fungal genus is recognized for causing diseases in several economically
important agricultural crops, including maize, wheat, barley, rice, and grasses (Huang etal.,
2005; Shirsath etal., 2018; Wang etal., 2022). Moreover, this fungus can also cause various
types of infections in humans and animals (Samaddar etal., 2023). Curvularia infections can
range from moderate to severe and aect numerous regions of the body, including the skin,
OPEN ACCESS
EDITED BY
Long Jin,
Nanjing Forestry University, China
REVIEWED BY
Sankarasubramanian Jagadesan,
University of Nebraska Medical Center,
UnitedStates
Soham Sengupta,
St. Jude Children’s Research Hospital,
UnitedStates
*CORRESPONDENCE
Ashish Patel
uni.ashish@gmail.com
Madhvi Joshi
jd1-gbrc@gujarat.gov.in
Dipak Kumar Sahoo
dsahoo@iastate.edu
Himanshu Bariya
hsbariya@gmail.com
†These authors have contributed equally to
this work and share first authorship
RECEIVED 31 December 2023
ACCEPTED 06 May 2024
PUBLISHED 23 May 2024
CITATION
Baranda P, Islam S, Modi A, Mistry H,
Al Obaid S, Ansari MJ, Yadav VK, Patel A,
Joshi M, Sahoo DK and Bariya H (2024)
Whole-genome sequencing of marine
water-derived Curvularia verruculosa KHW-7:
a pioneering study.
Front. Microbiol. 15:1363879.
doi: 10.3389/fmicb.2024.1363879
COPYRIGHT
© 2024 Baranda, Islam, Modi, Mistry,
Al Obaid, Ansari, Yadav, Patel, Joshi, Sahoo
and Bariya. This is an open-access article
distributed under the terms of the Creative
Commons Attribution License (CC BY). The
use, distribution or reproduction in other
forums is permitted, provided the original
author(s) and the copyright owner(s) are
credited and that the original publication in
this journal is cited, in accordance with
accepted academic practice. No use,
distribution or reproduction is permitted
which does not comply with these terms.
TYPE Original Research
PUBLISHED 23 May 2024
DOI 10.3389/fmicb.2024.1363879
Baranda et al. 10.3389/fmicb.2024.1363879
Frontiers in Microbiology 02 frontiersin.org
lungs, and nails (da Cunha etal., 2013). To date, there are 131 species
of Curvularia reported worldwide as per the list of Fungorum (Quach
etal., 2022). Among these species, C. verruculosa is a signicant plant
pathogen associated with causing various diseases such as leaf spot,
blight, and ear rot in dierent plant species (Wei etal., 2022). ese
diseases can lead to signicant yield losses in agricultural production.
It has a wide geographical distribution, impacting crops in diverse
regions globally, particularly in warm and humid climates where
conditions favor its growth and spread. e fungi can survive in soil
for a long time and infect plants through their roots or wounds on
their stems or leaves. Symptoms of C. verruculosa infection vary
among crops but commonly include leaf lesions, discoloration,
wilting, and, in severe cases, the rotting of seeds or ears (Rajput etal.,
2020). Managing diseases caused by C. verruculosa can bechallenging.
e pathogen exhibits certain resistance to fungicides, and its control
oen relies on integrated management practices involving cultural,
biological, and chemical measures.
Given its ability to affect staple food crops, C. verruculosa can
pose a threat to food security, especially in regions highly reliant
on these crops for sustenance. Understanding the significance of
C. verruculosa as a plant pathogen is crucial for implementing
appropriate disease management strategies and developing
resistant crop varieties to mitigate its impact on agricultural
productivity. As a result, traditional techniques are insufficient to
determine the boundaries of a species within their respective
genus, and complete genome sequencing is required for proper
identification and characterization.
Whole-genome sequencing (WGS) involves decoding an
organism’s full DNA sequence, providing a comprehensive grasp
of its genetic backbone. In fungi, WGS plays a crucial role in their
characterization and offers several significant advantages (Ta o
etal., 2022). WGS allows for the assessment of the entire genetic
diversity within a fungal species. It helps identify variations in
genes responsible for traits such as virulence, pathogenicity, and
fungicide resistance. For fungi, accurate taxonomic classification
is essential. WGS enables precise species identification and
phylogenetic analysis, contributing to a better understanding of
fungal evolution and relationships between different species
(Quach etal., 2022). By analyzing the entire genome, it is possible
to pinpoint specific genes or gene clusters associated with
virulence and pathogenicity in fungi. WGS helps in detecting
genetic markers associated with antifungal resistance. This
information is critical in guiding treatment strategies and
developing new antifungal substances to combat resistant strains.
