Application of a genome-scale model in tandem with enzyme assays for identification of metabolic signatures of high and low CHO cell producers

Cyrielle Calmels; Solène Arnoult; Bassem Ben Yahia; Laetitia Malphettes; Mikael Rørdam Andersen

doi:10.1016/j.mec.2019.e00097

Application of a genome-scale model in tandem with enzyme assays for identification of metabolic signatures of high and low CHO cell producers

Metab Eng Commun. 2019 Aug 1:9:e00097. doi: 10.1016/j.mec.2019.e00097. eCollection 2019 Dec.

Authors

Cyrielle Calmels^{1

2}, Solène Arnoult³, Bassem Ben Yahia¹, Laetitia Malphettes¹, Mikael Rørdam Andersen²

Affiliations

¹ Department of Upstream Process Sciences, UCB Pharma, Chemin du Foriest 1, 1420, Braine-l'Alleud, Belgium.
² Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 223, 2800, Kgs. Lyngby, Denmark.
³ Polytech Marseille, Parc scientifique et technologique de Luminy, 163 Avenue de Luminy, 13009, Marseille, France.

Abstract

Biopharmaceutical industrial processes are based on high yielding stable recombinant Chinese Hamster Ovary (CHO) cells that express monoclonal antibodies. However, the process and feeding regimes need to be adapted for each new cell line, as they all have a slightly different metabolism and product performance. A main limitation for accelerating process development is that the metabolic pathways underlying this physiological variability are not yet fully understood. This study describes the evolution of intracellular fluxes during the process for 4 industrial cell lines, 2 high producers and 2 low producers (n = 3), all of them producing a different antibody. In order to understand from a metabolic point of view the phenotypic differences observed, and to find potential targets for improving specific productivity of low producers, the analysis was supported by a tailored genome-scale model and was validated with enzymatic assays performed at different days of the process. A total of 59 reactions were examined from different key pathways, namely glycolysis, pentose phosphate pathway, TCA cycle, lipid metabolism, and oxidative phosphorylation. The intracellular fluxes did not show a metabolic correlation between high producers, but the degree of similitude observed between cell lines could be confirmed with additional experimental observations. The whole analysis led to a better understanding of the metabolic requirements for all the cell lines, allowed to the identification of metabolic bottlenecks and suggested targets for further cell line engineering. This study is a successful application of a curated genome-scale model to multiple industrial cell lines, which makes the metabolic model suitable for process platform.

Keywords: CHO, Chinese Hamster Ovary; Chinese hamster ovary; FBA, flux balance analysis; Flux distribution; GSM, genome-scale metabolic model; Genome-scale metabolic model; Mathematical modeling; Metabolic engineering; PPP, pentose phosphate pathway; TCA, tricarboxylic acid cycle; pFBA, parsimonious flux balance analysis.