Literature DB >> 17149768

Molecular portrait of high productivity in recombinant NS0 cells.

Gargi Seth1, Robin J Philp, Ally Lau, Kok Yee Jiun, Miranda Yap, Wei-Shou Hu.   

Abstract

Many important therapeutic proteins are produced in recombinant mammalian cells. Upon the introduction of the product gene, the isolated clones typically exhibit a wide range of productivity and high producers are subsequently selected for use in production. Using DNA microarray, two-dimensional gel electrophoresis (2DE), and iTRAQ as global surveying tools, we examined the transcriptome and proteome profiles of 11 lines of NS0 cells producing the same antibody molecule. Genes that are significantly differentially expressed between high and low producer groups statistically fall into a number of functional classes. Their distribution among the functional classes differs somewhat between transcriptomic and proteomic results. Overall, a high degree of consistency between transcriptome and proteome analysis are seen, although some genes exhibiting inconsistent trends between transcript and protein levels were observed as expected. In a novel approach, functional gene networks were retrieved using computational pathway analysis tools and their association with productivity was tested by physiological comprehension of the possible pathways involved in high recombinant protein production. Network analysis indicates that protein synthesis pathways were altered in high producers at both transcriptome and proteome levels, whereas the effect on cell growth/death pathways was more prominent only at the transcript level. The results suggest a common mechanism entailing the alteration of protein synthesis and cell growth control networks leading to high productivity. However, alternate routes with different sets of genes may be invoked to give rise to the same mechanistic outcomes. Such systematic approaches, combining transcriptomic and proteomic tools to examine high and low producers of recombinant mammalian cells will greatly enhance our capability to rationally design high producer cells. This work is a first step towards shedding a new light on the global physiological landscape of hyper productivity of recombinant cells. (c) 2006 Wiley Periodicals, Inc.

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Year:  2007        PMID: 17149768     DOI: 10.1002/bit.21234

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


  11 in total

Review 1.  Cell culture processes for monoclonal antibody production.

Authors:  Feng Li; Natarajan Vijayasankaran; Amy Yijuan Shen; Robert Kiss; Ashraf Amanullah
Journal:  MAbs       Date:  2010-09-01       Impact factor: 5.857

2.  Proteomic profiling of recombinant cells from large-scale mammalian cell culture processes.

Authors:  Paula Meleady
Journal:  Cytotechnology       Date:  2007-02-24       Impact factor: 2.058

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.  Towards the molecular characterization of the stable producer phenotype of recombinant antibody-producing NS0 myeloma cells.

Authors:  Y Prieto; L Rojas; L Hinojosa; I González; D Aguiar; K de la Luz; A Castillo; R Pérez
Journal:  Cytotechnology       Date:  2011-03-20       Impact factor: 2.058

5.  A multi-omics analysis of recombinant protein production in Hek293 cells.

Authors:  Stefanie Dietmair; Mark P Hodson; Lake-Ee Quek; Nicholas E Timmins; Peter Gray; Lars K Nielsen
Journal:  PLoS One       Date:  2012-08-24       Impact factor: 3.240

6.  Sustained productivity in recombinant Chinese hamster ovary (CHO) cell lines: proteome analysis of the molecular basis for a process-related phenotype.

Authors:  Paula Meleady; Padraig Doolan; Michael Henry; Niall Barron; Joanne Keenan; Finbar O'Sullivan; Colin Clarke; Patrick Gammell; Mark W Melville; Mark Leonard; Martin Clynes
Journal:  BMC Biotechnol       Date:  2011-07-24       Impact factor: 2.563

7.  A Population Proportion approach for ranking differentially expressed genes.

Authors:  Mugdha Gadgil
Journal:  BMC Bioinformatics       Date:  2008-09-18       Impact factor: 3.169

8.  Analyzing clonal variation of monoclonal antibody-producing CHO cell lines using an in silico metabolomic platform.

Authors:  Atefeh Ghorbaniaghdam; Jingkui Chen; Olivier Henry; Mario Jolicoeur
Journal:  PLoS One       Date:  2014-03-14       Impact factor: 3.240

9.  Proteomic differences in recombinant CHO cells producing two similar antibody fragments.

Authors:  Wolfgang Sommeregger; Patrick Mayrhofer; Willibald Steinfellner; David Reinhart; Michael Henry; Martin Clynes; Paula Meleady; Renate Kunert
Journal:  Biotechnol Bioeng       Date:  2016-03-16       Impact factor: 4.530

10.  Transcriptomic and proteomic profiling of two porcine tissues using high-throughput technologies.

Authors:  Henrik Hornshøj; Emøke Bendixen; Lene N Conley; Pernille K Andersen; Jakob Hedegaard; Frank Panitz; Christian Bendixen
Journal:  BMC Genomics       Date:  2009-01-19       Impact factor: 3.969

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