Improving the quality of biomarker candidates in untargeted metabolomics via peak table-based alignment of comprehensive two-dimensional gas chromatography-mass spectrometry data.

Autor: Bean HD; Dartmouth College, Thayer School of Engineering, Hanover, NH, USA., Hill JE; Dartmouth College, Thayer School of Engineering, Hanover, NH, USA., Dimandja JM; Spelman College, Department of Chemistry and Biochemistry, Atlanta, GA, USA. Electronic address: jdimandja@spelman.edu.
Jazyk: angličtina
Zdroj: Journal of chromatography. A [J Chromatogr A] 2015 May 15; Vol. 1394, pp. 111-7. Date of Electronic Publication: 2015 Mar 07.
DOI: 10.1016/j.chroma.2015.03.001
Abstrakt: The potential of high-resolution analytical technologies like GC×GC/TOF MS in untargeted metabolomics and biomarker discovery has been limited by the development of fully automated software that can efficiently align and extract information from multiple chromatographic data sets. In this work we report the first investigation on a peak-by-peak basis of the chromatographic factors that impact GC×GC data alignment. A representative set of 16 compounds of different chromatographic characteristics were followed through the alignment of 63 GC×GC chromatograms. We found that varying the mass spectral match parameter had a significant influence on the alignment for poorly-resolved peaks, especially those at the extremes of the detector linear range, and no influence on well-chromatographed peaks. Therefore, optimized chromatography is required for proper GC×GC data alignment. Based on these observations, a workflow is presented for the conservative selection of biomarker candidates from untargeted metabolomics analyses.
(Copyright © 2015 Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
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