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Inferring the mechanics of living tissue from statistical analysis of its deformation

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In order to address the complex behaviour of living tissue, we will rely on a very large set of live microscopy data of a very active one observed during the early stages of embryogenesis. Using a mechanical model and a statistical approach of the real data, we will infer both the bulk properties of the tissue and the out-of-equilibrium dynamics conferred by biological activity.

The dynamical and mechanical properties of active matter is a very intense field of research, both theoretically and experimentally [Marchetti et al., 2013]. Biological tissues represent a class of dense active matter, where living cells interact directly and hydrodynamic interactions via a solvent play a minor role. The theoretical description of these systems is either based on a microscopic discrete [Petrolli & Balland, 2019] or on a coarse-grained phenomenological approach [Dicko et al, 2017]. Both cases relie on adhoc assumptions to include active biological effects. We aim at establishing a more realistic mechanical framework for the modeling of active matter, by preserving however a physicist’s reductionist approach. Thereby a first step consists in elucidating the material bulk properties and the resulting microscopic and macroscopic dynamics.
Analysis of real data extracted from video microscopy of a living system will provide the basis for our theoretical developments. We will focus on a 2D model system of living tissues, namely embryonic epithelial tissues. Within the framework of a long term collaboration with developmental biologists of the University of Cambridge, we have access to a large data set of cellular motions (cell divisions and displacements) within monolayers of embryonic tissues. Preliminary work (Master’s project in 2019) shows that this dataset is sufficiently large to allow us to use statistical approaches. This system is driven by cell divisions, cell-cell interactions, and out-of-equilibrium fluctuations transmitted by the cellular cytoskeleton and molecular motors.
The major objective of this Master’s project will be to characterize the bulk properties and dynamics of the tissue using experimental data and to quantify the active materials in terms of macroscopic constitutive laws.

Background and skills expected : The student should be either a physicist, engineer or data scientist interested in complex matter, with a strong will to learn techniques and concepts from other fields. No previous biological knowledge is required.

5 to 6 month internship in LIPHY, Grenoble. A stipend of around 540 €/month will be paid.

Under the supervision of :
Jocelyn Étienne,

RDF of volume center of cells surrounding a dividing cell at 3 different times into the division process