By comparing multiple fungal genomes, scientists can identify
conserved regions and unique genes, shedding light on species-
specific characteristics and potential targets for diagnostics or
therapeutics. WGS aids in tracking outbreaks, understanding
transmission patterns, and differentiating between strains or
isolates. However, only seven genomes of other Curvularia species
are accessible through the GenBank (NCBI) database. The
genome of the plant pathogen C. verruculosa was previously
sequenced to facilitate in-depth evolutionary research and
enhance our understanding of pathogen origin and infection
processes. The results of this study will contribute to the existing
Curvularia genome database and facilitate future investigations
into its pathogenic nature.
Materials and methods
Sample collection, isolation, and
identification of fungi
e marine water sample was collected from four divergent spots
in the sea area of the Gulf of Khambhat, India (22.1775N 72.4763 E)
(Supplementary Figure S1). Sea water was collected 10 m apart from
each spot and at 1 m depth in a germ-free container and transported
to the laboratory under cool conditions for further isolation and
purication of fungi. Fungi from collected samples were isolated using
a marine agar medium (Bonugli-Santos etal., 2015) by adopting serial
dilution followed by incubation for 48–96 h at 25°C. Single and pure
fungal colonies were picked up and further allowed for growth on
marine agar plates. A pure fungal strain, KHW-7, was identied by
morphological and microscopic observation as well as by sequencing
of amplied ITS region of the fungal gene.
DNA isolation and quality analysis
e workow for the WGS experiments is shown in Figure1.
Genomic DNA from the KHW-7 strain was extracted using the silica
spin column DNA extraction method following the manufacturer’s
manual. Subsequently, 08% agarose gel electrophoresis was performed
to check the quality of isolated genomic DNA. e presence of a single
intact band within the gel matrix is indicative of the superior quality
of isolated genomic DNA. Additionally, a 2-μl fraction of the genomic
DNA sample was subjected to spectrophotometric analysis using the
BioTeK Epoch spectrophotometer to determine the A260/280 ratio.
is ratio serves as a pivotal measure of DNA purity.
Library preparation and sequencing
e libraries were prepared using the commercially available Ion
Xpress™ Plus Fragment Library Kit (ermo Fisher Scientic,
UnitedStates) as per the manufacturer’s instructions. is process
involved stages such as DNA fragmentation, fragment purication,
ligation of fragments, fragment amplication, and nal quantication.
e commercially available Ion Library TaqMan Quantitation kit was
used for quantication purposes. e size of the fragmented DNA was
assessed (Quality Control Step) using the Agilent™ High Sensitivity
DNA Kit on the Agilent™ 2,100 Bioanalyzer, following the provided
instructions. Aer library preparation, the template was prepared
using the Ion Chef automated system according to the manufacturer’s
instructions available with the Ion 550 Kit (ermo Scientic,
UnitedStates), and the Ion 550 Chip Kit was utilized for loading
samples with the assistance of the Ion Chef, followed by sequencing
on the Ion GeneStudio S5 Plus System (Ion Torrent, ermo Scientic,
UnitedStates).
Preannotation data processing
The Ion Torrent single-end sequencing reads were subjected
to adapter and quality trimming using cutadapt (v4.7) and Trim
Baranda et al. 10.3389/fmicb.2024.1363879
Frontiers in Microbiology 03 frontiersin.org
Galore (v0.4.1) with phred score cutoff of 20. The obtained
superior quality reads were built from scratch using SPAdes
v3.13.0. The initial analysis, such as base pair calling and
trimming of sequences, was performed using the Ion Torrent
browser. This process resulted in obtaining readings of good
quality. The sequence readings were assembled de novo using the
SPAdes assembler v3.1.0 (Torrent browser) with the default
parameters. The scaffolds obtained were filtered based on their
respective length, with a minimum threshold of 500 base pairs.
