Literature DB >> 18636615

Modeling assembly, aggregation, and chaperoning of immunoglobulin G production in insect cells.

E M Whiteley1, T A Hsu, M J Betenbaugh.   

Abstract

A model for immunoglobulin G (IgG) production in the baculovirus-insect cell system was developed that incorporates polypeptide synthesis, oligomer assembly, protein aggregation, and protein secretion. In addition, the capacity of a chaperone to protect heavy and light chain polypeptides from protein aggregation was considered by including in vitro chaperone-peptide binding and dissociation kinetic constants from the literature. Model predictions were then compared to experiments in which the chaperone immunoglobulin heavy chain binding protein, BiP, was coexpressed by coinfecting insect cells with BiP-containing baculovirus. The model predicted a nearly twofold increase in intracellular and secreted IgG that was similar to the behavior observed experimentally after approximately 3 days of coexpressing heterologous IgG and BiP. However, immunoglobulin aggregation was still significant in both the model simulation and experiments, so the model was then used to predict the effect of strategies for improving IgG production even further. Increasing expression of the chaperone BiP by 10-fold over current experimental levels provided a 2.5-fold increase in secreted IgG production over IgG assembly without BiP. Alternatively, the expression of BiP earlier in the baculovirus infection cycle achieved a twofold increase in protein secretion without requiring excessive BiP production. The potential effect of cochaperones on BiP activity was considered by varying the BiP binding and release constants. The utilization of lower binding and release kinetic constants led to a severalfold increase in IgG secretion because the polypeptides were protected from aggregation for greater periods. An optimized strategy for chaperone action would include the rapid peptide binding of a BiP-ATP conformation along with the slow peptide release of a BiP-ligand conformation. However, even with an optimized chaperoning system, limitations in the secretion kinetics can result in the accumulation of intracellular IgG. Thus, the entire secretory pathway must be considered when enhanced secretion of heterologous proteins is desired.

Entities:  

Year:  1997        PMID: 18636615     DOI: 10.1002/(SICI)1097-0290(19971005)56:1<106::AID-BIT12>3.0.CO;2-I

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


  6 in total

Review 1.  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

Review 2.  Insect cells as hosts for the expression of recombinant glycoproteins.

Authors:  F Altmann; E Staudacher; I B Wilson; L März
Journal:  Glycoconj J       Date:  1999-02       Impact factor: 2.916

3.  Modeling and measuring intracellular fluxes of secreted recombinant protein in Pichia pastoris with a novel 34S labeling procedure.

Authors:  Martin Pfeffer; Michael Maurer; Gunda Köllensperger; Stephan Hann; Alexandra B Graf; Diethard Mattanovich
Journal:  Microb Cell Fact       Date:  2011-06-26       Impact factor: 5.328

4.  Immune Response in Mice Immunized with Chimeric H1 Antigens.

Authors:  Erasmus Nikoi Kotey; William Kwabena Ampofo; Rebecca Daines; Jean-Remy Sadeyen; Munir Iqbal; Osbourne Quaye
Journal:  Vaccines (Basel)       Date:  2021-10-15

5.  Engineering of chaperone systems and of the unfolded protein response.

Authors:  Saeed U Khan; Martin Schröder
Journal:  Cytotechnology       Date:  2008-08-15       Impact factor: 2.058

6.  Experimental and in silico modelling analyses of the gene expression pathway for recombinant antibody and by-product production in NS0 cell lines.

Authors:  Emma J Mead; Lesley M Chiverton; Sarah K Spurgeon; Elaine B Martin; Gary A Montague; C Mark Smales; Tobias von der Haar
Journal:  PLoS One       Date:  2012-10-10       Impact factor: 3.240

  6 in total

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