Natural isotope correction of MS/MS measurements for metabolomics and super(13)C fluxomics

Fluxomics and metabolomics are crucial tools for metabolic engineering and biomedical analysis to determine the in vivo cellular state. Especially, the application of super(13)C isotopes allows comprehensive insights into the functional operation of cellular metabolism. Compared to single MS, tandem...

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Veröffentlicht in:Biotechnology and bioengineering 2016-05, Vol.113 (5), p.1137-1147
Hauptverfasser: Niedenfuehr, Sebastian, ten Pierick, Angela, van Dam, Patricia TN, Suarez-Mendez, Camilo A, Noh, Katharina, Wahl, SAljoscha
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Sprache:eng
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Zusammenfassung:Fluxomics and metabolomics are crucial tools for metabolic engineering and biomedical analysis to determine the in vivo cellular state. Especially, the application of super(13)C isotopes allows comprehensive insights into the functional operation of cellular metabolism. Compared to single MS, tandem mass spectrometry (MS/MS) provides more detailed and accurate measurements of the metabolite enrichment patterns (tandem mass isotopomers), increasing the accuracy of metabolite concentration measurements and metabolic flux estimation. MS-type data from isotope labeling experiments is biased by naturally occurring stable isotopes (C, H, N, O, etc.). In particular, GC-MS(/MS) requires derivatization for the usually non-volatile intracellular metabolites introducing additional natural isotopes leading to measurements that do not directly represent the carbon labeling distribution. To make full useof LC- and GC-MS/MS mass isotopomer measurements, the influence of natural isotopes has to be eliminated (corrected). Our correction approach is analyzed for the two most common applications; super(13)C fluxomics and isotope dilution mass spectrometry (IDMS) based metabolomics. Natural isotopes can have an impact on the calculated flux distribution which strongly depends on the substrate labeling and the actual flux distribution. Second, we show that in IDMS based metabolomics natural isotopes lead to underestimated concentrations that can and should be corrected with a nonlinear calibration. Our simulations indicate that the correction for natural abundance in isotope based fluxomics and quantitative metabolomics is essential for correct data interpretation. Biotechnol. Bioeng. 2016; 113: 1137-1147. Fluxomics and metabolomics have become crucial tools for metabolic engineering and biomedical analysis. The authors focus on the first steps in data processing of MS/MS measurements, namely eliminating the effect of natural isotopes that are inherently measured together with the carbon mass isotopomers. This step should be included for unbiased super(13)C flux analysis as well as metabolomics studies.
ISSN:0006-3592
1097-0290
DOI:10.1002/bit.25859