Thermodynamic principles governing metabolic operation : inference, analysis, and prediction

The principles governing metabolic flux are poorly understood. Because diverse organisms show similar metabolic flux patterns, we hypothesized that fundamental thermodynamic constraints might shape cellular metabolism. We developed a constraint-based model for Saccharomyces cerevisiae that included a comprehensive description of biochemical thermodynamics and a Gibbs energy balance. Nonlinear regression analyses of quantitative metabolome and physiology data showed that there is an upper limit for the cellular entropy transfer rate. Applying this limit in flux balance analyses with growth maximization as the objective, our model correctly predicted the physiology, intracellular metabolic fluxes, and maximal growth rates for different glucose uptake rates and carbon sources. Thus, reaction stoichiometry, fundamental thermodynamic constraints, and the objective of growth maximization shape metabolic fluxes in yeast.Then, we combined this model with isotopomer balancing in order to quantify metabolic fluxes in S. cerevisiae. This statistical method allowed us to combine a wide range of different experimental data, i.e. extracellular rates, metabolite concentrations, standard Gibbs energies of reactions, and 13C based isotopomer patterns, and estimated with a minimal set of assumptions the metabolic fluxes along with their confidence intervals, thereby delivering a precise view on the true flux space. Further, this method also enabled us to estimate the ratio of the forward and backward fluxes through enzymatic reactions, opening the door towards identifying kinetic rates laws in vivo.With this work, we can now exactly quantify and predict cellular metabolism. These capabilities will greatly facilitate fundamental research and the industrial development of microbial production strains