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Shrinking the Metabolome for Systems Biology Reveals a New Metabolic Function of an Old Protein
Author(s) -
Patti Gary
Publication year - 2018
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.2018.32.1_supplement.476.3
Subject(s) - metabolomics , metabolome , computational biology , function (biology) , computer science , systems biology , biology , bioinformatics , genetics
When using liquid chromatography/mass spectrometry to perform metabolomics, it is common to detect thousands of signals from biological samples. A substantial number of these signals, however, cannot be biochemically identified. This has complicated the use of metabolomics for discovery profiling and created uncertainty about the number of “unknown metabolites” in a data set. Here we describe a suite of informatic and experimental approaches that were applied to completely annotate one metabolomic data set. The analysis revealed that >90% of our signals corresponded to artifacts, contaminants, and redundancies. A workflow will be presented for removing such signals to simplify discovery analysis by metabolomics. As an example, a study will be described in which we applied metabolomics to discover a new function of the protein carnitine palmitoyltransferase I (CPT1) that is unrelated to fatty acid oxidation. Support or Funding Information This work was supported by the National Institutes of Health Grant R35 ES028365, the Alfred P. Sloan Foundation, the Pew Scholars Program in the Biomedical sciences, and the Edward Mallinckrodt, Jr. Foundation. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .