EffectorP: predicting fungal effector proteins from secretomes using machine learning

Effector Identification in Plant Pathogens

Effectors play a central role in determining the outcome of plant-pathogen interactions. As key virulence proteins, effectors are collectively indispensable for disease development. By understanding the virulence mechanisms of effectors, fundamental knowledge of microbial pathogenesis and disease resistance have been revealed. Effectors are also considered double-edged swords because some of them activate immunity in disease resistant plants after being recognized by specific immune receptors, which evolved to monitor pathogen presence or activity. Characterization of effector recognition by their cognate immune receptors and the downstream immune signaling pathways is instrumental in implementing resistance. Over the past decades, substantial research effort has focused on effector biology, especially concerning their interactions with virulence targets or immune receptors in plant cells. A foundation of this research is robust identification of the effector repertoire from a given pathogen, which depends heavily on bioinformatic prediction. In this review, we summarize methodologies that have been used for effector mining in various microbial pathogens which use different effector delivery mechanisms. We also discuss current limitations and provide perspectives on how recently developed analytic tools and technologies may facilitate effector identification and hence generation of a more complete vision of host-pathogen interactions. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Fungal biotechnology: From yesterday to tomorrow

Fungi have been used to better the lives of everyday people and unravel the mysteries of higher eukaryotic organisms for decades. However, comparing progress and development stemming from fungal research to that of human, plant, and bacterial research, fungi remain largely understudied and underutilized. Recent commercial ventures have begun to gain popularity in society, providing a new surge of interest in fungi, mycelia, and potential new applications of these organisms to various aspects of research. Biotechnological advancements in fungal research cannot occur without intensive amounts of time, investments, and research tool development. In this review, we highlight past breakthroughs in fungal biotechnology, discuss requirements to advance fungal biotechnology even further, and touch on the horizon of new breakthroughs with the highest potential to positively impact both research and society.

Characterization and Genome Analysis of Cladobotryum mycophilum, the Causal Agent of Cobweb Disease of Morchella sextelata in China

Cobweb disease is a fungal disease that can cause serious damage to edible mushrooms worldwide. To investigate cobweb disease in Morchella sextelata in Guizhou Province, China, we isolated and purified the pathogen responsible for the disease. Through morphological and molecular identification and pathogenicity testing on infected M. sextelata, we identified Cladobotryum mycophilum as the cause of cobweb disease in this region. This is the first known occurrence of this pathogen causing cobweb disease in M. sextelata anywhere in the world. We then obtained the genome of C. mycophilum BJWN07 using the HiFi sequencing platform, resulting in a high-quality genome assembly with a size of 38.56 Mb, 10 contigs, and a GC content of 47.84%. We annotated 8428 protein-coding genes in the genome, including many secreted proteins, host interaction-related genes, and carbohydrate-active enzymes (CAZymes) related to the pathogenesis of the disease. Our findings shed new light on the pathogenesis of C. mycophilum and provide a theoretical basis for developing potential prevention and control strategies for cobweb disease.

Ab Initio Modelling of the Structure of ToxA-like and MAX Fungal Effector Proteins

Pathogenic fungal diseases in crops are mediated by the release of effector proteins that facilitate infection. Characterising the structure of these fungal effectors is vital to understanding their virulence mechanisms and interactions with their hosts, which is crucial in the breeding of plant cultivars for disease resistance. Several effectors have been identified and validated experimentally; however, their lack of sequence conservation often impedes the identification and prediction of their structure using sequence similarity approaches. Structural similarity has, nonetheless, been observed within fungal effector protein families, creating interest in validating the use of computational methods to predict their tertiary structure from their sequence. We used Rosetta ab initio modelling to predict the structures of members of the ToxA-like and MAX effector families for which experimental structures are known to validate this method. An optimised approach was then used to predict the structures of phenotypically validated effectors lacking known structures. Rosetta was found to successfully predict the structure of fungal effectors in the ToxA-like and MAX families, as well as phenotypically validated but structurally unconfirmed effector sequences. Interestingly, potential new effector structural families were identified on the basis of comparisons with structural homologues and the identification of associated protein domains.

Intraspecific Comparative Analysis Reveals Genomic Variation of Didymella arachidicola and Pathogenicity Factors Potentially Related to Lesion Phenotype

Didymella arachidicola is one of the most important fungal pathogens, causing foliar disease and leading to severe yield losses of peanuts (Arachis hypogaea L.) in China. Two main lesion phenotypes of peanut web blotch have been identified as reticulation type (R type) and blotch type (B type). As no satisfactory reference genome is available, the genomic variations and pathogenicity factors of D. arachidicola remain to be revealed. In the present study, we collected 41 D. arachidicola isolates from 26 geographic locations across China (33 for R type and 8 for B type). The chromosome-scale genome of the most virulent isolate (YY187) was assembled as a reference using PacBio and Hi-C technologies. In addition, we re-sequenced 40 isolates from different sampling sites. Genome-wide alignments showed high similarity among the genomic sequences from the 40 isolates, with an average mapping rate of 97.38%. An average of 3242 SNPs and 315 InDels were identified in the genomic variation analysis, which revealed an intraspecific polymorphism in D. arachidicola. The comparative analysis of the most and least virulent isolates generated an integrated gene set containing 512 differential genes. Moreover, 225 genes individually or simultaneously harbored hits in CAZy-base, PHI-base, DFVF, etc. Compared with the R type reference, the differential gene sets from all B type isolates identified 13 shared genes potentially related to lesion phenotype. Our results reveal the intraspecific genomic variation of D. arachidicola isolates and pathogenicity factors potentially related to different lesion phenotypes. This work sets a genomic foundation for understanding the mechanisms behind genomic diversity driving different pathogenic phenotypes of D. arachidicola.

Genome sequencing and annotation of Cercospora sesami, a fungal pathogen causing leaf spot to Sesamum indicum

Cercospora sesami is a plant pathogen that causes leaf spot disease in sesame plants worldwide. In this study, genome sequence assembly of C. sesami isolate Cers 52-10 (MCC 9069) was generated using native paired-end and mate-pair DNA sequencing based on the Illumina HiSeq 2500 platform. The genome assembly of C. sesami is 34.3 Mb in size with an N50 of 26,222 bp and an average GC content of 53.02%. A total number of 10,872 genes were predicted in this study, out of which 9,712 genes were functionally annotated. Genes assigned to carbohydrate-active enzyme classes were also identified during the study. A total of 80 putative effector candidates were predicted and functionally annotated. The C. sesami genome sequence is available at DDBJ/ENA/GenBank, and other associated information is submitted to Mendeley's data.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03468-4.

A Bioinformatic Guide to Identify Protein Effectors from Phytopathogens

Phytopathogenic fungi are a diverse and widespread group that has a significant detrimental impact on crops with an estimated annual average loss of 15% worldwide. Understanding the interaction between host plants and pathogenic fungi is critical to delineate underlying mechanisms of plant defense to mitigate agricultural losses. Fungal pathogens utilize suites of secreted molecules, called effectors, to modulate plant metabolism and immune response to overcome host defenses and promote colonization. Effectors come in many flavors including proteinaceous products, small RNAs, and metabolites such as mycotoxins. This review will focus on methods for identifying protein effectors from fungi. Excellent reviews have been published to identify secondary metabolites and small RNAs from fungi and therefore will not be part of this review.

