alexa Characterization of the stability of recombinant protein production in the GS-NS0 expression system.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Proteomics & Bioinformatics

Author(s): Barnes LM, Bentley CM, Dickson AJ

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Abstract The GS-NS0 system is an important mammalian expression system used largely within industry for the high-level expression of recombinant proteins for therapeutic use. It is essential that the productivity of this system remains stable throughout culture expansion for the successful long-term production of recombinant proteins. Here we present a study of the stability of recombinant protein production from unamplified GS-NS0 cell lines over extended period of continuous culture. The cell lines used in this study were generated by the transfection of NS0 cells with DNA encoding for a secreted recombinant protein and by two subsequent rounds of limiting dilution cloning prior to analysis of stability. The stability of recombinant protein production was assessed at intervals over a period of 134 days using repeated batch culture in shake flasks. Heterogeneous stability was identified. The productivity of some clones remained consistent throughout 134 days of continuous culture. Others exhibit rapid and progressive loss of productivity. Analysis of the causal relationships underlying stability indicates that the initial transfectant determines the susceptibility to loss or retention of productivity. Selection of production clones on the basis of growth and productivity alone will not predict stability during long-term culture. Our research indicates that stable high-producing clones can readily be obtained from use of the GS-NS0 system in the absence of amplification but there may be molecular features of the original transfectants that could serve as very important predictive indicators of the stability of recombinant protein production. Copyright 2001 John Wiley & Sons, Inc.
This article was published in Biotechnol Bioeng and referenced in Journal of Proteomics & Bioinformatics

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