Digital Single-Cell Analysis of Plant Organ Development Using 3DCellAtlas

Topological analysis of 3D digital ovules identifies cellular patterns associated with ovule shape diversity

Tissue morphogenesis remains poorly understood. In plants, a central problem is how the 3D cellular architecture of a developing organ contributes to its final shape. We address this question through a comparative analysis of ovule morphogenesis, taking advantage of the diversity in ovule shape across angiosperms. Here, we provide a 3D digital atlas of Cardamine hirsuta ovule development at single cell resolution and compare it with an equivalent atlas of Arabidopsis thaliana. We introduce nerve-based topological analysis as a tool for unbiased detection of differences in cellular architectures and corroborate identified topological differences between two homologous tissues by comparative morphometrics and visual inspection. We find that differences in topology, cell volume variation and tissue growth patterns in the sheet-like integuments and the bulbous chalaza are associated with differences in ovule curvature. In contrast, the radialized conical ovule primordia and nucelli exhibit similar shapes, despite differences in internal cellular topology and tissue growth patterns. Our results support the notion that the structural organization of a tissue is associated with its susceptibility to shape changes during evolutionary shifts in 3D cellular architecture.

A deep learning-based toolkit for 3D nuclei segmentation and quantitative analysis in cellular and tissue context

We present a new set of computational tools that enable accurate and widely applicable 3D segmentation of nuclei in various 3D digital organs. We have developed an approach for ground truth generation and iterative training of 3D nuclear segmentation models, which we applied to popular CellPose, PlantSeg and StarDist algorithms. We provide two high-quality models trained on plant nuclei that enable 3D segmentation of nuclei in datasets obtained from fixed or live samples, acquired from different plant and animal tissues, and stained with various nuclear stains or fluorescent protein-based nuclear reporters. We also share a diverse high-quality training dataset of about 10,000 nuclei. Furthermore, we advanced the MorphoGraphX analysis and visualization software by, among other things, providing a method for linking 3D segmented nuclei to their surrounding cells in 3D digital organs. We found that the nuclear-to-cell volume ratio varies between different ovule tissues and during the development of a tissue. Finally, we extended the PlantSeg 3D segmentation pipeline with a proofreading tool that uses 3D segmented nuclei as seeds to correct cell segmentation errors in difficult-to-segment tissues.

A quantitative morphospace of multicellular organ design in the plant Arabidopsis

Organ function emerges from the interactions between their constituent cells. The investigation of cellular organization can provide insight into organ function following structure-function relationships. Here, we investigate the extent to which properties in cellular organization can arise "for free" as an emergent property of embedding cells in space versus those that are actively generated by patterning processes. Default cellular configurations were established using three-dimensional (3D) digital tissue models. Network-based analysis of these synthetic cellular assemblies established a quantitative topological baseline of cellular organization, granted by virtue of passive spatial packing and the minimal amount of order that emerges for free in tessellated tissues. A 3D cellular-resolution digital tissue atlas for the model plant species Arabidopsis was generated, and the extent to which the organs in this organism conform to the default configurations was established through statistical comparisons with digital tissue models. Cells in different tissues of Arabidopsis do not conform to random packing arrangements to varying degrees. Most closely matching the random models was the undifferentiated shoot apical meristem (SAM) from which aerial organs emanate. By contrast, leaf and sepal tissue showed the greatest deviation from this baseline, suggesting these to be the most "complex" tissues in Arabidopsis. Investigation of the patterning principles responsible for the gap between these tissues and default patterns revealed cell elongation and the introduction of air spaces to contribute toward additional organ patterning complexity. This work establishes a quantitative morphospace to understand the principles of organ construction and its diversity within a single organism.

3D imaging reveals apical stem cell responses to ambient temperature

Plant growth is driven by apical meristems at the shoot and root growth points, which comprise continuously active stem cell populations. While many of the key factors involved in homeostasis of the shoot apical meristem (SAM) have been extensively studied under artificial constant growth conditions, only little is known how variations in the environment affect the underlying regulatory network. To shed light on the responses of the SAM to ambient temperature, we combined 3D live imaging of fluorescent reporter lines that allowed us to monitor the activity of two key regulators of stem cell homeostasis in the SAM namely CLAVATA3 (CLV3) and WUSCHEL (WUS), with computational image analysis to derive morphological and cellular parameters of the SAM. Whereas CLV3 expression marks the stem cell population, WUS promoter activity is confined to the organizing center (OC), the niche cells adjacent to the stem cells, hence allowing us to record on the two central cell populations of the SAM. Applying an integrated computational analysis of our data we found that variations in ambient temperature not only led to specific changes in spatial expression patterns of key regulators of SAM homeostasis, but also correlated with modifications in overall cellular organization and shoot meristem morphology.

Tissues as networks of cells: towards generative rules of complex organ development

Network analysis is a well-known and powerful tool in molecular biology. More recently, it has been introduced in developmental biology. Tissues can be readily translated into spatial networks such that cells are represented by nodes and intercellular connections by edges. This discretization of cellular organization enables mathematical approaches rooted in network science to be applied towards the understanding of tissue structure and function. Here, we describe how such tissue abstractions can enable the principles that underpin tissue formation and function to be uncovered. We provide an introduction into biologically relevant network measures, then present an overview of different areas of developmental biology where these approaches have been applied. We then summarize the general developmental rules underpinning tissue topology generation. Finally, we discuss how generative models can help to link the developmental rule back to the tissue topologies. Our collection of results points at general mechanisms as to how local developmental rules can give rise to observed topological properties in multicellular systems.

