Literature DB >> 24728980

Identification of manipulated variables for a glycosylation control strategy.

Melissa M St Amand1, Devesh Radhakrishnan, Anne S Robinson, Babatunde A Ogunnaike.   

Abstract

N-linked glycan distribution affects important end-use characteristics such as the bioactivity and efficacy of many therapeutic proteins, (including monoclonal antibodies), in vivo. Yet, obtaining desired glycan distributions consistently during batch-to-batch production can be challenging for biopharmaceutical manufacturers. While an appropriately implemented on-line glycosylation control strategy during production can help to ensure a consistent glycan distribution, to date no such strategies have been reported. Our goal is to develop and validate a comprehensive strategy for effective on-line control of glycosylation, the successful achievement of which requires first identifying appropriate manipulated variables that can be used to direct the glycan distribution to a desired state. While various culture conditions such as bioreactor process variables, media type, and media supplements have been shown to affect the glycan distribution, in this study we focus on the latter. Specifically, we implemented a statistically designed series of experiments to determine the significant main effects (as well as interaction effects) of media supplementation with manganese, galactose, ammonia and found that each had significant effects on certain glycans. We also include data indicating the glycosylation enzyme gene transcript levels as well as the intracellular nucleotide sugar concentrations in the presence of the media supplements to provide insight into the intracellular conditions that may be contributing to the changes in glycan distribution. The acquired experimental data sets were then used to identify which glycans can be controlled by the media supplements and to what degree. We determined that MnCl2 can be used as a manipulated variable to increase the relative abundance of M51 and decrease FA2 simultaneously, and galactose can be used as a manipulated variable to increase the relative abundance of FA2G1 and decrease FA2 and A2 simultaneously.
© 2014 Wiley Periodicals, Inc.

Entities:  

Keywords:  controllability; design of experiments (DoE); enzyme expression; glycosylation; media supplements; monoclonal antibody; nucleotide sugar

Mesh:

Substances:

Year:  2014        PMID: 24728980     DOI: 10.1002/bit.25251

Source DB:  PubMed          Journal:  Biotechnol Bioeng        ISSN: 0006-3592            Impact factor:   4.530


  9 in total

1.  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

2.  Predictive glycoengineering of biosimilars using a Markov chain glycosylation model.

Authors:  Philipp N Spahn; Anders H Hansen; Stefan Kol; Bjørn G Voldborg; Nathan E Lewis
Journal:  Biotechnol J       Date:  2016-12-28       Impact factor: 4.677

3.  Comprehensive manipulation of glycosylation profiles across development scales.

Authors:  Sven Loebrich; Elisa Clark; Kristina Ladd; Stefani Takahashi; Anna Brousseau; Seth Kitchener; Robert Herbst; Thomas Ryll
Journal:  MAbs       Date:  2018-10-22       Impact factor: 5.857

4.  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

5.  A system identification approach for developing model predictive controllers of antibody quality attributes in cell culture processes.

Authors:  Brandon Downey; John Schmitt; Justin Beller; Brian Russell; Anthony Quach; Elizabeth Hermann; David Lyon; Jeffrey Breit
Journal:  Biotechnol Prog       Date:  2017-08-24

Review 6.  Expression of Lectins in Heterologous Systems.

Authors:  Dania Martínez-Alarcón; Alejandro Blanco-Labra; Teresa García-Gasca
Journal:  Int J Mol Sci       Date:  2018-02-21       Impact factor: 5.923

Review 7.  Developments and opportunities in continuous biopharmaceutical manufacturing.

Authors:  Ohnmar Khanal; Abraham M Lenhoff
Journal:  MAbs       Date:  2021 Jan-Dec       Impact factor: 5.857

Review 8.  Strategies to control therapeutic antibody glycosylation during bioprocessing: Synthesis and separation.

Authors:  Elizabeth Edwards; Maria Livanos; Anja Krueger; Anne Dell; Stuart M Haslam; C Mark Smales; Daniel G Bracewell
Journal:  Biotechnol Bioeng       Date:  2022-02-28       Impact factor: 4.395

9.  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

  9 in total

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