Assembly statistics were generated by QUAST (v5.2.0).
Gene annotation
A repeat library was created from scratch for the chosen
assembly of the KHW-7 strain using RepeatModeler v2.0.4. This
library was then utilized as a customized library for softmasking
with RepeatMasker v4.1.5. The Funannotate v1.8.16 pipeline was
used to structurally annotate the masked assemblies. The BUSCO
database v5.7.1 was utilized to identify conserved gene models for
the purpose of training the Ab initio gene predictors such as
Augustus, glimmerhmm, and snap. The generation of gene
models was based on evidence, achieved by matching the
sequences of contigs with the unified protein sequence database
(UniProtKB; https://www.uniprot.org/) using the DIAMOND
program. Subsequently, the gene models were refined using
Exonerate. The Funannotate process utilized the
EVidenceModeler,
1
which included a weighting method, to
choose the consensus models from a pool of ab initio and
evidence-based gene models. Functional annotation of the
consensus models was conducted following the elimination of
models with insufficient lengths, gaps, and transposable
elements (TEs).
e gene models were functionally predicted using InterProScan
(v-5.67-99.0), which involved mapping to the Gene Ontology (GO)
database
2
and eggNOG-mapper (v4.5.1) based on the eggNOGorthology
database.
3
e signicantly enriched GO terms were further analyzed
to nd out the interactions among several biosynthetic pathways using
the “ClueGO”
4
plugin of the CytoScape soware (v3.7.2.0). Signal
peptides (secretome) were predicted using SignalP (v6.0) and Phobius.
5
Biosynthetic gene clusters (BGCs) were identied in the genome using
fungiSMASH,
6
which is a specialized version of antiSMASH designed
1 https://github.com/EVidenceModeler
2 https://geneontology.org/
3 http://eggnog45.embl.de/#/app/home
4 https://apps.cytoscape.org/apps/cluego
5 https://phobius.sbc.su.se/
6 https://fungismash.secondarymetabolites.org/#!/start
FIGURE1
Workflow showing whole-genome sequencing. DNA quantification is carried out following the samples’ DNA isolation. The latter stages of the WGS
procedure are sequencing and library preparation. Finally, several bioinformatic techniques are used to carry out downstream analysis. The figure was
generated using BioRender (www.biorender.com; accessed on 23rd April 2024).
Baranda et al. 10.3389/fmicb.2024.1363879
Frontiers in Microbiology 04 frontiersin.org
for fungal genomes. e tRNA and rRNA genes were detected using
tRNAscan-SE7 and Barrnap,8 respectively.
Functional annotation using the annotate pipeline
9
used to
annotate genes by performing similarity search against databases of
UniProt, Pfam, dbCAN (CAZyme), MEROPS, and BUSCO
pezizomycotina gene models. Output of InterPro, EggNog, SignalP,
Phobius, tRNAscan-SE, and antiSMASH was added to the nal
comprehensive annotation les, which can bedirectly submitted to
the National Center for Biotechnology Information (NCBI). Further
annotation was conducted using the NCBI non-redundant (NR)
genome database,
10
Pathogen Host Interactions (PHIs),
11
and the
Comprehensive Antibiotic Resistance Database (RGI-CARD).12
Results
Fungal strain identification
e fungal isolate, KHW-7, was identied using ITS gene
sequencing. is partial ITS gene sequence showed 100% homology
with reference strains of C. verruculosa. Barrnap was used to predict
rRNA genes within the assembled genome. Partial ITS gene sequence
was searched in the predicted 9 rRNA sequences of KHW-7 using
local NCBI blastn application, and Blast output produced 100%
alignment against contig574 spanning 5.8S region as well as between
start and end of 18S and 28S rRNA regions, respectively. Other
phylogenetic marker genes, glyceraldehyde 3-phosphate
dehydrogenase (gdph), found in the annotated protein sequences,
show 100% similarity with other partial gdph genes of C. verruculosa.
e taxonomy of this genome is:
Cellular organisms >Eukaryota >Opisthokonta >Fungi >Dikarya
>Ascomycota >saccharomyceta >Pezizomycotina >leotiomyceta
>dothideomyceta >Dothideomycetes >Pleosporomycetidae
>Pleosporales > Pleosporineae >Pleosporaceae > Curvularia
>Curvularia verruculosa.
