Email updates

Keep up to date with the latest news and content from BMC Genomics and BioMed Central.

Open Access Research article

Metabolic modeling and analysis of the metabolic switch in Streptomyces coelicolor

Mohammad T Alam1, Maria E Merlo12, The STREAM Consortium, David A Hodgson3, Elizabeth MH Wellington3, Eriko Takano2 and Rainer Breitling14*

Author Affiliations

1 Groningen Bioinformatics Center, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Kerklaan 30, 9751 NN Haren, The Netherlands

2 Department of Microbial Physiology, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Kerklaan 30, 9751 NN Haren, The Netherlands

3 Department of Biological Sciences, University of Warwick, Gibbet Hill Road, Coventry CV4 7AL, UK

4 Integrative and Systems Biology, Faculty of Biomedical and Life Sciences, University of Glasgow, Glasgow G12 8QQ, UK

For all author emails, please log on.

BMC Genomics 2010, 11:202  doi:10.1186/1471-2164-11-202

Published: 26 March 2010

Abstract

Background

The transition from exponential to stationary phase in Streptomyces coelicolor is accompanied by a major metabolic switch and results in a strong activation of secondary metabolism. Here we have explored the underlying reorganization of the metabolome by combining computational predictions based on constraint-based modeling and detailed transcriptomics time course observations.

Results

We reconstructed the stoichiometric matrix of S. coelicolor, including the major antibiotic biosynthesis pathways, and performed flux balance analysis to predict flux changes that occur when the cell switches from biomass to antibiotic production. We defined the model input based on observed fermenter culture data and used a dynamically varying objective function to represent the metabolic switch. The predicted fluxes of many genes show highly significant correlation to the time series of the corresponding gene expression data. Individual mispredictions identify novel links between antibiotic production and primary metabolism.

Conclusion

Our results show the usefulness of constraint-based modeling for providing a detailed interpretation of time course gene expression data.