Title
Semi-automated non-target processing in GC × GC-MS metabolomics analysis: Applicability for biomedical studies
Author
Koek, M.M.
van der Kloet, F.M.
Kleemann, R.
Kooistra, T.
Verheij, E.R.
Hankemeier, T.
Publication year
2011
Abstract
Due to the complexity of typical metabolomics samples and the many steps required to obtain quantitative data in GC × GC-MS consisting of deconvolution, peak picking, peak merging, and integration, the unbiased non-target quantification of GC × GC-MS data still poses a major challenge in metabolomics analysis. The feasibility of using commercially available software for non-target processing of GC × GC-MS data was assessed. For this purpose a set of mouse liver samples (24 study samples and five quality control (QC) samples prepared from the study samples) were measured with GC × GC-MS and GC-MS to study the development and progression of insulin resistance, a primary characteristic of diabetes type 2. A total of 170 and 691 peaks were quantified in, respectively, the GC-MS and GC × GC-MS data for all study and QC samples. The quantitative results for the QC samples were compared to assess the quality of semi-automated GC × GC-MS processing compared to targeted GC-MS processing which involved time-consuming manual correction of all wrongly integrated metabolites and was considered as golden standard. The relative standard deviations (RSDs) obtained with GC × GC-MS were somewhat higher than with GC-MS, due to less accurate processing. Still, the biological information in the study samples was preserved and the added value of GC × GC-MS was demonstrated; many additional candidate biomarkers were found with GC × GC-MS compared to GC-MS. © 2010 The Author(s).
Subject
Triskelion BV Life
TAP - Toxicology and Applied Pharmacology QS - Quality & Safety
EELS - Earth, Environmental and Life Sciences
Nutrition
Automated data processing
Comprehensive two-dimensional gas chromatography mass spectrometry
Diabetes
GC × GC-MS
Insulin resistance
Metabolomics
To reference this document use:
http://resolver.tudelft.nl/uuid:df7bfcfd-6613-4580-ba60-19651c4968d1
DOI
https://doi.org/10.1007/s11306-010-0219-6
TNO identifier
427715
ISSN
1573-3882
Source
Metabolomics, 7 (1), 1-4
Document type
article