Tuberculosis (TB) remains a global public health emergency with 1.5 million people dying from the disease every year. TB is caused by a group of closely related bacteria known as the Mycobacterium tuberculosis complex (MTBC). The global TB epidemic is made worse by the emergence of MTBC strains resistant to multiple antibiotics and the lack of an effective vaccine. The outcome of TB infection and disease is highly variable ranging from latent infection to pulmonary and extrapulmonary disease.
To date, most of the work on host-pathogen interaction in TB has focused on patient and environmental variables, neglecting the phylogenetic diversity of MTBC clinical strains. Yet, an increasing number of experimental studies demonstrate that MTBC clinical strains differ in virulence and immunogenicity, and epidemiological studies show that these strains also differ in transmissibility. However, linking experimental phenotypes to relevant clinical outcomes in patient populations has proven difficult. Because the MTBC has co-evolved with humans for thousands of years, human and MTBC diversity will likely interact in shaping the epidemiology of TB.
In support of this view, we and others have shown using molecular epidemiological approaches that sympatric associations between some MTBC genotypes and their respective human host populations remain stable over time. This is consistent with a specialist phenotype in which MTBC variants have adapted to particular human populations. Other MTBC genotypes occur worldwide, consistent with a generalist phenotype capable of infecting many different human populations. Both generalist and specialist MTBC strains are epidemiologically successful on their own right, which is in contrast to many unsuccessful strains that are generally rare and exhibit a reduced transmission potential. Here we propose to pursue these epidemiological observations experimentally, taking advantage of our ongoing TB patient cohort (TB-DAR) in Dar es Salaam, Tanzania.
The overall goal of this project is to define the detailed population structure and phylogenomic diversity of the MTBC circulating in Dar es Salaam, the evolutionary forces driving this diversity, and its phenotypic consequences as a function of the associated host diversity.
We hypothesise that i) the epidemiological success of generalist versus specialist versus unsuccessful MTBC clinical strains differs as a function of the phylogenetic strain background and the human host population, ii) these differences in epidemiological success are reflected in signatures of selection in the MTBC genome, iii) in experimental phenotypes, and iv) in different demographic, clinical and epidemiological characteristics. We will test these hypotheses by addressing the following three main
1. Analyse the population structure, genomic diversity and signatures of selection in MTBC clinical strains circulating in Dar es Salaam compared to the national and global MTBC diversity.
2. Characterise the phenotypic consequences of MTBC diversity following infection of human macrophages as a function of host variation in Tanzania.
3. Link MTBC population genomic data (Objective 1) to phenotypic data obtained experimentally (Objective 2) with epidemiological data collected through the TB-DAR cohort.
We will take an integrated multidisciplinary approach and combine i) in-depth population genomic analyses of MTBC clinical strains from the TB-DAR cohort compared to our global collection of ~20,000 MTBC genome sequences, ii) dual RNAseq and dual proteomics analyses of TB patient-derived macrophages infected with matched and miss-matched MTBC clinical strains, iii) intracellular bacterial growth assays, iv) cytokine/chemokine measurements of infected macrophages, v) genomic epidemiological analyses of TB transmission, and vi) detailed clinical and epidemiological data collected through the TB-DAR cohort. Importantly, we will be able to correlate MTBC genomic diversity with experimental and clinical phenotypic diversity because all our genomic, functional and epidemiological data will be linked to individual TB patients.
This approach will generate new insights into the genomic diversity and molecular evolution of the MTBC, as well as into the cross-talk between MTBC diversity and host innate immunity in different human genetic backgrounds. Ultimately, this project will improve our understanding of the biology of host-pathogen interaction in TB, so far mainly obtained through model systems, by focusing on human macrophages and MTBC clinical isolates from well-characterised TB patients studied in a well-defined epidemiological context.