The root meristem is shaped by brassinosteroid control of cell geometry

Abstract

Growth extent and direction determine cell and whole-organ architecture. How they are spatio-temporally modulated to control size and shape is not well known. Here we tackled this question by studying the effect of brassinosteroid (BR) signalling on the structure of the root meristem. Quantification of the three-dimensional geometry of thousands of individual meristematic cells across different tissue types showed that the modulation of BR signalling yields distinct changes in growth rate and anisotropy, which affects the time that cells spend in the meristem and has a strong impact on the final root form. By contrast, the hormone effect on cell volume was minor, establishing cell volume as invariant to the effect of BR. Thus, BR has the highest effect on cell shape and growth anisotropy, regulating the overall longitudinal and radial growth of the meristem, while maintaining a coherent distribution of cell sizes. Moving from single-cell quantification to the whole organ, we developed a computational model of radial growth. The simulation demonstrates how differential BR-regulated growth between the inner and outer tissues shapes the meristem and thus explains the non-intuitive outcomes of tissue-specific perturbation of BR signalling. The combined experimental data and simulation suggest that the inner and outer tissues have distinct but coordinated roles in growth regulation.

Brassinosteroids Mitigate Cadmium Effects in Arabidopsis Root System without Any Cooperation with Nitric Oxide

“…In Arabidopsis, the positive role of BRs in controlling QC identity in addition to auxin [ 46 ] and in interacting with auxin signaling and acropetal auxin transport has been reported [ 47 ]. In addition, present data show that, in the absence of stress, specific eBL concentrations do not change auxin localization in the apices of all root types demonstrating that exogenous low levels of BRs do not alter the correct auxin maxima.…”

Using positional information to provide context for biological image analysis with MorphoGraphX 2.0

“…Most of the volume growth occurs along the longitudinal direction and is reflected by the increase in cell length, which is highly synchronized due to the physical connections of the cell layers ( Figure 7F ). Growth along width and depth directions is less synchronized, but much smaller than the length increase, reflecting the strong anisotropic growth of this system ( Fridman et al, 2021 )⁠.…”

“…Surface landmarks can also be combined with 3D cell centers and/or face centers as material points to improve the internal resolution of the deformation functions for full 3D samples. These techniques allow the methods used to calculate growth rates and PDGs in 2.5D to be extended to full 3D ( Figure 7 ; Fridman et al, 2021 )⁠. Cell proliferation and most of the other measures can also be quantified from 3D time-lapse data ( Figure 7—figure supplement 1 ).…”

“…MorphoGraphX is a computer software platform that is specialized for image processing on surface layers of cells ( Barbier de Reuille et al, 2015 )⁠. It has proven especially useful for the analysis of confocal microscopy images from time-lapse data in order to quantify the cellular-level dynamics of growth, cell division, and gene expression (e.g., Bringmann and Bergmann, 2017 ; Feng et al, 2018 ; Hervieux et al, 2016 ; Hong et al, 2016 ; Kierzkowski et al, 2019 ; Louveaux et al, 2016 ; Sapala et al, 2018 ; Scheuring et al, 2016 ; Tsugawa et al, 2017 ; Vlad et al, 2014 ; Zhang et al, 2020 ; Zhu et al, 2020 ; Fridman et al, 2021 )⁠. Key to the approach taken in the software is the representation of cell layers as curved, triangulated surface meshes that capture the overall 3D shape of organs, which retains much of the simplicity of 2D segmentation and lineage tracking.…”

The annotation and analysis of complex 3D plant organs using 3DCoordX

“…Thus, they usually feature a cellular anatomy of manageable complexity. Accordingly, a growing number of realistic 3D digital tissues with cellular resolution are being generated, mainly in the model plant Arabidopsis ( Arabidopsis thaliana ; Bassel et al, 2014 ; Schmidt et al, 2014 ; Yoshida et al, 2014 ; Montenegro-Johnson et al, 2015 , 2019 ; Lora et al, 2017 ; Pasternak et al, 2017 ; Fridman et al, 2021 ; Graeff et al, 2021 ; Hernandez-Lagana et al, 2021 ; Refahi et al, 2021 ; Vijayan et al, 2021 ; Silveira et al, 2022 ).…”