Importance of metabolic coupling for the dynamics of gene expression following a diauxic shift in Escherichia coli.

Gene regulatory networks consist of direct interactions, but also include indirect interactions mediated by metabolism. We investigate to which extent these indirect interactions arising from metabolic coupling influence the dynamics of the system. To this end, we build a qualitative model of the gene regulatory network controlling carbon assimilation in Escherichia coli, and use this model to study the changes in gene expression following a diauxic shift from glucose to acetate. In particular, we compare the relative variation in the steady-state concentrations of enzymes and transcription regulators during growth on glucose and acetate, as well as the dynamic response of gene expression to the exhaustion of glucose and the subsequent assimilation of acetate. We find significant differences between the dynamics of the system in the absence and presence of metabolic coupling. This shows that interactions arising from metabolic coupling cannot be ignored when studying the dynamics of gene regulatory networks.

[1]  M. Keyhan,et al.  The σS level in starving Escherichia coli cells increases solely as a result of its increased stability, despite decreased synthesis , 1997, Molecular microbiology.

[2]  Nan Xiao,et al.  Integrating metabolic, transcriptional regulatory and signal transduction models in Escherichia coli , 2008, Bioinform..

[3]  M. Araúzo-Bravo,et al.  Effect of cra gene knockout together with edd and iclR genes knockout on the metabolism in Escherichia coli , 2008, Archives of Microbiology.

[4]  Hidde de Jong,et al.  Symbolic reachability analysis of genetic regulatory networks using discrete abstractions , 2008, Autom..

[5]  V. Venturi.  Control of rpoS transcription in Escherichia coli and Pseudomonas: why so different? , 2003, Molecular microbiology.

[6]  Peter D. Karp,et al.  EcoCyc: a comprehensive database of Escherichia coli biology , 2010, Nucleic Acids Res..

[7]  J. Leigh,et al.  Nitrogen regulation in bacteria and archaea. , 2007, Annual review of microbiology.

[8]  Hidde de Jong,et al.  The Carbon Assimilation Network in Escherichia coli Is Densely Connected and Largely Sign-Determined by Directions of Metabolic Fluxes , 2010, PLoS Comput. Biol..

[9]  Hidde de Jong,et al.  Genetic Network Analyzer: qualitative simulation of genetic regulatory networks , 2003, Bioinform..

[10]  Julio Collado-Vides,et al.  Identification of regulatory network topological units coordinating the genome-wide transcriptional response to glucose in Escherichia coli , 2007, BMC Microbiology.

[11]  D. Schneider,et al.  Qualitative simulation of the carbon starvation response in Escherichia coli. , 2006, Bio Systems.

[12]  Global Gene Regulation in Metabolic Networks , 2011 .

[13]  R. Sharan,et al.  A genome-scale computational study of the interplay between transcriptional regulation and metabolism , 2007, Molecular systems biology.

[14]  A Kremling,et al.  Comment on mathematical models which describe transcription and calculate the relationship between mRNA and protein expression ratio. , 2007, Biotechnology and bioengineering.

[15]  J. Giovannoni,et al.  Molecular biology of ethylene during tomato fruit development and maturation , 2008 .

[16]  M Chaves,et al.  Methods of robustness analysis for Boolean models of gene control networks. , 2006, Systems biology.

[17]  Peter K. Sorger,et al.  Logic-Based Models for the Analysis of Cell Signaling Networks† , 2010, Biochemistry.

[18]  El Houssine Snoussi.  Qualitative dynamics of piecewise-linear differential equations: a discrete mapping approach , 1989 .

[19]  C. Branlant,et al.  The strong efficiency of the Escherichia coli gapA P1 promoter depends on a complex combination of functional determinants. , 2004, The Biochemical journal.

[20]  R. Heinrich,et al.  The Regulation of Cellular Systems , 1996, Springer US.

[21]  Roderick Edwards,et al.  Dynamics in high-dimensional model gene networks , 2003, Signal Process..

[22]  H. D. Jong,et al.  Qualitative simulation of the initiation of sporulation in Bacillus subtilis , 2004, Bulletin of mathematical biology.

[23]  M. di Bernardo,et al.  Comparing different ODE modelling approaches for gene regulatory networks. , 2009, Journal of theoretical biology.

[24]  Katy C. Kao,et al.  Global Expression Profiling of Acetate-grown Escherichia coli * , 2002, The Journal of Biological Chemistry.

[25]  Radu Mateescu,et al.  Temporal logic patterns for querying dynamic models of cellular interaction networks , 2008, ECCB.

[26]  Markus J. Herrgård,et al.  Integrating high-throughput and computational data elucidates bacterial networks , 2004, Nature.

[27]  Judith B. Zaugg,et al.  Bacterial adaptation through distributed sensing of metabolic fluxes , 2010, Molecular systems biology.

[28]  Hidde de Jong,et al.  Model Reduction Using Piecewise-Linear Approximations Preserves Dynamic Properties of the Carbon Starvation Response in Escherichia coli , 2011, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[29]  D. Lauffenburger,et al.  Discrete logic modelling as a means to link protein signalling networks with functional analysis of mammalian signal transduction , 2009, Molecular systems biology.

[30]  P. Brazhnik,et al.  Gene networks: how to put the function in genomics. , 2002, Trends in biotechnology.

[31]  M. Estelle,et al.  Recent advances and emerging trends in plant hormone signalling , 2009, Nature.