Pathogenicity Variation in Two Genomes of Cercospora Species Causing Gray Leaf Spot in Maize

The gray leaf spots caused by Cercospora spp. severely affect the yield and quality of maize. However, the evolutionary relation and pathogenicity variation between species of the Cercospora genus is largely unknown. In this study, we constructed high-quality reference genomes by nanopore sequencing two Cercospora species, namely, C. zeae-maydis and C. zeina, with differing pathogenicity, collected from northeast (Liaoning [LN]) and southeast (Yunnan [YN]) China, respectively. The genome size of C. zeae-maydis-LN is 45.08 Mb, containing 10,839 annotated genes, whereas that of Cercospora zeina-YN is 42.18 Mb, containing 10,867 annotated genes, of which approximately 86.58% are common in the two species. The difference in their genome size is largely attributed to increased long terminal repeat retrotransposons of 3.8 Mb in total length in C. zeae-maydis-LN. There are 41 and 30 carbohydrate-binding gene subfamilies identified in C. zeae-maydis-LN and C. zeina-YN, respectively. A higher number of carbohydrate-binding families found in C. zeae-maydis-LN, and its unique CBM4, CBM37, and CBM66, in particular, may contribute to variation in pathogenicity between the two species, as the carbohydrate-binding genes are known to encode cell wall-degrading enzymes. Moreover, there are 114 and 107 effectors predicted, with 47 and 46 having unique potential pathogenicity in C. zeae-maydis-LN and C. zeina-YN, respectively. Of eight effectors randomly selected for pathogenic testing, five were found to inhibit cell apoptosis induced by Bcl-2-associated X. Taken together, our results provide genomic insights into variation in pathogenicity between C. zeae-maydis and C. zeina. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Identification and analysis of the secretome of plant pathogenic fungi reveals lifestyle adaptation

The secretory proteome plays an important role in the pathogenesis of phytopathogenic fungi. However, the relationship between the large-scale secretome of phytopathogenic fungi and their lifestyle is not fully understood. In the present study, the secretomes of 150 plant pathogenic fungi were predicted and the characteristics associated with different lifestyles were investigated. In total, 94,974 secreted proteins (SPs) were predicted from these fungi. The number of the SPs ranged from 64 to 1,662. Among these fungi, hemibiotrophic fungi had the highest number (average of 970) and proportion (7.1%) of SPs. Functional annotation showed that hemibiotrophic and necrotroph fungi, differ from biotrophic and symbiotic fungi, contained much more carbohydrate enzymes, especially polysaccharide lyases and carbohydrate esterases. Furthermore, the core and lifestyle-specific SPs orthogroups were identified. Twenty-seven core orthogroups contained 16% of the total SPs and their motif function annotation was represented by serine carboxypeptidase, carboxylesterase and asparaginase. In contrast, 97 lifestyle-specific orthogroups contained only 1% of the total SPs, with diverse functions such as PAN_AP in hemibiotroph-specific and flavin monooxygenases in necrotroph-specific. Moreover, obligate biotrophic fungi had the largest number of effectors (average of 150), followed by hemibiotrophic fungi (average of 120). Among these effectors, 4,155 had known functional annotation and pectin lyase had the highest proportion in the functionally annotated effectors. In addition, 32 sets of RNA-Seq data on pathogen-host interactions were collected and the expression levels of SPs were higher than that of non-SPs, and the expression level of effector genes was higher in biotrophic and hemibiotrophic fungi than in necrotrophic fungi, while secretase genes were highly expressed in necrotrophic fungi. Finally, the secretory activity of five predicted SPs from Setosphearia turcica was experimentally verified. In conclusion, our results provide a foundation for the study of pathogen-host interaction and help us to understand the fungal lifestyle adaptation.

Complete Genome Sequences of Septoria linicola: A Resource for Studying a Damaging Flax Pathogen

Fungal genus Septoria causes diseases in a wide range of plants. Here, we report the first genome sequences of two strains of Septoria linicola, the causal agent of the pasmo disease of flax (Linum usitatissimum). The genome of the first strain, SE15195, was fully assembled in 16 chromosomes, while 35 unitigs were obtained for a second strain, SE14017. Structural annotations predicted 13,096 and 13,085 protein-encoding genes and transposable elements content of 19.0 and 18.1% of the genome for SE15195 and SE14017, respectively. The four smaller chromosomes 13 to 16 show genomics features of potential accessory chromosomes. The assembly of these two genomes is a new resource for studying S. linicola and improving management of pasmo. [Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Transcriptome analysis of Lr19-virulent mutants provides clues for the AvrLr19 of Puccinia triticina

Introduction

Wheat leaf rust caused by Puccinia triticina (Pt) remains one of the most destructive diseases of common wheat worldwide. Understanding the pathogenicity mechanisms of Pt is important to control wheat leaf rust.

Methods

The urediniospores of Pt race PHNT (wheat leaf rust resistance gene Lr19-avirulent isolate) were mutagenized with ethyl methanesulfonate (EMS), and two Lr19-virulent mutants named M1 and M2 were isolated. RNA sequencing was performed on samples collected from wheat cultivars Chinese Spring and TcLr19 infected with wild-type (WT) PHNT, M1, and M2 isolates at 14 days post-inoculation (dpi), respectively. Screening AvrLr19 candidates by quantitative reverse transcription PCR (qPCR) and Agrobacterium-mediated transient assays in Nicotiana benthamiana.

Results

560 genes with single nucleotide polymorphisms (SNPs) and insertions or deletions (Indels) from non-differentially expressed genes were identified. Among them, 10 secreted proteins were screened based on their fragments per kilobase of exon model per million mapped reads (FPKM) values in the database. qPCR results showed that the expression profiles of 7 secreted proteins including PTTG_27471, PTTG_12441, PTTG_28324, PTTG_26499, PTTG_06910, PTTG_26516, and PTTG_03570 among 10 secreted proteins in mutants were significantly different with that in wild-type isolate after infection wheat TcLr19 and might be related to the recognition between Lr19 and AvrLr19. In addition, a total of 216 differentially expressed genes (DEGs) were obtained from three different sample comparisons including M1-vs-WT, M2-vs-WT, and M1-vs-M2. Among 216 DEGs, 15 were predicted to be secreted proteins. One secreted protein named PTTG_04779 could inhibit programmed progress of cell death (PCD) induced by apoptosis-controlling genes B-cell lymphoma-2 associated X protein (BAX) on Nicotiana benthamiana, indicating that it might play a virulence function in plant. Taken together, total 8 secreted proteins, PTTG_04779, PTTG_27471, PTTG_12441, PTTG_28324, PTTG_26499, PTTG_06910, PTTG_26516, PTTG_03570 are identified as AvrLr19 candidates.

Discussion

Our results showed that a large number of genes participate in the interaction between Pt and TcLr19, which will provide valuable resources for the identification of AvrLr19 candidates and pathogenesis-related genes.

Draft genome sequencing and secretome profiling of Sclerotinia sclerotiorum revealed effector repertoire diversity and allied broad-host range necrotrophy

White mold commonly known as Sclerotinia sclerotiorum causes stem rot disease and has emerged as one of the major fungal pathogens of oilseed Brassica across the world. In the present study, consistently virulent S. sclerotiorum isolate "ESR-01" was sequenced and an assembly size of ~ 41 Mb with 328 scaffolds having N50 of 447,128 was obtained. Additionally, 27,450 single nucleotide polymorphisms (SNPs) were identified from 155 scaffolds against S. sclerotiorum 1980 isolate, with an average SNP density of ~ 1.5 per kb genome. 667 repetitive elements were identified and approximately comprised 7% of the total annotated genes. The DDE_1 with 454 in numbers was found to be the most abundant and accounts for 68% of the total predicted repetitive elements. In total, 3844 simple sequence repeats are identified in the 328 scaffolds. A total of 9469 protein-coding genes were predicted from the whole genome assembly with an average gene length of 1587 bp and their distribution as 230.95 genes per Mb in the genome. Out of 9469 predicted protein-coding genes, 529 genes were observed encoding the CAZymes (Carbohydrate-Active enzymes) capable of degradation of the complex polysaccharides. Glycosyltransferase (GT) families were most abundant (49.71%) among the predicted CAZymes and GT2 (23%), GT4 (20%), and glycoside hydrolase (GH) 23% with GH18 (11%) were the prominent cell wall degrading enzyme families in the ESR-01 secretome. Besides this, 156 genes essential for the pathogen-host interactions were also identified. The effector analysis in the whole genome proteomics dataset revealed a total of 57 effector candidates (ECs) and 27 of them were having their analogs whereas the remaining 30 were novel ones. Eleven selected ECs were validated experimentally by analyzing the expression profile of the ESR-01 isolate of S. sclerotiorum. Together, the present investigation offers a better understanding of the S. sclerotiorum genome, secretome, and its effector repertoire which will help in refining the present knowledge on S. sclerotiorum-Brassica interactions and necrotrophic lifestyle of the phytopathogen in general.

