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. 2012 Feb 1:32:1-14.
doi: 10.1016/j.trac.2011.08.009.

Metabolite identification and quantitation in LC-MS/MS-based metabolomics

Jun Feng Xiao  1 , Bin Zhou, Habtom W Ressom
Affiliations

Metabolite identification and quantitation in LC-MS/MS-based metabolomics

Jun Feng Xiao et al. Trends Analyt Chem. .

Abstract

Metabolomics aims at detection and quantitation of all metabolites in biological samples. The presence of metabolites with a wide variety of physicochemical properties and different levels of abundance challenges existing analytical platforms used for identification and quantitation of metabolites. Significant efforts have been made to improve analytical and computational methods for metabolomics studies.This review focuses on the use of liquid chromatography with tandem mass spectrometry (LC-MS/MS) for quantitative and qualitative metabolomics studies. It illustrates recent developments in computational methods for metabolite identification, including ion annotation, spectral interpretation and spectral matching. We also review selected reaction monitoring and high-resolution MS for metabolite quantitation. We discuss current challenges in metabolite identification and quantitation as well as potential solutions.

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Figures

Figure 1
Figure 1
The metabolite identification framework, which uses EICs, m/z values, and MS/MS spectra. EICs are used for ion annotation. The m/z values are used in mass-based search to obtain a list of putative identifications. MS/MS spectra are used for spectral interpretation, spectral matching, and metabolite verification.
Figure 2
Figure 2
An example of spectra matching using MassBank database. A spectrum of unknown metabolite is searched against the database and the library spectrum of L-histidine gives the best matching score.
Figure 3
Figure 3
The Pearson correlation coefficients between a set of MS/MS spectra from the same metabolites (A) and various spectra from different metabolites (B). The data in this analysis include in-house datasets generated by UPLC-QTOF (Waters Premier) and LC-QqQ (Waters Micromass Quattro) datasets from the HMDB database.
Figure 3
Figure 3
The Pearson correlation coefficients between a set of MS/MS spectra from the same metabolites (A) and various spectra from different metabolites (B). The data in this analysis include in-house datasets generated by UPLC-QTOF (Waters Premier) and LC-QqQ (Waters Micromass Quattro) datasets from the HMDB database.
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