Sequencing and assembly of the genome
For genome assembly, the SPAdes assembler, version 3.13.0, was
used to process and utilize a total of 6,110,868 high-quality reads. e
31.59 Mb genome of C. verruculosa KHW-7 featured a guanine–
cytosine (GC) content of 50.44%. e screened reads were ordered
into 1,323 contigs (≥500 bp), making 31,589,880 bp large genome with
81,050 N50 value. Moreover, the integrity was 97%, indicating excellent
quality of genome assembly. e circos plot of the annotated genome
of C. verruculosa KHW-7 is depicted in Figure2. Another reported
Curvularia spp. was also reported to have a genome size of 33–36 Mb
and an average 50% G + C content (Quach etal., 2022). Comparative
genome features of reported Curvularia spp. are depicted in Table1.
7 http://lowelab.ucsc.edu/tRNAscan-SE/
8 https://bio.tools/barrnap
9 https://github.com/nextgenusfs/funannotate
10 https://www.ncbi.nlm.nih.gov/refseq/about/nonredundantproteins/
11 http://www.phi-base.org/
12 https://card.mcmaster.ca/
At the species level, C. verruculosa KHW-7 is the rst sequenced whole
genome. e presence of repetitive elements, such as interspersed
repeats and low-complexity DNA sequences, in the genome assembly
is signicant due to their recognized involvement in genome length
expansion and evolution (Sun etal., 2012). Annotation of the dra
genome using funannotate pipeline and other RNA prediction tools
predicted a total of 9,877 genes, of which 9,745 mRNA (CDSs), 123
tRNA, and 9 rRNA were predicted. As per the funannotate pipeline,
complete CDSs were 9,489, and partial CDSs were 256. Predicted
multiple exon transcripts were 7,541 and single exon transcripts were
2,204, with an average protein length of 502.68. TEs are mobile genetic
elements that have a role in the occurrence of mutations, regulation of
gene expression, and rearrangement of chromosomes, enabling
populations to adapt eciently to environmental changes (Lorrain
etal., 2021). A total of 9,877 genes were functionally annotated by
performing sequence similarity searches against the Pfam, InterPro,
BUSCO, EggNOG, MEROPS, and CAZyme databases and utilizing
the SignalPsecretome prediction program. ese searches resulted in
a total of 25,199 annotations. Further, the KEGG annotation predicts
a total of 3,724 genes, the COG annotation predicts a total of 6,979
genes, and the GO terms annotation predicts a total of 6,318 genes.
(Table2). Supplementary Table S1 shows the comparison of genome
features between C. verruculosa KHW-7 and other Curvularia species.
EggNOG annotation
EggNOG-mapper annotated 75% of the predicted proteins in the
genome, assigning them to 6,979 eggNOGorthogroups, which represent
over 24 functional categories. e most abundant functional categories
were S, G, O, U, and E. ese results suggest that C. verruculosa KHW-7
is well-adapted to carbohydrate metabolism, protein turnover, and
intracellular tracking. e annotation comprised 991 putative proteins
and 6,979 proteins with conrmed functions. e proteins were
categorized as follows: 1,771 proteins were assigned Enzyme
Commission (EC) numbers, 3,374 proteins were assigned GO
assignments, and 3,803 proteins were linked to the KEGG pathways.
EggNOG annotated 6,964 proteins using Pfam, a curated protein
domain family (Figure3). While EggNOG provides a reliable and precise
genome annotation, the approach and execution of the annotation dier
conceptually from that of BlastKoala (KEGG). us, the functional
annotation was conducted utilizing the anticipated protein sequences of
the genome. BlastKoala annotated 3,724 entries (38.2%) from a total of
9,868 entries (protein sequences), and 403 pathways were classied into
22 functional categories as per Figure4 and Table3.
Interproscan and go annotation
InterProScan consolidates protein signatures from many databases
into a unied and searchable resource, leveraging their unique
capabilities to create a robust integrated database and diagnostic tool
for classifying protein sequences. InterProScan classies proteins into
families and identies important domains and sites, which is invaluable
for identifying distantly related proteins and predicting their functions.