Whole-mount smFISH allows combining RNA and protein quantification at cellular and subcellular resolution

Multicellular organisms result from complex developmental processes largely orchestrated through the quantitative spatiotemporal regulation of gene expression. Yet, obtaining absolute counts of messenger RNAs at a three-dimensional resolution remains challenging, especially in plants, owing to high levels of tissue autofluorescence that prevent the detection of diffraction-limited fluorescent spots. In situ hybridization methods based on amplification cycles have recently emerged, but they are laborious and often lead to quantification biases. In this article, we present a simple method based on single-molecule RNA fluorescence in situ hybridization to visualize and count the number of mRNA molecules in several intact plant tissues. In addition, with the use of fluorescent protein reporters, our method also enables simultaneous detection of mRNA and protein quantity, as well as subcellular distribution, in single cells. With this method, research in plants can now fully explore the benefits of the quantitative analysis of transcription and protein levels at cellular and subcellular resolution in plant tissues.

Multiscale microscopy to decipher plant cell structure and dynamics

New imaging methodologies with high contrast and molecular specificity allow researchers to analyze dynamic processes in plant cells at multiple scales, from single protein and RNA molecules to organelles and cells, to whole organs and tissues. These techniques produce informative images and quantitative data on molecular dynamics to address questions that cannot be answered by conventional biochemical assays. Here, we review selected microscopy techniques, focusing on their basic principles and applications in plant science, discussing the pros and cons of each technique, and introducing methods for quantitative analysis. This review thus provides guidance for plant scientists in selecting the most appropriate techniques to decipher structures and dynamic processes at different levels, from protein dynamics to morphogenesis.

To curve for survival: Apical hook development

Apical hook is a simple curved structure formed at the upper part of hypocotyls when dicot seeds germinate in darkness. The hook structure is transient but essential for seedlings' survival during soil emergence due to its efficient protection of the delicate shoot apex from mechanical injury. As a superb model system for studying plant differential growth, apical hook has fascinated botanists as early as the Darwin age, and significant advances have been achieved at both the morphological and molecular levels to understand how apical hook development is regulated. Here, we will mainly summarize the research progress at these two levels. We will also briefly compare the growth dynamics between apical hook and hypocotyl gravitropic bending at early seed germination phase, with the aim to deduce a certain consensus on their connections. Finally, we will outline the remaining questions and future research perspectives for apical hook development.

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

A fundamental question in biology concerns how molecular and cellular processes become integrated during morphogenesis. In plants, characterization of 3D digital representations of organs at single-cell resolution represents a promising approach to addressing this problem. A major challenge is to provide organ-centric spatial context to cells of an organ. We developed several general rules for the annotation of cell position and embodied them in 3DCoordX, a user-interactive computer toolbox implemented in the open-source software MorphoGraphX. 3DCoordX enables rapid spatial annotation of cells even in highly curved biological shapes. Using 3DCoordX, we analyzed cellular growth patterns in organs of several species. For example, the data indicated the presence of a basal cell proliferation zone in the ovule primordium of Arabidopsis (Arabidopsis thaliana). Proof-of-concept analyses suggested a preferential increase in cell length associated with neck elongation in the archegonium of Marchantia (Marchantia polymorpha) and variations in cell volume linked to central morphogenetic features of a trap of the carnivorous plant Utricularia (Utricularia gibba). Our work demonstrates the broad applicability of the developed strategies as they provide organ-centric spatial context to cellular features in plant organs of diverse shape complexity.

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

Positional information is a central concept in developmental biology. In developing organs, positional information can be idealized as a local coordinate system that arises from morphogen gradients controlled by organizers at key locations. This offers a plausible mechanism for the integration of the molecular networks operating in individual cells into the spatially coordinated multicellular responses necessary for the organization of emergent forms. Understanding how positional cues guide morphogenesis requires the quantification of gene expression and growth dynamics in the context of their underlying coordinate systems. Here, we present recent advances in the MorphoGraphX software (Barbier de Reuille et al., 2015⁠) that implement a generalized framework to annotate developing organs with local coordinate systems. These coordinate systems introduce an organ-centric spatial context to microscopy data, allowing gene expression and growth to be quantified and compared in the context of the positional information thought to control them.

Cytokinin promotes growth cessation in the Arabidopsis root

The Arabidopsis root offers good opportunities to investigate how regulated cellular growth shapes different tissues and organs, a key question in developmental biology. Along the root's longitudinal axis, cells sequentially occupy different developmental states. Proliferative meristematic cells give rise to differentiating cells, which rapidly elongate in the elongation zone, then mature and stop growing in the differentiation zone. The phytohormone cytokinin contributes to this zonation by positioning the boundary between the meristem and the elongation zone, called the transition zone. However, the cellular growth profile underlying root zonation is not well understood, and the cellular mechanisms that mediate growth cessation remain unclear. By using time-lapse imaging, genetics, and computational analysis, we analyze the effect of cytokinin on root zonation and cellular growth. We found that cytokinin promotes growth cessation in the distal (shootward) elongation zone in conjunction with accelerating the transition from elongation to differentiation. We estimated cell-wall stiffness by using osmotic treatment experiments and found that cytokinin-mediated growth cessation is associated with cell-wall stiffening and requires the action of an auxin influx carrier, AUX1. Our measurement of growth and cell-wall mechanical properties at a cellular resolution reveal mechanisms via which cytokinin influences cell behavior to shape tissue patterns.

Quantification of Cell Division Angles in the Arabidopsis Root

In many plant tissues, division plane orientation within cell files is highly predictable since all cells divide almost perpendicular to the cell file axis. Many mutations can affect division plane orientation, and the quantification of the deviation from the expected transverse orientation in various genetic backgrounds is thus an important issue.While several software tools have been proposed for the quantification of cellular morphology in plant tissues, none of them allowed investigating division plane orientation. We propose here a complete method for measuring orientation of division planes in 2D, using an open-source ImageJ plugin named "Cell File Angles." The method comprises the staining of cell wall within whole mount roots with the calcofluor dye, the acquisition of 3D Z-stacks of the stained roots, and the measurement of cell wall orientation using image processing algorithms and semi-automated analysis.

