Compartmentalized Proteomic Profiling Outlines the Crucial Role of the Classical Secretory Pathway during Recombinant Protein Production in Chinese Hamster Ovary Cells

2021 
Different cellular processes that contribute to protein production in Chinese hamster ovary (CHO) cells have been previously investigated by proteomics. However, although the classical secretory pathway (CSP) has been well documented as a bottleneck during recombinant protein (RP) production, it has not been well represented in previous proteomic studies. Hence, the significance of this pathway for production of RP was assessed by identifying its own proteins that were associated to changes in RP production, through subcellular fractionation coupled to shot-gun proteomics. Two CHO cell lines producing a monoclonal antibody with different specific productivities were used as cellular models, from which 4952 protein groups were identified, which represent a coverage of 59% of the Chinese hamster proteome. Data are available via ProteomeXchange with identifier PXD021014. By using SAM and ROTS algorithms, 493 proteins were classified as differentially expressed, of which about 80% was proposed as novel targets and one-third were assigned to the CSP. Endoplasmic reticulum (ER) stress, unfolded protein response, calcium homeostasis, vesicle traffic, glycosylation, autophagy, proteasomal activity, protein synthesis and translocation into ER lumen, and secretion of extracellular matrix components were some of the affected processes that occurred in the secretory pathway. Processes from other cellular compartments, such as DNA replication, transcription, cytoskeleton organization, signaling, and metabolism, were also modified. This study gives new insights into the molecular traits of higher producer cells and provides novel targets for development of new sub-lines with improved phenotypes for RP production.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    213
    References
    0
    Citations
    NaN
    KQI
    []