Computational morphodynamics of plants: integrating development over space and time

An optimized pipeline for live imaging whole Arabidopsis leaves at cellular resolution

BACKGROUND

Live imaging is the gold standard for determining how cells give rise to organs. However, tracking many cells across whole organs over large developmental time windows is extremely challenging. In this work, we provide a comparably simple method for confocal live imaging entire Arabidopsis thaliana first leaves across early development. Our imaging method works for both wild-type leaves and the complex curved leaves of the jaw-1D mutant.

RESULTS

We find that dissecting the cotyledons, affixing a coverslip above the samples and mounting samples with perfluorodecalin yields optimal imaging series for robust cellular and organ level analysis. We provide details of our complementary image processing steps in MorphoGraphX software for segmenting, tracking lineages, and measuring a suite of cellular properties. We also provide MorphoGraphX image processing scripts we developed to automate analysis of segmented images and data presentation.

CONCLUSIONS

Our imaging techniques and processing steps combine into a robust imaging pipeline. With this pipeline we are able to examine important nuances in the cellular growth and differentiation of jaw-D versus WT leaves that have not been demonstrated before. Our pipeline is approachable and easy to use for leaf development live imaging.

Modelling the evolution of novelty: a review

Evolution has been an inventive process since its inception, about 4 billion years ago. It has generated an astounding diversity of novel mechanisms and structures for adaptation to the environment, for competition and cooperation, and for organisation of the internal and external dynamics of the organism. How does this novelty come about? Evolution builds with the tools available, and on top of what it has already built - therefore, much novelty consists in repurposing old functions in a different context. In the process, the tools themselves evolve, allowing yet more novelty to arise. Despite evolutionary novelty being the most striking observable of evolution, it is not accounted for in classical evolutionary theory. Nevertheless, mathematical and computational models that illustrate mechanisms of evolutionary innovation have been developed. In the present review, we present and compare several examples of computational evo-devo models that capture two aspects of novelty: 'between-level novelty' and 'constructive novelty.' Novelty can evolve between predefined levels of organisation to dynamically transcode biological information across these levels - as occurs during development. Constructive novelty instead generates a level of biological organisation by exploiting the lower level as an informational scaffold to open a new space of possibilities - an example being the evolution of multicellularity. We propose that the field of computational evo-devo is well-poised to reveal many more exciting mechanisms for the evolution of novelty. A broader theory of evolutionary novelty may well be attainable in the near future.

Localized growth and remodelling drives spongy mesophyll morphogenesis

The spongy mesophyll is a complex, porous tissue found in plant leaves that enables carbon capture and provides mechanical stability. Unlike many other biological tissues, which remain confluent throughout development, the spongy mesophyll must develop from an initially confluent tissue into a tortuous network of cells with a large proportion of intercellular airspace. How the airspace in the spongy mesophyll develops while the tissue remains mechanically stable is unknown. Here, we use computer simulations of deformable polygons to develop a purely mechanical model for the development of the spongy mesophyll tissue. By stipulating that cell wall growth and remodelling occurs only near void space, our computational model is able to recapitulate spongy mesophyll development observed in Arabidopsis thaliana leaves. We find that robust generation of pore space in the spongy mesophyll requires a balance of cell growth, adhesion, stiffness and tissue pressure to ensure cell networks become porous yet maintain mechanical stability. The success of this mechanical model of morphogenesis suggests that simple physical principles can coordinate and drive the development of complex plant tissues like the spongy mesophyll.

Differential growth dynamics control aerial organ geometry

How gene activities and biomechanics together direct organ shapes is poorly understood. Plant leaf and floral organs develop from highly similar initial structures and share similar gene expression patterns, yet they gain drastically different shapes later-flat and bilateral leaf primordia and radially symmetric floral primordia, respectively. We analyzed cellular growth patterns and gene expression in young leaves and flowers of Arabidopsis thaliana and found significant differences in cell growth rates, which correlate with convergence sites of phytohormone auxin that require polar auxin transport. In leaf primordia, the PRESSED-FLOWER-expressing middle domain grows faster than adjacent adaxial domain and coincides with auxin convergence. In contrast, in floral primordia, the LEAFY-expressing domain shows accelerated growth rates and pronounced auxin convergence. This distinct cell growth dynamics between leaf and flower requires changes in levels of cell-wall pectin de-methyl-esterification and mechanical properties of the cell wall. Data-driven computer model simulations at organ and cellular levels demonstrate that growth differences are central to obtaining distinct organ shape, corroborating in planta observations. Together, our study provides a mechanistic basis for the establishment of early aerial organ symmetries through local modulation of differential growth patterns with auxin and biomechanics.

