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From microscopy images to mechanical models of tissues and back

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Fluorescence microscopy has become the most common technique for quantifying biological systems, from the subcellular scale to the tissue scale. Yet, extracting meaningful physical information from fluorescent images, especially in 3D, remains a challenging task. At the same time, physical and computer models of tissues are becoming more and more realistic, but their direct comparison, calibration or initialization from biological images remains generally out of reach. Here I will present our recent efforts to bridge the gap between images and mechanical models. I will start with the presentation of a novel segmentation and 3D tension inference method that can generate 3D atlases of the mechanics of embryos or tissues comprising up to a thousand cells from microscopy images. Then I will present a novel cell-resolved computational model of 3D tissues based on tension, which explicitly accounts for viscous dissipation at cell interfaces, can handle cell divisions or other topological events (T1, T2) and can coupled to a discrete reaction-diffusion scheme to model multicellular mechanochemical feedbacks. Finally, I will show how we can close the loop with a generic pipeline to create realistic fluorescence microscopy images from for devising, training or benchmarking novel image analysis methods.

Lab Twitter/X account: @virtual_embryo

Personal Twitter/X account: @HerveTurlier

This talk is part of the Morphogenesis Seminar Series series.

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