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A phylogenetic and experimental approach to understand the evolution of microbiota (MicrobiotaEvolution)
Date du début: 1 juin 2011, Date de fin: 31 mai 2016 PROJET  TERMINÉ 

Microbial communities (=microbiota) associated with multicellular organisms play an important role in host nutrition and development. Advances in sequencing technology have revealed an unexpectedly high diversity of microbiota; these advances are not, however, matched by advances in our understanding of the evolutionary factors that structure microbiota. The goal of this proposal is to fill this knowledge gap. Evolutionary models developed for simple host-symbiont relationships have identified a number of factors that shape these relationships: mode of transmission (horizontal versus maternal transmission), host ranges and fitness effects for the host. Together these factors influence the role of selection among hosts and the role of selection within hosts (among microbes), the two levels of selection that are believed to shape host-symbiont coevolution. Here I intend to expand these models to host - microbiota interactions.My objectives are to use next-generation sequencing to conduct a comparative study of bacterial microbiota structure and to combine this work with experiments that explore the underlying evolutionary processes. I will focus on the crustacean family Daphniidae (mainly the genus Daphnia)¿a system ideally suited for studies in the field and laboratory. I will test hypotheses about the evolution of mutualism, virulence, cheating and coevolution, as well as test for the role of mode of transmission and host specificity. The analysis of host-microbiota associations will be conducted for entire microbiota and for stepwise simplified, but biologically meaningful subsets.Testing general models for the evolution of microbiota will have implications far beyond the chosen model system, ranging from ecology and evolution to agricultural sciences and medicine. The proposed study is innovative, significant and risk-taking and will combine skills in evolutionary biology, experimental design, bioinformatics and molecular biology.

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