| Autor: |
Gutierrez, Jahir M., Feizi, Amir, Li, Shangzhong, Kallehauge, Thomas B., Hefzi, Hooman, Grav, Lise M., Ley, Daniel, Baycin Hizal, Deniz, Betenbaugh, Michael J., Voldborg, Bjorn, Faustrup Kildegaard, Helene, Min Lee, Gyun, Palsson, Bernhard O., Nielsen, Jens, Lewis, Nathan E. |
| Předmět: |
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| Zdroj: |
Nature Communications; 1/2/2020, Vol. 11 Issue 1, p1-10, 10p |
| Abstrakt: |
In mammalian cells, >25% of synthesized proteins are exported through the secretory pathway. The pathway complexity, however, obfuscates its impact on the secretion of different proteins. Unraveling its impact on diverse proteins is particularly important for biopharmaceutical production. Here we delineate the core secretory pathway functions and integrate them with genome-scale metabolic reconstructions of human, mouse, and Chinese hamster ovary cells. The resulting reconstructions enable the computation of energetic costs and machinery demands of each secreted protein. By integrating additional omics data, we find that highly secretory cells have adapted to reduce expression and secretion of other expensive host cell proteins. Furthermore, we predict metabolic costs and maximum productivities of biotherapeutic proteins and identify protein features that most significantly impact protein secretion. Finally, the model successfully predicts the increase in secretion of a monoclonal antibody after silencing a highly expressed selection marker. This work represents a knowledgebase of the mammalian secretory pathway that serves as a novel tool for systems biotechnology. The secretory pathway is used in the production of most biopharmaceuticals, but the associated biosynthetic costs are little understood. Here, the authors integrate the core secretory pathway into genome-scale metabolic models of human, mouse, and CHO cells, enabling in silico analysis. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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