The role of oomycete effectors in plant - pathogen interactions

2010 ◽  
Vol 37 (10) ◽  
pp. 919 ◽  
Author(s):  
Adrienne R. Hardham ◽  
David M. Cahill
Keyword(s):  
Plant Cell ◽  
Plant Pathogens ◽  
Plant Defence ◽  
Effector Proteins ◽  
Plant Structure ◽  
Cell Wall Degrading Enzymes ◽  
Cell Cytoplasm ◽  
Diverse Range ◽  
Successful Infection ◽  
Pathogen Effector

Plants constantly come into contact with a diverse range of microorganisms that are potential pathogens, and they have evolved multi-faceted physical and chemical strategies to inhibit pathogen ingress and establishment of disease. Microbes, however, have developed their own strategies to counteract plant defence responses. Recent research on plant–microbe interactions has revealed that an important part of the infection strategies of a diverse range of plant pathogens, including bacteria, fungi and oomycetes, is the production of effector proteins that are secreted by the pathogen and that promote successful infection by manipulating plant structure and metabolism, including interference in plant defence mechanisms. Pathogen effector proteins may function either in the extracellular spaces within plant tissues or within the plant cell cytoplasm. Extracellular effectors include cell wall degrading enzymes and inhibitors of plant enzymes that attack invading pathogens. Intracellular effectors move into the plant cell cytoplasm by as yet unknown mechanisms where, in incompatible interactions, they may be recognised by plant resistance proteins but where, in compatible interactions, they may suppress the plant’s immune response. This article presents a brief overview of our current understanding of the nature and function of effectors produced by oomycete plant pathogens.

scholarly journals The secreted hypersensitive response inducing protein 1 fromBotrytis cinereadisplays non-canonical PAMP-activity

2020 ◽  
Author(s):  
Tanja Jeblick ◽  
Thomas Leisen ◽  
Christina E. Steidele ◽  
Jonas Müller ◽  
Florian Mahler ◽  
...  
Keyword(s):  
Cell Death ◽  
Plant Cell ◽  
Hypersensitive Response ◽  
Plant Pathogens ◽  
Infection Process ◽  
Host Cells ◽  
Plant Responses ◽  
Cell Wall Degrading Enzymes ◽  
Molecular Pattern ◽  
Biotrophic Pathogens

AbstractAccording to their lifestyle, plant pathogens are divided into biotrophic and necrotrophic organisms. While biotrophic pathogens establish a relationship with living host cells, necrotrophic pathogens rapidly kill host cells and feed on the cell debris. To this end, the necrotrophic ascomycete fungusBotrytis cinereasecretes large amounts of phytotoxic proteins and cell wall degrading enzymes. However, the precise role of these proteins during the infection process is unknown. Here we report on the identification and characterization of the previously unknown toxic protein hypersensitive response inducing protein 1 (Hip1), which induces plant cell death. We found the adoption of a folded protein structure to be a prerequisite for Hip1 to exert its necrosis-inducing activity inNicotiana benthamiana. Localization and the induction of specific plant responses by Hip1 indicate recognition as pathogen-associated molecular pattern at the plant plasma membrane. Our results demonstrate that recognition of Hip1, even in the absence of obvious enzymatic or poreforming activity, induces strong plant defense reactions eventually leading to plant cell death.

scholarly journals Host targets of effectors of the lettuce downy mildew Bremia lactucae from cDNA-based yeast two-hybrid screening

2019 ◽  
Author(s):  
Alexandra J.E. Pelgrom ◽  
Claudia-Nicole Meisrimler ◽  
Joyce Elberse ◽  
Thijs Koorman ◽  
Mike Boxem ◽  
...  
Keyword(s):  
Downy Mildew ◽  
Pathogenic Bacteria ◽  
Plant Pathogens ◽  
Molecular Mechanisms ◽  
Effector Proteins ◽  
Bremia Lactucae ◽  
Yeast Two Hybrid ◽  
Target Proteins ◽  
Successful Infection ◽  
Two Hybrid

