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Determination of Flux Control Coefficients from transient metabolite concentrations.

ABSTRACT: Flux Control Coefficients have been used in the analysis of metabolic regulation for quantifying the effect of an enzyme on the overall steady-state flux. However, the experimental determination of these coefficients is very time-consuming, involving either determining the individual enzyme kinetics or perturbing the enzyme activity by genetic or other means. We developed a methodology that enables the determination of the Flux Control Coefficients from transient metabolite concentrations without knowing kinetic parameters. The transient states can be generated by changing the incubation conditions or adding the initial substrate. This approach is suitable for investigating metabolic regulation in vivo or multiple enzyme systems in vitro. It is particularly helpful if used in conjunction with n.m.r. measurements. The approach is based on a relationship between transient metabolite concentrations and the Flux Control Coefficients. The methodology has been improved from our previous results, and it is illustrated by three examples with simple pathway topologies.

SUBMITTER: Delgado J

PROVIDER: S-EPMC1130875 | biostudies-other | 1992 Mar

REPOSITORIES: biostudies-other

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Project description:BackgroundIn recent years, constrained optimization - usually referred to as flux balance analysis (FBA) - has become a widely applied method for the computation of stationary fluxes in large-scale metabolic networks. The striking advantage of FBA as compared to kinetic modeling is that it basically requires only knowledge of the stoichiometry of the network. On the other hand, results of FBA are to a large degree hypothetical because the method relies on plausible but hardly provable optimality principles that are thought to govern metabolic flux distributions.ResultsTo augment the reliability of FBA-based flux calculations we propose an additional side constraint which assures thermodynamic realizability, i.e. that the flux directions are consistent with the corresponding changes of Gibb's free energies. The latter depend on metabolite levels for which plausible ranges can be inferred from experimental data. Computationally, our method results in the solution of a mixed integer linear optimization problem with quadratic scoring function. An optimal flux distribution together with a metabolite profile is determined which assures thermodynamic realizability with minimal deviations of metabolite levels from their expected values. We applied our novel approach to two exemplary metabolic networks of different complexity, the metabolic core network of erythrocytes (30 reactions) and the metabolic network iJR904 of Escherichia coli (931 reactions). Our calculations show that increasing network complexity entails increasing sensitivity of predicted flux distributions to variations of standard Gibb's free energy changes and metabolite concentration ranges. We demonstrate the usefulness of our method for assessing critical concentrations of external metabolites preventing attainment of a metabolic steady state.ConclusionOur method incorporates the thermodynamic link between flux directions and metabolite concentrations into a practical computational algorithm. The weakness of conventional FBA to rely on intuitive assumptions about the reversibility of biochemical reactions is overcome. This enables the computation of reliable flux distributions even under extreme conditions of the network (e.g. enzyme inhibition, depletion of substrates or accumulation of end products) where metabolite concentrations may be drastically altered.

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Determination of Flux Control Coefficients from transient metabolite concentrations.

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