The N-terminus of a Fusarium graminearum-secreted protein enhances broad-spectrum disease resistance in plants

Fusarium head blight is a destructive disease caused by Fusarium species. Little is known about the pathogenic molecular weapons of Fusarium graminearum. The gene encoding a small secreted protein, Fg02685, in F. graminearum was found to be upregulated during wheat head infection. Knockout mutation of Fg02685 reduced the growth and development of Fusarium in wheat spikes. Transient expression of Fg02685 or recombinant protein led to plant cell death in a BAK1- and SOBIR1-independent system. Fg02685 was found to trigger plant basal immunity by increasing the deposition of callose, the accumulation of reactive oxygen species (ROS), and the expression of defence-related genes. The Fg02685 signal peptide was required for the plant's apoplast accumulation and induces cell death, indicating Fg02685 is a novel conserved pathogen-associated molecular pattern. Moreover, its homologues are widely distributed in oomycetes and fungal pathogens and induced cell death in tobacco. The conserved α-helical motif at the N-terminus was necessary for the induction of cell death. Moreover, a 32-amino-acid peptide, Fg02685 N-terminus peptide 32 (FgNP32), was essential for the induction of oxidative burst, callose deposition, and mitogen-activated protein kinase signal activation in plants. Prolonged exposure to FgNP32 enhanced the plant's resistance to Fusarium and Phytophthora. This study provides new approaches for an environment-friendly control strategy for crop diseases by applying plant immune inducers to strengthen broad-spectrum disease resistance in crops.

Puccinia striiformis f. sp. tritici effectors in wheat immune responses

The obligate biotrophic fungus Puccinia striiformis f. sp. tritici, which causes yellow (stripe) rust disease, is among the leading biological agents resulting in tremendous yield losses on global wheat productions per annum. The combatting strategies include, but are not limited to, fungicide applications and the development of resistant cultivars. However, evolutionary pressure drives rapid changes, especially in its "effectorome" repertoire, thus allowing pathogens to evade and breach resistance. The extracellular and intracellular effectors, predominantly secreted proteins, are tactical arsenals aiming for many defense processes of plants. Hence, the identity of the effectors and the molecular mechanisms of the interactions between the effectors and the plant immune system have long been targeted in research. The obligate biotrophic nature of P. striiformis f. sp. tritici and the challenging nature of its host, the wheat, impede research on this topic. Next-generation sequencing and novel prediction algorithms in bioinformatics, which are accompanied by in vitro and in vivo validation approaches, offer a speedy pace for the discovery of new effectors and investigations of their biological functions. Here, we briefly review recent findings exploring the roles of P. striiformis f. sp. tritici effectors together with their cellular/subcellular localizations, host responses, and interactors. The current status and the challenges will be discussed. We hope that the overall work will provide a broader view of where we stand and a reference point to compare and evaluate new findings.

WideEffHunter: An Algorithm to Predict Canonical and Non-Canonical Effectors in Fungi and Oomycetes

Newer effectorome prediction algorithms are considering effectors that may not comply with the canonical characteristics of small, secreted, cysteine-rich proteins. The use of effector-related motifs and domains is an emerging strategy for effector identification, but its use has been limited to individual species, whether oomycete or fungal, and certain domains and motifs have only been associated with one or the other. The use of these strategies is important for the identification of novel, non-canonical effectors (NCEs) which we have found to constitute approximately 90% of the effectoromes. We produced an algorithm in Bash called WideEffHunter that is founded on integrating three key characteristics: the presence of effector motifs, effector domains and homology to validated existing effectors. Interestingly, we found similar numbers of effectors with motifs and domains within two different taxonomic kingdoms: fungi and oomycetes, indicating that with respect to their effector content, the two organisms may be more similar than previously believed. WideEffHunter can identify the entire effectorome (non-canonical and canonical effectors) of oomycetes and fungi whether pathogenic or non-pathogenic, unifying effector prediction in these two kingdoms as well as the two different lifestyles. The elucidation of complete effectoromes is a crucial step towards advancing effectoromics and disease management in agriculture.

Fungal Effectoromics: A World in Constant Evolution

Effectors are small, secreted molecules that mediate the establishment of interactions in nature. While some concepts of effector biology have stood the test of time, this area of study is ever-evolving as new effectors and associated characteristics are being revealed. In the present review, the different characteristics that underly effector classifications are discussed, contrasting past and present knowledge regarding these molecules to foster a more comprehensive understanding of effectors for the reader. Research gaps in effector identification and perspectives for effector application in plant disease management are also presented, with a focus on fungal effectors in the plant-microbe interaction and interactions beyond the plant host. In summary, the review provides an amenable yet thorough introduction to fungal effector biology, presenting noteworthy examples of effectors and effector studies that have shaped our present understanding of the field.

Fusarium oxysporum effector clustering version 2: An updated pipeline to infer host range

The fungus Fusarium oxysporum is infamous for its devastating effects on economically important crops worldwide. F. oxysporum isolates are grouped into formae speciales based on their ability to cause disease on different hosts. Assigning F. oxysporum strains to formae speciales using non-experimental procedures has proven to be challenging due to their genetic heterogeneity and polyphyletic nature. However, genetically diverse isolates of the same forma specialis encode similar repertoires of effectors, proteins that are secreted by the fungus and contribute to the establishment of compatibility with the host. Based on this observation, we previously designed the F. oxysporum Effector Clustering (FoEC) pipeline which is able to classify F. oxysporum strains by forma specialis based on hierarchical clustering of the presence of predicted putative effector sequences, solely using genome assemblies as input. Here we present the updated FoEC2 pipeline which is more user friendly, customizable and, due to multithreading, has improved scalability. It is designed as a Snakemake pipeline and incorporates a new interactive visualization app. We showcase FoEC2 by clustering 537 publicly available F. oxysporum genomes and further analysis of putative effector families as multiple sequence alignments. We confirm classification of isolates into formae speciales and are able to further identify their subtypes. The pipeline is available on github: https://github.com/pvdam3/FoEC2.

Microbial Effectors: Key Determinants in Plant Health and Disease

Effectors are small, secreted molecules that alter host cell structure and function, thereby facilitating infection or triggering a defense response. Effectoromics studies have focused on effectors in plant-pathogen interactions, where their contributions to virulence are determined in the plant host, i.e., whether the effector induces resistance or susceptibility to plant disease. Effector molecules from plant pathogenic microorganisms such as fungi, oomycetes and bacteria are major disease determinants. Interestingly, the effectors of non-pathogenic plant organisms such as endophytes display similar functions but have different outcomes for plant health. Endophyte effectors commonly aid in the establishment of mutualistic interactions with the plant and contribute to plant health through the induction of systemic resistance against pathogens, while pathogenic effectors mainly debilitate the plant's immune response, resulting in the establishment of disease. Effectors of plant pathogens as well as plant endophytes are tools to be considered in effectoromics for the development of novel strategies for disease management. This review aims to present effectors in their roles as promotors of health or disease for the plant host.

