EffectorP: predicting fungal effector proteins from secretomes using machine learning

Decoding the Arsenal: Protist Effectors and Their Impact on Photosynthetic Hosts

Interactions between various microbial pathogens including viruses, bacteria, fungi, oomycetes, and their plant hosts have traditionally been the focus of phytopathology. In recent years, a significant and growing interest in the study of eukaryotic microorganisms not classified among fungi or oomycetes has emerged. Many of these protists establish complex interactions with photosynthetic hosts, and understanding these interactions is crucial in understanding the dynamics of these parasites within traditional and emerging types of farming, including marine aquaculture. Many phytopathogenic protists are biotrophs with complex polyphasic life cycles, which makes them difficult or impossible to culture, a fact reflected in a wide gap in the availability of comprehensive genomic data when compared to fungal and oomycete plant pathogens. Furthermore, our ability to use available genomic resources for these protists is limited by the broad taxonomic distance that these organisms span, which makes comparisons with other genomic datasets difficult. The current rapid progress in genomics and computational tools for the prediction of protein functions and interactions is revolutionizing the landscape in plant pathology. This is also opening novel possibilities, specifically for a deeper understanding of protist effectors. Tools like AlphaFold2 enable structure-based function prediction of effector candidates with divergent protein sequences. In turn, this allows us to ask better biological questions and, coupled with innovative experimental strategies, will lead into a new era of effector research, especially for protists, to expand our knowledge on these elusive pathogens and their interactions with photosynthetic hosts. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

The massive 340 megabase genome of Anisogramma anomala, a biotrophic ascomycete that causes eastern filbert blight of hazelnut

BACKGROUND

The ascomycete fungus Anisogramma anomala causes Eastern Filbert Blight (EFB) on hazelnut (Corylus spp.) trees. It is a minor disease on its native host, the American hazelnut (C. americana), but is highly destructive on the commercially important European hazelnut (C. avellana). In North America, EFB has historically limited commercial production of hazelnut to west of the Rocky Mountains. A. anomala is an obligately biotrophic fungus that has not been grown in continuous culture, rendering its study challenging. There is a 15-month latency before symptoms appear on infected hazelnut trees, and only a sexual reproductive stage has been observed. Here we report the sequencing, annotation, and characterization of its genome.

RESULTS

The genome of A. anomala was assembled into 108 scaffolds totaling 342,498,352 nt with a GC content of 34.46%. Scaffold N50 was 33.3 Mb and L50 was 5. Nineteen scaffolds with lengths over 1 Mb constituted 99% of the assembly. Telomere sequences were identified on both ends of two scaffolds and on one end of another 10 scaffolds. Flow cytometry estimated the genome size of A. anomala at 370 Mb. The genome exhibits two-speed evolution, with 93% of the assembly as AT-rich regions (32.9% GC) and the other 7% as GC-rich (57.1% GC). The AT-rich regions consist predominantly of repeats with low gene content, while 90% of predicted protein coding genes were identified in GC-rich regions. Copia-like retrotransposons accounted for more than half of the genome. Evidence of repeat-induced point mutation (RIP) was identified throughout the AT-rich regions, and two copies of the rid gene and one of dim-2, the key genes in the RIP mutation pathway, were identified in the genome. Consistent with its homothallic sexual reproduction cycle, both MAT1-1 and MAT1-2 idiomorphs were found. We identified a large suite of genes likely involved in pathogenicity, including 614 carbohydrate active enzymes, 762 secreted proteins and 165 effectors.

CONCLUSIONS

This study reveals the genomic structure, composition, and putative gene function of the important pathogen A. anomala. It provides insight into the molecular basis of the pathogen's life cycle and a solid foundation for studying EFB.

