Background Many methods have been developed to quantify cell shape in 2D in tissues. For instance, the analysis of epithelial cells in Drosophila embryogenesis or jigsaw puzzle-shaped pavement cells in plant epidermis has led to the development of numerous quantification methods that are applied to 2D images. However, proper extraction of 2D cell contours from 3D confocal stacks for such analysis can be problematic. Results We developed a macro in ImageJ, SurfCut, with the goal to provide a user-friendly pipeline specifically designed to extract epidermal cell contour signals, segment cells in 2D and analyze cell shape. As a reference point, we compared our output to that obtained with MorphoGraphX (MGX). While both methods differ in the approach used to extract the layer of signal, they output comparable results for tissues with shallow curvature, such as pavement cell shape in cotyledon epidermis (as quantified with PaCeQuant). SurfCut was however not appropriate for cell or tissue samples with high curvature, as evidenced by a significant bias in shape and area quantification. Conclusion We provide a new ImageJ pipeline, SurfCut, that allows the extraction of cell contours from 3D confocal stacks. SurfCut and MGX have complementary advantages: MGX is well suited for curvy samples and more complex analyses, up to computational cell-based modeling on real templates; SurfCut is well suited for rather flat samples, is simple to use, and has the advantage to be easily automated for batch analysis of images in ImageJ. The combination of these two methods thus provides an ideal suite of tools for cell contour extraction in most biological samples, whether 3D precision or high-throughput analysis is the main priority. Electronic supplementary material The online version of this article (10.1186/s12915-019-0657-1) contains supplementary material, which is available to authorized users.

To survive, cells must constantly resist mechanical stress. In plants, this involves the reinforcement of cell walls, notably through microtubule-dependent cellulose deposition. How wall sensing might contribute to this response is unknown. Here, we tested whether the microtubule response to stress acts downstream of known wall sensors. Using a multistep screen with 11 mutant lines, we identify FERONIA (FER) as the primary candidate for the cell’s response to stress in the shoot. However, this does not imply that FER acts upstream of the microtubule response to stress. In fact, when performing mechanical perturbations, we instead show that the expected microtubule response to stress does not require FER. We reveal that the feronia phenotype can be partially rescued by reducing tensile stress levels. Conversely, in the absence of both microtubules and FER, cells appear to swell and burst. Altogether, this shows that the microtubule response to stress acts as an independent pathway to resist stress, in parallel to FER. We propose that both pathways are required to maintain the mechanical integrity of plant cells.

To survive, cells must constantly resist mechanical stress. In plants, this involves the reinforcement of cell walls, notably through microtubule-dependent cellulose deposition, and thus wall sensing. Several receptor-like kinases have been proposed to act as mechanosensors. Here we tested whether the microtubule response to stress acts downstream of known wall sensors. Using a multi-step screen with eleven mutant lines, we identify FERONIA as the primary candidate for controlling the microtubule response to stress. However, when performing mechanical perturbations, we show that the microtubule response to stress can be independent from FER. We reveal that the feronia phenotype can be partially rescued by reducing tensile stress levels. Conversely, in the absence of both microtubules and FER, cells swell and burst like soap bubbles. Altogether, this shows that the microtubule response to stress acts as an independent pathway to resist stress, in parallel to FER. We propose that both pathways are key components to turn plant cells from passive to active material.

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