dc.contributor.author | Brown, Steven Richard | |
dc.date.accessioned | 2017-03-01T10:32:02Z | |
dc.date.issued | 2016-09-05 | |
dc.description.abstract | The proven ability to ferment Saccharomyces cerevisiae on a large scale presents an attractive target for producing chemicals and fuels from sustainable sources. Efficient and predominant carbon flux through to ethanol is a significant engineering issue in the development of this yeast as a multi-product cell chassis used in biorefineries. In order to evaluate diversion of carbon flux away from ethanol, combinatorial deletions were investigated in genes encoding the six isozymes of alcohol dehydrogenase (ADH), which catalyse the terminal step in ethanol production. The scarless, dominant and counter- selectable amdSYM gene deletion method was optimised for generation of a combinatorial ADH knockout library in an industrially relevant strain of S. cerevisiae. Current understanding of the individual ADH genes fails to fully evaluate genotype-by-genotype and genotype-by-environment interactions: rather, further research of such a complex biological process requires a multivariate mathematical modelling approach. Application of such an approach using the Design of Experiments (DoE) methodology is appraised here as essential for detailed empirical evaluation of complex systems. DoE provided empirical evidence that in S. cerevisiae: i) the ADH2 gene is not associated with producing ethanol under anaerobic culture conditions in combination with 25 g l-1 glucose substrate concentrations; ii) ADH4 is associated with increased ethanol production when the cell is confronted with a zinc-limited [1 μM] environment; and iii) ADH5 is linked with the production of ethanol, predominantly at pH 4.5. A successful metabolic engineering strategy is detailed which increases the product portfolio of S. cerevisiae, currently used for large-scale production of bioethanol. Heterologous expression of the cytochrome P450 fatty acid peroxygenase from Jeotgalicoccus sp., OleTJE, fused to the RhFRED reductase from Rhodococcus sp. NCIMB 978 converted free fatty acid precursors to C13, C15 and C17 alkenes (3.81 ng μl-1 total alkene concentration). | en_GB |
dc.description.sponsorship | Royal Dutch Shell | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/26158 | |
dc.language.iso | en | en_GB |
dc.publisher | University of Exeter | en_GB |
dc.rights.embargoreason | At the request of Industrial sponsor | en_GB |
dc.rights | 5 year embargo | en_GB |
dc.subject | Design of Experiments | en_GB |
dc.subject | Saccharomyces cerevisiae | en_GB |
dc.subject | Metabolic engineering | en_GB |
dc.subject | Hydrocarbon biosynthesis | en_GB |
dc.subject | Yeast | en_GB |
dc.subject | Multivariate | en_GB |
dc.subject | Carbon flux | en_GB |
dc.subject | Ethanol metabolism | en_GB |
dc.subject | Alcohol dehydrogenase | en_GB |
dc.subject | OleT | en_GB |
dc.subject | Genotype by environment | en_GB |
dc.subject | RhFRED | en_GB |
dc.subject | ADH knockout library | en_GB |
dc.subject | Combinatorial gene deletion | en_GB |
dc.subject | Mathematical modelling | en_GB |
dc.subject | Empirical evaluation of complex systems | en_GB |
dc.subject | PLS | en_GB |
dc.subject | Trade off evaluation | en_GB |
dc.subject | Fatty acid-derived biofuel | en_GB |
dc.subject | Biofuel | en_GB |
dc.subject | Ministat | en_GB |
dc.subject | CEN.PK113-7D | en_GB |
dc.subject | Cell factory | en_GB |
dc.subject | Alkene | en_GB |
dc.subject | Isozyme | en_GB |
dc.subject | Experiment design | en_GB |
dc.subject | Data visualisation | en_GB |
dc.subject | Genome scale models | en_GB |
dc.subject | Genotype by genotype | en_GB |
dc.subject | Model | en_GB |
dc.subject | Industrially relevant strain | en_GB |
dc.subject | Biorefinery | en_GB |
dc.title | A Design of Experiments Approach for Engineering Carbon Metabolism in the Yeast Saccharomyces cerevisiae | en_GB |
dc.type | Thesis or dissertation | en_GB |
dc.contributor.advisor | Aves, Stephen J. | |
dc.contributor.advisor | Howard, Thomas P. | |
dc.description | In conclusion, the Design of Experiments approach is beneficial to the rigour of scientific method required to evaluate complex biological systems, and its use would be advantageous for all such multivariate research areas. | en_GB |
dc.publisher.department | College of Life Sciences | en_GB |
dc.type.degreetitle | PhD in Biological Sciences | en_GB |
dc.type.qualificationlevel | Doctoral | en_GB |
dc.type.qualificationname | PhD | en_GB |