Genome-wide annotation, comparison and functional genomics of carbohydrate-active enzymes in legumes infecting Fusarium oxysporum formae speciales

Pangenomics of flax fungal parasite Fusarium oxysporum f. sp. lini

To assess the genomic diversity of Fusarium oxysporum f. sp. lini strains and compile a comprehensive gene repertoire, we constructed a pangenome using 13 isolates from four different clonal lineages, each exhibiting distinct levels of virulence. Syntenic analyses of two selected genomes revealed significant chromosomal rearrangements unique to each genome. A comprehensive examination of both core and accessory pangenome content and diversity points at an open genome state. Additionally, Gene Ontology (GO) enrichment analysis indicated that non-core pangenome genes are associated with pathogen recognition and immune signaling. Furthermore, the Folini pansecterome, encompassing secreted proteins critical for fungal pathogenicity, primarily consists of three functional classes: effector proteins, CAZYmes, and proteases. These three classes account for approximately 3.5% of the pangenome. Each functional class within the pansecterome was meticulously annotated and characterized with respect to pangenome category distribution, PFAM domain frequency, and strain virulence assessment. This analysis revealed that highly virulent isolates have specific types of PFAM domains that are exclusive to them. Upon examining the repertoire of SIX genes known for virulence in other formae speciales, it was found that all isolates had a similar gene content except for two, which lacked SIX genes entirely.

Genome sequencing and comparative genomics reveal insights into pathogenicity and evolution of Fusarium zanthoxyli, the causal agent of stem canker in prickly ash

BACKGROUND

Fusarium zanthoxyli is a destructive pathogen causing stem canker in prickly ash, an ecologically and economically important forest tree. However, the genome lack of F. zanthoxyli has hindered research on its interaction with prickly ash and the development of precise control strategies for stem canker.

RESULTS

In this study, we sequenced and annotated a relatively high-quality genome of F. zanthoxyli with a size of 43.39 Mb, encoding 11,316 putative genes. Pathogenicity-related factors are predicted, comprising 495 CAZymes, 217 effectors, 156 CYP450s, and 202 enzymes associated with secondary metabolism. Besides, a comparative genomics analysis revealed Fusarium and Colletotrichum diverged from a shared ancestor approximately 141.1 ~ 88.4 million years ago (MYA). Additionally, a phylogenomic investigation of 12 different phytopathogens within Fusarium indicated that F. zanthoxyli originated approximately 34.6 ~ 26.9 MYA, and events of gene expansion and contraction within them were also unveiled. Finally, utilizing conserved domain prediction, the results revealed that among the 59 unique genes, the most enriched domains were PnbA and ULP1. Among the 783 expanded genes, the most enriched domains were PKc_like kinases and those belonging to the APH_ChoK_Like family.

CONCLUSION

This study sheds light on the genetic basis of F. zanthoxyli's pathogenicity and evolution which provides valuable information for future research on its molecular interactions with prickly ash and the development of effective strategies to combat stem canker.

Genome sequencing and comparative genome analysis of Rhizoctonia solani AG-3

Rhizoctonia solani AG-3 is a plant pathogenic fungus that belongs to the group of multinucleate Rhizoctonia. According to its internal transcribed spacer (ITS) cluster analysis and host range, it is divided into TB, PT, and TM subgroups. AG-3 TB mainly causes tobacco target spots, AG-3 PT mainly causes potato black scurf, and AG-3 TM mainly causes tomato leaf blight. In our previous study, we found that all 36 tobacco target spot strains isolated from Yunnan (Southwest China) were classified into AG-3 TB subgroup, while only two of the six tobacco target spot strains isolated from Liaoning (Northeast China) were classified into AG-3 TB subgroup, and the remaining four strains were classified into AG-3 TM subgroup, which had a unique taxonomic status, and there was no previous report on the whole genome information of AG-3 TM subgroup. In this study, the whole genomes of R. solani AG-3 strains 3T-1 (AG-3 TM isolated from Liaoning) and MJ-102 (AG-3 TB isolated from Yunnan) isolated from tobacco target spot in Liaoning and Yunnan were sequenced by IIumina and PacBio sequencing platforms. Comparative genomic analysis was performed with the previously reported AG-3 PT strain Rhs1AP, revealing their differences in genomes and virulence factors. The results indicated that the genome size of 3T-1 was 42,103,597 bp with 11,290 coding genes and 49.74% GC content, and the genome size of MJ-102 was 41,908,281 bp with 10,592 coding genes and 48.91% GC content. Through comparative genomic analysis with the previously reported strain Rhs1AP (AG-3 PT), it was found that the GC content between the genomes was similar, but the strains 3T-1 and MJ-102 contained more repetitive sequences. Similarly, there are similarities between their virulence factors, but there are also some differences. In addition, the results of collinearity analysis showed that 3T-1 and MJ-102 had lower similarity and longer evolutionary distance with Rhs1AP, but the genetic relationship between 3T-1 and MJ-102 was closer. This study can lay a foundation for studying the molecular pathogenesis and virulence factors of R. solani AG-3, and revealing its genomic composition will also help to develop more effective disease control strategies.

