Final Report Summary - INTERRUPTB (Estimating the effective reproductive rate of M. tuberculosis from changes in molecular clustering rates, to measure the impact of public health interventions on TB transmission)
The integration of whole genome sequencing data in all aspects of pathogen detection and tracking is a growing area of research worldwide. Designing appropriate intervention studies requires not only accurate estimations of how pathogens transmit, but assessments of the impact of such interventions on the spread of a disease.
This project attempted to develop a novel model-based approach to assess the impact of an intervention study on curbing the transmission of Mycobacterium tuberculosis, the causative agent of tuberculosis. While setbacks in whole genome sequencing time resulted in delays in applying the modelling approaches that will come to fruition in 2018, many additional projects, findings and publications resulted from this endeavour.
We applied both genome- and transcriptome approaches to uncover the underlying biochemical reasons for the low sensitivity of the rapid TB test for diagnosing M. africanum infections, and the associated slow growth of this particular M. tuberculosis lineage on standard culture media. We found that key mutations in certain metabolic pathways, especially relating to the MPT64 antigen on which the rapid test is based, result in the likely vast under diagnosis and culture positivity of M. africanum. This has large implications for TB detection in West Africa, where this lineage is common, and may explain why M. africanum is thought to be declining in this region. This presumed decline is likely due to less sensitive diagnostic workflows. We will apply Bayesian modeling approaches to test for a true decline in the pathogen population.
We furthermore expanded the phylogeographic coverage of M. tuberculosis complex lineages circulating in the West African region, with the most diverse phylogenetics worldwide (all lineages other than Lineage 7 co-circulate in West Africa), through both retrospective and prospective studies, and identified an association between immunogenicity and transmissibility in M. africanum.
Within this project, we demonstrated the benefit of whole genome approaches for a multitude of research lines within the field of tuberculosis. We applied whole genome sequencing, leading to publications documenting resistance profiles to all main 1st and 2nd line drugs as well as within-host compartmentalisation and establishing fitness costs in HIV-positive populations.
Finally, we applied a Bayesian modelling approach to assess the current methods for transmission clustering in M. tuberculosis, demonstrating the value of whole genome sequencing for fine resolution of recent transmission events. These findings, coupled with the extensive testing and implementation of sequence analysis pipelines, will allow us and others to robustly apply model-based approaches for researching and evaluating the epidemiology of M. tuberculosis and assess the real impact of large scale interventions on turning off the tap of rapidly spreading tuberculosis.
This project attempted to develop a novel model-based approach to assess the impact of an intervention study on curbing the transmission of Mycobacterium tuberculosis, the causative agent of tuberculosis. While setbacks in whole genome sequencing time resulted in delays in applying the modelling approaches that will come to fruition in 2018, many additional projects, findings and publications resulted from this endeavour.
We applied both genome- and transcriptome approaches to uncover the underlying biochemical reasons for the low sensitivity of the rapid TB test for diagnosing M. africanum infections, and the associated slow growth of this particular M. tuberculosis lineage on standard culture media. We found that key mutations in certain metabolic pathways, especially relating to the MPT64 antigen on which the rapid test is based, result in the likely vast under diagnosis and culture positivity of M. africanum. This has large implications for TB detection in West Africa, where this lineage is common, and may explain why M. africanum is thought to be declining in this region. This presumed decline is likely due to less sensitive diagnostic workflows. We will apply Bayesian modeling approaches to test for a true decline in the pathogen population.
We furthermore expanded the phylogeographic coverage of M. tuberculosis complex lineages circulating in the West African region, with the most diverse phylogenetics worldwide (all lineages other than Lineage 7 co-circulate in West Africa), through both retrospective and prospective studies, and identified an association between immunogenicity and transmissibility in M. africanum.
Within this project, we demonstrated the benefit of whole genome approaches for a multitude of research lines within the field of tuberculosis. We applied whole genome sequencing, leading to publications documenting resistance profiles to all main 1st and 2nd line drugs as well as within-host compartmentalisation and establishing fitness costs in HIV-positive populations.
Finally, we applied a Bayesian modelling approach to assess the current methods for transmission clustering in M. tuberculosis, demonstrating the value of whole genome sequencing for fine resolution of recent transmission events. These findings, coupled with the extensive testing and implementation of sequence analysis pipelines, will allow us and others to robustly apply model-based approaches for researching and evaluating the epidemiology of M. tuberculosis and assess the real impact of large scale interventions on turning off the tap of rapidly spreading tuberculosis.