Evaluation of Secretion Prediction Highlights Differing Approaches Needed for Oomycete and Fungal Effectors

Annotation of RxLR Effectors in Oomycete Genomes

Pathogens have evolved effector proteins to suppress host immunity and facilitate plant infections. RxLR effectors are small, secreted effector proteins with conserved RxLR and dEER amino acid motifs at the N terminus and highly variable C termini and are commonly found in oomycete species. We provide computational approaches to annotate RxLR candidate effector genes in a genome assembly in FASTA format with an available GFF file. Hidden Markov Modeling (HHM) is used in combination with regular expressions to search for RxLR and EER amino acid patterns.

Identification and characterization of specific motifs in effector proteins of plant parasites using MOnSTER

Plant pathogens cause billions of dollars of crop loss every year and are a major threat to global food security. Identifying and characterizing pathogens effectors is crucial towards their improved control. Because of their poor sequence conservation, effector identification is challenging, and current methods generate too many candidates without indication for prioritizing experimental studies. In most phyla, effectors contain specific sequence motifs which influence their localization and targets in the plant. Therefore, there is an urgent need to develop bioinformatics tools tailored for pathogen effectors. To circumvent these limitations, we have developed MOnSTER a specific tool that identifies clusters of motifs of protein sequences (CLUMPs). MOnSTER can be fed with motifs identified by de novo tools or from databases such as Pfam and InterProScan. The advantage of MOnSTER is the reduction of motif redundancy by clustering them and associating a score. This score encompasses the physicochemical properties of AAs and the motif occurrences. We built up our method to identify discriminant CLUMPs in oomycetes effectors. Consequently, we applied MOnSTER on plant parasitic nematodes and identified six CLUMPs in about 60% of the known nematode candidate parasitism proteins. Furthermore, we found co-occurrences of CLUMPs with protein domains important for invasion and pathogenicity. The potentiality of this tool goes beyond the effector characterization and can be used to easily cluster motifs and calculate the CLUMP-score on any set of protein sequences.

Parascedosporium putredinis NO1 tailors its secretome for different lignocellulosic substrates

Parascedosporium putredinis NO1 is a plant biomass-degrading ascomycete with a propensity to target the most recalcitrant components of lignocellulose. Here we applied proteomics and activity-based protein profiling (ABPP) to investigate the ability of P. putredinis NO1 to tailor its secretome for growth on different lignocellulosic substrates. Proteomic analysis of soluble and insoluble culture fractions following the growth of P. putredinis NO1 on six lignocellulosic substrates highlights the adaptability of the response of the P. putredinis NO1 secretome to different substrates. Differences in protein abundance profiles were maintained and observed across substrates after bioinformatic filtering of the data to remove intracellular protein contamination to identify the components of the secretome more accurately. These differences across substrates extended to carbohydrate-active enzymes (CAZymes) at both class and family levels. Investigation of abundant activities in the secretomes for each substrate revealed similar variation but also a high abundance of "unknown" proteins in all conditions investigated. Fluorescence-based and chemical proteomic ABPP of secreted cellulases, xylanases, and β-glucosidases applied to secretomes from multiple growth substrates for the first time confirmed highly adaptive time- and substrate-dependent glycoside hydrolase production by this fungus. P. putredinis NO1 is a promising new candidate for the identification of enzymes suited to the degradation of recalcitrant lignocellulosic feedstocks. The investigation of proteomes from the biomass bound and culture supernatant fractions provides a more complete picture of a fungal lignocellulose-degrading response. An in-depth understanding of this varied response will enhance efforts toward the development of tailored enzyme systems for use in biorefining.IMPORTANCEThe ability of the lignocellulose-degrading fungus Parascedosporium putredinis NO1 to tailor its secreted enzymes to different sources of plant biomass was revealed here. Through a combination of proteomic, bioinformatic, and fluorescent labeling techniques, remarkable variation was demonstrated in the secreted enzyme response for this ascomycete when grown on multiple lignocellulosic substrates. The maintenance of this variation over time when exploring hydrolytic polysaccharide-active enzymes through fluorescent labeling, suggests that this variation results from an actively tailored secretome response based on substrate. Understanding the tailored secretomes of wood-degrading fungi, especially from underexplored and poorly represented families, will be important for the development of effective substrate-tailored treatments for the conversion and valorization of lignocellulose.

The structural landscape and diversity of Pyricularia oryzae MAX effectors revisited

Magnaporthe AVRs and ToxB-like (MAX) effectors constitute a family of secreted virulence proteins in the fungus Pyricularia oryzae (syn. Magnaporthe oryzae), which causes blast disease on numerous cereals and grasses. In spite of high sequence divergence, MAX effectors share a common fold characterized by a ß-sandwich core stabilized by a conserved disulfide bond. In this study, we investigated the structural landscape and diversity within the MAX effector repertoire of P. oryzae. Combining experimental protein structure determination and in silico structure modeling we validated the presence of the conserved MAX effector core domain in 77 out of 94 groups of orthologs (OG) identified in a previous population genomic study. Four novel MAX effector structures determined by NMR were in remarkably good agreement with AlphaFold2 (AF2) predictions. Based on the comparison of the AF2-generated 3D models we propose a classification of the MAX effectors superfamily in 20 structural groups that vary in the canonical MAX fold, disulfide bond patterns, and additional secondary structures in N- and C-terminal extensions. About one-third of the MAX family members remain singletons, without strong structural relationship to other MAX effectors. Analysis of the surface properties of the AF2 MAX models also highlights the high variability within the MAX family at the structural level, potentially reflecting the wide diversity of their virulence functions and host targets.

Codon usage bias of secretory protein in Fusarium oxysporum f. sp. cubense tropical race 4

Banana Fusarium oxysporum f. sp. cubense tropical race 4 (Foc-TR4) is a highly destructive pathogen that infects nearly all major banana cultivars and has a tendency to spread further. Secreted proteins play a crucial role in the process of Fusarium wilt infection in bananas. In this study, we analyzed the codon usage bias (CUB) of the Foc-TR4 classical secretory protein genome for the first time and observed a strong bias toward codons ending with C. We found that 572 out of the 14,543 amino acid sequences in the Foc-TR4 genome exhibited characteristics of classical secretory proteins. The CUB was largely influenced by selection optimization pressure, as indicated by the ENC value and neutral plot analysis. Among the identified codons, such as UCC and CCC, 11 were found to be optimal for Foc-TR4 gene expression. Codons with higher GC content and a C base in the third position showed greater selectivity. The CUB in the secretory proteins encoded by Foc-TR4 provides insights into their evolutionary patterns, contributing to the development and screening of novel and effective antifungal drugs.

Multi-Omics Approaches Provide New Insights into the Identification of Putative Fungal Effectors from Valsa mali

Pathogenic fungi secrete numerous effectors into host cells to manipulate plants' defense mechanisms. Valsa mali, a necrotrophic fungus, severely impacts apple production in China due to the occurrence of Valsa canker. Here, we predicted 210 candidate effector protein (CEP)-encoding genes from V. mali. The transcriptome analysis revealed that 146 CEP-encoding genes were differentially expressed during the infection of the host, Malus sieversii. Proteome analysis showed that 27 CEPs were differentially regulated during the infection stages. Overall, 25 of the 146 differentially expressed CEP-encoding genes were randomly selected to be transiently expressed in Nicotiana benthamiana. Pathogenicity analysis showed that the transient expression of VM1G-05058 suppressed BAX-triggered cell death while the expression of VM1G-10148 and VM1G-00140 caused cell death in N. benthamiana. In conclusion, by using multi-omics analysis, we identified potential effector candidates for further evaluation in vivo. Our results will provide new insights into the investigation of virulent mechanisms of V. mali.

