4.7 Article

Strategy of using microsome-based metabolite production to facilitate the identification of endogenous metabolites by liquid chromatography mass spectrometry

期刊

ANALYTICA CHIMICA ACTA
卷 685, 期 1, 页码 36-44

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.aca.2010.11.014

关键词

Metabolome analysis; Metabolite identification; Endogenous metabolite; Human liver microsomes; LC-MS; Metabolomics

资金

  1. Genome Canada
  2. Canada Research Chairs program

向作者/读者索取更多资源

One of the challenges in metabolomic profiling of complex biological samples is to identify new and unknown compounds. Typically, standards are used to help identify metabolites, yet standards cannot be purchased or readily synthesized for many unknowns. In this work we present a strategy of using human liver microsomes (HLM) to metabolize known endogenous human metabolites (substrates), producing potentially new metabolites that have yet to be documented. The metabolites produced by HLM can be tentatively identified based on the associated substrate structure, known metabolic processes, tandem mass spectrometry (MS/MS) fragmentation patterns and, if necessary, accurate mass measurements. Once identified, these metabolites can be used as references for identification of the same compounds in complex biological samples. As a proof of principle, a total of 9 metabolites have been identified from individual HLM incubations using 5 different substrates. Each metabolite was used as a standard. In the analysis of human urine sample by liquid chromatography MS/MS, four spectral matches were found from the 9 microsome-produced metabolite standards. Two of them have previously been documented as endogenous human metabolites, the third is an isomer of a microsome-metabolite and the fourth compound has not been previously reported and is also an isomer of a microsome-metabolite. This work illustrates the feasibility of using microsome-based metabolism to produce metabolites of endogenous human metabolites that can be used to facilitate the identification of unknowns in biological samples. Future work on improving the performance of this strategy is also discussed. (C) 2010 Elsevier B.V. All rights reserved.

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