[32]  Liliana Ironi,et al.  A computational framework for qualitative simulation of nonlinear dynamical models of gene-regulatory networks , 2009, BMC Bioinformatics.

[33]  Thomas Mestl,et al.  A methodological basis for description and analysis of systems with complex switch-like interactions , 1998, Journal of mathematical biology.

[34]  Víctor de Lorenzo,et al.  The logicome of environmental bacteria: merging catabolic and regulatory events with Boolean formalisms. , 2011, Environmental microbiology.

[35]  K. Shimizu,et al.  Global metabolic regulation analysis for Escherichia coli K12 based on protein expression by 2-dimensional electrophoresis and enzyme activity measurement , 2003, Applied Microbiology and Biotechnology.

[36]  E. Klipp,et al.  Integrative model of the response of yeast to osmotic shock , 2005, Nature Biotechnology.

[37]  Michael Hecker,et al.  Gene regulatory network inference: Data integration in dynamic models - A review , 2009, Biosyst..

[38]  F. Blattner,et al.  Global Transcriptional Programs Reveal a Carbon Source Foraging Strategy by Escherichia coli*♦ , 2005, Journal of Biological Chemistry.

[39]  Matthias Reuss,et al.  Topology of the global regulatory network of carbon limitation in Escherichia coli. , 2007, Journal of biotechnology.

[40]  J. Sepulchre,et al.  Modeling the onset of virulence in a pectinolytic bacterium. , 2007, Journal of theoretical biology.

[41]  C. Chassagnole,et al.  Dynamic modeling of the central carbon metabolism of Escherichia coli. , 2002, Biotechnology and bioengineering.

[42]  Giorgio Battistelli,et al.  Model-free Adaptive Switching Control of Uncertain Time-Varying Plants , 2011 .

[43]  James C Liao,et al.  A Global Regulatory Role of Gluconeogenic Genes in Escherichia coli Revealed by Transcriptome Network Analysis* , 2005, Journal of Biological Chemistry.

[44]  M. Page,et al.  Search for Steady States of Piecewise-Linear Differential Equation Models of Genetic Regulatory Networks , 2008, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[45]  Hidde de Jong,et al.  Modeling and Simulation of Genetic Regulatory Systems: A Literature Review , 2002, J. Comput. Biol..

[46]  Steffen Klamt,et al.  Transforming Boolean models to continuous models: methodology and application to T-cell receptor signaling , 2009, BMC Systems Biology.

[47]  H. Aiba,et al.  A lowered concentration of cAMP receptor protein caused by glucose is an important determinant for catabolite repression in Escherichia coli , 1993, Molecular microbiology.

[48]  C Reder,et al.  Metabolic control theory: a structural approach. , 1988, Journal of theoretical biology.

[49]  S. Bornholdt,et al.  The transition from differential equations to Boolean networks: a case study in simplifying a regulatory network model. , 2008, Journal of theoretical biology.

[50]  H. Bolouri.  Computational Modeling of Gene Regulatory Networks - A Primer , 2008 .

[51]  H. D. Jong,et al.  Qualitative simulation of genetic regulatory networks using piecewise-linear models , 2004, Bulletin of mathematical biology.

[52]  Martin Fussenegger,et al.  Modeling the Quorum Sensing Regulatory Network of Human‐Pathogenic Pseudomonas aeruginosa , 2004, Biotechnology progress.

[53]  Denis Thieffry,et al.  Logical modelling of cell cycle control in eukaryotes: a comparative study. , 2009, Molecular bioSystems.

[54]  M. Le Borgne,et al.  Topology and static response of interaction networks in molecular biology , 2006, Journal of The Royal Society Interface.

[55]  Hidde de Jong,et al.  Strategies for dealing with incomplete information in the modeling of molecular interaction networks , 2006, Briefings Bioinform..

[56]  R. Albert,et al.  Predicting Essential Components of Signal Transduction Networks: A Dynamic Model of Guard Cell Abscisic Acid Signaling , 2006, PLoS biology.

[57]  Andreas Kremling,et al.  A Quantitative Approach to Catabolite Repression in Escherichia coli* , 2006, Journal of Biological Chemistry.

[58]  U. Sauer,et al.  Cyclic AMP-Dependent Catabolite Repression Is the Dominant Control Mechanism of Metabolic Fluxes under Glucose Limitation in Escherichia coli , 2008, Journal of bacteriology.

[59]  Guy Karlebach,et al.  Modelling and analysis of gene regulatory networks , 2008, Nature Reviews Molecular Cell Biology.

[60]  Aurélien Naldi,et al.  Diversity and Plasticity of Th Cell Types Predicted from Regulatory Network Modelling , 2010, PLoS Comput. Biol..

[61]  L. Glass,et al.  The logical analysis of continuous, non-linear biochemical control networks. , 1973, Journal of theoretical biology.

[62]  T. Silhavy,et al.  Starvation for Different Nutrients in Escherichia coli Results in Differential Modulation of RpoS Levels and Stability , 2005, Journal of bacteriology.

[63]  M. Zanor,et al.  Systems Biology of Tomato Fruit Development: Combined Transcript, Protein, and Metabolite Analysis of Tomato Transcription Factor (nor, rin) and Ethylene Receptor (Nr) Mutants Reveals Novel Regulatory Interactions1[W][OA] , 2011, Plant Physiology.