Evaluation of predicted network modules in yeast metabolism using NMR-based metabolite profiling
Abstract
Genome-scale metabolic models promise important insights into cell function. However, the definition of pathways and functional network modules within these models, and in the biochemical literature in general, is often based on intuitive reasoning. Although mathematical methods have been proposed to identify modules, which are defined as groups of reactions with correlated fluxes, there is a need for experimental verification. We show here that multivariate statistical analysis of the NMR-derived intra- and extracellular metabolite profiles of single-gene deletion mutants in specific metabolic pathways in the yeast Saccharomyces cerevisiae identified outliers whose profiles were markedly different from those of the other mutants in their respective pathways. Application of flux coupling analysis to a metabolic model of this yeast showed that the deleted gene in an outlying mutant encoded an enzyme that was not part of the same functional network module as the other enzymes in the pathway. We suggest that metabolomic methods such as this, which do not require any knowledge of how a gene deletion might perturb the metabolic network, provide an empirical method for validating and ultimately refining the predicted network structure.
Footnotes
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↵3 Present address: Department of Biomolecular Medicine, Division of Surgery, Oncology, Reproductive Biology, and Anaesthetics, Faculty of Medicine, Sir Alexander Fleming Building, London SW7 2AZ, UK.
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↵4Corresponding author.
↵E-mail kmb{at}mole.bio.cam.ac.uk; fax 44-1223-766002.
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[Supplemental material is available online at www.genome.org.]
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Article published online before print. Article and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.5662207
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- Received June 19, 2006.
- Accepted January 3, 2007.
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Freely available online through the Genome Research Open Access option.
- Copyright © 2007, Cold Spring Harbor Laboratory Press
