Title: Targeted mutagenesis to identify resistance conferring mutations for new drugs for Mycobacterium tuberculosis
Funder: The Academy of Medical Sciences

Abstract: Antibiotic resistance in Mycobacterium tuberculosis is largely driven by spontaneous single nucleotide variants. For many established drugs, e.g. rifampicin, a limited number of well-characterised mutations are responsible for most phenotypic resistance. However, new drugs where resistance is caused by many individually rare mutations are becoming increasingly important (e.g. bedaquiline, delamanid). Their recent introduction and low frequencies of individual mutations make it is challenging to associate genotype and phenotype from of clinical isolates alone. I aim to generate mutations in candidate M. tuberculosis drug resistance genes to identify mutations conferring resistance. I will use two approaches to generate mutants: (i) error-prone PCR mutagenesis and expression on an episomal plasmid, with CRISPR knockdown of the native gene of interest and (ii) CRISPR base editor mutagenesis of native gene of interest. I will focus on resistance to two drugs with a well-characterised basis for resistance (rifampicin, isoniazid) and two which are poorly characterised (bedaquiline, delamanid). Objectives 1. Construct a library of pooled M. tuberculosis strains containing mutated target genes on episomal plasmids generated using error-prone random PCR mutagenesis. 2. Construct a library of pooled M. tuberculosis strains containing mutated target genes using sgRNA-targeted CRISPR base editors to cause controlled mutations in target genes under control of their native promoters. 3. Establish an in vitro infection model with prolonged antibiotic administration, sampling at several time-points with targeted sequencing of gene of interest. Resistant clones will be validated by single colony picks with subsequent minimum inhibitory concentration testing and whole genome sequencing.

Lay abstract: Tuberculosis is an infection that affects the lungs and other parts of the body, and is caused by a bacteria called Mycobacterium tuberculosis. Treatment normally takes six months with four different antibiotics. Sometimes the bacteria can become resistance to some or all of these drugs, causing drug-resistant tuberculosis, which is harder to treat. Resistance occurs due to mutations in the bacterial genome. Traditionally drug resistance was diagnosed by growing bacteria in the laboratory, which takes several weeks. However, a more rapid technique involving sequencing of the bacterial genome is increasingly used. This requires knowing which genetic mutations cause resistance. This is well understood for established drugs, but poorly understood for new drugs as these are not seen that often in patient samples yet. Understanding how and where mutations occur in the genome may also help develop new treatment strategies. The project aim is to use two techniques to artificially insert mutations at different points in the bacterial genome. I will then see which mutations lead to drug resistance and how they affect bacterial survival. Objectives: 1. Induce mutations in genomic areas that confer resistance to two well-understood drugs and two new drugs using an established technique called error-prone PCR mutagenesis 2. Repeat objective 1 with a newer technique called CRISPR base editing 3. Grow mutated bacteria in presence of drugs in order to see which mutations confer resistance. Validate these mutations by repeating genome sequencing and drug resistance testing in culture.

Research activity codes: 5.1 PHARMACEUTICALS
Health categories: INFECTION