Internship and thesis proposals
Data-driven modelling of fast evolution in response to environmental changes in bacterial proteins

Domaines
Statistical physics
Biophysics
Nonequilibrium statistical physics
Physics of living systems
Non-equilibrium Statistical Physics

Type of internship
Théorique, numérique
Description
The need to evolve in response to environmental changes has led living organisms to acquire powerful diversification strategies. Among these, Diversity-Generating Retroelements (DGRs) are natural directed mutagenesis systems capable of efficiently exploring sequence space. DGRs have recently been identified and characterized in populations of bacteria from the gut microbiota, allowing them to adapt to and colonize the human gut, particularly by diversifying ligand-binding proteins, including pilus-associated adhesins. In this internship project, we propose to study the extent to which a generic protein can undergo mutations with a DGR system. Our aim is to quantitatively characterize how this system is capable of generating a wide variety of protein variants with appropriate functional and structural properties.Results will be compared to existing data and, if time permits, will be used to generate new DGR template that could be tested by the experimental group of D. Bikard (Institut Pasteur).

Contact
Simona Cocco
Laboratory : LPENS - UMR8023
Team : Biophysique et Neuroscience Théoriques
Team Website
/ Thesis :    Funding :