3D epithelial cell topology tunes signaling range to promote precise patterning

Dynamic Filopodia Transmit Intermittent Delta-Notch Signaling to Drive Pattern Refinement during Lateral Inhibition

During development and tissue repair, cells reshape and reconfigure to ensure organs take specific shapes. This process is inherently three-dimensional (3D). Yet, in part due to limitations in imaging and data analysis, cell shape analysis within tissues has largely been studied in two-dimensions (2D), e.g., the Drosophila wing disc. With recent advances in imaging and machine learning, there has been significant progress in our understanding of 3D cell and tissue shape in vivo. However, even after gaining 3D segmentation of cells, it remains challenging to extract cell shape metrics beyond volume and surface area for cells within densely packed tissues. To address the challenge of extracting 3D cell shape metrics from dense tissues, we have developed the Python package CellMet. This user-friendly tool enables extraction of quantitative shape information from 3D cell and tissue segmentations, including cell face properties, cell twist, and cell rearrangements in 3D. Our method will improve the analysis of 3D cell shape and the understanding of cell organisation within tissues. Our tool is open source, available at https://github.com/TimSaundersLab/CellMet.

The dynamics of neurogenic signalling underlying bristle development in Drosophila melanogaster

Direct cell-cell communication with three-dimensional cell morphology on wrinkled microposts

Cell migration is fundamental for both physiological and pathological processes. Migrating cells usually display high dynamics in morphology, which is orchestrated by an integrative array of signalling pathways. Here we identify a novel pathway, we term lateral signalling, comprised of the planar cell polarity (PCP) protein Pk1 and the RhoGAPs, Arhgap21/23. We show that the Pk1–Arhgap21/23 complex inhibits RhoA, is localized on the non-protrusive lateral membrane cortex and its disruption leads to the disorganization of the actomyosin network and altered focal adhesion dynamics. Pk1-mediated lateral signalling confines protrusive activity and is regulated by Smurf2, an E3 ubiquitin ligase in the PCP pathway. Furthermore, we demonstrate that dynamic interplay between lateral and protrusive signalling generates cyclical fluctuations in cell shape that we quantify here as shape volatility, which strongly correlates with migration speed. These studies uncover a previously unrecognized lateral signalling pathway that coordinates shape volatility during productive cell migration.

Cells and tissues are constantly exposed to mechanical forces. Understanding how these forces act on cells to regulate essential processes like development, differentiation, tissue homeostasis and how their alteration is related to disease requires the characterization of their mechanical properties. Several methods have been developed to study mechanical properties of cells and nuclei. However, most of the established methods are not com- patible with culturing of cells in 3D substrates, a factor which plays an essential role in defining the structural and mechanical behavior of cells naturally existing in 3D environ- ments. In this work, image and model based methods have been developed to approach this problem and enable the characterization of the cells mechanical phenotype in 3D.
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\nOn a first step, a previously developed method to measure the compressibility of the nuclear interior was enhanced to enable statistical significant measurements of nuclei to perform comparative analyses between phenotypes. Optimization of both the experi- mental, as well as the image processing methods led to a robust framework that served to measure an increase in nuclear compressibility in nuclei of LMNA−/− mouse embryonic fibroblasts. This study served as a proof of principle for this contact free method, which in a subsequent step was adapted to work for cells embedded in 3D substrates.
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\nAiming to develop a method, in which specific forces could be applied and relate to cellular deformations, the second part of this work was centered in the development of the 3D substrate stretcher. This involved identifying and implementing the needs of the experimental and image analysis framework to ensure the required environment for the cells, while at the same time enabling the acquisition of suitable data for the mechanical analysis. The resulting experimental and analysis framework enables for the first time application and quantification of strains on cells embedded in 3D substrates.
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\nMotivation of the 3D-culture based methods was the analysis of epithelial-mesenchymal transition (EMT) in hepatocytes. These epithelial cells undergoing dedifferentiation upon treatment with TGF-β serve not only as a preeminent example of the need of 3D cell cultures in the characterization of mechanical properties, but also as a model of malignant transformation in fibrotic diseases and cancer. Quantification of previously unobserved morphological and structural properties led to the mechanical phenotyping of these cells, where a decrease in the compressibility of the nuclear interior, an enhanced resistance to deformation and a better anchorage of the nuclei inside the cells was observed after EMT.

Plasticity of epithelial cell shape in response to upstream signals: A whole-organism study using transgenic Hydra

3D Microscopy of Rod-Shaped Bacteria Reveals Roles of MreB in Diameter Control and Center-Line Curvature

Self-organized Notch dynamics generate stereotyped sensory organ patterns in Drosophila

Lethal Giant Larvae Acts Together with Numb in Notch Inhibition and Cell Fate Specification in the Drosophila Adult Sensory Organ Precursor Lineage