AbstractPlant pathogenic bacteria, fungi and oomycetes secrete effector proteins to manipulate host cell processes to establish a successful infection. Over the last decade the genomes and transcriptomes of many agriculturally important plant pathogens have been sequenced and vast candidate effector repertoires were identified using bioinformatic analyses. Elucidating the contribution of individual effectors to pathogenicity is the next major hurdle. To advance our understanding of the molecular mechanisms underlying lettuce susceptibility to the downy mildew Bremia lactucae, we mapped a network of physical interactions between B. lactucae effectors and lettuce target proteins. Using a lettuce cDNA library-based yeast-two-hybrid system, 61 protein-protein interactions were identified, involving 21 B. lactucae effectors and 46 unique lettuce proteins. The top ten targets based on the number of independent colonies identified in the Y2H and two targets that belong to gene families involved in plant immunity, were further characterized. We determined the subcellular localization of the fluorescently tagged target proteins and their interacting effectors. Importantly, relocalization of effectors or targets to the nucleus was observed for four effector-target pairs upon their co-expression, supporting their interaction in planta.

scholarly journals Accurate plant pathogen effector protein classification ab initio with deepredeff: an ensemble of convolutional neural networks

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ruth Kristianingsih ◽  
Dan MacLean
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Convolutional Neural Networks ◽  
Plant Pathogens ◽  
De Novo ◽  
Chemical Properties ◽  
Effector Proteins ◽  
Global Food Security ◽  
Pathogen Effector ◽  
Biological Insight

Abstract Background Plant pathogens cause billions of dollars of crop loss every year and are a major threat to global food security. Effector proteins are the tools such pathogens use to infect the cell, predicting effectors de novo from sequence is difficult because of the heterogeneity of the sequences. We hypothesised that deep learning classifiers based on Convolutional Neural Networks would be able to identify effectors and deliver new insights. Results We created a training set of manually curated effector sequences from PHI-Base and used these to train a range of model architectures for classifying bacteria, fungal and oomycete sequences. The best performing classifiers had accuracies from 93 to 84%. The models were tested against popular effector detection software on our own test data and data provided with those models. We observed better performance from our models. Specifically our models showed greater accuracy and lower tendencies to call false positives on a secreted protein negative test set and a greater generalisability. We used GRAD-CAM activation map analysis to identify the sequences that activated our CNN-LSTM models and found short but distinct N-terminal regions in each taxon that was indicative of effector sequences. No motifs could be observed in these regions but an analysis of amino acid types indicated differing patterns of enrichment and depletion that varied between taxa. Conclusions Small training sets can be used effectively to train highly accurate and sensitive deep learning models without need for the operator to know anything other than sequence and without arbitrary decisions made about what sequence features or physico-chemical properties are important. Biological insight on subsequences important for classification can be achieved by examining the activations in the model

scholarly journals Arabidopsis thaliana Cells: A Model to Evaluate the Virulence of Pectobacterium carotovorum

2010 ◽  
Vol 23 (2) ◽  
pp. 139-143 ◽  
Author(s):  
Meriam Terta ◽  
Mohamed Kettani-Halabi ◽  
Khadija Ibenyassine ◽  
Daniel Tran ◽  
Patrice Meimoun ◽  
...  
Keyword(s):  
Arabidopsis Thaliana ◽  
Cell Death ◽  
Plant Cell ◽  
Plant Pathogens ◽  
Plant Cell Wall ◽  
Pectate Lyase ◽  
Soft Rot ◽  
Pectobacterium Carotovorum ◽  
Cell Wall Degrading Enzymes ◽  
Suspension Cells

Pectobacterium carotovorum are economically important plant pathogens that cause plant soft rot. These enterobacteria display high diversity world-wide. Their pathogenesis depends on production and secretion of virulence factors such as plant cell wall–degrading enzymes, type III effectors, a necrosis-inducing protein, and a secreted virulence factor from Xanthomonas spp., which are tightly regulated by quorum sensing. Pectobacterium carotovorum also present pathogen-associated molecular patterns that could participate in their pathogenicity. In this study, by using suspension cells of Arabidopsis thaliana, we correlate plant cell death and pectate lyase activities during coinfection with different P. carotovorum strains. When comparing soft rot symptoms induced on potato slices with pectate lyase activities and plant cell death observed during coculture with Arabidopsis thaliana cells, the order of strain virulence was found to be the same. Therefore, Arabidopsis thaliana cells could be an alternative tool to evaluate rapidly and efficiently the virulence of different P. carotovorum strains.

scholarly journals Accurate plant pathogen effector protein classification ab initio with deepredeff, an ensemble of convolutional neural networks

