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Comprehensive Metabolite Identification Strategy Using Multiple Two-Dimensional NMR Spectra of a Complex Mixture Implemented in the COLMARm Web Server

Identification of metabolites in complex mixtures represents a key step in metabolomics. A new strategy is introduced, which is implemented in a new public web server, COLMARm, that permits the coanalysis of up to three two-dimensional (2D) NMR spectra, namely, 13C–1H HSQC (heteronuclear single quan...

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Bibliographic Details
Published in:Analytical chemistry (Washington) 2016-12, Vol.88 (24), p.12411-12418
Main Authors: Bingol, Kerem, Li, Da-Wei, Zhang, Bo, Brüschweiler, Rafael
Format: Article
Language:English
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Summary:Identification of metabolites in complex mixtures represents a key step in metabolomics. A new strategy is introduced, which is implemented in a new public web server, COLMARm, that permits the coanalysis of up to three two-dimensional (2D) NMR spectra, namely, 13C–1H HSQC (heteronuclear single quantum coherence spectroscopy), 1H–1H TOCSY (total correlation spectroscopy), and 13C–1H HSQC-TOCSY, for the comprehensive, accurate, and efficient performance of this task. The highly versatile and interactive nature of COLMARm permits its application to a wide range of metabolomics samples independent of the magnetic field. Database query is performed using the HSQC spectrum, and the top metabolite hits are then validated against the TOCSY-type experiment(s) by superimposing the expected cross-peaks on the mixture spectrum. In this way the user can directly accept or reject candidate metabolites by taking advantage of the complementary spectral information offered by these experiments and their different sensitivities. The power of COLMARm is demonstrated for a human serum sample uncovering the existence of 14 metabolites that hitherto were not identified by NMR.
ISSN:0003-2700
1520-6882
DOI:10.1021/acs.analchem.6b03724