Comparative omics analysis for novel target discovery in plant pathogens: A case study for Magnaporthe oryzae

Abstract

The central concern surrounding chemical pesticide application is its potential adverse effects on non-target organisms. For fungal pathogens, the search for specific targets has been complicated by the similarities in pathways shared between these pathogens and humans. We present a comprehensive strategy, integrating comparative omics and bioinformatics, to pinpoint precise targets for fungicides effective against the fungal pathogen Magnaporthe oryzae, responsible for rice blast disease. Our approach involves subtractive metabolic pathways, homology screening and target prioritization. Through subtractive metabolic analysis, we identified three unique M. oryzae pathways, distinct from human and rice. Nonredundant protein sequences were subsequently subjected to BLASTP screening against human and rice, as well as other databases from diverse organisms. Target subcellular localization was predicted using eight tools, including artificial intelligence and a deep-learning method. A comprehensive examination of biological processes was conducted, including gene expression, protein–protein interactions, network enrichment, broad-spectrum activity and physicochemical analysis. Glutamate 5-kinase emerged as the prime candidate for targeted fungicide development, promising progress in precision-oriented solutions.