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Decades of research have not yet fully explained the mechanisms of epithelial self-organization and 3D packing. Single-cell analysis of large 3D epithelial libraries is crucial for understanding the assembly and function of whole tissues. Combining 3D epithelial imaging with advanced deep-learning segmentation methods is essential for enabling this high-content analysis. We introduce CartoCell, a deep-learning-based pipeline that uses small datasets to generate accurate labels for hundreds of whole 3D epithelial cysts. Our method detects the realistic morphology of epithelial cells and their contacts in the 3D structure of the tissue. CartoCell enables the quantification of geometric and packing features at the cellular level. Our single-cell cartography approach then maps the distribution of these features on 2D plots and 3D surface maps, revealing cell morphology patterns in epithelial cysts. Additionally, we show that CartoCell can be adapted to other types of epithelial tissues.

Surface curvature both emerges from, and influences the behavior of, living objects at length scales ranging from cell membranes to single cells to tissues and organs. The relevance of surface curvature in biology is supported by numerous experimental and theoretical investigations in recent years. In this review, first, a brief introduction to the key ideas of surface curvature in the context of biological systems is given and the challenges that arise when measuring surface curvature are discussed. Giving an overview of the emergence of curvature in biological systems, its significance at different length scales becomes apparent. On the other hand, summarizing current findings also shows that both single cells and entire cell sheets, tissues or organisms respond to curvature by modulating their shape and their migration behavior. Finally, the interplay between the distribution of morphogens or micro-organisms and the emergence of curvature across length scales is addressed with examples demonstrating these key mechanistic principles of morphogenesis. Overall, this review highlights that curved interfaces are not merely a passive by-product of the chemical, biological, and mechanical processes but that curvature acts also as a signal that co-determines these processes.

Surface curvature both emerges from, and influences the behavior of, living objects at length scales ranging from cell membranes to single cells to tissues and organs. The relevance of surface curvature in biology is supported by numerous experimental and theoretical investigations in recent years. In this review, first, a brief introduction to the key ideas of surface curvature in the context of biological systems is given and the challenges that arise when measuring surface curvature are discussed. Giving an overview of the emergence of curvature in biological systems, its significance at different length scales becomes apparent. On the other hand, summarizing current findings also shows that both single cells and entire cell sheets, tissues or organisms respond to curvature by modulating their shape and their migration behavior. Finally, the interplay between the distribution of morphogens or micro-organisms and the emergence of curvature across length scales is addressed with examples demonstrating these key mechanistic principles of morphogenesis. Overall, this review highlights that curved interfaces are not merely a passive by-product of the chemical, biological, and mechanical processes but that curvature acts also as a signal that co-determines these processes.

Surface curvature both emerges from, and influences the behavior of, living objects at length scales ranging from cell membranes to single cells to tissues and organs. The relevance of surface curvature in biology is supported by numerous experimental and theoretical investigations in recent years. In this review, first, a brief introduction to the key ideas of surface curvature in the context of biological systems is given and the challenges that arise when measuring surface curvature are discussed. Giving an overview of the emergence of curvature in biological systems, its significance at different length scales becomes apparent. On the other hand, summarizing current findings also shows that both single cells and entire cell sheets, tissues or organisms respond to curvature by modulating their shape and their migration behavior. Finally, the interplay between the distribution of morphogens or micro-organisms and the emergence of curvature across length scales is addressed with examples demonstrating these key mechanistic principles of morphogenesis. Overall, this review highlights that curved interfaces are not merely a passive by-product of the chemical, biological, and mechanical processes but that curvature acts also as a signal that co-determines these processes.

In recent years, technological advances in microscopy have made available large amounts of data to biomedical researchers in the form of images. By learning from such large datasets, deep learning-based methods have successfully addressed previously inaccessible bioimage analysis tasks. However, most available solutions target a particular subset of problems, forcing users to be familiarized with different applications to complete their data analysis. On top of that, other issues, such as reproducibility, lack of documentation, or access to the code, arise. For these reasons, we introduce BiaPy, an open-source ready-to-use all-in-one library that provides deep-learning workflows for a large variety of bioimage analysis tasks, including 2D and 3D semantic and instance segmentation, object detection, super-resolution, denoising, self-supervised learning, and classification. All code and documentation are publicly available at https://github.com/danifranco/BiaPy.

Self-organization is an all-important feature of living systems that provides the means to achieve specialization and functionality at distinct spatio-temporal scales. Herein, we review this concept by addressing the packing organization of cells, the sorting/compartmentalization phenomenon of cell populations, and the propagation of organizing cues at the tissue level through traveling waves. We elaborate on how different theoretical models and tools from Topology, Physics, and Dynamical Systems have improved the understanding of self-organization by shedding light on the role played by mechanics as a driver of morphogenesis. Altogether, by providing a historical perspective, we show how ideas and hypotheses in the field have been revisited, developed, and/or rejected and what are the open questions that need to be tackled by future research.