Interproscan has annotated a total of 9,489 genes out of a total of 9,745
genes predicted, of which 6,318 are with GO annotation. A total of
3,056 genes were assigned the Enzyme Commission (EC) codes
Baranda et al. 10.3389/fmicb.2024.1363879
Frontiers in Microbiology 05 frontiersin.org
(Supplementary Figure S2; Table4). A more precise identication of
the interaction among dierent biosynthetic pathways was performed
by the CytoScape network analysis of the various signicantly enriched
GO terms (biological process, molecular function, and cellular
component), as shown in Figures5, 6 and Supplementary Figures S3, S4.
Secondary metabolites
The antiSMASH, specifically the fungal version
(fungiSMASH), analysis of C. verruculosa genome revealed 25
BGCs for secondary metabolites, of which 9 regions show
sequence similarity from 13 to 100%. C. verruculosa is found to
berich in T1PKS (Polyketides type 1) (6 hits, 13 to 100%) and
more so than with other secondary metabolites’ signals, such as
non-ribosomal peptide synthetase (NRPS) (2 hits, 46 and 50%)
and terpene (40%) (Supplementary Figure S5). The gene located
at position 73.1 exhibited a significant similarity with the choline
biosynthesis gene cluster (GenBank: CH236925.1) from
Aspergillus nidulans FGSC A4. Prior reports indicate that
administering choline and alpha-lipoic acid to Balb/c mice
resulted in a significant reduction in the levels of isoprostanes and
reactive oxygen species (ROS) produced in bronchoalveolar
lavage (BAL) fluid. This, in turn, effectively regulated oxidative
FIGURE2
Circos plot of the annotated genome of C. verruculosa KHW-7. The forward and reverse CDS. rRNA, tRNA, and GC contents are shown.
Baranda et al. 10.3389/fmicb.2024.1363879
Frontiers in Microbiology 06 frontiersin.org
stress. The administration of either choline or alpha-lipoic acid
resulted in a decrease in lipid peroxidation levels and NFkappaB
activity, as demonstrated by Mehta etal. (2009). Therefore, these
compounds can beregarded as major antioxidants. In fungi,
metabolites play a crucial role in the proliferation of filamentous
fungi (Markham etal., 1993). The genome BGC region 88.1 of
C. verruculosa exhibited significant resemblances to the Glarea
lozoyensis 1,3,6,8-tetrahydroxynaphthalene BGC (GenBank:
AF549411.1). The analysis suggests that the T1PKS gene cluster
present in the genome of C. verruculosa could beaccountable for
the synthesis of 1,3,6,8-tetrahydroxynaphthalene (T4HN). The
study conducted by Mosunova etal. (2022) showed that melanin-
forming fungus actively synthesizes T4HN using the acetogenic
pathway. T4HN was identified as a result of the pentaketide
synthase PKS1in the black fungus Colletotrichum lagenarium.
Several instances of BGCs have been documented in Aspergillus
section Nigri, which is mostly linked to the production of
bioactive secondary metabolites (Wang etal., 2023). Region 393.1
was discovered to bear a strong resemblance to the peramine BGC
observed in Epichloe festucae (GenBank: AB205145.1). Epichloë
synthesizes peramine, a compound that exhibits antibacterial,
fungicidal, and insecticidal properties. This measure protects
crops post-harvest by effectively countering phytopathogenic
organisms (Song etal., 2021).
Carbohydrate enzymes (CAZyme)
The fungal genome possesses CAZymes gene families, which
are widely responsible for many biological events, including the
degradation of lignocellulose materials (Garron and Henrissat,
2019). Functional annotation of the genes of C. verruculosa was
conducted using the CAZy database. CAZy is a specialized
database for data annotation that focuses on carbohydrate
enzymes (Brandi etal., 2009). There were 509 genes identified as
CAZymes, and they were classified into six different kinds in the
database. The genes were ranked in descending order based on
their abundance, with glycoside hydrolases (GHs) having the
highest count of 240, followed by auxiliary activities (AAs) with
133, glycosyl transfers (GTs) with 71, carbohydrate esterases
(CEs) with 47, carbohydrate-binding modules (CBMs) with 20,
and polysaccharide lyases (PLs) with 19 (Figure7). Moreover,
47.15% of total genes of CAZymes were occupied by GHs,
followed by auxiliary active enzymes (AAs) (26.12%), establishing
these fungias potent strain for the breakdown of biomaterials
mainly composed of lignin, cellulose, and hemicelluloses
(Chylenski etal., 2019). The presence of CEs, CBMs, and PLs also
confirms various plant biomass degradation capacities of
C. verruculosa (Geng etal., 2021). The comparative analysis of
CAZymes from all studied genomes of Curvularia spp. showed
similar patterns of CAZymes found in C. verruculosa KHW-7
(Quach etal., 2022). Other than GHs and AAs, the genome of
C. verruculosa KHW-7 also possesses 71 GTs family members
largely involved in the biosynthesis of various polysaccharides
and oligosaccharides (Lairson etal., 2008).
