What Is a Plant Cell Type in the Age of Single-Cell Biology? It's Complicated.

One of the fundamental questions in developmental biology is how a cell is specified to differentiate as a specialized cell type. Traditionally, plant cell types were defined based on their function, location, morphology, and lineage. Currently, in the age of single-cell biology, researchers typically attempt to assign plant cells to cell types by clustering them based on their transcriptomes. However, because cells are dynamic entities that progress through the cell cycle and respond to signals, the transcriptome also reflects the state of the cell at a particular moment in time, raising questions about how to define a cell type. We suggest that these complexities and dynamics of cell states are of interest and further consider the roles signaling, stochasticity, cell cycle, and mechanical forces play in plant cell fate specification. Once established, cell identity must also be maintained. With the wealth of single-cell data coming out, the field is poised to elucidate both the complexity and dynamics of cell states.

Robust organ size in Arabidopsis is primarily governed by cell growth rather than cell division patterns.

Organ sizes and shapes are highly reproducible, or robust, within a species and individuals. Arabidopsis thaliana sepals, which are the leaf-like organs that enclose flower buds, have consistent size and shape, indicating robust development. Cell growth is locally heterogeneous due to intrinsic and extrinsic noise. To achieve robust organ shape, fluctuations in cell growth must average to an even growth rate, which requires that fluctuations are uncorrelated or anti-correlated in time and space. Here, we live image and quantify the development of sepals with an increased or decreased number of cell divisions (lgo mutant and LGO overexpression, respectively), a mutant with altered cell growth variability (ftsh4), and double mutants combining these. Changes in the number of cell divisions do not change the overall growth pattern. By contrast, in ftsh4 mutants, cell growth accumulates in patches of over- and undergrowth owing to correlations that impair averaging, resulting in increased organ shape variability. Thus, we demonstrate in vivo that the number of cell divisions does not affect averaging of cell growth, preserving robust organ morphogenesis, whereas correlated growth fluctuations impair averaging.

Growth couples temporal and spatial fluctuations of tissue properties during morphogenesis.

Living tissues display fluctuations-random spatial and temporal variations of tissue properties around their reference values-at multiple scales. It is believed that such fluctuations may enable tissues to sense their state or their size. Recent theoretical studies developed specific models of fluctuations in growing tissues and predicted that fluctuations of growth show long-range correlations. Here, we elaborated upon these predictions and we tested them using experimental data. We first introduced a minimal model for the fluctuations of any quantity that has some level of temporal persistence or memory, such as concentration of a molecule, local growth rate, or mechanical property. We found that long-range correlations are generic, applying to any such quantity, and that growth couples temporal and spatial fluctuations, through a mechanism that we call "fluctuation stretching"-growth enlarges the length scale of variation of this quantity. We then analyzed growth data from sepals of the model plant Arabidopsis and we quantified spatial and temporal fluctuations of cell growth using the previously developed cellular Fourier transform. Growth appears to have long-range correlations. We compared different genotypes and growth conditions: mutants with lower or higher response to mechanical stress have lower temporal correlations and longer-range spatial correlations than wild-type plants. Finally, we used theoretical predictions to merge experimental data from all conditions and developmental stages into a unifying curve, validating the notion that temporal and spatial fluctuations are coupled by growth. Altogether, our work reveals kinematic constraints on spatiotemporal fluctuations that have an impact on the robustness of morphogenesis.

Enhancer activation via TCP and HD-ZIP and repression by Dof transcription factors mediate giant cell-specific expression.

Proper cell-type identity relies on highly coordinated regulation of gene expression. Regulatory elements such as enhancers can produce cell type-specific expression patterns, but the mechanisms underlying specificity are not well understood. We previously identified an enhancer region capable of driving specific expression in giant cells, which are large, highly endoreduplicated cells in the Arabidopsis thaliana sepal epidermis. In this study, we use the giant cell enhancer as a model to understand the regulatory logic that promotes cell type-specific expression. Our dissection of the enhancer revealed that giant cell specificity is mediated primarily through the combination of two activators and one repressor. HD-ZIP and TCP transcription factors are involved in the activation of expression throughout the epidermis. High expression of HD-ZIP transcription factor genes in giant cells promoted higher expression driven by the enhancer in giant cells. Dof transcription factors repressed the activity of the enhancer such that only giant cells maintained enhancer activity. Thus, our data are consistent with a conceptual model whereby cell type-specific expression emerges from the combined activities of three transcription factor families activating and repressing expression in epidermal cells.

