PROJECT SUMMARY The human gut microbiome is intimately connected with health, with disruptions of its ecological composition associated with numerous diseases. Manipulations of the microbiome via fecal microbiome transplants (FMTs), in which microbial strains derived from healthy donor stool are introduced to a patient's gut community, have been found to be effective treatments for certain diseases, but less effective for others. In several cases in which FMTs fail to resolve a disease, invading strains fail to colonize, but it is unknown why, and even when strains do colonize, a healthy clinical outcome still is not guaranteed. Experimental evolution studies in mouse and bee microbiomes have shown that strains invading a host rapidly adapt, enabling colonization via physical adherence to host cells, competition with resident strains, and evasion of the host immune system. Despite this strong experimental support for the importance of adaptation during colonization, its role in the human gut microbiome has received little attention. Recently, we and others found that microbiome can evolve rapidly on months and even days, but the impacts of this rapid pace of evolution on the colonization process remains unknown. The main roadblock to linking adaptation and colonization lies in the statistical challenges of quantifying the full landscape of adaptations from noisy metagenomic data. Here I propose to develop new statistical methods that elucidate the evolutionary processes relevant for colonization in the microbiome and apply them to one of the largest datasets of FMT recipients. My lab's main goal is to understand how microbiomes evolve in a range of contexts and timescales. To this end, the overarching objective of my proposed MIRA research program is to elucidate the evolutionary processes that permit colonization of a strain. To fully quantify the mode, tempo, and targets of evolution in the gut microbiome and their relevance to colonization, we will develop novel methodology capable of detecting evolutionary events that are undetectable presently, including evolutionary changes (1) arising within hosts on short timescales and (2) across hosts on longer time scales. To illustrate the potential of our statistical innovations, we will study FMT recipients given that the identities of invading versus resident strains can be easily distinguished. However, FMTs represent an example of a more general phenomenon of colonization relevant to a range of cohorts and questions that my lab is studying, including the role of evolution in infants experiencing an influx of microbes at birth, strain turnover during consumption of antibiotics and probiotics, and spatial segregation of evolutionary adaptations needed for colonization along the gut. In sum, successful completion of this work will not only generate statistical innovations needed to quantify evolution in the microbiome, but also elucidate the importance of evolution in colonization, knowledge that pr...