Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics

Nat Methods. 2018 Jan;15(1):53-56. doi: 10.1038/nmeth.4512. Epub 2017 Nov 27.

Abstract

Novel metabolites distinct from canonical pathways can be identified through the integration of three cheminformatics tools: BinVestigate, which queries the BinBase gas chromatography-mass spectrometry (GC-MS) metabolome database to match unknowns with biological metadata across over 110,000 samples; MS-DIAL 2.0, a software tool for chromatographic deconvolution of high-resolution GC-MS or liquid chromatography-mass spectrometry (LC-MS); and MS-FINDER 2.0, a structure-elucidation program that uses a combination of 14 metabolome databases in addition to an enzyme promiscuity library. We showcase our workflow by annotating N-methyl-uridine monophosphate (UMP), lysomonogalactosyl-monopalmitin, N-methylalanine, and two propofol derivatives.

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

  • Bacteria / metabolism
  • Blood Proteins / metabolism*
  • Chromatography, Liquid
  • Computational Biology / methods*
  • Databases, Factual*
  • Feces / chemistry
  • Gas Chromatography-Mass Spectrometry / methods*
  • Humans
  • Metabolome*
  • Metabolomics / methods*
  • Software*

Substances

  • Blood Proteins