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Open Access

Peer-reviewed

Research Article

Genomic analysis of Elsinoë arachidis reveals its potential pathogenic mechanism and the biosynthesis pathway of elsinochrome toxin

  • Wenli Jiao,

    Roles Data curation, Formal analysis, Methodology, Software, Writing – original draft

    Affiliation Department of Plant Pathology, College of Plant Protection, Shenyang Agricultural University, Shenyang, Liaoning, China

    ⨯
  • Mengxue Xu,

    Roles Writing – review & editing

    Affiliation Department of Plant Pathology, College of Plant Protection, Shenyang Agricultural University, Shenyang, Liaoning, China

    ⨯
  • Rujun Zhou ,

    Roles Conceptualization, Writing – review & editing

    zhourujun@syau.edu.cn

    Affiliation Department of Plant Pathology, College of Plant Protection, Shenyang Agricultural University, Shenyang, Liaoning, China

    ⨯
  • Yiwei Fu,

    Roles Software

    Affiliation Department of Plant Pathology, College of Plant Protection, Shenyang Agricultural University, Shenyang, Liaoning, China

    ⨯
  • Zibo Li,

    Roles Writing – review & editing

    Affiliation Department of Plant Pathology, College of Plant Protection, Shenyang Agricultural University, Shenyang, Liaoning, China

    ⨯
  • Caiyun Xue

    Roles Methodology, Writing – review & editing

    Affiliation Department of Plant Pathology, College of Plant Protection, Shenyang Agricultural University, Shenyang, Liaoning, China

    ⨯

Abstract

Elsinochromes (ESCs) are virulence factors produced by Elsinoë arachidis which is the cause of peanut scab. However, the biosynthesis pathway of ESCs in E. arachidis has not been elucidated and the potential pathogenic mechanism of E. arachidis is poorly understood. In this study, we report a high-quality genome sequence of E. arachidis. The size of the E. arachidis genome is 33.18Mb, which is comparable to the Ascomycota genome (average 36.91 Mb), encoding 9174 predicted genes. The self-detoxification family including transporters and cytochrome P450 enzymes were analysis, candidate effectors and cell wall degrading enzymes were investigated as the pathogenicity genes by using PHI and CAZy databases. Additionally, the E. arachidis genome contains 24 secondary metabolism gene clusters, in which ESCB1 was identified as the core gene of ESC biosynthesis. Taken together, the genome sequence of E. arachidis provides a new route to explore its potential pathogenic mechanism and the biosynthesis pathway of ESCs.

Citation: Jiao W, Xu M, Zhou R, Fu Y, Li Z, Xue C (2021) Genomic analysis of Elsinoë arachidis reveals its potential pathogenic mechanism and the biosynthesis pathway of elsinochrome toxin. PLoS ONE 16(12): e0261487. https://doi.org/10.1371/journal.pone.0261487

Editor: Zonghua Wang, Fujian Agriculture and Forestry University, CHINA

Received: June 25, 2021; Accepted: December 3, 2021; Published: December 16, 2021

Copyright: © 2021 Jiao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: Natural Science Foundation of Liaoning Province (CN) (2019-MS-278). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Elsinoë arachidis is a phytopathogenic fungus that causes peanut scab on Arachis hypogaea Linn., resulting in tremendous yield loss (regional losses can be greater than 50%) in peanut planting regions in China [1, 2]. Currently, disease occurrence patterns have been determined. However, the mechanism of host-pathogen interactions is largely unknown, indicating that new and effective prevention and control mechanisms of E. arachidis are urgently needed [3–6].

Interestingly, several Elsinoë produce elsinochromes (ESCs) [7], which are red, photosensitive, perylenequinone toxins. Previously, ESCs have been shown to promote electrolyte leakage, peroxidation of the plasma membrane, and production of reactive oxygen species such as superoxide (O2–). Additionally, ESCs contribute to pathogenesis and are essential for full virulence which was validated by constructing mutants in E. fawcettii of a polyketide synthase-encoding gene which is the core gene of ESC biosynthesis [8–10]. Cercosporin (Cercospora spp.) is the most well-known member of the group of perylenequinone fungal toxins. The biological functions and biosynthetic pathway of cercosporin have been clarified. Like many toxins identified in ascomycete fungi, its metabolic pathway is dependent on polyketide synthase (PKS) [11], and the other gene functions in the PKS gene clusters have also been determined. However, the biosynthetic pathway of ESCs in E. arachidis and their potential pathogenic mechanism remain to be explored. For instance, it is unclear whether, in addition to ESCs, there exist cell wall degrading enzymes or effectors that act as virulence factors in E. arachidis [12].

A growing number of studies have applied genome sequencing technology to the study of phytopathogenic fungi, such as Magnaporthe oryzae [13], Fusarium graminearum [14], Sclerotinia sclerotiorum and Botrytis cinerea [15], which has provided new research avenues for a better understanding of their genetic evolution, secondary metabolism, and pathogenic mechanisms.