A crosstalk between auxin and brassinosteroid regulates leaf shape by modulating growth anisotropy

Leaf shape is highly variable within and among plant species, ranging from slender to oval shaped. This is largely determined by the proximodistal axis of growth. However, little is known about how proximal-distal growth is controlled to determine leaf shape. Here, we show that Arabidopsis leaf and sepal proximodistal growth is tuned by two phytohormones. Two class A AUXIN RESPONSE FACTORs (ARFs), ARF6 and ARF8, activate the transcription of DWARF4, which encodes a key brassinosteroid (BR) biosynthetic enzyme. At the cellular level, the phytohormones promote more directional cell expansion along the proximodistal axis, as well as final cell sizes. BRs promote the demethyl-esterification of cell wall pectins, leading to isotropic in-plane cell wall loosening. Notably, numerical simulation showed that isotropic cell wall loosening could lead to directional cell and organ growth along the proximodistal axis. Taken together, we show that auxin acts through biosynthesis of BRs to determine cell wall mechanics and directional cell growth to generate leaves of variable roundness.

Arabidopsis sepals: A model system for the emergent process of morphogenesis

During development, Arabidopsis thaliana sepal primordium cells grow, divide and interact with their neighbours, giving rise to a sepal with the correct size, shape and form. Arabidopsis sepals have proven to be a good system for elucidating the emergent processes driving morphogenesis due to their simplicity, their accessibility for imaging and manipulation, and their reproducible development. Sepals undergo a basipetal gradient of growth, with cessation of cell division, slow growth and maturation starting at the tip of the sepal and progressing to the base. In this review, I discuss five recent examples of processes during sepal morphogenesis that yield emergent properties: robust size, tapered tip shape, laminar shape, scattered giant cells and complex gene expression patterns. In each case, experiments examining the dynamics of sepal development led to the hypotheses of local rules. In each example, a computational model was used to demonstrate that these local rules are sufficient to give rise to the emergent properties of morphogenesis.

A Life Cycle for Modeling Biology at Different Scales

Modeling has become a popular tool for inquiry and discovery across biological disciplines. Models allow biologists to probe complex questions and to guide experimentation. Modeling literacy among biologists, however, has not always kept pace with the rise in popularity of these techniques and the relevant advances in modeling theory. The result is a lack of understanding that inhibits communication and ultimately, progress in data gathering and analysis. In an effort to help bridge this gap, we present a blueprint that will empower biologists to interrogate and apply models in their field. We demonstrate the applicability of this blueprint in two case studies from distinct subdisciplines of biology; developmental-biomechanics and evolutionary biology. The models used in these fields vary from summarizing dynamical mechanisms to making statistical inferences, demonstrating the breadth of the utility of models to explore biological phenomena.

Overcoming the Challenges to Enhancing Experimental Plant Biology With Computational Modeling

The study of complex biological systems necessitates computational modeling approaches that are currently underutilized in plant biology. Many plant biologists have trouble identifying or adopting modeling methods to their research, particularly mechanistic mathematical modeling. Here we address challenges that limit the use of computational modeling methods, particularly mechanistic mathematical modeling. We divide computational modeling techniques into either pattern models (e.g., bioinformatics, machine learning, or morphology) or mechanistic mathematical models (e.g., biochemical reactions, biophysics, or population models), which both contribute to plant biology research at different scales to answer different research questions. We present arguments and recommendations for the increased adoption of modeling by plant biologists interested in incorporating more modeling into their research programs. As some researchers find math and quantitative methods to be an obstacle to modeling, we provide suggestions for easy-to-use tools for non-specialists and for collaboration with specialists. This may especially be the case for mechanistic mathematical modeling, and we spend some extra time discussing this. Through a more thorough appreciation and awareness of the power of different kinds of modeling in plant biology, we hope to facilitate interdisciplinary, transformative research.

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.

Imaging plant germline differentiation within Arabidopsis flowers by light sheet microscopy

In higher plants, germline differentiation occurs during a relatively short period within developing flowers. Understanding of the mechanisms that govern germline differentiation lags behind other plant developmental processes. This is largely because the germline is restricted to relatively few cells buried deep within floral tissues, which makes them difficult to study. To overcome this limitation, we have developed a methodology for live imaging of the germ cell lineage within floral organs of Arabidopsis using light sheet fluorescence microscopy. We have established reporter lines, cultivation conditions, and imaging protocols for high-resolution microscopy of developing flowers continuously for up to several days. We used multiview imagining to reconstruct a three-dimensional model of a flower at subcellular resolution. We demonstrate the power of this approach by capturing male and female meiosis, asymmetric pollen division, movement of meiotic chromosomes, and unusual restitution mitosis in tapetum cells. This method will enable new avenues of research into plant sexual reproduction.

Imaging plant germline differentiation within Arabidopsis flowers by light sheet microscopy

In higher plants, germline differentiation occurs during a relatively short period within developing flowers. Understanding of the mechanisms that govern germline differentiation lags behind other plant developmental processes. This is largely because the germline is restricted to relatively few cells buried deep within floral tissues, which makes them difficult to study. To overcome this limitation, we have developed a methodology for live imaging of the germ cell lineage within floral organs of Arabidopsis using light sheet fluorescence microscopy. We have established reporter lines, cultivation conditions, and imaging protocols for high-resolution microscopy of developing flowers continuously for up to several days. We used multiview imagining to reconstruct a three-dimensional model of a flower at subcellular resolution. We demonstrate the power of this approach by capturing male and female meiosis, asymmetric pollen division, movement of meiotic chromosomes, and unusual restitution mitosis in tapetum cells. This method will enable new avenues of research into plant sexual reproduction.

