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.

journal_name

Genome Res

journal_title

Genome research

authors

Bundy JG,Papp B,Harmston R,Browne RA,Clayson EM,Burton N,Reece RJ,Oliver SG,Brindle KM

doi

10.1101/gr.5662207

subject

Has Abstract

pub_date

2007-04-01 00:00:00

pages

510-9

issue

4

eissn

1088-9051

issn

1549-5469

pii

gr.5662207

journal_volume

17

pub_type

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