Clostridium thermocellum is a potential candidate for consolidated bioprocessing due to its ability to consume and ferment cellulose to ethanol. However, ethanol titers currently obtained in wild-type and engineered strains are below industrial requirements for economic viability. Strategies for improving ethanol production have been determined computationally through the analysis of metabolic fluxes generated via constraint-based models of metabolism, and experimentally based on measured extracellular metabolite concentrations and yields. However, metabolic flux distributions elucidated using 13C labeling data have not been used to validate constraint-based model predictions. Furthermore, constraint-based models do not account for the kinetics, thermodynamics, and regulatory interactions that govern the metabolic function. Kinetic models can be used to explore network designs for increasing desired product yields while accounting for the aforementioned interactions. In this work, we elucidate the intracellular metabolic fluxes in wild-type C. thermocellum grown on cellobiose via 13C-metabolic flux analysis (13C-MFA). The resultant flux distribution is used in conjunction with mutant strain batch fermentation process yield data to construct a kinetic model of C. thermocellum core metabolism. Kinetic parameterization was carried out using the K-FIT parameter estimation algorithm. Our 13C-MFA results indicate that both pyruvatephosphate dikinase and the malate shunt are primary means for pyruvate generation. Kinetic model fitness was improved by an order of magnitude over a similar model-generated using genetic algorithm-based ensemble modeling (GA) parameterization method. Predictive capabilities, however, were significantly reduced compared to the GA model for both metabolite yield under nitrogen limited conditions, and intracellular metabolite concentrations under ethanol stress conditions.
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