Leaf epidermis pavement cells form highly complex shapes with interlocking lobes and necks at their anticlinal walls. The microtubule cytoskeleton plays essential roles in pavement cell morphogenesis, in particular at necks. Vice versa, shape generates stress patterns that regulate microtubule organization. Genetic or pharmacological perturbations that affect pavement cell shape often affect microtubule organization. Pavement cell shape and microtubule organization are therefore closely interconnected. Here, we present commonly used approaches for the quantitative analysis of pavement cell shape characteristics and of microtubule organization. In combination with ablation experiments, these methods can be applied to investigate how different genotypes (or treatments) affect the organization and stress responsiveness of the microtubule cytoskeleton.

Leaf epidermis pavement cells develop complex jigsaw puzzle-like shapes in many plant species, including the model plant Arabidopsis thaliana. Due to their complex morphology, pavement cells have become a popular model system to study shape formation and coordination of growth in the context of mechanically coupled cells at the tissue level. To facilitate robust assessment and analysis of pavement cell shape characteristics in a high-throughput fashion, we have developed PaCeQuant and a collection of supplemental tools. The ImageJ-based MiToBo plugin PaCeQuant supports fully automatic segmentation of cell contours from microscopy images and the extraction of 28 shape features for each detected cell. These features now also include the Largest Empty Circle criterion as a proxy for mechanical stress. In addition, PaCeQuant provides a set of eight features for individual lobes, including the categorization as type I and type II lobes at two- and three-cell junctions, respectively. The segmentation and feature extraction results of PaCeQuant depend on the quality of input images. To allow for corrections in case of local segmentation errors, the LabelImageEditor is provided for user-friendly manual postprocessing of segmentation results. For statistical analysis and visualization, PaCeQuant is supplemented with the R package PaCeQuantAna, which provides statistical analysis functions and supports the generation of publication-ready plots in ready-to-use R workflows. In addition, we recently released the FeatureColorMapper tool which overlays feature values over cell regions for user-friendly visual exploration of selected features in a set of analyzed cells.

Plant microtubules form a highly dynamic intracellular network with important roles for regulating cell division, cell proliferation and cell morphology. Its organization and dynamics are coordinated by various microtubule-associated proteins (MAPs) that integrate environmental and developmental stimuli to fine-tune and adjust cytoskeletal arrays. IQ67 DOMAIN (IQD) proteins recently emerged as a class of plant-specific MAPs with largely unknown functions. Here, using a reverse genetics approach, we characterize Arabidopsis IQD5 in terms of its expression domains, subcellular localization and biological functions. We show that IQD5 is expressed mostly in vegetative tissues, where it localizes to cortical microtubule arrays. Our phenotypic analysis of iqd5 loss-of-function lines reveals functions of IQD5 in pavement cell (PC) shape morphogenesis. Histochemical analysis of cell wall composition further suggests reduced rates of cellulose deposition in anticlinal cell walls, which correlate with reduced anisotropic expansion. Lastly, we demonstrate IQD5-dependent recruitment of calmodulin calcium sensors to cortical microtubule arrays and provide first evidence for important roles of calcium in regulation of PC morphogenesis. Our work thus identifies IQD5 as a novel player in PC shape regulation, and, for the first time, links calcium signaling to developmental processes that regulate anisotropic growth in PCs.

The structure of the microtubule cytoskeleton provides valuable information related to morphogenesis of cells. The cytoskeleton organizes into diverse patterns that vary in cells of different types and tissues, but also within a single tissue. To assess differences in cytoskeleton organization methods are needed that quantify cytoskeleton patterns within a complete cell and which are suitable for large data sets. A major bottleneck in most approaches, however, is a lack of techniques for automatic extraction of cell contours. Here, we present a semi-automatic pipeline for cell segmentation and quantification of microtubule organization. Automatic methods are applied to extract major parts of the contours and a handy image editor is provided to manually add missing information efficiently. Experimental results prove that our approach yields high-quality contour data with minimal user intervention and serves a suitable basis for subsequent quantitative studies.

The microtubule cytoskeleton plays important roles in cell morphogenesis. To investigate the mechanisms of cytoskeletal organization, for example, during growth or development, in genetic studies, or in response to environmental stimuli, image analysis tools for quantitative assessment are needed. Here, we present a method for texture measure-based quantification and comparative analysis of global microtubule cytoskeleton patterns and subsequent visualization of output data. In contrast to other approaches that focus on the extraction of individual cytoskeletal fibers and analysis of their orientation relative to the growth axis, CytoskeletonAnalyzer2D quantifies cytoskeletal organization based on the analysis of local binary patterns. CytoskeletonAnalyzer2D thus is particularly well suited to study cytoskeletal organization in cells where individual fibers are difficult to extract or which lack a clearly defined growth axis, such as leaf epidermal pavement cells. The tool is available as ImageJ plugin and can be combined with publicly available software and tools, such as R and Cytoscape, to visualize similarity networks of cytoskeletal patterns.

