Ying Bai, Ivan Domenech Mercadé, Ramy Elgendy, Giulia Lambiase, Sew Peak-Chew, Catarina Franco, Steven W Wingett, Tim J Stevens, Luigi Grassi, Noah Hitchcock, Cristina Sayago Ferreira, Diane Hatton, Elizabeth A Miller, Rajesh K Mistry
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引用次数: 0
Abstract
The secretory capacity of Chinese hamster ovary (CHO) cells remains a fundamental bottleneck in the manufacturing of protein-based therapeutics. Unconventional biological drugs with complex structures and processing requirements are particularly problematic. Although engineered vector DNA elements can achieve rapid and high-level therapeutic protein production, a high metabolic and protein folding burden is imposed on the host cell. Cellular adaptations to these conditions include differential gene expression profiles that can in turn influence the productivity and quality control of recombinant proteins. In this study, we used quantitative transcriptomic and proteomic analyses to investigate how biological pathways change with antibody titre. Gene and protein expression profiles of CHO cell pools and clones producing a panel of different monoclonal and bispecific antibodies were analysed during fed-batch production. Antibody-expressing CHO cell pools were heterogeneous, resulting in few discernible genetic signatures. Clonal cell lines derived from these pools, selected for high and low production, yielded a small number of differentially expressed proteins that correlated with productivity and were shared across the biotherapeutics. However, the dominant feature associated with higher protein production was transgene copy number and the resulting mRNA expression level. Moreover, variability between clonal cell lines suggested that the process of cellular adaptation is variable with diverse cellular changes associated with individual adaptation events.
期刊介绍:
Computational and Structural Biotechnology Journal (CSBJ) is an online gold open access journal publishing research articles and reviews after full peer review. All articles are published, without barriers to access, immediately upon acceptance. The journal places a strong emphasis on functional and mechanistic understanding of how molecular components in a biological process work together through the application of computational methods. Structural data may provide such insights, but they are not a pre-requisite for publication in the journal. Specific areas of interest include, but are not limited to:
Structure and function of proteins, nucleic acids and other macromolecules
Structure and function of multi-component complexes
Protein folding, processing and degradation
Enzymology
Computational and structural studies of plant systems
Microbial Informatics
Genomics
Proteomics
Metabolomics
Algorithms and Hypothesis in Bioinformatics
Mathematical and Theoretical Biology
Computational Chemistry and Drug Discovery
Microscopy and Molecular Imaging
Nanotechnology
Systems and Synthetic Biology