A targeted metabolomic method to detect epigenetically relevant metabolites

Abstract

AbstractMetabolites play a central role in the chemical crosstalk between metabolism and epigenetic marks. Epigenetically relevant metabolites are substrates, products and cofactors that can act as activators or inhibitors of epigenetic enzymes, which control gene expression by adding or removing chemical marks in the DNA, RNA and histones. Diet composition, and biosynthetic pathways encoded in the gut microbiome and the host genome are the main sources of these metabolites for mammals. Despite the increasing interest in the study of the ‘microbiota-nutrient metabolism-host epigenetic axis’ to understand health and disease, there is a lack of a sensitive and easy analytical method to detect epigenetically relevant metabolites simultaneously. Here, we show an straightforward biphasic extraction where the organic phase is directly analyzed by GC-EI MS to detect short-chain fatty acids and formate without chemical derivatization, and the aqueous phase is analyzed by HILIC coupled to ESI-MS/MS, which together can cover >30 epigenetically relevant metabolites in biological samples such as liver, plasma or feces. In addition, we propose a stable isotope tracing method based on multiple-reaction monitoring (MRM) transitions by LC-QqQ MS to understand how13C-labeled glucose or glutamine are used to build SAM and acetyl-CoA, the main methyl and acetyl group donors in epigenetic modifications, respectively. We anticipate that our methods will complement epigenomic and proteomic analyses adding another layer of molecular information towards mechanistic insights.HighlightsHost and microbiota metabolites link metabolism with epigenetic regulation.Chemical structure diversity in epigenetically relevant metabolites challenges its analysis with a single method.A biphasic extraction with no chemical derivatization is able to recover SCFAs and other epigenetically relevant metabolites.A novel isotope trace experiment approach allows isotopomer resolution using MS2 data.