Peptidase database and transcription
factors
e MEROPS database discovered a total of 326 proteases, which
may beclassied into dierent groups, including aspartic (A), cysteine
TABLE1 General features of the C. verruculosa KHW-7 genome.
Features Number/bp
Total raw bases 1,023,799,652 bp
Good quality (>Q20) bases 849,468,143 bp
Total raw reads (sequences) 6,276,793
Good quality reads (sequences) 6,133,114
Number of assembled reads
(sequences)
6,110,868
Mean read length 158 bp
Mean GC percent 52.3%
Contigs (≥ 500 bp) 1,323
Total length 31,589,880 (31.59 Mb)
Largest contig 390,585 bp
GC (%) 50.44
N50 81,050
N90 18,713
L50 120
L90 409
TABLE2 Complete gene prediction and functional annotation of C.
verruculosa KHW-7 genome.
Gene prediction and annotation
parameters
Number
Gene prediction Total nos. of genes 9,877
Mean gene length (bp) 1638.3
Genome % covered by
genes
46.61
Total nos. of proteins 9,745
tRNA 123
rRna 9
Complete CDSs 9,489
Partial CDSs 256
Secretome prediction Secreted proteins 852
Transmembrane proteins 2048
Secondary metabolites T1PKS, NRPS, Terpene, etc. 25
Functional annotation Pfam 6,964
CAZyme 509
Merops 326
Busco 1,262
Gene ontology 6,318
InterProScan 7,316
Eggnog 7,970
NCBI NR (protein
database)
9,651
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Frontiers in Microbiology 07 frontiersin.org
(C), metallo (M), serine (S), mixed (P), and threonine (T).
Additionally, the database also includes a class for protease inhibitors
(I), as depicted in Figure8. e two highest ranking families among
the transcription factor (TF) families were the fungal Zn(2)-Cys(6)
binuclear cluster domain (IPR001138) and the fungal-specic TF
domain (IPR007219) (Figure9).
Genes regulating pathogenicity factors
The Comprehensive Antibiotic Resistance Database (CARD)
is designed as an antibiotic resistance ontology (ARO) that links
antibiotic modules with their targets, resistance mechanisms, gene
variants, and other relevant information. The Resistance Gene
Identifier has given no hits against the CARD database. Hence, no
drug resistance genes are present in the C. verruculosa
KHW-7 genome.
Genes associated with pathogenicity factors were examined
and identied utilizing the Pathogen Host Interaction (PHI)
database. Sequences from the PHI database were downloaded from
the Virulence Factor Database (VFDB). e total number of
protein sequences in the full database was 8,216. A BLAST
homology search between the DNA sequences of C. verruculosa
strain KHW-7 and PHI database proteins revealed a total of 136
hits (Supplementary Table S2).
e analysis has revealed that critical pathogenic genes exhibit a
variety of interacting behaviors, including an increase in virulence (4
genes), lethal (5 genes), unaected pathogenicity (35 genes), and key
non-pathogenic/low virulence genes, including the loss of
pathogenicity (17 genes) and reduced virulence (69 genes), are
detailed in Supplementary Table S2.
