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Natural isotope correction of MS/MS measurements for metabolomics and 13 C fluxomics
Author(s) -
Niedenführ Sebastian,
ten Pierick Angela,
van Dam Patricia T.N.,
SuarezMendez Camilo A.,
Nöh Katharina,
Wahl S. Aljoscha
Publication year - 2016
Publication title -
biotechnology and bioengineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 189
eISSN - 1097-0290
pISSN - 0006-3592
DOI - 10.1002/bit.25859
Subject(s) - metabolomics , isotopomers , isotope , chemistry , metabolic flux analysis , stable isotope ratio , mass spectrometry , isotope dilution , metabolite , metabolome , tandem mass spectrometry , isotope ratio mass spectrometry , flux (metallurgy) , analytical chemistry (journal) , chromatography , metabolism , biochemistry , physics , organic chemistry , quantum mechanics , molecule
Fluxomics and metabolomics are crucial tools for metabolic engineering and biomedical analysis to determine the in vivo cellular state. Especially, the application of 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; 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. © 2015 Wiley Periodicals, Inc.