Project Summary/Abstract (from Parent R35 Grant) The progression of cancer and infectious disease is an evolutionary process. Pathogens engage in an arms race with their hosts, and while antibiotics/antivirals have enabled us to skew the outcome of these contests, these bulwarks against contagion are being steadily eroded. Mutation and natural selection, coupled with rapid generation times and immense pathogen population sizes, provide pathogens a decisive advantage. To regain the upper hand, we must better understand the evolutionary process, 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 evade them. Until recently, efforts to gain a deep understanding of the adaptive process were stymied, because adaptive mutations are rare and identifying them is challenging. To solve this, we developed a system to track the evolutionary process, isolate thousands of adaptive lineages, remeasure the fitness of those lineages across many environments, and cheaply whole genome sequence hundreds to thousands of such mutants. I propose a new phase in my ambitious, integrated research program that takes full advantage of this lineage tracking system, and our discovery of Pareto fronts, which are indicative of trade-offs. We will pursue two major goals. First, we will expand our understanding of evolution in the face of abiotic selection pressures, especially those that produce adaptive trade-offs. Specifically, we will determine the role of historical contingency as it pertains to trade-offs in adaptation, the potential for trade-offs to force canalization (e.g., trapping lineages into extreme specialization), the influence that epistasis exerts on the geometry of trait space, and the extent to which adaptive constraints underlie negative and diminishing returns epistasis. Second, we will expand to contrast these findings with evolutionary outcomes under biotic selection pressures, using two new systems. To model genetic conflict and arms race dynamics within species we will use the killer yeast system. Killer yeast secrete a toxin that destroys sensitive yeast, while retaining an intracellular antitoxin. Toxin and antitoxin are both encoded by a vertically inherited virus, which itself parasitizes a second virus. We will co-evolve killer and sensitive cells and determine whether, as theory predicts, there are recurrent periods of selection and whether coevolved solutions show greater trade-offs than typically observed from abiotic selection pressures. To experimentally model arms race dynamics between species we will use crAssphage, one of the most prevalent bacteriophages associated with the human gut microbiome. The aim of these evolution experiments will be to evaluate the dynamics of phage and its bacterial host co-adaptation over trials of short- and medium-term duration. Overall, this integrated, multi-level research strategy will yield fundament...