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

Valentina Baldazzi (1) , Delphine Ropers (1) , Yves Markowicz (1, 2) , Daniel Kahn (3) , Johannes Geiselmann (1, 2) , Hidde de Jong (1)

1 IBIS - Modeling, simulation, measurement, and control of bacterial regulatory networks
2 LAPM - Laboratoire Adaptation et pathogénie des micro-organismes [Grenoble]
3 BPGE - Bioinformatique, phylogénie et génomique évolutive

Gene regulatory networks consist of direct interactions but also include indirect interactions mediated by metabolites and signaling molecules. We describe how these indirect interactions can be derived from a model of the underlying biochemical reaction network, using weak time-scale assumptions in combination with sensitivity criteria from metabolic control analysis. We apply this approach to a model of the carbon assimilation network in Escherichia coli. Our results show that the derived gene regulatory network is densely connected, contrary to what is usually assumed. Moreover, the network is largely sign-determined, meaning that the signs of the indirect interactions are fixed by the flux directions of biochemical reactions, independently of specific parameter values and rate laws. An inversion of the fluxes following a change in growth conditions may affect the signs of the indirect interactions though. This leads to a feedback structure that is at the same time robust to changes in the kinetic properties of enzymes and that has the flexibility to accommodate radical changes in the environment.

Mots clés: Gene Regulatory Networks; Glycolysis; Biological; Signal Transduction; Algorithms; Gluconeogenesis; Escherichia coli; Carbon; Models; Allosteric Regulation

Domaines: Bio-Informatique, Biologie Systémique [q-bio.QM]; Bio-informatique [q-bio.QM]; Biochimie, Biologie Moléculaire

Valentina Baldazzi, Delphine Ropers, Yves Markowicz, Daniel Kahn, Johannes Geiselmann, et al.. The carbon assimilation network in Escherichia coli is densely connected and largely sign-determined by directions of metabolic fluxes.. PLoS Computational Biology, 2010, 6 (6), pp.e1000812. ⟨10.1371/journal.pcbi.1000812⟩. ⟨inria-00527140⟩