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The renaissance of continuous culture in the post-genomics age

  • Review
  • Published:
Journal of Industrial Microbiology & Biotechnology

Abstract

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.

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Notes

  1. MRE, Porton Down, Wiltshire 1967.

  2. The prediction of observations is a forward problem that has a unique solution; the use of actual observations to infer properties of a system is an inverse problem that may not have a unique solution. “As an example, consider measurements of the gravity field around a planet: given the distribution of mass inside the planet, we can uniquely predict the values of the gravity field around the planet (forward problem), but there are different distributions of mass that give exactly the same gravity field in the space outside the planet. Therefore, the inverse problem—of inferring the mass distribution from observations of the gravity field—has multiple solutions (in fact, an infinite number)” [180].

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Acknowledgments

It is a pleasure to acknowledge the inspirational inputs of numerous students and post-docs in my group over so many years, and of the wider community of continuous culturalists the names of most of whom can be found in Table 2 and from whose friendship my thinking and research has greatly benefited. My thanks to those colleagues who sent me papers prior to publication. Michael Bushell read the review at draft stage and provided valuable comments. This review is dedicated to the next generation of scientists who will carry the torch for continuous culture.

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    Alan T. Bull

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Bull, A.T. The renaissance of continuous culture in the post-genomics age. J Ind Microbiol Biotechnol 37, 993–1021 (2010). https://doi.org/10.1007/s10295-010-0816-4

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