STRESS, an automated geometrical characterization of deformable particles forin vivomeasurements of cell and tissue mechanical stresses

Abstract

From cellular mechanotransduction to the formation of embryonic tissues and organs, mechanics has been shown to play an important role in the control of cell behavior and embryonic development. Most of our existing knowledge of how mechanics affects cell behavior comes from in vitro studies, mainly because measuring cell and tissue mechanics in 3D multicellular systems, and especially in vivo, remains challenging. Oil microdroplet sensors, and more recently gel microbeads, use surface deformations to directly quantify mechanical stresses within developing tissues, in vivo and in situ, as well as in 3D in vitro systems like organoids or multicellular spheroids. However, an automated analysis software able to quantify the spatiotemporal evolution of stresses and their characteristics from particle deformations is lacking. Here we develop STRESS (Surface Topography Reconstruction for Evaluation of Spatiotemporal Stresses), an analysis software to quantify the geometry of deformable particles of spherical topology, such as microdroplets or gel microbeads, that enables the automatic quantification of the temporal evolution of stresses in the system and the spatiotemporal features of stress inhomogeneities in the tissue. As a test case, we apply this new code to measure the temporal evolution of mechanical stresses using oil microdroplets in developing zebrafish tissues. Starting from a 3D timelapse of a droplet, the software automatically calculates the statistics of local anisotropic stresses, decouples the deformation modes associated with tissue- and cell-scale stresses, obtains their spatial features on the droplet surface and analyzes their spatiotemporal variations using spatial and temporal stress autocorrelations. The automated nature of the analysis will help users obtain quantitative information about mechanical stresses in a wide range of 3D multicellular systems, from developing embryos or tissue explants to organoids.

Non-Ionic Fluorosurfactants for Droplet-Based in vivo Applications

“…31 The shape of the droplet is reconstituted in 3D using confocal microscopy, and the endogenous stresses are then quantified from the deformations of the droplet and knowledge of the droplet IFT. 31,40,41 If the IFT is too large, cells cannot deform the droplet, precluding any measurements. Therefore, lower IFT values enhance the measurement sensitivity (better signal-to-noise) as they allow cells to deform the droplets more easily.…”

“…In this system, any deviations from the spherical state are noise, as the gel-confined, spherical microdroplet experiences no net forces. We imaged the spherical droplets in 3D using confocal microscopy (Figure 5a') and reconstructed the surface deformations using previously developed STRESS software 41 (Figure 5a''). The width of the distribution of surface mean curvature, H, quantifies the deviations of the droplet curvature from the expected constant mean curvature, H0, of the spherical droplet.…”

“…40 Having determined our measurement sensitivity, we inserted the fluorous formulation (KP600 (2 wt%) and FCy5 (100 µM) in HFE-7700) without and with PEG5PFPE1 (8 wt%) into the anterior presomitic mesoderm (aPSM) of developing zebrafish embryos. Inserted microdroplets, without (Figure b-b''') and with PEG5PFPE1 (Figure c-c'''), were imaged using confocal microscopy (Figure 5b, b' and c, c'), 3D reconstructed and the distribution of droplet mean curvature, H, was quantified using the STRESS software 41 (Figure 5 b'', c''). We then obtained the normalized frequency distribution of the deviations of the mean curvature H from the average mean curvature H0 in each condition (Figure 5b''', c''').…”