Measuring Intercellular Interface Area in Plant Tissues Using Quantitative 3D Image Analysis

The cells which make up plant tissues remain fixed together through shared cell walls. Cell-to-cell communication principally takes place through these shared interfaces through a combination of plasmodesmata, transporters, and the apoplastic space. To better understand the capacity for intercellular communication in plant tissues, this chapter outlines a method which can be used to quantify the surface area of shared intercellular interfaces using whole mount imaging and quantitative 3D image analysis. This method allows the potential for intercellular communication as prescribed by cellular architecture to be measured at single cell resolution.

A single-cell morpho-transcriptomic map of brassinosteroid action in the Arabidopsis root

The effects of brassinosteroid signaling on shoot and root development have been characterized in great detail but a simple consistent positive or negative impact on a basic cellular parameter was not identified. In this study, we combined digital 3D single-cell shape analysis and single-cell mRNA sequencing to characterize root meristems and mature root segments of brassinosteroid-blind mutants and wild type. The resultant datasets demonstrate that brassinosteroid signaling affects neither cell volume nor cell proliferation capacity. Instead, brassinosteroid signaling is essential for the precise orientation of cell division planes and the extent and timing of anisotropic cell expansion. Moreover, we found that the cell-aligning effects of brassinosteroid signaling can propagate to normalize the anatomy of both adjacent and distant brassinosteroid-blind cells through non-cell-autonomous functions, which are sufficient to restore growth vigor. Finally, single-cell transcriptome data discern directly brassinosteroid-responsive genes from genes that can react non-cell-autonomously and highlight arabinogalactans as sentinels of brassinosteroid-dependent anisotropic cell expansion.

Auxin-dependent control of cytoskeleton and cell shape regulates division orientation in the Arabidopsis embryo

Premitotic control of cell division orientation is critical for plant development, as cell walls prevent extensive cell remodeling or migration. While many divisions are proliferative and add cells to existing tissues, some divisions are formative and generate new tissue layers or growth axes. Such formative divisions are often asymmetric in nature, producing daughters with different fates. We have previously shown that, in the Arabidopsis thaliana embryo, developmental asymmetry is correlated with geometric asymmetry, creating daughter cells of unequal volume. Such divisions are generated by division planes that deviate from a default “minimal surface area” rule. Inhibition of auxin response leads to reversal to this default, yet the mechanisms underlying division plane choice in the embryo have been unclear. Here, we show that auxin-dependent division plane control involves alterations in cell geometry, but not in cell polarity axis or nuclear position. Through transcriptome profiling, we find that auxin regulates genes controlling cell wall and cytoskeleton properties. We confirm the involvement of microtubule (MT)-binding proteins in embryo division control. Organization of both MT and actin cytoskeleton depends on auxin response, and genetically controlled MT or actin depolymerization in embryos leads to disruption of asymmetric divisions, including reversion to the default. Our work shows how auxin-dependent control of MT and actin cytoskeleton properties interacts with cell geometry to generate asymmetric divisions during the earliest steps in plant development.

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Auxin responses regulate directional cell expansion in Arabidopsis embryos

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Cell shape and division orientation are tightly coupled

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Transcriptome analysis identifies MT-associated IQD proteins in division control

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Cytoskeletal dynamics control division orientation

The root meristem is shaped by brassinosteroid control of cell geometry

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.

A multiscale analysis of early flower development in Arabidopsis provides an integrated view of molecular regulation and growth control

We have analyzed the link between the gene regulation and growth during the early stages of flower development in Arabidopsis. Starting from time-lapse images, we generated a 4D atlas of early flower development, including cell lineage, cellular growth rates, and the expression patterns of regulatory genes. This information was introduced in MorphoNet, a web-based platform. Using computational models, we found that the literature-based molecular network only explained a minority of the gene expression patterns. This was substantially improved by adding regulatory hypotheses for individual genes. Correlating growth with the combinatorial expression of multiple regulators led to a set of hypotheses for the action of individual genes in morphogenesis. This identified the central factor LEAFY as a potential regulator of heterogeneous growth, which was supported by quantifying growth patterns in a leafy mutant. By providing an integrated view, this atlas should represent a fundamental step toward mechanistic models of flower development.

BioVision Tracker: A semi-automated image analysis software for spatiotemporal gene expression tracking in Arabidopsis thaliana

Fluorescence microscopy can produce large quantities of data that reveal the spatiotemporal behavior of gene expression at the cellular level in plants. Automated or semi-automated image analysis methods are required to extract data from these images. These data are helpful in revealing spatial and/or temporal-dependent processes that influence development in the meristematic region of plant roots. Tracking spatiotemporal gene expression in the meristem requires the processing of multiple microscopy imaging channels (one channel used to image root geometry which serves as a reference for relating locations within the root, and one or more channels used to image fluorescent gene expression signals). Many automated image analysis methods rely on the staining of cell walls with fluorescent dyes to capture cellular geometry and overall root geometry. However, in long time-course imaging experiments, dyes may fade which hinders spatial assessment in image analysis. Here, we describe a procedure for analyzing 3D microscopy images to track spatiotemporal gene expression signals using the MATLAB-based BioVision Tracker software. This software requires either a fluorescence image or a brightfield image to analyze root geometry and a fluorescence image to capture and track temporal changes in gene expression.

Three-dimensional quantification of twisting in the Arabidopsis petiole

Organisms have a variety of three-dimensional (3D) structures that change over time. These changes include twisting, which is 3D deformation that cannot happen in two dimensions. Twisting is linked to important adaptive functions of organs, such as adjusting the orientation of leaves and flowers in plants to align with environmental stimuli (e.g. light, gravity). Despite its importance, the underlying mechanism for twisting remains to be determined, partly because there is no rigorous method for quantifying the twisting of plant organs. Conventional studies have relied on approximate measurements of the twisting angle in 2D, with arbitrary choices of observation angle. Here, we present the first rigorous quantification of the 3D twisting angles of Arabidopsis petioles based on light sheet microscopy. Mathematical separation of bending and twisting with strict definition of petiole cross-sections were implemented; differences in the spatial distribution of bending and twisting were detected via the quantification of angles along the petiole. Based on the measured values, we discuss that minute degrees of differential growth can result in pronounced twisting in petioles.

Plant multiscale networks: charting plant connectivity by multi-level analysis and imaging techniques

In multicellular and even single-celled organisms, individual components are interconnected at multiscale levels to produce enormously complex biological networks that help these systems maintain homeostasis for development and environmental adaptation. Systems biology studies initially adopted network analysis to explore how relationships between individual components give rise to complex biological processes. Network analysis has been applied to dissect the complex connectivity of mammalian brains across different scales in time and space in The Human Brain Project. In plant science, network analysis has similarly been applied to study the connectivity of plant components at the molecular, subcellular, cellular, organic, and organism levels. Analysis of these multiscale networks contributes to our understanding of how genotype determines phenotype. In this review, we summarized the theoretical framework of plant multiscale networks and introduced studies investigating plant networks by various experimental and computational modalities. We next discussed the currently available analytic methodologies and multi-level imaging techniques used to map multiscale networks in plants. Finally, we highlighted some of the technical challenges and key questions remaining to be addressed in this emerging field.

High-throughput image segmentation and machine learning approaches in the plant sciences across multiple scales

Agriculture has benefited greatly from the rise of big data and high-performance computing. The acquisition and analysis of data across biological scales have resulted in strategies modeling inter- actions between plant genotype and environment, models of root architecture that provide insight into resource utilization, and the elucidation of cell-to-cell communication mechanisms that are instrumental in plant development. Image segmentation and machine learning approaches for interpreting plant image data are among many of the computational methodologies that have evolved to address challenging agricultural and biological problems. These approaches have led to contributions such as the accelerated identification of gene that modulate stress responses in plants and automated high-throughput phenotyping for early detection of plant diseases. The continued acquisition of high throughput imaging across multiple biological scales provides opportunities to further push the boundaries of our understandings quicker than ever before. In this review, we explore the current state of the art methodologies in plant image segmentation and machine learning at the agricultural, organ, and cellular scales in plants. We show how the methodologies for segmentation and classification differ due to the diversity of physical characteristics found at these different scales. We also discuss the hardware technologies most commonly used at these different scales, the types of quantitative metrics that can be extracted from these images, and how the biological mechanisms by which plants respond to abiotic/biotic stresses or genotypic modifications can be extracted from these approaches.

A digital 3D reference atlas reveals cellular growth patterns shaping the Arabidopsis ovule

A fundamental question in biology is how morphogenesis integrates the multitude of processes that act at different scales, ranging from the molecular control of gene expression to cellular coordination in a tissue. Using machine-learning-based digital image analysis, we generated a three-dimensional atlas of ovule development in Arabidopsis thaliana, enabling the quantitative spatio-temporal analysis of cellular and gene expression patterns with cell and tissue resolution. We discovered novel morphological manifestations of ovule polarity, a new mode of cell layer formation, and previously unrecognized subepidermal cell populations that initiate ovule curvature. The data suggest an irregular cellular build-up of WUSCHEL expression in the primordium and new functions for INNER NO OUTER in restricting nucellar cell proliferation and the organization of the interior chalaza. Our work demonstrates the analytical power of a three-dimensional digital representation when studying the morphogenesis of an organ of complex architecture that eventually consists of 1900 cells.

Linking Genes to Shape in Plants Using Morphometrics

A transition from qualitative to quantitative descriptors of morphology has been facilitated through the growing field of morphometrics, representing the conversion of shapes and patterns into numbers. The analysis of plant form at the macromorphological scale using morphometric approaches quantifies what is commonly referred to as a phenotype. Quantitative phenotypic analysis of individuals with contrasting genotypes in turn provides a means to establish links between genes and shapes. The path from a gene to a morphological phenotype is, however, not direct, with instructive information progressing both across multiple scales of biological complexity and through nonintuitive feedback, such as mechanical signals. In this review, we explore morphometric approaches used to perform whole-plant phenotyping and quantitative approaches in capture processes in the mesoscales, which bridge the gaps between genes and shapes in plants. Quantitative frameworks involving both the computational simulation and the discretization of data into networks provide a putative path to predicting emergent shape from underlying genetic programs.

Characterization of rhizome transcriptome and identification of a rhizomatous ER body in the clonal plant Cardamine leucantha

The rhizome is a plant organ that develops from a shoot apical meristem but penetrates into belowground environments. To characterize the gene expression profile of rhizomes, we compared the rhizome transcriptome with those of the leaves, shoots and roots of a rhizomatous Brassicaceae plant, Cardamine leucantha. Overall, rhizome transcriptomes were characterized by the absence of genes that show rhizome-specific expression and expression profiles intermediate between those of shoots and roots. Our results suggest that both endogenous developmental factors and external environmental factors are important for controlling the rhizome transcriptome. Genes that showed relatively high expression in the rhizome compared to shoots and roots included those related to belowground defense, control of reactive oxygen species and cell elongation under dark conditions. A comparison of transcriptomes further allowed us to identify the presence of an ER body, a defense-related belowground organelle, in epidermal cells of the C. leucantha rhizome, which is the first report of ER bodies in rhizome tissue.

