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Updated: Aug 28, 2025

Rapid Antibody Glycoengineering in Chinese Hamster Ovary Cells
Published on: June 2, 2022
Comprehensive N- and O-Glycoproteomic Analysis of Multiple Chinese Hamster Ovary Host Cell Lines
Qiong Wang1,2, Tiexin Wang2, Wells W Wu3
1Laboratory of Bacterial Polysaccharides, Division of Bacterial, Parasitic and Allergenic Products, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland 20993, United States.
Abstract:
Glycoproteomic analysis of three Chinese hamster ovary (CHO) suspension host cell lines (CHO-K1, CHO-S, and CHO-Pro5) commonly utilized in biopharmaceutical settings for recombinant protein production is reported. Intracellular and secreted glycoproteins were examined. We utilized an immobilization and chemoenzymatic strategy in our analysis. Glycoproteins or glycopeptides were first immobilized through reductive amination, and the sialyl moieties were amidated for protection. The desired N- or O-glycans and glycopeptides were released from the immobilization resin by enzymatic or chemical digestion. Glycopeptides were studied by Orbitrap Liquid chromatography-mass spectrometry (LC/MS), and the released glycans were analyzed by Matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF). Differences were detected in the relative abundances of N- and O-glycopeptide types, their resident and released glycans, and their glycoprotein complexity. Ontogeny analysis revealed key differences in features, such as general metabolic and biosynthetic pathways, including glycosylation systems, as well as distributions in cellular compartments. Host cell lines and subfraction differences were observed in both N- and O-glycan and glycoprotein pools. Differences were observed in sialyl and fucosyl glycan distributions. Key differences were also observed among glycoproteins that are problematic contaminants in recombinant antibody production. The differences revealed in this study should inform the choice of cell lines best suited for a particular bioproduction application.
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