Growth dynamics of the Arabidopsis fruit is mediated by cell expansion

Fruit have evolved a sophisticated tissue and cellular architecture to secure plant reproductive success. Postfertilization growth is perhaps the most dramatic event during fruit morphogenesis. Several studies have proposed that fertilized ovules and developing seeds initiate signaling cascades to coordinate and promote the growth of the accompanying fruit tissues. This dynamic process allows the fruit to conspicuously increase its size and acquire its final shape and means for seed dispersal. All these features are key for plant survival and crop yield. Despite its importance, we lack a high-resolution spatiotemporal map of how postfertilization fruit growth proceeds at the cellular level. In this study, we have combined live imaging, mutant backgrounds in which fertilization can be controlled, and computational modeling to monitor and predict postfertilization fruit growth in Arabidopsis We have uncovered that, unlike leaves, sepals, or roots, fruit do not exhibit a spatial separation of cell division and expansion domains; instead, there is a separation into temporal stages with fertilization as the trigger for transitioning to cell expansion, which drives postfertilization fruit growth. We quantified the coordination between fertilization and fruit growth by imaging no transmitting tract (ntt) mutants, in which fertilization fails in the bottom half of the fruit. By combining our experimental data with computational modeling, we delineated the mobility properties of the seed-derived signaling cascades promoting growth in the fruit. Our study provides the basis for generating a comprehensive understanding of the molecular and cellular mechanisms governing fruit growth and shape.

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.

Cellular basis of growth in plants: geometry matters

The growth of individual cells underlies the development of biological forms. In plants, cells are interconnected by rigid walls, fixing their position with respect to one another and generating mechanical feedbacks between cells. Current research is shedding new light on how plant growth is controlled by physical inputs at the level of individual cells and growing tissues. In this review, we discuss recent progress in our understanding of the cellular basis of growth from a biomechanical perspective. We describe the role of the cell wall and turgor pressure in growth and highlight the often-overlooked role of cell geometry in this process. It is becoming apparent that a combination of experimental and theoretical approaches is required to answer new emerging questions in the biomechanics of plant morphogenesis. We summarise how this multidisciplinary approach brings us closer to a unified understanding of the generation of biological forms in plants.

Getting into shape: the mechanics behind plant morphogenesis

The process of shape change in cells and tissues inevitably involves the modification of structural elements, therefore it is necessary to integrate mechanics with biochemistry to develop a full understanding of morphogenesis. Here, we discuss recent findings on the role of biomechanics and biochemical processes in plant cell growth and development. In particular, we focus on how the plant cytoskeleton components, which are known to regulate morphogenesis, are influenced by biomechanical stress. We also discuss new insights into the role that pectin plays in biomechanics and morphogenesis. Using the jigsaw-shaped pavement cells of the leaf as a case study, we review new findings on the biomechanics behind the morphogenesis of these intricately-shaped cell types. Finally, we summarize important quantitative techniques that has allowed for the testing and the generation of hypotheses that link biomechanics to morphogenesis.

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.

Molecular Mechanisms of Leaf Morphogenesis

Plants maintain the ability to form lateral appendages throughout their life cycle and form leaves as the principal lateral appendages of the stem. Leaves initiate at the peripheral zone of the shoot apical meristem and then develop into flattened structures. In most plants, the leaf functions as a solar panel, where photosynthesis converts carbon dioxide and water into carbohydrates and oxygen. To produce structures that can optimally fulfill this function, plants precisely control the initiation, shape, and polarity of leaves. Moreover, leaf development is highly flexible but follows common themes with conserved regulatory mechanisms. Leaves may have evolved from lateral branches that are converted into determinate, flattened structures. Many other plant parts, such as floral organs, are considered specialized leaves, and thus leaf development underlies their morphogenesis. Here, we review recent advances in the understanding of how three-dimensional leaf forms are established. We focus on how genes, phytohormones, and mechanical properties modulate leaf development, and discuss these factors in the context of leaf initiation, polarity establishment and maintenance, leaf flattening, and intercalary growth.

Use it or average it: stochasticity in plant development

A process that is stochastic has a probabilistic or randomly determined outcome. At the molecular level, all processes are stochastic; but development is highly reproducible, suggesting that plants and other multicellular organisms have evolved mechanisms to ensure robustness (achieving correct development despite stochastic and environmental perturbations). Mechanisms of robustness can be discovered through isolating mutants with increased variability in phenotype; such mutations do not necessarily change the average phenotype. Surprisingly, some developmental robustness mechanisms actually exploit stochasticity as a useful source of variation. For example, gene expression is stochastic and can be utilized to create subtle differences between identical cells that can initiate the patterning of specialized cell types. Stochasticity can also be used to promote robustness through spatiotemporal averaging-stochasticity can be averaged out across space and over time. Thus, organisms often harness stochasticity to ensure robust development.