Template-Based Modelling of the Structure of Fungal Effector Proteins

The discovery of new fungal effector proteins is necessary to enable the screening of cultivars for disease resistance. Sequence-based bioinformatics methods have been used for this purpose, but only a limited number of functional effector proteins have been successfully predicted and subsequently validated experimentally. A significant obstacle is that many fungal effector proteins discovered so far lack sequence similarity or conserved sequence motifs. The availability of experimentally determined three-dimensional (3D) structures of a number of effector proteins has recently highlighted structural similarities amongst groups of sequence-dissimilar fungal effectors, enabling the search for similar structural folds amongst effector sequence candidates. We have applied template-based modelling to predict the 3D structures of candidate effector sequences obtained from bioinformatics predictions and the PHI-BASE database. Structural matches were found not only with ToxA- and MAX-like effector candidates but also with non-fungal effector-like proteins-including plant defensins and animal venoms-suggesting the broad conservation of ancestral structural folds amongst cytotoxic peptides from a diverse range of distant species. Accurate modelling of fungal effectors were achieved using RaptorX. The utility of predicted structures of effector proteins lies in the prediction of their interactions with plant receptors through molecular docking, which will improve the understanding of effector-plant interactions.

Characterization of Microbotryum lychnidis-dioicae Secreted Effector Proteins, Their Potential Host Targets, and Localization in a Heterologous Host Plant

Microbotryum lychnidis-dioicae is an obligate fungal species colonizing the plant host, Silene latifolia. The fungus synthesizes and secretes effector proteins into the plant host during infection to manipulate the host for completion of the fungal lifecycle. The goal of this study was to continue functional characterization of such M. lychnidis-dioicae effectors. Here, we identified three putative effectors and their putative host-plant target proteins. MVLG_02245 is highly upregulated in M. lychnidis-dioicae during infection; yeast two-hybrid analysis suggests it targets a tubulin α-1 chain protein ortholog in the host, Silene latifolia. A potential plant protein interacting with MVLG_06175 was identified as CASP-like protein 2C1 (CASPL2C1), which facilitates the polymerization of the Casparian strip at the endodermal cells. Proteins interacting with MVLG_05122 were identified as CSN5a or 5b, involved in protein turnover. Fluorescently labelled MVLG_06175 and MVLG_05122 were expressed in the heterologous plant, Arabidopsis thaliana. MVLG_06175 formed clustered granules at the tips of trichomes on leaves and in root caps, while MVLG_05122 formed a band structure at the base of leaf trichomes. Plants expressing MVLG_05122 alone were more resistant to infection with Fusarium oxysporum. These results indicate that the fungus might affect the formation of the Casparian strip in the roots and the development of trichomes during infection as well as alter plant innate immunity.

A review of artificial intelligence-assisted omics techniques in plant defense: current trends and future directions

Plants intricately deploy defense systems to counter diverse biotic and abiotic stresses. Omics technologies, spanning genomics, transcriptomics, proteomics, and metabolomics, have revolutionized the exploration of plant defense mechanisms, unraveling molecular intricacies in response to various stressors. However, the complexity and scale of omics data necessitate sophisticated analytical tools for meaningful insights. This review delves into the application of artificial intelligence algorithms, particularly machine learning and deep learning, as promising approaches for deciphering complex omics data in plant defense research. The overview encompasses key omics techniques and addresses the challenges and limitations inherent in current AI-assisted omics approaches. Moreover, it contemplates potential future directions in this dynamic field. In summary, AI-assisted omics techniques present a robust toolkit, enabling a profound understanding of the molecular foundations of plant defense and paving the way for more effective crop protection strategies amidst climate change and emerging diseases.

Unraveling plant-microbe interactions: can integrated omics approaches offer concrete answers?

