PhD Oral Exam - Mohamed Nasr, Biology
Designer Biosensors as Tools for Optimizing Engineered Biosynthetic Pathways
This event is free
School of Graduate Studies
When studying for a doctoral degree (PhD), candidates submit a thesis that provides a critical review of the current state of knowledge of the thesis subject as well as the student’s own contributions to the subject. The distinguishing criterion of doctoral graduate research is a significant and original contribution to knowledge.
Once accepted, the candidate presents the thesis orally. This oral exam is open to the public.
Synthetic biology techniques aimed at constructing artificial metabolic pathways in genetically modified microorganisms are important to develop sustainable methods to produce biofuels, pharmaceuticals, and value-added chemicals. To reach industrially relevant scales, challenges related to pathway bottlenecks and system optimization must be addressed. Since these are typically complex multi-enzyme pathways, techniques such as enzyme and genome engineering offer solutions to these limitations. However, screening methods for most products are laborious and inefficient. In this work, we utilize and engineer transcription factor-based biosensors to develop high-throughput molecule detection tools. Bacterial allosteric transcription factors (aTFs) bind a limited set of effectors, which restricts their utility as biosensors. Our aim is to expand the toolbox of available aTFs, which we achieve by using two methods. First, we use high-throughput in vivo biosensor assays to uncover novel ligands for an aTF that could be used towards detecting new chemistries. As well, we employ protein engineering and directed evolution methodologies to engineer another aTF over several generations towards multiple aromatic molecules of increasing complexity, namely catechol, methyl catechol, caffeic acid, protocatechuate, L-DOPA, and the tumour biomarker homovanillic acid. In addition to their response in Escherichia coli, we demonstrate the functionality of our engineered biosensors in the model eukaryote Saccharomyces cerevisiae. Finally, we coupled our engineered biosensors with a genome-wide, multi-functional CRISPR system to identify genetic changes that contribute towards improving the productivity of an engineered cis,cis-muconic acid pathway in Saccharomyces cerevisiae.