The global transcriptional regulatory network for metabolism in Escherichia coli exhibits few dominant functional states.

TitleThe global transcriptional regulatory network for metabolism in Escherichia coli exhibits few dominant functional states.
Publication TypeJournal Article
Year of Publication2005
AuthorsBarrett CL, Herring CD, Reed JL, Palsson BØ
JournalProceedings of the National Academy of Sciences of the United States of America
PubMed Date2005 Dec 27
KeywordsBacterial Proteins, Carbon, Cell Physiological Phenomena, Cluster Analysis, Computational Biology, Computer Simulation, Environment, Escherichia coli, Escherichia coli Proteins, Gene Expression Regulation, Bacterial, Genes, Bacterial, Genome, Bacterial, Models, Biological, Oligonucleotide Array Sequence Analysis, Phenotype, Protein Structure, Tertiary, Software, Systems Biology, Transcription, Genetic

A principal aim of systems biology is to develop in silico models of whole cells or cellular processes that explain and predict observable cellular phenotypes. Here, we use a model of a genome-scale reconstruction of the integrated metabolic and transcriptional regulatory networks for Escherichia coli, composed of 1,010 gene products, to assess the properties of all functional states computed in 15,580 different growth environments. The set of all functional states of the integrated network exhibits a discernable structure that can be visualized in 3-dimensional space, showing that the transcriptional regulatory network governing metabolism in E. coli responds primarily to the available electron acceptor and the presence of glucose as the carbon source. This result is consistent with recently published experimental data. The observation that a complex network composed of 1,010 genes is organized to achieve few dominant modes demonstrates the utility of the systems approach for consolidating large amounts of genome-scale molecular information about a genome and its regulation to elucidate an organism's preferred environments and functional capabilities.

Alternate JournalProc. Natl. Acad. Sci. U.S.A.
PubMed ID16357206



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