Experimental studies on ecological and genetic complexity in adaptation

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Why is the natural world so diverse? Arguably, this question remains one of the central unresolved problems in biology. My research aims to supply an answer. My aim is to provide a general, empirically-grounded theory for the origins and fate of biodiversity. I use microbial model systems to test foundational theories in evolution through experiment to do this, a technique known as experimental evolution. This approach allows me to track the emergence and fate of diversity in real time and, in combination with genome sequencing, allows me to identify the genetic changes responsible for adaptation and diversification. The research proposed here asks how well our existing models fare at explaining patterns of adaptive diversification when confronted with more ecologically and genetically complex systems than have been considered previously. Our short-term objectives are (1) to evaluate the impact of network topology on adaptation in metapopulations and, (2) test predictions on how the structure of fitness landscapes - the mapping of genotype to fitness - changes during adaptation. More specifically, we ask whether spatial structure, the network of sub-populations connected by dispersal, impacts the outcome of selection in an otherwise uniform environment. What if the environment is also spatially variable, in the sense that different patches contain different resources or stresses, a situation that should promote the evolution of diversity? How good are models of adaptation at predicting which sequence of genetic changes cause adaptation? This work is motivated by foundational problems, and so will contribute to basic knowledge in evolution, genetics, and ecology and training at least 17 highly qualified people, from undergraduate through to PhD, over the course of this grant. However, the lens through which much of this research happens is the management of pathogenic microbes, especially in regards to antimicrobial resistance. It has long been appreciated that many of the challenges we face in treating infectious disease have evolution at their core. This work constitutes a first step towards evaluating evolutionary theories that can inform practical solutions associated with the treatment and management of infectious disease.