Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.788197
Title: Automation-aided high-throughput technologies for synthetic biology
Author: Kanigowska, Paulina Julita
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 2011
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Abstract:
Synthetic biology is a research discipline which harnesses technological progress in de novo DNA synthesis as well as combining expertise of biological sciences and engineering research fields to facilitate construction of novel artificial biological systems. Since the past two decades, application of its methodologies has led to significant advances in metabolic engineering, providing alternative biochemical routes for the production of therapeutic products, cosmetics and biofuels. However, several challenges remain to be addressed to support development of synthetic biology applications, notably the demand for faster, cheaper and more reliable DNA manufacturing as well as efficient methods for genome-scale engineering of living organisms. This doctoral thesis proposes new interdisciplinary approaches to these problems, taking advantage of the latest laboratory automation technologies to improve efficiency of modern DNA assembly and genome editing methods. The first results chapter proposes application of a robotic platform for an acoustic liquid transfer for miniaturisation of DNA fabrication. This research, published in 2016, demonstrates the possibility to cost-efficiently assemble DNA in sub-microlitre assembly reactions. The second results chapter presents efforts to develop a method for genome-scale engineering of a model eukaryote, the budding yeast. This work capitalises on the recent progress in on-chip DNA synthesis and the next-generation sequencing (NGS) technology. Finally, the last results chapter demonstrates computational studies to predict and accelerate turnaround times of a commercial DNA supply chain using probabilistic simulations. The developed software is used to estimate sequence-specific DNA manufacturing turnaround times in order to help plan DNA manufacturing and guide decisions regarding further automation of different experimental procedures.
Supervisor: French, Chris ; Cai, Yizhi Sponsor: Engineering and Physical Sciences Research Council (EPSRC)
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.788197  DOI: Not available
Keywords: synthetic biology ; laboratory automation ; high-throughput ; DNA assembly ; miniaturisation ; CRISPR ; process engineering ; data mining
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