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Stage de M2: Identifying adaptive and evolutionary drivers of microorganisms living in extreme environments
Life can be found even the most inhospitable environments on Earth, such as radioactive waste sites, acid mine drainage, hot springs, or environmental ices (snow and glaciers), which contain many viable microorganisms. Importantly, the phylogenetic diversity of these environments is incompletely described. Typically, environmental sequences lacking taxonomic annotations are considered to form a ‘microbial dark matter’. The driving forces for microbial community structure and function, including dark microbes, are likely the result of the physical-chemical conditions that define their habitats. For extreme environments these can include: low temperatures, scarcity of nutrients and water as well as high radiation. These environmental conditions vary temporally as well as spatially and require physiological acclimation and microbial adaptation. The comparison of molecular sequences from organisms, environmental samples and mobile genetic elements are crucial for studying genes, genomes and species evolution, and to mine the microbial dark matter to discover novel, deep branching microbial groups. The recent advances in sequencing technologies have led to an exponential increase in molecular sequences, however much of this data remains underexplored due to bioinformatic analysis limitations. In order to further enhance the evolutionary comparison of molecular sequences, large complex similarity networks (typically a few million nodes and tens of millions of edges), adapted to evolutionary biology questions have recently been developed. They allow for fast inclusive comparative analyses of both (highly) divergent and conserved sequences, fully or partly similar. These networks can now be turned into massive phylogenies, allowing to construct inclusive Tree/Webs of life. The main objective of this Master’s project is i) to identify novel, deep branching microbial groups, and ii), if time permits, to identify some of the adaptive/evolutionary processes that these microorganisms undergo to survive and thrive in extreme environments.
Several different metagenomic and metatranscriptomic data sets collected from extreme environments such as Arctic snowpacks, Antarctic ice cores, soils exposed to radioactivity and soils collected in Chernobyl will be analyzed using the above-mentioned approaches. Therefore, this project requires skills in bioinformatics, environmental microbiology and evolutionary biology.
The student will conduct part of the research at the Ampère Laboratory (January/June) and will carry out the network analyses in Paris (February-May).