High-efficiency procedure to characterize, segment, and quantify complex multicellularity in raw micrographs in plants

BACKGROUND

The increasing number of novel approaches for large-scale, multi-dimensional imaging of cells has created an unprecedented opportunity to analyze plant morphogenesis. However, complex image processing, including identifying specific cells and quantitating parameters, and high running cost of some image analysis softwares remains challenging. Therefore, it is essential to develop an efficient method for identifying plant complex multicellularity in raw micrographs in plants.

RESULTS

Here, we developed a high-efficiency procedure to characterize, segment, and quantify plant multicellularity in various raw images using the open-source software packages ImageJ and SR-Tesseler. This procedure allows for the rapid, accurate, automatic quantification of cell patterns and organization at different scales, from large tissues down to the cellular level. We validated our method using different images captured from Arabidopsis thaliana roots and seeds and Populus tremula stems, including fluorescently labeled images, Micro-CT scans, and dyed sections. Finally, we determined the area, centroid coordinate, perimeter, and Feret's diameter of the cells and harvested the cell distribution patterns from Voronoï diagrams by setting the threshold at localization density, mean distance, or area.

CONCLUSIONS

This procedure can be used to determine the character and organization of multicellular plant tissues at high efficiency, including precise parameter identification and polygon-based segmentation of plant cells.

From Stained Plant Tissues to Quantitative Cell Segmentation Analysis with MorphoGraphX

Development and growth of plant organs is determined by a myriad of molecular processes that occur in each individual cell. As a direct consequence of these processes, cells alter in size and shape. They therefore serve as excellent parameters to thoroughly understand gene function. However, conventional single-plane analyses fail to accurately capture cell metrics. Here, we present a comprehensive illustrated guide that demonstrates how SCRI Renaissance 2200 staining of Arabidopsis thaliana embryos and roots can be combined with the open-source application MorphoGraphX to quantify cell parameters in 3D. We compare this staining method with other common staining techniques and provide examples of embryo and root tissue segmentation. With our novel approach, subtle single-cell phenotypes can be identified in their native context, providing new possibilities to dissect gene networks.

From Stained Plant Tissues to Quantitative Cell Segmentation Analysis with MorphoGraphX

Development and growth of plant organs is determined by a myriad of molecular processes that occur in each individual cell. As a direct consequence of these processes, cells alter in size and shape. They therefore serve as excellent parameters to thoroughly understand gene function. However, conventional single-plane analyses fail to accurately capture cell metrics. Here, we present a comprehensive illustrated guide that demonstrates how SCRI Renaissance 2200 staining of Arabidopsis thaliana embryos and roots can be combined with the open-source application MorphoGraphX to quantify cell parameters in 3D. We compare this staining method with other common staining techniques and provide examples of embryo and root tissue segmentation. With our novel approach, subtle single-cell phenotypes can be identified in their native context, providing new possibilities to dissect gene networks.

Formal description of plant morphogenesis

Plant morphogenesis may be characterized by complex feedback mechanisms between signals specifying growth and by the growth of the plant body itself. Comprehension of such feedback mechanisms is an ongoing research task and can be aided with formal descriptions of morphogenesis. In this review, we present a number of established mathematical paradigms that are useful to the formal representation of plant shape, and of biomechanical and biochemical signaling. Specifically, we discuss work from a range of research areas including plant biology, material sciences, fluid dynamics, and computer graphics. Treating plants as organized systems of information processing allows us to compare these different mathematical methods in terms of their expressive power of biological hypotheses. This is an attempt to bring together a large number of computational modeling concepts and make them accessible to the analytical as well as empirical student of plant morphogenesis.

Multicellular Systems Biology: Quantifying Cellular Patterning and Function in Plant Organs Using Network Science

Organ function is at least partially shaped and constrained by the organization of their constituent cells. Extensive investigation has revealed mechanisms explaining how these patterns are generated, with less being known about their functional relevance. In this paper, a methodology to discretize and quantitatively analyze cellular patterning is described. By performing global organ-scale cellular interaction mapping, the organization of cells can be extracted and analyzed using network science. This provides a means to take the developmental analysis of cellular organization in complex organisms beyond qualitative descriptions and provides data-driven approaches to inferring cellular function. The bridging of a structure-function relationship in hypocotyl epidermal cell patterning through global topological analysis provides support for this approach. The analysis of cellular topologies from patterning mutants further enables the contribution of gene activity toward the organizational properties of tissues to be linked, bridging molecular and tissue scales. This systems-based approach to investigate multicellular complexity paves the way to uncovering the principles of complex organ design and achieving predictive genotype-phenotype mapping.

Global Topological Order Emerges through Local Mechanical Control of Cell Divisions in the Arabidopsis Shoot Apical Meristem

The control of cell position and division act in concert to dictate multicellular organization in tissues and organs. How these processes shape global order and molecular movement across organs is an outstanding problem in biology. Using live 3D imaging and computational analyses, we extracted networks capturing cellular connectivity dynamics across the Arabidopsis shoot apical meristem (SAM) and topologically analyzed the local and global properties of cellular architecture. Locally generated cell division rules lead to the emergence of global tissue-scale organization of the SAM, facilitating robust global communication. Cells that lie upon more shorter paths have an increased propensity to divide, with division plane placement acting to limit the number of shortest paths their daughter cells lie upon. Cell shape heterogeneity and global cellular organization requires KATANIN, providing a multiscale link between cell geometry, mechanical cell-cell interactions, and global tissue order.

