E-cadherin expression pattern during zebrafish embryonic epidermis development [version 1; referees: 1 approved, 2 approved with reservations]

Background: E-cadherin is the major adhesion receptor in epithelial adherens junctions (AJs). On established epidermis, E-cadherin performs fine-tuned cell-cell contact remodeling to maintain tissue integrity, which is characterized by modulation of cell shape, size and packing density. In zebrafish, the organization and distribution of E-cadherin in AJs during embryonic epidermis development remain scarcely described. Methods: Combining classical immunofluorescence, deconvolution microscopy and 3D-segmentation of AJs in epithelial cells, a quantitative approach was implemented to assess the spatial and temporal distribution of E-cadherin across zebrafish epidermis between 24 and 72 hpf. Results: increasing levels of E-cadh protein parallel higher cell density and the appearance of hexagonal cells in the enveloping layer (EVL) as well as the establishments of new cell-cell contacts in the epidermal basal layer (EBL), being significantly between 31 and 48 hpf. Conclusions: Increasing levels of E-cadherin in AJs correlates with extensive changes in cell morphology towards hexagonal packing during the epidermis morphogenesis

Segmentation and Tracking of Adherens Junctions in 3D for the Analysis of Epithelial Tissue Morphogenesis

<div><p>Epithelial morphogenesis generates the shape of tissues, organs and embryos and is fundamental for their proper function. It is a dynamic process that occurs at multiple spatial scales from macromolecular dynamics, to cell deformations, mitosis and apoptosis, to coordinated cell rearrangements that lead to global changes of tissue shape. Using time lapse imaging, it is possible to observe these events at a system level. However, to investigate morphogenetic events it is necessary to develop computational tools to extract quantitative information from the time lapse data. Toward this goal, we developed an image-based computational pipeline to preprocess, segment and track epithelial cells in 4D confocal microscopy data. The computational pipeline we developed, for the first time, detects the adherens junctions of epithelial cells in 3D, without the need to first detect cell nuclei. We accentuate and detect cell outlines in a series of steps, symbolically describe the cells and their connectivity, and employ this information to track the cells. We validated the performance of the pipeline for its ability to detect vertices and cell-cell contacts, track cells, and identify mitosis and apoptosis in surface epithelia of <i>Drosophila</i> imaginal discs. We demonstrate the utility of the pipeline to extract key quantitative features of cell behavior with which to elucidate the dynamics and biomechanical control of epithelial tissue morphogenesis. We have made our methods and data available as an open-source multiplatform software tool called TTT (<a href="http://github.com/morganrcu/TTT" target="_blank">http://github.com/morganrcu/TTT</a>)</p></div

Modélisation multi-échelle de la morphogenèse : transmission et canalisation des forces au cours de l'invagination épithéliale

La morphogenèse regroupe les évènements conduisant aux modifications de forme d'un organisme. Ces modifications tissulaires reposent sur le réarrangement et le changement de forme des cellules, orchestrés par des interactions entre forces mécaniques et signalisations chimiques pour permettre la formation de différents tissus avec des fonctions diverses. Les modèles vertex jouent un rôle important dans l'étude des mécanismes morphogénétiques. Ils permettent d'aborder certaines questions qu'il n'est pas toujours possible de tester in vivo du fait de limitations techniques. Ils peuvent aussi avoir un rôle prédictif sur le comportement d'un tissu. J'ai participé au développement d'une bibliothèque de modélisation appelée Tyssue, proposant différents modules afin de donner la possibilité à des biologistes de créer leur propre modèle avec une dynamique adaptée qui lui est propre. J'ai également travaillé sur deux modèles morphogénétiques de formation de plis différents chez la drosophile : l'invagination du mésoderme dans l'embryon et la formation des plis dans le disque imaginal de patte. Par une combinaison d'approches expérimentales et de modélisation, nous avons pu mettre en avant différents mécanismes dans la formation des plis. Tout d'abord, nous avons caractérisé le rôle des différentes forces (apicale et apico-basale) et testé leur importance dans la formation de l'invagination du mésoderme. Puis nous avons pu montrer que la canalisation des forces repose sur une polarité de tension dans les cellules du futur pli, ce qui permet une transmission préférentielle des forces dans la direction du pli. Au cours de la formation du pli, les forces se transmettent d'une cellule à ses voisines ce qui propage une déformation à l'échelle du tissu. Je me suis intéressée à la modélisation de cette réponse mécanique des cellules au cours de la transmission des forces. Enfin, j'ai travaillé sur le développement d'un programme de segmentation de surface apicale de cellule en 3D, afin de pouvoir réaliser des analyses morphologiques de surface apicale de cellule dans un tissu 3D. L'ensemble de ces différents projets ont permis de mieux comprendre les mécanismes fondamentaux gouvernant la mécanique des tissus lors de leur remodelage.Morphogenesis includes all the events driving changes in the shape of an organism. Tissue modifications are based on cell rearrangement and cell shape changes, which are orchestrated by interactions between mechanical forces and chemical signals to allow the formation of different tissues with various functions. Vertex models play an important role in the study of morphogenetic mechanisms. They make it possible to address certain questions that are not always possible to test in vivo due to technical limitations. They can also have a predictive role on the behaviour of a tissue. I participated in the development of a modelling library called Tyssue, offering different modules in order to give the possibility to biologists to create their own model with its own dynamics. I have also worked on two morphogenetic models of fold formation in Drosophila: mesoderm invagination in the embryo and fold formation in the leg imaginal disc. I characterised the role of the different forces (apical and apico-basal) and tested their importance in the formation of mesoderm invagination. Then, I became interested in a force channelling mechanism ensuring the robustness of fold formation in the leg imaginal disc. By a combination of experimental and modelling approaches, we were able to show that the channelling of these forces is driven by the polarity of cells from the future fold, which allows preferential transmission in the direction of the fold. During the formation of the fold, forces are transmitted from one cell to its neighbours, which propagates a deformation throughout the tissue. I am interested in modelling this mechanical response of cells during force transmission. Finally, I worked on the development of a 3D apical cell surface segmentation program, in order to perform morphological analysis of the apical cell surface in 3D tissue. All of these different projects have made it possible to better understand the fundamental mechanisms governing the mechanics of tissues during their remodelling

