Projects
Projects: Projects for Investigator |
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| Reference Number | BB/F003390/1 | |
| Title | System biology of Clostridium acetobutylicum - a possible answer to dwindling crude oil reserves | |
| Status | Completed | |
| Energy Categories | Renewable Energy Sources(Bio-Energy, Production of other biomass-derived fuels (incl. Production from wastes)) 50%; Renewable Energy Sources(Bio-Energy, Production of transport biofuels (incl. Production from wastes)) 50%; |
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| Research Types | Basic and strategic applied research 100% | |
| Science and Technology Fields | BIOLOGICAL AND AGRICULTURAL SCIENCES (Biological Sciences) 100% | |
| UKERC Cross Cutting Characterisation | Not Cross-cutting 100% | |
| Principal Investigator |
Prof N (Nigel ) Minton No email address given Centre for Biomolecular Sciences University of Nottingham |
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| Award Type | Research Grant | |
| Funding Source | BBSRC | |
| Start Date | 01 April 2007 | |
| End Date | 30 June 2010 | |
| Duration | 39 months | |
| Total Grant Value | £364,436 | |
| Industrial Sectors | Manufacturing; Transport Systems and Vehicles | |
| Region | East Midlands | |
| Programme | Systems Biology of Microorganisms (SysMo) | |
| Investigators | Principal Investigator | Prof N (Nigel ) Minton , Centre for Biomolecular Sciences, University of Nottingham (99.999%) |
| Other Investigator | Dr K (Klaus ) Winzer , Centre for Biomolecular Sciences, University of Nottingham (0.001%) |
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| Web Site | ||
| Objectives | This grant is linked to BB/F003382/1. |
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| Abstract | Our strategy is to inactivate the genes responsible for AI production and response, and then determine the effect on expression using DNA arrays. Effects will be verified by quantitative RT-PCR and proteome analysis. Qualitative and quantitative data obtained will be used for computational modelling of QS and the major regulatory networks and events occurring during the transition to stationary phase. Predictions derived at different stages of the developing model will be tested, eg., by adjustment of growth conditions and further rounds of mutation. Target gene identification will follow established procedures, ie., generation of AI-deficient mutants and the addition of synthetic AI to mutant cultures. Components of the AI-response system will also be mutated to verify observed changes. Specifically, agrD and luxS mutants will be made and analysed for differential gene expression. Addition of synthetic AIP and AI-2, respectively, will identify those genes dependent on signal production and also allow us to establish threshold concentrations and dose-response relationships. Genes under AIP or AI-2 control will be confirmed by mutation of genes involved in the signal response, ie., agrA and agrC will be inactivated. Furthermore, mutants will be constructed that encodes AgrA locked in either the active or inactive state. Mutants and parent strain will be grown in a chemostat under a set of different conditions. These include growth at varying pH values (shift from acid to solvent formation), different growth rates, and most importantly, different cell densities. This will allow us to identify those conditions where the QS mechanisms are most active or suppressed by other regulatory systems. Such cross-regulatory mechanisms are likely to be revealed through studies undertaken in the other WPs of this proposal: mutation of other major regulatory pathways will identify commonly regulated target genes or even cross-regulation between the major regulators themselves. | |
| Data | No related datasets |
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| Projects | No related projects |
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| Publications | No related publications |
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| Added to Database | 10/12/13 | |
