A targeted metabolomic method to detect epigenetically relevant metabolites

To develop a sensitive, versatile analytical method capable of simultaneously detecting epigenetically relevant metabolites without chemical derivatization. We also aim to establish a stable isotope tracing methodology to track the biosynthesis of key epigenetic donors, S-adenosylmethionine (SAM) and acetyl-coenzyme A (acetyl-CoA), and demonstrate the method's reproducibility and quantitative accuracy through case–control studies that link metabolism to epigenetics. After a comprehensive literature review, we selected 42 metabolites based on their roles in epigenetic processes such as methylation and acetylation, and devised a targeted metabolomics approach to extract, detect, and quantify these metabolites (Supplementary table 1 and Figure 1). We then optimized ionization parameters and scan rate using pure standards to maximize metabolite coverage in LC-MS/MS. We chose a biphasic extraction method adapted from Lotti et al., using phosphoric acid (15%) and methyl tert-butyl ether (MTBE) for efficient extraction of a wide range of metabolites, including short-chain fatty acids (SCFAs) and formate, without the need for chemical derivatization. The organic phase was analyzed by GC-MS/MS, while the aqueous phase was subjected to LC-MS/MS using a zwitterionic HILIC column with medronic acid to improve peak shape and retention of charged metabolites. To potentially link metabolism and epigenetic modifications, we implemented a stable isotope tracing methodology to track 13 C-labeled glucose, glutamine, or serine into SAM and acetyl-CoA. Our method focuses on measuring isotopomers rather than isotopologues, offering a nuanced understanding of labeled carbon atom fate. Our method demonstrated high reproducibility and sensitivity, enabling the quantitative analysis of over 30 epigenetically relevant metabolites, including SCFAs, SAM, and acetyl-CoA, in various biological samples. We successfully quantified these metabolites in three case–control studies: (1) liver and gut content from germ-free and conventional mice, revealing significant differences in SCFA levels and other metabolites linked to one-carbon metabolism and energy production. (2) During OSKM reprogramming of mouse embryonic fibroblasts vitamin B12 supplementation enhances cellular reprogramming. Using 13 C-serine as a tracer, we observed a time-dependent increase in SAM enrichment, with additive effects from vitamin B12, primarily due to heightened labeling of the +1 isotopomers formate and methyl group. (3) In an isogenic human glioma cell line with the IDH1 R132H mutation, both wild-type and mutant cells predominantly used glucose carbons for acetyl-CoA synthesis. However, while no significant differences were observed in glucose metabolism between WT and mutant cells, we noted increased glutamine consumption in IDH1-R132H cells, evidenced by higher enrichment of the acetyl group in acetyl-CoA. We present an innovative analytical methodology for the simultaneous detection and quantification of over 30 epigenetically relevant metabolites, including short chain fatty acids. Using stable isotope tracing to track the synthesis of S-adenosylmethionine (SAM) and acetyl-Coenzyme A (acetyl-CoA), our method reveals new insights into metabolism linked to epigenetic modifications, including glycolysis, the pentose phosphate pathway, de novo glycine synthesis, and the folate and methionine cycle. Demonstrating practical utility in case-control studies, this approach supports integrative multi-omics strategies to explore the interplay between metabolism and epigenetics across various biological systems and diseases. • Optimized metabolite extraction targets over 30 epigenetically relevant compounds without derivatization. • Combined GC-MS and LC-MS/MS technologies cover SCFAs, formate, TCA cycle, purines, vitamins, and more. • The method detects SCFAs and formate in liver, plasma, and feces. • MRM-based strategy traces 13 C-glucose/glutamine/serine in SAM and acetyl-CoA synthesis. • Method well-suited for integrative multi-omics approaches.