3DCellAtlas Meristem: a tool for the global cellular annotation of shoot apical meristems

Modern imaging approaches enable the acquisition of 3D and 4D datasets capturing plant organ development at cellular resolution. Computational analyses of these data enable the digitization and analysis of individual cells. In order to fully harness the information encoded within these datasets, annotation of the cell types within organs may be performed. This enables data points to be placed within the context of their position and identity, and for equivalent cell types to be compared between samples. The shoot apical meristem (SAM) in plants is the apical stem cell niche from which all above ground organs are derived. We developed 3DCellAtlas Meristem which enables the complete cellular annotation of all cells within the SAM with up to 96% accuracy across all cell types in Arabidopsis and 99% accuracy in tomato SAMs. Successive layers of cells are identified along with the central stem cells, boundary regions, and layers within developing primordia. Geometric analyses provide insight into the morphogenetic process that occurs during these developmental processes. Coupling these digital analyses with reporter expression will enable multidimensional analyses to be performed at single cell resolution. This provides a rapid and robust means to perform comprehensive cellular annotation of plant SAMs and digital single cell analyses, including cell geometry and gene expression. This fills a key gap in our ability to analyse and understand complex multicellular biology in the apical plant stem cell niche and paves the way for digital cellular atlases and analyses.

Information Processing and Distributed Computation in Plant Organs

The molecular networks plant cells evolved to tune their development in response to the environment are becoming increasingly well understood. Much less is known about how these programs function in the multicellular context of organs and the impact this spatial embedding has on emergent decision-making. Here I address these questions and investigate whether the computational control principles identified in engineered information processing systems also apply to plant development. Examples of distributed computing underlying plant development are presented and support the presence of shared mechanisms of information processing across these domains. The coinvestigation of computation across plant biology and computer science can provide novel insight into the principles of plant development and suggest novel algorithms for use in distributed computing.

3D Reconstruction of Lipid Droplets in the Seed of Brassica napus

Rapeseed is one of the most important and widely cultured oilseed crops for food and nonfood purposes worldwide. Neutral lipids are stored in lipid droplets (LDs) as fuel for germination and subsequent seedling growth. Most of the LD detection in seeds was still in 2D levels, and some of the details might have been lost in previous studies. In the present work, the configuration of LDs in seeds was obtained by confocal imaging combined with 3D reconstruction technology in Brassica napus. The size and shape of LDs, LD numbers, cell interval spaces and cell size were observed and compared at 3D levels in the seeds of different materials with high and low oil content. It was also revealed that different cells located in the same tissue exhibited various oil contents according to the construction at the 3D level, which was not previously reported in B. napus. The present work provides a new way to understand the differential in cell populations and enhance the seed oil content at the single cell level within seeds.

Fluorescein Transport Assay to Assess Bulk Flow of Molecules Through the Hypocotyl in Arabidopsis thaliana

The bulk transport of molecules through plant tissues underpins growth and development. The stem acts as a conduit between the upper and low domains of the plant, facilitating transport of solutes and water from the roots to the shoot system, and sugar plus other elaborated metabolites towards the non-photosynthetic organs. In order to perform this function efficiently, the stem needs to be optimized for transport. This is achieved through the formation of vasculature that connects the whole plant but also through connectivity signatures that reduce path length distributions outside the vascular system. This protocol was devised to characterize how cell connectivity affects the bulk flow of molecules traversing the stem. This is achieved by exposing young seedlings to fluorescein, for which no specific transporter is assumed to be present in A. thaliana, and assessing the relative concentration of this fluorescent compound in individual cells of the embryonic stem (hypocotyl) using confocal microscopy and quantitative 3D image analysis after a given exposure time.

A PLA-iRoCS Pipeline for the Localization of Protein-Protein Interactions In Situ

In plants as well as other organisms, protein localization alone is insufficient to provide a mechanistic link between stimulus and process regulation. This is because protein-protein interactions are central to the regulation of biological processes. However, they remain very difficult to detect in situ, with the choice of tools for the detection of protein-protein interaction in situ still in need of expansion. Here, we provide a protocol for the detection and accurate localization of protein interactions based on the combination of a whole-mount proximity ligation assay and iRoCS, a coordinate system able to standardize subtle differences between the architecture of individual Arabidopsis roots.

Exploiting DELLA Signaling in Cereals

The spectacular yield increases in rice and wheat during the green revolution were partly realized by reduced gibberellin (GA) synthesis or sensitivity, both causing the accumulation of DELLA proteins. Although insights into the regulation of plant growth and development by DELLA proteins advanced rapidly in arabidopsis (Arabidopsis thaliana), DELLA-mediated regulation of downstream responses in cereals has received little attention to date. Furthermore, translating this research from arabidopsis to cereals is challenging given their different growth patterns and our phylogenetic analysis which reveals that DELLA-related DGLLA proteins exist in cereals but not in arabidopsis. Therefore, understanding the molecular basis of DELLA function in cereals holds great potential to improve yield. In this review, we propose to extend the focus of DELLA functional research to cereals, and highlight the appropriate tools that are now available to achieve this.

Network-based approaches to quantify multicellular development

Multicellularity and cellular cooperation confer novel functions on organs following a structure-function relationship. How regulated cell migration, division and differentiation events generate cellular arrangements has been investigated, providing insight into the regulation of genetically encoded patterning processes. Much less is known about the higher-order properties of cellular organization within organs, and how their functional coordination through global spatial relations shape and constrain organ function. Key questions to be addressed include: why are cells organized in the way they are? What is the significance of the patterns of cellular organization selected for by evolution? What other configurations are possible? These may be addressed through a combination of global cellular interaction mapping and network science to uncover the relationship between organ structure and function. Using this approach, global cellular organization can be discretized and analysed, providing a quantitative framework to explore developmental processes. Each of the local and global properties of integrated multicellular systems can be analysed and compared across different tissues and models in discrete terms. Advances in high-resolution microscopy and image analysis continue to make cellular interaction mapping possible in an increasing variety of biological systems and tissues, broadening the further potential application of this approach. Understanding the higher-order properties of complex cellular assemblies provides the opportunity to explore the evolution and constraints of cell organization, establishing structure-function relationships that can guide future organ design.

