Amino Acid Requirements of the Chinese Hamster Ovary Cell Metabolism during Recombinant Protein Production

Abstract

Majority of biopharmaceutical drugs today are produced by Chinese hamster ovary (CHO) cells, which have been the standard industry host for the past decades. To produce and secrete a substantial amount of the target recombinant proteins the CHO cells must be provided with suitable growth conditions and provided with the necessary nutrients. Amino acids play a key role in this as the building blocks of proteins, playing important roles in a large number of metabolic pathways and being important sources of nitrogen as well as carbon under certain conditions. In this study exploratory analysis of the amino acid requirements of CHO cells was carried out using metabolic modelling approaches. Flux balance analysis was employed to evaluate the optimal distribution of fluxes in a genome-scale model of CHO cells to gain information on the cells' metabolic response in silico.The results showed that providing non-essential amino acids (NEAAs) has a positive effect on CHO cell biomass production and that cysteine as well as tyrosine play a fundamental role in this.This implies that extracellular provision of NEAAs limits the extent of energy loss in amino acid biosynthetic pathways and renders additional reducing power available for other biological processes.Detailed analysis of the possible secretion and uptake of D-serine in the CHO model was also performed and its influence on the rest of the metabolism mapped out, which revealed results matching various existing literature. This is interesting since no mention of D-serine in regard to CHO cells was found in current literature, as well as the fact that this opens up the possibility of using the model for better understanding of certain disorders in higher up organisms that have been implicated with D-serine, such as motor neuron and cognitive degeneration. Finally, outcome from the model optimisation of different recombinant proteins demonstrated clearly how the difference in protein structure and size can influence the production outcome. These results show that systematic and model-based approaches have great potential for broad de novo exploration as well as being able to handle the cellular burden associated with the production of different types of recombinant protein.

A Metabolomics Approach to Increasing Chinese Hamster Ovary (CHO) Cell Productivity

“…Meanwhile, enriched pathways for metabolites that only correlated with growth were aminoacyl-tRNA biosynthesis and tyrosine metabolism (data not shown). The latter is consistent with a recent study reporting a beneficial impact of tyrosine on cell growth [26].…”

“…Meanwhile, enriched pathways for metabolites that only correlated with growth were aminoacyl-tRNA biosynthesis and tyrosine metabolism (data not shown). The latter is consistent with a recent study reporting a beneficial impact of tyrosine on cell growth [26]. In general, metabolites significantly correlating with qP had positive associations (higher extracellular metabolite levels correlated with higher qP), while those significantly correlating with growth had negative associations (Figure 2B).…”

Incorporating RNA‐Seq transcriptomics into glycosylation‐integrating metabolic network modelling kinetics: Multiomic Chinese hamster ovary (CHO) cell bioreactors

“…On the other hand, nonessential amino acids can be synthesized by cells to partially or fully meet their growth needs. In the case of recombinant CHO cell lines, the production of amino acids alone may not be sufficient to balance amino acid consumption, therefore amino acid supplementation is needed to maximize recombinant protein production (Carrillo‐Cocom et al, 2015; Traustason, 2019).…”

Computer-Aided Strategies for Determining the Amino Acid Composition of Medium for Chinese Hamster Ovary Cell-Based Biomanufacturing Platforms

“…Furthermore, the amino acid requirements of the medium did not match with the amino acid content of the antibody product indicating that blindly increasing the composition of the amino acids with the highest composition in the target protein was not necessarily the best strategy. This indicated that optimization of the amino acid formulation of the medium is a multi-parametric problem, which necessitates taking metabolic complexity into account, in order to narrow down the search space for experimental analysis [64].…”