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Evaluating metabolic stress and plasmid stability in plasmid DNA production by Escherichia coli

期刊

BIOTECHNOLOGY ADVANCES
卷 30, 期 3, 页码 691-708

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.biotechadv.2011.12.005

关键词

Escherichia coli; Metabolic burden; Plasmid stability; Bioprocess monitoring techniques

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In the context of recombinant DNA technology, the development of feasible and high-yielding plasmid DNA production processes has regained attention as more evidence for its efficacy as vectors for gene therapy and DNA vaccination arise. When producing plasmid DNA in Escherichia coli, a number of biological restraints, triggered by plasmid maintenance and replication as well as culture conditions are responsible for limiting final biomass and product yields. This termed metabolic burden can also cause detrimental effects on plasmid stability and quality, since the cell machinery is no longer capable of maintaining an active metabolism towards plasmid synthesis and the stress responses elicited by plasmid maintenance can also cause increased plasmid instability. The optimization of plasmid DNA production bioprocesses is still hindered by the lack of information on the host metabolic responses as well as information on plasmid instability. Therefore, systematic and on-line approaches are required not only to characterise this metabolic burden and plasmid stability but also for the design of appropriate metabolic engineering and culture strategies. The monitoring tools described to date rapidly evolve from laborious, off-line and at-line monitoring to online monitoring, at a time-scale that enables researchers to solve these bioprocessing problems as they occur. This review highlights major E. coli biological alterations caused by plasmid maintenance and replication, possible causes for plasmid instability and discusses the ability of currently employed bioprocess monitoring techniques to provide information in order to circumvent metabolic burden and plasmid instability, pointing out the possible evolution of these methods towards online bioprocess monitoring. (C) 2012 Elsevier Inc. All rights reserved.

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