Fifteen compelling open questions in plant cell biology.

As scientists, we are at least as excited about the open questions-the things we do not know-as the discoveries. Here, we asked 15 experts to describe the most compelling open questions in plant cell biology. These are their questions: How are organelle identity, domains, and boundaries maintained under the continuous flux of vesicle trafficking and membrane remodeling? Is the plant cortical microtubule cytoskeleton a mechanosensory apparatus? How are the cellular pathways of cell wall synthesis, assembly, modification, and integrity sensing linked in plants? Why do plasmodesmata open and close? Is there retrograde signaling from vacuoles to the nucleus? How do root cells accommodate fungal endosymbionts? What is the role of cell edges in plant morphogenesis? How is the cell division site determined? What are the emergent effects of polyploidy on the biology of the cell, and how are any such "rules" conditioned by cell type? Can mechanical forces trigger new cell fates in plants? How does a single differentiated somatic cell reprogram and gain pluripotency? How does polarity develop de-novo in isolated plant cells? What is the spectrum of cellular functions for membraneless organelles and intrinsically disordered proteins? How do plants deal with internal noise? How does order emerge in cells and propagate to organs and organisms from complex dynamical processes? We hope you find the discussions of these questions thought provoking and inspiring.

Cytokinin-CLAVATA cross-talk is an ancient mechanism regulating shoot meristem homeostasis in land plants.

SignificancePlants grow from their tips. The gametophore (shoot-like organ) tip of the moss Physcomitrium patens is a single cell that performs the same functions as those of multicellular flowering plants, producing the cells that make leaves and regenerating new stem cells to maintain the shoot tip. Several pathways, including CLAVATA and cytokinin hormonal signaling, regulate stem cell abundance in flowering plants and in mosses, although the mechanisms whereby these pathways regulate stem cell abundance and their conservation between these plant lineages is poorly understood. Using moss, we investigated how PpCLAVATA and cytokinin signaling interact. Overall, we found evidence that PpCLAVATA and cytokinin signaling interact similarly in moss and flowering plants, despite their distinct anatomies, life cycles, and evolutionary distance.

The ratio of auxin to cytokinin controls leaf development and meristem initiation in Physcomitrium patens.

Crosstalk between auxin and cytokinin contributes to widespread developmental processes, including root and shoot meristem maintenance, phyllotaxy, and vascular patterning. However, our understanding of crosstalk between these hormones is limited primarily to angiosperms. The moss Physcomitrium patens (formerly Physcomitrella patens) is a powerful system for studying plant hormone function. Auxin and cytokinin play similar roles in regulating moss gametophore (shoot) architecture, to those in flowering plant shoots. However, auxin-cytokinin crosstalk is poorly understood in moss. Here we find that the ratio of auxin to cytokinin is an important determinant of development in P. patens, especially during leaf development and branch stem cell initiation. Addition of high levels of auxin to P. patens gametophores blocks leaf outgrowth. However, simultaneous addition of high levels of both auxin and cytokinin partially restores leaf outgrowth, suggesting that the ratio of these hormones is the predominant factor. Likewise, during branch initiation and outgrowth, chemical inhibition of auxin synthesis phenocopies cytokinin application. Finally, cytokinin-insensitive mutants resemble plants with altered auxin signaling and are hypersensitive to auxin. In summary, our results suggest that the ratio between auxin and cytokinin signaling is the basis for developmental decisions in the moss gametophore.

Computational morphodynamics of plants: integrating development over space and time.

The emerging field of computational morphodynamics aims to understand the changes that occur in space and time during development by combining three technical strategies: live imaging to observe development as it happens; image processing and analysis to extract quantitative information; and computational modelling to express and test time-dependent hypotheses. The strength of the field comes from the iterative and combined use of these techniques, which has provided important insights into plant development.

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.

Ploidy and Size at Multiple Scales in the Arabidopsis Sepal.