Understanding the cellular organization of tissues is key to developmental biology. In order to deal with this complex problem, researchers have taken advantage of reductionist approaches to reveal fundamental morphogenetic mechanisms and quantitative laws. For epithelia, their two-dimensional representation as polygonal tessellations has proved successful for understanding tissue organization. Yet, epithelial tissues bend and fold to shape organs in three dimensions. In this context, epithelial cells are too often simplified as prismatic blocks with a limited plasticity. However, there is increasing evidence that a realistic approach, even from a reductionist perspective, must include apico-basal intercalations (i.e. scutoidal cell shapes) for explaining epithelial organization convincingly. Here, we present an historical perspective about the tissue organization problem. Specifically, we analyze past and recent breakthroughs, and discuss how and why simplified, but realistic, in silico models require scutoidal features to address key morphogenetic events.

The human Alzheimer’s disease (AD) brain accumulates angiogenic markers but paradoxically, the cerebral microvasculature is reduced around Aß plaques. Here we demonstrate that angiogenesis is started near Aß plaques in both AD mouse models and human AD samples. However, endothelial cells express the molecular signature of non-productive angiogenesis (NPA) and accumulate, around Aß plaques, a tip cell marker and IB4 reactive vascular anomalies with reduced NOTCH activity. Notably, NPA induction by endothelial loss of presenilin, whose mutations cause familial AD and which activity has been shown to decrease with age, produced a similar vascular phenotype in the absence of Aß pathology. We also show that Aß plaque-associated NPA locally disassembles blood vessels, leaving behind vascular scars, and that microglial phagocytosis contributes to the local loss of endothelial cells. These results define the role of NPA and microglia in local blood vessel disassembly and highlight the vascular component of presenilin loss of function in AD.

As animals develop, the initial simple planar epithelia of the early embryos must acquire complex three-dimensional architectures to form the final functional tissues of the organism. Epithelial bending is, therefore, a general principle of all developing systems. Scholarly publications depict epithelial cells as prisms where their basal and apical faces resemble polygons with the same number of sides. The accepted view is that, when a tissue bend, the cells of the epithelia modify their shape from columnar to what has been traditionally called “bottle shape”. However, the morphology and packing of curved epithelia remain largely unknown. Here, through mathematical and computational modelling, we show that cells in bent epithelia necessarily undergo intercalations along the apico-basal axis. This event forces cells to exchange their neighbours between their basal and apical surfaces. Therefore, the traditional view of epithelial cells as simple prisms is incompatible with this phenomenon. Consequently, epithelial cells are compelled to adopt a novel geometrical shape that we have named “scutoid”. The in-depth analysis of diverse epithelial tissues and organs confirm the generation of apico-basal transitions among cell during morphogenesis. Using biophysics arguments, we determine that scutoids support the energetic minimization on the tissue and conclude that the transitions along the apico-basal axis stabilize the threedimensional packing of the tissue. Altogether, we argue that scutoids are nature’s solution to bend efficiently epithelia, and the missing piece for developing a unifying and realistic model of epithelial architecture.

