Toggle Main Menu Toggle Search

Open Access padlockePrints

Experimental and In Silico Modelling Analyses of the Gene Expression Pathway for Recombinant Antibody and By-Product Production in NS0 Cell Lines

Lookup NU author(s): Professor Elaine Martin, Professor Gary Montague

Downloads


Abstract

Monoclonal antibodies are commercially important, high value biotherapeutic drugs used in the treatment of a variety of diseases. These complex molecules consist of two heavy chain and two light chain polypeptides covalently linked by disulphide bonds. They are usually expressed as recombinant proteins from cultured mammalian cells, which are capable of correctly modifying, folding and assembling the polypeptide chains into the native quaternary structure. Such recombinant cell lines often vary in the amounts of product produced and in the heterogeneity of the secreted products. The biological mechanisms of this variation are not fully defined. Here we have utilised experimental and modelling strategies to characterise and define the biology underpinning product heterogeneity in cell lines exhibiting varying antibody expression levels, and then experimentally validated these models. In undertaking these studies we applied and validated biochemical (rate-constant based) and engineering (nonlinear) models of antibody expression to experimental data from four NS0 cell lines with different IgG4 secretion rates. The models predict that export of the full antibody and its fragments are intrinsically linked, and cannot therefore be manipulated individually at the level of the secretory machinery. Instead, the models highlight strategies for the manipulation at the precursor species level to increase recombinant protein yields in both high and low producing cell lines. The models also highlight cell line specific limitations in the antibody expression pathway.


Publication metadata

Author(s): Mead EJ, Chiverton LM, Spurgeon SK, Martin EB, Montague GA, Smales CM, von der Haar T

Publication type: Article

Publication status: Published

Journal: PLoS One

Year: 2012

Volume: 7

Issue: 10

Print publication date: 10/10/2012

Date deposited: 29/10/2012

ISSN (electronic): 1932-6203

Publisher: Public Library of Science

URL: http://dx.doi.org/10.1371/journal.pone.0047422

DOI: 10.1371/journal.pone.0047422


Altmetrics

Altmetrics provided by Altmetric


Funding

Funder referenceFunder name
BBSRC
BB/E005969/1EPSRC under the Bioprocessing Research Industry Club (BRIC) initiative

Share