RESUMEN
Formation of the apical hook in etiolated dicot seedlings results from differential growth in the hypocotyl apex and is tightly controlled by environmental cues and hormones, among which auxin and gibberellins (GAs) play an important role. Cell expansion is tightly regulated by the cell wall, but whether and how feedback from this structure contributes to hook development is still unclear. Here, we show that etiolated seedlings of the Arabidopsis (Arabidopsis thaliana) quasimodo2-1 (qua2) mutant, defective in pectin biosynthesis, display severe defects in apical hook formation and maintenance, accompanied by loss of asymmetric auxin maxima and of differential cell expansion. Moreover, qua2 seedlings show reduced expression of HOOKLESS 1 (HLS1) and PHYTOCHROME INTERACTING FACTOR 4 (PIF4), which are positive regulators of hook formation. Treatment of wild-type seedlings with the cellulose inhibitor isoxaben (isx) also prevents hook development and represses HLS1 and PIF4 expression. Exogenous GAs, loss of DELLA proteins or HLS1 overexpression partially restore hook development in qua2 and isx-treated seedlings. Interestingly, increased agar concentration in the medium restores, both in qua2 and isx-treated seedlings, hook formation, asymmetric auxin maxima and PIF4 and HLS1 expression. Analysis of plants expressing a FRET-based GA sensor indicate that isx reduces accumulation of GAs in the apical hook region in a turgor-dependent manner. Lack of the cell wall integrity sensor THESEUS 1, which modulates turgor loss point, restores hook formation in qua2 and isx-treated seedlings. We propose that turgor-dependent signals link changes in cell wall integrity to the PIF4-HLS1 signalling module to control differential cell elongation during hook formation.
RESUMEN
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.
Asunto(s)
Proteínas de Arabidopsis/metabolismo , Arabidopsis/metabolismo , Microtúbulos/metabolismo , Fosfotransferasas/metabolismo , Brotes de la Planta/fisiología , Arabidopsis/citología , Arabidopsis/efectos de los fármacos , Proteínas de Arabidopsis/genética , Benzamidas/farmacología , Fenómenos Biomecánicos , Hipocótilo/anatomía & histología , Hipocótilo/efectos de los fármacos , Microtúbulos/efectos de los fármacos , Mutación/genética , Fenotipo , Fosfotransferasas/genética , Brotes de la Planta/citología , Estrés Mecánico , Resistencia a la TracciónRESUMEN
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.