Optimising synthetic biosynthesis of natural products by yeast genome engineering
File(s)
Author(s)
Gowers, Glen Oliver
Type
Thesis
Abstract
The sustainable manufacturing of products is a cornerstone of society’s move towards a sustainable circular economy. Many industrial specialty and bulk chemicals that are normally derived from fossil fuel can also be made by engineering microbes with biosynthetic pathways. However, augmenting these microbes to reach industrial scale remains a bottleneck in adoption of biological manufacturing practices. Many new synthetic biology tools are being developed to address this bottleneck, leveraging the application of engineering principles to biology. Notably, advances in synthetic genomics are affording novel tools to optimise host microbes towards improved chemical biosynthesis. Furthermore, the modularisation of genetic parts has given rise to automated biosynthetic strain construction workflows. While these technological advances show great promise there remains a dependency on high throughput screening of candidate strains in order to identify those with the highest biosynthesis titre, and therefore most use to industry.
Here, we explored an emerging black box tool to rearrange synthetic yeast chromosomes to rapidly create phenotype diversity. To complement this tool, we developed a higher throughput screening workflow that leveraged automation and a new ultra-fast LCMS method. Further to this we also developed a rapid pre-screening mass spectrometry tool that could screen yeast strains directly from the agar plate, obviating the need for any sample preparation. Finally, we explored how we could improve automated yeast strain construction workflows using a Design of Experiments framework to maximise the probability of identifying strains with the highest biosynthetic potential. Throughout this thesis we used biosynthesis of betulinic acid, a promising therapeutic precursor, as a test metabolite for which biosynthesis is a viable candidate for future industrial scale production. Together, this thesis explored emerging tools in synthetic biology for metabolic engineering and developed complementary higher throughput screening approaches to maximise the benefit they offer.
Here, we explored an emerging black box tool to rearrange synthetic yeast chromosomes to rapidly create phenotype diversity. To complement this tool, we developed a higher throughput screening workflow that leveraged automation and a new ultra-fast LCMS method. Further to this we also developed a rapid pre-screening mass spectrometry tool that could screen yeast strains directly from the agar plate, obviating the need for any sample preparation. Finally, we explored how we could improve automated yeast strain construction workflows using a Design of Experiments framework to maximise the probability of identifying strains with the highest biosynthetic potential. Throughout this thesis we used biosynthesis of betulinic acid, a promising therapeutic precursor, as a test metabolite for which biosynthesis is a viable candidate for future industrial scale production. Together, this thesis explored emerging tools in synthetic biology for metabolic engineering and developed complementary higher throughput screening approaches to maximise the benefit they offer.
Version
Open Access
Date Issued
2020-05
Date Awarded
2021-03
Copyright Statement
Creative Commons Attribution NonCommercial Licence
License URL
Advisor
Ellis, Thomas
Sponsor
Biotechnology and Biological Sciences Research Council (Great Britain)
GlaxoSmithKline
Grant Number
BB/P504579/1
Publisher Department
Bioengineering
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)