Extracting Subcellular Fibrillar Alignment with Error Estimation: Application to Microtubules

Automatic extraction of actin networks in plants

The actin cytoskeleton is essential in eukaryotes, not least in the plant kingdom where it plays key roles in cell expansion, cell division, environmental responses and pathogen defence. Yet, the precise structure-function relationships of properties of the actin network in plants are still to be unravelled, including details of how the network configuration depends upon cell type, tissue type and developmental stage. Part of the problem lies in the difficulty of extracting high-quality, quantitative measures of actin network features from microscopy data. To address this problem, we have developed DRAGoN, a novel image analysis algorithm that can automatically extract the actin network across a range of cell types, providing seventeen different quantitative measures that describe the network at a local level. Using this algorithm, we then studied a number of cases in Arabidopsis thaliana, including several different tissues, a variety of actin-affected mutants, and cells responding to powdery mildew. In many cases we found statistically-significant differences in actin network properties. In addition to these results, our algorithm is designed to be easily adaptable to other tissues, mutants and plants, and so will be a valuable asset for the study and future biological engineering of the actin cytoskeleton in globally-important crops.

Single-Cell Confinement Methods to Study Plant Cytoskeleton

Progress in cytoskeletal research in animal systems has been accompanied by the development of single-cell systems (e.g., fibroblasts in culture). Single-cell systems exist for plant research, but the presence of a cell wall hinders the possibility to relate cytoskeleton dynamics to changes in cell shape or in mechanical stress pattern. Here we present two protocols to confine wall-less plant protoplasts in microwells with defined geometries. Either protocol might be more or less adapted to the question at hand. For instance, when using microwells made of agarose, the composition of the well can be easily modified to analyze the impact of biochemical cues. When using microwells in a stiff polymer (NOA73), protoplasts can be pressurized, and the wall of the well can be coated with cell wall components. Using both protocols, we could analyze microtubule and actin dynamics in vivo while also revealing the relative contribution of geometry and stress in their self-organization.

Sculpting the surface: Structural patterning of plant epidermis

Plant epidermis are multifunctional surfaces that directly affect how plants interact with animals or microorganisms and influence their ability to harvest or protect from abiotic factors. To do this, plants rely on minuscule structures that confer remarkable properties to their outer layer. These microscopic features emerge from the hierarchical organization of epidermal cells with various shapes and dimensions combined with different elaborations of the cuticle, a protective film that covers plant surfaces. Understanding the properties and functions of those tridimensional elements as well as disentangling the mechanisms that control their formation and spatial distribution warrant a multidisciplinary approach. Here we show how interdisciplinary efforts of coupling modern tools of experimental biology, physics, and chemistry with advanced computational modeling and state-of-the art microscopy are yielding broad new insights into the seemingly arcane patterning processes that sculpt the outer layer of plants.

Automated and semi-automated enhancement, segmentation and tracing of cytoskeletal networks in microscopic images: A review

Cytoskeletal filaments are structures of utmost importance to biological cells and organisms due to their versatility and the significant functions they perform. These biopolymers are most often organised into network-like scaffolds with a complex morphology. Understanding the geometrical and topological organisation of these networks provides key insights into their functional roles. However, this non-trivial task requires a combination of high-resolution microscopy and sophisticated image processing/analysis software. The correct analysis of the network structure and connectivity needs precise segmentation of microscopic images. While segmentation of filament-like objects is a well-studied concept in biomedical imaging, where tracing of neurons and blood vessels is routine, there are comparatively fewer studies focusing on the segmentation of cytoskeletal filaments and networks from microscopic images. The developments in the fields of microscopy, computer vision and deep learning, however, began to facilitate the task, as reflected by an increase in the recent literature on the topic. Here, we aim to provide a short summary of the research on the (semi-)automated enhancement, segmentation and tracing methods that are particularly designed and developed for microscopic images of cytoskeletal networks. In addition to providing an overview of the conventional methods, we cover the recently introduced, deep-learning-assisted methods alongside the advantages they offer over classical methods.

Root shape adaptation to mechanical stress derived from unidirectional vibrations in Populus nigra

While it is known that plant roots can change their shapes to the stress direction, it remains unclear if the root orientation can change as a means for mechanical reinforcement. When stress in form of a unidirectional vibration is applied to cuttings of Populus nigra for 5 min a day over a period of 20 days, the root system architecture changes. The contribution of roots with a diameter larger than 0.04 cm increases, while the allocation to roots smaller than 0.03 cm decreases. In addition to the root diameter allocation, the root orientation in the stem proximity was analyzed by appearance and with a nematic tensor analysis in an attempt to calculate the average root orientation. The significant different allocation to roots with a larger diameter, and the tendency of roots to align in the vicinity of the stress axis (not significantly different), are indicating a mechanical reinforcement to cope with the received strain. This work indicates an adaptive root system architecture and a possible adaptive root orientation for mechanical reinforcement.

Cortical tension overrides geometrical cues to orient microtubules in confined protoplasts

In plants, microtubules largely determine the direction of cell expansion and the orientation of cell division planes. However, what processes orient the microtubules has remained debated. Here, we used microfabricated wells to confine and deform wallless plant cells in a controlled way to analyze the response of microtubules to cell geometry and surface tension. We demonstrate that microtubules align with cell geometry by default, whereas when surface tension increases (e.g. when turgor pressure increases), they align with the direction of maximal tension. Not only does this explain many observations in plant tissues, but it also provides a simple mechanism at the core of plant morphogenesis, in which microtubules can spontaneously align with tension, in a typical self-organized system.

