Literature DB >> 12006566

Transcriptional regulation in constraints-based metabolic models of Escherichia coli.

Markus W Covert1, Bernhard Ø Palsson.   

Abstract

Full genome sequences enable the construction of genome-scale in silico models of complex cellular functions. Genome-scale constraints-based models of Escherichia coli metabolism have been constructed and used to successfully interpret and predict cellular behavior under a range of conditions. These previous models do not account for regulation of gene transcription and thus cannot accurately predict some organism functions. Here we present an in silico model of the central E. coli metabolism that accounts for regulation of gene expression. This model accounts for 149 genes, the products of which include 16 regulatory proteins and 73 enzymes. These enzymes catalyze 113 reactions, 45 of which are controlled by transcriptional regulation. The combined metabolic/regulatory model can predict the ability of mutant E. coli strains to grow on defined media as well as time courses of cell growth, substrate uptake, metabolic by-product secretion, and qualitative gene expression under various conditions, as indicated by comparison with experimental data under a variety of environmental conditions. The in silico model may also be used to interpret dynamic behaviors observed in cell cultures. This combined metabolic/regulatory model is thus an important step toward the goal of synthesizing genome-scale models that accurately represent E. coli behavior.

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Year:  2002        PMID: 12006566     DOI: 10.1074/jbc.M201691200

Source DB:  PubMed          Journal:  J Biol Chem        ISSN: 0021-9258            Impact factor:   5.157


  103 in total

Review 1.  Thirteen years of building constraint-based in silico models of Escherichia coli.

Authors:  Jennifer L Reed; Bernhard Ø Palsson
Journal:  J Bacteriol       Date:  2003-05       Impact factor: 3.490

2.  Reconciling gene expression data with known genome-scale regulatory network structures.

Authors:  Markus J Herrgård; Markus W Covert; Bernhard Ø Palsson
Journal:  Genome Res       Date:  2003-10-14       Impact factor: 9.043

3.  The JAK-STAT signaling network in the human B-cell: an extreme signaling pathway analysis.

Authors:  Jason A Papin; Bernhard O Palsson
Journal:  Biophys J       Date:  2004-07       Impact factor: 4.033

4.  OptStrain: a computational framework for redesign of microbial production systems.

Authors:  Priti Pharkya; Anthony P Burgard; Costas D Maranas
Journal:  Genome Res       Date:  2004-11       Impact factor: 9.043

5.  Kinetic constraints for formation of steady states in biochemical networks.

Authors:  Junli Liu
Journal:  Biophys J       Date:  2005-02-24       Impact factor: 4.033

Review 6.  Gene expression profiling and the use of genome-scale in silico models of Escherichia coli for analysis: providing context for content.

Authors:  Nathan E Lewis; Byung-Kwan Cho; Eric M Knight; Bernhard O Palsson
Journal:  J Bacteriol       Date:  2009-04-10       Impact factor: 3.490

7.  Integrating metabolic, transcriptional regulatory and signal transduction models in Escherichia coli.

Authors:  Markus W Covert; Nan Xiao; Tiffany J Chen; Jonathan R Karr
Journal:  Bioinformatics       Date:  2008-07-10       Impact factor: 6.937

Review 8.  Harnessing nature's toolbox: regulatory elements for synthetic biology.

Authors:  Patrick M Boyle; Pamela A Silver
Journal:  J R Soc Interface       Date:  2009-03-04       Impact factor: 4.118

Review 9.  Systems-biology approaches for predicting genomic evolution.

Authors:  Balázs Papp; Richard A Notebaart; Csaba Pál
Journal:  Nat Rev Genet       Date:  2011-08-02       Impact factor: 53.242

10.  Lysine overproducing Corynebacterium glutamicum is characterized by a robust linear combination of two optimal phenotypic states.

Authors:  Meghna Rajvanshi; Kalyan Gayen; K V Venkatesh
Journal:  Syst Synth Biol       Date:  2013-04-17
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