Untargeted metabolomics analysis by UHPLC-MS/MS of soybean plant in a compatible response to Phakopsora pachyrhizi infection

Abstract

Phakopsora pachyrhizi is a biotrophic fungus, causer of the disease Asian Soybean Rust, a severe crop disease of soybean and one that demands greater investment from producers. Thus, research efforts to control this disease are still needed. We investigated the expression of metabolites in soybean plants presenting a resistant genotype inoculated with P. pachyrhizi through the untargeted metabolomics approach. The analysis was performed in control and inoculated plants with P. pachyrhizi using UHPLC-MS/MS. Principal component analysis (PCA) and the partial least squares discriminant analysis (PLS-DA), was applied to the data analysis. PCA and PLS-DA resulted in a clear separation and classification of groups between control and inoculated plants. The metabolites were putative classified and identified using the Global Natural Products Social Molecular Networking platform in flavonoids, isoflavonoids, lipids, fatty acyls, terpenes, and carboxylic acids. Flavonoids and isoflavonoids were up-regulation, while terpenes were down-regulated in response to the soybean-P. pachyrhizi interaction. Our data provide insights into the potential role of some metabolites as flavonoids and isoflavonoids in the plant resistance to ASR. This information could result in the development of resistant genotypes of soybean to P. pachyrhizi, and effective and specific products against the pathogen.