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Biotechnology Journal
Article . 2018 . Peer-reviewed
License: Wiley Online Library User Agreement
Data sources: Crossref
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Glycoengineering in CHO Cells: Advances in Systems Biology

Authors: Vijay Tejwani; Mikael R. Andersen; Jong Hyun Nam; Susan T. Sharfstein;

Glycoengineering in CHO Cells: Advances in Systems Biology

Abstract

For several decades, glycoprotein biologics have been successfully produced from Chinese hamster ovary (CHO) cells. The therapeutic efficacy and potency of glycoprotein biologics are often dictated by their post‐translational modifications, particularly glycosylation, which unlike protein synthesis, is a non‐templated process. Consequently, both native and recombinant glycoprotein production generate heterogeneous mixtures containing variable amounts of different glycoforms. Stability, potency, plasma half‐life, and immunogenicity of the glycoprotein biologic are directly influenced by the glycoforms. Recently, CHO cells have also been explored for production of therapeutic glycosaminoglycans (e.g., heparin), which presents similar challenges as producing glycoproteins biologics. Approaches to controlling heterogeneity in CHO cells and directing the biosynthetic process toward desired glycoforms are not well understood. A systems biology approach combining different technologies is needed for complete understanding of the molecular processes accounting for this variability and to open up new venues in cell line development. In this review, we describe several advances in genetic manipulation, modeling, and glycan and glycoprotein analysis that together will provide new strategies for glycoengineering of CHO cells with desired or enhanced glycosylation capabilities.

Country
Denmark
Keywords

Glycosylation, Systems Biology, Cellular engineering, CHO Cells, Recombinant Proteins, Cricetulus, Cricetinae, Chinese hamster ovary cells, Protein glycosylation, Animals, Humans, Mathematical modeling, Protein Processing, Post-Translational, Glycosaminoglycans, Glycoproteins

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
61
Top 10%
Top 10%
Top 1%
Green
bronze