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Label-Free Quantitative Proteomics Workflow for Discovery-Driven Host-Pathogen Interactions
Published on: October 20, 2020
Comprehensive Proteomic Profiling of Alternaria gansuense Provides Insights into Candidate Virulence-Associated
Huaqi Liu1, Lili Zhang1, Tongtong Wang1
1State Key Laboratory of Herbage Improvement and Grassland Agro-Ecosystems, College of Pastoral Agriculture Science and Technology, Engineering Research Center of Grassland Industry, Ministry of Education, Lanzhou University, Lanzhou 730020, China.
Abstract:
Although Alternaria gansuense causes yellow stunt and root rot (YSRR)-a destructive disease of the leguminous forage Astragalus adsurgens in northern China-systematic investigations of this pathogen at the protein level remain scarce. In this study, we establish an optimized proteomic workflow for A. gansuense by comparing two protein extraction methods. Using data-independent acquisition (DIA) mass spectrometry with a DIA-NN search against the Alternaria protein database, we construct the first comprehensive proteome reference map of A. gansuense, then perform functional annotation via Gene Ontology, KOG, KEGG, InterPro domain, and subcellular localization analyses. A total of 5052 proteins were identified from vegetative mycelia, and the proteome was found to be predominantly composed of proteins involved in primary metabolism, signal transduction, secondary metabolism, and stress responses. Notably, a set of putative pathogenicity-associated proteins, including two-component regulators (SSK1p), protein kinases, cytochrome P450 enzymes, and ABC transporters, was identified. These proteins are homologs of well-characterized virulence factors in other pathogenic fungi, suggesting a potential coordinated signaling-metabolism-defense network that may contribute to fungal virulence. Subcellular localization further shows that cytoplasmic and nuclear proteins together account for over 50% of the annotated proteome. This study presents the first comprehensive proteomic reference map for A. gansuense, providing a valuable resource for functional genomics. Subsequent experimental validation of the bioinformatically predicted candidate molecular targets presented here may help to dissect the pathogenic mechanisms of YSRR and enable the development of novel disease management strategies.
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