抗体产生的 CHO 细胞系的多组学特征阐明了代谢重编程和营养吸收瓶颈。

IF 6.8 1区 生物学 Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY Metabolic engineering Pub Date : 2024-07-22 DOI:10.1016/j.ymben.2024.07.009
Saratram Gopalakrishnan , William Johnson , Miguel A. Valderrama-Gomez , Elcin Icten , Jasmine Tat , Fides Lay , Jonathan Diep , Natalia Gomez , Jennitte Stevens , Fabrice Schlegel , Pablo Rolandi , Cleo Kontoravdi , Nathan E. Lewis
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引用次数: 0

摘要

表征工业生产细胞系的表型多样性和代谢能力对于生物工艺优化和细胞系开发至关重要。生产宿主的代谢能力会限制营养和资源进入所需的细胞过程,并对生产率产生深远影响。这些限制无法直接从废培养基浓度或转录组学等测量数据中推断。在这里,我们介绍了一个综合的多组学分析管道,它结合了外显子代谢组学、转录组学和基因组规模的代谢网络分析,并将其应用于三个生产抗体的中国仓鼠卵巢细胞系,以确定与高产克隆相关的重编程特征,以及在工业生物过程中限制产品形成的代谢瓶颈。对单个数据类型的分析表明,高产克隆的含氮副产物分泌减少,外周代谢途径表达的拓扑变化与相变有关。在基因组尺度代谢模型背景下进行的综合全元素分析阐明了中心代谢的差异,并发现了限制细胞生长和抗体产生的氨基酸利用瓶颈,而这些瓶颈在外显子代谢组学或转录组学中并不明显。因此,我们证明了多组学特征描述在深入了解细胞代谢方面的效用,这对细胞工程和生物工艺优化工作至关重要。
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Multi-omic characterization of antibody-producing CHO cell lines elucidates metabolic reprogramming and nutrient uptake bottlenecks

Characterizing the phenotypic diversity and metabolic capabilities of industrially relevant manufacturing cell lines is critical to bioprocess optimization and cell line development. Metabolic capabilities of production hosts limit nutrient and resource channeling into desired cellular processes and can have a profound impact on productivity. These limitations cannot be directly inferred from measured data such as spent media concentrations or transcriptomics. Here, we present an integrated multi-omic analysis pipeline combining exo-metabolomics, transcriptomics, and genome-scale metabolic network analysis and apply it to three antibody-producing Chinese Hamster Ovary cell lines to identify reprogramming features associated with high-producing clones and metabolic bottlenecks limiting product formation in an industrial bioprocess. Analysis of individual datatypes revealed a decreased nitrogenous byproduct secretion in high-producing clones and the topological changes in peripheral metabolic pathway expression associated with phase shifts. An integrated omics analysis in the context of the genome-scale metabolic model elucidated the differences in central metabolism and identified amino acid utilization bottlenecks limiting cell growth and antibody production that were not evident from exo-metabolomics or transcriptomics alone. Thus, we demonstrate the utility of a multi-omics characterization in providing an in-depth understanding of cellular metabolism, which is critical to efforts in cell engineering and bioprocess optimization.

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来源期刊
Metabolic engineering
Metabolic engineering 工程技术-生物工程与应用微生物
CiteScore
15.60
自引率
6.00%
发文量
140
审稿时长
44 days
期刊介绍: Metabolic Engineering (MBE) is a journal that focuses on publishing original research papers on the directed modulation of metabolic pathways for metabolite overproduction or the enhancement of cellular properties. It welcomes papers that describe the engineering of native pathways and the synthesis of heterologous pathways to convert microorganisms into microbial cell factories. The journal covers experimental, computational, and modeling approaches for understanding metabolic pathways and manipulating them through genetic, media, or environmental means. Effective exploration of metabolic pathways necessitates the use of molecular biology and biochemistry methods, as well as engineering techniques for modeling and data analysis. MBE serves as a platform for interdisciplinary research in fields such as biochemistry, molecular biology, applied microbiology, cellular physiology, cellular nutrition in health and disease, and biochemical engineering. The journal publishes various types of papers, including original research papers and review papers. It is indexed and abstracted in databases such as Scopus, Embase, EMBiology, Current Contents - Life Sciences and Clinical Medicine, Science Citation Index, PubMed/Medline, CAS and Biotechnology Citation Index.
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