Environmental and Genetic Factors Regulating Localization of the Plant Plasma Membrane H+-ATPase

A P-type H⁺-ATPase is the primary transporter that converts ATP to electrochemical energy at the plasma membrane of higher plants. Its product, the proton-motive force, is composed of an electrical potential and a pH gradient. Many studies have demonstrated that this proton-motive force not only drives the secondary transporters required for nutrient uptake, but also plays a direct role in regulating cell expansion. Here, we have generated a transgenic Arabidopsis (Arabidopsis thaliana) plant expressing H⁺-ATPase isoform 2 (AHA2) that is translationally fused with a fluorescent protein and examined its cellular localization by live-cell microscopy. Using a 3D imaging approach with seedlings grown for various times under a variety of light intensities, we demonstrate that AHA2 localization at the plasma membrane of root cells requires light. In dim light conditions, AHA2 is found in intracellular compartments, in addition to the plasma membrane. This localization profile was age-dependent and specific to cell types found in the transition zone located between the meristem and elongation zones. The accumulation of AHA2 in intracellular compartments is consistent with reduced H⁺ secretion near the transition zone and the suppression of root growth. By examining AHA2 localization in a knockout mutant of a receptor protein kinase, FERONIA, we found that the intracellular accumulation of AHA2 in the transition zone is dependent on a functional FERONIA-dependent inhibitory response in root elongation. Overall, this study provides a molecular underpinning for understanding the genetic, environmental, and developmental factors influencing root growth via localization of the plasma membrane H⁺-ATPase.

PaCeQuant: A Tool for High-Throughput Quantification of Pavement Cell Shape Characteristics

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.

Analysis of 3D Cellular Organization of Fixed Plant Tissues Using a User-guided Platform for Image Segmentation

The advent of non-invasive, high-resolution microscopy imaging techniques and computational pipelines for high-throughput image processing has contributed to gain insights in plant organ morphogenesis at the cellular level. Confocal scanning laser microscopy (CSLM) allows the generation of three dimensional images constituted of serial optical sections reporting on stained subcellular structures. Fluorescent labels of cell walls or cell membranes, either chemically or through reporter proteins, are particularly useful for the analyses of tissue organization and cellular shapes in 3D. Image segmentation based on cell boundary signals is used as an input to generate 3D-segments representing cells. These digitalized, 3D objects provide quantitative data on cell shape, size, geometry, position or on (intercellular) intensity signals if additional reporters are used. Herein, we report a detailed, annotated workflow for image segmentation using microscopic data. We used it in the context of a study of tissue patterning during ovule primordium development in Arabidopsis thaliana. Whole carpels are stained for cell boundaries using a modified pseudo-Schiff propidium iodide (mPS-PI) protocol, 3D images are acquired at high resolution by CSLM, segmented and annotated for individual cell types using ImarisCell. This allows for quantitative analyses of cell shape and cell number that are relevant for tissue morphodynamic studies.

Variable Cell Growth Yields Reproducible OrganDevelopment through Spatiotemporal Averaging

Organ sizes and shapes are strikingly reproducible, despite the variable growth and division of individual cells within them. To reveal which mechanisms enable this precision, we designed a screen for disrupted sepal size and shape uniformity in Arabidopsis and identified mutations in the mitochondrial i-AAA protease FtsH4. Counterintuitively, through live imaging we observed that variability of neighboring cell growth was reduced in ftsh4 sepals. We found that regular organ shape results from spatiotemporal averaging of the cellular variability in wild-type sepals, which is disrupted in the less-variable cells of ftsh4 mutants. We also found that abnormal, increased accumulation of reactive oxygen species (ROS) in ftsh4 mutants disrupts organ size consistency. In wild-type sepals, ROS accumulate in maturing cells and limit organ growth, suggesting that ROS are endogenous signals promoting termination of growth. Our results demonstrate that spatiotemporal averaging of cellular variability is required for precision in organ size.

Plant Development: Differential Growth Rates in Distinct Zones Shape an Ancient Plant Form

A long-standing question in biology is how a group of primordial cells can give rise to complex organs. A new study finds that, in an ancient land plant, growth rate variation patterned by meristematic cells primarily determines shape.

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.

Gene-regulatory networks controlling inflorescence and flower development in Arabidopsis thaliana

Reproductive development in plants is controlled by complex and intricate gene-regulatory networks of transcription factors. These networks integrate the information from endogenous, hormonal and environmental regulatory pathways. Many of the key players have been identified in Arabidopsis and other flowering plant species, and their interactions and molecular modes of action are being elucidated. An emerging theme is that there is extensive crosstalk between different pathways, which can be accomplished at the molecular level by modulation of transcription factor activity or of their downstream targets. In this review, we aim to summarize current knowledge on transcription factors and epigenetic regulators that control basic developmental programs during inflorescence and flower morphogenesis in the model plant Arabidopsis thaliana. This article is part of a Special Issue entitled: Plant Gene Regulatory Mechanisms and Networks, edited by Dr. Erich Grotewold and Dr. Nathan Springer.

