焊剂(冶金)
代谢通量分析
抗体
采样(信号处理)
中国仓鼠卵巢细胞
化学
计算生物学
生物
细胞生物学
生物化学
物理
新陈代谢
免疫学
受体
有机化学
探测器
光学
作者
Kate E. Meeson,Joanne Watson,Susan J. Rosser,Ellie Hawke,Andrew R. Pitt,Tessa Moses,Leon P. Pybus,Magnus Rattray,Alan J. Dickson,Jean‐Marc Schwartz
摘要
Chinese hamster ovary (CHO) cells remain the industry standard for producing numerous therapeutic proteins, particularly monoclonal antibodies (mAbs). However, achieving higher recombinant protein titers remains an ongoing challenge and a fundamental understanding of the cellular mechanism driving improved bioprocess performance remains elusive. To directly address these challenges and achieve substantial improvements, a more in-depth understanding of cellular function within a bioprocess environment may be required. Over the past decade, significant advancements have been made in the building of genome-scale metabolic models (GEMs) for CHO cells, bridging the gap between high information content 'omics data and the ability to perform in silico phenotypic predictions. Here, time-course transcriptomics has been employed to constrain culture phase-specific GEMs, representing the early exponential, late exponential, and stationary/death phases of CHO cell fed-batch bioreactor culture. Temporal bioprocess data, including metabolite uptake and secretion rates, as well as growth and productivity, has been used to validate flux sampling results. Additionally, high mAb-producing solutions have been identified and the metabolic signatures associated with improved mAb production have been hypothesized. Finally, constraint-based modeling has been utilized to infer specific amino acids, cysteine, histidine, leucine, isoleucine, asparagine, and serine, which could drive increased mAb production and guide optimal media and feed formulations.
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