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SysMO: Systems Biology of Clostridium acetobutylicum - a possible answer to dwindling crude oil reserves.

Reference Number
BB/F003382/1
Title
SysMO: Systems Biology of Clostridium acetobutylicum - a possible answer to dwindling crude oil reserves.
Status
Completed
Energy Categories
Renewable Energy Sources(Bio-Energy, Production of transport biofuels (incl. Production from wastes))
Renewable Energy Sources(Bio-Energy, Production of other biomass-derived fuels (incl. Production from wastes))
Research Types
Basic and strategic applied research
Science and Technology Fields
PHYSICAL SCIENCES AND MATHEMATICS (Applied Mathematics)
UKERC Cross Cutting Characterisation
Not Cross-cutting
Principal Investigator
Prof J King
Mathematical Sciences
University of Nottingham
Award Type
Research Grant
Funding Source
BBSRC
Start Date
03 April 2007
End Date
02 April 2010
Duration
36 months
Total Grant Value
£260,304
Industrial Sectors
Manufacturing; Transport Systems and Vehicles
Region
East Midlands
Programme
Systems Biology of Microorganisms (SysMo)
Investigators
Principal Investigator
Prof J King, Mathematical Sciences, University of Nottingham
Web Site
Objectives
This grant is linked to BB/F003390/1.
Abstract
The current research forms part of a SysMO project on the systems biology of Clostridium acetobutylicum and is focussed on the development of multiscale mathematical models for key processes involved, namely: (1) intercellular signalling and quorum sensing; (2) the regulatory networks associated with solventogenesis and sporulation; (3) the effects of redox state and glycosylation on solventogenesis; (4) stress response during transition. The main focus will be on the development and analysis of deterministic (primarily ordinary-differential-equation) models describing the above processes; stochastic effects will also be considered where appropriate. These new models will be the subject of extensive numerical simulations, together with parametrisation using, and verification against, experimental data (including that from partner teams). They will also be subject to sensitivity analyses and studies using asymptotic and dynamical-systems approaches in order to enhance their predictive capacity and to maximise the intuition they provide into the complex hierarchies of network interactions that are possible.
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Added to Database
10/12/13