Embryo mechanics cartography: inference of 3D force atlases from fluorescence microscopy

Ichbiah, Sacha; Delbary, Fabrice; McDougall, Alex; Dumollard, Rémi; Turlier, Hervé

doi:10.1101/2023.04.12.536641

Cited by 3 publications

(1 citation statement)

References 94 publications

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“…In Drosophila , Kong et al (2019) used FFI to infer tensions in epithelium tissue and ommatidia, and validated the results with single junction laser ablation. More recently, Ichbiah et al (2023) used FFI to infer forces in mouse and ascidian embryos, demonstrating that the inferred tensions explain observed cell shapes without the need for direct measurements. They also applied their method on C. elegans and discussed how the eggshell induces confinement, which is not accounted for by FFI.…”

Section: Introductionmentioning

confidence: 99%

Image-based force inference by biomechanical simulation

Vanslambrouck,

Thiels,

Vangheel

et al. 2023

Preprint

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During morphogenesis, cells precisely generate forces that drive cell shape changes and cellular motion. These forces predominantly arise from contractility of the actomyosin cortex, allowing for cortical tension, protrusion formation, and cell division. Image-based force inference can derive such forces from microscopy images, without complicated and time-consuming experimental set-ups. However, current methods are limited by not accounting for physical confinement and local force generation. Here we propose a force-inference method based on a biophysical model of cell shape, and assess cellular cortical tension, adhesion strength between cells, as well as cytokinesis and protrusion formation. We applied our method on fluorescent microscopy images of the earlyC. elegansembryo. Predictions for cortical tension at the 7-cell stage were validated by measurements using cortical laser ablation. Our non-invasive method facilitates the accurate tracking of force generation, and offers many new perspectives for studying morphogenesis.AvailabilityThe data and code needed to recreate the results are freely available athttps://doi.org/10.5281/zenodo.10223739. The most recent version of the software is maintained athttps://bitbucket.org/pgmsembryogenesis/fides/.Contactrob.jelier@kuleuven.be

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Section: Introductionmentioning

confidence: 99%

Image-based force inference by biomechanical simulation

Vanslambrouck,

Thiels,

Vangheel

et al. 2023

Preprint

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A computational pipeline for spatial mechano-transcriptomics

Hallou,

He,

Simons

et al. 2023

Preprint

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Advances in spatial profiling technologies are providing insights into how molecular programs are influenced by local signaling and environmental cues. However, cell fate specification and tissue patterning involve the interplay of biochemical and mechanical feedback. Here, we develop a computational framework that enables the joint statistical analysis of transcriptional and mechanical signals in the context of spatial transcriptomics. To illustrate the application and utility of the approach, we use spatial transcriptomics data from the developing mouse embryo to infer the forces acting on individual cells, and use these results to identify mechanical, morphometric, and gene expression signatures that are predictive of tissue compartment boundaries. In addition, we use geoadditive structural equation modeling to identify gene modules that predict the mechanical behavior of cells in an unbiased manner. This computational framework is easily generalized to other spatial profiling contexts, m providing a generic scheme for exploring the interplay of biomolecular and mechanical cues in tissues.

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Mechanical characterization of regeneratingHydratissue spheres

Perros,

Biquet-Bisquert,

Ben Meriem

et al. 2023

Preprint

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Hydra vulgaris has long been known for its remarkable regenerative capabilities. As such, they are an historical inspiration for reaction-diffusion systems trying to explain their spontaneous patterning. Recently, it became clear that their patterning is an integrated mechano-chemical process where morphogen dynamics is influenced by tissue mechanics. One roadblock to understand their self-organization is our lack of knowledge about the mechanical properties of these organisms. In this paper, we combined microfluidic developments to perform parallelized microaspiration rheological experiments and numerical simulations to fully characterize these mechanical properties. We found three different behaviors depending on the amount of applied stresses: an elastic response, a visco-elastic one and tissue rupture. Using rheological models of deformable shells, we quantify their elastic modulus, effective viscosity as well as the critical stresses required to switch between behaviors. Based on these experimental results, we propose a full description of the internal tissue mechanics during normal regeneration. Our results provide the first step towards the development of original mechano-chemical models of patterning grounded in quantitative, experimental data.

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Embryo mechanics cartography: inference of 3D force atlases from fluorescence microscopy

Cited by 3 publications

References 94 publications

Image-based force inference by biomechanical simulation

Image-based force inference by biomechanical simulation

A computational pipeline for spatial mechano-transcriptomics

Mechanical characterization of regeneratingHydratissue spheres

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