Integrative Normalization and Comparative Analysis for Metabolic Fingerprinting by Comprehensive Two-Dimensional Gas Chromatography-Time-of-Flight Mass Spectrometry

Almstetter, Martin F. and Appel, Inka J. and Gruber, Michael A. and Lottaz, Claudia and Timischl, Birgit and Spang, Rainer and Dettmer, Katja and Oefnert, Peter J. (2009) Integrative Normalization and Comparative Analysis for Metabolic Fingerprinting by Comprehensive Two-Dimensional Gas Chromatography-Time-of-Flight Mass Spectrometry. ANALYTICAL CHEMISTRY, 81 (14). pp. 5731-5739. ISSN 0003-2700, 1520-6882

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Abstract

Comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC x GC-TOF-MS) was applied to the comparative metabolic fingerprinting of a wild-type versus a double mutant strain of Escherichia coli lacking the transhydrogenases UdhA and PntAB. Using peak lists generated with the Leco ChromaTOF software as input, we developed retention time correction and data alignment tools (INCA). The accuracy of peak alignment and detection of 1.1- to 4-fold changes in metabolite concentration was validated by a spike-in experiment with 20 standard compounds. A list of 48 significant features that differentiated the two E. coli strains was obtained with an estimated false discovery rate (FDR) of < 0.05. A total of 27 metabolites, mainly from the citrate cycle, were identified. That the signal intensity of the m/z 73 trace of the trimethylsilyl (TMS) group reflected true differences in metabolite abundance was confirmed by quantification of pyruvate, fumarate, malate, succinate, alpha-ketoglutarate, citrate, cis-aconitate, myo-inositol, and glucose-6-phosphate using compound specific fragment ions and stable isotope labeled standards. Relative standard deviations for metabolite extraction and GC x GC-TOF-MS analysis of those analytes ranged from 13.2 to 26.3% for the universal m/z 73 trace and 7.4 to 24.5% for the analyte specific fragment ion trace.

Item Type: Article
Uncontrolled Keywords: GENE-EXPRESSION; SEPARATION DATA; PROFILE DATA; X GC; POWERFUL; EXTRACTS;
Subjects: 600 Technology > 610 Medical sciences Medicine
Divisions: Medicine > Lehrstuhl für Anästhesiologie
Medicine > Institut für Funktionelle Genomik > Lehrstuhl für Funktionelle Genomik (Prof. Oefner)
Medicine > Institut für Funktionelle Genomik > Lehrstuhl für Statistische Bioinformatik (Prof. Spang)
Depositing User: Dr. Gernot Deinzer
Date Deposited: 10 Sep 2020 09:39
Last Modified: 10 Sep 2020 09:39
URI: https://pred.uni-regensburg.de/id/eprint/28702

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