Abstract
| Original language | English |
|---|---|
| Article number | e00097 |
| Journal | Metabolic Engineering Communications |
| Volume | 9 |
| Number of pages | 11 |
| ISSN | 2214-0301 |
| DOIs | |
| Publication status | Published - 2019 |
Keywords
- Genome-scale metabolic model
- Chinese hamster ovary
- Flux distribution
- Mathematical modeling
- Metabolic engineering
Cite this
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Application of a genome-scale model in tandem with enzyme assays for identification of metabolic signatures of high and low CHO cell producers. / Calmels, Cyrielle; Arnoult, Solène; Ben Yahia, Bassem; Malphettes, Laetitia; Andersen, Mikael Rørdam.
In: Metabolic Engineering Communications, Vol. 9, e00097, 2019.Research output: Contribution to journal › Journal article › Research › peer-review
TY - JOUR
T1 - Application of a genome-scale model in tandem with enzyme assays for identification of metabolic signatures of high and low CHO cell producers
AU - Calmels, Cyrielle
AU - Arnoult, Solène
AU - Ben Yahia, Bassem
AU - Malphettes, Laetitia
AU - Andersen, Mikael Rørdam
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
KW - Genome-scale metabolic model
KW - Chinese hamster ovary
KW - Flux distribution
KW - Mathematical modeling
KW - Metabolic engineering
U2 - 10.1016/j.mec.2019.e00097
DO - 10.1016/j.mec.2019.e00097
M3 - Journal article
VL - 9
JO - Metabolic Engineering Communications
JF - Metabolic Engineering Communications
SN - 2214-0301
M1 - e00097
ER -