Author
Listed:
- Jahir M. Gutierrez
(University of California, San Diego
Novo Nordisk Foundation Center for Biosustainability at the University of California, San Diego, School of Medicine)
- Amir Feizi
(Kemivägen 10, Chalmers University of Technology)
- Shangzhong Li
(University of California, San Diego
Novo Nordisk Foundation Center for Biosustainability at the University of California, San Diego, School of Medicine)
- Thomas B. Kallehauge
(Technical University of Denmark)
- Hooman Hefzi
(University of California, San Diego
Novo Nordisk Foundation Center for Biosustainability at the University of California, San Diego, School of Medicine)
- Lise M. Grav
(Technical University of Denmark)
- Daniel Ley
(Technical University of Denmark
Technical University of Denmark)
- Deniz Baycin Hizal
(Pharmaceutical R&D Department, Turgut Illaclari A.S)
- Michael J. Betenbaugh
(Johns Hopkins University)
- Bjorn Voldborg
(Technical University of Denmark)
- Helene Kildegaard
(Technical University of Denmark)
- Gyun Lee
(Technical University of Denmark)
- Bernhard O. Palsson
(University of California, San Diego
Novo Nordisk Foundation Center for Biosustainability at the University of California, San Diego, School of Medicine
Technical University of Denmark
University of California, San Diego, School of Medicine)
- Jens Nielsen
(Kemivägen 10, Chalmers University of Technology
Technical University of Denmark)
- Nathan E. Lewis
(University of California, San Diego
Novo Nordisk Foundation Center for Biosustainability at the University of California, San Diego, School of Medicine
University of California, San Diego, School of Medicine)
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.
Suggested Citation
Jahir M. Gutierrez & Amir Feizi & Shangzhong Li & Thomas B. Kallehauge & Hooman Hefzi & Lise M. Grav & Daniel Ley & Deniz Baycin Hizal & Michael J. Betenbaugh & Bjorn Voldborg & Helene Kildegaard & Gy, 2020.
"Genome-scale reconstructions of the mammalian secretory pathway predict metabolic costs and limitations of protein secretion,"
Nature Communications, Nature, vol. 11(1), pages 1-10, December.
Handle:
RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-019-13867-y
DOI: 10.1038/s41467-019-13867-y
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