Large-scale genomic analyses with machine learning uncover predictive patterns associated with fungal phytopathogenic lifestyles and traits

Invasive plant pathogenic fungi have a global impact, with devastating economic and environmental effects on crops and forests. Biosurveillance, a critical component of threat mitigation, requires risk prediction based on fungal lifestyles and traits. Recent studies have revealed distinct genomic patterns associated with specific groups of plant pathogenic fungi. We sought to establish whether these phytopathogenic genomic patterns hold across diverse taxonomic and ecological groups from the Ascomycota and Basidiomycota, and furthermore, if those patterns can be used in a predictive capacity for biosurveillance. Using a supervised machine learning approach that integrates phylogenetic and genomic data, we analyzed 387 fungal genomes to test a proof-of-concept for the use of genomic signatures in predicting fungal phytopathogenic lifestyles and traits during biosurveillance activities. Our machine learning feature sets were derived from genome annotation data of carbohydrate-active enzymes (CAZymes), peptidases, secondary metabolite clusters (SMCs), transporters, and transcription factors. We found that machine learning could successfully predict fungal lifestyles and traits across taxonomic groups, with the best predictive performance coming from feature sets comprising CAZyme, peptidase, and SMC data. While phylogeny was an important component in most predictions, the inclusion of genomic data improved prediction performance for every lifestyle and trait tested. Plant pathogenicity was one of the best-predicted traits, showing the promise of predictive genomics for biosurveillance applications. Furthermore, our machine learning approach revealed expansions in the number of genes from specific CAZyme and peptidase families in the genomes of plant pathogens compared to non-phytopathogenic genomes (saprotrophs, endo- and ectomycorrhizal fungi). Such genomic feature profiles give insight into the evolution of fungal phytopathogenicity and could be useful to predict the risks of unknown fungi in future biosurveillance activities.

The Invasive Tradescantia zebrina Affects Litter Decomposition, but It Does Not Change the Lignocellulolytic Fungal Community in the Atlantic Forest, Brazil

Invasive plants affect ecosystems across various scales. In particular, they affect the quality and quantity of litter, which influences the composition of decomposing (lignocellulolytic) fungal communities. However, the relationship among the quality of invasive litter, lignocellulolytic cultivated fungal community composition, and litter decomposition rates under invasive conditions is still unknown. We evaluated whether the invasive herbaceous Tradescantia zebrina affects the litter decomposition in the Atlantic Forest and the lignocellulolytic cultivated fungal community composition. We placed litter bags with litter from the invader and native plants in invaded and non-invaded areas, as well as under controlled conditions. We evaluated the lignocellulolytic fungal communities by culture method and molecular identification. Litter from T. zebrina decomposed faster than litter from native species. However, the invasion of T. zebrina did not alter decomposition rates of either litter type. Although the lignocellulolytic fungal community composition changed over decomposition time, neither the invasion of T. zebrina nor litter type influenced lignocellulolytic fungal communities. We believe that the high plant richness in the Atlantic Forest enables a highly diversified and stable decomposing biota formed in conditions of high plant diversity. This diversified fungal community is capable of interacting with different litter types under different environmental conditions.

Identification and Characterization of Fusarium fujikuroi Pathotypes Responsible for an Emerging Bakanae Disease of Rice in India

The bakanae disease of rice, or foolish seedling disease, is a well-known pathogen infecting rice hosts. Several studies have characterized Fusarium fujikuroi isolates collected from distant geographical regions and within similar geographical areas for secondary metabolite production, population structure, and diversity analysis, but none have attempted to characterize the isolates for virulence in a differential set of rice genotypes. Based on the disease response, a set of five rice genotypes with differing resistance levels were selected as a differential set for further characterization of the pathogen. Ninety-seven Fusarium fujikuroi isolates collected from different rice-growing areas of the country during the years 2011 to 2020 were characterized and evaluated for bakanae disease. Rice genotypes PB1509 and C101A51 were found to be highly susceptible and highly resistant, respectively. Further, based on the disease response, the isolates were grouped into 15 pathotypes. Pathotype 1, with the maximum isolates (19), was observed to be most prevalent, followed by pathotypes 2 and 3. Pathotype 8 was classified as highly virulent, as all the genotypes were susceptible, except for C101A51. When we compared the pathotype distribution in different states, pathotypes 11 and 15 were found to have originated from the state of Punjab. A positive correlation could be established between six pathotype groups and the gene expression of virulence-related genes such as acetylxylan (FFAC), exopolygalacturanase (FFEX), and pisatin demethylase (FFPD). The present study provides the distribution profiles of different pathotypes in Basmati-growing states of India, which will be further helpful for the deployment of breeding strategies and bakanae disease management.

