Region-Based PDEs for Cells Counting and Segmentation in 3D+Time Images of Vertebrate Early Embryogenesis

This paper is devoted to the segmentation of cell nuclei from time lapse confocal microscopy images, taken throughout early Zebrafish embryogenesis. The segmentation allows to identify and quantify the number of cells in the animal model. This kind of information is relevant to estimate important biological parameters such as the cell proliferation rate in time and space. Our approach is based on the active contour model without edges. We compare two different formulations of the model equation and evaluate their performances in segmenting nuclei of different shapes and sizes. Qualitative and quantitative comparisons are performed on both synthetic and real data, by means of suitable gold standard. The best approach is then applied on a number of time lapses for the segmentation and counting of cells during the development of a zebrafish embryo between the sphere and the shield stage

PhOTO Zebrafish: A Transgenic Resource for In Vivo Lineage Tracing during Development and Regeneration

Background: Elucidating the complex cell dynamics (divisions, movement, morphological changes, etc.) underlying embryonic development and adult tissue regeneration requires an efficient means to track cells with high fidelity in space and time. To satisfy this criterion, we developed a transgenic zebrafish line, called PhOTO, that allows photoconvertible optical tracking of nuclear and membrane dynamics in vivo. Methodology: PhOTO zebrafish ubiquitously express targeted blue fluorescent protein (FP) Cerulean and photoconvertible FP Dendra2 fusions, allowing for instantaneous, precise targeting and tracking of any number of cells using Dendra2 photoconversion while simultaneously monitoring global cell behavior and morphology. Expression persists through adulthood, making the PhOTO zebrafish an excellent tool for studying tissue regeneration: after tail fin amputation and photoconversion of a ~100µm stripe along the cut area, marked differences seen in how cells contribute to the new tissue give detailed insight into the dynamic process of regeneration. Photoconverted cells that contributed to the regenerate were separated into three distinct populations corresponding to the extent of cell division 7 days after amputation, and a subset of cells that divided the least were organized into an evenly spaced, linear orientation along the length of the newly regenerating fin. Conclusions/Significance: PhOTO zebrafish have wide applicability for lineage tracing at the systems-level in the early embryo as well as in the adult, making them ideal candidate tools for future research in development, traumatic injury and regeneration, cancer progression, and stem cell behavior

Tissue-level Mechanisms Driving Cardiac Progenitor and Extracellular Matrix Movements during Early Vertebrate Heart Development

Vertebrate cardiogenesis involves heart progenitor cell movements from their initial lateral positions to the embryonic midline, where they assemble into a primitive heart. This early heart tube consists of an outer myocardium, a medial extracellular matrix (ECM), and an endocardial lining. Cardiac morphogenesis in avians and mammals is inseparable from development of the foregut, which provides molecular cues to regulate endocardial and myocardial differentiation from mesodermal progenitors. Concomitantly with the initiation of midline-directed cardiac progenitor movements, foregut endoderm undergoes dramatic folding and elongation. Following their initial assembly, the heart and foregut are transiently connected through a mesentery. Previous research focused on the molecular factors involved in guiding cardiac progenitors to the midline, yet cellular and tissue mechanisms coordinating these movements remain poorly understood. This work investigates movements of all three early heart constituents - the endocardial and myocardial progenitors, and surrounding ECM - in live quail embryos using a combination of time-lapse microscopy, chemical and mechanical perturbations, computational analysis and modeling. By visualizing the tissue environment for cell displacements, we distinguish the active (tissue-independent) movements from those cells undergo in a manner coordinated with the surrounding tissues. First, we analyzed the movements of endocardial progenitors and fluorescently-labeled ECM (fibronectin, fibrillin-2) fibrils. We found the bulk of midline-directed movement of pre-endocardial cells is coordinated with their surrounding ECM. Further, that ECM from extracardiac sources is transferred to and incorporated into the growing heart. By assessing the contributions of active cell motility to the observed midline endocardial displacements we found its role to be secondary to that of convective tissue movement within the anterior embryo. Second, we assessed myocardial progenitor movements relative to fibronectin ECM and endoderm. We discovered that observed antero-medial myocardial displacements are driven by a combination of: 1) medial tissue motion, and 2) anterior movement, accomplished via a coordinated deformation of myocardial progenitors, organized into a continuous epithelial sheet. Finally, we investigated the effects of VEGF overexposure on progenitor movements during early cardiogenesis. We found a dramatic VEGF-induced increase in cardiac inflow region size, which affected the coordinated movements/deformations displayed by myocardial progenitors, and resulted in heart tube elongation defects

New Methods to Improve Large-Scale Microscopy Image Analysis with Prior Knowledge and Uncertainty

Multidimensional imaging techniques provide powerful ways to examine various kinds of scientific questions. The routinely produced datasets in the terabyte-range, however, can hardly be analyzed manually and require an extensive use of automated image analysis. The present thesis introduces a new concept for the estimation and propagation of uncertainty involved in image analysis operators and new segmentation algorithms that are suitable for terabyte-scale analyses of 3D+t microscopy images.Comment: 218 pages, 58 figures, PhD thesis, Department of Mechanical Engineering, Karlsruhe Institute of Technology, published online with KITopen (License: CC BY-SA 3.0, http://dx.doi.org/10.5445/IR/1000057821

Systems Biology Derived Mechanism Of Bmp Gradient Formation

A morphogen gradient of Bone Morphogenetic Protein (BMP) signaling patterns the dorsoventral (DV) axis of all vertebrates. This gradient is established by the extracellular interaction of the asymmetric expression of the BMP ligand and its extracellular regulators. Though the basic agonism and antagonism of BMP by these regulators has been established over the last two decades, the mechanism by which they come together to form a robust BMP signaling gradient remains poorly understood. The prevailing view in vertebrates for BMP gradient formation is through a counter gradient of BMP antagonists, often along with ligand shuttling to generate peak signaling levels. To delineate the mechanism in zebrafish, I created a quantitative method of measuring BMP signaling, and used it to precisely quantify the BMP activity gradient in wild-type and mutant embryos. We combined these data with a computational model-based screen to test hypotheses for gradient formation. Surprisingly, the analysis did not support a counter-gradient mechanism and rules out both a BMP shuttling mechanism, and a bmp transcriptionally-informed gradient mechanism. Instead a fourth model emerged, a source-sink mechanism, which relies on a restricted BMP antagonist distribution acting as a BMP sink that drives BMP diffusion and gradient formation. We measured Bmp2 diffusion and found that it supports the source-sink model, suggesting a new mechanism to shape BMP gradients during development. We have developing a way to quantify the BMP signaling gradient, a mathematical model incorporating the core extracellular BMP regulators, and mathematical definitions for the different gradient mechanisms. In doing so, we have opened the door for future studies to add in additional BMP regulators to the model such as Bmper, Twisted Gastrulation and Sizzled, to identify and measure key biophysical parameters, and to address questions about how cells sense a BMP morphogen gradient and translate that signal into target gene expression

New Methods to Improve Large-Scale Microscopy Image Analysis with Prior Knowledge and Uncertainty

Multidimensional imaging techniques provide powerful ways to examine various kinds of scientific questions. The routinely produced data sets in the terabyte-range, however, can hardly be analyzed manually and require an extensive use of automated image analysis. The present work introduces a new concept for the estimation and propagation of uncertainty involved in image analysis operators and new segmentation algorithms that are suitable for terabyte-scale analyses of 3D+t microscopy images

To what extent is digit patterning a Turing System?

Building precise, robust patterns and structures from an initially homogeneous state is fundamental to developmental biology. Digit patterning is a representative example of a periodic pattern in development. Previous studies have shown that a reaction–diffusion (Turing) system, in which diffusible activators and inhibitors interact, is the most likely explanation of how the spatial pattern of the digits is formed. Although self-organisation mechanisms such as the Turing system successfully recapitulate many aspects of digit patterning, critical questions remain regarding its timing and behaviour. First I addressed the question of timing, or how long reaction-diffusion plays a role in the developing digits. I perturbed the digit patterning process of embryonic limbs by inserting beads that contain morphogens involved in the reaction-diffusion mechanism. Then I quantified the degree of pattern change, or plasticity of the patterning, from limbs harvested at different developmental timing throughout the digit patterning stage. For quantification, I developed a custom image analytic pipeline that extracts relevant topology and represents the difference between perturbed and unperturbed patterns. Modelling the plasticity profile over the digit patterning process, through extensive interplay of experiments and modelling, revealed that plasticity during digit patterning decreases in a sigmoidal manner. Transcriptomics analysis that matches with the sigmoidal decrease observed in expression patterns further identified gene candidates that could be critical to the digit patterning. Further, the timing of reaction-diffusion is discussed in the context of the tissue movements, revealing that Sox9 digit patterning happens significantly earlier than cell density changes. The second part aims at improving our understanding about which pathways and components of the pathways are involved in the digit forming Turing network. Previously identified digit patterning Turing network, such as BSW model, abstracts the entire Wnt and Bmp signalling pathways’ activities into each node. Thus there is insufficient knowledge on the mechanistic role of Wnt signalling mediated Sox9 repression. To further clarify detailed mechanisms of the Turing network, I used an unbiased screening approach to systematically perturb digit patterning using small molecule inhibitors, ligands, and peptides at different doses in systems such as limb culture and micromass. Out of multiple steps critical to Wnt signalling, including Wnt production, Wnt receptor interaction, Wnt canonical pathway cytosolic interactions, and Wnt canonical pathway transcriptional interactions, I identified that inhibition of Wnt production and Wnt transcriptional component inhibition category most effectively disrupt digit patterning. I also identified candidate ligands such as sFRP1 and Dkk1 as potential extracellular Wnt inhibitors that effectively change digit patterning upon application. These results provide the first quantitative insight into the duration of the reaction-diffusion based mechanism in a biological system, and how a screening approach complemented with data driven modelling can complement and clarify workings of a reaction diffusion based system. Further work in improving our knowledge on the Turing system with tissue growth, cell movements, and ectodermal-mesenchymal interaction will eventually allow generation of a complete organogenesis simulation model

Quantifying and perturbing the movement of extracellular proteins in zebrafish embryos

Cell-cell communication mediated by secreted signaling molecules is crucial to coordinate early embryonic development. In the classical morphogen model secreted signaling molecules control embryogenesis as follows: After secretion from a source they disperse in the tissue and instruct target cells at a distance to adopt different cell fates that are defined by signaling levels. Thus, the signal’s distribution controls the cellular patterning of the tissue. However, the mechanisms underlying signal distribution in vivo and the requirement for signals acting at a distance remain controversial. Nodals are extracellular signaling molecules of the Transforming growth factor-β (TGF-β) superfamily and are required for mesoderm and endoderm formation in vertebrates. In the zebrafish Danio rerio, Nodals were proposed to function as classical morphogens that disperse from localized Nodal-secreting cells to act on distant cells. However, recent findings suggest that Nodals signal only to neighboring cells and that their signaling is propagated to distant cells by a combination of auto-induction and cell-to-cell signal relay, thus challenging the classical morphogen model. To directly test the two models of Nodal signaling I performed in vivo experiments to observe the endogenous Nodal signaling range. My results suggest that zebrafish Nodals can signal directly – i.e. without relay – to cells at a distance from their source. However, the importance of Nodal dispersal for its function during embryonic patterning remains to be determined. The morphogen model predicts that an altered signal dispersal leads to an altered signaling range and aberrant tissue patterning. To examine whether extracellular signal movement is required for the signal’s biological function, tools that restrict extracellular signal mobility are needed. Recently developed synthetic signal binders can be used to reversibly tether extracellular signals to the cell membrane and perturb signal spreading. I investigated how the transient membrane-tethering can be harnessed to experimentally reduce the effective diffusivity of extracellular proteins and thus regulate their mobility in a tuned manner. This approach allowed me to hinder the diffusion of the long-range Nodal inhibitor Lefty1 and investigate its long-range function in live zebrafish embryos. In zebrafish, Nodals have lower effective diffusion coefficients and a shorter range than their antagonists, the long-range Leftys. To explain the contrasting mobilities of these two TGF-β-related factors that are similar in molecular weight, binding partners in the extracellular matrix were proposed to act as diffusion regulators. My aim was to reveal these hypothetical diffusion regulators. I established a co-immunoprecipitation approach for zebrafish Nodals and Leftys and identified putative interaction partners by mass spectrometry. Surprisingly, known Nodal interaction partners were not identified as diffusion regulators with this approach, raising the possibility that other factors regulate the Nodal/Lefty system. In my work I investigated extracellular signal movement and focused on its modulation by diffusion regulators. My findings highlight that synthetic membrane tethers can be used as experimental diffusion regulators and that they serve as valuable tools to challenge models of long-range morphogen function

New Methods to Improve Large-Scale Microscopy Image Analysis with Prior Knowledge and Uncertainty

Multidimensional imaging techniques provide powerful ways to examine various kinds of scientific questions. The routinely produced data sets in the terabyte-range, however, can hardly be analyzed manually and require an extensive use of automated image analysis. The present work introduces a new concept for the estimation and propagation of uncertainty involved in image analysis operators and new segmentation algorithms that are suitable for terabyte-scale analyses of 3D+t microscopy images