Advances in high throughput omics techniques provide avenues to decipher plant microbiomes. However, there is limited information on how integrated informatics can help provide deeper insights into plant-microbe interactions in a concerted way. Integrating multi-omics datasets can transform our understanding of the plant microbiome from unspecified genetic influences on interacting species to specific gene-by-gene interactions. Here, we highlight recent progress and emerging strategies in crop microbiome omics research and review key aspects of how the integration of host and microbial omics-based datasets can be used to provide a comprehensive outline of complex crop-microbe interactions. We describe how these technological advances have helped unravel crucial plant and microbial genes and pathways that control beneficial, pathogenic, and commensal plant-microbe interactions. We identify crucial knowledge gaps and synthesize current limitations in our understanding of crop microbiome omics approaches. We highlight recent studies in which multi-omics-based approaches have led to improved models of crop microbial community structure and function. Finally, we recommend holistic approaches in integrating host and microbial omics datasets to achieve precision and efficiency in data analysis, which is crucial for biotic and abiotic stress control and in understanding the contribution of the microbiota in shaping plant fitness.

Analysis of five near-complete genome assemblies of the tomato pathogen Cladosporium fulvum uncovers additional accessory chromosomes and structural variations induced by transposable elements effecting the loss of avirulence genes

BACKGROUND

Fungal plant pathogens have dynamic genomes that allow them to rapidly adapt to adverse conditions and overcome host resistance. One way by which this dynamic genome plasticity is expressed is through effector gene loss, which enables plant pathogens to overcome recognition by cognate resistance genes in the host. However, the exact nature of these loses remains elusive in many fungi. This includes the tomato pathogen Cladosporium fulvum, which is the first fungal plant pathogen from which avirulence (Avr) genes were ever cloned and in which loss of Avr genes is often reported as a means of overcoming recognition by cognate tomato Cf resistance genes. A recent near-complete reference genome assembly of C. fulvum isolate Race 5 revealed a compartmentalized genome architecture and the presence of an accessory chromosome, thereby creating a basis for studying genome plasticity in fungal plant pathogens and its impact on avirulence genes.

RESULTS

Here, we obtained near-complete genome assemblies of four additional C. fulvum isolates. The genome assemblies had similar sizes (66.96 to 67.78 Mb), number of predicted genes (14,895 to 14,981), and estimated completeness (98.8 to 98.9%). Comparative analysis that included the genome of isolate Race 5 revealed high levels of synteny and colinearity, which extended to the density and distribution of repetitive elements and of repeat-induced point (RIP) mutations across homologous chromosomes. Nonetheless, structural variations, likely mediated by transposable elements and effecting the deletion of the avirulence genes Avr4E, Avr5, and Avr9, were also identified. The isolates further shared a core set of 13 chromosomes, but two accessory chromosomes were identified as well. Accessory chromosomes were significantly smaller in size, and one carried pseudogenized copies of two effector genes. Whole-genome alignments further revealed genomic islands of near-zero nucleotide diversity interspersed with islands of high nucleotide diversity that co-localized with repeat-rich regions. These regions were likely generated by RIP, which generally asymmetrically affected the genome of C. fulvum.

CONCLUSIONS

Our results reveal new evolutionary aspects of the C. fulvum genome and provide new insights on the importance of genomic structural variations in overcoming host resistance in fungal plant pathogens.

POOE: predicting oomycete effectors based on a pre-trained large protein language model