The present study was aimed at exploring the possible virulence factors of E. arachidis during host invasion. We report on the 33.18Mb genome sequence of E. arachidis, the secondary metabolism gene cluster, and the discovery of 6 PKS gene clusters in E. arachidis including the ESC biosynthetic gene cluster and the core gene ESCB1. Through our analysis of the whole genome, we show that E. arachidis has a complex pathogenesis, with, in addition to the toxin, several candidate virulence factors including effectors, enzymes, and transporters. Moreover, the putative pathogenicity genes provide new horizons to unravel the pathogenic mechanism of E. arachidis.

Materials and methods

Whole-genome sequencing and assembly

In this paper, we used E. arachidis strain LNFT-H01, which was purified by single spores and cultured on potato dextrose agar (PDA) under 5 microeinstein (μE) m-2s-1. The genome of LNFT-H01 was sequenced by PacBio RS II using a 20kb library of LNFT-H01 genomic DNA under 100 ×sequencing depth and assembled by Canu [16–18]. The assembled whole-genome sequence, totaling 33.18 Mb and containing 16 scaffolds, was submitted to NCBI (GenBank accession JAAPAX000000000). The characteristics of the genome were mapped in a circus-plot.

Phylogenetic and syntenic analysis

The evolutionary history can be deduced from conserved sequences and conserved biochemical functions. In addition, clustering the orthologous genes of different genomes can be helpful to integrate the information of conserved gene families and biological processes. We calculated the closest relatives to sequences from E. arachidis within reference genomes by OrthoMCL, then constructed a phylogenetic tree by SMS implemented in the PhyML (http://www.atgc-montpellier.fr/ phyml-sms/) [19, 20]. Syntenic regions between E. arachidis and E. australis were analyzed using MCScanX, which can effectively determine the changes in chromosome structure and reveal the history of the gene family expansion [21].

Repetitive sequence

Due to the low conservation of repetitive sequence (RS) between species according to MITE Hunter, LTR FINDER, Repeat Scout, and PILER [22–25], we exploited the genome sequence to established a RS database, classified and merged by PASTEClassifier and Repbase [26, 27]. Finally, we predicted the repetitive sequences with RepeatMasker [28].

Gene prediction and annotation

The ab initio-based and homology-based methods were performed to predict gene numbers in the E. arachidis genome. A combination of Augustus, Glimmer HMM, Genscan GeneID, and SNAP [29–32] homology-based methods were used by GeMoMa [33] and the results were integrated using EVM [34]. Non-coding RNA including rRNA, tRNA, and other RNAs were also classified and analyzed. According to the structural characteristics of different non-coding RNAs, different strategies were used to predict different non-coding RNAs. Based on the Rfam [35] database, Blastn [36] was used to identify rRNA. We used tRNAscan-SE [37] to identify tRNA. As for the pseudogenes, which have similar sequences to functional genes but have lost their original functions due to mutations, we searched for homologous sequences in the genome through BLAT [38] alignment, and we then used GeneWise [39] to search for immature stop codons and frameshift mutations in the gene sequence to obtain pseudogenes. The preliminary functional annotation was conducted with multiple databases, including the Pfam, NR, KOG/COG, KEGG, and GO databases [40–43]. The pathogen-host interaction (PHI) database, carbohydrate-active enzymes (CAZy) database, and transporter classification database (TCDB) were used to identify potential virulence-related proteins [44–46].

Identification and characterization of polyketide synthases (PKSs) and secondary metabolite clusters

Secondary metabolite clusters were predicted by performing antiSMASH2 (https://fungismash.Secondarymetabolites.org). In order to confirm the function of polyketide synthase (PKS), which is the core protein that responsible for the biosynthesis of mycotoxin in different organisms, PKS sequences were used to construct the phylogenetic tree by MEGA 10.0.5. The detailed information on PKS is reported in S9 Table. Domains of PKSs were identified via InterPro (https://www.ebi.ac.uk/interpro) and their location visualized by DOG 2.0.

ESCB1 expression and toxin determination

Elsinochrome extraction and quantitation were performed as previously described [12]. As for ESCB1 expression, the strain used for the colony culture was the same as for toxin extraction. Total RNA extraction was done using TransZolTM Up Plus RNA kit (Beijing, TransGen Biotech). RT-PCR was performed using TransScript® One-Step gDNA Removal and cDNA Synthesis (Beijing, TransGen Biotech). qPCR was done using SuperMix TransStart® Green qPCR SuperMix with primers ESCB1F (ATCCGAGGTCATTGGTGATG) and ESCB1R (GAGGTTGACATCTGGC ATTTG).

Results

The characteristics of the whole-genome

Whole genome sequencing of E. arachidis was performed using PacBio RS II (100×coverage). A total of 6.28 Gb high-quality sequencing raw data were assembled by CANU into 16 scaffolds (N50, 3,376,838bp) and the characteristics that are displayed in a circus-plot (Fig 1). We analyzed the genome sequence through Augustus [29] and we identified 7,950 genes. In order to obtain accurate information, we further performed a combination of Glimmer HMM (9,277), Genscan (6,599), GeneID (11,100), and SNAP (10,175) [30–32]. By homology-based methods using GeMoMa [33], taking E. australis as a reference genome, 8,339 genes were predicted. The above results were integrated by EVM [34] showing that the E. arachidis genome contains 9,174 genes (Table 1). KOG, KEGG, and GO annotation were in S1 Fig.