Dynamic network modelling to understand flowering transition and floral patterning

Differentiation and morphogenetic processes during plant development are particularly robust. At the cellular level, however, plants also show great plasticity in response to environmental conditions, and can even reverse apparently terminal differentiated states with remarkable ease. Can we understand and predict both robust and plastic systemic responses as a general consequence of the non-trivial interplay between intracellular regulatory networks, extrinsic environmental signalling, and tissue-level mechanical constraints? Flower development has become an ideal model system to study these general questions of developmental biology, which are especially relevant to understanding stem cell patterning in plants, animals, and human disease. Decades of detailed study of molecular developmental genetics, as well as novel experimental techniques for in vivo assays in both wild-type and mutant plants, enable the postulation and testing of experimentally grounded mathematical and computational network dynamical models. Research in our group aims to explain the emergence of robust transitions that occur at the shoot apical meristem, as well as flower development, as the result of the collective action of key molecular components in regulatory networks subjected to intra-organismal signalling and extracellular constraints. Here we present a brief overview of recent work from our group, and that of others, focusing on the use of simple dynamical models to address cell-fate specification and cell-state stochastic dynamics during flowering transition and cell-state transitions at the shoot apical meristem of Arabidopsis thaliana. We also focus on how our work fits within the general field of plant developmental modelling, which is being developed by many others.

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.

Variability and Constancy in Cellular Growth of Arabidopsis Sepals

Growth of tissues is highly reproducible; yet, growth of individual cells in a tissue is highly variable, and neighboring cells can grow at different rates. We analyzed the growth of epidermal cell lineages in the Arabidopsis (Arabidopsis thaliana) sepal to determine how the growth curves of individual cell lineages relate to one another in a developing tissue. To identify underlying growth trends, we developed a continuous displacement field to predict spatially averaged growth rates. We showed that this displacement field accurately describes the growth of sepal cell lineages and reveals underlying trends within the variability of in vivo cellular growth. We found that the tissue, individual cell lineages, and cell walls all exhibit growth rates that are initially low, accelerate to a maximum, and decrease again. Accordingly, these growth curves can be represented by sigmoid functions. We examined the relationships among the cell lineage growth curves and surprisingly found that all lineages reach the same maximum growth rate relative to their size. However, the cell lineages are not synchronized; each cell lineage reaches this same maximum relative growth rate but at different times. The heterogeneity in observed growth results from shifting the same underlying sigmoid curve in time and scaling by size. Thus, despite the variability in growth observed in our study and others, individual cell lineages in the developing sepal follow similarly shaped growth curves.

Accuracy in Quantitative 3D Image Analysis

Quantitative 3D imaging is becoming an increasingly popular and powerful approach to investigate plant growth and development. With the increased use of 3D image analysis, standards to ensure the accuracy and reproducibility of these data are required. This commentary highlights how image acquisition and postprocessing can introduce artifacts into 3D image data and proposes steps to increase both the accuracy and reproducibility of these analyses. It is intended to aid researchers entering the field of 3D image processing of plant cells and tissues and to help general readers in understanding and evaluating such data.

Themes and variations in cell type patterning in the plant epidermis

It has recently become evident that plant development, like animal development, has molecular patterning modules that are reused again and again to create different cell type patterns. Here we focus on three of these plant modules: (1) the MYB-bHLH-WD40 protein complex, (2) the transmembrane calpain protease DEFECTIVE KERNEL1 (DEK1), and (3) homeodomain leucine zipper (HD-ZIP) class IV transcription factors acting in concert with SIAMESE-related cyclin-dependent kinase inhibitors. These three modules initiate the patterning of multiple cell types in the plant epidermis: the regular spacing of trichomes (leaf hairs), the stripes of root hairs, diverse pigmentation patterns in petals, the scattering of giant cells, and the files of bulliform cells. Varied combinations of players and additional regulatory inputs partially account for the diversity of patterns that are generated by reusing the same molecular mechanisms.

Quantitative and in toto imaging in ascidians: working toward an image-centric systems biology of chordate morphogenesis

Developmental biology relies heavily on microscopy to image the finely controlled cell behaviors that drive embryonic development. Most embryos are large enough that a field of view with the resolution and magnification needed to resolve single cells will not span more than a small region of the embryo. Ascidian embryos, however, are sufficiently small that they can be imaged in toto with fine subcellular detail using conventional microscopes and objectives. Unlike other model organisms with particularly small embryos, ascidians have a chordate embryonic body plan that includes a notochord, hollow dorsal neural tube, heart primordium and numerous other anatomical details conserved with the vertebrates. Here we compare the size and anatomy of ascidian embryos with those of more traditional model organisms, and relate these features to the capabilities of both conventional and exotic imaging methods. We review the emergence of Ciona and related ascidian species as model organisms for a new era of image-based developmental systems biology. We conclude by discussing some important challenges in ascidian imaging and image analysis that remain to be solved.

