Using the Mycobacterium tuberculosis Genome to Predict Tuberculosis Pathology, Drug Resistance Acquisition and Identify Community Transmission Sites

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PROJECT SUMMARY Peru has the second highest incidence of tuberculosis (TB) disease in the Americas [1]. Despite causing the largest number of deaths worldwide due to any single agent infectious disease, no study has yet examined the influence of the pathogen genome on TB pathology as defined by the extent of radiological involvement on the chest radiograph. Therefore, our first Aim is to combine population level genome sequencing data with radiological data and linked clinical and demographic metadata to determine using novel multivariate genome wide association (GWAS) techniques the bacterial genomic biomarkers of TB pathology More than 80% of TB disease arises following a transmission event that occurs outside the home [2]. Understanding where, when and how frequently transmission events occur in the community is therefore critical in order to intervene and prevent spread of the disease. Identifying transmission sites, intervening and thereby preventing transmission is critical to diminishing the spread of primary drug resistance [3]. Therefore, our second Aim is to use population level whole genome sequencing together with real time GPS monitoring and the latest in spatial ecology mapping analysis to uncover new sites of TB transmission relative to matched controls Acquired drug resistance also contributes significantly to the global burden of drug resistance [4]. How TB strain genotype influences the acquisition of drug resistance remains disputed and insufficiently understood [5–11]. Identifying which genetic background is most associated with the acquisition of drug resistance to specific drugs would enable patients with drug susceptible TB to receive a personalized treatment regimen that minimizes the development of drug resistance on that genetic background. Therefore, our third aim is to use a unique set of >9000 bacterial strains collected in Peru at the population level over 20 years to phylogenetically infer which genetic background is associated with drug resistance acquisition; then confirm these findings in the laboratory and on a similar Moldovan dataset collection of >3000 strains. Preliminary studies have identified a TB bacterial genetic background that is highly associated with drug resistance [12]. We have also identified new community sites where significant TB transmission occurs [13] as well as identifying putative bacterial genetic polymorphisms independently associated with pathology in drug resistant TB. Our proposed study could help to diminish TB transmission in the region, identify new biomarkers of pathology, uncover new sites of TB transmission, and identify the bacterial genetic associations with drug resistance acquisition.