Key processes required for the different stages of fungal carnivory by a nematode-trapping fungus

Nutritional deprivation triggers a switch from a saprotrophic to predatory lifestyle in soil-dwelling nematode-trapping fungi (NTF). In particular, the NTF Arthrobotrys oligospora secretes food and sex cues to lure nematodes to its mycelium and is triggered to develop specialized trapping devices. Captured nematodes are then invaded and digested by the fungus, thus serving as a food source. In this study, we examined the transcriptomic response of A. oligospora across the stages of sensing, trap development, and digestion upon exposure to the model nematode Caenorhabditis elegans. A. oligospora enacts a dynamic transcriptomic response, especially of protein secretion-related genes, in the presence of prey. Two-thirds of the predicted secretome of A. oligospora was up-regulated in the presence of C. elegans at all time points examined, and among these secreted proteins, 38.5% are predicted to be effector proteins. Furthermore, functional studies disrupting the t-SNARE protein Sso2 resulted in impaired ability to capture nematodes. Additionally, genes of the DUF3129 family, which are expanded in the genomes of several NTF, were highly up-regulated upon nematode exposure. We observed the accumulation of highly expressed DUF3129 proteins in trap cells, leading us to name members of this gene family as Trap Enriched Proteins (TEPs). Gene deletion of the most highly expressed TEP gene, TEP1, impairs the function of traps and prevents the fungus from capturing prey efficiently. In late stages of predation, we observed up-regulation of a variety of proteases, including metalloproteases. Following penetration of nematodes, these metalloproteases facilitate hyphal growth required for colonization of prey. These findings provide insights into the biology of the predatory lifestyle switch in a carnivorous fungus and provide frameworks for other fungal-nematode predator-prey systems.

Seeking the interspecies crosswalk for filamentous microbe effectors

Both pathogenic and symbiotic microorganisms modulate the immune response and physiology of their host to establish a suitable niche. Key players in mediating colonization outcome are microbial effector proteins that act either inside (cytoplasmic) or outside (apoplastic) the plant cells and modify the abundance or activity of host macromolecules. We compile novel insights into the much-disputed processes of effector secretion and translocation of filamentous organisms, namely fungi and oomycetes. We report how recent studies that focus on unconventional secretion and effector structure challenge the long-standing image of effectors as conventionally secreted proteins that are translocated with the aid of primary amino acid sequence motifs. Furthermore, we emphasize the potential of diverse, unbiased, state-of-the-art proteomics approaches in the holistic characterization of fungal and oomycete effectomes.

Pathogen Profile of Klebsiella variicola, the Causative Agent of Banana Sheath Rot

Banana (Musa spp.) is an important fruit and food crop worldwide. In recent years, banana sheath rot has become a major problem in banana cultivation, causing plant death and substantial economic losses. Nevertheless, the pathogen profile of this disease has not been fully characterized. Klebsiella variicola is a versatile bacterium capable of colonizing different hosts, such as plants, humans, insects, and animals, and is recognized as an emerging pathogen in various hosts. In this study, we obtained 12 bacterial isolates from 12 different banana samples showing banana sheath rot in Guangdong and Guangxi Provinces, China. Phylogenetic analysis based on 16S rRNA sequences confirmed that all 12 isolates were K. variicola strains. We sequenced the genomes of these strains, performed comparative genomic analysis with other sequenced K. variicola strains, and found a lack of consistency in accessory gene content among these K. variicola strains. However, prediction based on the pan-genome of K. variicola revealed 22 unique virulence factors carried by the 12 pathogenic K. variicola isolates. Microbiome and microbial interaction network analysis of endophytes between the healthy tissues of diseased plants and healthy plants of two cultivars showed that Methanobacterium negatively interacts with Klebsiella in banana plants and that Herbaspirillum might indirectly inhibit Methanobacterium to promote Klebsiella growth. These results suggest that banana sheath rot is caused by the imbalance of plant endophytes and opportunistic pathogenic bacteria, providing an important basis for research and control of this disease.[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.

Genome analysis of Phytophthora cactorum strains associated with crown- and leather-rot in strawberry

Phytophthora cactorum has two distinct pathotypes that cause crown rot and leather rot in strawberry (Fragaria × ananassa). Strains of the crown rot pathotype can infect both the rhizome (crown) and fruit tissues, while strains of the leather rot pathotype can only infect the fruits of strawberry. The genome of a highly virulent crown rot strain, a low virulent crown rot strain, and three leather rot strains were sequenced using PacBio high fidelity (HiFi) long read sequencing. The reads were de novo assembled to 66.4-67.6 megabases genomes in 178-204 contigs, with N50 values ranging from 892 to 1,036 kilobases. The total number of predicted complete genes in the five P. cactorum genomes ranged from 17,286 to 17,398. Orthology analysis identified a core secretome of 8,238 genes. Comparative genomic analysis revealed differences in the composition of potential virulence effectors, such as putative RxLR and Crinklers, between the crown rot and the leather rot pathotypes. Insertions, deletions, and amino acid substitutions were detected in genes encoding putative elicitors such as beta elicitin and cellulose-binding domain proteins from the leather rot strains compared to the highly virulent crown rot strain, suggesting a potential mechanism for the crown rot strain to escape host recognition during compatible interaction with strawberry. The results presented here highlight several effectors that may facilitate the tissue-specific colonization of P. cactorum in strawberry.

Characterization of Arbuscular Mycorrhizal Effector Proteins

Plants are colonized by various fungi with both pathogenic and beneficial lifestyles. One type of colonization strategy is through the secretion of effector proteins that alter the plant's physiology to accommodate the fungus. The oldest plant symbionts, the arbuscular mycorrhizal fungi (AMF), may exploit effectors to their benefit. Genome analysis coupled with transcriptomic studies in different AMFs has intensified research on the effector function, evolution, and diversification of AMF. However, of the current 338 predicted effector proteins from the AM fungus Rhizophagus irregularis, only five have been characterized, of which merely two have been studied in detail to understand which plant proteins they associate with to affect the host physiology. Here, we review the most recent findings in AMF effector research and discuss the techniques used for the functional characterization of effector proteins, from their in silico prediction to their mode of action, with an emphasis on high-throughput approaches for the identification of plant targets of the effectors through which they manipulate their hosts.

A tell tail sign: a conserved C-terminal tail-anchor domain targets a subset of pathogen effectors to the plant endoplasmic reticulum

The endoplasmic reticulum (ER) is the entry point to the secretory pathway and, as such, is critical for adaptive responses to biotic stress, when the demand for de novo synthesis of immunity-related proteins and signalling components increases significantly. Successful phytopathogens have evolved an arsenal of small effector proteins which collectively reconfigure multiple host components and signalling pathways to promote virulence; a small, but important, subset of which are targeted to the endomembrane system including the ER. We identified and validated a conserved C-terminal tail-anchor motif in a set of pathogen effectors known to localize to the ER from the oomycetes Hyaloperonospora arabidopsidis and Plasmopara halstedii (downy mildew of Arabidopsis and sunflower, respectively) and used this protein topology to develop a bioinformatic pipeline to identify putative ER-localized effectors within the effectorome of the related oomycete, Phytophthora infestans, the causal agent of potato late blight. Many of the identified P. infestans tail-anchor effectors converged on ER-localized NAC transcription factors, indicating that this family is a critical host target for multiple pathogens.

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.

Chromosome-level assembly of the Phytophthora agathidicida genome reveals adaptation in effector gene families

Phytophthora species are notorious plant pathogens, with some causing devastating tree diseases that threaten the survival of their host species. One such example is Phytophthora agathidicida, the causal agent of kauri dieback - a root and trunk rot disease that kills the ancient, iconic and culturally significant tree species, Agathis australis (New Zealand kauri). A deeper understanding of how Phytophthora pathogens infect their hosts and cause disease is critical for the development of effective treatments. Such an understanding can be gained by interrogating pathogen genomes for effector genes, which are involved in virulence or pathogenicity. Although genome sequencing has become more affordable, the complete assembly of Phytophthora genomes has been problematic, particularly for those with a high abundance of repetitive sequences. Therefore, effector genes located in repetitive regions could be truncated or missed in a fragmented genome assembly. Using a combination of long-read PacBio sequences, chromatin conformation capture (Hi-C) and Illumina short reads, we assembled the P. agathidicida genome into ten complete chromosomes, with a genome size of 57 Mb including 34% repeats. This is the first Phytophthora genome assembled to chromosome level and it reveals a high level of syntenic conservation with the complete genome of Peronospora effusa, the only other completely assembled genome sequence of an oomycete. All P. agathidicida chromosomes have clearly defined centromeres and contain candidate effector genes such as RXLRs and CRNs, but in different proportions, reflecting the presence of gene family clusters. Candidate effector genes are predominantly found in gene-poor, repeat-rich regions of the genome, and in some cases showed a high degree of duplication. Analysis of candidate RXLR effector genes that occur in multicopy gene families indicated half of them were not expressed in planta. Candidate CRN effector gene families showed evidence of transposon-mediated recombination leading to new combinations of protein domains, both within and between chromosomes. Further analysis of this complete genome assembly will help inform new methods of disease control against P. agathidicida and other Phytophthora species, ultimately helping decipher how Phytophthora pathogens have evolved to shape their effector repertoires and how they might adapt in the future.