Interplay between cell growth and cell cycle in plants

The growth of organs and whole plants depends on both cell growth and cell-cycle progression, but the interaction between both processes is poorly understood. In plants, the balance between growth and cell-cycle progression requires coordinated regulation of four different processes: macromolecular synthesis (cytoplasmic growth), turgor-driven cell-wall extension, mitotic cycle, and endocycle. Potential feedbacks between these processes include a cell-size checkpoint operating before DNA synthesis and a link between DNA contents and maximum cell size. In addition, key intercellular signals and growth regulatory genes appear to target at the same time cell-cycle and cell-growth functions. For example, auxin, gibberellin, and brassinosteroid all have parallel links to cell-cycle progression (through S-phase Cyclin D-CDK and the anaphase-promoting complex) and cell-wall functions (through cell-wall extensibility or microtubule dynamics). Another intercellular signal mediated by microtubule dynamics is the mechanical stress caused by growth of interconnected cells. Superimposed on developmental controls, sugar signalling through the TOR pathway has recently emerged as a central control point linking cytoplasmic growth, cell-cycle and cell-wall functions. Recent progress in quantitative imaging and computational modelling will facilitate analysis of the multiple interconnections between plant cell growth and cell cycle and ultimately will be required for the predictive manipulation of plant growth.

Quantifying Shape Changes and Tissue Deformation in Leaf Development

The analysis of biological shapes has applications in many areas of biology, and tools exist to quantify organ shape and detect shape differences between species or among variants. However, such measurements do not provide any information about the mechanisms of shape generation. Quantitative data on growth patterns may provide insights into morphogenetic processes, but since growth is a complex process occurring in four dimensions, growth patterns alone cannot intuitively be linked to shape outcomes. Here, we present computational tools to quantify tissue deformation and surface shape changes over the course of leaf development, applied to the first leaf of Arabidopsis (Arabidopsis thaliana). The results show that the overall leaf shape does not change notably during the developmental stages analyzed, yet there is a clear upward radial deformation of the leaf tissue in early time points. This deformation pattern may provide an explanation for how the Arabidopsis leaf maintains a relatively constant shape despite spatial heterogeneities in growth. These findings highlight the importance of quantifying tissue deformation when investigating the control of leaf shape. More generally, experimental mapping of deformation patterns may help us to better understand the link between growth and shape in organ development.

Mechanical constraints imposed by 3D cellular geometry and arrangement modulate growth patterns in the Arabidopsis embryo

Morphogenesis occurs in 3D space over time and is guided by coordinated gene expression programs. Here we use postembryonic development in Arabidopsis plants to investigate the genetic control of growth. We demonstrate that gene expression driving the production of the growth-stimulating hormone gibberellic acid and downstream growth factors is first induced within the radicle tip of the embryo. The center of cell expansion is, however, spatially displaced from the center of gene expression. Because the rapidly growing cells have very different geometry from that of those at the tip, we hypothesized that mechanical factors may contribute to this growth displacement. To this end we developed 3D finite-element method models of growing custom-designed digital embryos at cellular resolution. We used this framework to conceptualize how cell size, shape, and topology influence tissue growth and to explore the interplay of geometrical and genetic inputs into growth distribution. Our simulations showed that mechanical constraints are sufficient to explain the disconnect between the experimentally observed spatiotemporal patterns of gene expression and early postembryonic growth. The center of cell expansion is the position where genetic and mechanical facilitators of growth converge. We have thus uncovered a mechanism whereby 3D cellular geometry helps direct where genetically specified growth takes place.

Advanced imaging techniques for the study of plant growth and development

A variety of imaging methodologies are being used to collect data for quantitative studies of plant growth and development from living plants. Multi-level data, from macroscopic to molecular, and from weeks to seconds, can be acquired. Furthermore, advances in parallelized and automated image acquisition enable the throughput to capture images from large populations of plants under specific growth conditions. Image-processing capabilities allow for 3D or 4D reconstruction of image data and automated quantification of biological features. These advances facilitate the integration of imaging data with genome-wide molecular data to enable systems-level modeling.

Gene networks controlling Arabidopsis thaliana flower development

The formation of flowers is one of the main models for studying the regulatory mechanisms that underlie plant development and evolution. Over the past three decades, extensive genetic and molecular analyses have led to the identification of a large number of key floral regulators and to detailed insights into how they control flower morphogenesis. In recent years, genome-wide approaches have been applied to obtaining a global view of the gene regulatory networks underlying flower formation. Furthermore, mathematical models have been developed that can simulate certain aspects of this process and drive further experimentation. Here, we review some of the main findings made in the field of Arabidopsis thaliana flower development, with an emphasis on recent advances. In particular, we discuss the activities of the floral organ identity factors, which are pivotal for the specification of the different types of floral organs, and explore the experimental avenues that may elucidate the molecular mechanisms and gene expression programs through which these master regulators of flower development act.

