Abstract
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.
| Original language | English |
|---|---|
| Article number | 68 |
| Journal | Nature Communications |
| Volume | 11 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 1 Dec 2020 |
Bibliographical note
Funding Information: We would like to thank Philipp Spahn, Austin Chiang, and Chih-Chung Kuo for their insightful comments on this manuscript. This work was supported by generous funding from the Novo Nordisk Foundation provided to the Center for Biosustainability at the Technical University of Denmark (NNF10CC1016517 and NNF16CC0021858), and from NIGMS (R35 GM119850), and a fellowship from the Government of Mexico (CONACYT) and the University of California Institute for Mexico and the United States (UC-MEXUS). Publisher Copyright: © 2020, The Author(s).Fingerprint
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