Ploidy and size phenomena are observed to be correlated across several biological scales, from subcellular to organismal. Two kinds of ploidy change can affect plants. Whole-genome multiplication increases ploidy in whole plants and is broadly associated with increases in cell and organism size. Endoreduplication increases ploidy in individual cells. Ploidy increase is strongly correlated with increased cell size and nuclear volume. Here, we investigate scaling relationships between ploidy and size by simultaneously quantifying nuclear size, cell size, and organ size in sepals from an isogenic series of diploid, tetraploid, and octoploid Arabidopsis thaliana plants, each of which contains an internal endopolyploidy series. We find that pavement cell size and transcriptome size increase linearly with whole-organism ploidy, but organ area increases more modestly due to a compensatory decrease in cell number. We observe that cell size and nuclear size are maintained at a constant ratio; the value of this constant is similar in diploid and tetraploid plants and slightly lower in octoploid plants. However, cell size is maintained in a mutant with reduced nuclear size, indicating that cell size is scaled to cell ploidy rather than to nuclear size. These results shed light on how size is regulated in plants and how cells and organisms of differing sizes are generated by ploidy change.

Clones of cells switch from reduction to enhancement of size variability in Arabidopsis sepals.

Organs form with remarkably consistent sizes and shapes during development, whereas a high variability in growth is observed at the cell level. Given this contrast, it is unclear how such consistency in organ scale can emerge from cellular behavior. Here, we examine an intermediate scale, the growth of clones of cells in Arabidopsis sepals. Each clone consists of the progeny of a single progenitor cell. At early stages, we find that clones derived from a small progenitor cell grow faster than those derived from a large progenitor cell. This results in a reduction in clone size variability, a phenomenon we refer to as size uniformization. By contrast, at later stages of clone growth, clones change their growth pattern to enhance size variability, when clones derived from larger progenitor cells grow faster than those derived from smaller progenitor cells. Finally, we find that, at early stages, fast growing clones exhibit greater cell growth heterogeneity. Thus, cellular variability in growth might contribute to a decrease in the variability of clones throughout the sepal.

Can the French flag and reaction-diffusion models explain flower patterning? Celebrating the 50th anniversary of the French flag model.

It has been 50 years since Lewis Wolpert introduced the French flag model proposing the patterning of different cell types based on threshold concentrations of a morphogen diffusing in the tissue. Sixty-seven years ago, Alan Turing introduced the idea of patterns initiating de novo from a reaction-diffusion network. Together these models have been used to explain many patterning events in animal development, so here we take a look at their applicability to flower development. First, although many plant transcription factors move through plasmodesmata from cell to cell, in the flower there is little evidence that they specify fate in a concentration-dependent manner, so they cannot yet be described as morphogens. Secondly, the reaction-diffusion model appears to be a reasonably good description of the formation of spots of pigment on petals, although additional nuances are present. Thirdly, aspects of both of these combine in a new fluctuation-based patterning system creating the scattered pattern of giant cells in Arabidopsis sepals. In the future, more precise imaging and manipulations of the dynamics of patterning networks combined with mathematical modeling will allow us to better understand how the multilayered complex and beautiful patterns of flowers emerge de novo.

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.

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.

A computational image analysis glossary for biologists.

Recent advances in biological imaging have resulted in an explosion in the quality and quantity of images obtained in a digital format. Developmental biologists are increasingly acquiring beautiful and complex images, thus creating vast image datasets. In the past, patterns in image data have been detected by the human eye. Larger datasets, however, necessitate high-throughput objective analysis tools to computationally extract quantitative information from the images. These tools have been developed in collaborations between biologists, computer scientists, mathematicians and physicists. In this Primer we present a glossary of image analysis terms to aid biologists and briefly discuss the importance of robust image analysis in developmental studies.

Endomembrane trafficking protein SEC24A regulates cell size patterning in Arabidopsis.

Size is a critical property of a cell, but how it is determined is still not well understood. The sepal epidermis of Arabidopsis (Arabidopsis thaliana) contains cells with a diversity of sizes ranging from giant cells to small cells. Giant cells have undergone endoreduplication, a specialized cell cycle in which cells replicate their DNA but fail to divide, becoming polyploid and enlarged. Through forward genetics, we have identified a new mutant with ectopic giant cells covering the sepal epidermis. Surprisingly, the mutated gene, SEC24A, encodes a coat protein complex II vesicle coat subunit involved in endoplasmic reticulum-to-Golgi trafficking in the early secretory pathway. We show that the ectopic giant cells of sec24a-2 are highly endoreduplicated and that their formation requires the activity of giant cell pathway genes LOSS OF GIANT CELLS FROM ORGANS, DEFECTIVE KERNEL1, and Arabidopsis CRINKLY4. In contrast to other trafficking mutants, cytokinesis appears to occur normally in sec24a-2. Our study reveals an unexpected yet specific role of SEC24A in endoreduplication and cell size patterning in the Arabidopsis sepal.

A novel role for the floral homeotic gene APETALA2 during Arabidopsis fruit development.

