Team Charvin - GMGM - Génétique moléculaire, génomique, microbiologie - Université de Strasbourg

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Time-lapse video of individual cells in division trapped in a microfluidic chip.
Left: Classification of the cell state to follow successive divisions of the same cell using a deep learning classification model;
Middle: Wide field microscopy image.
Right: fluorescence microscopy image of a histone-GFP fusion protein. The yellow and red contours represent respectively the cellular and nuclear contours, obtained by segmentation following a deep learning model.

The Quantitative Biology of Cell Growth team studies the fundamental processes that regulate cell growth either in response to environmental changes (stress, nutrients) or during the replicative life of cells (aging). We study how the cell orients its response to a stress (e.g. oxidative stress) either towards an active resistance mechanism or towards a state of tolerance, the prerequisite of which is a total stop of proliferation. Furthermore, we are interested in characterizing in detail the mechanism(s) that limit the replicative proliferation of a cell after a limited number of divisions.

To answer these questions, the originality of the team is to use microfluidics and time-lapse imaging by fluorescence microscopy to follow individual yeast cells in a controlled environment. We are developing our own microfluidic systems as well as image analysis methods based on artificial intelligence (deep learning) to quantitatively and automatically measure cell dynamics in response to environmental changes over time. We are particularly interested in the emergence of phenotypic heterogeneity within micro-cultures and its role as a physiological adaptation strategy.