Oomycetes are fungus-like eukaryotic microorganisms which can cause catastrophic diseases in many plants. Successful infection of oomycetes depends highly on their effector proteins that are secreted into plant cells to subvert plant immunity. Thus, systematic identification of effectors from the oomycete proteomes remains an initial but crucial step in understanding plant-pathogen relationships. However, the number of experimentally identified oomycete effectors is still limited. Currently, only a few bioinformatics predictors exist to detect potential effectors, and their prediction performance needs to be improved. Here, we used the sequence embeddings from a pre-trained large protein language model (ProtTrans) as input and developed a support vector machine-based method called POOE for predicting oomycete effectors. POOE could achieve a highly accurate performance with an area under the precision-recall curve of 0.804 (area under the receiver operating characteristic curve = 0.893, accuracy = 0.874, precision = 0.777, recall = 0.684, and specificity = 0.936) in the fivefold cross-validation, considerably outperforming various combinations of popular machine learning algorithms and other commonly used sequence encoding schemes. A similar prediction performance was also observed in the independent test. Compared with the existing oomycete effector prediction methods, POOE provided very competitive and promising performance, suggesting that ProtTrans effectively captures rich protein semantic information and dramatically improves the prediction task. We anticipate that POOE can accelerate the identification of oomycete effectors and provide new hints to systematically understand the functional roles of effectors in plant-pathogen interactions. The web server of POOE is freely accessible at http://zzdlab.com/pooe/index.php. The corresponding source codes and data sets are also available at https://github.com/zzdlabzm/POOE.IMPORTANCEIn this work, we use the sequence representations from a pre-trained large protein language model (ProtTrans) as input and develop a Support Vector Machine-based method called POOE for predicting oomycete effectors. POOE could achieve a highly accurate performance in the independent test set, considerably outperforming existing oomycete effector prediction methods. We expect that this new bioinformatics tool will accelerate the identification of oomycete effectors and further guide the experimental efforts to interrogate the functional roles of effectors in plant-pathogen interaction.

Genome-Wide Identification and Characterization of Effector Candidates with Conserved Motif in Falciphora oryzae

Microbes employ effectors to disrupt immune responses and promote host colonization. Conserved motifs including RXLR, LFLAK-HVLVxxP (CRN), Y/F/WxC, CFEM, LysM, Chitin-bind, DPBB_1 (PNPi), and Cutinase have been discovered to play crucial roles in the functioning of effectors in filamentous fungi. Nevertheless, little is known about effectors with conserved motifs in endophytes. This research aims to discover the effector genes with conserved motifs in the genome of rice endophyte Falciphora oryzae. SignalP identified a total of 622 secreted proteins, out of which 227 were predicted as effector candidates by EffectorP. By utilizing HMM features, we discovered a total of 169 effector candidates with conserved motifs and three novel motifs. Effector candidates containing LysM, CFEM, DPBB_1, Cutinase, and Chitin_bind domains were conserved across species. In the transient expression assay, it was observed that one CFEM and one LysM activated cell death in tobacco leaves. Moreover, two CFEM and one Chitin_bind inhibited cell death induced by Bax protein. At various points during the infection, the genes' expression levels were increased. These results will help to identify functional effector proteins involving omics methods using new bioinformatics tools, thus providing a basis for the study of symbiosis mechanisms.

The genomes of Scedosporium between environmental challenges and opportunism

Emerging fungal pathogens are a global challenge for humankind. Many efforts have been made to understand the mechanisms underlying pathogenicity in bacteria, and OMICs techniques are largely responsible for those advancements. By contrast, our limited understanding of opportunism and antifungal resistance is preventing us from identifying, limiting and interpreting the emergence of fungal pathogens. The genus Scedosporium (Microascaceae) includes fungi with high tolerance to environmental pollution, whilst some species can be considered major human pathogens, such as Scedosporium apiospermum and Scedosporium boydii. However, unlike other fungal pathogens, little is known about the genome evolution of these organisms. We sequenced two novel genomes of Scedosporium aurantiacum and Scedosporium minutisporum isolated from extreme, strongly anthropized environments. We compared all the available Scedosporium and Microascaceae genomes, that we systematically annotated and characterized ex novo in most cases. The genomes in this family were integrated in a Phylum-level comparison to infer the presence of putative, shared genomic traits in filamentous ascomycetes with pathogenic potential. The analysis included the genomes of 100 environmental and clinical fungi, revealing poor evolutionary convergence of putative pathogenicity traits. By contrast, several features in Microascaceae and Scedosporium were detected that might have a dual role in responding to environmental challenges and allowing colonization of the human body, including chitin, melanin and other cell wall related genes, proteases, glutaredoxins and magnesium transporters. We found these gene families to be impacted by expansions, orthologous transposon insertions, and point mutations. With RNA-seq, we demonstrated that most of these anciently impacted genomic features responded to the stress imposed by an antifungal compound (voriconazole) in the two environmental strains S. aurantiacum MUT6114 and S. minutisporum MUT6113. Therefore, the present genomics and transcriptomics investigation stands on the edge between stress resistance and pathogenic potential, to elucidate whether fungi were pre-adapted to infect humans. We highlight the strengths and limitations of genomics applied to opportunistic human pathogens, the multifactoriality of pathogenicity and resistance to drugs, and suggest a scenario where pressures other than anthropic contributed to forge filamentous human pathogens.