Pathotypes of Fusarium oxysporum f. sp. fragariae express discrete repertoires of accessory genes and induce distinct host transcriptional responses during root infection

Convergent evolution of phytopathogenicity is poorly described, especially among multiple strains of a single microbial species. We investigated this phenomenon with genetically diverse isolates of Fusarium oxysporum f. sp. fragariae (Fof) that cause one of two syndromes: chlorosis and wilting (the 'yellows-fragariae' pathotype), or only wilting (the 'wilt-fragariae' pathotype). We challenged strawberry (Fragaria × ananassa) plants to root infection by five fungal isolates: three yellows-fragariae, one wilt-fragariae and one that is not pathogenic to strawberry. All Fof isolates had chromosome-level assemblies; three were newly generated. The two pathotypes triggered distinct host responses, especially among phytohormone-associated genes; yellows-fragariae isolates strongly induced jasmonic acid-associated genes, whereas the wilt-fragariae isolate primarily induced ethylene biosynthesis and signalling. The differentially expressed genes on fungal accessory chromosomes were almost entirely distinct between pathotypes. We identified an ~150 kbp 'pathogenicity island' that was horizontally transferred between wilt-fragariae strains. This predicted pathogenicity island was enriched with differentially expressed genes whose predicted functions were related to plant infection, and only one of these genes was also upregulated in planta by yellows-fragariae isolates. These results support the conclusion that wilt- and yellows-fragariae cause physiologically distinct syndromes by the expression of discrete repertoires of genes on accessory chromosomes.

Proximity-dependent biotinylation identifies a suite of candidate effector proteins from Fusarium graminearum

Fusarium graminearum is a fungal pathogen that causes Fusarium head blight in cereal crops. The identification of proteins secreted from pathogens to overcome plant defenses and cause disease, collectively known as effectors, can reveal the etiology of a disease process. Proximity-dependent biotin identification (BioID) was used to identify potential effector proteins secreted in planta by F. graminearum during the infection of Arabidopsis. Mass spectrometry analysis of streptavidin affinity-purified proteins revealed over 300 proteins from F. graminearum, of which 62 were candidate effector proteins (CEPs). An independent analysis of secreted proteins from axenic cultures of F. graminearum showed a 42% overlap with CEPs, thereby assuring confidence in the BioID methodology. The analysis also revealed that 19 out of 62 CEPs (approx. 30%) had been previously characterized with virulence function in fungi. The functional characterization of additional CEPs was undertaken through deletion analysis by the CRISPR/Cas9 method, and by overexpression into Triticum aestivum (wheat) leaves by the Ustilago hordei delivery system. Deletion studies of 12 CEPs confirmed the effector function of three previously characterized CEPs and validated the function of another four CEPs on wheat inflorescence or vegetative tissues. Lastly, overexpression in wheat showed that all seven CEPs enhanced resistance against the bacterial pathogen Pseudomonas syringae DC3000.

Inactivation of a candidate effector gene of Zymoseptoria tritici affects its sporulation

BACKGROUND

Wheat is one of the most important staple crops produced worldwide. Its susceptibility to plant diseases reduces its production significantly. One of the most important diseases of wheat is septoria tritici blotch, a devastating disease observed in fields with wet and temperate conditions. Z. tritici secretes effector proteins to influence the host's defense mechanisms, as is typical of plant pathogens. In this investigation, we evaluated the pathogenicity of some Zymoseptoria tritici effector candidate genes having a signal peptide for secretion with no known function.

METHODS AND RESULTS

Three genes named Mycgr3G104383, Mycgr3G104444 and Mycgr3G105826 were knocked out separately through homologous recombination, generating Z. tritici IPO323 mutants lacking the functional copy of the corresponding genes. While KO1 and KO3 mutants did not show any significant differences during phenotypic and virulence investigations, the KO2 mutant generated exclusively macropycnidiospores in artificial media, different from wild-type IPO323 which produce only micropycidiospores. The mycelial growth capability of KO2 was also severely attenuated in all of the investigated growth conditions. These changes were observed independent of growth media and growth temperatures, implying that changes were genetic and inherited through generations. Virulence of knockout mutants in wheat leaves was observed to be similar to the wild-type IPO323.

CONCLUSION

Understanding the biology of Z. tritici and its interactions with wheat will reveal new strategies to fight septoria tritici blotch, enabling breeding wheat cultivars resistant to a broader spectrum of Z. tritici strains. Furthermore, gene knockout via homologous recombination proved to be a powerful tool for discovering novel gene functions.

Genome and Transcriptome Sequencing Analysis of Fusarium commune Provides Insights into the Pathogenic Mechanisms of the Lotus Rhizome Rot

Fusarium wilt, a vascular wilt caused by F. commune, has been a serious problem for the lotus. Although some F. commune isolate genomes have been sequenced, little is known about the genomic information of the strain that causes Fusarium wilt of aquatic plants. In this study, the genome of F. commune FCN23 isolated from lotuses in China was sequenced using Illumina and PacBio sequencing platforms. The FCN23 genome consisted of 53 scaffolds with a combined size of 46,211,149 bp. According to the reference genome, F. oxysporum f. sp. lycopersici 4287 isolated from tomato, it was finally assembled into 14 putative chromosomes, including 10 core and 4 lineage-specific chromosomes. The genome contains about 3.45% repeats and encodes 14,698 putative protein-coding genes. Among these, 1,038 and 296 proteins were potentially secreted proteins and candidate effector proteins, respectively. Comparative genomic analysis showed that the CAZyme-coding genes and secondary metabolite biosynthesis genes of FCN23 were similar to those of other Ascomycetes. Additionally, the transcriptome of FCN23 during infection of lotus was analyzed and 7,013 differentially expressed genes were identified. Eight putative effectors that were upregulated in the infection stage were cloned. Among them, F23a002499 exhibited strong hypersensitive response after transiently expressed in Nicotiana benthamiana leaves. Our results provide a valuable genetic basis for understanding the molecular mechanism of the interaction between F. commune and aquatic plants. IMPORTANCE Fusarium commune is an important soilborne pathogen with a wide range of hosts and can cause Fusarium wilt of land plants. However, there are few studies on Fusarium wilt of aquatic plants. Lotus rhizome rot mainly caused by F. commune is a devastating disease that causes extensive yield and quality losses in China. Here, we obtained high-quality genomic information of the FCN23 using Illumina NovaSeq and the third-generation sequencing technology PacBio Sequel II. Compared to the reference genome F. oxysporum f. sp. lycopersici strain 4287, it contains 11 core and 3 lineage-specific chromosomes. Many differentially expressed genes associated with pathogenicity were identified by RNA sequencing. The genome and transcriptome sequences of FCN23 will provide important genomic information and insights into the infection mechanisms of F. commune on aquatic plants.

Unveiling the Core Effector Proteins of Oil Palm Pathogen Ganoderma boninense via Pan-Secretome Analysis

Ganoderma boninense is the major causal agent of basal stem rot (BSR) disease in oil palm, causing the progressive rot of the basal part of the stem. Despite its prominence, the key pathogenicity determinants for the aggressive nature of hemibiotrophic infection remain unknown. In this study, genome sequencing and the annotation of G. boninense T10 were carried out using the Illumina sequencing platform, and comparative genome analysis was performed with previously reported G. boninense strains (NJ3 and G3). The pan-secretome of G. boninense was constructed and comprised 937 core orthogroups, 243 accessory orthogroups, and 84 strain-specific orthogroups. In total, 320 core orthogroups were enriched with candidate effector proteins (CEPs) that could be classified as carbohydrate-active enzymes, hydrolases, and non-catalytic proteins. Differential expression analysis revealed an upregulation of five CEP genes that was linked to the suppression of PTI signaling cascade, while the downregulation of four CEP genes was linked to the inhibition of PTI by preventing host defense elicitation. Genome architecture analysis revealed the one-speed architecture of the G. boninense genome and the lack of preferential association of CEP genes to transposable elements. The findings obtained from this study aid in the characterization of pathogenicity determinants and molecular biomarkers of BSR disease.

