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Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics.

  • Author(s): Lai, Zijuan
  • Tsugawa, Hiroshi
  • Wohlgemuth, Gert
  • Mehta, Sajjan
  • Mueller, Matthew
  • Zheng, Yuxuan
  • Ogiwara, Atsushi
  • Meissen, John
  • Showalter, Megan
  • Takeuchi, Kohei
  • Kind, Tobias
  • Beal, Peter
  • Arita, Masanori
  • Fiehn, Oliver
  • et al.
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.

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