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Updated: Jul 25, 2025

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry UPLC-MS
Published on: March 14, 2013
Intensity-dependent mass search for improving metabolite database matches in chemical isotope labeling
Yunong Li1, Hao Li1, Taibo Luo2
1Department of Chemistry, University of Alberta, Edmonton, Alberta, Canada.
Abstract:
Liquid chromatography mass spectrometry (LC-MS) has been increasingly used for metabolome analysis. One of the critical steps in the LC-MS metabolome analysis workflow is related to metabolite identification. Among the measured parameters, peak mass is commonly used to search against a database for potential metabolite matches. Higher accuracy mass measurement allows the use of a narrower mass tolerance window for mass search. While various types of mass analyzers can routinely measure a peak mass with an error of less than a few ppm, mass measurement accuracy is not uniform for peaks with different intensities, particularly for quadrupole time-of-flight (QTOF) MS. Herein we present a simple and convenient method to determine the relation between peak intensity and mass error in LC-QTOF-MS-based metabolome analysis, followed by intensity-dependent mass search (IDMS) of a database for metabolite matches. This method is based on running a series of sodium formate mass calibrants, as part of the standard operating procedure (SOP) in LC-MS data acquisition, and then curve-fitting the measured mass errors and peak intensities. We show that, in two different quadrupole time-of-flight (QTOF) mass analyzers, mass accuracy is generally reduced as peak intensity decreases, which is independent of m/z values in the range commonly used for metabolite detection (e.g., m/z < 1000). We demonstrate the improvement in metabolite matches using IDMS in the analyses of dansyl labeled standards and human urine samples. We have implemented the IDMS method in the freely available MCID database at www.mycompoundid.org, which is composed of 8021 known human endogenous metabolites and their predicted metabolic products (375,809 compounds from one metabolic reaction and 10,583,901 compounds from two reactions).
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