Quantitative proteomic approaches to characterize the dynamic and comprehensive defence responses of wheat to leaf rust

Citation

Huang M, Fernando U, Djuric-Ciganovic S, Wang X, Bakkeren G, Linning R, Bykova NV, Rampitsch C (2018) Quantitative proteomic approaches to characterize the dynamic and comprehensive defence responses of wheat to leaf rust. 66th ASMS Conference on Mass Spectrometry and Allied Topics, San Diego, CA, USA, June 3-7, 2018. Poster

Plain language summary

The fungus Puccinia triticina (Pt) is an obligate parasite that causes leaf rust, one of the most important foliar diseases on wheat. Pt enters wheat leaves through stomata and colonizes the apoplastic space with hyphae, which in the early stages of infection communicate with the host and attempt to evade the host immune system using effector proteins. Various races of Pt exist, classified based on their ability to overcome certain host resistance genes. For example, Lr2a confers resistance to Pt Race 161 (avirulent) but is overcome by Pt Race 9 (virulent). The aim of the present work was to study the defence responses of wheat cultivar bearing the Lr2a resistance gene using quantitative proteomic approaches.
Interpretation of results is complicated by the presence of two proteomes and by a lack of sequence annotation and resources for these economically important non-model organisms. We have established race-specific databases for Pt. Race 1, Race 9 and 161. The host, bread wheat (Triticum aestivum), has also recently been sequenced, however annotation is incomplete. We have created a comprehensive annotated non-redundant EST database of Tae (226,863 sequence contigs) based on an extensive NCBI EST database that is publicly available for wheat, which has proven to be a useful resource for identifying wheat proteins from MS spectra. Over 3,000 pathogen and host protein clusters were identified for both label free and iTRAQ data sets. After rigorous statistical analysis, further bioinformatics approaches were used to view the plant-pathogen interaction. Quantifying host and pathogen proteins in both susceptible and resistant host-pathogen interactions happening at different days after infection revealed a dynamic and comprehensive progress of leaf rust activity and the corresponding defense responses triggered by the host.

Abstract

The fungus Puccinia triticina (Pt) is an obligate parasite that causes leaf rust, one of the most important foliar diseases on wheat. Pt enters wheat leaves through stomata and colonizes the apoplastic space with hyphae, which in the early stages of infection communicate with the host and attempt to evade the host immune system using effector proteins. Various races of Pt exist, classified based on their ability to overcome certain host resistance genes. For example, Lr2a confers resistance to Pt Race 161 (avirulent) but is overcome by Pt Race 9 (virulent). The aim of the present work was to study the defence responses of wheat cultivar bearing the Lr2a resistance gene using quantitative proteomic approaches.
In the present study, Pt races either 161 or 9 were used to infect Thatcher Lr2a wheat and both pathogen and host proteomes were quantitatively characterized using 8-plex iTRAQ, peptide pre-fractionation and LC-MS/MS with a stepped HCD on the Q-Exactive instrument. In addition, a single race of Pt (the well characterized Race 1) was used to infect two near-isogenic host genotypes: resistant (bearing the Lr1 resistance gene) and susceptible (lacking Lr1) wheat. Only apoplastic proteome was extracted and investigated using label free proteomic approach.
MS data were searched against in-house customized EST wheat and race-specific Pt databases for protein identification followed by validation and quantitative analysis with Scaffold Q+ and MaxQuant to generate insightful result for study of leaf rust.
Interpretation of results is complicated by the presence of two proteomes and by a lack of sequence annotation and resources for these economically important non-model organisms. We have established race-specific databases for Pt. Race 1, Race 9 and 161. The host, bread wheat (Triticum aestivum), has also recently been sequenced, however annotation is incomplete. We have created a comprehensive annotated non-redundant EST database of Tae (226,863 sequence contigs) based on an extensive NCBI EST database that is publicly available for wheat, which has proven to be a useful resource for identifying wheat proteins from MS spectra. Peptide identifications with probability greater than 95.0% and protein identifications that contained at least two identified peptides with greater than a 99.0% probability that achieved a decoy false discovery rate of 0.26% and 0.4%, respectively, were accepted for further analysis. Proteins sharing significant peptide evidence were grouped into clusters, and only exclusive unique peptides were used for peptide and protein quantitation. Our strategies to identify proteins and peptide origins correctly will be explained.
Over 3,000 pathogen and host protein clusters were identified for both label free and iTRAQ data sets. After rigorous statistical analysis, further bioinformatics approaches were used to view the plant-pathogen interaction. Quantifying host and pathogen proteins in both susceptible and resistant host-pathogen interactions happening at different days after infection revealed a dynamic and comprehensive progress of leaf rust activity and the corresponding defense responses triggered by the host.