Long-term live-cell imaging techniques for visualizing pavement cell morphogenesis

Mechano-chemical regulation of complex cell shape formation: Epidermal pavement cells-A case study

All plant cells are encased by walls, which provide structural support and control their morphology. How plant cells regulate the deposition of the wall to generate complex shapes is a topic of ongoing research. Scientists have identified several model systems, the epidermal pavement cells of cotyledons and leaves being an ideal platform to study the formation of complex cell shapes. These cells indeed grow alternating protrusions and indentations resulting in jigsaw puzzle cell shapes. How and why these cells adopt such shapes has shown to be a challenging problem to solve, notably because it involves the integration of molecular and mechanical regulation together with cytoskeletal dynamics and cell wall modifications. In this review, we highlight some recent progress focusing on how these processes may be integrated at the cellular level along with recent quantitative morphometric approaches.

Noninvasive Long-Term Imaging of the Cytoskeleton in Arabidopsis Seedlings

The preparation of biological samples, especially for live-cell microscopy, remains a major experimental challenge in the lab despite technological advances. In addition, high-resolution microscopy techniques require higher sample quality and uniformity, which is difficult to ensure during manual preparation while maintaining "ideal" growth conditions. In this protocol, we provide a way out by growing Arabidopsis thaliana seedlings directly in an imaging chamber, which eliminates invasive sample preparation directly before imaging. This method hinges on the precise placement of seeds into imaging chambers, which can be grown in conventional climate chambers. We detail three methods to grow hypocotyls, cotyledons, leaves, and roots for high-resolution and long-term imaging of the plant cytoskeleton. Furthermore, we show that the growth and development of seedlings inside the chambers can be externally manipulated by the addition of chemicals.

Metal-Nano-Ink Coating for Monitoring and Quantification of Cotyledon Epidermal Cell Morphogenesis

During cotyledon growth, the pavement cells, which make up most of the epidermal layer, undergo dynamic morphological changes from simple to jigsaw puzzle-like shapes in most dicotyledonous plants. Morphological analysis of cell shapes generally involves the segmentation of cells from input images followed by the extraction of shape descriptors that can be used to assess cell shape. Traditionally, replica and fluorescent labeling methods have been used for time-lapse observation of cotyledon epidermal cell morphogenesis, but these methods require expensive microscopes and can be technically demanding. Here, we propose a silver-nano-ink coating method for time-lapse imaging and quantification of morphological changes in the epidermal cells of growing Arabidopsis thaliana cotyledons. To obtain high-resolution and wide-area cotyledon surface images, we placed the seedlings on a biaxial goniometer and adjusted the cotyledons, which were coated by dropping silver ink onto them, to be as horizontal to the focal plane as possible. The omnifocal images that had the most epidermal cell shapes in the observation area were taken at multiple points to cover the whole surface area of the cotyledon. The multi-point omnifocal images were automatically stitched, and the epidermal cells were automatically and accurately segmented by machine learning. Quantification of cell morphological features based on the segmented images demonstrated that the proposed method could quantitatively evaluate jigsaw puzzle-shaped cell growth and morphogenesis. The method was successfully applied to phenotyping of the bpp125 triple mutant, which has defective pavement cell morphogenesis. The proposed method will be useful for time-lapse non-destructive phenotyping of plant surface structures and is easier to use than the conversional methods that require fluorescent dye labeling or transformation with marker gene constructs and expensive microscopes such as the confocal laser microscope.

Stomatal development in the context of epidermal tissues

BACKGROUND

Stomata are adjustable pores on the surface of plant shoots for efficient gas exchange and water control. The presence of stomata is essential for plant growth and survival, and the evolution of stomata is considered as a key developmental innovation of the land plants, allowing colonization on land from aquatic environments some 450 million years ago. In the past two decades, molecular genetic studies using the model plant Arabidopsis thaliana identified key genes and signalling modules that regulate stomatal development: master regulatory transcription factors that orchestrate cell state transitions and peptide-receptor signal transduction pathways, which, together, enforce proper patterning of stomata within the epidermis. Studies in diverse plant species, ranging from bryophytes to angiosperm grasses, have begun to unravel the conservation and uniqueness of the core modules in stomatal development.

SCOPE

Here, I review the mechanisms of stomatal development in the context of epidermal tissue patterning. First, I introduce the core regulatory mechanisms of stomatal patterning and differentiation in the model species A. thaliana. Subsequently, experimental evidence is presented supporting the idea that different cell types within the leaf epidermis, namely stomata, hydathodes pores, pavement cells and trichomes, either share developmental origins or mutually influence each other's gene regulatory circuits during development. Emphasis is placed on extrinsic and intrinsic signals regulating the balance between stomata and pavement cells, specifically by controlling the fate of stomatal-lineage ground cells (SLGCs) to remain within the stomatal cell lineage or differentiate into pavement cells. Finally, I discuss the influence of intertissue layer communication between the epidermis and underlying mesophyll/vascular tissues on stomatal differentiation. Understanding the dynamic behaviours of stomatal precursor cells and their differentiation in the broader context of tissue and organ development may help design plants tailored for optimal growth and productivity in specific agricultural applications and a changing environment.

A Sight on Single-Cell Transcriptomics in Plants Through the Prism of Cell-Based Computational Modeling Approaches: Benefits and Challenges for Data Analysis

Single-cell technology is a relatively new and promising way to obtain high-resolution transcriptomic data mostly used for animals during the last decade. However, several scientific groups developed and applied the protocols for some plant tissues. Together with deeply-developed cell-resolution imaging techniques, this achievement opens up new horizons for studying the complex mechanisms of plant tissue architecture formation. While the opportunities for integrating data from transcriptomic to morphogenetic levels in a unified system still present several difficulties, plant tissues have some additional peculiarities. One of the plants' features is that cell-to-cell communication topology through plasmodesmata forms during tissue growth and morphogenesis and results in mutual regulation of expression between neighboring cells affecting internal processes and cell domain development. Undoubtedly, we must take this fact into account when analyzing single-cell transcriptomic data. Cell-based computational modeling approaches successfully used in plant morphogenesis studies promise to be an efficient way to summarize such novel multiscale data. The inverse problem's solutions for these models computed on the real tissue templates can shed light on the restoration of individual cells' spatial localization in the initial plant organ-one of the most ambiguous and challenging stages in single-cell transcriptomic data analysis. This review summarizes new opportunities for advanced plant morphogenesis models, which become possible thanks to single-cell transcriptome data. Besides, we show the prospects of microscopy and cell-resolution imaging techniques to solve several spatial problems in single-cell transcriptomic data analysis and enhance the hybrid modeling framework opportunities.