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Fig 1. Circos-plot of E. arachidis.

The outermost circle is the size of the genome, each scale is 5 Kb; the second circle and third circle are the genes on the positive and negative strands of the genome, respectively (different colors represent different COG functional); the fourth circle is repeated sequence; the fifth circle is tRNA and rRNA (blue: tRNA, purple: rRNA); the sixth circle is GC content (light yellow: the GC content is higher than the average GC content, blue: the GC content is lower than the average GC content); the innermost circle is GC-skew (dark gray: the G content is greater than C, red: the C content is greater than G).

https://doi.org/10.1371/journal.pone.0261487.g001

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Table 1. Gene annotation summary statistics.

https://doi.org/10.1371/journal.pone.0261487.t001

The assembled size of the E. arachidis genome (33.18 Mb) was comparable in size to the Ascomycota genome (36.91 Mb) [47], as well as M. oryzae, (38.10 Mb), Fusarium graminearum (35.45 Mb), and Sclerotinia sclerotiorum (38.68 Mb). However, phylogenetic analysis showed that the species used in this comparative study were distinct from one another. Notably, E. arachidis was only close to Sphaceloma murrayae and E. australis (S2A Fig), but in terms of genome size, E. arachidis was larger than S. murrayae (20.72 Mb) or E. australis (23.34 Mb). Additionally, synteny analysis indicated the highest synteny between E. arachidis and E. australis (S2B Fig). Concerning the identification of repetitive DNA sequences, among 33,184,353bp of the E. arachidis genome, a total of 7,033,311bp (21.20%) repeat sequences were identified including LTR retrotransposons and DNA transposons (S1 Table).

Genes associated with detoxification

Transporters.

Transporters are membrane-associated proteins that can assist the movement of ions, amino acids, and macromolecules across the membrane, which plays an important role in a broad range of cellular activities such as nutrient uptake, the release of secondary metabolites, and signal transduction [48]. The major facilitator superfamily (MFS) and ATP-binding cassette (ABC) transporter superfamily are the two largest families of fungal transporters [48]. Among these, the ABC transporters are the primary active transporters, usually as part of multicomponent transporters, that transport different compounds including polysaccharides, heavy metals, oligopeptides, and inorganic ions. In addition, MFS transporters are secondary carriers that facilitate the secretion of endogenous fungal toxins, such as aflatoxins, trichothecenes, and cercosporin. A large number of ABC genes (57) and MFS genes (190) were found in E. arachidis (S2 Table), which represents 57% of the total number of transporters (Fig 2A). EVM0006810.1, EVM0008188.1, EVM0008646.1, EVM0004073.1, EVM0001603.1, EVM0008241.1, EVM0001951.1, EVM0000776.1, EVM0002663.1 are related to CTB4 (Table 2), which encodes the MFS transporter, and are located in the cercosporin biosynthetic gene cluster. They play a role in the secretion of cercosporin in Cercospora nicotianae and are involved in cercosporin resistance [49]. ESC, biosynthesized by E. arachidis, produces reactive oxygen species in the light acting on the cell membranes and destroying the cellular structure. Meanwhile, E. arachidis can grow and develop in the presence of high concentrations of reactive oxygen species, which suggesting the certain detoxification of E. arachidis. The ABC and MFS transporters may play functional roles in the secretion of toxins and play an important role in the virulence toward the plant.

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Fig 2. Characteristic of E. arachidis genome.

(A) Transporters of E. arachidis genome. (B) pathogen-host interaction genes in E. arachidis genome. (C) CAZymes in compared genomes. (D) Annotation of pectin and cellulase in E. arachidis.

https://doi.org/10.1371/journal.pone.0261487.g002

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Table 2. Detoxification genes in E. arachidis genome involved in PHI data.

https://doi.org/10.1371/journal.pone.0261487.t002

Cytochrome P450.

The cytochrome P450 enzymes (CYPs) are multifunctional oxidoreductases that can aid in the detoxification of natural and environmental pollutants, involved in the primary and secondary metabolism [50]. A total of 78 CYPs (S3 Table) were predicted in E. arachidis genome, of which 20 CYPs were analyzed in the PHI data (Table 2), mainly including the CYP51 and CYP52 families. The CYP51 families, the conserved fungal P450, are involved in the biosynthesis of membrane ergosterol. MoCYP51B and MoCYP51A both encode a sterol 14α-demethylase enzyme in M. oryzae that is required for conidiogenesis and mediating the action of sterol demethylation inhibitor (DMI) fungicides [51]. CYP52X1, a member of the CYP52 family, are involved in the degradation of specific epidermal lipid components in the insect waxy layer [52]. In general, the CYPs may be involved in the detoxification of the pathogen’s own toxins.

Analyses of pathogenicity proteins encoded by the E. arachidis genome

Through the pathogen-host interaction database, 2,752 potential pathogenic genes were screened in E. arachidis (Fig 2B), mainly concerning the increased virulence and effectors, the loss of pathogenicity, and reduced virulence as shown in S4 Table.

Effectors.

During the interaction between pathogens and hosts, pathogens can produce different effector proteins to change the cell structure and metabolic pathways of the host plants, thereby promoting successful infection of the host plants or triggering host defense reactions. In total, 734 genes were predicted to code for secreted proteins in the E. arachidis genome. Analysis of the PHI database revealed 25 candidate effectors (Table 3) including EVM0006757.1, a gene homologous to PemG1, an elicitor-encoding gene of Magnaporthe oryzae which triggered the expression of phenylalanine ammonia-lyase gene [53] and EVM0003806, a gene homologous to glucanase inhibitor protein GPI1 [54] secreted by Phytophthora sojae, which inhibits the EGaseA mediated release of elicitor active glucan oligosaccharides from P. sojae cell wall. The function of candidate effectors from E. arachidis needs further testing and verification, but also provides a novel research direction for the elucidation of pathogenic mechanisms.

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Table 3. Effector candidates of E. arachidis in PHI database.

https://doi.org/10.1371/journal.pone.0261487.t003

Carbohydrate-active enzymes.

The cuticle and cell wall of plants are the primary barriers that prevent the invasion of pathogens. Therefore, the ability to degrade complex plant cell wall carbohydrates such as cellulose and pectin is an indispensable part of the fungal life cycle. The CAZymes secreted by pathogenic fungi are capable of degrading complex plant cell wall carbohydrates to simple monomers that can be used as carbon sources to help pathogen invasion [55]. Mapped E. arachidis genomes with CAZy database detected 602 genes potentially encoding CAZymes (S6 Table). Subsequently, we compared the CAZyme content to other ascomycetes including necrotrophic plant pathogens (S. sclerotiorum and B. cinerea), a biotrophic pathogen (B. graminis), and hemi-biotrophic pathogens (M. oryzae and F. graminearum) (Fig 2C, S7 Table). The CAZyme-content in E. arachidis is the largest in all compared fungi genomes. This suggests that the CAZymes content does not directly correlate with the lifestyle of the fungus. Further analysis showed, that the pectin and cellulase content of E. arachidis (39) was smaller than that of the necrotrophic plant pathogens S. sclerotiorum (53) and B. cinerea (62). However, it was significantly larger than that of B. graminis (2) (Fig 2D). In addition to cell wall degrading enzymes, different pathogens likely use different strategies to penetrate plant tissues.

Secondary metabolism

Gene clusters of PKS in E. arachidis.

E. arachidis encodes 24 secondary metabolism clusters, including PKS (6), nonribosomal peptide synthetase (NRPS) (11), NRPS-PKS (1), terpene (6) (S3 Fig). The number of PKS clusters in E. arachidis were lower than in M. oryzae, similar to E. fawcettii and F. graminearum, but the number of NRPS clusters was twice that of E. fawcettii, indicating significant differences in metabolic pathways between E. fawcettii and E. arachidis (S4 Fig). We analyzed the PKS proteins from E. arachidis for conserved domains by InterProScan and visualized them using DOG 2.0. (Fig 3). We found that E. arachidis contains 8 different domains including KS, AT, TE, ER, KR, MeT, ACP, and DH. According to their domain structures, the 6 PKS genes could be further divided into reduced (EVM0002563, EVM0005988, EVM0006869) and non-reduced (EVM0003759, EVM0004732, EVM0005880) due to the reducing activity of ER and KR.

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Fig 3. Structure of polyketide synthases proteins.

The conservative domain of polyketide synthases was clarified by InterProScan, and the visualization of different domains by using DOG 2.0.

https://doi.org/10.1371/journal.pone.0261487.g003

In order to further differentiate the 6 PKS genes, 19 different PKS genes were analyzed (S8 Table). Among the 6 PKS from E. arachidis, EVM0003759 was in the same clade as EaPKS which is encoding for ESC biosynthesis in E. australis and therefore we named it ESCB1 (Elsinochrome Biosynthesis gene 1). Interestingly, EVM0004732 and EVM0005880 are related to the biosynthesis of melanin (Fig 4). This is the first time that melanin has been predicted in this pathogen. Whether melanin in E. arachidis plays a role in pathogenicity as it does in M. oryzae by aiding to penetrate the host plant remains to be verified.

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Fig 4. Phylogenetic analyses of E. arachidis and other fungal polyketide synthases (PKS).

Phylogenetic tree was constructed with PKS sequences from different organisms which classified with the types of reducing domains are divided into five clades.

https://doi.org/10.1371/journal.pone.0261487.g004

Expression of ESCB1 and analysis of flanking genes in E. arachidis.

Noteworthily, we previously determined that the content of ESC in E. arachidis was obviously decreased under dark conditions [12]. We compared the toxin content and ESCB1 expression under light and dark conditions, as expected, the change tendency was similarity (Fig 5). 13 putative Open Reading Frames were identified in the flanking of ESCB1 (Fig 6), including EVM0001135 and EVM0007299 which encode O-methyltransferase, EVM0006582 and EVM0006794 similarity to MFS transporter, EVM0002495 Cytochrome P450, and EVM0002638 zinc finger transcription factor.

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Fig 5. ESC and expression levels analysis of ESCB1.

ESC and expression levels of ESCB1 was investigated in light and dark condition, respectively.

https://doi.org/10.1371/journal.pone.0261487.g005

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Fig 6. Distribution of the ESCB1 gene cluster.

BLASTX was used to search the NCBI database to predict the function of related genes.

https://doi.org/10.1371/journal.pone.0261487.g006

Discussion

Elsinoë species cause scab and spot anthracnose on various crops including peanut, cassava, citrus, mango, and grape. In this paper, the first whole genome sequence of E. arachidis were reported and revealed the complex gene structures that may be involved in its pathogenic mechanism. Additionally, we predicted the ESC toxin biosynthesis gene cluster. The genome size of E. arachidis is 33.18Mb, which was comparable in size to the Ascomycota genome size, however, compared with E. australis (23.34 Mb), E. arachidis has a larger genome size. This may be due to the lower proportion of repeat sequences in the E. fawcettii genome [56]. The GC content was 48.24% and CDSs percentage of the genome was 43.94%.

Mycotoxins play an important part in the pathogenic mechanisms of pathogens. Mycotoxin ESCs, perylenequinones photosensitive toxins, can produce reactive oxygen species (ROS) and act on the cell membrane to destroy the cell structure. E. arachidis can maintain growth and development even in the presence of high toxin levels, which indicates an efficient self-detoxification mechanism. We identified ABC transporters and MFS transporters in E. arachidis indicating the complex transportation of substances in E. arachidis and that some of them may have an effect on the secretion of ESCs. Cytochrome P450 enzyme system, a multifunctional oxidoreductase, may involve in the self-detoxification of E. arachidis by providing redox conditions to maintain its own steady state for various physiological and biochemical reactions.

ESC is a crucial virulent factor in the pathogenic process of E. arachidis. However, compared with mycotoxins such as aflatoxins, fumonisin, and trichothecenes, and host-selective toxins such as T-toxin, still little is known about the biosynthetic pathways of perylenequinone mycotoxins. Cercosporin, the same group of perylenequinone toxins with ESC, has been proved that CTB1 (cercosporin synthase gene 1) which encoding polyketide synthase is the core gene of cercosporin biosynthesis pathway [10]. Efpks1 has been shown to function the in ESC biosynthesis in E. fawcettii, but the specific biosynthesis pathway still needs to be further clarified [8, 9]. With the prediction of the secondary metabolism gene cluster of E. arachidis, 6 gene clusters related to polyketide synthase were obtained. The core genes were EVM0002563, EVM0003759, EVM0004732, EVM0005880, EVM0005988, and EVM0006869. Phylogenetic tree constructions showed that EVM0003759 is involved in ESCs synthesis, while EVM0004732 and EVM0005880 play a role in melanin synthesis. To our knowledge, this is the first time that melanin has been identified in E. arachidis. Interestingly, analysis of the position between the core genes of ESCs and melanin gene clusters, we found that the three genes are all located in Contig00003. This result also cast some doubt on whether PKS synthesis pathways from ESC and melanin are interrelated or competing.

Pathogens employ complex mechanisms to break through the defenses of plants, including toxins, enzymes, and other pathogenic factors to help invasion and colonization. Analysis of the CAZy and PHI databases revealed that, in addition to ESCs, enzymes, effectors, and certain transcription factors may be involved in the pathogenic process. Increased virulence factors (3%) that cause increased pathogenicity include O-methylsterigmatocystin oxidoreductase, AK-toxin biosynthetic gene 7 (AKT7) and bZIP transcription factor MeaB. EVM0005728, EVM0001699 and EVM0004784 are related to AKT7, which encodes a cytochrome P450 monooxygenase in Alternaria alternata and can limit the host-selective toxin AK-toxin production [57]. EVM0002472 is endowed with a basic leucine zipper (bZIP) domain similar to the MeaB transcription factor in Fusarium oxysporum [58], which activates a conserved nitrogen responsive pathway to control the virulence of plant pathogenic fungi (S5 Table).

In conclusion, we reported the whole-genome sequence of E. arachidis. Analysis of its assembly and annotation allowed the identification of the presumptive PKS gene clusters. Based on our results, we hypothesize that ESCB1 maybe the core gene of the biosynthesis of ESC. Additionally, pathogenic factors including CAZymes and effectors may help E. arachidis to circumvent the defense mechanisms of peanuts. Our work lays the foundation of future research aimed at elucidating the detailed pathogenic mechanisms of E. arachidis.

Conclusions

In conclusion, this is the first report of the high-quality genome of E. arachidis by PacBio RS II. The basic information of the sequence, gene family and metabolic gene cluster of E. arachidis were clarified. Through further analysis of the key genes in different PKS gene clusters, the expression of ESCB1 (EVM0003759) under light and dark condition was initially determined to participate in the ESC biosynthetic pathway, and the flanking sequences of this gene cluster were annotation, including major facilitator superfamily transporter, cytochrome P450, monooxygenase and O-methyltransferase. In addition to ESC toxins, genes related to mycotoxin biosynthesis such as melanin are also noted. This information provides new ideas for further exploration of the pathogenic mechanism of E. arachidis.

Supporting information

S1 Fig. GO, KOG and KEGG annotation of E. arachidis.

https://doi.org/10.1371/journal.pone.0261487.s001

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S2 Fig. Collinear analysis and evolutionary analysis of E. arachidis.

(A) A phylogenetic tree constructed the evolutionary relationships of E. arachidis and other fungi. (B) Collinear analysis.

https://doi.org/10.1371/journal.pone.0261487.s002

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S3 Fig. Gene clusters in E. arachidis.

https://doi.org/10.1371/journal.pone.0261487.s003

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S4 Fig. PKS, NRPS and NRPS-PKS hybrid in different genome.

https://doi.org/10.1371/journal.pone.0261487.s004

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S1 Table. Repetitive sequence in E. arachidis.

https://doi.org/10.1371/journal.pone.0261487.s005

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S2 Table. ABC transporter and major facilitator superfamily in E. arachidis.

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S3 Table. Cytochrome P450 in E. arachidis.

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S4 Table. The loss of pathogenicity and reduced virulence genes in E. arachidis.

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S5 Table. Increased virulence genes in E. arachidis.

https://doi.org/10.1371/journal.pone.0261487.s009

(DOCX)

S6 Table. CAZyme_family in E. arachidis.

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S7 Table. CAZymes in E. arachidis and compared genome.

https://doi.org/10.1371/journal.pone.0261487.s011

(DOCX)

S8 Table. The information of the different PKSs.

https://doi.org/10.1371/journal.pone.0261487.s012

(DOC)

Acknowledgments

We would like to thank BioMarker for the much-valued help.