Genomics and Informatics, Conjoined Tools Vital for Understanding and Protecting Plant Health

Genomics' impact on crop production continuously expands. The number of sequenced plant and microbial species and strains representing diverse populations of individual species rapidly increases thanks to the advent of next-generation sequencing technologies. Their genomic blueprints revealed candidate genes involved in various functions and processes crucial for crop health and helped in understanding how the sequenced organisms have evolved at the genome level. Functional genomics quickly translates these blueprints into a detailed mechanistic understanding of how such functions and processes work and are regulated; this understanding guides and empowers efforts to protect crops from diverse biotic and abiotic threats. Metagenome analyses help identify candidate microbes crucial for crop health and uncover how microbial communities associated with crop production respond to environmental conditions and cultural practices, presenting opportunities to enhance crop health by judiciously configuring microbial communities. Efficient conversion of disparate types of massive genomics data into actionable knowledge requires a robust informatics infrastructure supporting data preservation, analysis, and sharing. This review starts with an overview of how genomics came about and has quickly transformed life science. We illuminate how genomics and informatics can be applied to investigate various crop health-related problems using selected studies. We end the review by noting why community empowerment via crowdsourcing is crucial to harnessing genomics to protect global food and nutrition security without continuously expanding the environmental footprint of crop production.

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.

Computational Structural Genomics Unravels Common Folds and Novel Families in the Secretome of Fungal Phytopathogen Magnaporthe oryzae

Structural biology has the potential to illuminate the evolution of pathogen effectors and their commonalities that cannot be readily detected at the primary sequence level. Recent breakthroughs in protein structure modeling have demonstrated the feasibility to predict the protein folds without depending on homologous templates. These advances enabled a genome-wide computational structural biology approach to help understand proteins based on their predicted folds. In this study, we employed structure prediction methods on the secretome of the destructive fungal pathogen Magnaporthe oryzae. Out of 1,854 secreted proteins, we predicted the folds of 1,295 proteins (70%). We showed that template-free modeling by TrRosetta captured 514 folds missed by homology modeling, including many known effectors and virulence factors, and that TrRosetta generally produced higher quality models for secreted proteins. Along with sensitive homology search, we employed structure-based clustering, defining not only homologous groups with divergent members but also sequence-unrelated structurally analogous groups. We demonstrate that this approach can reveal new putative members of structurally similar MAX effectors and novel analogous effector families present in M. oryzae and possibly in other phytopathogens. We also investigated the evolution of expanded putative ADP-ribose transferases with predicted structures. We suggest that the loss of catalytic activities of the enzymes might have led them to new evolutionary trajectories to be specialized as protein binders. Collectively, we propose that computational structural genomics approaches can be an integral part of studying effector biology and provide valuable resources that were inaccessible before the advent of machine learning-based structure prediction.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

An automated and combinative method for the predictive ranking of candidate effector proteins of fungal plant pathogens

Fungal plant-pathogens promote infection of their hosts through the release of 'effectors'-a broad class of cytotoxic or virulence-promoting molecules. Effectors may be recognised by resistance or sensitivity receptors in the host, which can determine disease outcomes. Accurate prediction of effectors remains a major challenge in plant pathology, but if achieved will facilitate rapid improvements to host disease resistance. This study presents a novel tool and pipeline for the ranking of predicted effector candidates-Predector-which interfaces with multiple software tools and methods, aggregates disparate features that are relevant to fungal effector proteins, and applies a pairwise learning to rank approach. Predector outperformed a typical combination of secretion and effector prediction methods in terms of ranking performance when applied to a curated set of confirmed effectors derived from multiple species. We present Predector ( https://github.com/ccdmb/predector ) as a useful tool for the ranking of predicted effector candidates, which also aggregates and reports additional supporting information relevant to effector and secretome prediction in a simple, efficient, and reproducible manner.

Comparative analyses of saprotrophy in Salisapilia sapeloensis and diverse plant pathogenic oomycetes reveal lifestyle-specific gene expression

Oomycetes include many devastating plant pathogens. Across oomycete diversity, plant-infecting lineages are interspersed by non-pathogenic ones. Unfortunately, our understanding of the evolution of lifestyle switches is hampered by a scarcity of data on the molecular biology of saprotrophic oomycetes, ecologically important primary colonizers of dead tissue that can serve as informative reference points for understanding the evolution of pathogens. Here, we established Salisapilia sapeloensis as a tractable system for the study of saprotrophic oomycetes. We generated multiple transcriptomes from S. sapeloensis and compared them with (i) 22 oomycete genomes and (ii) the transcriptomes of eight pathogenic oomycetes grown under 13 conditions. We obtained a global perspective on gene expression signatures of oomycete lifestyles. Our data reveal that oomycete saprotrophs and pathogens use similar molecular mechanisms for colonization but exhibit distinct expression patterns. We identify a S. sapeloensis-specific array and expression of carbohydrate-active enzymes and putative regulatory differences, highlighted by distinct expression levels of transcription factors. Salisapilia sapeloensis expresses only a small repertoire of candidates for virulence-associated genes. Our analyses suggest lifestyle-specific gene regulatory signatures and that, in addition to variation in gene content, shifts in gene regulatory networks underpin the evolution of oomycete lifestyles.

Characterization of CRN-Like Genes From Plasmopara viticola: Searching for the Most Virulent Ones

Grapevine downy mildew is an insurmountable disease that endangers grapevine production and the wine industry worldwide. The causal agent of the disease is the obligate biotrophic oomycete Plasmopara viticola, for which the pathogenic mechanism remains largely unknown. Crinkling and necrosis proteins (CRN) are an ancient class of effectors utilized by pathogens, including oomycetes, that interfere with host plant defense reactions. In this study, 27 CRN-like genes were cloned from the P. viticola isolate YL genome, hereafter referred to as PvCRN genes, and characterized in silico and in planta. PvCRN genes in ‘YL’ share high sequence identities with their ortholog genes in the other three previously sequenced P. viticola isolates. Sequence divergence among the genes in the PvCRN family indicates that different PvCRN genes have different roles. Phylogenetic analysis of the PvCRN and the CRN proteins encoded by genes in the P. halstedii genome suggests that various functions might have been acquired by the CRN superfamily through independent evolution of Plasmopara species. When transiently expressed in plant cells, the PvCRN protein family shows multiple subcellular localizations. None of the cloned PvCRN proteins induced hypersensitive response (HR)-like cell death on the downy mildew-resistant grapevine Vitis riparia. This was in accordance with the result that most PvCRN proteins, except PvCRN11, failed to induce necrosis in Nicotiana benthamiana. Pattern-triggered immunity (PTI) induced by INF1 was hampered by several PvCRN proteins. In addition, 15 PvCRN proteins prevented Bax-induced plant programmed cell death. Among the cell death-suppressing members, PvCRN17, PvCRN20, and PvCRN23 were found to promote the susceptibility of N. benthamiana to Phytophthora capsici, which is a semi-biotrophic oomycete. Moreover, the nucleus-targeting member, PvCRN19, promoted the susceptibility of N. benthamiana to P. capsici. Therefore, these PvCRN proteins were estimated to be virulent effectors involved in the pathogenicity of P. viticola YL. Collectively, this study provides comprehensive insight into the CRN effector repertoire of P. viticola YL, which will help further elucidate the molecular mechanisms of the pathogenesis of grapevine downy mildew.

Genome Assembly and Transcriptome Analysis of the Fungus Coniella diplodiella During Infection on Grapevine (Vitis vinifera L.)

