Illuminating a plant’s tissue-specific metabolic diversity using computational metabolomics and information theory

While cross-tissue metabolite variations are increasingly regarded as important readouts of tissue-level gene regulatory processes, these have rarely been explored by non-targeted metabolomics. Here we explore tissue-level metabolic specialization in Nicotiana attenuata, an ecological model with rich secondary metabolism by combining tissue-wide non-targeted mass spectral data acquisition, information theory analysis, and MS/MS molecular networks. This analysis was conducted for two different methanolic extracts of 14 tissues and deconvoluted 895 non-redundant MS/MS spectra. Using information theory analysis, anthers were found to harbor the most specialized metabolome and, through MS/MS molecular networks, most unique metabolites of anthers and other tissues were annotated. Finally, tissue-metabolite association maps were used to predict tissue-specific gene functions. Predictions for the function of two UDP-glycosyltransferases in flavonoid metabolism were confirmed by virus-induced gene-silencing. The present workflow allows biologists to amortize the vast amount of data produced by modern MS instrumentation for their quest to understand gene function.