Glycan Residues Balance Analysis - GReBA: A novel model for the N-linked glycosylation of IgG produced by CHO cells.
CHO cells
IgG
Mathematical modelling
N-linked glycosylation
Pseudo-perfusion
Journal
Metabolic engineering
ISSN: 1096-7184
Titre abrégé: Metab Eng
Pays: Belgium
ID NLM: 9815657
Informations de publication
Date de publication:
01 2020
01 2020
Historique:
received:
04
03
2019
revised:
12
07
2019
accepted:
22
08
2019
pubmed:
21
9
2019
medline:
28
1
2021
entrez:
21
9
2019
Statut:
ppublish
Résumé
The structure of N-linked glycosylation is a very important quality attribute for therapeutic monoclonal antibodies. Different carbon sources in cell culture media, such as mannose and galactose, have been reported to have different influences on the glycosylation patterns. Accurate prediction and control of the glycosylation profile are important for the process development of mammalian cell cultures. In this study, a mathematical model, that we named Glycan Residues Balance Analysis (GReBA), was developed based on the concept of Elementary Flux Mode (EFM), and used to predict the glycosylation profile for steady state cell cultures. Experiments were carried out in pseudo-perfusion cultivation of antibody producing Chinese Hamster Ovary (CHO) cells with various concentrations and combinations of glucose, mannose and galactose. Cultivation of CHO cells with mannose or the combinations of mannose and galactose resulted in decreased lactate and ammonium production, and more matured glycosylation patterns compared to the cultures with glucose. Furthermore, the growth rate and IgG productivity were similar in all the conditions. When the cells were cultured with galactose alone, lactate was fed as well to be used as complementary carbon source, leading to cell growth rate and IgG productivity comparable to feeding the other sugars. The data of the glycoprofiles were used for training the model, and then to simulate the glycosylation changes with varying the concentrations of mannose and galactose. In this study we showed that the GReBA model had a good predictive capacity of the N-linked glycosylation. The GReBA can be used as a guidance for development of glycoprotein cultivation processes.
Identifiants
pubmed: 31539564
pii: S1096-7176(19)30086-2
doi: 10.1016/j.ymben.2019.08.016
pii:
doi:
Substances chimiques
Antibodies, Monoclonal
0
Glycoproteins
0
Immunoglobulin G
0
Polysaccharides
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
118-128Informations de copyright
Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.