Comparative Genome Analyses of Plant Rust Pathogen Genomes Reveal a Confluence of Pathogenicity Factors to Quell Host Plant Defense Responses

Switchgrass rust caused by Puccinia novopanici (P. novopanici) has the ability to significantly affect the biomass yield of switchgrass, an important biofuel crop in the United States. A comparative genome analysis of P. novopanici with rust pathogen genomes infecting monocot cereal crops wheat, barley, oats, maize and sorghum revealed the presence of larger structural variations contributing to their genome sizes. A comparative alignment of the rust pathogen genomes resulted in the identification of collinear and syntenic relationships between P. novopanici and P. sorghi; P. graminis tritici 21–0 (Pgt 21) and P. graminis tritici Ug99 (Pgt Ug99) and between Pgt 21 and P. triticina (Pt). Repeat element analysis indicated a strong presence of retro elements among different Puccinia genomes, contributing to the genome size variation between ~1 and 3%. A comparative look at the enriched protein families of Puccinia spp. revealed a predominant role of restriction of telomere capping proteins (RTC), disulfide isomerases, polysaccharide deacetylases, glycoside hydrolases, superoxide dismutases and multi-copper oxidases (MCOs). All the proteomes of Puccinia spp. share in common a repertoire of 75 secretory and 24 effector proteins, including glycoside hydrolases cellobiohydrolases, peptidyl-propyl isomerases, polysaccharide deacetylases and protein disulfide-isomerases, that remain central to their pathogenicity. Comparison of the predicted effector proteins from Puccinia spp. genomes to the validated proteins from the Pathogen–Host Interactions database (PHI-base) resulted in the identification of validated effector proteins PgtSR1 (PGTG_09586) from P. graminis and Mlp124478 from Melampsora laricis across all the rust pathogen genomes.

Comparative genomic analysis reveals cellulase plays an important role in the pathogenicity of Setosphaeria turcica f. sp. zeae

Setosphaeria turcica f. sp. zeae and S. turcica f. sp. sorghi, the two formae speciales of S. turcica, cause northern leaf blight disease of corn and sorghum, respectively, and often cause serious economic losses. They have obvious physiological differentiation and show complete host specificity. Host specificity is often closely related to pathogen virulence factors, including secreted protein effectors and secondary metabolites. Genomic sequencing can provide more information for understanding the virulence mechanisms of pathogens. However, the complete genomic sequence of S. turcica f. sp. sorghi has not yet been reported, and no comparative genomic information is available for the two formae speciales. In this study, S. turcica f. sp. zeae was predicted to have fewer secreted proteins, pathogen-host interaction (PHI) genes and carbohydrate-active enzymes (CAZys) than S. turcica f. sp. sorghi. Fifteen and 20 polyketide synthase (PKS) genes were identified in S. turcica f. sp. zeae and S. turcica f. sp. sorghi, respectively, which maintained high homology. There were eight functionally annotated effector protein-encoding genes specifically in S. turcica f. sp. zeae, among which the encoding gene StCEL2 of endo-1, 4-β-D-glucanase, an important component of cellulase, was significantly up-regulated during the interaction process. Finally, gluconolactone inhibited cellulase activity and decreased infection rate and pathogenicity, which indicates that cellulase is essential for maintaining virulence. These findings demonstrate that cellulase plays an important role in the pathogenicity of S. turcica f. sp. zeae. Our results also provide a theoretical basis for future research on the molecular mechanisms underlying the pathogenicity of the two formae speciales and for identifying any associated genes.

Whole-body transcriptome mining for candidate effectors from Diuraphis noxia

Background

Proteins within aphid saliva play a crucial role as the molecular interface between aphids and their host plants. These salivary effectors modulate plant responses to favour aphid feeding and facilitate infestation. The identification of effectors from economically important pest species is central in understanding the molecular events during the aphid-plant interaction. The Russian wheat aphid (Diuraphis noxia, Kurdjumov) is one such pest that causes devastating losses to wheat and barley yields worldwide. Despite the severe threat to food security posed by D. noxia, the non-model nature of this pest and its host has hindered progress towards understanding this interaction. In this study, in the absence of a salivary gland transcriptome, whole-body transcriptomics data was mined to generate a candidate effector catalogue for D. noxia.

Results

Mining the transcriptome identified 725 transcripts encoding putatively secreted proteins amongst which were transcripts specific to D. noxia. Six of the seven examined D. noxia putative effectors, termed DnE’s (Diuraphis noxia effectors) exhibited salivary gland-specific expression. A comparative analysis between whole-body D. noxia transcriptome data versus the head and body transcriptomes from three other aphid species allowed us to define a catalogue of transcripts putatively upregulated in D. noxia head tissue. Five of these were selected for RT-qPCR confirmation, and were found to corroborate the differential expression predictions, with a further three confirmed to be highly expressed in D. noxia salivary gland tissue.

Conclusions

Determining a putative effector catalogue for D. noxia from whole-transcriptome data, particularly the identification of salivary-specific sequences potentially unique to D. noxia, provide the basis for future functional characterisation studies to gain further insight into this aphid-plant interaction. Furthermore, due to a lack of publicly available aphid salivary gland transcriptome data, the capacity to use comparative transcriptomics to compile a list of putative effector candidates from whole-body transcriptomics data will further the study of effectors in various aphid species.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08712-4.

Using a Hybrid Mapping Population to Identify Genomic Regions of Pyrenophora teres Associated With Virulence

Net blotches caused by Pyrenophora teres are important foliar fungal diseases of barley and result in significant yield losses of up to 40%. The two types of net blotch, net-form net blotch and spot-form net blotch, are caused by P. teres f. teres (Ptt) and P. teres f. maculata (Ptm), respectively. This study is the first to use a cross between Ptt and Ptm to identify quantitative trait loci (QTL) associated with virulence and leaf symptoms. A genetic map consisting of 1,965 Diversity Arrays Technology (DArT) markers was constructed using 351 progenies of the Ptt/Ptm cross. Eight barley cultivars showing differential reactions to the parental isolates were used to phenotype the hybrid progeny isolates. Five QTL associated with virulence and four QTL associated with leaf symptoms were identified across five linkage groups. Phenotypic variation explained by these QTL ranged from 6 to 16%. Further phenotyping of selected progeny isolates on 12 more barley cultivars revealed that three progeny isolates are moderately to highly virulent across these cultivars. The results of this study suggest that accumulation of QTL in hybrid isolates can result in enhanced virulence.

Identification of Pathogenicity-Related Effector Proteins and the Role of Piwsc1 in the Virulence of Penicillium italicum on Citrus Fruits

Blue mold caused by Penicillium italicum is one of the two major postharvest diseases of citrus fruits. The interactions of pathogens with their hosts are complicated, and virulence factors that mediate pathogenicity have not yet been identified. In present study, a prediction pipeline approach based on bioinformatics and transcriptomic data is designed to determine the effector proteins of P. italicum. Three hundred and seventy-five secreted proteins of P. italicum were identified, many of which (29.07%) were enzymes for carbohydrate utilization. Twenty-nine candidates were further analyzed and the expression patterns of 12 randomly selected candidate effector genes were monitored during the early stages of growth on PDA and infection of Navel oranges for validation. Functional analysis of a cell wall integrity-related gene Piwsc1, a core candidate, was performed by gene knockout. The deletion of Piwsc1 resulted in reduced virulence on citrus fruits, as presented by an approximate 57% reduction in the diameter of lesions. In addition, the mycelial growth rate, spore germination rate, and sporulation of ΔPiwsc1 decreased. The findings provide us with new insights to understand the pathogenesis of P. italicum and develop an effective and sustainable control method for blue mold.

Comparative Genomic Analyses Provide Insight Into the Pathogenicity of Metschnikowia bicuspidata LNES0119

Metschnikowia bicuspidata is a globally distributed pathogenic yeast with a wide range of aquatic hosts. A new strain, M. bicuspidata LNES0119, isolated from the Chinese mitten crab Eriocheir sinensis, has caused a serious reduction in production and marked economic loss for the aquaculture industry in China. Therefore, the whole-genome sequence of M. bicuspidata LNES0119 was sequenced using Illumina and Oxford Nanopore technology; whole-genome annotation and comparative genomic analyses of this pathogen were performed as well. A high-quality genome of M. bicuspidata LNES0119 was 16.13 Mb in size, with six scaffolds and six contigs, and encoded 5,567 putative predicted genes. Of these, 1,467 genes shared substantial homology with genes in the pathogen–host interactions database. Comparative genomic analyses of three M. bicuspidata strains and one non-pathogenic yeast, M. aff. pulcherrima, showed 331 unique genes in M. bicuspidata LNES0119, 30 of which were putatively related to pathogenicity. Overall, we identified several meaningful characteristics related to pathogenicity and virulence that may play essential roles in the infection and pathogenicity of M. bicuspidata LNES0119. Our study will aid in identifying potential targets for further exploration of the molecular basis of the pathogenicity of M. bicuspidata as well as the therapeutic intervention of M. bicuspidata infection.

