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Home page > Research > Metabolic Genomics Group > Computational Systems Biology (NeMo) > Coupling of metabolic flux > Coupling of metabolic flux

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Coupling of metabolic flux

Two reactions which immediately follow each other in a metabolic pathway will have a tendency to function in a concerted manner: the flux of material in the first determines the flux of material in the second. This intuitive observation may be generalized to ensembles of two or more reactions which are not necessarily neighboring in the metabolic network. In a given chemical environment, the structure and stochiometry of the network induce constraints in this way in the coupling between reactions [* Burgard AP & al. (2004)], i.e. the dependences between the flux of these reactions are valid for all states of the cell.
  The project aims on one hand to identify these coupling constraints, and on the other hand, to evaluate the effects of this on the organization of the regulation of reactions or on the evolutionary history of the genes involved. We will first explore the variability of coupling constraints for Escherichia coli with changes in the biochemical environment by a series of in silico experiments. A large portion of these couplings turn out to be independent of the medium, and the ensembles of coupled reactions present a great similarity with classical elementary metabolic pathways. Furthermore, we observe ensembles of constraints which are specific to certain categories of environments. This enables classification of environments into groups according to their effects on metabolic function, and to locate metabolic branch points. Next we will try to evaluate the eventual impact of metabolic constraints on the evolution of bacterial genomes. Does a constraint that involves two reactions which function at equal or proportional flux lead the organism to adapt its regulatory system to this ? To attempt to answer this question, the team is developing methods of comparative analysis of metabolic models.

  [*] Burgard AP, Nikolaev EV, et al.
  “Flux coupling analysis of genome-scale metabolic network reconstructions.
  Genome Res. 2004. 14(2): 301-12.

Last update on 22 January 2008

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