Mathematical modelling of clostridial acetone-butanol-ethanol fermentation

Millat, Thomas and Winzer, Klaus (2017) Mathematical modelling of clostridial acetone-butanol-ethanol fermentation. Applied Microbiology and Biotechnology, 101 (6). pp. 2251-2271. ISSN 1432-0614

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Abstract

Clostridial acetone-butanol-ethanol (ABE) fermentation features a remarkable shift in the cellular metabolic activity from acid formation, acidogenesis, to the production of industrial-relevant solvents, solventogensis. In recent decades, mathematical models have been employed to elucidate the complex interlinked regulation and conditions that determine these two distinct metabolic states and govern the transition between them. In this review, we discuss these models with a focus on the mechanisms controlling intra- and extracellular changes between acidogenesis and solventogenesis. In particular, we critically evaluate underlying model assumptions and predictions in the light of current experimental knowledge. Towards this end, we briefly introduce key ideas and assumptions applied in the discussed modelling approaches, but waive a comprehensive mathematical presentation. We distinguish between structural and dynamical models, which will be discussed in their chronological order to illustrate how new biological information facilitates the ‘evolution’ of mathematical models. Mathematical models and their analysis have significantly contributed to our knowledge of ABE fermentation and the underlying regulatory network which spans all levels of biological organization. However, the ties between the different levels of cellular regulation are not well understood. Furthermore, contradictory experimental and theoretical results challenge our current notion of ABE metabolic network structure. Thus, clostridial ABE fermentation still poses theoretical as well as experimental challenges which are best approached in close collaboration between modellers and experimentalists.

Item Type: Article
Keywords: Clostridial ABE fermentation, pH-induced metabolic shift, Mathematical modelling, Structural and dynamical models, Batch and continuous culture
Schools/Departments: University of Nottingham, UK > Faculty of Medicine and Health Sciences > School of Life Sciences
Identification Number: 10.1007/s00253-017-8137-4
Depositing User: Eprints, Support
Date Deposited: 03 Feb 2017 13:36
Last Modified: 16 Oct 2017 06:09
URI: http://eprints.nottingham.ac.uk/id/eprint/40316

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