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Title: Harnessing synthetic biology for the bioprospecting and engineering of aromatic polyketide synthases
Author: Cummings, Matthew
ISNI:       0000 0004 7657 2961
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 2018
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Antimicrobial resistant microorganisms are predicted to pose an existential threat to humanity inside of the next 3 decades. Characterisation of novel acting antimicrobial small molecules from microorganisms has historically counteracted this evolutionary arms race, however the bountiful source of pharmaceutically relevant bioactive specialised metabolites discovered in the Golden era of drug discovery has long since dried up. The clinicians' arsenal of useful antimicrobials is diminishing, and a fresh perspective on specialised metabolite discovery is necessary. This call to action is being answered, in part, through advances in genome sequencing, bioinformatics predictions and the development of next generation synthetic biology tools aiming to translate the biological sciences into an engineering discipline. To expedite our route to new pharmaceutically relevant specialised metabolites using the synthetic biology toolbox several bottlenecks need to be addressed, and are tackled here in. Biosynthetic gene clusters (BGCs) represent blueprints to pharmaceuticals, however to date the vast wealth of knowledge about biosynthetic gene clusters is inconsistently reported and sporadically disseminated throughout the literature and databases. To bring the reporting of BGCs in line with engineering principles we designed and built a community supported standard, the Minimum Information about a Biosynthetic Gene cluster (MIBiG), for reporting BGCs in a consistent manner, and centralised this information in an easy to operate and open access repository for rapid retrieval of information, an essential resource for the bioengineer. Prioritisation represents the next bottleneck in specialised metabolite discovery. Bioinformatics tools have predicted a cache of thousands of BGCs within publicly available genome sequences, however high experimental attrition rates drastically slows characterisation of the corresponding specialised metabolite. We designed and built an Output Ordering and Prioritisation System (OOPS), to rank thousands of BGCs in parallel against molecular biology relevant parameters, pairing BGCs with appropriate heterologous expression hosts and facilitating a judicious choice of BGCs for characterisation to reduce experimental attrition. To fully realise the potential of synthetic biology in specialised metabolite discovery a genetically amenable heterologous host, capable of completing rapid design-build-test-learn cycles, is necessary. This cannot be achieved for the pharmaceutically important type II polyketides, as their biosynthetic machinery is largely restricted to Actinobacteria. Using MIBiG datasets, antiSMASH and BLASTP we identify 5 sets of soluble type II polyketide synthases (PKS) in Escherichia coli for the first time. We construct and test the robustness of a plug-and-play scaffold for bioproduction of aromatic polyketides using one PKS in E. coli, yielding anthraquinones, dianthrones and benzoisochromanequinones intermediates. Through bioprospecting for biological 'parts' to expand the chemical diversity of our plug-and-play scaffold we describe a new lineage of type II PKSs predominantly from non-Actinobacteria. The standards, softwares, and plug-and-play scaffold and biosynthetic 'parts' described here-in will act as an engine for rapid and automated bioproduction of existing, and novel, pharmaceutically relevant aromatic polyketides in E. coli using the synthetic biology toolbox.
Supervisor: Micklefield, Jason ; Breitling, Rainer ; Takano, Eriko Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: plug-and-play ; refactoring ; bioprospecting ; Synthetic biology ; Aromatic polyketides ; specialised metabolites