Dynamic Genome-Scale Metabolic Modeling of the Yeast Pichia Pastoris

Abstract

Pichia pastoris shows physiological advantages for the production of recombinant proteins compared to other commonly used cell factories. This yeast is mostly grown in dynamic cultivation systems, where the cell’s environment is continuously changing and many variables influence process productivity. In this context, a model capable of explaining and predicting cell behavior for the rational design of bioprocesses is highly desirable. Currently, there are five genome-scale metabolic reconstructions of P. pastoris, which have been used to predict extracellular cell behavior in stationary conditions.Results: In this work, we assembled and evaluated a dynamic genome-scale metabolic model for glucose-limited, aerobic cultivations of Pichia pastoris. Starting from an initial structure for both, batch and fed-batch configurations, we performed pre/post regression diagnostics to determine identifiability, significance and sensitivity issues between model parameters. Once identified, the non-relevant parameters were iteratively fixed until an a priori robust modeling structure was found for both types of cultivation. Next, the robustness of these structures was confirmed by calibrating new datasets, where no parametric problems appeared. Afterwards, the model was validated for the prediction of batch and fed-batch dynamics in the studied conditionsLastly, the model was employed to unravel genetic and process engineering strategies to improve the heterologous production of recombinant Human Serum Albumin (HSA. Simulation of single knock-outs indicated that deviation of carbon towards cysteine and tryptophan formation improves HSA production. In particular, the deletion of methylene tetrahydrofolate dehydrogenase could increase the HSA volumetric productivity by 630%. Moreover, given specific bioprocess limitations and strain characteristics, the model suggests that implementation of a decreasing specific growth rate during the feed phase of a fed-batch culture results in a 25% increase of the volumetric productivity of the protein.Conclusion: in this work, we formulated a dynamic genome scale metabolic model of Pichia pastoris that yields reasonable metabolic flux distributions throughout dynamic cultivations. The model can be used to calibrate experimental data and to rationally propose molecular, as well as process engineering strategies to improve the performance of a biotechnological process in P. pastoris.