A chromosome-scale genome assembly of the grape powdery mildew pathogen Erysiphe necator reveals its genomic architecture and previously unknown features of its biology

Erysiphe necator is an obligate fungal pathogen that causes grape powdery mildew, globally the most important disease on grapevines. Previous attempts to obtain a quality genome assembly for this pathogen were hindered by its high repetitive DNA content. Here, chromatin conformation capture (Hi-C) with long-read PacBio sequencing was combined to obtain a chromosome-scale assembly and a high-quality annotation for E. necator isolate EnFRAME01. The resulting 81.1 Mb genome assembly is 98% complete and consists of 34 scaffolds, 11 of which represent complete chromosomes. All chromosomes contain large centromeric-like regions and lack synteny to the 11 chromosomes of the cereal PM pathogen Blumeria graminis. Further analysis of their composition showed that repeats and transposable elements (TEs) occupy 62.7% of their content. TEs were almost evenly interspersed outside centromeric and telomeric regions and massively overlapped with regions of annotated genes, suggesting that they could have a significant functional impact. Abundant gene duplicates were observed as well, particularly in genes encoding candidate secreted effector proteins. Moreover, younger in age gene duplicates exhibited more relaxed selection pressure and were more likely to be located physically close in the genome than older duplicates. A total of 122 genes with copy number variations among six isolates of E. necator were also identified and were enriched in genes that were duplicated in EnFRAME01, indicating they may reflect an adaptive variation. Taken together, our study illuminates higher-order genomic architectural features of E. necator and provides a valuable resource for studying genomic structural variations in this pathogen. IMPORTANCE Grape powdery mildew caused by the ascomycete fungus Erysiphe necator is economically the most important and recurrent disease in vineyards across the world. The obligate biotrophic nature of E. necator hinders the use of typical genetic methods to elucidate its pathogenicity and adaptation to adverse conditions, and thus comparative genomics has been a major method to study its genome biology. However, the current reference genome of E. necator isolate C-strain is highly fragmented with many non-coding regions left unassembled. This incompleteness prohibits in-depth comparative genomic analyses and the study of genomic structural variations (SVs) that are known to affect several aspects of microbial life, including fitness, virulence, and host adaptation. By obtaining a chromosome-scale genome assembly and a high-quality gene annotation for E. necator, we reveal the organization of its chromosomal content, unearth previously unknown features of its biology, and provide a reference for studying genomic SVs in this pathogen.

Crop-saving with AI: latest trends in deep learning techniques for plant pathology

Plant diseases pose a major threat to agricultural production and the food supply chain, as they expose plants to potentially disruptive pathogens that can affect the lives of those who are associated with it. Deep learning has been applied in a range of fields such as object detection, autonomous vehicles, fraud detection etc. Several researchers have tried to implement deep learning techniques in precision agriculture. However, there are pros and cons to the approaches they have opted for disease detection and identification. In this survey, we have made an attempt to capture the significant advancements in machine-learning based disease detection. We have discussed prevalent datasets and techniques that have been employed as well as highlighted emerging approaches being used for plant disease detection. By exploring these advancements, we aim to present a comprehensive overview of the prominent approaches in precision agriculture, along with their associated challenges and potential improvements. This paper delves into the challenges associated with the implementation and briefly discusses the future trends. Overall, this paper presents a bird's eye view of plant disease datasets, deep learning techniques, their accuracies and the challenges associated with them. Our insights will serve as a valuable resource for researchers and practitioners in the field. We hope that this survey will inform and inspire future research efforts, ultimately leading to improved precision agriculture practices and enhanced crop health management.

