Thermodynamic and stoichiometric constraint-based inference of metabolic phenotypes

Here, we developed a new type of metabolic models resting on a mass and Gibbs energy balanced stoichiometric metabolic network reconstruction. With these models and experimental data, we estimated the Gibbs energy dissipated by cellular operations at various conditions. We found that the Gibbs energy dissipation rate reaches a plateau (i.e. has seemingly an upper limit). When constraining otherwise normal flux balance analysis by this identified limit in cellular Gibbs energy dissipation and maximizing for biomass production, we could correctly predict the switch from a respiratory metabolism towards a seemingly suboptimal fermentative metabolism as well as maximal growth rates for a variety of carbon sources. Thus, we conjectured that growth maximization constrained by a limited cellular Gibbs energy dissipation rate is the governing principle, which shaped the evolution of cellular metabolism across organisms and carbon sources. We speculate that the limit in Gibbs energy dissipation corresponds to a critical threshold of non-thermal intracellular motion.Further demonstrating the capabilities of this predictive method, we inferred phenotypic changes over the course of cell aging in S. cerevisiae. Here we found that cells switch with increasing age from a fermentative towards a respiratory metabolism, accompanied by drastic metabolic rearrangements.In summary we here present a thermodynamic principle thought to govern metabolic operation. Based on this finding we develop a computational method to predict cellular phenotypes