Unraveling the Inhibitory Effects of Acetate on Ethanol Production in Cen.PK

Saccharomyces cerevisiae, besides being a model eukaryotic organism, is one of the most commonly used yeast species for production of bioethanol and other biofuels. Even though S. cerevisiae is a natively proficient ethanologenic yeast strain, the presence of weak acid inhibitors, such as acetic acid, found in cellulosic feedstocks for 2^nd generation bioethanol production has detrimental effects on its productivity.

In this study, we used the ORACLE (Optimization and Risk Analysis of Complex Living Entities) framework to unravel the metabolic impact of extracellular acetic acid on S. cerevisiae metabolism in order to generate metabolic engineering targets for improving ethanol production rates in the presence of acetic acid. For this objective, first we developed a consistently reduced core model (279 metabolites and 382 reactions) for S. cerevisiae, based on the recent genome scale model. Subsequently, we integrated thermodynamic and experimentally measured information about the metabolites concentrations and reaction fluxes, to identify thermodynamically feasible operational configurations of the network under different experimental conditions using the novel Flux Directionality Profile Analysis (FDPA) technique. We then used the ORACLE framework, to develop sets of log-linear kinetics models, which are stoichiometrically, thermodynamically, kinetically and physiologically consistent, to explore the flexibility and robustness of the operational states. Analysis of the models allowed us to identify: 1) the differences of the flux profiles between different doses of acetate during ethanol production in the CEN.PK strain; and 2) the optimal strategies to improve ethanol production under these different conditions.