EffectorO: Motif-Independent Prediction of Effectors in Oomycete Genomes Using Machine Learning and Lineage Specificity

Oomycete plant pathogens cause a wide variety of diseases, including late blight of potato, sudden oak death, and downy mildews of plants. These pathogens are major contributors to loss in numerous food crops. Oomycetes secrete effector proteins to manipulate their hosts to the advantage of the pathogen. Plants have evolved to recognize effectors, resulting in an evolutionary cycle of defense and counter-defense in plant-microbe interactions. This selective pressure results in highly diverse effector sequences that can be difficult to computationally identify using only sequence similarity. We developed a novel effector prediction tool, EffectorO, that uses two complementary approaches to predict effectors in oomycete pathogen genomes: i) a machine learning-based pipeline that predicts effector probability based on the biochemical properties of the N-terminal amino-acid sequence of a protein and ii) a pipeline based on lineage specificity to find proteins that are unique to one species or genus, a sign of evolutionary divergence due to adaptation to the host. We tested EffectorO on Bremia lactucae, which causes lettuce downy mildew, and Phytophthora infestans, which causes late blight of potato and tomato, and predicted many novel effector candidates while recovering the majority of known effector candidates. EffectorO will be useful for discovering novel families of oomycete effectors without relying on sequence similarity to known effectors. [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.

The Phantom Menace: latest findings on effector biology in the rice blast fungus

Magnaporthe oryzae is a hemibiotrophic fungus responsible for the economically devastating and recalcitrant rice blast disease. However, the blast fungus is not only restricted to rice plants as it can also infect wheat, millet, and other crops. Despite previous outstanding discoveries aimed to understand and control the disease, the fungus remains one of the most important pathogens that threatens global food security. To cause disease, M. oryzae initiates morphological changes to attach, penetrate, and colonize rice cells, all while suppressing plant immune defenses that would otherwise hinder its proliferation. As such, M. oryzae actively secretes a battery of small proteins called "effectors" to manipulate host machinery. In this review, we summarize the latest findings in effector identification, expression, regulation, and functionality. We review the most studied effectors and their roles in pathogenesis. Additionally, we discern the current methodologies to structurally catalog effectors, and we highlight the importance of climate change and its impact on the future of rice blast disease.

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.

Comparative proteome analysis identifies species-specific signature proteins in Aspergillus pathogens

Aspergillus flavus and Aspergillus fumigatus are important human pathogens that can infect the lung and cornea. During infection, Aspergillus dormant conidia are the primary morphotype that comes in contact with the host. As the conidial surface-associated proteins (CSPs) and the extracellular proteins during the early stages of growth play a crucial role in establishing infection, we profiled and compared these proteins between a clinical strain of A. flavus and a clinical strain of A. fumigatus. We identified nearly 100 CSPs in both Aspergillus, and these non-covalently associated surface proteins were able to stimulate the neutrophils to secrete interleukin IL-8. Mass spectrometry analysis identified more than 200 proteins in the extracellular space during the early stages of conidial growth and germination (early exoproteome). The conidial surface proteins and the early exoproteome of A. fumigatus were enriched with immunoreactive proteins and those with pathogenicity-related functions while that of the A. flavus were primarily enzymes involved in cell wall reorganization and binding. Comparative proteome analysis of the CSPs and the early exoproteome between A. flavus and A. fumigatus enabled the identification of a common core proteome and potential species-specific signature proteins. Transcript analysis of selected proteins indicate that the transcript-protein level correlation does not exist for all proteins and might depend on factors such as membrane-anchor signals and protein half-life. The probable signature proteins of A. flavus and A. fumigatus identified in this study can serve as potential candidates for developing species-specific diagnostic tests. KEY POINTS: • CSPs and exoproteins could differentiate A. flavus and A. fumigatus. • A. fumigatus conidial surface harbored more antigenic proteins than A. flavus. • Identified species-specific signature proteins of A. flavus and A. fumigatus.