Topological analysis of multicellular complexity in the plant hypocotyl

Multicellularity arose as a result of adaptive advantages conferred to complex cellular assemblies. The arrangement of cells within organs endows higher-order functionality through a structure-function relationship, though the organizational properties of these multicellular configurations remain poorly understood. We investigated the topological properties of complex organ architecture by digitally capturing global cellular interactions in the plant embryonic stem (hypocotyl), and analyzing these using quantitative network analysis. This revealed the presence of coherent conduits of reduced path length across epidermal atrichoblast cell files. The preferential movement of small molecules along this cell type was demonstrated using fluorescence transport assays. Both robustness and plasticity in this higher order property of atrichoblast patterning was observed across diverse genetic backgrounds, and the analysis of genetic patterning mutants identified the contribution of gene activity towards their construction. This topological analysis of multicellular structural organization reveals higher order functions for patterning and principles of complex organ construction.

Temperature variability is integrated by a spatially embedded decision-making center to break dormancy in Arabidopsis seeds

Plants perceive and integrate information from the environment to time critical transitions in their life cycle. Some mechanisms underlying this quantitative signal processing have been described, whereas others await discovery. Seeds have evolved a mechanism to integrate environmental information by regulating the abundance of the antagonistically acting hormones abscisic acid (ABA) and gibberellin (GA). Here, we show that hormone metabolic interactions and their feedbacks are sufficient to create a bistable developmental fate switch in Arabidopsis seeds. A digital single-cell atlas mapping the distribution of hormone metabolic and response components revealed their enrichment within the embryonic radicle, identifying the presence of a decision-making center within dormant seeds. The responses to both GA and ABA were found to occur within distinct cell types, suggesting cross-talk occurs at the level of hormone transport between these signaling centers. We describe theoretically, and demonstrate experimentally, that this spatial separation within the decision-making center is required to process variable temperature inputs from the environment to promote the breaking of dormancy. In contrast to other noise-filtering systems, including human neurons, the functional role of this spatial embedding is to leverage variability in temperature to transduce a fate-switching signal within this biological system. Fluctuating inputs therefore act as an instructive signal for seeds, enhancing the accuracy with which plants are established in ecosystems, and distributed computation within the radicle underlies this signal integration mechanism.

Quantitative analysis of the 3D cell shape changes driving soybean germination

Seed germination is central to plant establishment and is the starting point for the majority of world agriculture. This transition from seed to seedling has been extensively studied at an organ level, while few studies have examined the cellular events which underlie it. Reports in the model species Arabidopsis have identified a radicle-derived wave of cell expansion underlying the germination process. Whether this spatiotemporal pattern of cell expansion is specific to this model plant or conserved in other species remains unknown. Here we examined the 3D cell anisotropy driving germination in soybean. By examining changes in cell shape at two positions along the length of the axis over time, preferential growth was observed in the portion of the axis closest to the radicle. A gradient of cell size was observed across the cortical cell layers of the soybean axis, and differences in starting cell size translated into differential relative growth rates across cell layers where larger cells showed greater relative growth rates than smaller cells. Differences in cell position-specific cell anisotropy were also observed. These data demonstrate that a radicle-derived growth pattern is present in the crop species soybean, and reveal the presence of a complex cellular organization in this hypocotyl which show cell type-specific anisotropy diving germination.

In Silico Methods for Cell Annotation, Quantification of Gene Expression, and Cell Geometry at Single-Cell Resolution Using 3DCellAtlas

A comprehensive understanding of plant growth and development requires the integration of the spatial and temporal dynamics of gene regulatory networks with changes in cellular geometry during 3D organ growth. 3DCellAtlas is an integrative computational pipeline that semi-automatically identifies cell type and position within radially symmetric plant organs, and simultaneously quantifies 3D cell anisotropy and reporter abundance at single-cell resolution. It is a powerful tool that generates digital single-cell cellular atlases of plant organs and enables 3D cell geometry and reporter abundance (gene/protein/biosensor) from multiple samples to be integrated at single-cell resolution across whole organs. Here we describe how to use 3DCellAtlas to process and analyze radially symmetric organs, and to identify cell types and extract geometric cell data within these 3D cellular datasets. We detail how to use two statistical tools in 3DCellAtlas to compare cellular geometries, and to analyze reporter abundance at single-cell resolution.

The Transcription Factor ATHB5 Affects GA-Mediated Plasticity in Hypocotyl Cell Growth during Seed Germination

Gibberellic acid (GA)-mediated cell expansion initiates the seed-to-seedling transition in plants and is repressed by DELLA proteins. Using digital single-cell analysis, we identified a cellular subdomain within the midhypocotyl, whose expansion drives the final step of this developmental transition under optimal conditions. Using network inference, the transcription factor ATHB5 was identified as a genetic factor whose localized expression promotes GA-mediated expansion specifically within these cells. Both this protein and its putative growth-promoting target EXPANSIN3 are repressed by DELLA, and coregulated at single-cell resolution during seed germination. The cellular domains of hormone sensitivity were explored within the Arabidopsis (Arabidopsis thaliana) embryo by putting seeds under GA-limiting conditions and quantifying cellular growth responses. The middle and upper hypocotyl have a greater requirement for GA to promote cell expansion than the lower embryo axis. Under these conditions, germination was still completed following enhanced growth within the radicle and lower axis. Under GA-limiting conditions, the athb5 mutant did not show a phenotype at the level of seed germination, but it did at a cellular level with reduced cell expansion in the hypocotyl relative to the wild type. These data reveal that the spatiotemporal cell expansion events driving this transition are not determinate, and the conditional use of GA-ATHB5-mediated hypocotyl growth under optimal conditions may be used to optionally support rapid seedling growth. This study demonstrates that multiple genetic and spatiotemporal cell expansion mechanisms underlie the seed to seedling transition in Arabidopsis.

