Abstract
The efficacy of antibiotics in treating human infections is currently threatened by the rapid evolution of pathogenic bacteria. This adaptation is enabled in part by horizontal gene transfer (HGT), or the cell-to-cell transfer of genes often between distantly related bacteria. Mobile genetic elements (MGE) are the primary vehicles of HGT, as they can transfer genes between DNA elements within cells and externally between cells. Importantly, the genes MGEs transfer include those conferring multi-drug resistance (MDR). Comparatively little is known about the evolution of MGEs and their genes despite this prodigious role in pathogen adaptation. To address this knowledge deficit my research sought to determine the function of previously uncharacterized genes encoded on MGEs, which influence the evolutionary trajectory of the MGEs themselves. The MGEs in this work are all associated with human pathogens and were investigated using both experimental and bioinformatic approaches. In a plasmid isolated from Bordetella pertussis, the etiological agent of whooping cough, we discovered that one gene of unknown function caused the plasmid to quickly go to extinction in Escherichia coli. Inactivation of this gene led to improved maintenance of the plasmids, likely due to loss of binding to a key plasmid regulator, which changed the transcriptional regulation of the plasmid. This provides an example where evolution of a plasmid regulatory system can enable successful plasmid-host adaptation by restoring host growth rates. We next examined whether such plasmid-encoded genes, who alter host fitness and plasmid host range, might drive plasmid diversification into subgroups. Importantly, this study showed that IncP-1 plasmid core genes primarily evolve through vertical inheritance rather than horizontally via frequent homologous recombination between similar plasmids. Finally, we present bioinformatic software created to investigate horizontally acquired genes of unknown function in the current pandemic strain of Vibrio cholerae. The work in this dissertation collectively highlights both the potential and pitfalls of an increasing reliance on computational predictions, and we show a continued role for both experimental and computational approaches to test biological hypotheses.