References

  1. 1. Zhou R J, Xu Z, Fu J F, Cui J C, He J J, Xue C Y. Resistance evaluation of peanut varieties to peanut scab and the epidemic dynamics in Liaoning Province. Acta Phytophylacica Sinica. 2014;41(5):597–601.
  2. 2. Fang S M, Wang Z R, Ke Y Q, Chen Y S, Huang C M, Yu J X. The Evaluation of Resistance and Resistant Mechanisms of Peanut Varieties to Scab Disease. Scientia Agricultura Sinica. 2007; 40(2):291–297.
  3. 3. Fan X L, Barreto R W, Groenewald J Z, Bezerra J D P, Pereira O L, Cheewangkoon R, et al. Phylogeny and taxonomy of the scab and spot anthracnose fungus Elsinoë (Myriangiales, Dothideomycetes). Studies in Mycology. 2017; 87(C):1–41. pmid:28373739
  4. 4. Zhao J F, Zhou R J, Li Y J, Lu L, Fu J F, Xue C Y. Infectious condition of Sphaceloma arachidis and physiological responses to pathogen infection in peanut. Chinese Journal of Oil Crop Sciences. 2017; (1)
  5. 5. Lu Liu, Wenli Jiao, Rujun Zhou, Yuanjie Li, Mengxue Xu, Junfan Fu. Extraction Technology and Activity Analysis of Elsinoë arachidis Toxin. Journal of Shenyang Agricultural University. 2018; 49(3): 272–278.
  6. 6. Fang SM, Wang ZR, Guo JM. Fungicides selection for peanut scab disease, Chinese Journal of Oil Crop Sciences. 2006; 28, 220–223.
  7. 7. Weiss U, Flon H, Burger WC. The photodynamic pigment of some species of Elsinoë and Sphaceloma. Arch Biochem Biophys. 1957;69:311–319. pmid:13445204
  8. 8. Liao HL, Chung KR. Cellular toxicity of elsinochrome phytotoxins produced by the pathogenic fungus, Elsinoë fawcettii causing citrus scab. New Phytol. 2008;177(1):239–250. pmid:17953652
  9. 9. Daub ME, Herrero S, Chung KR. Photoactivated perylenequinone toxins in fungal pathogenesis of plants. FEMS Microbiol Lett. 2005;252(2):197–206. pmid:16165316
  10. 10. Choquer M, Dekkers KL, Chen HQ, et al. The CTB1 gene encoding a fungal polyketide synthase is required for cercosporin biosynthesis and fungal virulence of Cercospora nicotianae. Mol Plant Microbe Interact. 2005;18(5):468–476. pmid:15915645
  11. 11. Daub ME. Cercosporin, a photosensitizing toxin from Cercospora species. Phytopathology. 1982; 72, 370–374.
  12. 12. Jiao W, Liu L, Zhou R, Xu M, Xiao D, Xue C. Elsinochrome phytotoxin production and pathogenicity of Elsinoë arachidis isolates in China. PLoS One. 2019;14(6):e0218391. pmid:31194853
  13. 13. Dong Y, Li Y, Zhao M, et al. Global genome and transcriptome analyses of Magnaporthe oryzae epidemic isolate 98–06 uncover novel effectors and pathogenicity-related genes, revealing gene gain and lose dynamics in genome evolution. PLoS Pathog. 2015;11(4):e1004801. pmid:25837042
  14. 14. Walkowiak S, Rowland O, Rodrigue N, Subramaniam R. Whole genome sequencing and comparative genomics of closely related Fusarium Head Blight fungi: Fusarium graminearum, F. meridionale and F. asiaticum. BMC Genomics. 2016;17(1):1014. pmid:27938326
  15. 15. Amselem J, Cuomo C A, van Kan JA, et al., Genomic Analysis of the Necrotrophic Fungal Pathogens Sclerotinia sclerotiorum and Botrytis cinerea. PLoS Genetics. 2011, 7(8):e1002230. pmid:21876677
  16. 16. Chin CS, Alexander DH, Marks P, et al. Nonhybrid, finished microbial genome assemblies from long-read SMRT sequencing data. Nat Methods. 2013;10(6):563–569. pmid:23644548
  17. 17. Berlin K, Koren S, Chin C S, Drake J P, Landolin J M, and Phillippy A M. Assembling large genomes with single-molecule sequencing and locality-sensitive hashing. Nature biotechnology. 2015; 33, 623–630 pmid:26006009
  18. 18. Koren S, Walenz BP, Berlin K, Miller JR, Bergman NH, Phillippy AM. Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation. Genome Res. 2017;27(5):722–736. pmid:28298431
  19. 19. Lefort V, Longueville JE, Gascuel O. SMS: Smart Model Selection in PhyML. Mol Biol Evol. 2017;34(9):2422–2424. pmid:28472384
  20. 20. Li L, Stoeckert CJ Jr, Roos DS. OrthoMCL: identification of ortholog groups for eukaryotic genomes. Genome Res. 2003;13(9):2178–2189. pmid:12952885
  21. 21. Wang Y, Tang H, Debarry JD, et al. MCScanX: a toolkit for detection and evolutionary analysis of gene synteny and collinearity. Nucleic Acids Res. 2012;40(7):e49. pmid:22217600
  22. 22. Xu Z, Wang H. LTR_FINDER: an efficient tool for the prediction of full-length LTR retrotransposons. Nucleic Acids Res. 2007;35(Web Server issue):W265–W268. pmid:17485477
  23. 23. Han Y, Wessler SR. MITE-Hunter: a program for discovering miniature inverted-repeat transposable elements from genomic sequences. Nucleic Acids Res. 2010;38(22):e199. pmid:20880995
  24. 24. Price AL, Jones NC, Pevzner PA. De novo identification of repeat families in large genomes. Bioinformatics. 2005; 21, 351–358. pmid:15961478
  25. 25. Edgar RC, Myers EW. PILER: identification and classification of genomic repeats. Bioinformatics. 2005;21 Suppl 1:i152–i158 pmid:15961452
  26. 26. Wicker T, Sabot F, Hua-Van A, et al. A unified classification system for eukaryotic transposable elements. Nat Rev Genet. 2007;8(12):973–982. pmid:17984973
  27. 27. Jurka J, Kapitonov VV, Pavlicek A, Klonowski P, Kohany O, Walichiewicz J. Repbase Update, a database of eukaryotic repetitive elements. Cytogenet Genome Res. 2005;110(1–4):462–467. pmid:16093699
  28. 28. Tarailo-Graovac M, Chen N. Using RepeatMasker to identify repetitive elements in genomic sequences. Curr Protoc Bioinformatics. 2009;Chapter 4. pmid:19274634
  29. 29. Stanke M, Waack S. Gene prediction with a hidden Markov model and a new intron submodel. Bioinformatics. 2003; 19, 215–225. pmid:14534192