It has been argued that the cell-cell and cell-matrix interaction networks in normal tissues are disrupted by radiation and that this largely controls many of the most important cellular radiation responses. This has led to the broader assertion that individual cells in normal tissue or a 3D normal-tissue-like culture will respond to radiation very differently than the same cells in a 2D monolayer culture. While many studies have shown that, in some cases, cell-cell contact in spheroids of transformed or tumor cell lines can alter radiation responses relative to those for the same cells in monolayer cultures, a question remains regarding the possible effect of the above-mentioned disruption of signaling networks that operate more specifically for cells in normal tissues or in a 3D tissue-like context. To test the generality of this notion, we used human MCF-10A cells, an immortalized mammary epithelial cell line that produces acinar structures in culture with many properties of human mammary ducts. We compared the dose responses for these cells in the 2D monolayer and in 3D ductal or acinar structures. The responses examined were reproductive cell death, induction of chromosomal aberrations, and the levels of gamma-H2AX foci in cells after single acute gamma-ray doses and immediately after 20 h of irradiation at a dose rate of 0.0017 Gy/min. We found no significant differences in the dose responses of these cells in 2D or 3D growth conditions. While this does not mean that such differences cannot occur in other situations, it does mean that they do not generally or necessarily occur.

BackgroundMany methods have been developed to quantify cell shape in 2D in tissues. For instance, the analysis of epithelial cells in Drosophila embryogenesis or jigsaw puzzle-shaped pavement cells in plant epidermis has led to the development of numerous quantification methods that are applied to 2D images. However, proper extraction of 2D cell contours from 3D confocal stacks for such analysis can be problematic.ResultsWe developed a macro in ImageJ, SurfCut, with the goal to provide a user-friendly pipeline specifically designed to extract epidermal cell contour signals, segment cells in 2D and analyze cell shape. As a reference point, we compared our output to that obtained with MorphoGraphX (MGX). While both methods differ in the approach used to extract the layer of signal, they output comparable results for tissues with shallow curvature, such as pavement cell shape in cotyledon epidermis (as quantified with PaCeQuant). SurfCut was however not appropriate for cell or tissue samples with high curvature, as evidenced by a significant bias in shape and area quantification.ConclusionWe provide a new ImageJ pipeline, SurfCut, that allows the extraction of cell contours from 3D confocal stacks. SurfCut and MGX have complementary advantages: MGX is well suited for curvy samples and more complex analyses, up to computational cell-based modeling on real templates; SurfCut is well suited for rather flat samples, is simple to use, and has the advantage to be easily automated for batch analysis of images in ImageJ. The combination of these two methods thus provides an ideal suite of tools for cell contour extraction in most biological samples, whether 3D precision or high-throughput analysis is the main priority.

In many organs, epithelial cells are polarized not only along the apicobasal axis, but also along a second axis within a plane. Acquisition of the latter polarity, known as planar cell polarity (PCP) or tissue polarity, is crucial for specialized cellular functions. Genetic programming of PCP has been most thoroughly studied in Drosophila, which has allowed identification of a number of regulatory molecules that are evolutionally conserved. One group of the regulators is responsible for interpreting a hypothetical polarity cue and directing local cytoskeletal reorganization. This group includes a seven-pass transmembrane cadherin known as Flamingo (also known as Starry night), other receptors, and downstream components; and many of those molecules are redistributed to restricted subcellular compartments. Recent studies on a trio of cell-surface molecules challenge a previous hypothesis about the identity of the polarity cue and prompt a novel hypothesis about a global input. Studies on vertebrate systems support the notion that the molecular mechanisms demonstrated in Drosophila are applicable to at least two classes of polarized behaviors of vertebrate cells: sensory hair morphogenesis in the inner ear epithelium, and convergent extension movements during gastrulation.

Gap junctional communication in microinjected human limbal and peripheral corneal epithelial cells cultured on intact amniotic membrane

Cell segmentation plays a crucial role in understanding, diagnosing, and treating diseases. Despite the recent success of deep learning-based cell segmentation methods, it remains challenging to accurately segment densely packed cells in 3D cell membrane images. Existing approaches also require fine-tuning multiple manually selected hyperparameters on the new datasets. We develop a deep learning-based 3D cell segmentation pipeline, 3DCellSeg, to address these challenges. Compared to the existing methods, our approach carries the following novelties: (1) a robust two-stage pipeline, requiring only one hyperparameter; (2) a light-weight deep convolutional neural network (3DCellSegNet) to efficiently output voxel-wise masks; (3) a custom loss function (3DCellSeg Loss) to tackle the clumped cell problem; and (4) an efficient touching area-based clustering algorithm (TASCAN) to separate 3D cells from the foreground masks. Cell segmentation experiments conducted on four different cell datasets show that 3DCellSeg outperforms the baseline models on the ATAS (plant), HMS (animal), and LRP (plant) datasets with an overall accuracy of 95.6%, 76.4%, and 74.7%, respectively, while achieving an accuracy comparable to the baselines on the Ovules (plant) dataset with an overall accuracy of 82.2%. Ablation studies show that the individual improvements in accuracy is attributable to 3DCellSegNet, 3DCellSeg Loss, and TASCAN, with the 3DCellSeg demonstrating robustness across different datasets and cell shapes. Our results suggest that 3DCellSeg can serve a powerful biomedical and clinical tool, such as histo-pathological image analysis, for cancer diagnosis and grading.