Grape white rot caused by Coniella diplodiella (Speg.) affects the production and quality of grapevine in China and other grapevine-growing countries. Despite the importance of C. diplodiella as a serious disease-causing agent in grape, the genome information and molecular mechanisms underlying its pathogenicity are poorly understood. To bridge this gap, 40.93 Mbp of C. diplodiella strain WR01 was de novo assembled. A total of 9,403 putative protein-coding genes were predicted. Among these, 608 and 248 genes are potentially secreted proteins and candidate effector proteins (CEPs), respectively. Additionally, the transcriptome of C. diplodiella was analyzed after feeding with crude grapevine leaf homogenates, which reveals the transcriptional expression of 9,115 genes. Gene ontology enrichment analysis indicated that the highly enriched genes are related with carbohydrate metabolism and secondary metabolite synthesis. Forty-three putative effectors were cloned from C. diplodiella, and applied for further functional analysis. Among them, one protein exhibited strong effect in the suppression of BCL2-associated X (BAX)-induced hypersensitive response after transiently expressed in Nicotiana benthamiana leaves. This work facilitates valuable genetic basis for understanding the molecular mechanism underlying C. diplodiella-grapevine interaction.

The Effector Repertoire of the Hop Downy Mildew Pathogen Pseudoperonospora humuli

Pseudoperonospora humuli is an obligate biotrophic oomycete that causes downy mildew (DM), one of the most destructive diseases of cultivated hop that can lead to 100% crop loss in susceptible cultivars. We used the published genome of P. humuli to predict the secretome and effectorome and analyze the transcriptome variation among diverse isolates and during infection of hop leaves. Mining the predicted coding genes of the sequenced isolate OR502AA of P. humuli revealed a secretome of 1,250 genes. We identified 296 RXLR and RXLR-like effector-encoding genes in the secretome. Among the predicted RXLRs, there were several WY-motif-containing effectors that lacked canonical RXLR domains. Transcriptome analysis of sporangia from 12 different isolates collected from various hop cultivars revealed 754 secreted proteins and 201 RXLR effectors that showed transcript evidence across all isolates with reads per kilobase million (RPKM) values > 0. RNA-seq analysis of OR502AA-infected hop leaf samples at different time points after infection revealed highly expressed effectors that may play a relevant role in pathogenicity. Quantitative RT-PCR analysis confirmed the differential expression of selected effectors. We identified a set of P. humuli core effectors that showed transcript evidence in all tested isolates and elevated expression during infection. These effectors are ideal candidates for functional analysis and effector-assisted breeding to develop DM resistant hop cultivars.

Secretomes of medically important fungi reflect morphological and phylogenetic diversity

Secretome represents a main target for understanding the mechanisms of fungal adaptation. In the present study, we focus on the secretomes of fungi associated with infections in humans and other mammals in order to explore relationships between the diverse morphological and phylogenetic groups. Almost all the mammalian pathogenic fungi analyzed have secretome sizes smaller than 1000 proteins and, secreted proteins comprise between 5% and 10% of the total proteome. As expected, the correlation pattern between the secretome size and the total proteome was similar to that described in previous secretome studies of fungi. With regard to the morphological groups, minimum secretome sizes of less than 250 secreted proteins and low values for the fraction of secreted proteins are shown in mammalian pathogenic fungi with reduced proteomes such as microsporidia, atypical fungi and some species of yeasts and yeast-like fungi (Malassezia). On the other hand, filamentous fungi have significantly more secreted proteins and the highest numbers are present in species of filamentous fungi that also are plant or insect pathogens (Fusarium verticilloides, Fusarium oxysporum and Basidiobolus meristosporus). With respect to phylogeny, there are also variations in secretome size across fungal subphyla: Microsporidia, Taphrinomycotina, Ustilagomycotina and Saccharomycotina contain small secretomes; whereas larger secretomes are found in Agaricomycotina, Pezizomycotina, Mucoromycotina and Entomophthoromycotina. Finally, principal component analysis (PCA) was conducted on the complete secretomes. The PCA results revealed that, in general, secretomes of fungi belonging to the same morphological group or subphyla cluster together. In conclusion, our results point out that in medically important fungi there is a relationship between the secretome and the morphological group or phylogenetic classification.

Genome reconstruction of the non-culturable spinach downy mildew Peronospora effusa by metagenome filtering

Peronospora effusa (previously known as P. farinosa f. sp. spinaciae, and here referred to as Pfs) is an obligate biotrophic oomycete that causes downy mildew on spinach (Spinacia oleracea). To combat this destructive many disease resistant cultivars have been bred and used. However, new Pfs races rapidly break the employed resistance genes. To get insight into the gene repertoire of Pfs and identify infection-related genes, the genome of the first reference race, Pfs1, was sequenced, assembled, and annotated. Due to the obligate biotrophic nature of this pathogen, material for DNA isolation can only be collected from infected spinach leaves that, however, also contain many other microorganisms. The obtained sequences can, therefore, be considered a metagenome. To filter and obtain Pfs sequences we utilized the CAT tool to taxonomically annotate ORFs residing on long sequences of a genome pre-assembly. This study is the first to show that CAT filtering performs well on eukaryotic contigs. Based on the taxonomy, determined on multiple ORFs, contaminating long sequences and corresponding reads were removed from the metagenome. Filtered reads were re-assembled to provide a clean and improved Pfs genome sequence of 32.4 Mbp consisting of 8,635 scaffolds. Transcript sequencing of a range of infection time points aided the prediction of a total of 13,277 gene models, including 99 RxLR(-like) effector, and 14 putative Crinkler genes. Comparative analysis identified common features in the predicted secretomes of different obligate biotrophic oomycetes, regardless of their phylogenetic distance. Their secretomes are generally smaller, compared to hemi-biotrophic and necrotrophic oomycete species. We observe a reduction in proteins involved in cell wall degradation, in Nep1-like proteins (NLPs), proteins with PAN/apple domains, and host translocated effectors. The genome of Pfs1 will be instrumental in studying downy mildew virulence and for understanding the molecular adaptations by which new isolates break spinach resistance.

EffHunter: A Tool for Prediction of Effector Protein Candidates in Fungal Proteomic Databases

Pathogens are able to deliver small-secreted, cysteine-rich proteins into plant cells to enable infection. The computational prediction of effector proteins remains one of the most challenging areas in the study of plant fungi interactions. At present, there are several bioinformatic programs that can help in the identification of these proteins; however, in most cases, these programs are managed independently. Here, we present EffHunter, an easy and fast bioinformatics tool for the identification of effectors. This predictor was used to identify putative effectors in 88 proteomes using characteristics such as size, cysteine residue content, secretion signal and transmembrane domains.

Comparative Genomic and Proteomic Analyses of Three Widespread Phytophthora Species: Phytophthora chlamydospora, Phytophthora gonapodyides and Phytophthora pseudosyringae

The Phytophthora genus includes some of the most devastating plant pathogens. Here we report draft genome sequences for three ubiquitous Phytophthora species-Phytophthora chlamydospora, Phytophthora gonapodyides, and Phytophthora pseudosyringae. Phytophthora pseudosyringae is an important forest pathogen that is abundant in Europe and North America. Phytophthora chlamydospora and Ph. gonapodyides are globally widespread species often associated with aquatic habitats. They are both regarded as opportunistic plant pathogens. The three sequenced genomes range in size from 45 Mb to 61 Mb. Similar to other oomycete species, tandem gene duplication appears to have played an important role in the expansion of effector arsenals. Comparative analysis of carbohydrate-active enzymes (CAZymes) across 44 oomycete genomes indicates that oomycete lifestyles may be linked to CAZyme repertoires. The mitochondrial genome sequence of each species was also determined, and their gene content and genome structure were compared. Using mass spectrometry, we characterised the extracellular proteome of each species and identified large numbers of proteins putatively involved in pathogenicity and osmotrophy. The mycelial proteome of each species was also characterised using mass spectrometry. In total, the expression of approximately 3000 genes per species was validated at the protein level. These genome resources will be valuable for future studies to understand the behaviour of these three widespread Phytophthora species.

