CHOGlycoNET: Comprehensive glycosylation reaction network for CHO cells

• Published in: Metabolic engineering Vol. 76; pp. 87 - 96
• Main Authors: Kotidis, Pavlos, Donini, Roberto, Arnsdorf, Johnny, Hansen, Anders Holmgaard, Voldborg, Bjørn Gunnar Rude, Chiang, Austin W.T., Haslam, Stuart M., Betenbaugh, Michael, Jimenez del Val, Ioscani, Lewis, Nathan E., Krambeck, Frederick, Kontoravdi, Cleo
• Format: Journal Article
• Language: English
• Published: Belgium Elsevier Inc 01.03.2023
• Subjects: Animals; Chinese hamster ovary cells; CHO Cells; Cricetinae; Cricetulus; Glycoengineering; Glycoproteins - genetics; Glycosylation; Glycosyltransferases - genetics; Glycosyltransferases - metabolism; Polysaccharides - genetics; Protein glycosylation; Recombinant Proteins - genetics; Recombinant Proteins - metabolism; Systems glycobiology; Systems glycobiology; Protein glycosylation; Glycoengineering; Chinese hamster ovary cells
• ISSN: 1096-7176; 1096-7184
• DOI: 10.1016/j.ymben.2022.12.009

Chinese hamster ovary (CHO) cells are extensively used for the production of glycoprotein therapeutics proteins, for which N-linked glycans are a critical quality attribute due to their influence on activity and immunogenicity. Manipulation of protein glycosylation is commonly achieved through cell or process engineering, which are often guided by mathematical models. However, each study considers a unique glycosylation reaction network that is tailored around the cell line and product at hand. Herein, we use 200 glycan datasets for both recombinantly produced and native proteins from different CHO cell lines to reconstruct a comprehensive reaction network, CHOGlycoNET, based on the individual minimal reaction networks describing each dataset. CHOGlycoNET is used to investigate the distribution of mannosidase and glycosyltransferase enzymes in the Golgi apparatus and identify key network reactions using machine learning and dimensionality reduction techniques. CHOGlycoNET can be used for accelerating glycomodel development and predicting the effect of glycoengineering strategies. Finally, CHOGlycoNET is wrapped in a SBML file to be used as a standalone model or in combination with CHO cell genome scale models. •Host glycosylation network determines protein glycoprofile.•CHO cells used extensively for industrial glycoprotein production.•We built a comprehensive glycosylation reaction network for CHO cells.•CHOGlycoNET is informed by 200 glycan datasets.•It can accelerate model development and design of glycoengineering studies.