In plant cells, cortical microtubules (CMTs) generally control morphogenesis by guiding cellulose synthesis. CMT alignment has been proposed to depend on geometrical cues, with microtubules aligning with the cell long axis in silico and in vitro. Yet, CMTs are usually transverse in vivo, i.e., along predicted maximal tension, which is transverse for cylindrical pressurized vessels. Here, we adapted a microwell setup to test these predictions in a single-cell system. We confined protoplasts laterally to impose a curvature ratio and modulated pressurization through osmotic changes. We find that CMTs can be longitudinal or transverse in wallless protoplasts and that the switch in CMT orientation depends on pressurization. In particular, longitudinal CMTs become transverse when cortical tension increases. This explains the dual behavior of CMTs in planta: CMTs become longitudinal when stress levels become low, while stable transverse CMT alignments in tissues result from their autonomous response to tensile stress fluctuations.

Density fields for branching, stiff networks in rigid confining regions

We develop a formalism to describe the equilibrium distributions for segments of confined branched networks consisting of stiff filaments. This is applicable to certain situations of cytoskeleton in cells, such as for example actin filaments with branching due to the Arp2/3 complex. We develop a grand ensemble formalism that enables the computation of segment density and polarisation profiles within the confines of the cell. This is expressed in terms of the solution to nonlinear integral equations for auxiliary functions. We find three specific classes of behaviour depending on filament length, degree of branching and the ratio of persistence length to the dimensions of the geometry. Our method allows a numerical approach for semi-flexible filaments that are networked.

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.

Regulation of plant cell wall stiffness by mechanical stress: a mesoscale physical model

A crucial question in developmental biology is how cell growth is coordinated in living tissue to generate complex and reproducible shapes. We address this issue here in plants, where stiff extracellular walls prevent cell migration and morphogenesis mostly results from growth driven by turgor pressure. How cells grow in response to pressure partly depends on the mechanical properties of their walls, which are generally heterogeneous, anisotropic and dynamic. The active control of these properties is therefore a cornerstone of plant morphogenesis. Here, we focus on wall stiffness, which is under the control of both molecular and mechanical signaling. Indeed, in plant tissues, the balance between turgor and cell wall elasticity generates a tissue-wide stress field. Within cells, mechano-sensitive structures, such as cortical microtubules, adapt their behavior accordingly and locally influence cell wall remodeling dynamics. To fully apprehend the properties of this feedback loop, modeling approaches are indispensable. To that end, several modeling tools in the form of virtual tissues have been developed. However, these models often relate mechanical stress and cell wall stiffness in relatively abstract manners, where the molecular specificities of the various actors are not fully captured. In this paper, we propose to refine this approach by including parsimonious biochemical and biomechanical properties of the main molecular actors involved. Through a coarse-grained approach and through finite element simulations, we study the role of stress-sensing microtubules on organ-scale mechanics.

Heterogeneity and Robustness in Plant Morphogenesis: From Cells to Organs

Development is remarkably reproducible, producing organs with the same size, shape, and function repeatedly from individual to individual. For example, every flower on the Antirrhinum stalk has the same snapping dragon mouth. This reproducibility has allowed taxonomists to classify plants and animals according to their morphology. Yet these reproducible organs are composed of highly variable cells. For example, neighboring cells grow at different rates in Arabidopsis leaves, sepals, and shoot apical meristems. This cellular variability occurs in normal, wild-type organisms, indicating that cellular heterogeneity (or diversity in a characteristic such as growth rate) is either actively maintained or, at a minimum, not entirely suppressed. In fact, cellular heterogeneity can contribute to producing invariant organs. Here, we focus on how plant organs are reproducibly created during development from these highly variable cells.

An automated quantitative image analysis tool for the identification of microtubule patterns in plants

High throughput confocal imaging poses challenges in the computational image analysis of complex subcellular structures such as the microtubule cytoskeleton. Here, we developed CellArchitect, an automated image analysis tool that quantifies changes to subcellular patterns illustrated by microtubule markers in plants. We screened microtubule-targeted herbicides and demonstrate that high throughput confocal imaging with integrated image analysis by CellArchitect can distinguish effects induced by the known herbicides indaziflam and trifluralin. The same platform was used to examine 6 other compounds with herbicidal activity, and at least 3 different effects induced by these compounds were profiled. We further show that CellArchitect can detect subcellular patterns tagged by actin and endoplasmic reticulum markers. Thus, the platform developed here can be used to automate image analysis of complex subcellular patterns for purposes such as herbicide discovery and mode of action characterisation. The capacity to use this tool to quantitatively characterize cellular responses lends itself to application across many areas of biology.

In-vivo analysis of morphogenesis in plants

Although many molecular regulators of morphogenesis have been identified in plants, it remains largely unknown how the molecular networks influence local cell shape and how cell growth, form, and position are coordinated during tissue and organ formations. So far, analyses of gene function in morphogenesis have mainly focused on the qualitative analysis of phenotypes, often providing limited mechanistic insight into how particular factors act. For this reason, there has been a growing interest in mathematical and computational models to formalize and test hypotheses. These require much more rigorous, quantitative approaches; in parallel, new quantitative and correlative imaging pipelines have been developed to study morphogenesis. Here, we describe a number of such methods, focusing on live imaging.