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基于酶能力的 CHO 细胞基因组规模建模。

Enzyme capacity-based genome scale modelling of CHO cells.

机构信息

Bioprocessing Technology Institute, Agency for Science, Technology and Research (A*STAR), 20 Biopolis Way, #06-01, 138668, Singapore; Department of Chemical and Biomolecular Engineering, National University of Singapore, 4 Engineering Drive 4, 117585, Singapore.

Bioprocessing Technology Institute, Agency for Science, Technology and Research (A*STAR), 20 Biopolis Way, #06-01, 138668, Singapore.

出版信息

Metab Eng. 2020 Jul;60:138-147. doi: 10.1016/j.ymben.2020.04.005. Epub 2020 Apr 21.

Abstract

Chinese hamster ovary (CHO) cells are most prevalently used for producing recombinant therapeutics in biomanufacturing. Recently, more rational and systems approaches have been increasingly exploited to identify key metabolic bottlenecks and engineering targets for cell line engineering and process development based on the CHO genome-scale metabolic model which mechanistically characterizes cell culture behaviours. However, it is still challenging to quantify plausible intracellular fluxes and discern metabolic pathway usages considering various clonal traits and bioprocessing conditions. Thus, we newly incorporated enzyme kinetic information into the updated CHO genome-scale model (iCHO2291) and added enzyme capacity constraints within the flux balance analysis framework (ecFBA) to significantly reduce the flux variability in biologically meaningful manner, as such improving the accuracy of intracellular flux prediction. Interestingly, ecFBA could capture the overflow metabolism under the glucose excess condition where the usage of oxidative phosphorylation is limited by the enzyme capacity. In addition, its applicability was successfully demonstrated via a case study where the clone- and media-specific lactate metabolism was deciphered, suggesting that the lactate-pyruvate cycling could be beneficial for CHO cells to efficiently utilize the mitochondrial redox capacity. In summary, iCHO2296 with ecFBA can be used to confidently elucidate cell cultures and effectively identify key engineering targets, thus guiding bioprocess optimization and cell engineering efforts as a part of digital twin model for advanced biomanufacturing in future.

摘要

中国仓鼠卵巢 (CHO) 细胞是生物制药中最常用于生产重组治疗药物的细胞。最近,越来越多的基于 CHO 基因组规模代谢模型的合理的、系统的方法被用于鉴定关键代谢瓶颈和工程靶点,该模型从机械上描述了细胞培养行为。然而,考虑到各种克隆特性和生物处理条件,定量推测性的细胞内通量并辨别代谢途径的使用仍然具有挑战性。因此,我们将酶动力学信息新纳入到更新的 CHO 基因组规模模型 (iCHO2291) 中,并在通量平衡分析框架 (ecFBA) 中添加酶容量约束,以有意义的方式显著减少通量可变性,从而提高细胞内通量预测的准确性。有趣的是,ecFBA 可以在葡萄糖过剩条件下捕获溢出代谢,在这种条件下,氧化磷酸化的使用受到酶容量的限制。此外,通过一个案例研究成功证明了其适用性,该案例研究揭示了克隆和培养基特异性的乳酸代谢,表明乳酸-丙酮酸循环可以使 CHO 细胞有效地利用线粒体氧化还原能力。总之,带有 ecFBA 的 iCHO2296 可用于阐明细胞培养并有效地确定关键的工程靶点,从而指导生物工艺优化和细胞工程工作,作为未来先进生物制造数字孪生模型的一部分。

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