Molecular diagnosis of infectious disease and cancer via synthetic biological methods

Synthetic biology is an emerging field that unveils a new dimension to biology, where the disciplines of engineering and biological sciences are brought together to program novel biological entities or re-wire existing ones. The ultimate goal is to achieve de novo engineering of biological systems to address the most pressing societal issues ranging from environmental and industrial to healthcare while accelerating the progress of fundamental biological research to answer important questions about life. However, the complications, instability and insecurity of a genetic network have hindered the translation of synthetic biological technologies into real-world applications. This thesis aims to contribute partly to these challenges and seeks to address two of the most urgent global health threats at the moment, the COVID-19 pandemic and cancer. To support the testing strategy for COVID-19, I begin by re-purposing a traditional cell-free enzymatic reaction, RT-LAMP to detect multiple targets on the SARS-CoV-2 RNA genome. Reported here are proof-of-concept experiments to demonstrate the diagnostic sensitivity and specificity of this method and highlight the practicality of using RT-LAMP as a rapid diagnostic test for COVID-19. To refine the testing method, I introduce a molecular switch that reduces the false positive likelihood by preventing self- and off-target amplification. In particular, the adoption of molecular switch has seen a drop of the false positive rate from 60 % to 0 % in a RT-LAMP experiment with 20 replicates. Through a large-scale clinical validation, this optimised RT-LAMP is shown to provide COVID-19 diagnosis within a short turn-around time at point-of-care setting. To design a diagnostic for colorectal cancer, I first develop a bacterial whole-cell biosensor by expressing a specific single-domain antibody on the outer membrane of Escherichia coli BL21 to confer binding specificity to a cancer biomarker, carcinoembryonic antigen. I then demonstrate the diagnostic sensitivity of the whole-cell biosensor in a biological agglutination assay format. To transform the whole-cell biosensor into a potential in vivo diagnostic and therapeutic agent, I adopt two different top-down approaches to generate synthetic biological chasses, SimCell and minicell, which are non-replicable, non-growing and metabolically active. These chasses allow the housing and actuation of synthetic circuits without any interference from the host genome, which can thus be exploited for a wide range of healthcare-related applications. Overall, the research on the cell-free system and genome-less chassis described herein provides a genetically stable and secure system to help synthetic biology reach its translational potential.