Publication | April 11, 2025
Isotope tracing-based metabolite identification for mass spectrometry metabolomics
Get the Resource
Read the PaperMass spectrometry-based metabolomics is integral to the advancement of precision medicines. This technology enables the capture and measure of thousands of small molecules in biosamples that inform on physiological state and that can represent important biomarkers of human disease pathogenesis and drug response. Yet, a long-standing challenge for metabolomics lies in metabolite identification, as only a fraction of human metabolites and lipids have been structurally determined. If a large portion of the molecules that underlie the myriad of signals observed in mass spectrometry data are unknown, it limits translatability of findings.
To date, metabolite identification had relied largely on comparing MS2 fragmentation patterns against known standards, related compounds or predicted spectra. This manuscript, now published in bioRxiv, describes a new orthogonal approach using isotope tracing-based metabolite identification.
The paper, authored by Sapient’s scientists and to which Sapient provided analytical chemistry support for validation experiments, describes an isotope-based metabolite identification workflow using human cells grown on nutrients containing carbon-13. The metabolic products formed by cells acquire complex patterns of carbon-13 isotopes, which can be used as “fingerprints” to identify molecules and their biosynthetic origin.
Using this isotope tracing-based method, the researchers were able to discover a novel human metabolite, trimethylglycyl-lysine (TMGL), that appears to play a role in muscle physiology. This is the first report of the existence of TMGL in any organism, and an analysis of the metabolite in skeletal muscle from people with obesity and type 2 diabetes randomized to receive an 8-month intensive lifestyle therapy (ILT) found muscle TMGL content was markedly increased in the ILT group, concurrent with marked weight loss and muscle remodeling.
These results demonstrate that isotope-based metabolite identification can be leveraged to systematically annotate unknown mass spectrometry signals from endogenous metabolites and identify novel compounds that inform drug development strategies. The approach is fully complementary to existing metabolite identification techniques based on ion fragmentation, and can help extend the reach of mass spectrometry in biomedicine.
To learn more, read the full paper and findings.
