Population genomic analysis of bacterial pathogen niche adaptation
Globally disseminated bacterial pathogens frequently cause epidemics that are of major importance in public health. Of particular significance is the capacity for some of these bacteria to switch into a new environment leading to the emergence of pathogenic clones. Understanding the evolution and epidemiology of such pathogens is essential for designing rational ways for prevention, diagnosis and treatment of the diseases they cause. Whole-genome sequencing of multiple isolates facilitating comparative genomics and phylogenomic analyses provides high-resolution insights, which are revolutionizing our understanding of infectious diseases. In this thesis, a range of population genomic analyses are employed to study the molecular mechanisms and the evolutionary dynamics of bacterial pathogen niche adaptation, specifically between humans, animals and the environment. A large-scale population genomic approach was used to provide a global perspective of the host-switching events that have defined the evolution of Staphylococcus aureus in the context of its host-species. To investigate the genetic basis of host-adaptation, we performed genome-wide association analysis, revealing an array of accessory genes linked to S. aureus host-specificity. In addition, positive selection analysis identified biological pathways encoded in the core genome that are under diversifying selection in different host-species, suggesting a role in host-adaptation. These findings provide a high-resolution view of the evolutionary landscape of a model multi-host pathogen and its capacity to undergo changes in host ecology by genetic adaptation. To further explore S. aureus host-adaptive evolution, we examined the population dynamics of this pathogen after a simulated host-switch event. S. aureus strains of human origin were used to infect the mammary glands of sheep, and bacteria were passaged in multiple animals to simulate onward transmission events. Comparative genomics of passaged isolates allowed us to characterize the genetic changes acquired during the early stages of evolution in a novel host-species. Co-infection experiments using progenitor and passaged strains indicated that accumulated mutations contributed to enhanced fitness, indicating adaptation. Within-host population genomic analysis revealed the existence of population bottlenecks associated with transmission and establishment of infection in new hosts. Computational simulations of evolving genomes under regular bottlenecks supported that the fitness gain of beneficial mutations is high enough to overcome genetic drift and sweep through the population. Overall, these data provide new information relating to the critical early events associated with adaptation to novel host-species. Finally, population genomics was used to study the total diversity of Legionella longbeachae from patient and environmental sources and to investigate the epidemiology of a L. longbeachae outbreak in Scotland. We analysed the genomes of isolates from a cluster of legionellosis cases linked to commercial growing media in Scotland and of non-outbreak-associated strains from this and other countries. Extensive genetic diversity across the L. longbeachae species was identified, associated with intraspecies and interspecies gene flow, and a wide geographic distribution of closely related genotypes. Of note, a highly diverse pool of L. longbeachae genotypes within compost samples that precluded the genetic establishment of an infection source was observed. These data represent a view of the genomic diversity of this pathogen that will inform strategies for investigating future outbreaks. Overall, our findings demonstrate the application of population genomics to understand the molecular mechanisms and the evolutionary dynamics of bacterial adaptation to different ecological niches, and provide new insights relevant to other major bacterial pathogens with the capacity to spread between environments.