Infection Strategies and Pathogenicity of Biotrophic Plant Fungal Pathogens

Biotrophic plant pathogenic fungi are widely distributed and are among the most damaging pathogenic organisms of agriculturally important crops responsible for significant losses in quality and yield. However, the pathogenesis of obligate parasitic pathogenic microorganisms is still under investigation because they cannot reproduce and complete their life cycle on an artificial medium. The successful lifestyle of biotrophic fungal pathogens depends on their ability to secrete effector proteins to manipulate or evade plant defense response. By integrating genomics, transcriptomics, and effectoromics, insights into how the adaptation of biotrophic plant fungal pathogens adapt to their host populations can be gained. Efficient tools to decipher the precise molecular mechanisms of rust–plant interactions, and standardized routines in genomics and functional pipelines have been established and will pave the way for comparative studies. Deciphering fungal pathogenesis not only allows us to better understand how fungal pathogens infect host plants but also provides valuable information for plant diseases control, including new strategies to prevent, delay, or inhibit fungal development. Our review provides a comprehensive overview of the efforts that have been made to decipher the effector proteins of biotrophic fungal pathogens and demonstrates how rapidly research in the field of obligate biotrophy has progressed.

Comparative Genomics of Fusarium circinatum Isolates Used to Screen Southern Pines for Pitch Canker Resistance

Pitch canker, caused by the fungal pathogen Fusarium circinatum, is a global disease affecting many Pinus spp. Often fatal, this disease causes significant mortality in both commercially grown and natural pine forests and is an issue of current and growing concern. F. circinatum isolates collected from three locations in the U.S. state of Florida were shown to be virulent on both slash and loblolly pine, with two of the isolates causing equivalent and significantly larger lesions than those caused by the third isolate during pathogenicity trials. In addition, significant genetic variation in lesion length in the pedigreed slash pine population was evident and rankings of parents for lesion length were similar across isolates. Experimental data demonstrate that both host and pathogen genetics contribute to disease severity. High-quality genomic assemblies of all three isolates were created and compared for structural differences and gene content. No major structural differences were observed among the isolates; however, missing or altered genes do contribute to genomic variation in the pathogen population. This work evaluates in planta virulence among three isolates of F. circinatum, provides genomic resources to facilitate study of this organism, and details comparative genomic methods that may be used to explore the pathogen's contribution to disease development.[Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Effector-GAN: prediction of fungal effector proteins based on pretrained deep representation learning methods and generative adversarial networks

MOTIVATION

Phytopathogenic fungi secrete effector proteins to subvert host defenses and facilitate infection. Systematic analysis and prediction of candidate fungal effector proteins is crucial for experimental validation and biological control of plant disease. However, two problems are still considered intractable to be solved in fungal effector prediction: one is the high-level diversity in effector sequences that increases the difficulty of protein feature learning, and the other is the class imbalance between effector and non-effector samples in the training dataset.

RESULTS

In our study, pretrained deep representation learning methods are presented to represent multiple characteristics of sequences for predicting fungal effectors and generative adversarial networks are adapted to create synthetic feature samples to address the data imbalance problem. Compared with the state-of-the-art fungal effector prediction methods, Effector-GAN shows an overall improvement in accuracy in the independent test set.

AVAILABILITY AND IMPLEMENTATION

Effector-GAN offers a user-friendly interface to inspect potential fungal effector proteins (http://lab.malab.cn/~wys/webserver/Effector-GAN). The Python script can be downloaded from http://lab.malab.cn/~wys/gitlab/effector-gan.

RFPDR: a random forest approach for plant disease resistance protein prediction

Background

Plant innate immunity relies on a broad repertoire of receptor proteins that can detect pathogens and trigger an effective defense response. Bioinformatic tools based on conserved domain and sequence similarity are within the most popular strategies for protein identification and characterization. However, the multi-domain nature, high sequence diversity and complex evolutionary history of disease resistance (DR) proteins make their prediction a real challenge. Here we present RFPDR, which pioneers the application of Random Forest (RF) for Plant DR protein prediction.

Methods

A recently published collection of experimentally validated DR proteins was used as a positive dataset, while 10x10 nested datasets, ranging from 400-4,000 non-DR proteins, were used as negative datasets. A total of 9,631 features were extracted from each protein sequence, and included in a full dimension (FD) RFPDR model. Sequence selection was performed, to generate a reduced-dimension (RD) RFPDR model. Model performances were evaluated using an 80/20 (training/testing) partition, with 10-cross fold validation, and compared to baseline, sequence-based and state-of-the-art strategies. To gain some insights into the underlying biology, the most discriminatory sequence-based features in the RF classifier were identified.

Results and Discussion

RD-RFPDR showed to be sensitive (86.4 ± 4.0%) and specific (96.9 ± 1.5%) for identifying DR proteins, while robust to data imbalance. Its high performance and robustness, added to the fact that RD-RFPDR provides valuable information related to DR proteins underlying properties, make RD-RFPDR an interesting approach for DR protein prediction, complementing the state-of-the-art strategies.

Pangenome Analysis of the Soilborne Fungal Phytopathogen Rhizoctonia solani and Development of a Comprehensive Web Resource: RsolaniDB

Rhizoctonia solani is a collective group of genetically and pathologically diverse basidiomycetous fungi that damage economically important crops. Its isolates are classified into 13 Anastomosis Groups (AGs) and subgroups having distinctive morphology and host ranges. The genetic factors driving the unique features of R. solani pathology are not well characterized due to the limited availability of its annotated genomes. Therefore, we performed genome sequencing, assembly, annotation and functional analysis of 12 R. solani isolates covering 7 AGs and select subgroups (AG1-IA; AG1-IB; AG1-IC; AG2-2IIIB; AG3-PT, isolates Rhs 1AP and the hypovirulent Rhs1A1; AG3-TB; AG4-HG-I, isolates Rs23 and R118-11; AG5; AG6; and AG8), in which six genomes are reported for the first time. Using a pangenome comparative analysis of 12 R. solani isolates and 15 other Basidiomycetes, we defined the unique and shared secretomes, CAZymes, and effectors across the AGs. We have also elucidated the R. solani-derived factors potentially involved in determining AG-specific host preference, and the attributes distinguishing them from other Basidiomycetes. Finally, we present the largest repertoire of R. solani genomes and their annotated components as a comprehensive database, viz. RsolaniDB, with tools for large-scale data mining, functional enrichment and sequence analysis not available with other state-of-the-art platforms.

Root-associated microbiota drive phytoremediation strategies to lead of Sonchus Asper (L.) Hill as revealed by intercropping-induced modifications of the rhizosphere microbiome

Intercropping or assistant endophytes promote phytoremediation capacities of hyperaccumulators and enhance their tolerance to heavy metal (HM) stress. Findings from a previous study showed that intercropping the hyperaccumulator Sonchus asper (L.) Hill grown in HM-contaminated soils with maize improved the remediating properties and indicated an excluder-to-hyperaccumulator switched mode of action towards lead. In the current study, RNA-Seq analysis was conducted on Sonchus roots grown under intercropping or monoculture systems to explore the molecular events underlying this shift in lead sequestering strategy. The findings showed that intercropping only slightly affects S. asper transcriptome but significantly affects expression of root-associated microbial genomes. Further, intercropping triggers significant reshaping of endophytic communities associated with a 'root-to-shoot' transition of lead sequestration and improved phytoremediation capacities of S. asper. These findings indicate that accumulator activities of a weed are partially attributed to the root-associated microbiota, and a complex network of plant-microbe-plant interactions shapes the phytoremediation potential of S. asper. Analysis showed that intercropping may significantly change the structure of root-associated communities resulting in novel remediation properties, thus providing a basis for improving phytoremediation practices to restore contaminated soils.

