Evolutionary processes underlie the etiology of many human diseases. For example, the progress of infectious disease, be it chronic or acute, is an evolutionary process, in which pathogens engage in an arms race with their human hosts. In modern times, vaccines and antibiotics have enabled mankind to skew the outcome of these contests. However, these bulwarks against contagion are being steadily eroded. Mutation and natural selection, coupled with the rapid generation times and immense pathogen population sizes, appear to provide pathogens a decisive advantage in the evolutionary contest. To regain the upper hand we must better understand the evolutionary process itself, to aid in the development of novel classes of antimicrobials and devise therapeutic strategies that take into account how these weapons work and how pathogens adaptively evolve to subvert them. However, until recently, we have been stymied in our efforts to gain a deep understanding of the adaptive process, because adaptive mutations are rare. My lab has developed a lineage tracking system that uses high throughput sequencing to allows us to follow the evolutionary process in almost real time. We are able to track the evolutionary process, readily isolate thousands of adaptive lineages, remeasure fitness of those lineages across many environments, and cheaply whole genome sequence hundreds to thousands of such mutants. I propose an ambitious, integrated program that will take advantage of this lineage tracking system. First, we will determine how the environment in which a population is evolving ? and the ploidy of that population ? controls which mutations are selected and the distribution of their fitness effects. Next, we will identify how mutations selected in one environment trade-off in others and establish why they do so mechanistically. Lastly, we will investigate epistasis between adaptive mutations, systematically determining the degree to which the sign and magnitude of gene interactions depend on their environmental context. To achieve these goals, we will evolve both haploid and diploid populations of Saccharomyces cerevisiae under a rationally designed set of experimental conditions, isolate hundreds of adaptive lineages from each of these evolutions, then remeasure the fitness of these adaptive clones under each of the other conditions. This experimental program will enable us to describe the ?joint distribution of fitness effects?, a comprehensive picture of a genome?s adaptive possibilities under one condition, the evolutionary constraints on those possibilities others, and the mechanistic connection between those opportunities and constraints, all viewed through the lenses of ploidy and epistasis. Executing this program will provide unprecedented insight the adaptive process under alternative forms of selection and genome structure. Comparative analysis of these mutants will shed light on the underlying genetic circuitry that allows certain evolutionary trajectories to be followed but prevents others. Armed with this deeper understanding of the adaptive process, we will better be able to predict evolutionary futures given knowledge of a genomic present, and maintain the upper hand in our battle with chronic infectious disease.
Evolution underlies the emergence of drug resistance in infectious diseases, as well as the progression of cancer. I propose a comprehensive and integrated program of research, building upon technologies and approaches developed by my lab, which will elucidate mechanistically why mutations that are adaptive in one environment are often maladaptive in others. A detailed understanding of such ?trade-offs? opens the possibility of predicting evolutionary trajectories and improving the design of multi-drug therapy.