[EN] Solid tumours and their tumour microenvironment (TME) can be considered as complex networks whose elements are in constant physical stress. All the elements of the TME, including tumour cells, stromal cells, immune and stem cells, blood/lymphatic vessels, nerve fibers and extracellular matrix components, belong to a highly balanced compressiontension molecular and cellular structure. Through mechanical signals, each element could affect its surroundings modulating tumour growth and migration. The analysis of these complex interactions and the understanding of the structural organization of a tumour requires the collaboration of different disciplines. In this thesis, we focus on a particular solid tumour: Neuroblastoma, a rare type of cancer, originated during the embryo development. We apply computational and mathematical tools to analyse the topology of vitronectin, a glycoprotein of the extracellular matrix, in neuroblastoma tumours. Vitronectin has a particular interest in tumour biology where it is associated with cell migration, angiogenesis, and matrix degradation. Still, its role in Neuroblastoma is not clear. Here, we study the organization of vitronectin within the TME considering Neuroblastoma patient prognosis and tumoral aggressiveness. Combing graph theory and image analysis, we characterize histopathological images taken, from a human sample, by analysing different topological features that capture the organizational cues of vitronectin. By means of statistical analyses, we find that two topological features (Euler number and branching), related to the organization of the existing vitronectin within and surrounding the cells (territorial), correlates with risk pre-stratification group and genetic instability criterion. We interpret that a large amount of recently synthesized VN would create tracks to aid malignant neuroblasts to invade other organs, pinpointed by both topological features, which in turn would change, dramatically, the constitution, [ES] Los tumores sólidos y su microambiente tumoral (TME) pueden ser vistos como redes complejas cuyos elementos están en constante estrés físico. Todos los elementos del TME, incluidas células tumorales, células del estroma, células inmunes y células troncales, vasos sanguíneos o linfáticos, fibras nerviosas y componentes de la matriz extracelular, pertenecen a una maquinaria molecular y celular de tensión-compresión altamente equilibrada. A través de señales mecánicas, cada elemento podría afectar su entorno modulando el crecimiento tumoral y la migración. El análisis de estas interacciones complejas y la comprensión de la organización estructural de un tumor requiere la colaboración de diferentes disciplinas. En esta tesis, nos centramos en un tumor sólido particular: el neuroblastoma, un cáncer considerado como ‘raro’, que se origina durante el desarrollo del embrión. Aplicando herramientas computacionales y matemáticas, analizamos la topología de la vitronectina, una glicoproteína de la matriz extracelular, en tumores de neuroblastoma. La vitronectina tiene un interés particular en la biología tumoral, ya que está asociada con migración celular, angiogénesis y degradación de la propia matriz. Aún así, su papel en el neuroblastoma no está claro. En este trabajo, estudiamos la organización de la vitronectina dentro del microambiente tumoral, considerando el pronóstico del paciente con neuroblastoma y su agresividad tumoral. Combinando la teoría de gráficos y el análisis de imagen, caracterizamos las imágenes histopatológicas tomadas de una muestra humana, mediante el análisis de diferentes características topológicas que capturan la organización de la vitronectina. Mediante análisis estadísticos, encontramos que dos características topológicas (número de Euler y ‘ramificación’), relacionadas con la organización de la vitronectina existente dentro y alrededor de las células (territorial), se correlacionan con el grupo de pre-estratificación de riesgo y la inestabi

Tumors are complex networks of constantly interacting elements: tumor cells, stromal cells, immune and stem cells, blood/lympathic vessels, nerve fibers and extracellular matrix components. These elements can influence their microenvironment through mechanical and physical signals to promote tumor cell growth. To get a better understanding of tumor biology, cooperation between multidisciplinary fields is needed. Diverse mathematic computations and algorithms have been designed to find prognostic targets and enhance diagnostic assessment. In this work, we use computational digital tools to study the topology of vitronectin, a glycoprotein of the extracellular matrix. Vitronectin is linked to angiogenesis and migration, two processes closely related to tumor cell spread. Here, we investigate whether the distribution of this molecule in the tumor stroma may confer mechanical properties affecting neuroblastoma aggressiveness. Combining image analysis and graph theory, we analyze different topological features that capture the organizational cues of vitronectin in histopathological images taken from human samples. We find that the Euler number and the branching of territorial vitronectin, two topological features, could allow for a more precise pretreatment risk stratification to guide treatment strategies in neuroblastoma patients. A large amount of recently synthesized VN would create migration tracks, pinpointed by both topological features, for malignant neuroblasts, so that dramatic change in the extracellular matrix would increase tumor aggressiveness and worsen patient outcomes.

Here we present EpiGraph, an image analysis tool that quantifies epithelial organization. Our method combines computational geometry and graph theory to measure the degree of order of any packed tissue. EpiGraph goes beyond the traditional polygon distribution analysis, capturing other organizational traits that improve the characterization of epithelia. EpiGraph can objectively compare the rearrangements of epithelial cells during development and homeostasis to quantify how the global ensemble is affected. Importantly, it has been implemented in the open-access platform Fiji. This makes EpiGraph very user friendly, with no programming skills required.

As animals develop, tissue bending contributes to shape the organs into complex three-dimensional structures. However, the architecture and packing of curved epithelia remains largely unknown. Here we show by means of mathematical modelling that cells in bent epithelia can undergo intercalations along the apico-basal axis. This phenomenon forces cells to have different neighbours in their basal and apical surfaces. As a consequence, epithelial cells adopt a novel shape that we term ¿scutoid¿. The detailed analysis of diverse tissues confirms that generation of apico-basal intercalations between cells is a common feature during morphogenesis. Using biophysical arguments, we propose that scutoids make possible the minimization of the tissue energy and stabilize three-dimensional packing. Hence, we conclude that scutoids are one of nature's solutions to achieve epithelial bending. Our findings pave the way to understand the three-dimensional organization of epithelial organs.