ArticlePloS one2017
Model-based analysis of N-glycosylation in Chinese hamster ovary cells.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Delineating the Transcriptional and Phenotypic Impact from Biotherapeutic Glycoengineering.bioRxiv : the preprint server for biology · 2026Article
- Wheels turning: CHO cell modeling moves into a digital biomanufacturing era: Subtitle: CHO Metabolic Modeling.Computational and structural biotechnology journal · 2025Review
- In silico simulation of glycosylation and related pathways.Analytical and bioanalytical chemistry · 2024Review
- Glycosylation Modulation Dictates Trafficking and Interaction of SARS-CoV-2 S1 Subunit and ACE2 in Intestinal Epithelial Caco-2 Cells.Biomolecules · 2024Article
- Soft-sensor model development for CHO growth/production, intracellular metabolite, and glycan predictions.Frontiers in molecular biosciences · 2024Article
- Glycosylation shapes the efficacy and safety of diverse protein, gene and cell therapies.Biotechnology advances · 2023Review
- CHOGlycoNET: Comprehensive glycosylation reaction network for CHO cells.Metabolic engineering · 2023Article
- In silico analysis of the human milk oligosaccharide glycome reveals key enzymes of their biosynthesis.Scientific reports · 2022Article
- Immunoglobulin G N-glycan Biomarkers for Autoimmune Diseases: Current State and a Glycoinformatics Perspective.International journal of molecular sciences · 2022Review
- Elucidating Human Milk Oligosaccharide biosynthetic genes through network-based multi-omics integration.Nature communications · 2022Article
- Hidden Relationships betweenInternational journal of molecular sciences · 2022Review
- Computational Modeling ofMolecules (Basel, Switzerland) · 2022Article
- An Interactive View of Glycosylation.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Correcting for sparsity and interdependence in glycomics by accounting for glycan biosynthesis.Nature communications · 2021Article
- Systems glycobiology for discovering drug targets, biomarkers, and rational designs for glyco-immunotherapy.Journal of biomedical science · 2021Review
- Simulating the enzymes of ganglioside biosynthesis with Glycologue.Beilstein journal of organic chemistry · 2021Article
- N-Glycosylation Network Construction and Analysis to Modify Glycans on the Spike (S) Glycoprotein of SARS-CoV-2.Frontiers in bioinformatics · 2021Article
- A Markov model of glycosylation elucidates isozyme specificity and glycosyltransferase interactions for glycoengineering.Current research in biotechnology · 2020Article
- Harnessing the potential of artificial neural networks for predicting protein glycosylation.Metabolic engineering communications · 2020Article
- Protein Glycoengineering: An Approach for Improving Protein Properties.Frontiers in chemistry · 2020Review
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
The Chinese hamster ovary (CHO) cell is the gold standard for manufacturing of glycosylated recombinant proteins for production of biotherapeutics. The similarity of its glycosylation patterns to the human versions enable the products of this cell line favorable pharmacokinetic properties and lower likelihood of causing immunogenic responses. Because glycan structures are the product of the concerted action of intracellular enzymes, it is difficult to predict a priori how the effects of genetic manipulations alter glycan structures of cells and therapeutic properties. For that reason, quantitative models able to predict glycosylation have emerged as promising tools to deal with the complexity of glycosylation processing. For example, an earlier version of the same model used in this study was used by others to successfully predict changes in enzyme activities that could produce a desired change in glycan structure. In this study we utilize an updated version of this model to provide a comprehensive analysis of N-glycosylation in ten Chinese hamster ovary (CHO) cell lines that include a wild type parent and nine mutants of CHO, through interpretation of previously published mass spectrometry data. The updated N-glycosylation mathematical model contains up to 50,605 glycan structures. Adjusting the enzyme activities in this model to match N-glycan mass spectra produces detailed predictions of the glycosylation process, enzyme activity profiles and complete glycosylation profiles of each of the cell lines. These profiles are consistent with biochemical and genetic data reported previously. The model-based results also predict glycosylation features of the cell lines not previously published, indicating more complex changes in glycosylation enzyme activities than just those resulting directly from gene mutations. The model predicts that the CHO cell lines possess regulatory mechanisms that allow them to adjust glycosylation enzyme activities to mitigate side effects of the primary loss or gain of glycosylation function known to exist in these mutant cell lines. Quantitative models of CHO cell glycosylation have the potential for predicting how glycoengineering manipulations might affect glycoform distributions to improve the therapeutic performance of glycoprotein products.
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