Natural variation in Avr3D1 from Zymoseptoria sp. contributes to quantitative gene-for-gene resistance and to host specificity

Successful host colonization by plant pathogens requires the circumvention of host defense responses, frequently through sequence modifications in secreted pathogen proteins known as avirulence factors (Avrs). Although Avr sequences are often polymorphic, the contribution of these polymorphisms to virulence diversity in natural pathogen populations remains largely unexplored. We used molecular genetic tools to determine how natural sequence polymorphisms of the avirulence factor Avr3D1 in the wheat pathogen Zymoseptoria tritici contributed to adaptive changes in virulence. We showed that there is a continuous distribution in the magnitude of resistance triggered by different Avr3D1 isoforms and demonstrated that natural variation in an Avr gene can lead to a quantitative resistance phenotype. We further showed that homologues of Avr3D1 in two nonpathogenic sister species of Z. tritici are recognized by some wheat cultivars, suggesting that Avr-R gene-for-gene interactions can contribute to nonhost resistance. We suggest that the mechanisms underlying host range, qualitative resistance, and quantitative resistance are not exclusive.

A Novel Effector FlSp1 Inhibits the Colonization of Endophytic Fusarium lateritium and Increases the Resistance to Ralstonia solanacearum in Tobacco

Effectors are crucial for the interaction between endophytes and their host plants. However, limited attention has been paid to endophyte effectors, with only a few reports published. This work focuses on an effector of Fusarium lateritium, namely FlSp1 (Fusarium-lateritium-Secreted-Protein), a typical unknown secreted protein. The transcription of FlSp1 was up-regulated after 48 h following fungal inoculation in the host plant, i.e., tobacco. The inactivation of FlSp1 with the inhibition rate decreasing by 18% (p < 0.01) resulted in a remarkable increase in the tolerance of F. lateritium to oxidative stress. The transient expression of FlSp1 stimulated the accumulation of reactive oxygen species (ROS) without causing plant necrosis. In comparison with the wild type of F. lateritium (WT), the FlSp1 mutant of the F. lateritium plant (ΔFlSp1) reduced the ROS accumulation and weakened the plant immune response, which resulted in significantly higher colonization in the host plants. Meanwhile, the resistance of the ΔFlSp1 plant to the pathogenic Ralstonia solanacearum, which causes bacterial wilt, was increased. These results suggest that the novel secreted protein FlSp1 might act as an immune-triggering effector to limit fungal proliferation by stimulating the plant immune system through ROS accumulation and thus balance the interaction between the endophytic fungi and their host plants.

Extracellular Vesicles of the Plant Pathogen Botrytis cinerea

Fungal secretomes are known to contain a multitude of components involved in nutrition, cell growth or biotic interactions. Recently, extra-cellular vesicles have been identified in a few fungal species. Here, we used a multidisciplinary approach to identify and characterize extracellular vesicles produced by the plant necrotroph Botrytis cinerea. Transmission electron microscopy of infectious hyphae and hyphae grown in vitro revealed extracellular vesicles of various sizes and densities. Electron tomography showed the co-existence of ovoid and tubular vesicles and pointed to their release via the fusion of multi-vesicular bodies with the cell plasma membrane. The isolation of these vesicles and exploration of their protein content using mass spectrometry led to the identification of soluble and membrane proteins involved in transport, metabolism, cell wall synthesis and remodeling, proteostasis, oxidoreduction and traffic. Confocal microscopy highlighted the capacity of fluorescently labeled vesicles to target cells of B. cinerea, cells of the fungus Fusarium graminearum, and onion epidermal cells but not yeast cells. In addition, a specific positive effect of these vesicles on the growth of B. cinerea was quantified. Altogether, this study broadens our view on the secretion capacity of B. cinerea and its cell-to-cell communication.

