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Unconventionally secreted effectors of two filamentous pathogens target plant salicylate biosynthesis.

ABSTRACT: Plant diseases caused by fungi and oomycetes pose an increasing threat to food security and ecosystem health worldwide. These filamentous pathogens, while taxonomically distinct, modulate host defense responses by secreting effectors, which are typically identified based on the presence of signal peptides. Here we show that Phytophthora sojae and Verticillium dahliae secrete isochorismatases (PsIsc1 and VdIsc1, respectively) that are required for full pathogenesis. PsIsc1 and VdIsc1 can suppress salicylate-mediated innate immunity in planta and hydrolyse isochorismate in vitro. A conserved triad of catalytic residues is essential for both functions. Thus, the two proteins are isochorismatase effectors that disrupt the plant salicylate metabolism pathway by suppressing its precursor. Furthermore, these proteins lack signal peptides, but exhibit characteristics that lead to unconventional secretion. Therefore, this secretion pathway is a novel mechanism for delivering effectors and might play an important role in host-pathogen interactions.

SUBMITTER: Liu T

PROVIDER: S-EPMC4348438 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Unconventionally secreted effectors of two filamentous pathogens target plant salicylate biosynthesis.

Liu Tingli T Song Tianqiao T Zhang Xiong X Yuan Hongbo H Su Liming L Li Wanlin W Xu Jing J Liu Shiheng S Chen Linlin L Chen Tianzi T Zhang Meixiang M Gu Lichuan L Zhang Baolong B Dou Daolong D

Nature communications 20140826

Plant diseases caused by fungi and oomycetes pose an increasing threat to food security and ecosystem health worldwide. These filamentous pathogens, while taxonomically distinct, modulate host defense responses by secreting effectors, which are typically identified based on the presence of signal peptides. Here we show that Phytophthora sojae and Verticillium dahliae secrete isochorismatases (PsIsc1 and VdIsc1, respectively) that are required for full pathogenesis. PsIsc1 and VdIsc1 can suppress ...[more]

PMID: 25156390

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Project description:Current models of plant-pathogen interactions stipulate that pathogens secrete effector proteins that disable plant defense components known as virulence targets. Occasionally, the perturbations caused by these effectors trigger innate immunity via plant disease resistance proteins as described by the "guard hypothesis." This model is nicely illustrated by the interaction between the fungal plant pathogen Cladosporium fulvum and tomato. C. fulvum secretes a protease inhibitor Avr2 that targets the tomato cysteine protease Rcr3(pim). In plants that carry the resistance protein Cf2, Rcr3(pim) is required for resistance to C. fulvum strains expressing Avr2, thus fulfilling one of the predictions of the guard hypothesis. Another prediction of the guard hypothesis has not yet been tested. Considering that virulence targets are important components of defense, different effectors from unrelated pathogens are expected to evolve to disable the same host target. In this study we confirm this prediction using a different pathogen of tomato, the oomycete Phytophthora infestans that is distantly related to fungi such as C. fulvum. This pathogen secretes an array of protease inhibitors including EPIC1 and EPIC2B that inhibit tomato cysteine proteases. Here we show that, similar to Avr2, EPIC1 and EPIC2B bind and inhibit Rcr3(pim). However, unlike Avr2, EPIC1 and EPIC2B do not trigger hypersensitive cell death or defenses on Cf-2/Rcr3(pim) tomato. We also found that the rcr3-3 mutant of tomato that carries a premature stop codon in the Rcr3 gene exhibits enhanced susceptibility to P. infestans, suggesting a role for Rcr3(pim) in defense. In conclusion, our findings fulfill a key prediction of the guard hypothesis and suggest that the effectors Avr2, EPIC1, and EPIC2B secreted by two unrelated pathogens of tomato target the same defense protease Rcr3(pim). In contrast to C. fulvum, P. infestans appears to have evolved stealthy effectors that carry inhibitory activity without triggering plant innate immunity.

Project description:MotivationType III secreted effectors (T3SEs) can be injected into host cell cytoplasm via type III secretion systems (T3SSs) to modulate interactions between Gram-negative bacterial pathogens and their hosts. Due to their relevance in pathogen-host interactions, significant computational efforts have been put toward identification of T3SEs and these in turn have stimulated new T3SE discoveries. However, as T3SEs with new characteristics are discovered, these existing computational tools reveal important limitations: (i) most of the trained machine learning models are based on the N-terminus (or incorporating also the C-terminus) instead of the proteins' complete sequences, and (ii) the underlying models (trained with classic algorithms) employed only few features, most of which were extracted based on sequence-information alone. To achieve better T3SE prediction, we must identify more powerful, informative features and investigate how to effectively integrate these into a comprehensive model.ResultsIn this work, we present Bastion3, a two-layer ensemble predictor developed to accurately identify type III secreted effectors from protein sequence data. In contrast with existing methods that employ single models with few features, Bastion3 explores a wide range of features, from various types, trains single models based on these features and finally integrates these models through ensemble learning. We trained the models using a new gradient boosting machine, LightGBM and further boosted the models' performances through a novel genetic algorithm (GA) based two-step parameter optimization strategy. Our benchmark test demonstrates that Bastion3 achieves a much better performance compared to commonly used methods, with an ACC value of 0.959, F-value of 0.958, MCC value of 0.917 and AUC value of 0.956, which comprehensively outperformed all other toolkits by more than 5.6% in ACC value, 5.7% in F-value, 12.4% in MCC value and 5.8% in AUC value. Based on our proposed two-layer ensemble model, we further developed a user-friendly online toolkit, maximizing convenience for experimental scientists toward T3SE prediction. With its design to ease future discoveries of novel T3SEs and improved performance, Bastion3 is poised to become a widely used, state-of-the-art toolkit for T3SE prediction.Availability and implementationhttp://bastion3.erc.monash.edu/.Contactselkrig@embl.de or wyztli@163.com or or trevor.lithgow@monash.edu.Supplementary informationSupplementary data are available at Bioinformatics online.

Dataset Information

Unconventionally secreted effectors of two filamentous pathogens target plant salicylate biosynthesis.

Publications

Unconventionally secreted effectors of two filamentous pathogens target plant salicylate biosynthesis.

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