Published on Tue Jul 20 2021

CHOmpact: a reduced metabolic model of Chinese hamster ovary cells with enhanced interpretability

Jimenez del Val, I., Kyriakopoulos, S., Albrecht, S., Stöckmann, H., Rudd, P. M., Polizzi, K. M., Kontoravdi, C.

Metabolic models have been instrumental in identifying genetic engineering targets and developing feeding strategies that optimise the growth and productivity of Chinese hamster ovary (CHO) cells. Despite their success, metabolic models of CHO cells still present considerable challenges.

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Abstract

Metabolic modelling has emerged as a key tool for the characterisation of biopharmaceutical cell culture processes. Metabolic models have also been instrumental in identifying genetic engineering targets and developing feeding strategies that optimise the growth and productivity of Chinese hamster ovary (CHO) cells. Despite their success, metabolic models of CHO cells still present considerable challenges. Genome scale metabolic models (GeMs) of CHO cells are very large (>6000 reactions) and are, therefore, difficult to constrain to yield physiologically consistent flux distributions. The large scale of GeMs also makes interpretation of their outputs difficult. To address these challenges, we have developed CHOmpact, a reduced metabolic network that encompasses 101 metabolites linked through 144 reactions. Our compact reaction network allows us to deploy multi-objective optimisation and ensure that the computed flux distributions are physiologically consistent. Furthermore, our CHOmpact model delivers enhanced interpretability of simulation results and has allowed us to identify the mechanisms governing shifts in the anaplerotic consumption of asparagine and glutamate as well as an important mechanism of ammonia detoxification within mitochondria. CHOmpact, thus, addresses key challenges of large-scale metabolic models and, with further development, will serve as a platform to develop dynamic metabolic models for the control and optimisation of biopharmaceutical cell culture processes.