Proteomic investigation of interhyphal interactions between strains of Agaricus bisporus

Hyphae of filamentous fungi undergo polar extension, bifurcation and hyphal fusion to form reticulating networks of mycelia. Hyphal fusion or anastomosis, a ubiquitous process among filamentous fungi, is a vital strategy for how fungi expand over their substrate and interact with or recognise self- and non-self hyphae of neighbouring mycelia in their environment. Morphological and genetic characterisation of anastomosis has been studied in many model fungal species, but little is known of the direct proteomic response of two interacting fungal isolates. Agaricus bisporus, the most widely cultivated edible mushroom crop worldwide, was used as an in vitro model to profile the proteomes of interacting cultures. The globally cultivated strain (A15) was paired with two distinct strains; a commercial hybrid strain and a wild isolate strain. Each co-culture presented a different interaction ranging from complete vegetative compatibility (self), lack of interactions, and antagonistic interactions. These incompatible strains are the focus of research into disease-resistance in commercial crops as the spread of intracellular pathogens, namely mycoviruses, is limited by the lack of interhyphal anastomosis. Unique proteomic responses were detected between all co-cultures. An array of cell wall modifying enzymes, plus fungal growth and morphogenesis proteins were found in significantly (P < 0.05) altered abundances. Nitrogen metabolism dominated in the intracellular proteome, with evidence of nitrogen starvation between competing, non-compatible cultures. Changes in key enzymes of A. bisporus morphogenesis were observed, particularly via increased abundance of glucanosyltransferase in competing interactions and certain chitinases in vegetative compatible interactions only. Carbohydrate-active enzyme arsenals are expanded in antagonistic interactions in A. bisporus. Pathways involved in carbohydrate metabolism and genetic information processing were higher in interacting cultures, most notably during self-recognition. New insights into the differential response of interacting strains of A. bisporus will enhance our understanding of potential barriers to viral transmission through vegetative incompatibility. Our results suggest that a differential proteomic response occurs between A. bisporus at strain-level and findings from this work may guide future proteomic investigation of fungal anastomosis.

Receptor-Like Kinases BAK1 and SOBIR1 Are Required for Necrotizing Activity of a Novel Group of Sclerotinia sclerotiorum Necrosis-Inducing Effectors

Sclerotinia sclerotiorum is a characteristic necrotrophic plant pathogen and is dependent on the induction of host cell death for nutrient acquisition. To identify necrosis-inducing effectors, the genome of S. sclerotiorum was scanned for genes encoding small, secreted, cysteine-rich proteins. These potential effectors were tested for their ability to induce necrosis in Nicotiana benthamiana via Agrobacterium-mediated expression and for cellular localization in host cells. Six novel proteins were discovered, of which all but one required a signal peptide for export to the apoplast for necrotizing activity. Virus-induced gene silencing revealed that the five necrosis-inducing effectors with a requirement for secretion also required the plant co-receptor-like kinases Brassinosteroid Insensitive 1-Associated Receptor Kinase 1 (BAK1) and Suppressor of BAK1-Interacting Receptor-like Kinase 1 (SOBIR1) for the induction of necrosis. S. sclerotiorum necrosis-inducing effector 2 (SsNE2) represented a new class of necrosis-inducing proteins as orthologs were identified in several other phytopathogenic fungi that were also capable of inducing necrosis. Substitution of conserved cysteine residues with alanine reduced, but did not abolish, the necrotizing activity of SsNE2 and full-length protein was required for function as peptides spanning the entire protein were unable to induce necrosis. These results illustrate the importance of necrosis-inducing effectors for S. sclerotiorum virulence and the role of host extracellular receptor(s) in effector-triggered susceptibility to this pathogen.

Effector mining from the Erysiphe pisi haustorial transcriptome identifies novel candidates involved in pea powdery mildew pathogenesis

Pea powdery mildew (PM) is an important fungal disease caused by an obligate biotroph, Erysiphe pisi (Ep), which significantly impacts pea production worldwide. The phytopathogen secretes a plethora of effectors, primarily through specialized infection structures termed haustoria, to establish a dynamic relationship with its host. To identify Ep effector candidates, a cDNA library of enriched haustoria from Ep-infected pea leaves was sequenced. The Ep transcriptome encodes 622 Ep candidate secreted proteins (CSPs), of which 167 were predicted to be candidate secreted effector proteins (CSEPs). Phylogenetic analysis indicates that Ep CSEPs are highly diverse, but, unlike cereal PM CSEPs, exhibit extensive sequence similarity with effectors from other PMs. Quantitative real-time PCR of a subset of EpCSEP/CSPs revealed that the majority are preferentially expressed in haustoria and exhibit infection stage-specific expression patterns. The functional roles of EpCSEP001, EpCSEP009 and EpCSP083 were probed by host-induced gene silencing (HIGS) via a double-stranded (ds) RNA-mediated RNAi approach. Foliar application of individual EpCSEP/CSP dsRNAs resulted in a marked reduction in PM disease symptoms. These findings were consistent with microscopic and molecular studies, suggesting that these Ep CSEP/CSPs play important roles in pea PM pathogenesis. Homology modelling revealed that EpCSEP001 and EpCSEP009 are analogous to fungal ribonucleases and belong to the RALPH family of effectors. This is the first study to identify and functionally validate candidate effectors from the agriculturally relevant pea PM, and highlights the utility of transcriptomics and HIGS to elucidate the key proteins associated with Ep pathogenesis.

De Novo Genome Assembly and Comparative Genomics of the Barley Leaf Rust Pathogen Puccinia hordei Identifies Candidates for Three Avirulence Genes

Puccinia hordei (Ph) is a damaging pathogen of barley throughout the world. Despite its importance, almost nothing is known about the genomics of this pathogen, and a reference genome is lacking. In this study, the first reference genome was assembled for an Australian isolate of Ph ("Ph560") using long-read SMRT sequencing. A total of 838 contigs were assembled, with a total size of 207 Mbp. This included both haplotype collapsed and separated regions, consistent with an estimated haploid genome size of about 150Mbp. An annotation pipeline that combined RNA-Seq of Ph-infected host tissues and homology to proteins from four other Puccinia species predicted 25,543 gene models of which 1,450 genes were classified as encoding secreted proteins based on the prediction of a signal peptide and no transmembrane domain. Genome resequencing using short-read technology was conducted for four additional Australian strains, Ph612, Ph626, Ph608 and Ph584, which are considered to be simple mutational derivatives of Ph560 with added virulence to one or two of three barley leaf rust resistance genes (viz. Rph3, Rph13 and Rph19). To identify candidate genes for the corresponding avirulence genes AvrRph3, AvrRph13 and AvrRph19, genetic variation in predicted secreted protein genes between the strains was correlated to the virulence profiles of each, identifying 35, 29 and 46 candidates for AvrRph13, AvrRph3 and AvrRph19, respectively. The identification of these candidate genes provides a strong foundation for future efforts to isolate these three avirulence genes, investigate their biological properties, and develop new diagnostic tests for monitoring pathogen virulence.

effectR: An Expandable R Package to Predict Candidate RxLR and CRN Effectors in Oomycetes Using Motif Searches

Effectors are small, secreted proteins that facilitate infection of host plants by all major groups of plant pathogens. Effector protein identification in oomycetes relies on identification of open reading frames with certain amino acid motifs among additional minor criteria. To date, identification of effectors relies on custom scripts to identify motifs in candidate open reading frames. Here, we developed the R package effectR, which provides a convenient tool for rapid prediction of effectors in oomycete genomes, or with custom scripts for any genome, in a reproducible way. The effectR package relies on a combination of regular expressions statements and hidden Markov model approaches to predict candidate RxLR and crinkler effectors. Other custom motifs for novel effectors can easily be implemented and added to package updates. The effectR package has been validated with published oomycete genomes. This package provides a convenient tool for wet lab researchers interested in reproducible identification of candidate effectors in oomycete genomes.

Rust pathogen effectors: perspectives in resistance breeding

Identification and functional characterization of plant pathogen effectors promise to ameliorate future research and develop effective and sustainable strategies for controlling or containing crop diseases. Wheat is the second most important food crop of the world after rice. Rust pathogens, one of the major biotic stresses in wheat production, are capable of threatening the world food security. Understanding the molecular basis of plant-pathogen interactions is essential for devising novel strategies for resistance breeding and disease management. Now, it has been established that effectors, the proteins secreted by pathogens, play a key role in plant-pathogen interactions. Therefore, effector biology has emerged as one of the most important research fields in plant biology. Recent advances in genomics and bioinformatics have allowed identification of a large repertoire of candidate effectors, while the evolving high-throughput tools have continued to assist in their functional characterization. The repertoires of effectors have become an important resource for better understanding of effector biology of pathosystems and resistance breeding of crop plants. In recent years, a significant progress has been made in the field of rust effector biology. This review describes the recent advances in effector biology of obligate fungal pathogens, identification and functional analysis of wheat rust pathogens effectors and the potential applications of effectors in molecular plant biology and rust resistance breeding in wheat.

Comparative Analysis of Oomycete Genome Evolution Using the Oomycete Gene Order Browser (OGOB)

The oomycetes are a class of microscopic, filamentous eukaryotes within the stramenopiles–alveolates–rhizaria eukaryotic supergroup. They include some of the most destructive pathogens of animals and plants, such as Phytophthora infestans, the causative agent of late potato blight. Despite the threat they pose to worldwide food security and natural ecosystems, there is a lack of tools and databases available to study oomycete genetics and evolution. To this end, we have developed the Oomycete Gene Order Browser (OGOB), a curated database that facilitates comparative genomic and syntenic analyses of oomycete species. OGOB incorporates genomic data for 20 oomycete species including functional annotations and a number of bioinformatics tools. OGOB hosts a robust set of orthologous oomycete genes for evolutionary analyses. Here, we present the structure and function of OGOB as well as a number of comparative genomic analyses we have performed to better understand oomycete genome evolution. We analyze the extent of oomycete gene duplication and identify tandem gene duplication as a driving force of the expansion of secreted oomycete genes. We identify core genes that are present and microsyntenically conserved (termed syntenologs) in oomycete lineages and identify the degree of microsynteny between each pair of the 20 species housed in OGOB. Consistent with previous comparative synteny analyses between a small number of oomycete species, our results reveal an extensive degree of microsyntenic conservation amongst genes with housekeeping functions within the oomycetes. OGOB is available at https://ogob.ie.

Prediction of the Diplocarpon rosae secretome reveals candidate genes for effectors and virulence factors

Rose black spot is one of the most severe diseases of field-grown roses. Though R-genes have been characterised, little information is known about the molecular details of the interaction between pathogen and host. Based on the recently published genome sequence of the black spot fungus, we analysed gene models with various bioinformatic tools utilising the expression data of infected host tissues, which led to the prediction of 827 secreted proteins. A significant proportion of the predicted secretome comprises enzymes for the degradation of cell wall components, several of which were highly expressed during the first infection stages. As the secretome comprises major factors determining the ability of the fungus to colonise its host, we focused our further analyses on predicted effector candidates. In total, 52 sequences of 251 effector candidates matched several bioinformatic criteria of effectors, contained a Y/F/WxC motif, and did not match annotated proteins from other fungi. Additional sequences were identified based on their high expression levels during the penetration/haustorium formation phase and/or by matching known effectors from other fungi. Several host genotypes that are resistant to the sequenced isolate but differ in the R-genes responsible for this resistance are available. The combination of these genotypes with functional studies of the identified candidate effectors will allow the mechanisms of the rose black spot interaction to be dissected.

Prediction of Signal Peptides in Proteins from Malaria Parasites

Signal peptides are N-terminal presequences responsible for targeting proteins to the endomembrane system, and subsequent subcellular or extracellular compartments, and consequently condition their proper function. The significance of signal peptides stimulates development of new computational methods for their detection. These methods employ learning systems trained on datasets comprising signal peptides from different types of proteins and taxonomic groups. As a result, the accuracy of predictions are high in the case of signal peptides that are well-represented in databases, but might be low in other, atypical cases. Such atypical signal peptides are present in proteins found in apicomplexan parasites, causative agents of malaria and toxoplasmosis. Apicomplexan proteins have a unique amino acid composition due to their AT-biased genomes. Therefore, we designed a new, more flexible and universal probabilistic model for recognition of atypical eukaryotic signal peptides. Our approach called signalHsmm includes knowledge about the structure of signal peptides and physicochemical properties of amino acids. It is able to recognize signal peptides from the malaria parasites and related species more accurately than popular programs. Moreover, it is still universal enough to provide prediction of other signal peptides on par with the best preforming predictors.

Comparative genome analyses reveal sequence features reflecting distinct modes of host-adaptation between dicot and monocot powdery mildew

BACKGROUND

Powdery mildew (PM) is one of the most important and widespread plant diseases caused by biotrophic fungi. Notably, while monocot (grass) PM fungi exhibit high-level of host-specialization, many dicot PM fungi display a broad host range. To understand such distinct modes of host-adaptation, we sequenced the genomes of four dicot PM biotypes belonging to Golovinomyces cichoracearum or Oidium neolycopersici.

RESULTS

We compared genomes of the four dicot PM together with those of Blumeria graminis f.sp. hordei (both DH14 and RACE1 isolates), B. graminis f.sp. tritici, and Erysiphe necator infectious on barley, wheat and grapevine, respectively. We found that despite having a similar gene number (6620-6961), the PM genomes vary from 120 to 222 Mb in size. This high-level of genome size variation is indicative of highly differential transposon activities in the PM genomes. While the total number of genes in any given PM genome is only about half of that in the genomes of closely related ascomycete fungi, most (~ 93%) of the ascomycete core genes (ACGs) can be found in the PM genomes. Yet, 186 ACGs were found absent in at least two of the eight PM genomes, of which 35 are missing in some dicot PM biotypes, but present in the three monocot PM genomes, indicating remarkable, independent and perhaps ongoing gene loss in different PM lineages. Consistent with this, we found that only 4192 (3819 singleton) genes are shared by all the eight PM genomes, the remaining genes are lineage- or biotype-specific. Strikingly, whereas the three monocot PM genomes possess up to 661 genes encoding candidate secreted effector proteins (CSEPs) with families containing up to 38 members, all the five dicot PM fungi have only 116-175 genes encoding CSEPs with limited gene amplification.

CONCLUSIONS

Compared to monocot (grass) PM fungi, dicot PM fungi have a much smaller effectorome. This is consistent with their contrasting modes of host-adaption: while the monocot PM fungi show a high-level of host specialization, which may reflect an advanced host-pathogen arms race, the dicot PM fungi tend to practice polyphagy, which might have lessened selective pressure for escalating an with a particular host.

Genomic insights into host adaptation between the wheat stripe rust pathogen (Puccinia striiformis f. sp. tritici) and the barley stripe rust pathogen (Puccinia striiformis f. sp. hordei)

BACKGROUND

Plant fungal pathogens can rapidly evolve and adapt to new environmental conditions in response to sudden changes of host populations in agro-ecosystems. However, the genomic basis of their host adaptation, especially at the forma specialis level, remains unclear.

RESULTS

We sequenced two isolates each representing Puccinia striiformis f. sp. tritici (Pst) and P. striiformis f. sp. hordei (Psh), different formae speciales of the stripe rust fungus P. striiformis highly adapted to wheat and barley, respectively. The divergence of Pst and Psh, estimated to start 8.12 million years ago, has been driven by high nucleotide mutation rates. The high genomic variation within dikaryotic urediniospores of P. striiformis has provided raw genetic materials for genome evolution. No specific gene families have enriched in either isolate, but extensive gene loss events have occurred in both Pst and Psh after the divergence from their most recent common ancestor. A large number of isolate-specific genes were identified, with unique genomic features compared to the conserved genes, including 1) significantly shorter in length; 2) significantly less expressed; 3) significantly closer to transposable elements; and 4) redundant in pathways. The presence of specific genes in one isolate (or forma specialis) was resulted from the loss of the homologues in the other isolate (or forma specialis) by the replacements of transposable elements or losses of genomic fragments. In addition, different patterns and numbers of telomeric repeats were observed between the isolates.

CONCLUSIONS

Host adaptation of P. striiformis at the forma specialis level is a complex pathogenic trait, involving not only virulence-related genes but also other genes. Gene loss, which might be adaptive and driven by transposable element activities, provides genomic basis for host adaptation of different formae speciales of P. striiformis.