Modeling framework for the establishment of the apical-basal embryonic axis in plants

The apical-basal axis of the early plant embryo determines the body plan of the adult organism. To establish a polarized embryonic axis, plants evolved a unique mechanism that involves directional, cell-to-cell transport of the growth regulator auxin. Auxin transport relies on PIN auxin transporters, whose polar subcellular localization determines the flow directionality. PIN-mediated auxin transport mediates the spatial and temporal activity of the auxin response machinery that contributes to embryo patterning processes, including establishment of the apical (shoot) and basal (root) embryo poles. However, little is known of upstream mechanisms guiding the (re)polarization of auxin fluxes during embryogenesis. Here, we developed a model of plant embryogenesis that correctly generates emergent cell polarities and auxin-mediated sequential initiation of apical-basal axis of plant embryo. The model relies on two precisely localized auxin sources and a feedback between auxin and the polar, subcellular PIN transporter localization. Simulations reproduced PIN polarity and auxin distribution, as well as previously unknown polarization events during early embryogenesis. The spectrum of validated model predictions suggests that our model corresponds to a minimal mechanistic framework for initiation and orientation of the apical-basal axis to guide both embryonic and postembryonic plant development.

Cooperation and competition in the dynamics of tissue architecture during homeostasis and tumorigenesis

The construction of a network of cell-to-cell contacts makes it possible to characterize the patterns and spatial organization of tissues. Such networks are highly dynamic, depending on the changes of the tissue architecture caused by cell division, death and migration. Local competitive and cooperative cell-to-cell interactions influence the choices cells make. We review the literature on quantitative data of epithelial tissue topology and present a dynamical network model that can be used to explore the evolutionary dynamics of a two dimensional tissue architecture with arbitrary cell-to-cell interactions. In particular, we show that various forms of experimentally observed types of interactions can be modelled using game theory. We discuss a model of cooperative and non-cooperative cell-to-cell communication that can capture the interplay between cellular competition and tissue dynamics. We conclude with an outlook on the possible uses of this approach in modelling tumorigenesis and tissue homeostasis.

Computational modeling of epidermal cell fate determination systems

Cell fate decisions are of primary importance for plant development. Their simple 'either-or' outcome and dynamic nature has attracted the attention of computational modelers. Recent efforts have focused on modeling the determination of several epidermal cell types in the root and shoot of Arabidopsis where many molecular components have been defined. Results of integrated modeling and molecular biology experimentation in these systems have highlighted the importance of competitive positive and negative factors and interconnected feedback loops in generating flexible yet robust mechanisms for establishing distinct gene expression programs in neighboring cells. These models have proven useful in judging hypotheses and guiding future research.

Emerging role of the ubiquitin proteasome system in the control of shoot apical meristem function(f)

The shoot apical meristem (SAM) is a population of undifferentiated cells at the tip of the shoot axis that establishes early during plant embryogenesis and gives rise to all shoot organs throughout the plant's life. A plethora of different families of transcription factors (TFs) play a key role in establishing the equilibrium between cell differentiation and stem cell maintenance in the SAM. Fine tuning of these regulatory proteins is crucial for a proper and fast SAM response to environmental and hormonal cues, and for development progression. One effective way to rapidly inactivate TFs involves regulated proteolysis by the ubiquitin/26S proteasome system (UPS). However, a possible role of UPS-dependent protein degradation in the regulation of key SAM TFs has not been thoroughly investigated. Here, we summarize recent evidence supporting a role for the UPS in SAM maintenance and function. We integrate this survey with an in silico analysis of publicly-available microarray databases which identified ubiquitin ligases that are expressed in specific areas within the SAM, suggesting that they may regulate or act downstream of meristem-specific factors.

New insights into the dynamics of plant cell nuclei and chromosomes

The plant lamin-like protein NMCP/AtLINC and orthologues of the SUN-KASH complex across the nuclear envelope (NE) show the universality of nuclear structure in eukaryotes. However, depletion of components in the connection complex of the NE in plants does not induce severe defects, unlike in animals. Appearance of the Rabl configuration is not dependent on genome size in plant species. Topoisomerase II and condensin II are not essential for plant chromosome condensation. Plant endoreduplication shares several common characteristics with animals, including involvement of cyclin-dependent kinases and E2F transcription factors. Recent finding regarding endomitosis regulator GIG1 shed light on the suppression mechanism of endomitosis in plants. The robustness of plants, compared with animals, is reflected in their genome redundancy. Spatiotemporal functional analyses using chromophore-assisted light inactivation, super-resolution microscopy, and 4D (3D plus time) imaging will reveal new insights into plant nuclear and chromosomal dynamics.