A chromosome-scale genome assembly of the tomato pathogen Cladosporium fulvum reveals a compartmentalized genome architecture and the presence of a dispensable chromosome

Cladosporium fulvum is a fungal pathogen that causes leaf mould of tomato. The reference genome of this pathogen was released in 2012 but its high repetitive DNA content prevented a contiguous assembly and further prohibited the analysis of its genome architecture. In this study, we combined third generation sequencing technology with the Hi-C chromatin conformation capture technique, to produce a high-quality and near complete genome assembly and gene annotation of a Race 5 isolate of C. fulvum. The resulting genome assembly contained 67.17 Mb organized into 14 chromosomes (Chr1-to-Chr14), all of which were assembled telomere-to-telomere. The smallest of the chromosomes, Chr14, is only 460 kb in size and contains 25 genes that all encode hypothetical proteins. Notably, PCR assays revealed that Chr14 was absent in 19 out of 24 isolates of a world-wide collection of C. fulvum, indicating that Chr14 is dispensable. Thus, C. fulvum is currently the second species of Capnodiales shown to harbour dispensable chromosomes. The genome of C. fulvum Race 5 is 49.7 % repetitive and contains 14 690 predicted genes with an estimated completeness of 98.9%, currently one of the highest among the Capnodiales. Genome structure analysis revealed a compartmentalized architecture composed of gene-dense and repeat-poor regions interspersed with gene-sparse and repeat-rich regions. Nearly 39.2 % of the C. fulvum Race 5 genome is affected by Repeat-Induced Point (RIP) mutations and evidence of RIP leakage toward non-repetitive regions was observed in all chromosomes, indicating the RIP plays an important role in the evolution of this pathogen. Finally, 345 genes encoding candidate effectors were identified in C. fulvum Race 5, with a significant enrichment of their location in gene-sparse regions, in accordance with the 'two-speed genome' model of evolution. Overall, the new reference genome of C. fulvum presents several notable features and is a valuable resource for studies in plant pathogens.

Tracking of Diversity and Evolution in the Brown Rot Fungi Monilinia fructicola, Monilinia fructigena, and Monilinia laxa

Monilinia species are among the most devastating fungi worldwide as they cause brown rot and blossom blight on fruit trees. To understand the molecular bases of their pathogenic lifestyles, we compared the newly assembled genomes of single strains of Monilinia fructicola, M. fructigena and M. laxa, with those of Botrytis cinerea and Sclerotinia sclerotiorum, as the closest species within Sclerotiniaceae. Phylogenomic analysis of orthologous proteins and syntenic investigation suggest that M. laxa is closer to M. fructigena than M. fructicola, and is closest to the other investigated Sclerotiniaceae species. This indicates that M. laxa was the earliest result of the speciation process. Distinct evolutionary profiles were observed for transposable elements (TEs). M. fructicola and M. laxa showed older bursts of TE insertions, which were affected (mainly in M. fructicola) by repeat-induced point (RIP) mutation gene silencing mechanisms. These suggested frequent occurrence of the sexual process in M. fructicola. More recent TE expansion linked with low RIP action was observed in M. fructigena, with very little in S. sclerotiorum and B. cinerea. The detection of active non-syntenic TEs is indicative of horizontal gene transfer and has resulted in alterations in specific gene functions. Analysis of candidate effectors, biosynthetic gene clusters for secondary metabolites and carbohydrate-active enzymes, indicated that Monilinia genus has multiple virulence mechanisms to infect host plants, including toxins, cell-death elicitor, putative virulence factors and cell-wall-degrading enzymes. Some species-specific pathogenic factors might explain differences in terms of host plant and organ preferences between M. fructigena and the other two Monilinia species.

Application of machine learning in understanding plant virus pathogenesis: trends and perspectives on emergence, diagnosis, host-virus interplay and management

BACKGROUND

Inclusion of high throughput technologies in the field of biology has generated massive amounts of data in the recent years. Now, transforming these huge volumes of data into knowledge is the primary challenge in computational biology. The traditional methods of data analysis have failed to carry out the task. Hence, researchers are turning to machine learning based approaches for the analysis of high-dimensional big data. In machine learning, once a model is trained with a training dataset, it can be applied on a testing dataset which is independent. In current times, deep learning algorithms further promote the application of machine learning in several field of biology including plant virology.

MAIN BODY

Plant viruses have emerged as one of the principal global threats to food security due to their devastating impact on crops and vegetables. The emergence of new viral strains and species help viruses to evade the concurrent preventive methods. According to a survey conducted in 2014, plant viruses are anticipated to cause a global yield loss of more than thirty billion USD per year. In order to design effective, durable and broad-spectrum management protocols, it is very important to understand the mechanistic details of viral pathogenesis. The application of machine learning enables precise diagnosis of plant viral diseases at an early stage. Furthermore, the development of several machine learning-guided bioinformatics platforms has primed plant virologists to understand the host-virus interplay better. In addition, machine learning has tremendous potential in deciphering the pattern of plant virus evolution and emergence as well as in developing viable control options.

CONCLUSIONS

Considering a significant progress in the application of machine learning in understanding plant virology, this review highlights an introductory note on machine learning and comprehensively discusses the trends and prospects of machine learning in the diagnosis of viral diseases, understanding host-virus interplay and emergence of plant viruses.

Comparative genomics of plant pathogenic Diaporthe species and transcriptomics of Diaporthe caulivora during host infection reveal insights into pathogenic strategies of the genus

Background

Diaporthe caulivora is a fungal pathogen causing stem canker in soybean worldwide. The generation of genomic and transcriptomic information of this ascomycete, together with a comparative genomic approach with other pathogens of this genus, will contribute to get insights into the molecular basis of pathogenicity strategies used by D. caulivora and other Diaporthe species.

Results

In the present work, the nuclear genome of D. caulivora isolate (D57) was resolved, and a comprehensive annotation based on gene expression and genomic analysis is provided. Diaporthe caulivora D57 has an estimated size of 57,86 Mb and contains 18,385 predicted protein-coding genes, from which 1501 encode predicted secreted proteins. A large array of D. caulivora genes encoding secreted pathogenicity-related proteins was identified, including carbohydrate-active enzymes (CAZymes), necrosis-inducing proteins, oxidoreductases, proteases and effector candidates. Comparative genomics with other plant pathogenic Diaporthe species revealed a core secretome present in all Diaporthe species as well as Diaporthe-specific and D. caulivora-specific secreted proteins. Transcriptional profiling during early soybean infection stages showed differential expression of 2659 D. caulivora genes. Expression patterns of upregulated genes and gene ontology enrichment analysis revealed that host infection strategies depends on plant cell wall degradation and modification, detoxification of compounds, transporter activities and toxin production. Increased expression of effectors candidates suggests that D. caulivora pathogenicity also rely on plant defense evasion. A high proportion of the upregulated genes correspond to the core secretome and are represented in the pathogen-host interaction (PHI) database, which is consistent with their potential roles in pathogenic strategies of the genus Diaporthe.

Conclusions

Our findings give novel and relevant insights into the molecular traits involved in pathogenicity of D. caulivora towards soybean plants. Some of these traits are in common with other Diaporthe pathogens with different host specificity, while others are species-specific. Our analyses also highlight the importance to have a deeper understanding of pathogenicity functions among Diaporthe pathogens and their interference with plant defense activation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08413-y.