Discussion
Due to advancements in next-generation sequencing
technology, there has been a growing focus on studying fungal
genomes because of their intricate genomic and physiological
characteristics. This paper is the initial publication of a complete
genome sequencing of Curvularia verruculosa, a widely
recognized plant pathogen. The findings enhance our
comprehension of the genetic characteristics of C. verruculosa,
particularly in relation to the synthesis of diverse metabolites
and their components contributing to pathogenicity. Presently,
there are a mere eight Curvularia genomes that have been
sequenced and stored in the GenBank database maintained by
the National Center for Biotechnology Information (NCBI), and
at the species level, C. verruculosa KHW-7 is the first sequenced
genome. The 31.59 Md genome of C. verruculosa KHW-7
contained a total of 9,877 genes, which is somehow lower
FIGURE3
EggNOG COG annotation of C. verruculosa KHW-7. Proteins related to carbohydrate transport, posttranslational modifications, amino acid transport,
and intracellular tracking were significantly enriched.
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Frontiers in Microbiology 08 frontiersin.org
compared to other Curvularia species, C. lunata W3 (33.5 Mb,
10,165 protein-coding genes), C. kusanoi 30 M1 (33.3 Mb,
11,004 protein-coding genes), and Curvularia sp. IFB-Z10
(33 Mb, 9,469 protein-coding genes) (Quach etal., 2022). The
presence of repetitive components, such as interspersed
repetitions and low-complexity DNA sequences, was detected in
the genome assembly of C. verruculosa KHW-7. However, a high
repetitive content might beassociated with accelerated species
evolution (Pisupati etal., 2018).
TEs are mobile genetic units that can induce mutations, alter
gene expression, and cause chromosomal rearrangements
(Castanera etal., 2016; Lorrain et al., 2021). These processes
contribute to the successful adaptation of populations to
environmental changes. Phytophthora infestans and Blumeriagrami
f. sp. hordei are two major plant infections with large genome
sizes due to the presence of a large number of TEs, which make
up approximately 29% of the genome (Haas etal., 2009; Spanu
etal., 2010). Furthermore, the TE repertoires exhibit variations
not just at the genus level but also among closely related fungal
TABLE3 KEGG pathway prediction.
Functional categories Entries
Protein families: genetic information processing 788
Genetic information processing 719
Carbohydrate metabolism 346
Protein families: signaling and cellular processes 257
Cellular processes 231
Unclassied: metabolism 194
Amino acid metabolism 171
Protein families: metabolism 146
Environmental information processing 142
Lipid metabolism 132
Energy metabolism 110
Metabolism of cofactors and vitamins 104
Glycan biosynthesis and metabolism 68
Nucleotide metabolism 66
Organismal systems 63
Human diseases 53
Unclassied: signaling and cellular processes 24
Metabolism of other amino acids 22
Xenobiotics biodegradation and metabolism 21
Metabolism of terpenoids and polyketides 20
Biosynthesis of the secondary metabolites 9
Unclassied 29
TABLE4 GO category summary of C. verruculosa KHW-7.
GO Classification GO counts Associated genes
Biological process 15,364 4,758
Molecular function 9,319 5,372
Cellular component 10,439 4,282
FIGURE4
KEGG pathway annotation. The highest enrichment was found in the protein families related to genetic information processing, followed by
carbohydrate metabolism.
Baranda et al. 10.3389/fmicb.2024.1363879
Frontiers in Microbiology 09 frontiersin.org
taxa. In addition, TEs also serve as unique promoters that disrupt
transcription processes, hence playing a significant role in fungal
development and evolution (Mita and Boeke, 2016). The genetic
analysis detected a total of 2048 transmembrane helices related to
30 significantly enriched transcription factors in C. verruculosa
KHW-7 (Figure9). Moreover, the KEGG analysis has identified
FIGURE5
Significantly enriched GO terms (biological process). The total number of genes associated with a specific GO term and % of associated genes are
shown.
Baranda et al. 10.3389/fmicb.2024.1363879
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142 genes related to environmental information processing
(Table3). Therefore, this discovery has the potential to facilitate
the examination of the evolutionary connections and lifestyle
modifications of C. verruculosa KHW-7 across numerous
ecological habitats that have yet to bestudied.
In C. verruculosa KHW-7, 509 genes were found to berelated
to carbohydrate enzymes (CAZymes) (Figure7). CAZymes play
major roles in plant polysaccharide degradation (Ospina-Giraldo
etal., 2010). erefore, investigating and analyzing CAZymes from
fungi with distinct methods of nourishment or infection
mechanisms can yield insights into their lifestyles and infection
patterns (Zhao etal., 2013).