ACME: automated cell morphology extractor for comprehensive reconstruction of cell membranes

The quantification of cell shape, cell migration, and cell rearrangements is important for addressing classical questions in developmental biology such as patterning and tissue morphogenesis. Time-lapse microscopic imaging of transgenic embryos expressing fluorescent reporters is the method of choice for tracking morphogenetic changes and establishing cell lineages and fate maps in vivo. However, the manual steps involved in curating thousands of putative cell segmentations have been a major bottleneck in the application of these technologies especially for cell membranes. Segmentation of cell membranes while more difficult than nuclear segmentation is necessary for quantifying the relations between changes in cell morphology and morphogenesis. We present a novel and fully automated method to first reconstruct membrane signals and then segment out cells from 3D membrane images even in dense tissues. The approach has three stages: 1) detection of local membrane planes, 2) voting to fill structural gaps, and 3) region segmentation. We demonstrate the superior performance of the algorithms quantitatively on time-lapse confocal and two-photon images of zebrafish neuroectoderm and paraxial mesoderm by comparing its results with those derived from human inspection. We also compared with synthetic microscopic images generated by simulating the process of imaging with fluorescent reporters under varying conditions of noise. Both the over-segmentation and under-segmentation percentages of our method are around 5%. The volume overlap of individual cells, compared to expert manual segmentation, is consistently over 84%. By using our software (ACME) to study somite formation, we were able to segment touching cells with high accuracy and reliably quantify changes in morphogenetic parameters such as cell shape and size, and the arrangement of epithelial and mesenchymal cells. Our software has been developed and tested on Windows, Mac, and Linux platforms and is available publicly under an open source BSD license (https://github.com/krm15/ACME).

When and where plant cells divide: a perspective from computational modeling

Computational modeling of growing plant tissues raises two basic questions about plant cell division: when does a cell decide to divide and where is the new wall placed? Although biologists and modelers commonly assume that a cell divides after it reaches a threshold size, two recent experiments show that models with variable division sizes better replicate the tissue. Similarly, comparing model predictions with living plant cells reveals that the choice of division plane is variable, although the shortest path dividing a cell in half (i.e. the minimal surface area) is the most probable division plane.

Cell cycle regulates cell type in the Arabidopsis sepal

The formation of cellular patterns during development requires the coordination of cell division with cell identity specification. This coordination is essential in patterning the highly elongated giant cells, which are interspersed between small cells, in the outer epidermis of the Arabidopsis thaliana sepal. Giant cells undergo endocycles, replicating their DNA without dividing, whereas small cells divide mitotically. We show that distinct enhancers are expressed in giant cells and small cells, indicating that these cell types have different identities as well as different sizes. We find that members of the epidermal specification pathway, DEFECTIVE KERNEL1 (DEK1), MERISTEM LAYER1 (ATML1), Arabidopsis CRINKLY4 (ACR4) and HOMEODOMAIN GLABROUS11 (HDG11), control the identity of giant cells. Giant cell identity is established upstream of cell cycle regulation. Conversely, endoreduplication represses small cell identity. These results show not only that cell type affects cell cycle regulation, but also that changes in the cell cycle can regulate cell type.

Computational multiscale modeling of embryo development

Recent advances in live imaging and genetics of mammalian development which integrate observations of biochemical activity, cell-cell signaling and mechanical interactions between cells pave the way for predictive mathematical multi-scale modeling. In early mammalian embryo development, two of the most critical events which lead to tissue patterning involve changes in gene expression as well as mechanical interactions between cells. We discuss the relevance of mathematical modeling of multi-cellular systems and in particular in simulating these patterns and describe some of the technical challenges one encounters. Many of these issues are not unique for the embryonic system but are shared by other multi-cellular modeling areas.

The Measurement of Local Variation in Shape

Geometric morphometrics comprises tools for measuring and analyzing shape as captured by an entire set of landmark configurations. Many interesting questions in evolutionary, genetic, and developmental research, however, are only meaningful at a local level, where a focus on "parts" or "traits" takes priority over properties of wholes. To study variational properties of such traits, current approaches partition configurations into subsets of landmarks which are then studied separately. This approach is unable to fully capture both variational and spatial characteristics of these subsets because interpretability of shape differences is context-dependent. Landmarks omitted from a partition usually contain information about that partition's shape. We present an interpolation-based approach that can be used to model shape differences at a local, infinitesimal level as a function of information available globally. This approach belongs in a large family of methods that see shape differences as continuous "fields" spanning an entire structure, for which landmarks serve as reference parameters rather than as data. We show, via analyses of simulated and real data, how interpolation models provide a more accurate representation of regional shapes than partitioned data. A key difference of this interpolation approach from current morphometric practice is that one must assume an explicit interpolation model, which in turn implies a particular kind of behavior of the regions between landmarks. This choice presents novel methodological challenges, but also an opportunity to incorporate and test biomechanical models that have sought to explain tissue-level processes underlying the generation of morphological shape.