A metabolic network-based approach for developing feeding strategies for CHO cells to increase monoclonal antibody production
A metabolic network-based approach for developing feeding strategies for CHO cells to increase monoclonal antibody production
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DOI：
10.1007/s00449-020-02332-6
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发表时间：
2020-03-24
影响因子：
3.8
通讯作者：
Vaziri, Behrouz
中科院分区：
文献类型：
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作者：
Fouladiha, Hamideh;Marashi, Sayed-Amir;Vaziri, Behrouz
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）的主要主力。迄今为止，各种代谢工程方法已被用于提高CHO细胞的生产力。虽然在哺乳动物细胞中进行遗传操作可能很费力，但合理设计CHO细胞培养基或有效的分批喂料策略是更流行的生物过程优化方法。本研究利用CHO细胞的基因组尺度代谢网络模型设计CHO细胞的喂养策略，以提高单克隆抗体（mAb）的产生。该模型建议将苏氨酸和花生四烯酸等多种代谢物加入细胞培养基中。利用实验方法的设计，对所设计的配方进行了实验验证和优化。使用这种策略可以观察到单抗总表达量增加约两倍。我们的方法可以用于类似的生物过程优化问题，提出在不同的细胞工厂增加产量的新方法。
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.