  30. 30. Blanco E, Parra G, Guigó R. Using geneid to identify genes. Curr Protoc Bioinformatics. 2007;Chapter 4. pmid:18428791
  31. 31. Majoros WH, Pertea M, Salzberg SL. TigrScan and GlimmerHMM: two open source ab initio eukaryotic gene-finders. Bioinformatics. 2004;20(16):2878–2879. pmid:15145805
  32. 32. Korf I. Gene finding in novel genomes. BMC Bioinformatics. 2004;5:59. pmid:15144565
  33. 33. Keilwagen J, Hartung F, Grau J. GeMoMa: Homology-Based Gene Prediction Utilizing Intron Position Conservation and RNA-seq Data. Methods Mol Biol. 2019;1962:161–177 pmid:31020559
  34. 34. Haas BJ, Salzberg SL, Zhu W, et al. Automated eukaryotic gene structure annotation using EVidenceModeler and the Program to Assemble Spliced Alignments. Genome Biol. 2008;9(1):R7. pmid:18190707
  35. 35. Griffiths-Jones S, Moxon S, Marshall M, Khanna A, Eddy SR, Bateman A. Rfam: annotating non-coding RNAs in complete genomes. Nucleic Acids Res. 2005;33(Database issue):D121–D124. pmid:15608160
  36. 36. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ: Basic local alignment search tool. Journal of molecular biology. 1990, 215:403–410. pmid:2231712
  37. 37. Lowe TM, Eddy SR. tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res. 1997;25(5):955–964. pmid:9023104
  38. 38. Kent WJ. BLAT—the BLAST-like alignment tool. Genome research 2002, 12:656–664. pmid:11932250
  39. 39. Birney E, Clamp M, Durbin R. GeneWise and genomewise. Genome research. 2004; 14:988–995. pmid:15123596
  40. 40. Finn RD, Bateman A, Clements J, et al. Pfam: the protein families database. Nucleic Acids Res. 2014;42(Database issue):D222–D230. pmid:24288371
  41. 41. Tatusov RL, Galperin MY, Natale DA, Koonin EV. The COG database: a tool for genome-scale analysis of protein functions and evolution. Nucleic Acids Res. 2000;28(1):33–36. pmid:10592175
  42. 42. Kanehisa M, Goto S, Kawashima S, Okuno Y, Hattori M. The KEGG resource for deciphering the genome. Nucleic Acids Res. 2004;32(Database issue):D277–D280. pmid:14681412
  43. 43. Ashburner M, Ball C A, Blake J A. Gene Ontology: tool for the unification of biology. Nature genetics. 2000; 25, 25–29. pmid:10802651
  44. 44. Lombard V, Golaconda Ramulu H, Drula E, Coutinho PM, Henrissat B. The carbohydrate-active enzymes database (CAZy) in 2013. Nucleic Acids Res. 2014;42(Database issue):D490–D495. pmid:24270786
  45. 45. Saier MH Jr, Tran CV, Barabote RD. TCDB: The Transporter Classification Database for membrane transport protein analyses and information. Nucleic Acids Res. 2006;34(Database issue):D181–D186. pmid:16381841
  46. 46. Winnenburg R, Baldwin TK, Urban M, Rawlings C, Köhler J, Hammond-Kosack KE. PHI-base: a new database for pathogen host interactions. Nucleic Acids Res. 2006;34(Database issue):D459–D464. pmid:16381911
  47. 47. Mohanta TK, Bae H. The diversity of fungal genome. Biol Proced Online. 2015;17:8. pmid:25866485
  48. 48. Perlin MH, Andrews J, Toh SS. Essential letters in the fungal alphabet: ABC and MFS transporters and their roles in survival and pathogenicity. Adv Genet. 2014;85:201–253. pmid:24880736
  49. 49. Choquer M, Lee MH, Bau HJ, Chung KR. Deletion of a MFS transporter-like gene in Cercospora nicotianae reduces cercosporin toxin accumulation and fungal virulence. FEBS Lett. 2007;581(3):489–494. pmid:17250832
  50. 50. Guengerich FP. Cytochrome P450 research and The Journal of Biological Chemistry. J Biol Chem. 2019;294(5):1671–1680. pmid:29871932
  51. 51. Yan X, Ma WB, Li Y, et al. A sterol 14α-demethylase is required for conidiation, virulence and for mediating sensitivity to sterol demethylation inhibitors by the rice blast fungus Magnaporthe oryzae. Fungal Genet Biol. 2011;48(2):144–153. pmid:20887796
  52. 52. Pedrini N, Ortiz-Urquiza A, Huarte-Bonnet C, Zhang S, Keyhani NO. Targeting of insect epicuticular lipids by the entomopathogenic fungus Beauveria bassiana: hydrocarbon oxidation within the context of a host-pathogen interaction. Front Microbiol. 2013;4:24. pmid:23422735
  53. 53. Qiu D, Mao J, Yang X, Zeng H. Expression of an elicitor-encoding gene from Magnaporthe grisea enhances resistance against blast disease in transgenic rice. Plant Cell Rep. 2009;28(6):925–933. pmid:19337737
  54. 54. Rose JK, Ham KS, Darvill AG, Albersheim P. Molecular cloning and characterization of glucanase inhibitor proteins: coevolution of a counterdefense mechanism by plant pathogens. Plant Cell. 2002;14(6):1329–1345. pmid:12084830
  55. 55. van den Brink J, de Vries RP. Fungal enzyme sets for plant polysaccharide degradation. Appl Microbiol Biotechnol. 2011;91(6):1477–1492. pmid:21785931
  56. 56. Jeffress S, Arun-Chinnappa K, Stodart B, Vaghefi N, Tan YP, Ash G. Genome mining of the citrus pathogen Elsinoë fawcettii; prediction and prioritisation of candidate effectors, cell wall degrading enzymes and secondary metabolite gene clusters. PLoS One. 2020;15(5):e0227396. pmid:32469865
  57. 57. Takaoka S, Kurata M, Harimoto Y, et al. Complex regulation of secondary metabolism controlling pathogenicity in the phytopathogenic fungus Alternaria alternata. New Phytol. 2014;202(4):1297–1309. pmid:24611558
  58. 58. López-Berges MS, Rispail N, Prados-Rosales RC, Di Pietro A. A nitrogen response pathway regulates virulence functions in Fusarium oxysporum via the protein kinase TOR and the bZIP protein MeaB. Plant Cell. 2010, 22(7):2459–75. pmid:20639450