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Title: Automated BioPart characterisation for synthetic biology
Author: Hirst, Christopher David
ISNI:       0000 0004 5354 7667
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2014
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Synthetic Biology is an approach to the development of biological systems based on engineering principles. By using concepts from other engineering disciplines such as abstraction it is possible to break down complicated biological functions into components termed 'BioParts'. BioParts can be assembled collectively into modules and systems to carry out advanced functions, designed from the bottom up. A key part of this approach is the standardisation of BioParts and practices to aid design, testing and implementation. An automated characterisation methodology focused primarily on promoter BioParts has been developed which is potentially scalable to other BioPart families. The standardised workflow is optimised to enable BioPart characterisation under highly reproducible growth conditions, reliably producing high quality data. It has been designed around automation equipment which should ensure accurate reproduction of experiments at other sites. The automated characterisation workflow has been demonstrated to produce high quality data for both constitutive and inducible promoters. The entire Anderson promoter collection has been characterised and high details results for all library members are available for the first time. A pair of inducible promoter BioPart were characterised to obtain a deep data level regarding their activity in response to inducer over time. To allow the characterisation of more inducible BioParts in a shorter period of time, promoter engineering was also used to generate novel promoters which are induced by xylose. The development of the automated workflow should be a step towards the standardisation of characterisation protocols and production of large numbers of BioParts with associated high quality, reproducible characterisations. Standardisation will further aid the comparison of the data sets produced, potentially shining light on unknown interactions between BioParts and their environment and improving the ability of Synthetic Biologists to design novel biological systems from the ground up.
Supervisor: Kitney, Richard; Baldwin, Geoff; Freemont, Paul Sponsor: Engineering and Physical Sciences Research Council
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral