Global morphogenetic flow is accurately predicted by the spatial distribution of myosin motors.

During embryogenesis tissue layers undergo morphogenetic flow rearranging and folding into specific shapes. While developmental biology has identified key genes and local cellular processes, global coordination of tissue remodeling at the organ scale remains unclear. Here, we combine in toto light-sheet microscopy of the Drosophila embryo with quantitative analysis and physical modeling to relate cellular flow with the patterns of force generation during the gastrulation process. We find that the complex spatio-temporal flow pattern can be predicted from the measured meso-scale myosin density and anisotropy using a simple, effective viscous model of the tissue, achieving close to 90% accuracy with one time dependent and two constant parameters. Our analysis uncovers the importance of a) spatial modulation of myosin distribution on the scale of the embryo and b) the non-locality of its effect due to mechanical interaction of cells, demonstrating the need for the global perspective in the study of morphogenetic flow

On biophysical aspects of growth and dynamics of epithelial tissues

A fundamental and unresolved question of life is how organs are formed. The shape and form of organs emerges by spatio temporally controlled division and motility of cells. As both processes are tightly coordinated, interactions amongst cells are required to ensure stability and integrity. Many genetic networks controlling the polarised cell motility or promoting cell division have been identified. Action between cells results in an increased complexity. Yet cells give rise to regular patterned organs. The form of objects and their motion is subject to physical laws. Cells are of an active character, divide and move, interesting properties for a material, with potentially new knowledge emerging from their study. Here, we perform a quantitative characterisation of two experimental models for tissue morphogenesis. Using cultured epithelial sheets we address the mechanical properties of growth control and identify regulatory mechanisms. Based on this study, we propose a phenomenological description of tissue dynamics, reproducing the observed data. Using the methods developed to understand the cultured sheet, we approach the role of mechanics in the migration of an embryonic tissue. We measure the directed motion of the tissue and show that the findings can be reproduced by coupling the biophysical model of motile cells to a dynamically regulated polarisation mechanism.Formgebung von Organen ist ein grundlegendes, ungelöstes Problem des Lebens. Ihre Gestalt resultiert aus raumzeitlich kontrollierten Zellteilungen sowie Bewegungen von Zellen. Um mechanische Stabilität sowie Integrität des Gewebes zu gewährleisten, werden Zell-Zell Wechselwirkungen benötigt. Viele genetische Netzwerke kontrollieren die polarisierte Zellbeweglichkeit oder fördern die Zellteilung. Interaktion zwischen Zellen führt zu einer erhöhten Komplexität. Dennoch bilden sich reguläre Muster. Die Form von Objekten und deren Bewegung unterliegt physikalischen Gesetzen. Zellen sind von aktiver Art, teilen und bewegen sich, interessante Eigenschaften für ein Material, welche in neuen Erkenntnissen münden könnten. In dieser Arbeit führen wir eine quantitative Charakterisierung von zwei Modellsystemen der Morphogenese von Geweben durch. Anhand von kultivierten Epithelien behandeln wir die mechanischen Eigenschaften der Wachstumskontrolle und identifizieren Regulationsmechanismen. Darauf aufbauend, schlagen wir eine phänomenologische Modellbeschreibung für Gewebedynamik vor, welche die Beobachtungen reproduziert. Wir machen Gebrauch von diesen Methoden um die Mechanik der Migration eines embryonalen Epithels zu verstehen. Dabei messen wir die gerichtete Bewegung des Gewebes und zeigen, dass die resultierenden Daten durch Kopplung der biophysikalischen Motilitätsbeschreibung an einen dynamisch regulierten Polarisationsmechanismus reproduziert werden

Identification of a neural crest stem cell niche by Spatial Genomic Analysis

The neural crest is an embryonic population of multipotent stem cells that form numerous defining features of vertebrates. Due to lack of reliable techniques to perform transcriptional profiling in intact tissues, it remains controversial whether the neural crest is a heterogeneous or homogeneous population. By coupling multiplex single molecule fluorescence in situ hybridization with machine learning algorithm based cell segmentation, we examine expression of 35 genes at single cell resolution in vivo. Unbiased hierarchical clustering reveals five spatially distinct subpopulations within the chick dorsal neural tube. Here we identify a neural crest stem cell niche that centers around the dorsal midline with high expression of neural crest genes, pluripotency factors, and lineage markers. Interestingly, neural and neural crest stem cells express distinct pluripotency signatures. This Spatial Genomic Analysis toolkit provides a straightforward approach to study quantitative multiplex gene expression in numerous biological systems, while offering insights into gene regulatory networks via synexpression analysis

Multiscale mechanisms of cell migration during development: theory and experiment

Long-distance cell migration is an important feature of embryonic development, adult morphogenesis and cancer, yet the mechanisms that drive subpopulations of cells to distinct targets are poorly understood. Here, we use the embryonic neural crest (NC) in tandem with theoretical studies to evaluate model mechanisms of long-distance cell migration. We find that a simple chemotaxis model is insufficient to explain our experimental data. Instead, model simulations predict that NC cell migration requires leading cells to respond to long-range guidance signals and trailing cells to short-range cues in order to maintain a directed, multicellular stream. Experiments confirm differences in leading versus trailing NC cell subpopulations, manifested in unique cell orientation and gene expression patterns that respond to non-linear tissue growth of the migratory domain. Ablation experiments that delete the trailing NC cell subpopulation reveal that leading NC cells distribute all along the migratory pathway and develop a leading/trailing cellular orientation and gene expression profile that is predicted by model simulations. Transplantation experiments and model predictions that move trailing NC cells to the migratory front, or vice versa, reveal that cells adopt a gene expression profile and cell behaviors corresponding to the new position within the migratory stream. These results offer a mechanistic model in which leading cells create and respond to a cell-induced chemotactic gradient and transmit guidance information to trailing cells that use short-range signals to move in a directional manner

Identification of a neural crest stem cell niche by Spatial Genomic Analysis

The neural crest is an embryonic population of multipotent stem cells that form numerous defining features of vertebrates. Due to lack of reliable techniques to perform transcriptional profiling in intact tissues, it remains controversial whether the neural crest is a heterogeneous or homogeneous population. By coupling multiplex single molecule fluorescence in situ hybridization with machine learning algorithm based cell segmentation, we examine expression of 35 genes at single cell resolution in vivo. Unbiased hierarchical clustering reveals five spatially distinct subpopulations within the chick dorsal neural tube. Here we identify a neural crest stem cell niche that centers around the dorsal midline with high expression of neural crest genes, pluripotency factors, and lineage markers. Interestingly, neural and neural crest stem cells express distinct pluripotency signatures. This Spatial Genomic Analysis toolkit provides a straightforward approach to study quantitative multiplex gene expression in numerous biological systems, while offering insights into gene regulatory networks via synexpression analysis