Transmission and evolution of "Mycobacterium tuberculosis" studied by whole genome sequencing and single nucleotide polymorphism-typing

Abstract

Each year close to 9 million cases of tuberculosis (TB) are caused by bacteria of the Mycobacterium tuberculosis complex (MTBC). The genetic and phenotypic diversity of the pathogen has been underestimated for a long time. Recently, large-scale whole genome sequencing (WGS) became available and has revealed thousands of single nucleotide polymorphisms (SNPs). In contrast to other molecular markers, these SNPs can be used to construct robust phylogenies and to characterize the population structure of MTBC. WGS also shows great promise as the new method of choice for molecular epidemiology of TB. WGS has a higher discriminatory power than classical genotyping methods, and additionally allows for the studying of MTBC micro-evolution during chains of TB transmission. However, for both research and clinical applications, the costs of WGS are still high and the analytical challenges numerous. Routine application of WGS to large collections of MTBC isolates is not yet feasible. Particularly in settings where the burden of TB is highest, the capacities to generate and analyse WGS data are limited. Hence, innovative approaches are needed to identify the subset of MTBC isolates for which WGS brings the highest level of added value. Due to the strictly clonal nature of the MTBC, we can often use single mutations (i.e. SNPs) to identify isolates of a specific genotype. In this thesis, we first aimed at developing new, cost-effective strategies for MTBC strain classification based on SNP-typing. We then aimed at applying a combination of SNP-screening and targeted WGS to study the transmission and micro-evolution of MTBC in a local TB outbreak during 20 years. Third, we aimed at using a similar combination of SNP-typing and WGS to infer the global evolutionary scenario of one particular lineage of MTBC, Lineage 4, during historical times.