The majority of the Arabidopsis fruit comprises an ovary with three primary tissue types: the valves, the replum and the valve margins. The valves, which are derived from the ovary walls, are separated along their entire length by the replum. The valve margin, which consists of a separation layer and a lignified layer, forms as a narrow stripe of cells at the valve-replum boundaries. The valve margin identity genes are expressed at the valve-replum boundary and are negatively regulated by FUL and RPL in the valves and replum, respectively. In ful rpl double mutants, the valve margin identity genes become ectopically expressed, and, as a result, the entire outer surface of the ovary takes on valve margin identity. We carried out a genetic screen in this sensitized genetic background and identified a suppressor mutation that restored replum development. Surprisingly, we found that the corresponding suppressor gene was AP2, a gene that is well known for its role in floral organ identity, but whose role in Arabidopsis fruit development had not been previously described. We found that AP2 acts to prevent replum overgrowth by negatively regulating BP and RPL, two genes that normally act to promote replum formation. We also determined that AP2 acts to prevent overgrowth of the valve margin by repressing valve margin identity gene expression. We have incorporated AP2 into the current genetic network controlling fruit development in Arabidopsis.

An optimized live imaging and growth analysis approach for Arabidopsis Sepals.

Background: Arabidopsis thaliana sepals are excellent models for analyzing growth of entire organs due to their relatively small size, which can be captured at a cellular resolution under a confocal microscope [1]. To investigate how growth of different tissue layers generates unique organ morphologies, it is necessary to live-image deep into the tissue. However, imaging deep cell layers of the sepal is practically challenging, as it is hindered by the presence of extracellular air spaces between mesophyll cells, among other factors which causes optical aberrations. Image processing is also difficult due to the low signal-to-noise ratio of the deeper tissue layers, an issue mainly associated with live imaging datasets. Addressing some of these challenges, we provide an optimized methodology for live imaging sepals and subsequent image processing. This helps us track the growth of individual cells on the outer and inner epidermal layers, which are the key drivers of sepal morphogenesis. Results: For live imaging sepals across all tissue layers at early stages of development, we found that the use of a bright fluorescent membrane marker, coupled with increased laser intensity and an enhanced Z- resolution produces high-quality images suitable for downstream image processing. Our optimized parameters allowed us to image the bottommost cell layer of the sepal (inner epidermal layer) without compromising viability. We used a 'voxel removal' technique to visualize the inner epidermal layer in MorphoGraphX [2, 3] image processing software. Finally, we describe the process of optimizing the parameters for creating a 2.5D mesh surface for the inner epidermis. This allowed segmentation and parent tracking of individual cells through multiple time points, despite the weak signal of the inner epidermal cells. Conclusion: We provide a robust pipeline for imaging and analyzing growth across inner and outer epidermal layers during early sepal development. Our approach can potentially be employed for analyzing growth of other internal cell layers of the sepals as well. For each of the steps, approaches, and parameters we used, we have provided in-depth explanations to help researchers understand the rationale and replicate our pipeline.

An optimized live imaging and multiple cell layer growth analysis approach using Arabidopsis sepals.

Arabidopsis thaliana sepals are excellent models for analyzing growth of entire organs due to their relatively small size, which can be captured at a cellular resolution under a confocal microscope. To investigate how differential growth of connected cell layers generate unique organ morphologies, it is necessary to live-image deep into the tissue. However, imaging deep cell layers of the sepal (or plant tissues in general) is practically challenging. Image processing is also difficult due to the low signal-to-noise ratio of the deeper tissue layers, an issue mainly associated with live imaging datasets. Addressing some of these challenges, we provide an optimized methodology for live imaging sepals, and subsequent image processing. For live imaging early-stage sepals, we found that the use of a bright fluorescent membrane marker, coupled with increased laser intensity and an enhanced Z- resolution produces high-quality images suitable for downstream image processing. Our optimized parameters allowed us to image the bottommost cell layer of the sepal (inner epidermal layer) without compromising viability. We used a 'voxel removal' technique to visualize the inner epidermal layer in MorphoGraphX image processing software. We also describe the MorphoGraphX parameters for creating a 2.5D mesh surface for the inner epidermis. Our parameters allow for the segmentation and parent tracking of individual cells through multiple time points, despite the weak signal of the inner epidermal cells. While we have used sepals to illustrate our approach, the methodology will be useful for researchers intending to live-image and track growth of deeper cell layers in 2.5D for any plant tissue.