Refactoring yeast signalling pathways for tuneable extracellular biosensing
File(s)
Author(s)
Shaw, William
Type
Thesis
Abstract
G protein-coupled receptors (GPCRs) present themselves as an attractive class of membrane protein for use within eukaryotic whole-cell biosensors due to their responsiveness to an extensive and diverse range of ligands. Despite being a comparatively simple organism, Saccharomyces cerevisiae has the complex machinery necessary for coupling heterologous GPCRs to a cellular output, thus enabling this highly amenable chassis with the sensing abilities of higher eukaryotes. Although examples are beginning to emerge within the field of synthetic biology, GPCR signalling in yeast remains an underutilised foundation for the creation of new biosensors. Current designs are often limited due to a mismatch between the input concentrations to which these biosensors respond and the application requirements. Here we present a new platform for rationally tuning GPCR-based biosensors in Saccharomyces cerevisiae to address these limitations. While previous efforts to manipulate GPCR signalling in yeast have involved a top-down approach or overlaying complexity, we sought to identify the minimal requirements to achieve fully tuneable behaviour from the bottom-up. Using genome engineering, we constructed an insulated, modular GPCR signal transduction system to study how the response to stimuli can be predictably tuned using synthetic tools. By systematically refactoring the system, we delineated the contributions of a minimal set of components, identifying robust and straightforward design rules for tuning the sensitivity, leakiness, and signal output. Using these principles, we then established novel community-based approaches for tuning the final dose-response property – the Hill slope. This work enables the development of diverse yeast biosensors that are well-suited to their applications demands, while also providing a framework to guide the reprogramming of GPCR-based signalling in more complex systems.
Version
Open Access
Date Issued
2018-10
Date Awarded
2019-02
Copyright Statement
Creative Commons Attribution NonCommercial NoDerivatives Licence
Advisor
Ellis, Tom
Sponsor
Biotechnology and Biological Sciences Research Council (Great Britain)
Grant Number
BMAD NN0608
Publisher Department
Bioengineering
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)