A Complete Genome Sequence of Podosphaera xanthii Isolate YZU573, the Causal Agent of Powdery Mildew Isolated from Cucumber in China

Podosphaera xanthii is a well-known obligate biotrophic pathogen that causes powdery mildew (PM) disease on cucurbitaceous plants and is one of the most important limiting factors for cucumber production worldwide. To better understand the avirulence effector proteins in this species that are known to be involved in host-pathogen interaction, the draft genome assembly of P. xanthii isolate YZU573 from cucumber leaves with symptoms of PM was obtained with a hybrid approach, combining nanopore long-read and llumina paired-end sequencing. The final P. xanthii YZU573 genome assembly of 152.7 Mb consists of 58 contigs, with an N50 value of 0.75 Mb and 6491 predicted protein-coding genes. The effector analysis using the whole-genome sequence information revealed a total of 87 putative effector candidates, and 65 of them had their analogs, whereas the remaining 22 were novel ones. The new P. xanthii genome provides valuable resources to better understand plant-microbe interaction in cucumber PM disease.

Major proliferation of transposable elements shaped the genome of the soybean rust pathogen Phakopsora pachyrhizi

With >7000 species the order of rust fungi has a disproportionately large impact on agriculture, horticulture, forestry and foreign ecosystems. The infectious spores are typically dikaryotic, a feature unique to fungi in which two haploid nuclei reside in the same cell. A key example is Phakopsora pachyrhizi, the causal agent of Asian soybean rust disease, one of the world's most economically damaging agricultural diseases. Despite P. pachyrhizi's impact, the exceptional size and complexity of its genome prevented generation of an accurate genome assembly. Here, we sequence three independent P. pachyrhizi genomes and uncover a genome up to 1.25 Gb comprising two haplotypes with a transposable element (TE) content of ~93%. We study the incursion and dominant impact of these TEs on the genome and show how they have a key impact on various processes such as host range adaptation, stress responses and genetic plasticity.

Insights on Novel Effectors and Characterization of Metacaspase (RS107_6) as a Potential Cell Death-Inducing Protein in Rhizoctonia solani

Effectors play an important role in host–pathogen interactions. Though an economically significant disease in rice, knowledge regarding the infection strategy of Rhizoctonia solani is obscure. In this study, we performed a genome-wide identification of the effectors in R. solani based on the characteristics of previously reported effector proteins. A total of seven novel effectors (designated as RS107_1 to RS107_7) in the disease mechanism of R. solani were identified and were predicted to be non-classically secreted proteins with functionally conserved domains. The function, reactivity, and stability of these proteins were evaluated through physiochemical characterization. The target proteins involved in the regulation of rice defense mechanisms were identified. Furthermore, the effector genes were cloned and RS107_6 (metacaspase) was heterologously expressed in Escherichia coli to obtain a purified protein of ~36.5 kDa. The MALD-TOF characterization confirmed that the protein belonged to a metacaspase of the Peptidase_C14 protein family, 906 bp in size, and encoded a polypeptide of 301 amino acids. These findings suggest that the identified effectors can potentially serve as a virulence factor and can be targeted for the management of sheath blight in rice.

Effector Identification in Plant Pathogens

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

Fungal biotechnology: From yesterday to tomorrow

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

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

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

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

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

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

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

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

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

Supplementary Information

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

A Bioinformatic Guide to Identify Protein Effectors from Phytopathogens

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

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

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

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

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

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

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

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

Introduction

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

Methods

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

Results

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

Discussion

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

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

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

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

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

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

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

Fungal Effectoromics: A World in Constant Evolution

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

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

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

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

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

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

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

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

BACKGROUND

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

METHODS AND RESULTS

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

CONCLUSION

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

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

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

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

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

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

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

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

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

Whole-body transcriptome mining for candidate effectors from Diuraphis noxia

Background

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

Results

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

Conclusions

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

Supplementary Information

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

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

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

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

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