{"title":"Molecular biomarkers identification and applications in CHO bioprocessing","authors":"Caroline Desmurget , Arnaud Perilleux , Jonathan Souquet , Nicole Borth , Julien Douet","doi":"10.1016/j.jbiotec.2024.06.005","DOIUrl":null,"url":null,"abstract":"<div><p>Biomarkers are valuable tools in clinical research where they allow to predict susceptibility to diseases, or response to specific treatments. Likewise, biomarkers can be extremely useful in the biomanufacturing of therapeutic proteins. Indeed, constraints such as short timelines and the need to find hyper-productive cells could benefit from a data-driven approach during cell line and process development. Many companies still rely on large screening capacities to develop productive cell lines, but as they reach a limit of production, there is a need to go from empirical to rationale procedures. Similarly, during bioprocessing runs, substrate consumption and metabolism wastes are commonly monitored. None of them possess the ability to predict the culture behavior in the bioreactor. Big data driven approaches are being adapted to the study of industrial mammalian cell lines, enabled by the publication of Chinese hamster and CHO genome assemblies which allowed the use of next-generation sequencing with these cells, as well as continuous proteome and metabolome annotation. However, if these different -omics technologies contributed to the characterization of CHO cells, there is a significant effort remaining to apply this knowledge to biomanufacturing methods. The correlation of a complex phenotype such as high productivity or rapid growth to the presence or expression level of a specific biomarker could save time and effort in the screening of manufacturing cell lines or culture conditions. In this review we will first discuss the different biological molecules that can be identified and quantified in cells, their detection techniques, and associated challenges. We will then review how these markers are used during the different steps of cell line and bioprocess development, and the inherent limitations of this strategy.</p></div>","PeriodicalId":15153,"journal":{"name":"Journal of biotechnology","volume":null,"pages":null},"PeriodicalIF":4.1000,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0168165624001640/pdfft?md5=e543988c7142b1b021941335f7d07fb1&pid=1-s2.0-S0168165624001640-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of biotechnology","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0168165624001640","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOTECHNOLOGY & APPLIED MICROBIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Biomarkers are valuable tools in clinical research where they allow to predict susceptibility to diseases, or response to specific treatments. Likewise, biomarkers can be extremely useful in the biomanufacturing of therapeutic proteins. Indeed, constraints such as short timelines and the need to find hyper-productive cells could benefit from a data-driven approach during cell line and process development. Many companies still rely on large screening capacities to develop productive cell lines, but as they reach a limit of production, there is a need to go from empirical to rationale procedures. Similarly, during bioprocessing runs, substrate consumption and metabolism wastes are commonly monitored. None of them possess the ability to predict the culture behavior in the bioreactor. Big data driven approaches are being adapted to the study of industrial mammalian cell lines, enabled by the publication of Chinese hamster and CHO genome assemblies which allowed the use of next-generation sequencing with these cells, as well as continuous proteome and metabolome annotation. However, if these different -omics technologies contributed to the characterization of CHO cells, there is a significant effort remaining to apply this knowledge to biomanufacturing methods. The correlation of a complex phenotype such as high productivity or rapid growth to the presence or expression level of a specific biomarker could save time and effort in the screening of manufacturing cell lines or culture conditions. In this review we will first discuss the different biological molecules that can be identified and quantified in cells, their detection techniques, and associated challenges. We will then review how these markers are used during the different steps of cell line and bioprocess development, and the inherent limitations of this strategy.
生物标志物是临床研究的重要工具,可用于预测疾病的易感性或对特定治疗的反应。同样,生物标志物在治疗蛋白质的生物制造中也非常有用。事实上,在细胞系和工艺开发过程中,数据驱动方法可以使时间紧迫和需要找到高产细胞等限制因素受益。许多公司仍在依赖大型筛选能力来开发高产细胞系,但当它们达到生产极限时,就需要从经验程序转向合理程序。同样,在生物工艺运行过程中,通常会对底物消耗和代谢废物进行监测。它们都不具备预测生物反应器中培养行为的能力。中国仓鼠和 CHO 基因组汇编的发布,使下一代测序技术得以在这些细胞中使用,也使连续的蛋白质组和代谢组注释得以实现。然而,如果说这些不同的组学技术有助于描述 CHO 细胞的特征,那么要将这些知识应用到生物制造方法中,还有大量工作要做。将高生产率或快速生长等复杂表型与特定生物标志物的存在或表达水平相关联,可以节省筛选制造细胞系或培养条件的时间和精力。在本综述中,我们将首先讨论可在细胞中识别和量化的不同生物分子、其检测技术以及相关挑战。然后,我们将回顾在细胞系和生物工艺开发的不同步骤中如何使用这些标记物,以及这种策略固有的局限性。
期刊介绍:
The Journal of Biotechnology has an open access mirror journal, the Journal of Biotechnology: X, sharing the same aims and scope, editorial team, submission system and rigorous peer review.
The Journal provides a medium for the rapid publication of both full-length articles and short communications on novel and innovative aspects of biotechnology. The Journal will accept papers ranging from genetic or molecular biological positions to those covering biochemical, chemical or bioprocess engineering aspects as well as computer application of new software concepts, provided that in each case the material is directly relevant to biotechnological systems. Papers presenting information of a multidisciplinary nature that would not be suitable for publication in a journal devoted to a single discipline, are particularly welcome.