Drug resistance in Mycobacterium tuberculosis is of serious concern due to the large number of associated deaths worldwide. This resistance is driven by a lack of new therapeutics and patient non-compliance, while re-emergence is driven by immigration. Large scale genomic studies have revealed resistant mutations however, their molecular consequences are poorly understood.
We have used in silico predictive tools to estimate the enthalpic effects of point mutations from a genome wide association study related to isoniazid, rifampicin and D-cycloserine resistance. 189 mutations were identified within catalase peroxidase (katG) conferring isoniazid resistance, 201 within RNA Polymerase-β (rpoB) conferring rifampicin resistance and 48 within alanine racemase (alr) conferring D-cycloserine resistance.
Resistance arose through measurable biophysical changes and were often associated with large steric and electrostatic changes, likely resulting in conformational changes. Only 18% of all mutations lead to the drug resistance phenotype through local effects at the active site, while the remaining 82% acted allosterically. By contrast, frequent mutations correlated with mild effects, thought to impose a lower fitness cost and barrier to resistance.
Together with the Victorian TB Reference Centre, we are building upon this to implement a novel screening strategy to guide patient treatment. Genetic testing for rifampicin resistance has proven unreliable for many local cases, which is compounded by the presence of many uncharacterized rpoB mutations in Victorian patients. Structural and biophysical changes can be used to accurately distinguish whether these uncharacterized variants are likely to be resistant or sensitive to rifampicin or rifabutin.
Analysis of these molecular consequences enables us to statistically identify patterns within mutational effects, to aid the development of new drugs less prone to resistance and, through their integration into predictive tools, in pathogen surveillance.