The production of chemicals using microbes is an area of significant interest for academia and industry. Significant resources are often devoted to strain development not only for the increase of productivity and yield but also for the improvement of robustness and tolerance to industrial production conditions. The genetic regulatory network of microbial organisms has evolved to maximize growth and survival in a variety of dynamic environmental conditions found in nature. Many of these responses can be suboptimal for the purpose of industrial manufacture of valuable bioproducts. A small number of methods have been developed to explore the effect of perturbing these networks with the objective of obtaining improved strains. This thesis explores the use of transcriptional regulatory network rewiring as a general strategy for improvement of strains used in the production of chemical compounds. Libraries generated using a regulatory network rewiring strategy - addition of nodes to wildtype background - were screened for enhanced production of a target compound or other phenotypes of interest. Combinatorial libraries of promoters and coding regions of transcriptional regulators were used to test the strategy towards the improvement of phenotypical limitations of M. smegmatis (growth rate) and for the isolation of strains with improved production of lycopene in P. pastoris. The method was shown to allow for the identification of potential fast growing strains in M. smegmatis and for the isolation of strains with improved production of lycopene in P. pastoris. In the lycopene project, a strain was isolated that was shown to produce significantly higher levels of lycopene in suboptimal aeration conditions as well as modest improvements in non-limited cultures, providing a hint that the strategy could be applied for the development of strains with large phenotypical diversity, and towards the understanding of complex factors limiting production of compounds of interest.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:684264 |
| Date | January 2015 |
| Creators | Rodrigues, Rui Tiago de Lima |
| Contributors | Bayer, Travis |
| Publisher | Imperial College London |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/10044/1/30834 |
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