Literature DB >> 21956887

A dynamic mathematical model for monoclonal antibody N-linked glycosylation and nucleotide sugar donor transport within a maturing Golgi apparatus.

Ioscani Jimenez del Val1, Judit M Nagy, Cleo Kontoravdi.   

Abstract

Monoclonal antibodies (mAbs) are one of the most important products of the biopharmaceutical industry. Their therapeutic efficacy depends on the post-translational process of glycosylation, which is influenced by manufacturing process conditions. Herein, we present a dynamic mathematical model for mAb glycosylation that considers cisternal maturation by approximating the Golgi apparatus to a plug flow reactor and by including recycling of Golgi-resident proteins (glycosylation enzymes and transport proteins [TPs]). The glycosylation reaction rate expressions were derived based on the reported kinetic mechanisms for each enzyme, and transport of nucleotide sugar donors [NSDs] from the cytosol to the Golgi lumen was modeled to serve as a link between glycosylation and cellular metabolism. Optimization-based methodologies were developed for estimating unknown enzyme and TP concentration profile parameters. The resulting model is capable of reproducing glycosylation profiles of commercial mAbs. It can further reproduce the effect gene silencing of the FucT glycosylation enzyme and cytosolic NSD depletion have on the mAb oligosaccharide profile. All novel elements of our model are based on biological evidence and generate more accurate results than previous reports. We therefore believe that the improvements contribute to a more detailed representation of the N-linked glycosylation process. The overall results show the potential of our model toward evaluating cell engineering strategies that yield desired glycosylation profiles. Additionally, when coupled to cellular metabolism, this model could be used to assess the effect of process conditions on glycosylation and aid in the design, control, and optimization of biopharmaceutical manufacturing processes.
Copyright © 2011 American Institute of Chemical Engineers (AIChE).

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Year:  2011        PMID: 21956887     DOI: 10.1002/btpr.688

Source DB:  PubMed          Journal:  Biotechnol Prog        ISSN: 1520-6033


  23 in total

1.  Analysis of site-specific N-glycan remodeling in the endoplasmic reticulum and the Golgi.

Authors:  Ivan Hang; Chia-wei Lin; Oliver C Grant; Susanna Fleurkens; Thomas K Villiger; Miroslav Soos; Massimo Morbidelli; Robert J Woods; Robert Gauss; Markus Aebi
Journal:  Glycobiology       Date:  2015-08-03       Impact factor: 4.313

2.  A Markov chain model for N-linked protein glycosylation--towards a low-parameter tool for model-driven glycoengineering.

Authors:  Philipp N Spahn; Anders H Hansen; Henning G Hansen; Johnny Arnsdorf; Helene F Kildegaard; Nathan E Lewis
Journal:  Metab Eng       Date:  2015-10-29       Impact factor: 9.783

Review 3.  Engineering the supply chain for protein production/secretion in yeasts and mammalian cells.

Authors:  Tobias Klein; Jens Niklas; Elmar Heinzle
Journal:  J Ind Microbiol Biotechnol       Date:  2015-01-06       Impact factor: 3.346

4.  Model-Driven Engineering of N-Linked Glycosylation in Chinese Hamster Ovary Cells.

Authors:  Christopher S Stach; Meghan G McCann; Conor M O'Brien; Tung S Le; Nikunj Somia; Xinning Chen; Kyoungho Lee; Hsu-Yuan Fu; Prodromos Daoutidis; Liang Zhao; Wei-Shou Hu; Michael Smanski
Journal:  ACS Synth Biol       Date:  2019-10-18       Impact factor: 5.110

5.  Recombinant Proteins and Monoclonal Antibodies.

Authors:  Roy Jefferis
Journal:  Adv Biochem Eng Biotechnol       Date:  2021       Impact factor: 2.635

6.  A high-resolution measurement of nucleotide sugars by using ion-pair reverse chromatography and tandem columns.

Authors:  Sha Sha; Garry Handelman; Cyrus Agarabi; Seongkyu Yoon
Journal:  Anal Bioanal Chem       Date:  2020-04-16       Impact factor: 4.142

7.  Global mapping of glycosylation pathways in human-derived cells.

Authors:  Yi-Fan Huang; Kazuhiro Aoki; Sachiko Akase; Mayumi Ishihara; Yi-Shi Liu; Ganglong Yang; Yasuhiko Kizuka; Shuji Mizumoto; Michael Tiemeyer; Xiao-Dong Gao; Kiyoko F Aoki-Kinoshita; Morihisa Fujita
Journal:  Dev Cell       Date:  2021-03-16       Impact factor: 12.270

Review 8.  Big-Data Glycomics: Tools to Connect Glycan Biosynthesis to Extracellular Communication.

Authors:  Benjamin P Kellman; Nathan E Lewis
Journal:  Trends Biochem Sci       Date:  2020-12-18       Impact factor: 13.807

9.  Towards controlling the glycoform: a model framework linking extracellular metabolites to antibody glycosylation.

Authors:  Philip M Jedrzejewski; Ioscani Jimenez del Val; Antony Constantinou; Anne Dell; Stuart M Haslam; Karen M Polizzi; Cleo Kontoravdi
Journal:  Int J Mol Sci       Date:  2014-03-14       Impact factor: 5.923

10.  Controllability analysis of protein glycosylation in CHO cells.

Authors:  Melissa M St Amand; Kevin Tran; Devesh Radhakrishnan; Anne S Robinson; Babatunde A Ogunnaike
Journal:  PLoS One       Date:  2014-02-03       Impact factor: 3.240

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