Supplementation Strategies for Tuning Glycosylation of Monoclonal Antibodies and Enhancing Growth in Mammalian Cell Culture by Omics Analysis

CHO cells;Protein quality;Glycosylation;Nucleotide sugars;N-acetylglucosamine GlcNAc;glucosamine GlcN;2D-DIGE;Proteomics;NMR;Metabolomics;Omics

Blondeel, Ericadvisor:Aucoin, Marc ; affiliation1:Faculty of Engineering ; Aucoin, Marc ;

University of Waterloo

关键词: Metabolomics;    NMR;    2D-DIGE;    N-acetylglucosamine GlcNAc;    Proteomics;    Omics;    glucosamine GlcN;    Protein quality;    Glycosylation;    Nucleotide sugars;    CHO cells;    Doctoral Thesis;   

Others  :  https://uwspace.uwaterloo.ca/bitstream/10012/13096/3/Blondeel_Eric.pdf

瑞士|英语

来源: UWSPACE Waterloo Institutional Repository

【 摘 要 】

Two fundamental objectives of bioprocess engineering are to increase productivity and improve product quality. Glycosylation is a critical and variable factor in the quality of several therapeutic proteins, particularly those with immune-system interactions such as monoclonal antibodies (mAbs). In this thesis, supplementation of nutrients to growth medium of CHO1A7 mammalian cell cultures are examined towards enhancing cell growth, by increasing peak cell density, and improving product quality, by tuning glycosylation of EG2-hFc heavy-chain camelid antibodies. Targeted profiling via 1D-1H-NMR metabolomics and differential expression analysis via 2D-DIGE proteomics, elucidate factors to create a nutrient cocktail to enhance culture growth. Eight target nutrients corresponding with five identified metabolic systems for CHO cells including anaplerotic TCA-replenishment; NADH/NADPH replenishment; tetrahydrofolate cycle C1 cofactor conversions; limitations to lipid synthesis; and redox modulation; resulted in a ~75% improvement to peak cell densities. Towards improving product quality, nucleotide-sugar precursors, capable of shifting glycan distributions were supplemented to growth medium to tune glycosylation of EG2-hFc towards a single G0 glycoform. Growth inhibition from glucosamine-based precursors was mitigated given a priori knowledge from metabolomic analysis of the system – identifying cytosolic acetyl-CoA as a sensitive metabolic pool for CHO1A7 cell growth. Additional nucleotide-sugar precursor nutrients were examined to better resolve conflicting reports of effects to glycan distributions. These conflicts are subsequently attributed to five key factors: differences across cell platforms; differences between glycan sites of expressed proteins; the fermentation and sampling timeline; glutamine levels; finally, no standardized metrics for reporting shifts in glycan distributions with respect to controls.