2020 ◽  
Author(s):  
Ruth Kristianingsih ◽  
Dan MacLean
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Plant Pathogens ◽  
De Novo ◽  
R Package ◽  
Effector Proteins ◽  
Global Food Security ◽  
Pathogen Effector ◽  
Detection Software ◽  
Map Analysis

Plant pathogens cause billions of dollars of crop loss every year and are a major threat to global food security. Effector proteins are the tools such pathogens use to infect the cell, predicting effectors de novo from sequence is difficult because of the heterogeneity of the sequences. We hypothesised that deep learning classifiers based on Convolutional Neural Networks would be able to identify effectors and deliver new insights. We built a training set of manually curated effector sequences from PHI-Base and used these to train a range of model architectures for classifying bacteria, fungal and oomycete sequences. The best performing classifiers had accuracies from 93 % to 84 %. The models were tested against popular effector detection software on our own test data and data provided with those models. We observed better performance from our models. Specifically our models showed greater accuracy and lower tendencies to call false positives on a secreted protein negative test set and a greater generalisability. We used GRAD-CAM activation map analysis to identify the sequences that activated our CNN-LSTM models and found short but distinct N-terminal regions in each taxon that was indicative of effector sequences. No motifs could be observed in these regions but an analysis of amino acid types indicated differing patterns of enrichment and depletion that varied between taxa. We have produced an R package that will allow others to make easy effector predictions using our models.

scholarly journals Roq1 confers resistance to Xanthomonas, Pseudomonas syringae and Ralstonia solanacearum in tomato

2019 ◽  
Author(s):  
Nicholas C. Thomas ◽  
Connor G. Hendrich ◽  
Upinder S. Gill ◽  
Caitilyn Allen ◽  
Samuel F. Hutton ◽  
...  
Keyword(s):  
Pseudomonas Syringae ◽  
Ralstonia Solanacearum ◽  
Plant Pathogens ◽  
Field Trials ◽  
Current Control ◽  
Effector Proteins ◽  
Effective Control ◽  
Crop Species ◽  
Xanthomonas Perforans ◽  
Pathogen Effector

AbstractXanthomonas species, Pseudomonas syringae and Ralstonia solanacearum are bacterial plant pathogens that cause significant yield loss in many crop species. Current control methods for these pathogens are insufficient but there is significant potential for generating new disease-resistant crop varieties. Plant immune receptors encoded by nucleotide-binding, leucine-rich repeat (NLR) genes typically confer resistance to pathogens that produce a cognate elicitor, often an effector protein secreted by the pathogen to promote virulence. The diverse sequence and presence / absence variation of pathogen effector proteins within and between pathogen species usually limits the utility of a single NLR gene to protecting a plant from a single pathogen species or particular strains. The NLR protein Recognition of XopQ 1 (Roq1) was recently identified from the plant Nicotiana benthamiana and mediates perception of the effector proteins XopQ and HopQ1 from Xanthomonas and P. syringae respectively. Unlike most recognized effectors, alleles of XopQ/HopQ1 are highly conserved and present in most plant pathogenic strains of Xanthomonas and P. syringae. A homolog of XopQ/HopQ1, named RipB, is present in many R. solanacearum strains. We found that Roq1 also mediates perception of RipB and confers immunity to Xanthomonas, P. syringae, and R. solanacearum when expressed in tomato. Strong resistance to Xanthomonas perforans was observed in three seasons of field trials with both natural and artificial inoculation. The Roq1 gene can therefore be used to provide safe, economical and effective control of these pathogens in tomato and other crop species and reduce or eliminate the need for traditional chemical controls.SummaryA single immune receptor expressed in tomato confers strong resistance to three different bacterial diseases.

scholarly journals The Endo-Arabinanase BcAra1 Is a Novel Host-Specific Virulence Factor of the Necrotic Fungal Phytopathogen Botrytis cinerea

2014 ◽  
Vol 27 (8) ◽  
pp. 781-792 ◽  
Author(s):  
Majse Nafisi ◽  
Maria Stranne ◽  
Lisha Zhang ◽  
Jan A. L. van Kan ◽  
Yumiko Sakuragi
Keyword(s):  
Cell Wall ◽  
Botrytis Cinerea ◽  
Plant Cell ◽  
Plant Pathogens ◽  
Plant Cell Wall ◽  
High Efficiency ◽  
Microbial Infection ◽  
Cell Wall Degrading Enzymes ◽  
Novel Host

