Quantitative proteomics analysis of defense responses triggered by the Pi1 gene following Magnaporthe oryzae infection in rice

Rice blast disease, caused by Magnaporthe oryzae (M. oryzae), poses a major threat to global rice production annually. The Pi1 gene is a key determinant of resistance to this pathogen. However, the proteomic responses of rice to M. oryzae infection in both Pi1-containing and Pi1-deficient backgrounds remain poorly understood. This study investigated Pi1-mediated protein responses in rice using quantitative proteomics to compare the susceptible line MeiB and its Pi1-introgression line 96B. Comparative analysis of 4-day post-infection samples versus untreated controls identified 121 differentially expressed proteins (DEPs) in 96B and 126 in MeiB. Functional classification showed that DEPs related to cellular processes, metabolic processesprocesses, and responses to stimuli were significantly enriched in Gene Ontology (GO) analysis. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed enrichment in metabolic pathways, secondary metabolite biosynthesis, and phenylpropanoid biosynthesis in both lines. Notably, Pi1 modulated proteins associated with apoptosis and purine metabolism during M. oryzae infection in 96B. Network analysis revealed 44 DEPs, including the pathogenesis-related protein PR10a, forming protein–protein interaction networks in 96B, compared to only 22 DEPs in MeiB. The key findings include the specific regulation of biotic stress-related proteins such as Gnk2-homologous domain-containing protein and AT-hook motif nuclear-localized protein in 96B; apoptosis and purine metabolism pathways being unique to DEPs from 96B; and the presence of pathogenesis-related protein 10a and stress-responsive proteins (e.g., Bet_v_1 domain-containing and Gnk2-homologous domain-containing proteins) in the 96B interaction network. Therefore, these results suggest that Pi1 contributes to rice blast resistance by modulating apoptosis/purine metabolism pathways and protein–protein interaction networks.