title: Bar Coding MS(2) Spectra for Metabolite Identification.
abstract: Metabolite identifications are most frequently achieved in untargeted metabolomics by matching precursor mass and full, high-resolution MS(2) spectra to metabolite databases and standards. Here we considered an alternative approach for establishing metabolite identifications that does not rely on full, high-resolution MS(2) spectra. First, we select mass-to-charge regions containing the most informative metabolite fragments and designate them as bins. We then translate each metabolite fragmentation pattern into a binary code by assigning 1's to bins containing fragments and 0's to bins without fragments. With 20 bins, this binary-code system is capable of distinguishing 96% of the compounds in the METLIN MS(2) library. A major advantage of the approach is that it extends untargeted metabolomics to low-resolution triple quadrupole (QqQ) instruments, which are typically less expensive and more robust than other types of mass spectrometers. We demonstrate a method of acquiring MS(2) data in which the third quadrupole of a QqQ instrument cycles over 20 wide isolation windows (coinciding with the location and width of our bins) for each precursor mass selected by the first quadrupole. Operating the QqQ instrument in this mode yields diagnostic bar codes for each precursor mass that can be matched to the bar codes of metabolite standards. Furthermore, our data suggest that using low-resolution bar codes enables QqQ instruments to make MS(2)-based identifications in untargeted metabolomics with a specificity and sensitivity that is competitive to high-resolution time-of-flight technologies.
authors.affiliation: Department of Chemistry, Washington University in St. Louis , St. Louis, Missouri 63130, United States.|Department of Genetics, Washington University School of Medicine , St. Louis, Missouri 63110, United States.
authors.forename: Jonathan L
authors.initials: JL
authors.lastname: Spalding
authors.affiliation: Department of Chemistry, Washington University in St. Louis , St. Louis, Missouri 63130, United States.|Department of Medicine, Washington University School of Medicine , St. Louis, Missouri 63110, United States.
authors.forename: Kevin
authors.initials: K
authors.lastname: Cho
authors.affiliation: Department of Chemistry, Washington University in St. Louis , St. Louis, Missouri 63130, United States.|Department of Medicine, Washington University School of Medicine , St. Louis, Missouri 63110, United States.
authors.forename: Nathaniel G
authors.initials: NG
authors.lastname: Mahieu
authors.affiliation: Department of Chemistry, Washington University in St. Louis , St. Louis, Missouri 63130, United States.|Department of Genetics, Washington University School of Medicine , St. Louis, Missouri 63110, United States.
authors.forename: Igor
authors.initials: I
authors.lastname: Nikolskiy
authors.affiliation: Department of Chemistry, Washington University in St. Louis , St. Louis, Missouri 63130, United States.|Department of Medicine, Washington University School of Medicine , St. Louis, Missouri 63110, United States.
authors.forename: Elizabeth M
authors.initials: EM
authors.lastname: Llufrio
authors.affiliation: Department of Genetics, Washington University School of Medicine , St. Louis, Missouri 63110, United States.
authors.forename: Stephen L
authors.initials: SL
authors.lastname: Johnson
authors.affiliation: Department of Chemistry, Washington University in St. Louis , St. Louis, Missouri 63130, United States.|Department of Medicine, Washington University School of Medicine , St. Louis, Missouri 63110, United States.
authors.forename: Gary J
authors.initials: GJ
authors.lastname: Patti
mesh_terms: D001330:Electronic Data Processing / Q000379:methods*; D057230:Limit of Detection; D013058:Mass Spectrometry; D055442:Metabolome; D055432:Metabolomics / Q000379:methods*
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