Improved prediction of fungal effector proteins from secretomes with EffectorP 2.0

Plant-pathogenic fungi secrete effector proteins to facilitate infection. We describe extensive improvements to EffectorP, the first machine learning classifier for fungal effector prediction. EffectorP 2.0 is now trained on a larger set of effectors and utilizes a different approach based on an ensemble of classifiers trained on different subsets of negative data, offering different views on classification. EffectorP 2.0 achieves an accuracy of 89%, compared with 82% for EffectorP 1.0 and 59.8% for a small size classifier. Important features for effector prediction appear to be protein size, protein net charge as well as the amino acids serine and cysteine. EffectorP 2.0 decreases the number of predicted effectors in secretomes of fungal plant symbionts and saprophytes by 40% when compared with EffectorP 1.0. However, EffectorP 1.0 retains value, and combining EffectorP 1.0 and 2.0 results in a stringent classifier with a low false positive rate of 9%. EffectorP 2.0 predicts significant enrichments of effectors in 12 of 13 sets of infection-induced proteins from diverse fungal pathogens, whereas a small cysteine-rich classifier detects enrichment in only seven of 13. EffectorP 2.0 will fast track the prioritization of high-confidence effector candidates for functional validation and aid in improving our understanding of effector biology. EffectorP 2.0 is available at http://effectorp.csiro.au.

Evaluation of Unconventional Protein Secretion by Saccharomyces cerevisiae and other Fungi

Development of proteome analysis of extracellular proteins has revealed that a wide variety of proteins, including fungal allergens are present outside the cell. These secreted allergens often do not contain known secretion signal sequences. Recent research progress shows that some fungal allergens are secreted by unconventional secretion pathways, including autophagy- and extracellular-vesicle-dependent pathways. However, secretion pathways remain unknown for the majority of extracellular proteins. This review summarizes recent data on unconventional protein secretion in Saccharomyces cerevisiae and other fungi. Particularly, methods for evaluating unconventional protein secretion are proposed for fungal species, including S. cerevisiae, a popular model organism for investigating protein secretion pathways.

Comprehensive analysis of Verticillium nonalfalfae in silico secretome uncovers putative effector proteins expressed during hop invasion

The vascular plant pathogen Verticillium nonalfalfae causes Verticillium wilt in several important crops. VnaSSP4.2 was recently discovered as a V. nonalfalfae virulence effector protein in the xylem sap of infected hop. Here, we expanded our search for candidate secreted effector proteins (CSEPs) in the V. nonalfalfae predicted secretome using a bioinformatic pipeline built on V. nonalfalfae genome data, RNA-Seq and proteomic studies of the interaction with hop. The secretome, rich in carbohydrate active enzymes, proteases, redox proteins and proteins involved in secondary metabolism, cellular processing and signaling, includes 263 CSEPs. Several homologs of known fungal effectors (LysM, NLPs, Hce2, Cerato-platanins, Cyanovirin-N lectins, hydrophobins and CFEM domain containing proteins) and avirulence determinants in the PHI database (Avr-Pita1 and MgSM1) were found. The majority of CSEPs were non-annotated and were narrowed down to 44 top priority candidates based on their likelihood of being effectors. These were examined by spatio-temporal gene expression profiling of infected hop. Among the highest in planta expressed CSEPs, five deletion mutants were tested in pathogenicity assays. A deletion mutant of VnaUn.279, a lethal pathotype specific gene with sequence similarity to SAM-dependent methyltransferase (LaeA), had lower infectivity and showed highly reduced virulence, but no changes in morphology, fungal growth or conidiation were observed. Several putative secreted effector proteins that probably contribute to V. nonalfalfae colonization of hop were identified in this study. Among them, LaeA gene homolog was found to act as a potential novel virulence effector of V. nonalfalfae. The combined results will serve for future characterization of V. nonalfalfae effectors, which will advance our understanding of Verticillium wilt disease.

Comparative systems analysis of the secretome of the opportunistic pathogen Aspergillus fumigatus and other Aspergillus species

Aspergillus fumigatus and multiple other Aspergillus species cause a wide range of lung infections, collectively termed aspergillosis. Aspergilli are ubiquitous in environment with healthy immune systems routinely eliminating inhaled conidia, however, Aspergilli can become an opportunistic pathogen in immune-compromised patients. The aspergillosis mortality rate and emergence of drug-resistance reveals an urgent need to identify novel targets. Secreted and cell membrane proteins play a critical role in fungal-host interactions and pathogenesis. Using a computational pipeline integrating data from high-throughput experiments and bioinformatic predictions, we have identified secreted and cell membrane proteins in ten Aspergillus species known to cause aspergillosis. Small secreted and effector-like proteins similar to agents of fungal-plant pathogenesis were also identified within each secretome. A comparison with humans revealed that at least 70% of Aspergillus secretomes have no sequence similarity with the human proteome. An analysis of antigenic qualities of Aspergillus proteins revealed that the secretome is significantly more antigenic than cell membrane proteins or the complete proteome. Finally, overlaying an expression dataset, four A. fumigatus proteins upregulated during infection and with available structures, were found to be structurally similar to known drug target proteins in other organisms, and were able to dock in silico with the respective drug.

ApoplastP: prediction of effectors and plant proteins in the apoplast using machine learning

The plant apoplast is integral to intercellular signalling, transport and plant-pathogen interactions. Plant pathogens deliver effectors both into the apoplast and inside host cells, but no computational method currently exists to discriminate between these localizations. We present ApoplastP, the first method for predicting whether an effector or plant protein localizes to the apoplast. ApoplastP uncovers features of apoplastic localization common to both effectors and plant proteins, namely depletion in glutamic acid, acidic amino acids and charged amino acids and enrichment in small amino acids. ApoplastP predicts apoplastic localization in effectors with a sensitivity of 75% and a false positive rate of 5%, improving the accuracy of cysteine-rich classifiers by > 13%. ApoplastP does not depend on the presence of a signal peptide and correctly predicts the localization of unconventionally secreted proteins. The secretomes of fungal saprophytes as well as necrotrophic, hemibiotrophic and extracellular fungal pathogens are enriched for predicted apoplastic proteins. Rust pathogens have low proportions of predicted apoplastic proteins, but these are highly enriched for predicted effectors. ApoplastP pioneers apoplastic localization prediction using machine learning. It will facilitate functional studies and will be valuable for predicting if an effector localizes to the apoplast or if it enters plant cells.

De Novo Assembly and Phasing of Dikaryotic Genomes from Two Isolates of Puccinia coronata f. sp. avenae, the Causal Agent of Oat Crown Rust

Oat crown rust, caused by the fungus Pucinnia coronata f. sp. avenae, is a devastating disease that impacts worldwide oat production. For much of its life cycle, P. coronata f. sp. avenae is dikaryotic, with two separate haploid nuclei that may vary in virulence genotype, highlighting the importance of understanding haplotype diversity in this species. We generated highly contiguous de novo genome assemblies of two P. coronata f. sp. avenae isolates, 12SD80 and 12NC29, from long-read sequences. In total, we assembled 603 primary contigs for 12SD80, for a total assembly length of 99.16 Mbp, and 777 primary contigs for 12NC29, for a total length of 105.25 Mbp; approximately 52% of each genome was assembled into alternate haplotypes. This revealed structural variation between haplotypes in each isolate equivalent to more than 2% of the genome size, in addition to about 260,000 and 380,000 heterozygous single-nucleotide polymorphisms in 12SD80 and 12NC29, respectively. Transcript-based annotation identified 26,796 and 28,801 coding sequences for isolates 12SD80 and 12NC29, respectively, including about 7,000 allele pairs in haplotype-phased regions. Furthermore, expression profiling revealed clusters of coexpressed secreted effector candidates, and the majority of orthologous effectors between isolates showed conservation of expression patterns. However, a small subset of orthologs showed divergence in expression, which may contribute to differences in virulence between 12SD80 and 12NC29. This study provides the first haplotype-phased reference genome for a dikaryotic rust fungus as a foundation for future studies into virulence mechanisms in P. coronata f. sp. avenaeIMPORTANCE Disease management strategies for oat crown rust are challenged by the rapid evolution of Puccinia coronata f. sp. avenae, which renders resistance genes in oat varieties ineffective. Despite the economic importance of understanding P. coronata f. sp. avenae, resources to study the molecular mechanisms underpinning pathogenicity and the emergence of new virulence traits are lacking. Such limitations are partly due to the obligate biotrophic lifestyle of P. coronata f. sp. avenae as well as the dikaryotic nature of the genome, features that are also shared with other important rust pathogens. This study reports the first release of a haplotype-phased genome assembly for a dikaryotic fungal species and demonstrates the amenability of using emerging technologies to investigate genetic diversity in populations of P. coronata f. sp. avenae.