Genome Analysis of the Broad Host Range Necrotroph Nalanthamala psidii Highlights Genes Associated With Virulence

Guava wilt disease is caused by the fungus Nalanthamala psidii. The wilt disease results in large-scale destruction of orchards in South Africa, Taiwan, and several Southeast Asian countries. De novo assembly, annotation, and in-depth analysis of the N. psidii genome were carried out to facilitate the identification of characteristics associated with pathogenicity and pathogen evolution. The predicted secretome revealed a range of CAZymes, proteases, lipases and peroxidases associated with plant cell wall degradation, nutrient acquisition, and disease development. Further analysis of the N. psidii carbohydrate-active enzyme profile exposed the broad-spectrum necrotrophic lifestyle of the pathogen, which was corroborated by the identification of putative effectors and secondary metabolites with the potential to induce tissue necrosis and cell surface-dependent immune responses. Putative regulatory proteins including transcription factors and kinases were identified in addition to transporters potentially involved in the secretion of secondary metabolites. Transporters identified included important ABC and MFS transporters involved in the efflux of fungicides. Analysis of the repetitive landscape and the detection of mechanisms linked to reproduction such as het and mating genes rendered insights into the biological complexity and evolutionary potential of N. psidii as guava pathogen. Hence, the assembly and annotation of the N. psidii genome provided a valuable platform to explore the pathogenic potential and necrotrophic lifestyle of the guava wilt pathogen.

EffectorP 3.0: Prediction of Apoplastic and Cytoplasmic Effectors in Fungi and Oomycetes

Many fungi and oomycete species are devasting plant pathogens. These eukaryotic filamentous pathogens secrete effector proteins to facilitate plant infection. Fungi and oomycete pathogens have diverse infection strategies and their effectors generally do not share sequence homology. However, they occupy similar host environments, either the plant apoplast or plant cytoplasm, and, therefore, may share some unifying properties based on the requirements of these host compartments. Here, we exploit these biological signals and present the first classifier (EffectorP 3.0) that uses two machine-learning models: one trained on apoplastic effectors and one trained on cytoplasmic effectors. EffectorP 3.0 accurately predicts known apoplastic and cytoplasmic effectors in fungal and oomycete secretomes with low estimated false-positive rates of 3 and 8%, respectively. Cytoplasmic effectors have a higher proportion of positively charged amino acids, whereas apoplastic effectors are enriched for cysteine residues. The combination of fungal and oomycete effectors in training leads to a higher number of predicted cytoplasmic effectors in biotrophic fungi. EffectorP 3.0 expands predicted effector repertoires beyond small, cysteine-rich secreted proteins in fungi and RxLR-motif containing secreted proteins in oomycetes. We show that signal peptide prediction is essential for accurate effector prediction, because EffectorP 3.0 recognizes a cytoplasmic signal also in intracellular, nonsecreted proteins.[Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Host-Induced Gene Silencing Using BPMV on Soybean to Study Genes in the Soybean Rust Fungus Phakopsora pachyrhizi

To obtain direct evidence for the influence of an effector on the virulence or pathogenicity of a pathogen, it is necessary to knock out, knock down, or silence the respective gene. Since genetic transformation is not yet possible for rust fungi, silencing the gene is the only option. Posttranscriptional gene silencing uses RNAi. RNAi in plant pathogens can be accomplished by introducing dsRNA either by direct application of in vitro synthesized dsRNA or through positive-strand or double-strand RNA plant viruses. For studying effectors in Phakopsora pachyrhizi, we have implemented a host-induced silencing procedure based on virus-induced gene silencing using the bean pod mottle virus system. Here, procedures and interpretations of results are described and limitations of the system are discussed.

The Parastagonospora nodorum necrotrophic effector SnTox5 targets the wheat gene Snn5 and facilitates entry into the leaf mesophyll

Parastagonospora nodorum is an economically important necrotrophic fungal pathogen of wheat. Parastagonospora nodorum secretes necrotrophic effectors that target wheat susceptibility genes to induce programmed cell death (PCD). In this study, we cloned and functionally validated SnTox5 and characterized its role in pathogenesis. We used whole genome sequencing, genome-wide association study (GWAS) mapping, CRISPR-Cas9-based gene disruption, gain-of-function transformation, quantitative trait locus (QTL) analysis, haplotype and isoform analysis, protein modeling, quantitative PCR, and laser confocal microscopy to validate SnTox5 and functionally characterize SnTox5. SnTox5 is a mature 16.26 kDa protein with high structural similarity to SnTox3. Wild-type and mutant P. nodorum strains and wheat genotypes of SnTox5 and Snn5, respectively, were used to show that SnTox5 not only targets Snn5 to induce PCD but also facilitates the colonization of the mesophyll layer even in the absence of Snn5. Here we show that SnTox5 facilitates the efficient colonization of the mesophyll tissue and elicits PCD specific to host lines carrying Snn5. The homology to SnTox3 and the ability of SnTox5 to facilitate the colonizing of the mesophyll also suggest a role in the suppression of host defense before PCD induction.

A triple threat: the Parastagonospora nodorum SnTox267 effector exploits three distinct host genetic factors to cause disease in wheat

Parastagonospora nodorum is a fungal pathogen of wheat. As a necrotrophic specialist, it deploys effector proteins that target dominant host susceptibility genes to elicit programmed cell death (PCD). Here we identify and functionally validate the effector targeting the host susceptibility genes Snn2, Snn6 and Snn7. We utilized whole-genome sequencing, association mapping, gene-disrupted mutants, gain-of-function transformants, virulence assays, bioinformatics and quantitative PCR to characterize these interactions. A single proteinaceous effector, SnTox267, targeted Snn2, Snn6 and Snn7 to trigger PCD. Snn2 and Snn6 functioned cooperatively to trigger PCD in a light-dependent pathway, whereas Snn7-mediated PCD functioned in a light-independent pathway. Isolates harboring 20 SnTox267 protein isoforms quantitatively varied in virulence. The diversity and distribution of isoforms varied between populations, indicating adaptation to local selection pressures. SnTox267 deletion resulted in the upregulation of effector genes SnToxA, SnTox1 and SnTox3. We validated a novel effector operating in an inverse-gene-for-gene manner to target three genetically distinct host susceptibility genes and elicit PCD. The discovery of the complementary gene action of Snn2 and Snn6 indicates their potential function in a guard or decoy model. Additionally, differences in light dependency in the elicited pathways and upregulation of unlinked effectors sheds new light onto a complex fungal necrotroph-host interaction.

Functional Genomics and Comparative Lineage-Specific Region Analyses Reveal Novel Insights into Race Divergence in Verticillium dahliae

Verticillium dahliae is a widespread soilborne fungus that causes Verticillium wilt on numerous economically important plant species. In tomato, until now, three races have been characterized based on the response of differential cultivars to V. dahliae, but the genetic basis of race divergence in V. dahliae remains undetermined. To investigate the genetic basis of race divergence, we sequenced the genomes of two race 2 strains and four race 3 strains for comparative analyses with two known race 1 genomes. The genetic basis of race divergence was described by the pathogenicity-related genes among the three races, orthologue analyses, and genomic structural variations. Global comparative genomics showed that chromosomal rearrangements are not the only source of race divergence and that race 3 should be split into two genotypes based on orthologue clustering. Lineage-specific regions (LSRs), frequently observed between genomes of the three races, encode several predicted secreted proteins that potentially function as suppressors of immunity triggered by known effectors. These likely contribute to the virulence of the three races. Two genes in particular that can act as markers for race 2 and race 3 (VdR2e and VdR3e, respectively) contribute to virulence on tomato, and the latter acts as an avirulence factor of race 3. We elucidated the genetic basis of race divergence through global comparative genomics and identified secreted proteins in LSRs that could potentially play critical roles in the differential virulence among the races in V. dahliae.

IMPORTANCE Deciphering the gene-for-gene relationships during host-pathogen interactions is the basis of modern plant resistance breeding. In the Verticillium dahliae-tomato pathosystem, two races (races 1 and 2) and their corresponding avirulence (Avr) genes have been identified, but strains that lack these two Avr genes exist in nature. In this system, race 3 has been described, but the corresponding Avr gene has not been identified. We de novo-sequenced genomes of six strains and identified secreted proteins within the lineage-specific regions (LSRs) distributed among the genomes of the three races that could potentially function as manipulators of host immunity. One of the LSR genes, VdR3e, was confirmed as the Avr gene for race 3. The results indicate that differences in transcriptional regulation may contribute to race differentiation. This is the first study to describe these differences and elucidate roles of secreted proteins in LSRs that play roles in race differentiation.