Towards Accurate and Efficient Cell Tracking During Fly Wing Development

Understanding the development, organization, and function of tissues is a central goal in developmental biology. With modern time-lapse microscopy, it is now possible to image entire tissues during development and thereby localize subcellular proteins. A particularly productive area of research is the study of single layer epithelial tissues, which can be simply described as a 2D manifold. For example, the apical band of cell adhesions in epithelial cell layers actually forms a 2D manifold within the tissue and provides a 2D outline of each cell. The Drosophila melanogaster wing has become an important model system, because its 2D cell organization has the potential to reveal mechanisms that create the final fly wing shape. Other examples include structures that naturally localize at the surface of the tissue, such as the ciliary components of planarians. Data from these time-lapse movies typically consists of mosaics of overlapping 3D stacks. This is necessary because the surface of interest exceeds the field of view of todays microscopes. To quantify cellular tissue dynamics, these mosaics need to be processed in three main steps: (a) Extracting, correcting, and stitching individ- ual stacks into a single, seamless 2D projection per time point, (b) obtaining cell characteristics that occur at individual time points, and (c) determine cell dynamics over time. It is therefore necessary that the applied methods are capable of handling large amounts of data efficiently, while still producing accurate results. This task is made especially difficult by the low signal to noise ratios that are typical in live-cell imaging. In this PhD thesis, I develop algorithms that cover all three processing tasks men- tioned above and apply them in the analysis of polarity and tissue dynamics in large epithelial cell layers, namely the Drosophila wing and the planarian epithelium. First, I introduce an efficient pipeline that preprocesses raw image mosaics. This pipeline accurately extracts the stained surface of interest from each raw image stack and projects it onto a single 2D plane. It then corrects uneven illumination, aligns all mosaic planes, and adjusts brightness and contrast before finally stitching the processed images together. This preprocessing does not only significantly reduce the data quantity, but also simplifies downstream data analyses. Here, I apply this pipeline to datasets of the developing fly wing as well as a planarian epithelium. I additionally address the problem of determining cell polarities in chemically fixed samples of planarians. Here, I introduce a method that automatically estimates cell polarities by computing the orientation of rootlets in motile cilia. With this technique one can for the first time routinely measure and visualize how tissue polarities are established and maintained in entire planarian epithelia. Finally, I analyze cell migration patterns in the entire developing wing tissue in Drosophila. At each time point, cells are segmented using a progressive merging ap- proach with merging criteria that take typical cell shape characteristics into account. The method enforces biologically relevant constraints to improve the quality of the resulting segmentations. For cases where a full cell tracking is desired, I introduce a pipeline using a tracking-by-assignment approach. This allows me to link cells over time while considering critical events such as cell divisions or cell death. This work presents a very accurate large-scale cell tracking pipeline and opens up many avenues for further study including several in-vivo perturbation experiments as well as biophysical modeling. The methods introduced in this thesis are examples for computational pipelines that catalyze biological insights by enabling the quantification of tissue scale phenomena and dynamics. I provide not only detailed descriptions of the methods, but also show how they perform on concrete biological research projects