Mycobacterium tuberculosis genetic diversity
and host-pathogen interactions
Improvement in TB control requires the development of new tools for rapid and accurate diagnosis and intervention. This development is likely to benefit from more detailed knowledge of microbe-host relationships during infection. Following M. tuberculosis infection, only 5-10% of immunocompetent individuals develop TB. It is increasingly thought that the virulence of the infecting strain, together with host genetic factors, contribute to such differences between infected individuals.
The M. tuberculosis W-Beijing lineage is one of the most predominant mycobacterial families, in terms of morbidity and mortality. This lineage has been detected almost worldwide. This predominance of the W-Beijing lineage probably results from genetic advantages, including unidentified virulence factors and the induction/modification of specific host responses not yet thoroughly investigated.
Our research aims to unravel the links between differential host responses to M. tuberculosis infection and mycobacterial genetic diversity and virulence at the global genomic and post-genomic levels within the W-Beijing family, and between the W-Beijing family and other M. tuberculosis families, in order to improve our understanding of the epidemiological success of this particular lineage.
We will use M. tuberculosis strains from different genotypes representative of the genetic diversity found in the Shanghai area, infect host human macrophages and perform a global and comparative profiling of host cell gene expression. This will allow identify signatures in host cell response to infection with different mycobacterial genotypes.
This work will provide to the scientific and clinical community pioneering research and novel information that will help to increase our understanding of the impact of M. tuberculosis strain diversity on virulence, immune response and pathology. This project will complement and expand the efforts of several internationally recognized laboratories to unveil new genotype-phenotype associations by integrating complex phenotypic data and information about mycobacterial genetic diversity.
