Evolution of many viruses is so rapid that they can quickly adapt to new hosts or evolve resistance that renders antiviral drugs ineffective. Large population size, high mutation rate, and relative small genome size facilitate rapid and extensive exploration of the local adaptive landscape. It has generally been assumed that evolution has too many degrees of freedom to allow predicting the molecular bases of such changes. However, the molecular changes leading to short-term viral evolution may be predictable when there are limited alternative solutions to an adaptive challenge, or when population size and mutation rate allow the virus to quickly find the best of many possible solutions. 'Predictability' may take the form of general principles, statistical predictions about changes in response to specific adaptive challenges, or definitions of conditions under which evolution is predictable or not. Thus, predictability will give rise to a set of rules of molecular evolution, and we are now well positioned to learn these rules. While it is easy to learn the rules for a specific virus evolving under a defined set of conditions, it is more challenging to determine the generality of these rules. This project uses a bacteriophage model system to begin to address questions about the generality of rules of viral evolution..
The Specific Aims are: 1) to look for signatures of specific evolutionary processes, such as recombination, deletions, and a predictive model of the specific molecular changes that confer gain or loss of host specificity; 3) to assess the impact of the spatial population structure on the trajectory of evolution using coordinated experimental and mathematical models; and 4) to test our ability to accurately reconstruct short-term viral phylogenies using known phylogenies evolved under conditions of large population size, high mutation rate and strong selection. Information from natural isolates will be used to refine our hypothesis about the specific molecular changes involved in host specificity. Experimental evolution will be carried out in chemostats or on plates, and adapted genomes will be sequenced. These experiments will test both the validity and the generality of the hypothesis. A better understanding of the roles of molecular evolution could ultimately help us track pathogens, anticipate and control mechanisms of resistance, and develop long- lasting vaccines and drugs.
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