title: Experimental evolution can unravel the complex causes of natural selection in clinical infections.
abstract: It is increasingly clear that rapid evolutionary dynamics are an important process in microbial ecology. Experimental evolution, wherein microbial evolution is observed in real-time, has revealed many instances of appreciable evolutionary change occurring on very short timescales of a few days or weeks in response to a variety of biotic and abiotic selection pressures. From clinical infections, including the chronic bacterial lung infections associated with cystic fibrosis that form a focus of my research, there is now abundant evidence suggesting that rapid evolution by infecting microbes contributes to host adaptation, treatment failure and worsening patient prognosis. However, disentangling the drivers of natural selection in complex infection environments is extremely challenging and limits our understanding of the selective pressures acting upon microbes in infections. Controlled evolution experiments can make a vital contribution to this by determining the causal links between predicted drivers of natural selection and the evolutionary responses of microbes. Integration of experimental evolution into studies of clinical infections is a key next step towards a better understanding of the causes and consequences of rapid microbial evolution in infections, and discovering how these evolutionary processes might be influenced to improve patient health.A video of this Prize Lecture, presented at the Society for General Microbiology Annual Conference 2015, can be viewed via this link: Michael A. Brockhurst https://www.youtube.com/watch?v=N1bodVSl27E.
authors.affiliation: Department of Biology, University of York, York YO10 5DD, UK.
authors.forename: Michael A
authors.initials: MA
authors.lastname: Brockhurst
mesh_terms: D000220:Adaptation, Biological; D001424:Bacterial Infections / Q000382:microbiology*; D003550:Cystic Fibrosis / Q000150:complications*; D006801:Humans; D008962:Models, Theoretical; D012641:Selection, Genetic