Enhancing untargeted metabolomics using metadata-based source annotation

Nat Biotechnol. 2022 Dec;40(12):1774-1779. doi: 10.1038/s41587-022-01368-1. Epub 2022 Jul 7.


Human untargeted metabolomics studies annotate only ~10% of molecular features. We introduce reference-data-driven analysis to match metabolomics tandem mass spectrometry (MS/MS) data against metadata-annotated source data as a pseudo-MS/MS reference library. Applying this approach to food source data, we show that it increases MS/MS spectral usage 5.1-fold over conventional structural MS/MS library matches and allows empirical assessment of dietary patterns from untargeted data.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Humans
  • Metabolomics / methods
  • Metadata*
  • Tandem Mass Spectrometry*