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Michaela Gallucci

BS: Chemical Engineering, Lehigh University

Contact Information:
Email username (at gallucci
Office: 249 DBI
Phone: (302) 831-2939

Research Project:

Glycosylation, the enzymatic attachment of various saccharide residues to a protein backbone, is a critical process of protein secretion. Optimal and consistent glycosylation is necessary to ensure the safety and efficacy of many protein therapeutics in vivo. However, the complexity of glycosylation makes it difficult to predict the quantitative effect(s) of process changes on glycosylation patterns and consistency. Current models can describe glycosylation in great detail, but are limited by their reliance on a multitude of unknown kinetic parameters. Here, we present an in silico model that uses constraint-based analysis to quantitatively predict glycosylation patterns without the use of kinetic parameters. Our model uses a small, discrete set of parameters that control the flux of sugars through all major N-glycosylation pathways. This framework was applied to model both the kinetic modification of glycans via the action of various glycosyltransferases and the production of all sugars required for glycosylation. Our model has been shown to accurately reproduce various published glycosylation profiles, identify novel network behavior exhibited by glycosyltransferase expression or media changes, and correctly predict quantitative trends in glycosylation from glycosyltransferase knockouts. Our unique approach to modeling glycosylation could be used to aid in CHO cell engineering, media formulation, and real-time glycosylation analysis to increase the quality and consistency of therapeutics being developed in CHO cells.

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