Conclusion
In this study, a high-quality de novo genome of the fungal
isolate C. verruculosa KHW-7 was obtained via WGS and assembly.
As per NCBI genome submission status, this is the rst WGS
sequencing of C. verruculosa. WGS has revolutionized fungal
characterization by providing a holistic view of their genetic
blueprint. From our ndings, important genome features and
annotations were produced using various open-source tools and
databases. e discovery not only aids in understanding the
biology and evolution of C. verruculosa but also holds immense
potential for guiding disease management strategies.
FIGURE6
ClueGO network analysis results of the significantly enriched GO terms (biological process). This analysis demonstrates the strong
connections between biological processes that could have a substantial impact on the biology of C. verruculosa KHW-7. These activities
include the biosynthesis of methionine and ubiquinone, 5′-flap endonuclease activity, RNA alterations, and protein insertion into
membranes.
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FIGURE7
Carbohydrate enzymes identified from the C. verruculosa genome. Most of the carbohydrates belonged to glycoside hydrolases followed by auxiliary
active enzymes.
FIGURE8
Identified proteases from the C. verruculosa genome. Cysteine was found to bethe most enriched protease, followed by metalloprotease.
Baranda et al. 10.3389/fmicb.2024.1363879
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FIGURE9
Identified TFs from the C. verruculosa genome. The fungal Zn(2)-Cys(6) binuclear cluster domain (IPR001138) was the most abundantly present TFs.
Data availability statement
e datasets presented in this study can befound in online
repositories. e names of the repository/repositories and accession
number(s) can be found at: https://www.ncbi.nlm.nih.gov/,
PRJNA1023514.
Author contributions
PB: Writing – review & editing, Writing – original dra,
Methodology, Investigation, Formal analysis. SI: Writing – review
& editing, Writing – original dra, Methodology, Investigation,
Data curation. AM: Writing – review & editing, Resources,
Methodology, Investigation, Formal analysis. HM: Writing –
review & editing, Formal analysis, Soware, Investigation. SA:
Writing – review & editing, Validation, Methodology, Formal
analysis. MA: Writing – review & editing, Validation, Data
curation, Formal analysis. VY: Writing – review & editing,
Validation, Soware, Methodology, Data curation. AP: Writing –
review & editing, Writing – original dra, Visualization,
Supervision, Conceptualization. MJ: Writing – review & editing,
Soware, Methodology, Formal analysis, Data curation. DS:
Writing – review & editing, Soware, Resources, Formal analysis,
Data curation. HB: Writing – review & editing, Writing – original
dra, Visualization, Supervision, Project administration.
Funding
e author(s) declare nancial support was received for the
research, authorship, and/or publication of this article. is project
was supported by the Researchers Supporting Project (project number
RSP2024R315) at King Saud University, Riyadh, Saudi Arabia. e
article processing charge was funded by the Publication Subvention
Grants Program to DS –For Open Access Journal Articles, Oce of
the Vice-President for Research, Iowa State University.
Conflict of interest
e authors declare that the research was conducted in the
absence of any commercial or nancial relationships that could
beconstrued as a potential conict of interest.
Publisher's note
All claims expressed in this article are solely those of the
authors and do not necessarily represent those of their affiliated
organizations, or those of the publisher, the editors and the
reviewers. Any product that may beevaluated in this article, or
claim that may bemade by its manufacturer, is not guaranteed or
endorsed by the publisher.
Baranda et al. 10.3389/fmicb.2024.1363879
Frontiers in Microbiology 13 frontiersin.org
Supplementary material
e Supplementary material for this article can befound online
at: https://www.frontiersin.org/articles/10.3389/fmicb.2024.1363879/
full#supplementary-material
SUPPLEMENTARY FIGURE S1
Sample collection site. Blue spot indicates sample collection site from
Gujarat province, India with location coordinates.
SUPPLEMENTARY FIGURE S2
Number of Curvularia verruculosa gene sequences with annotations from
dierent databases.
SUPPLEMENTARY FIGURE S3
ClueGO network analysis results of the significantly enriched GO terms
(molecular functions).
SUPPLEMENTARY FIGURE S4
ClueGO network analysis results of the significantly enriched GO terms
(cellular components).
SUPPLEMENTARY FIGURE S5
Biosynthetic gene cluster identified by antiSMASH.
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