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The methylotrophic yeast Pichia pastoris is widely used for production of recombinant proteins. Here we characterize a vitamin-sensitive regulatory sequence, which can be controlled independently of the main culture medium compounds such as carbon, nitrogen, or phosphor source. The THI11 promoter (P ) sequence derives from a gene involved in biosynthesis of thiamine. For characterization, a P. pastoris strain expressing recombinant human serum albumin under control of P was grown in the controlled environment of a bioreactor. The thiamine sensitivity of P was proven and specified in batch cultures containing different amounts of extracellular thiamine. Under non-repressing conditions P offers a constitutive expression pattern with growth rate dependent product formation. Furthermore, promoter activity and thus product formation can be repressed for a desired period of time by supplementing the culture with a pre-defined amount of exogenous thiamine. Once a threshold of biomass is reached, P driven expression starts autonomously without external intervention. Based on these findings a tailor-made process strategy was developed and experimentally verified. Additionally, we compared the THI11 promoter with the commonly used GAP promoter. In conclusion, the THI11 promoter is a versatile and easy to control regulatory sequence which enables the realization of novel protein production strategies. Biotechnol. Bioeng. 2016;113: 2633-2643. © 2016 Wiley Periodicals, Inc.

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Chinese hamster ovary (CHO) cells are the leading platform for the production of biopharmaceuticals with human-like glycosylation. The standard practice for cell line generation relies on trial and error approaches such as adaptive evolution and high-throughput screening, which typically take several months. Metabolic modeling could aid in designing better producer cell lines and thus shorten development times. The genome-scale metabolic model (GSMM) of CHO can accurately predict growth rates. However, in order to predict rational engineering strategies it also needs to accurately predict intracellular fluxes. In this work we evaluated the agreement between the fluxes predicted by parsimonious flux balance analysis (pFBA) using the CHO GSMM and a wide range of 13C metabolic flux data from literature. While glycolytic fluxes were predicted relatively well, the fluxes of tricarboxylic acid (TCA) cycle were vastly underestimated due to too low energy demand. Inclusion of computationally estimated maintenance energy significantly improved the overall accuracy of intracellular flux predictions. Maintenance energy was therefore determined experimentally by running continuous cultures at different growth rates and evaluating their respective energy consumption. The experimentally and computationally determined maintenance energy were in good agreement. Additionally, we compared alternative objective functions (minimization of uptake rates of seven nonessential metabolites) to the biomass objective. While the predictions of the uptake rates were quite inaccurate for most objectives, the predictions of the intracellular fluxes were comparable to the biomass objective function.

Chinese hamster ovary (CHO) cells are the leading platform for the production of biopharmaceuticals with human-like glycosylation. The standard practice for cell line generation relies on trial and error approaches such as adaptive evolution and high-throughput screening, which typically take several months. Metabolic modeling could aid in designing better producer cell lines and thus shorten development times. The genome-scale metabolic model (GSMM) of CHO can accurately predict growth rates. However, in order to predict rational engineering strategies it also needs to accurately predict intracellular fluxes. In this work we evaluated the agreement between the fluxes predicted by pFBA using the CHO GSMM and a wide range of 13C metabolic flux data from literature. While glycolytic fluxes were predicted relatively well, the fluxes of tricarboxylic acid (TCA) cycle were vastly underestimated due to too low energy demand. Inclusion of computationally estimated maintenance energy significantly improved the overall accuracy of intracellular flux predictions. Maintenance energy was therefore determined experimentally by running continuous cultures at different growth rates and evaluating their respective energy consumption. The experimentally and computationally determined maintenance energy were in good agreement. Additionally, we compared alternative objective functions (minimization of uptake rates of seven nonessential metabolites) to the biomass objective. While the predictions of the uptake rates were quite inaccurate for most objectives, the predictions of the intracellular fluxes were comparable to the biomass objective function.