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通量采样表明高抗体产生CHO细胞的代谢特征。

Flux Sampling Suggests Metabolic Signatures of High Antibody-Producing CHO Cells.

作者信息

Meeson Kate E, Watson Joanne, Rosser Susan, Hawke Ellie, Pitt Andrew, Moses Tessa, Pybus Leon, Rattray Magnus, Dickson Alan J, Schwartz Jean-Marc

机构信息

Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.

Manchester Institute of Biotechnology, University of Manchester, Manchester, UK.

出版信息

Biotechnol Bioeng. 2025 Jul;122(7):1898-1913. doi: 10.1002/bit.28982. Epub 2025 Apr 11.

Abstract

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.

摘要

中国仓鼠卵巢(CHO)细胞仍然是生产众多治疗性蛋白质,特别是单克隆抗体(mAb)的行业标准。然而,实现更高的重组蛋白滴度仍然是一个持续存在的挑战,对驱动生物工艺性能改善的细胞机制的基本理解仍然难以捉摸。为了直接应对这些挑战并实现实质性改进,可能需要更深入地了解生物工艺环境中的细胞功能。在过去十年中,构建CHO细胞的基因组规模代谢模型(GEM)取得了重大进展,弥合了高信息含量的“组学”数据与进行计算机表型预测能力之间的差距。在这里,采用时间进程转录组学来约束特定培养阶段的GEM,代表CHO细胞补料分批生物反应器培养的早期指数期、晚期指数期和稳定期/死亡期。包括代谢物摄取和分泌速率以及生长和生产力在内的时间生物工艺数据已用于验证通量采样结果。此外,已确定了高mAb生产解决方案,并假设了与改善mAb生产相关的代谢特征。最后,基于约束的建模已被用于推断特定氨基酸,如半胱氨酸、组氨酸、亮氨酸、异亮氨酸、天冬酰胺和丝氨酸,这些氨基酸可以推动mAb产量的增加,并指导优化培养基和补料配方。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63aa/12152534/e48a14ba8ce5/BIT-122-1898-g004.jpg

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