Comparative transcriptome profiling and weighted gene co-expression network analysis to identify core genes in maize (Zea mays L.) silks infected by multiple fungi

Maize (Zea mays L.) is the third most popular Poaceae crop after wheat and rice and used in feed and pharmaceutical sectors. The maize silk contains bioactive components explored by traditional Chinese herbal medicine for various pharmacological activities. However, Fusarium graminearum, Fusarium verticillioides, Trichoderma atroviride, and Ustilago maydis can infect the maize, produce mycotoxins, hamper the quantity and quality of silk production, and further harm the primary consumer's health. However, the defense mechanism is not fully understood in multiple fungal infections in the silk of Z. mays. In this study, we applied bioinformatics approaches to use the publicly available transcriptome data of Z. mays silk affected by multiple fungal flora to identify core genes involved in combatting disease response. Differentially expressed genes (DEGs) were identified among intra- and inter-transcriptome data sets of control versus infected Z. mays silks. Upon further comparison between up- and downregulated genes within the control of datasets, 4,519 upregulated and 5,125 downregulated genes were found. The DEGs have been compared with genes in the modules of weighted gene co-expression network analysis to relevant specific traits towards identifying core genes. The expression pattern of transcription factors, carbohydrate-active enzymes (CAZyme), and resistance genes was analyzed. The present investigation is supportive of our findings that the gene ontology, immunity stimulus, and resistance genes are upregulated, but physical and metabolic processes such as cell wall organizations and pectin synthesis were downregulated respectively. Our results are indicative that terpene synthase TPS6 and TPS11 are involved in the defense mechanism against fungal infections in maize silk.

Computational identification and characterization of vascular wilt pathogen (Fusarium oxysporum f. sp. lycopersici) CAZymes in tomato xylem sap

Fusarium oxysporum f. sp. lycopersici is a devastating plant pathogenic fungi known for wilt disease in the tomato plant and secrete cell wall degrading enzymes. These enzymes are collectively known as carbohydrate-active enzymes (CAZymes), crucial for growth, colonization and pathogenesis. Therefore, the present study was aimed to identify and annotate pathogen CAZymes in the xylem sap of a susceptible tomato variety using downstream proteomics and meta servers. Further, structural elucidation and conformational stability analysis of the selected CAZyme families were done through homology modeling and molecular dynamics simulation. Among all the fungal proteins identified, the carbohydrate metabolic process was found to be enriched. Most of the annotated CAZymes belonged to the hydrolase and oxidoreductase families, and 90% were soluble and extracellular. Moreover, using a publically available interactome database, interactions were observed between the families acting on chitin, hemicellulose and pectin. Subsequently, important catalytic residues were identified in the candidate CAZymes belonging to carbohydrate esterase (CE8) and glycosyl hydrolase (GH18 and GH28). Further, essential dynamics after molecular simulation of 100 ns revealed the overall behavior of these CAZymes with distinct global minima and transition states in CE8. Thus, our study identified some of the CAZyme families that assist in pathogenesis and growth through host cell wall deconstruction with further structural insight into the selected CAZyme families.Communicated by Ramaswamy H. Sarma.

In Vitro Secretome Analysis Suggests Differential Pathogenic Mechanisms between Fusarium oxysporum f. sp. cubense Race 1 and Race 4

Banana Fusarium wilt, caused by the fungus pathogen Fusarium oxysporum f. sp. cubense (Foc), is a devastating disease that causes tremendous reductions in banana yield worldwide. Secreted proteins can act as pathogenicity factors and play important roles in the Foc-banana interactions. In this study, a shotgun-based proteomic approach was employed to characterize and compare the secretomes of Foc1 and Foc4 upon banana extract treatment, which detected 1183 Foc1 and 2450 Foc4 proteins. Comprehensive in silico analyses further identified 447 Foc1 and 433 Foc4 proteins in the classical and non-classical secretion pathways, while the remaining proteins might be secreted through currently unknown mechanisms. Further analyses showed that the secretomes of Foc1 and Foc4 are similar in their overall functional characteristics and share largely conserved repertoires of CAZymes and effectors. However, we also identified a number of potentially important pathogenicity factors that are differentially present in Foc1 and Foc4, which may contribute to their different pathogenicity against banana hosts. Furthermore, our quantitative PCR analysis revealed that genes encoding secreted pathogenicity factors differ significantly between Foc1 and Foc4 in their expression regulation in response to banana extract treatment. To our knowledge, this is the first experimental secretome analysis that focused on the pathogenicity mechanism in different Foc races. The results of this study provide useful resources for further exploration of the complicated pathogenicity mechanisms in Foc.

