A targeted metabolomics approach toward understanding metabolic variations in rice under pesticide stress

Abstract

Diazinon insecticide is widely applied throughout rice (Oryza sativa L.) fields in Iran. However, concerns are now being raised about its potential adverse impacts on rice fields. In this study, a time-course metabolic change in rice plants was investigated after diazinon treatment using gas chromatography–mass spectrometry (GC–MS), and subsequently the statistical strategy of random forest (RF) was performed in order to find the stress-associated effects. According to the results, a wide range of metabolites were dynamically varied as a result of the plant response to diazinon such as biosynthesis and metabolism of sugars, amino acids, organic acids, and phenylpropanoids, all correlating with the exposure time. Plant response was involved in multiple metabolic pathways, most of which were correlated with the exposure time. In this study, RF was explored as a potential multivariate method for GC–MS analysis of metabolomics data of rice (O. sativa L.) plants under diazinon stress; more than 31 metabolites were quantitatively determined, and time-course metabolic response of the plant during different days after treatment was measured. Results demonstrated RF as a potential multivariate method for GC–MS analysis of changes in plant metabolome under insecticide stress.