Abstract
The global rise of drug-resistant Mycobacterium tuberculosis necessitates the development of innovative therapeutic strategies and more efficient methods to uncover synergistic drug targets. Traditional approaches to genetic interaction mapping and compound screening remain limited by cost, scalability, and throughput. To overcome these challenges, this thesis leverages CRISPR interference (CRISPRi) to systematically investigate genetic vulnerabilities and interactions within M. tuberculosis.
A central focus of this work was the use of transcriptional repression to study the effects of single and combinatorial gene knockdowns across components of the mycobacterial respiratory chain. These experiments revealed novel interactions that affected cell viability and identified cases where simultaneous gene inhibition led to bactericidal outcomes, suggesting potential for targeted combination therapies.
To scale this approach, a high-throughput CRISPRi platform was developed to interrogate over 3,500 genetic interactions in a single experiment. This platform integrates multiplexed guide RNA design, an adapted multi-passage screening protocol, and a bespoke deep sequencing pipeline to capture dynamic changes in guide abundance over time. The resulting framework provides a powerful tool for mapping genetic interactions at scale and identifying synthetic lethal relationships.
Collectively, this thesis demonstrates how high-throughput CRISPRi screening can accelerate the discovery of druggable vulnerabilities in M. tuberculosis and guide the rational design of next-generation therapeutic combinations to counteract antimicrobial resistance.