Department of Biotechnology, College of Science, University of Tehran, Tehran, Iran.
Protein Chemistry and Proteomics Laboratory, Biotechnology Research Center, Pasteur Institute of Iran, Tehran, Iran.
Bioprocess Biosyst Eng. 2020 Aug;43(8):1381-1389. doi: 10.1007/s00449-020-02332-6. Epub 2020 Mar 24.
Chinese hamster ovary (CHO) cells are the main workhorse in the biopharmaceutical industry for the production of recombinant proteins, such as monoclonal antibodies. To date, a variety of metabolic engineering approaches have been used to improve the productivity of CHO cells. While genetic manipulations are potentially laborious in mammalian cells, rational design of CHO cell culture medium or efficient fed-batch strategies are more popular approaches for bioprocess optimization. In this study, a genome-scale metabolic network model of CHO cells was used to design feeding strategies for CHO cells to improve monoclonal antibody (mAb) production. A number of metabolites, including threonine and arachidonate, were suggested by the model to be added into cell culture medium. The designed composition has been experimentally validated, and then optimized, using design of experiment methods. About a two-fold increase in the total mAb expression has been observed using this strategy. Our approach can be used in similar bioprocess optimization problems, to suggest new ways of increasing production in different cell factories.
中国仓鼠卵巢（CHO）细胞是生物制药行业生产重组蛋白（如单克隆抗体）的主要工作细胞。迄今为止，已经采用了多种代谢工程方法来提高 CHO 细胞的生产力。虽然遗传操作在哺乳动物细胞中可能很繁琐，但合理设计 CHO 细胞培养基或高效补料分批策略是生物工艺优化的更受欢迎的方法。在这项研究中，使用 CHO 细胞的基因组规模代谢网络模型来设计 CHO 细胞的喂养策略，以提高单克隆抗体（mAb）的产量。该模型建议在细胞培养基中添加一些代谢物，包括苏氨酸和花生四烯酸。设计的组成已经使用实验设计方法进行了实验验证和优化。使用这种策略，总 mAb 表达量增加了约两倍。我们的方法可用于类似的生物工艺优化问题，为不同的细胞工厂提出提高产量的新方法。
