Literature DB >> 16325332

Qualitative simulation of the carbon starvation response in Escherichia coli.

Delphine Ropers1, Hidde de Jong, Michel Page, Dominique Schneider, Johannes Geiselmann.   

Abstract

In case of nutritional stress, like carbon starvation, Escherichia coli cells abandon their exponential-growth state to enter a more resistant, non-growth state called stationary phase. This growth-phase transition is controlled by a genetic regulatory network integrating various environmental signals. Although E. coli is a paradigm of the bacterial world, it is little understood how its response to carbon starvation conditions emerges from the interactions between the different components of the regulatory network. Using a qualitative method that is able to overcome the current lack of quantitative data on kinetic parameters and molecular concentrations, we model the carbon starvation response network and simulate the response of E. coli cells to carbon deprivation. This allows us to identify essential features of the transition between exponential and stationary phase and to make new predictions on the qualitative system behavior following a carbon upshift.

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Year:  2005        PMID: 16325332     DOI: 10.1016/j.biosystems.2005.10.005

Source DB:  PubMed          Journal:  Biosystems        ISSN: 0303-2647            Impact factor:   1.973


  21 in total

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5.  Hierarchical analysis of piecewise affine models of gene regulatory networks.

Authors:  Laurent Tournier; Jean-Luc Gouzé
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Review 7.  Mathematical modeling: bridging the gap between concept and realization in synthetic biology.

Authors:  Yuting Zheng; Ganesh Sriram
Journal:  J Biomed Biotechnol       Date:  2010-05-30

8.  The carbon assimilation network in Escherichia coli is densely connected and largely sign-determined by directions of metabolic fluxes.

Authors:  Valentina Baldazzi; Delphine Ropers; Yves Markowicz; Daniel Kahn; Johannes Geiselmann; Hidde de Jong
Journal:  PLoS Comput Biol       Date:  2010-06-10       Impact factor: 4.475

9.  A computational framework for qualitative simulation of nonlinear dynamical models of gene-regulatory networks.

Authors:  Liliana Ironi; Luigi Panzeri
Journal:  BMC Bioinformatics       Date:  2009-10-15       Impact factor: 3.169

10.  A service-oriented architecture for integrating the modeling and formal verification of genetic regulatory networks.

Authors:  Pedro T Monteiro; Estelle Dumas; Bruno Besson; Radu Mateescu; Michel Page; Ana T Freitas; Hidde de Jong
Journal:  BMC Bioinformatics       Date:  2009-12-30       Impact factor: 3.169

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