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. 2006 Dec 5;95(5):946-60.
doi: 10.1002/bit.21062.

GlycoVis: visualizing glycan distribution in the protein N-glycosylation pathway in mammalian cells

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GlycoVis: visualizing glycan distribution in the protein N-glycosylation pathway in mammalian cells

Patrick Hossler et al. Biotechnol Bioeng. .

Abstract

Glycosylation has profound effects on the quality of recombinant proteins produced in mammalian cells. The biosynthetic pathways of N-linked glycans on glycoproteins involves a relatively small number of enzymes and nucleotide sugars. Many of these glycoconjugate enzymes can utilize multiple N-glycans as substrates, thus generating a large number of glycan intermediates, and making the biosynthetic pathway resemble a network with diverging and converging paths. The N-glycans on secreted glycoprotein molecules include not only terminal glycans, but also pathway intermediates. To better assess the glycan distribution and the potential route of their synthesis, we created GlycoVis, a visualization program that displays the distribution and the potential reaction paths leading to each N-glycan on the reaction network. The substrate specificities of the enzymes involved were organized into a relationship matrix. With the input of glycan distribution data, the program outputs a reaction pathway map which labels the relative abundance levels of different glycans with different colors. The program also traces all possible reaction paths leading to each glycan and identifies each pathway on the map. Glycoform distribution of Chinese Hamster Ovary cell-derived tissue plasminogen activator (TPA), and human and mouse IgG were used as illustrations for the application of GlycoVis. In addition, the intracellular and secreted IgG from an NS0 producer cell line were isolated, and their glycoform profiles were displayed using GlycoVis for comparison. This visualization tool facilitates the analysis of potential reaction paths utilized under different physiological or culture conditions, and may provide insight on the potential targets for metabolic engineering.

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