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Reference : UMR7156-JOSSCH-001
Workplace : STRASBOURG
Date of publication : Monday, May 20, 2019
Scientific Responsible name : Joseph Schacherer
Type of Contract : PhD Student contract / Thesis offer
Contract Period : 36 months
Start date of the thesis : 1 September 2019
Proportion of work : Full time
Remuneration : 2 135,00 € gross monthly
Description of the thesis topic
Cells and their proteomes constantly evolve and adapt to survive in a wide variety of ecological niches. While phenotypic diversity arises in populations on relatively short timescales (1 to 100s thousand years), longer timescales (1 to 100s million years) are involved in divergence between species. The signatures of both evolutionary processes are carved in each and every single protein sequence through accumulation of mutations, thereby reshaping cell machineries, including protein complexes, signaling pathways, and metabolic pathways for example.
Interestingly, over long timescales, different proteins accumulate mutations at markedly different rates. For example, orthologous proteins in S. cerevisiae and S. pombe share 42% (+/- 14%) sequence identity on average, but some orthologs exhibit higher conservation. For example, actins share 89.7% sequence identity, illustrating that some proteins tolerate mutations more than others. One biophysical property correlates with sequence divergence more than any other and that is protein abundance. The more abundant a protein, the more conserved its sequence. While the abundance-conservation correlation is well established, its mechanistic origin is not well understood. Toxicity associated with mutation-induced misfolding has been suggested as a possible origin, but recent works, including ours show it is unlikely the main driving mechanism.
To resolve mechanisms shaping protein evolution, we propose to integrate analyses of sequence evolution across timescales. On the one hand, evolution across distant species shows wide dynamic range of sequence conservation, and reflects how entire proteomes diverge with time. On the other hand, it also presents two important drawbacks. First, that functional information of one species (e.g., protein abundance) is implicitly extrapolated to other species, and such an assumption is frequently incorrect. Second, the order in which mutations occur can hardly be traced. For example, considering a gene duplication event that occurred several million years ago, it is impossible to distinguish mutations that occurred right after the duplication event from those that arose later. Remarkably, both of these limitations are resolved when measuring evolution across a population. Indeed, the short evolutionary distances seen across strains mean that functional information can be extrapolated with high confidence, and mutations can be situated in a narrow time-window. Thus, by resolving these limitations, the integration of evolutionary data across species and strains will provide new insights into constraints that biophysics (in particular abundance) versus function place on protein evolution.
This project will unify our view of protein evolution by bridging timescales classically studied separately, and by integrating genomic and proteomic data. The collaboration between our laboratories uniquely allows such integration, with the Schacherer lab being focused on population genomics and the Levy lab being focused on evolution between distant species and on the impact of mutations on protein structure. Equally important, this project will build on recently developed resources, methodologies and concepts from our respective labs. The Schacherer lab has recently sequenced the genomes of over 1,011 isolates from S. cerevisiae and has developed strategies to infer reliable genetic variation from these data. In parallel, the Levy Lab has been developing new concepts to interpret the impact of mutations on proteins, as well as new methodologies for the systematic characterization of entire proteomes.
This thesis will take place at the Laboratory of Molecular Genetics, Genomics and Microbiology (GMGM, UMR7156). It is part of a CNRS-Weizmann Institute of Science collaboration between the teams of Joseph Schacherer (University of Strasbourg / CNRS) and Emmanuel Levy (Weizmann Institute of Science).
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