Bull, Alan T. (2010) The renaissance of continuous culture in the post-genomics age. Journal of Industrial Microbiology & Biotechnology, 37 (10). pp. 993-1021. ISSN 1476-5535. (The full text of this publication is not available from this repository)
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The development of continuous culture techniques 60 years ago and the subsequent formulation of theory and the diversification of experimental systems revolutionised microbiology and heralded a unique period of innovative research. Then, progressively, molecular biology and thence genomics and related high-information-density omics technologies took centre stage and microbial growth physiology in general faded from educational programmes and research funding priorities alike. However, there has been a gathering appreciation over the past decade that if the claims of systems biology are going to be realised, they will have to be based on rigorously controlled and reproducible microbial and cell growth platforms. This revival of continuous culture will be long lasting because its recognition as the growth system of choice is firmly established. The purpose of this review, therefore, is to remind microbiologists, particularly those new to continuous culture approaches, of the legacy of what I call the first age of continuous culture, and to explore a selection of researches that are using these techniques in this post-genomics age. The review looks at the impact of continuous culture across a comprehensive range of microbiological research and development. The ability to establish (quasi-) steady state conditions is a frequently stated advantage of continuous cultures thereby allowing environmental parameters to be manipulated without causing concomitant changes in the specific growth rate. However, the use of continuous cultures also enables the critical study of specified transition states and chemical, physical or biological perturbations. Such dynamic analyses enhance our understanding of microbial ecology and microbial pathology for example, and offer a wider scope for innovative drug discovery; they also can inform the optimization of batch and fed-batch operations that are characterized by sequential transitions states.
|Divisions:||Faculties > Science Technology and Medical Studies > School of Biosciences|
|Depositing User:||Sue Davies|
|Date Deposited:||29 Jun 2011 15:38|
|Last Modified:||07 May 2014 14:30|
|Resource URI:||http://kar.kent.ac.uk/id/eprint/26295 (The current URI for this page, for reference purposes)|