Charles Eldrid, Ellie Hawke, Kathleen M Cain, Kate Meeson, Joanne Watson, Reynard Spiess, Luke Johnston, William Smith, Matthew Russell, Robyn Hoare, John Raven, Jean-Marc Schwartz, Magnus Rattray, Leon Pybus, Alan Dickson, Andrew Pitt, Perdita Barran
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引用次数: 0
Abstract
Chinese hamster ovary (CHO) cells are the industrial workhorse for manufacturing biopharmaceuticals, including monoclonal antibodies. CHO cell line development requires a more data-driven approach for the accelerated identification of hyper-productive cell lines. Traditional methods, which rely on time-consuming hierarchical screening, often fail to elucidate the underlying cellular mechanisms driving optimal bioreactor performance. Big data analytics, coupled with advancements in 'omics' technologies, are revolutionizing the study of industrial cell lines. Translating this knowledge into practical methods widely utilized in industrial biomanufacturing remains a significant challenge. This study leverages discovery proteomics to characterize dynamic changes within the CHO cell proteome during a 14-day fed-batch bioreactor cultivation. Utilizing a global untargeted proteomics workflow on both a ZenoTOF 7600 and a Cyclic IMS QToF, we identify 3358 proteins and present a comprehensive data set that describes the molecular changes that occur within a well characterized host chassis. By mapping relative abundances to key cellular processes, eight protein targets were selected as potential biomarkers. The abundance of these proteins through the production run are quantified using a 15-minute targeted triple quadrupole (MRM) assay which provides a molecular level QC for cell viability. This discovery to target workflow has the potential to assist engineering of new chassis and provide simple read outs of successful bioreactor batches.
期刊介绍:
The mission of MCP is to foster the development and applications of proteomics in both basic and translational research. MCP will publish manuscripts that report significant new biological or clinical discoveries underpinned by proteomic observations across all kingdoms of life. Manuscripts must define the biological roles played by the proteins investigated or their mechanisms of action.
The journal also emphasizes articles that describe innovative new computational methods and technological advancements that will enable future discoveries. Manuscripts describing such approaches do not have to include a solution to a biological problem, but must demonstrate that the technology works as described, is reproducible and is appropriate to uncover yet unknown protein/proteome function or properties using relevant model systems or publicly available data.
Scope:
-Fundamental studies in biology, including integrative "omics" studies, that provide mechanistic insights
-Novel experimental and computational technologies
-Proteogenomic data integration and analysis that enable greater understanding of physiology and disease processes
-Pathway and network analyses of signaling that focus on the roles of post-translational modifications
-Studies of proteome dynamics and quality controls, and their roles in disease
-Studies of evolutionary processes effecting proteome dynamics, quality and regulation
-Chemical proteomics, including mechanisms of drug action
-Proteomics of the immune system and antigen presentation/recognition
-Microbiome proteomics, host-microbe and host-pathogen interactions, and their roles in health and disease
-Clinical and translational studies of human diseases
-Metabolomics to understand functional connections between genes, proteins and phenotypes