The plant cell wall is one of the first physical interfaces encountered by plant pathogens and consists of polysaccharides, of which arabinan is an important constituent. During infection, the necrotrophic plant pathogen Botrytis cinerea secretes a cocktail of plant cell-wall-degrading enzymes, including endo-arabinanase activity, which carries out the breakdown of arabinan. The roles of arabinan and endo-arabinanases during microbial infection were thus far elusive. In this study, the gene Bcara1 encoding for a novel α-1,5-L-endo-arabinanase was identified and the heterologously expressed BcAra1 protein was shown to hydrolyze linear arabinan with high efficiency whereas little or no activity was observed against the other oligo- and polysaccharides tested. The Bcara1 knockout mutants displayed reduced arabinanase activity in vitro and severe retardation in secondary lesion formation during infection of Arabidopsis leaves. These results indicate that BcAra1 is a novel endo-arabinanase and plays an important role during the infection of Arabidopsis. Interestingly, the level of Bcara1 transcript was considerably lower during the infection of Nicotiana benthamiana compared with Arabidopsis and, consequently, the ΔBcara1 mutants showed the wild-type level of virulence on N. benthamiana leaves. These results support the conclusion that the expression of Bcara1 is host dependent and is a key determinant of the disease outcome.

scholarly journals Harnessing Effector-Triggered Immunity for Durable Disease Resistance

2017 ◽  
Vol 107 (8) ◽  
pp. 912-919 ◽  
Author(s):  
Meixiang Zhang ◽  
Gitta Coaker
Keyword(s):  
Disease Resistance ◽  
Plant Pathogens ◽  
Domain Architecture ◽  
Effector Proteins ◽  
Plant Diseases ◽  
Sources Of Resistance ◽  
Pathogen Effectors ◽  
Pathogen Effector ◽  
Effector Triggered Immunity ◽  
Durable Disease Resistance

Genetic control of plant diseases has traditionally included the deployment of single immune receptors with nucleotide-binding leucine-rich repeat (NLR) domain architecture. These NLRs recognize corresponding pathogen effector proteins inside plant cells, resulting in effector-triggered immunity (ETI). Although ETI triggers robust resistance, deployment of single NLRs can be rapidly overcome by pathogen populations within a single or a few growing seasons. In order to generate more durable disease resistance against devastating plant pathogens, a multitiered strategy that incorporates stacked NLRs combined with other sources of disease resistance is necessary. New genetic and genomic technologies have enabled advancements in identifying conserved pathogen effectors, isolating NLR repertoires from diverse plants, and editing plant genomes to enhance resistance. Significant advancements have also been made in understanding plant immune perception at the receptor level, which has promise for engineering new sources of resistance. Here, we discuss how to utilize recent scientific advancements in a multilayered strategy for developing more durable disease resistance.

scholarly journals The Ustilago hordei–Barley Interaction is a Versatile System for Characterization of Fungal Effectors

2021 ◽  
Vol 7 (2) ◽  
pp. 86
Author(s):  
Bilal Ökmen ◽  
Daniela Schwammbach ◽  
Guus Bakkeren ◽  
Ulla Neumann ◽  
Gunther Doehlemann
Keyword(s):  
Fungal Pathogens ◽  
Plant Pathogens ◽  
Expression System ◽  
Pathogenic Fungi ◽  
Effector Proteins ◽  
Mating Partner ◽  
Fungal Virulence ◽  
Functional Studies ◽  
Infection Structures ◽  
Ustilago Hordei

Obligate biotrophic fungal pathogens, such as Blumeria graminis and Puccinia graminis, are amongst the most devastating plant pathogens, causing dramatic yield losses in many economically important crops worldwide. However, a lack of reliable tools for the efficient genetic transformation has hampered studies into the molecular basis of their virulence or pathogenicity. In this study, we present the Ustilago hordei–barley pathosystem as a model to characterize effectors from different plant pathogenic fungi. We generate U. hordei solopathogenic strains, which form infectious filaments without the presence of a compatible mating partner. Solopathogenic strains are suitable for heterologous expression system for fungal virulence factors. A highly efficient Crispr/Cas9 gene editing system is made available for U. hordei. In addition, U. hordei infection structures during barley colonization are analyzed using transmission electron microscopy, showing that U. hordei forms intracellular infection structures sharing high similarity to haustoria formed by obligate rust and powdery mildew fungi. Thus, U. hordei has high potential as a fungal expression platform for functional studies of heterologous effector proteins in barley.

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