title: 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.
authors.affiliation: Department of Biochemistry, University of Cambridge, Cambridge, UK.
authors.forename: Jacob G
authors.initials: JG
authors.lastname: Bundy
authors.forename: Balázs
authors.initials: B
authors.lastname: Papp
authors.forename: Rebecca
authors.initials: R
authors.lastname: Harmston
authors.forename: Roy A
authors.initials: RA
authors.lastname: Browne
authors.forename: Edward M
authors.initials: EM
authors.lastname: Clayson
authors.forename: Nicola
authors.initials: N
authors.lastname: Burton
authors.forename: Richard J
authors.initials: RJ
authors.lastname: Reece
authors.forename: Stephen G
authors.initials: SG
authors.lastname: Oliver
authors.forename: Kevin M
authors.initials: KM
authors.lastname: Brindle
mesh_terms: D005800:Genes, Fungal; D016681:Genome, Fungal; D006019:Glycolysis; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D053858:Metabolic Networks and Pathways; D008954:Models, Biological; D009154:Mutation; D011392:Proline / Q000378:metabolism; D011743:Pyrimidines / Q000096:biosynthesis / Q000378:metabolism; D012441:Saccharomyces cerevisiae / Q000235:genetics / Q000378:metabolism*; D029701:Saccharomyces cerevisiae Proteins / Q000235:genetics / Q000378:metabolism; D014199:Trehalose / Q000096:biosynthesis / Q000378:metabolism
chemical_list: D011743:Pyrimidines; D029701:Saccharomyces cerevisiae Proteins; D011392:Proline; D014199:Trehalose; C030986:pyrimidine