A Consensus Genome-scale Reconstruction of Chinese Hamster Ovary Cell Metabolism

Hooman Hefzi, Kok Siong Ang, Michael Hanscho, Aarash Bordbar, David Ruckerbauer, Meiyappan Lakshmanan, Camila A. Orellana, Deniz Baycin-Hizal, Yingxiang Huang, Daniel Ley, Veronica S. Martinez, Sarantos Kyriakopoulos, Natalia E. Jiménez, Daniel C. Zielinski, Lake-Ee Quek, Tune Wulff, Johnny Arnsdorf, Shangzhong Li, Jae Seong Lee, Giuseppe PagliaNicolas Loira, Philipp N. Spahn, Lasse E. Pedersen, Jahir M. Gutierrez, Zachary A. King, Anne Mathilde Lund, Harish Nagarajan, Alex Thomas, Alyaa M. Abdel-Haleem, Juergen Zanghellini, Helene F. Kildegaard, Bjørn G. Voldborg, Ziomara P. Gerdtzen, Michael J. Betenbaugh, Bernhard O. Palsson, Mikael R. Andersen, Lars K. Nielsen, Nicole Borth, Dong-Yup Lee, Nathan E. Lewis

Research output: Contribution to journalArticlepeer-review

171 Scopus citations


Chinese hamster ovary (CHO) cells dominate biotherapeutic protein production and are widely used in mammalian cell line engineering research. To elucidate metabolic bottlenecks in protein production and to guide cell engineering and bioprocess optimization, we reconstructed the metabolic pathways in CHO and associated them with >1,700 genes in the Cricetulus griseus genome. The genome-scale metabolic model based on this reconstruction, iCHO1766, and cell-line-specific models for CHO-K1, CHO-S, and CHO-DG44 cells provide the biochemical basis of growth and recombinant protein production. The models accurately predict growth phenotypes and known auxotrophies in CHO cells. With the models, we quantify the protein synthesis capacity of CHO cells and demonstrate that common bioprocess treatments, such as histone deacetylase inhibitors, inefficiently increase product yield. However, our simulations show that the metabolic resources in CHO are more than three times more efficiently utilized for growth or recombinant protein synthesis following targeted efforts to engineer the CHO secretory pathway. This model will further accelerate CHO cell engineering and help optimize bioprocesses.
Original languageEnglish (US)
Pages (from-to)434-443.e8
JournalCell Systems
Issue number5
StatePublished - Nov 23 2016

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: National Institutes of Health[R35 GM119850]


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