Genomic, Network, and Phylogenetic Analysis of the Oomycete Effector Arsenal

The oomycetes are a class of microscopic, filamentous eukaryotes and include ecologically significant animal and plant pathogens. Oomycetes secrete large arsenals of effector proteins that degrade host cell components, manipulate host immune responses, and induce necrosis, enabling parasitic colonization. In this study, we catalogued the number and evolution of effectors in 37 oomycete species whose genomes have been completely sequenced. Large expansions of effector protein families in Phytophthora species, including glycoside hydrolases, pectinases, and necrosis-inducing proteins, were observed. Species-specific expansions were detected, including chitinases in Aphanomyces astaci and Pythium oligandrum. Novel effectors which may be involved in suppressing animal immune responses were identified in Ap. astaci and Py. oligandrum. Type 2 necrosis-inducing proteins with an unusual phylogenetic history were also located. This work represents an up-to-date in silico catalogue of the effector arsenal of the oomycetes based on the 37 genomes currently available.

The oomycetes are a class of microscopic, filamentous eukaryotes within the stramenopiles-alveolate-Rhizaria (SAR) supergroup and include ecologically significant animal and plant pathogens. Oomycetes secrete large arsenals of effector proteins that degrade host cell components, manipulate host immune responses, and induce necrosis, enabling parasitic colonization. This study investigated the expansion and evolution of effectors in 37 oomycete species in 4 oomycete orders, including Albuginales, Peronosporales, Pythiales, and Saprolegniales species. Our results highlight the large expansions of effector protein families, including glycoside hydrolases, pectinases, and necrosis-inducing proteins, in Phytophthora species. Species-specific expansions, including expansions of chitinases in Aphanomyces astaci and Pythium oligandrum, were detected. Novel effectors which may be involved in suppressing animal immune responses in Ap. astaci and Py. insidiosum were also identified. Type 2 necrosis-inducing proteins with an unusual phylogenetic history were also located in a number of oomycete species. We also investigated the "RxLR" effector complement of all 37 species and, as expected, observed large expansions in Phytophthora species numbers. Our results provide in-depth sequence information on all putative RxLR effectors from all 37 species. This work represents an up-to-date in silico catalogue of the effector arsenal of the oomycetes based on the 37 genomes currently available.

IMPORTANCE The oomycetes are a class of microscopic, filamentous eukaryotes and include ecologically significant animal and plant pathogens. Oomycetes secrete large arsenals of effector proteins that degrade host cell components, manipulate host immune responses, and induce necrosis, enabling parasitic colonization. In this study, we catalogued the number and evolution of effectors in 37 oomycete species whose genomes have been completely sequenced. Large expansions of effector protein families in Phytophthora species, including glycoside hydrolases, pectinases, and necrosis-inducing proteins, were observed. Species-specific expansions were detected, including chitinases in Aphanomyces astaci and Pythium oligandrum. Novel effectors which may be involved in suppressing animal immune responses were identified in Ap. astaci and Py. oligandrum. Type 2 necrosis-inducing proteins with an unusual phylogenetic history were also located. This work represents an up-to-date in silico catalogue of the effector arsenal of the oomycetes based on the 37 genomes currently available.

Comparative secretome analysis of Rhizoctonia solani isolates with different host ranges reveals unique secretomes and cell death inducing effectors

Rhizoctonia solani is a fungal pathogen causing substantial damage to many of the worlds’ largest food crops including wheat, rice, maize and soybean. Despite impacting global food security, little is known about the pathogenicity mechanisms employed by R. solani. To enable prediction of effectors possessing either broad efficacy or host specificity, a combined secretome was constructed from a monocot specific isolate, a dicot specific isolate and broad host range isolate infecting both monocot and dicot hosts. Secretome analysis suggested R. solani employs largely different virulence mechanisms to well-studied pathogens, despite in many instances infecting the same host plants. Furthermore, the secretome of the broad host range AG8 isolate may be shaped by maintaining functions for saprophytic life stages while minimising opportunities for host plant recognition. Analysis of possible co-evolution with host plants and in-planta up-regulation in particular, aided identification of effectors including xylanase and inhibitor I9 domain containing proteins able to induce cell death in-planta. The inhibitor I9 domain was more abundant in the secretomes of a wide range of necrotising fungi relative to biotrophs. These findings provide novel targets for further dissection of the virulence mechanisms and potential avenues to control this under-characterised but important pathogen.

Time-resolved dual transcriptomics reveal early induced Nicotiana benthamiana root genes and conserved infection-promoting Phytophthora palmivora effectors

BACKGROUND

Plant-pathogenic oomycetes are responsible for economically important losses in crops worldwide. Phytophthora palmivora, a tropical relative of the potato late blight pathogen, causes rotting diseases in many tropical crops including papaya, cocoa, oil palm, black pepper, rubber, coconut, durian, mango, cassava and citrus. Transcriptomics have helped to identify repertoires of host-translocated microbial effector proteins which counteract defenses and reprogram the host in support of infection. As such, these studies have helped in understanding how pathogens cause diseases. Despite the importance of P. palmivora diseases, genetic resources to allow for disease resistance breeding and identification of microbial effectors are scarce.

RESULTS

We employed the model plant Nicotiana benthamiana to study the P. palmivora root infections at the cellular and molecular levels. Time-resolved dual transcriptomics revealed different pathogen and host transcriptome dynamics. De novo assembly of P. palmivora transcriptome and semi-automated prediction and annotation of the secretome enabled robust identification of conserved infection-promoting effectors. We show that one of them, REX3, suppresses plant secretion processes. In a survey for early transcriptionally activated plant genes we identified a N. benthamiana gene specifically induced at infected root tips that encodes a peptide with danger-associated molecular features.

CONCLUSIONS

These results constitute a major advance in our understanding of P. palmivora diseases and establish extensive resources for P. palmivora pathogenomics, effector-aided resistance breeding and the generation of induced resistance to Phytophthora root infections. Furthermore, our approach to find infection-relevant secreted genes is transferable to other pathogen-host interactions and not restricted to plants.

LOCALIZER: subcellular localization prediction of both plant and effector proteins in the plant cell

Pathogens secrete effector proteins and many operate inside plant cells to enable infection. Some effectors have been found to enter subcellular compartments by mimicking host targeting sequences. Although many computational methods exist to predict plant protein subcellular localization, they perform poorly for effectors. We introduce LOCALIZER for predicting plant and effector protein localization to chloroplasts, mitochondria, and nuclei. LOCALIZER shows greater prediction accuracy for chloroplast and mitochondrial targeting compared to other methods for 652 plant proteins. For 107 eukaryotic effectors, LOCALIZER outperforms other methods and predicts a previously unrecognized chloroplast transit peptide for the ToxA effector, which we show translocates into tobacco chloroplasts. Secretome-wide predictions and confocal microscopy reveal that rust fungi might have evolved multiple effectors that target chloroplasts or nuclei. LOCALIZER is the first method for predicting effector localisation in plants and is a valuable tool for prioritizing effector candidates for functional investigations. LOCALIZER is available at http://localizer.csiro.au/.

Computational Methods for Predicting Effectors in Rust Pathogens

Lower costs and improved sequencing technologies have led to a large number of high-quality rust pathogen genomes and deeper characterization of gene expression profiles during early and late infection stages. However, the set of secreted proteins expressed during infection is too large for experimental investigations and contains not only effectors but also proteins that play a role in niche colonization or in fighting off competing microbes. Therefore, accurate computational prediction is essential for identifying high-priority rust effector candidates from secretomes.