Novel tools for quantifying secondary growth

Secondary growth occurs in dicotyledons and gymnosperms, and results in an increased girth of plant organs. It is driven primarily by the vascular cambium, which produces thousands of cells throughout the life of several plant species. For instance, even in the small herbaceous model plant Arabidopsis, manual quantification of this massive process is impractical. Here, we provide a comprehensive overview of current methods used to measure radial growth. We discuss the issues and problematics related to its quantification. We highlight recent advances and tools developed for automated cellular phenotyping and its future applications.

Making microscopy count: quantitative light microscopy of dynamic processes in living plants

Cell theory has officially reached 350 years of age as the first use of the word 'cell' in a biological context can be traced to a description of plant material by Robert Hooke in his historic publication 'Micrographia: or some physiological definitions of minute bodies'. The 2015 Royal Microscopical Society Botanical Microscopy meeting was a celebration of the streams of investigation initiated by Hooke to understand at the subcellular scale how plant cell function and form arises. Much of the work presented, and Honorary Fellowships awarded, reflected the advanced application of bioimaging informatics to extract quantitative data from micrographs that reveal dynamic molecular processes driving cell growth and physiology. The field has progressed from collecting many pixels in multiple modes to associating these measurements with objects or features that are meaningful biologically. The additional complexity involves object identification that draws on a different type of expertise from computer science and statistics that is often impenetrable to biologists. There are many useful tools and approaches being developed, but we now need more interdisciplinary exchange to use them effectively. In this review we show how this quiet revolution has provided tools available to any personal computer user. We also discuss the oft-neglected issue of quantifying algorithm robustness and the exciting possibilities offered through the integration of physiological information generated by biosensors with object detection and tracking.

Quantifying morphogenesis in plants in 4D

Plant development occurs in 3D space over time (4D). Recent advances in image acquisition and computational analysis are now enabling development to be visualized and quantified in its entirety at the cellular level. The simultaneous quantification of reporter abundance and 3D cell shape change enables links between signaling processes and organ morphogenesis to be accomplished organ-wide and at single cell resolution. Current work to integrate this quantitative 3D image data with computational models is enabling causal relationships between gene expression and organ morphogenesis to be uncovered. Further technical advances in imaging and image analysis will enable this approach to be applied to a greater diversity of plant organs and will become a key tool to address many questions in plant development.

50 years of Arabidopsis research: highlights and future directions

922 I. 922 II. 922 III. 925 IV. 925 V. 926 VI. 927 VII. 928 VIII. 929 IX. 930 X. 931 XI. 932 XII. 933 XIII. Natural variation and genome-wide association studies 934 XIV. 934 XV. 935 XVI. 936 XVII. 937 937 References 937 SUMMARY: The year 2014 marked the 25(th) International Conference on Arabidopsis Research. In the 50 yr since the first International Conference on Arabidopsis Research, held in 1965 in Göttingen, Germany, > 54 000 papers that mention Arabidopsis thaliana in the title, abstract or keywords have been published. We present herein a citational network analysis of these papers, and touch on some of the important discoveries in plant biology that have been made in this powerful model system, and highlight how these discoveries have then had an impact in crop species. We also look to the future, highlighting some outstanding questions that can be readily addressed in Arabidopsis. Topics that are discussed include Arabidopsis reverse genetic resources, stock centers, databases and online tools, cell biology, development, hormones, plant immunity, signaling in response to abiotic stress, transporters, biosynthesis of cells walls and macromolecules such as starch and lipids, epigenetics and epigenomics, genome-wide association studies and natural variation, gene regulatory networks, modeling and systems biology, and synthetic biology.

Seed vigour and crop establishment: extending performance beyond adaptation

Seeds are central to crop production, human nutrition, and food security. A key component of the performance of crop seeds is the complex trait of seed vigour. Crop yield and resource use efficiency depend on successful plant establishment in the field, and it is the vigour of seeds that defines their ability to germinate and establish seedlings rapidly, uniformly, and robustly across diverse environmental conditions. Improving vigour to enhance the critical and yield-defining stage of crop establishment remains a primary objective of the agricultural industry and the seed/breeding companies that support it. Our knowledge of the regulation of seed germination has developed greatly in recent times, yet understanding of the basis of variation in vigour and therefore seed performance during the establishment of crops remains limited. Here we consider seed vigour at an ecophysiological, molecular, and biomechanical level. We discuss how some seed characteristics that serve as adaptive responses to the natural environment are not suitable for agriculture. Past domestication has provided incremental improvements, but further actively directed change is required to produce seeds with the characteristics required both now and in the future. We discuss ways in which basic plant science could be applied to enhance seed performance in crop production.

Precision Automation of Cell Type Classification and Sub-Cellular Fluorescence Quantification from Laser Scanning Confocal Images

While novel whole-plant phenotyping technologies have been successfully implemented into functional genomics and breeding programs, the potential of automated phenotyping with cellular resolution is largely unexploited. Laser scanning confocal microscopy has the potential to close this gap by providing spatially highly resolved images containing anatomic as well as chemical information on a subcellular basis. However, in the absence of automated methods, the assessment of the spatial patterns and abundance of fluorescent markers with subcellular resolution is still largely qualitative and time-consuming. Recent advances in image acquisition and analysis, coupled with improvements in microprocessor performance, have brought such automated methods within reach, so that information from thousands of cells per image for hundreds of images may be derived in an experimentally convenient time-frame. Here, we present a MATLAB-based analytical pipeline to (1) segment radial plant organs into individual cells, (2) classify cells into cell type categories based upon Random Forest classification, (3) divide each cell into sub-regions, and (4) quantify fluorescence intensity to a subcellular degree of precision for a separate fluorescence channel. In this research advance, we demonstrate the precision of this analytical process for the relatively complex tissues of Arabidopsis hypocotyls at various stages of development. High speed and robustness make our approach suitable for phenotyping of large collections of stem-like material and other tissue types.