Abstract
Tracking metabolic profiles has the potential to reveal crucial enzymatic steps that could be targeted in the drug discovery process. It is of special importance for various types of cancer known to be associated with substantial rewiring of metabolic networks. Here we introduce an integrated approach for the analysis of metabolome that allows us to simultaneously assess pathway activities (fluxes) and concentrations of a large number of the key components involved in central metabolism of human cells. This is accomplished by in vivo labeling with [U-13C]glucose followed by two-dimensional nuclear magnetic resonance (NMR) spectroscopy and gas chromatography-mass spectrometry (GC-MS) analysis. A comprehensive isotopomer model was developed, which enabled us to compare fluxes through the key central metabolic pathways including glycolysis, pentose phosphate pathway, tricarboxylic acid cycle, anaplerotic reactions, and biosynthetic pathways of fatty acids and amino acids. The validity and strength of this approach is illustrated by its application to a number of perturbations to breast cancer cells, including exposure to hypoxia, drug treatment, and tumor progression. We observed significant differences in the activities of specific metabolic pathways resulting from these perturbations and providing new mechanistic insights. Based on these findings we conclude that the developed metabolomic approach constitutes a promising analytical tool for revealing specific metabolic phenotypes in a variety of cell types and pathological conditions.
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Acknowledgements
This work was supported by Grants from the National Cancer Institute (P30 CA030199) and from the National Institutes of Health (U54 RR020843 (JWS), R01 AI059146 (AO), and R01 CA108959 (JWS)). Chen Yang was supported by a fellowship from the California Breast Cancer Research Program (12FB-0100).
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Chen Yang and Adam D. Richardson contributed equally to this work.
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Yang, C., Richardson, A.D., Osterman, A. et al. Profiling of central metabolism in human cancer cells by two-dimensional NMR, GC-MS analysis, and isotopomer modeling. Metabolomics 4, 13–29 (2008). https://doi.org/10.1007/s11306-007-0094-y
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DOI: https://doi.org/10.1007/s11306-007-0094-y