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Title: Tools and technologies for enabling characterisation in synthetic biology
Author: Smith, Jonathan Charles
ISNI:       0000 0004 6061 627X
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2017
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Synthetic Biology represents a movement to utilise biological organisms for novel applications through the use of rigorous engineering principles. These principles rely on a solid and well versed understanding of the underlying biological components and functions (relevant to the application). In order to achieve this understanding, reliable behavioural and contextual information is required (more commonly known as characterisation data). Focussing on lowering the barrier of entry for current research facilities to regularly and easily perform characterisation assays will directly improve the communal knowledge base for Synthetic Biology and enable the further application of rational engineering principles. Whilst characterisation remains a fundamental principle for Synthetic Biology research, the high time costs, subjective measurement protocols, and ambiguous data analysis specifications, deter regular performance of characterisation assays. Vitally, this prevents the valid application of many of the key Synthetic Biology processes that have been derived to improve research yield (with regards to solving application problems) and directly prevent the intended goal of addressing the ad hoc nature of modern research from being realised. Designing new technologies and tools to facilitate rapid 'hands off' characterisation assays for research facilities will improve the uptake of characterisation within the research pipeline. To achieve this two core problem areas have been identified that limit current characterisation attempts in conventional research. Therefore, it was the primary aim of this investigation to overcome these two core problems to promote regular characterisation. The first issue identified as preventing the regular use of characterisation assays was the user-intensive methodologies and technologies available to researchers. There is currently no standardised characterisation equipment for assaying samples and the methodologies are heavily dependent on the researcher and their application for successful and complete characterisation. This study proposed a novel high throughput solution to the characterisation problem that was capable of low cost, concurrent, and rapid characterisation of simple biological DNA elements. By combining in vitro transcription-translation with microfluidics a potent solution to the characterisation problem was proposed. By utilising a completely in vitro approach along with excellent control abilities of microfluidic technologies, a prototype platform for high throughput characterisation was developed. The second issue identified was the lack of flexible, versatile software designed specifically for the data handling needs that are quickly arising within the characterisation speciality. The lack of general solutions in this area is problematic because of the increasing amount of data that is both required and generated for the characterisation output to be considered as rigorous and of value. To alleviate this issue a novel framework for laboratory data handling was developed that employs a plugin strategy for data submission and analysis. Employing a plugin strategy improves the shelf life of data handling software by allowing it to grow with the needs of the speciality. Another advantage to this strategy is the increased ability for well documented processing and analysis standards to arise that are available for all researchers. Finally, the software provided a powerful and flexible data storage schema that allowed all currently conceivable characterisation data types to be stored in a well-documented manner. The two solutions identified within this study increase the amount of enabling tools and technologies available to researchers within Synthetic Biology, which in turn will increase the uptake of regular characterisation. Consequently, this will potentially improve the lateral transfer of knowledge between research projects and reduce the need to perform ad hoc experiments to investigate facets of the fundamental biological components being utilised.
Supervisor: Freemont, Paul S. ; de Mello, John Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral