Combined Analysis of NMR and MS Spectra (CANMS)

Mei Chong, Anusha Jayaraman, Silvia Marin, Vitaly Selivanov, Pedro R. de Atauri Carulla, Daniel A. Tennant, Marta Cascante*, Ulrich L. Günther, Christian Ludwig

*Corresponding author for this work

Abstract

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.

Original languageEnglish
JournalAngewandte Chemie - International Edition
Volume56
Issue number15
Pages (from-to)4140-4144
Number of pages5
ISSN1433-7851
DOIs
Publication statusPublished - 03.04.2017

Funding

Mei Chong and Anusha Jayaraman were supported by the EU grant METAFLUX FP7-PEOPLE-ITN-2010?264780. Ulrich G?nther and Marta Cascante acknowledge support from the European Commission (Metaflux FP7-PEOPLE-ITN-2010-264780 and Cosmos EC- 312941). Marta Cascante also acknowledges the Spanish Ministerio de Economia y Competitividad (SAF2014-56059-R), the Ag?ncia de Gesti? O'Ajuts Universitaris i de Recerca (AGAUR) Generalitat de Catalunya (2014SGR1017), and the support received through the prize ?ICREA Academia? for excellence in research, funded by ICREA foundation?Generalitat de Catalunya. Christian Ludwig acknowledges support by the metabolic tracer analysis core (MTAC) at the University of Birmingham. We also thank T. J. Ragan for helping with NUS data processing. The authors thank the Wellcome Trust for supporting the HWB-NMR facility in Birmingham.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Research Areas and Centers

  • Academic Focus: Center for Infection and Inflammation Research (ZIEL)

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