Morphological analysis of cell shapes requires segmentation of cell contours from input images and subsequent extraction of meaningful shape descriptors that provide the basis for qualitative and quantitative assessment of shape characteristics. Here, we describe the publicly available ImageJ plugin PaCeQuant and its associated R package PaCeQuantAna, which provides a pipeline for fully automatic segmentation, feature extraction, statistical analysis, and graphical visualization of cell shape properties. PaCeQuant is specifically well suited for analysis of jigsaw puzzle-like leaf epidermis pavement cells from 2D input images and supports the quantification of global, contour-based, skeleton-based, and pavement cell-specific shape descriptors.

Plant microtubules form a highly dynamic intracellular network with important roles for regulating cell division, cell proliferation and cell morphology. Its organization and dynamics are coordinated by various microtubule-associated proteins (MAPs) that integrate environmental and developmental stimuli to fine-tune and adjust cytoskeletal arrays. IQ67 DOMAIN (IQD) proteins recently emerged as a class of plant-specific MAPs with largely unknown functions. Here, using a reverse genetics approach, we characterize Arabidopsis IQD5 in terms of its expression domains, subcellular localization and biological functions. We show that IQD5 is expressed mostly in vegetative tissues, where it localizes to cortical microtubule arrays. Our phenotypic analysis of iqd5 loss-of-function lines reveals functions of IQD5 in pavement cell (PC) shape morphogenesis, as indicated by reduced interdigitation of neighboring cells in the leaf epidermis of iqd5 mutants. Histochemical analysis of cell wall composition further suggests reduced rates of cellulose deposition in anticlinal cell walls, which correlate with reduced asymmetric expansion. Lastly, we provide evidence for IQD5-dependent recruitment of calmodulin calcium sensors to cortical microtubule arrays. Our work thus identifies IQD5 as a novel player in PC shape regulation, and, for the first time, links calcium signaling to developmental processes that regulate multi-polar growth in PCs.

Calcium (Ca2+) signaling and dynamic reorganization of the cytoskeleton are essential processes for the coordination and control of plant cell shape and cell growth. Calmodulin (CaM) and closely related calmodulin-like (CML) polypeptides are principal sensors of Ca2+ signals. CaM/CMLs decode and relay information encrypted by the second messenger via differential interactions with a wide spectrum of targets to modulate their diverse biochemical activities. The plant-specific IQ67 DOMAIN (IQD) family emerged as possibly the largest class of CaM-interacting proteins with undefined molecular functions and biological roles. Here, we show that the 33 members of the IQD family in Arabidopsis (Arabidopsis thaliana) differentially localize, using green fluorescent protein (GFP)-tagged proteins, to multiple and distinct subcellular sites, including microtubule (MT) arrays, plasma membrane subdomains, and nuclear compartments. Intriguingly, the various IQD-specific localization patterns coincide with the subcellular patterns of IQD-dependent recruitment of CaM, suggesting that the diverse IQD members sequester Ca2+-CaM signaling modules to specific subcellular sites for precise regulation of Ca2+-dependent processes. Because MT localization is a hallmark of most IQD family members, we quantitatively analyzed GFP-labeled MT arrays in Nicotiana benthamiana cells transiently expressing GFP-IQD fusions and observed IQD-specific MT patterns, which point to a role of IQDs in MT organization and dynamics. Indeed, stable overexpression of select IQD proteins in Arabidopsis altered cellular MT orientation, cell shape, and organ morphology. Because IQDs share biochemical properties with scaffold proteins, we propose that IQD families provide an assortment of platform proteins for integrating CaM-dependent Ca2+ signaling at multiple cellular sites to regulate cell function, shape, and growth.

Pavement cells (PCs) are the most frequently occurring cell type in the leaf epidermis and play important roles in leaf growth and function. In many plant species, PCs form highly complex jigsaw-puzzle-shaped cells with interlocking lobes. Understanding of their development is of high interest for plant science research because of their importance for leaf growth and hence for plant fitness and crop yield. Studies of PC development, however, are limited, because robust methods are lacking that enable automatic segmentation and quantification of PC shape parameters suitable to reflect their cellular complexity. Here, we present our new ImageJ-based tool, PaCeQuant, which provides a fully automatic image analysis workflow for PC shape quantification. PaCeQuant automatically detects cell boundaries of PCs from confocal input images and enables manual correction of automatic segmentation results or direct import of manually segmented cells. PaCeQuant simultaneously extracts 27 shape features that include global, contour-based, skeleton-based, and PC-specific object descriptors. In addition, we included a method for classification and analysis of lobes at two-cell junctions and three-cell junctions, respectively. We provide an R script for graphical visualization and statistical analysis. We validated PaCeQuant by extensive comparative analysis to manual segmentation and existing quantification tools and demonstrated its usability to analyze PC shape characteristics during development and between different genotypes. PaCeQuant thus provides a platform for robust, efficient, and reproducible quantitative analysis of PC shape characteristics that can easily be applied to study PC development in large data sets.