Sequencing of non-virulent strains of Fusarium fujikuroi reveals genes putatively involved in bakanae disease of rice

Bakanae, one of the most important diseases of rice, is caused by the fungal pathogen Fusarium fujikuroi. The elongation of internodes is the most common symptom induced by the pathogen, and it is related to the production of gibberellins. Despite this, the pathogenicity mechanism of F. fujikuroi is still not completely clear, and there are some strains inducing stunting instead of elongation. Even if there are relatively many genomes of F. fujikuroi strains available in online databases, none of them belongs to an isolate of proven non-virulence, and therefore there has been no comparative genomics study conducted between virulent and non-virulent strains. In the present work, the genomes of non-virulent strain SG4 and scarcely virulent strain C2S were compared to the ones of 12 available virulent isolates. Genes present in the majority of available virulent strains, but not in the non-virulent one, underwent functional annotation with multiple tools, and their expression level during rice infection was checked using pre-existing data. Nine genes putatively related to pathogenicity in F. fujikuroi were identified throughout comparative and functional analyses. Among these, many are involved in the degradation of plant cell wall, which is poorly studied in F. fujikuroi-rice interactions. Three of them were validated through qPCR, showing higher expression in the virulent strain and low to no expression in the low virulent and non virulent strains during rice infection. This work helps to clarify the mechanisms of pathogenicity of F. fujikuroi on rice.

Do Lytic Polysaccharide Monooxygenases Aid in Plant Pathogenesis and Herbivory?

Lytic polysaccharide monooxygenases (LPMOs), copper-dependent enzymes mainly found in fungi, bacteria, and viruses, are responsible for enabling plant infection and degradation processes. Since their discovery 10 years ago, significant progress has been made in understanding the major role these enzymes play in biomass conversion. The recent discovery of additional LPMO families in fungi and oomycetes (AA16) as well as insects (AA15) strongly suggests that LPMOs might also be involved in biological processes such as overcoming plant defenses. In this review, we aim to give a comprehensive overview of the potential role of different LPMO families from the perspective of plant defense and their multiple implications in devising new strategies for achieving crop protection from plant pathogens and insect pests.

Whole genome analysis of the koa wilt pathogen (Fusarium oxysporum f. sp. koae) and the development of molecular tools for early detection and monitoring

BACKGROUND

Development and application of DNA-based methods to distinguish highly virulent isolates of Fusarium oxysporum f. sp. koae [Fo koae; cause of koa wilt disease on Acacia koa (koa)] will help disease management through early detection, enhanced monitoring, and improved disease resistance-breeding programs.

RESULTS

This study presents whole genome analyses of one highly virulent Fo koae isolate and one non-pathogenic F. oxysporum (Fo) isolate. These analyses allowed for the identification of putative lineage-specific DNA and predicted genes necessary for disease development on koa. Using putative chromosomes and predicted gene comparisons, Fo koae-exclusive, virulence genes were identified. The putative lineage-specific DNA included identified genes encoding products secreted in xylem (e. g., SIX1 and SIX6) that may be necessary for disease development on koa. Unique genes from Fo koae were used to develop pathogen-specific PCR primers. These diagnostic primers allowed target amplification in the characterized highly virulent Fo koae isolates but did not allow product amplification in low-virulence or non-pathogenic isolates of Fo. Thus, primers developed in this study will be useful for early detection and monitoring of highly virulent strains of Fo koae. Isolate verification is also important for disease resistance-breeding programs that require a diverse set of highly virulent Fo koae isolates for their disease-screening assays to develop disease-resistant koa.

CONCLUSIONS

These results provide the framework for understanding the pathogen genes necessary for koa wilt disease and the genetic variation of Fo koae populations across the Hawaiian Islands.

Real-Time Visualization of Cellulase Activity by Microorganisms on Surface

A variety of methods to detect cellulase secretion by microorganisms has been developed over the years, none of which enables the real-time visualization of cellulase activity on a surface. This visualization is critical to study the interaction between soil-borne cellulase-secreting microorganisms and the surface of plant roots and specifically, the effect of surface features on this interaction. Here, we modified the known carboxymethyl cellulase (CMC) hydrolysis visualization method to enable the real-time tracking of cellulase activity of microorganisms on a surface. A surface was formed using pure CMC with acridine orange dye incorporated in it. The dye disassociated from the film when hydrolysis occurred, forming a halo surrounding the point of hydrolysis. This enabled real-time visualization, since the common need for post hydrolysis dyeing was negated. Using root-knot nematode (RKN) as a model organism that penetrates plant roots, we showed that it was possible to follow microorganism cellulase secretion on the surface. Furthermore, the addition of natural additives was also shown to be an option and resulted in an increased RKN response. This method will be implemented in the future, investigating different microorganisms on a root surface microstructure replica, which can open a new avenue of research in the field of plant root-microorganism interactions.