Development of a synthetic biology biosensor using high-level modularity and multi-microbial systems

Abstract

Synthetic biology devices have proven to have a wide variety of applications, especially in the field of biosensors where pollutants, biomarkers, and a range of other stimuli can be detected. However, development of biosensor devices can be difficult due to issues surrounding optimisation, and inefficient use of engineering principles such as reusability, standardisation, and modularity. The work presented in this thesis aimed to investigate whether biosensor development could be aided by a framework which combines high-level modularity and multi-microbial systems. Previous work shows how high-level modularity could be used to develop biological devices but stop short of defining a framework which makes use of engineering principles. Building on previous work, biosensor designs were split into three module types, each of which could be implemented in separate cells and co-cultured to create the biosensor. Tools and resources were researched and developed with the aim of promoting the use of engineering principles within the framework. A pre-existing data standard was extended to allow for standard representation of multi-microbial systems. Additionally, a Python library was developed to allow for trivial and flexible generation of reproducible automation protocols for biosensor characterisation and a range of other synthetic biology workflows. Approaches for optimising biosensors developed within the modular and multi-microbial framework were investigated using computationally informed experimentation. Finally, an approach at implementing light-based intercellular communication is presented