Combined Analysis of NMR and MS Spectra (CANMS)

Cellular metabolism in mammalian cells represents a challenge for analytical chemistry in the context of current biomedical research. Mass spectrometry and NMR spectroscopy together with computational tools have been used to study metabolism in cells. Compartmentalization of metabolism complicates t...

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Veröffentlicht in:Angewandte Chemie International Edition 2017-04, Vol.56 (15), p.4140-4144
Hauptverfasser: Chong, Mei, Jayaraman, Anusha, Marin, Silvia, Selivanov, Vitaly, de Atauri Carulla, Pedro R., Tennant, Daniel A., Cascante, Marta, Günther, Ulrich L., Ludwig, Christian
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Sprache:eng
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Zusammenfassung:Cellular metabolism in mammalian cells represents a challenge for analytical chemistry in the context of current biomedical research. Mass spectrometry and NMR spectroscopy together with computational tools have been used to study metabolism in cells. Compartmentalization of metabolism complicates the interpretation of stable isotope patterns in mammalian cells owing to the superimposition of different pathways contributing to the same pool of analytes. This indicates a need for a model‐free approach to interpret such data. Mass spectrometry and NMR spectroscopy provide complementary analytical information on metabolites. Herein an approach that simulates 13C multiplets in NMR spectra and utilizes mass increments to obtain long‐range information is presented. The combined information is then utilized to derive isotopomer distributions. This is a first rigorous analytical and computational approach for a model‐free analysis of metabolic data applicable to mammalian cells. Complexity is no longer a problem: A model‐free isotopomer analysis of 13C‐enriched biological cell extracts has been developed. The combination of NMR and MS data in a single analysis enables a highly specific and accurate determination of 13C isotopomers from a complex mixture of metabolites, which can be used for the interpretation of metabolic pathways.
ISSN:1433-7851
1521-3773
DOI:10.1002/anie.201611634