Background:The type Ⅲ secreted effectors(T3SEs)are one of the indispensable proteins in the growth and reproduction of Gram-negative bacteria.In particular,the pathogenesis of Gram-negative bacteria depends on the ty...Background:The type Ⅲ secreted effectors(T3SEs)are one of the indispensable proteins in the growth and reproduction of Gram-negative bacteria.In particular,the pathogenesis of Gram-negative bacteria depends on the type Ⅲ secreted effectors,and by injecting T3SEs into a host cell,the host cell's immunity can be destroyed.The high diversity of T3SE sequences and the lack of defined secretion signals make it difficult to identify and predict.Moreover,the related study of the pathological system associated with T3SE remains a hot topic in bioinformatics.Some computational tools have been developed to meet the growing demand for the recognition of T3SEs and the studies of type Ⅲ secretion systems(T3SS).Although these tools can help biological experiments in certain procedures,there is still room for improvement,even for the current best model,as the existing methods adopt handdesigned feature and traditional machine learning methods.Methods:In this study,we propose a powerful predictor based on deep learning methods,called WEDeepT3.Our work consists mainly of three key steps.First,we train word embedding vectors for protein sequences in a large-scale amino acid sequence database.Second,we combine the word vectors with traditional features extracted from protein sequences,like PSSM,to construct a more comprehensive feature representation.Finally,we construct a deep neural network model in the prediction of type Ⅲ secreted effectors.Results:The feature representation of WEDeepT3 consists of both word embedding and position-specific features.Working together with convolutional neural networks,the new model achieves superior performance to the state-ofthe-art methods,demonstrating the effectiveness of the new feature representation and the powerful learning ability of deep models.Conclusion:WEDeepT3 exploits both semantic information of Ar-mer fragments and evolutional information of protein sequences to accurately difYerentiate between T3SEs and non-T3SEs.WEDeepT3 is available at bcmi.sjtu.edu.cn/~yangyang/WEDeepT3.html.展开更多
The powdery mildew fungi secrete numerous Candidate Secreted Effector Proteins(CSEPs)to manipulate host immunity during infection of host plants.However,the function of most of these CSEPs in cell death suppression ha...The powdery mildew fungi secrete numerous Candidate Secreted Effector Proteins(CSEPs)to manipulate host immunity during infection of host plants.However,the function of most of these CSEPs in cell death suppression has not yet been established.Here,we identified several CSEPs from Blumeria graminis f.sp.hordei(Bgh)that have the potential to suppress BAX-and NtMEK2^(DD)-triggered cell death in Nicotiana benthamiana.We further characterized two effector candidates,CSEP0139 and CSEP0182,from family six and thirty-two,respectively.CSEP0139 and CSEP0182 contain a functional signal peptide and are likely secreted effectors.Expression of either CSEP0139 or CSEP0182 suppressed cell death triggered by BAX and NtMEK2^(DD) but not by the AVRa13/MLA13 pair in N.benthamiana.Transient overexpression of CSEP0139 or CSEP0182 also inhibited BAX-induced cell death and collapse of cytoplasm in barley cells.Furthermore,overexpression of either CSEPs significantly increased Bgh haustorial formation in barley,whereas host-induced gene silencing(HIGS)of the CSEP genes reduced haustorial formation,suggesting both CSEPs promote Bgh virulence in barley.In addition,expression of CSEP0139 and CSEP0182 reduced size of the lesions caused by the necrotrophic Botrytis cinerea in N.benthamiana.Our findings suggest that CSEP0139 and CSEP0182 may target cell death components in plants to promote fungal virulence,which extends the current understanding of the functions of Bgh CSEPs and provides an opportunity for further investigation of fungal virulence in relation to cell death pathways in host plants.展开更多
Bacterial wilt disease caused by several Ralstonia species is one of the most destructive diseases in Solanaceae crops.Only a few functional resistance genes against bacterial wilt have been cloned to date.Here,we sho...Bacterial wilt disease caused by several Ralstonia species is one of the most destructive diseases in Solanaceae crops.Only a few functional resistance genes against bacterial wilt have been cloned to date.Here,we showthat the broadly conserved typeⅢsecreted effector RipY is recognized by the Nicotiana benthamiana immune system,leading to cell death induction,induction of defense-related gene expression,and restriction of bacterial pathogen growth.Using a multiplexed virus-induced gene-silencing-based N.benthamiana nucleotide-binding and leucine-rich repeat receptor(NbNLR)library,we identified a coiled-coil(CC)nucleotide-binding and leucine-rich repeat receptor(CNL)required for recognition of RipY,which we named RESISTANCE TO RALSTONIA SOLANACEARUM RIPY(RRS-Y).Genetic complementation assays in RRS-Y-silenced plants and stable rrs-y knockout mutants demonstrated that RRS-Y is sufficient to activate RipY-induced cell death andRipY-induced immunity to Ralstonia pseudosolanacearum.RRS-Y function is dependent on the phosphate-binding loop motif of the nucleotide-binding domain but independent of the characterized signaling components ENHANCED DISEASE SUSCEPTIBILITY 1,ACTIVATED DISEASE RESISTANCE 1,and N REQUIREMENT GENE 1 and the NLR helpers NB-LRR REQUIRED FOR HR-ASSOCIATED CELL DEATH-2,-3,and-4 in N.benthamiana.We further show that RRS-Y localization at the plasma membrane is mediated by two cysteine residues in the CC domain and is required for RipY recognition.RRSY also broadly recognizes RipY homologs across Ralstonia species.Lastly,we show that the C-terminal region of RipY is indispensable for RRS-Y activation.Together,our findings provide an additional effector/receptor pair system to deepen our understanding of CNL activation in plants.展开更多
基金supported by the National Natural Science Foundation of China(No.61972251).
文摘Background:The type Ⅲ secreted effectors(T3SEs)are one of the indispensable proteins in the growth and reproduction of Gram-negative bacteria.In particular,the pathogenesis of Gram-negative bacteria depends on the type Ⅲ secreted effectors,and by injecting T3SEs into a host cell,the host cell's immunity can be destroyed.The high diversity of T3SE sequences and the lack of defined secretion signals make it difficult to identify and predict.Moreover,the related study of the pathological system associated with T3SE remains a hot topic in bioinformatics.Some computational tools have been developed to meet the growing demand for the recognition of T3SEs and the studies of type Ⅲ secretion systems(T3SS).Although these tools can help biological experiments in certain procedures,there is still room for improvement,even for the current best model,as the existing methods adopt handdesigned feature and traditional machine learning methods.Methods:In this study,we propose a powerful predictor based on deep learning methods,called WEDeepT3.Our work consists mainly of three key steps.First,we train word embedding vectors for protein sequences in a large-scale amino acid sequence database.Second,we combine the word vectors with traditional features extracted from protein sequences,like PSSM,to construct a more comprehensive feature representation.Finally,we construct a deep neural network model in the prediction of type Ⅲ secreted effectors.Results:The feature representation of WEDeepT3 consists of both word embedding and position-specific features.Working together with convolutional neural networks,the new model achieves superior performance to the state-ofthe-art methods,demonstrating the effectiveness of the new feature representation and the powerful learning ability of deep models.Conclusion:WEDeepT3 exploits both semantic information of Ar-mer fragments and evolutional information of protein sequences to accurately difYerentiate between T3SEs and non-T3SEs.WEDeepT3 is available at bcmi.sjtu.edu.cn/~yangyang/WEDeepT3.html.
基金supported by the National Key R&D Program of China(2016YFD0100602)Ministry of Agriculture and Rural Affairs of China(2016ZX08009003–001)+1 种基金the National Natural Science Foundation of China(31530061)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB11020400).
文摘The powdery mildew fungi secrete numerous Candidate Secreted Effector Proteins(CSEPs)to manipulate host immunity during infection of host plants.However,the function of most of these CSEPs in cell death suppression has not yet been established.Here,we identified several CSEPs from Blumeria graminis f.sp.hordei(Bgh)that have the potential to suppress BAX-and NtMEK2^(DD)-triggered cell death in Nicotiana benthamiana.We further characterized two effector candidates,CSEP0139 and CSEP0182,from family six and thirty-two,respectively.CSEP0139 and CSEP0182 contain a functional signal peptide and are likely secreted effectors.Expression of either CSEP0139 or CSEP0182 suppressed cell death triggered by BAX and NtMEK2^(DD) but not by the AVRa13/MLA13 pair in N.benthamiana.Transient overexpression of CSEP0139 or CSEP0182 also inhibited BAX-induced cell death and collapse of cytoplasm in barley cells.Furthermore,overexpression of either CSEPs significantly increased Bgh haustorial formation in barley,whereas host-induced gene silencing(HIGS)of the CSEP genes reduced haustorial formation,suggesting both CSEPs promote Bgh virulence in barley.In addition,expression of CSEP0139 and CSEP0182 reduced size of the lesions caused by the necrotrophic Botrytis cinerea in N.benthamiana.Our findings suggest that CSEP0139 and CSEP0182 may target cell death components in plants to promote fungal virulence,which extends the current understanding of the functions of Bgh CSEPs and provides an opportunity for further investigation of fungal virulence in relation to cell death pathways in host plants.
基金supported by the National Research Foundation of Korea(NRF)funded by the Korean Ministry of Education(Global PhD Fellowship Program Project 500–20190213)by the Ministry of Sciences and ICT(Projects 2018R1A5A1023599,2020R1A2C1101419).
文摘Bacterial wilt disease caused by several Ralstonia species is one of the most destructive diseases in Solanaceae crops.Only a few functional resistance genes against bacterial wilt have been cloned to date.Here,we showthat the broadly conserved typeⅢsecreted effector RipY is recognized by the Nicotiana benthamiana immune system,leading to cell death induction,induction of defense-related gene expression,and restriction of bacterial pathogen growth.Using a multiplexed virus-induced gene-silencing-based N.benthamiana nucleotide-binding and leucine-rich repeat receptor(NbNLR)library,we identified a coiled-coil(CC)nucleotide-binding and leucine-rich repeat receptor(CNL)required for recognition of RipY,which we named RESISTANCE TO RALSTONIA SOLANACEARUM RIPY(RRS-Y).Genetic complementation assays in RRS-Y-silenced plants and stable rrs-y knockout mutants demonstrated that RRS-Y is sufficient to activate RipY-induced cell death andRipY-induced immunity to Ralstonia pseudosolanacearum.RRS-Y function is dependent on the phosphate-binding loop motif of the nucleotide-binding domain but independent of the characterized signaling components ENHANCED DISEASE SUSCEPTIBILITY 1,ACTIVATED DISEASE RESISTANCE 1,and N REQUIREMENT GENE 1 and the NLR helpers NB-LRR REQUIRED FOR HR-ASSOCIATED CELL DEATH-2,-3,and-4 in N.benthamiana.We further show that RRS-Y localization at the plasma membrane is mediated by two cysteine residues in the CC domain and is required for RipY recognition.RRSY also broadly recognizes RipY homologs across Ralstonia species.Lastly,we show that the C-terminal region of RipY is indispensable for RRS-Y activation.Together,our findings provide an additional effector/receptor pair system to deepen our understanding of CNL activation in plants.
