The cell is the central functional unit of life. Cell behaviors, such as cell division, movements, differentiation, cell death as well as cell shape and size changes, determine how tissues change shape and grow during regeneration and development. However, a generally applicable framework to measure and describe the behavior of the multitude of cells in a developing tissue is still lacking. Furthermore, the specific contribution of individual cell behaviors, and how exactly these cell behaviors collectively lead to the morphogenesis and growth of tissues are not clear for many developmental and regenerative processes. A promising strategy to fill these gaps is the continuing effort of making developmental biology a quantitative science. Recent advances in methods, especially in imaging, enable measurements of cell behaviors and tissue shapes in unprecedented detail and accuracy. Consequently, formalizing hypotheses in terms of mathematical models to obtain testable quantitative predictions is emerging as a powerful tool. Tests of the hypotheses involve the comparison of model predictions to experimentally observed data. The available data is often noisy and based on only few samples. Hence, this comparison of data and model predictions often requires very careful use of statistical inference methods. If one chooses this quantitative approach, the challenges are the choice of observables, i.e. what to measure, and the design of appropriate data-driven models to answer relevant questions. In this thesis, I applied this data-driven modeling approach to vertebrate morphogenesis, growth and regeneration. In particular, I study spinal cord and muscle regeneration in axolotl, muscle development in zebrafish, and neuron development and maintenance in the adult human brain. To do so, I analyzed images to quantify cell behaviors and tissue shapes. Especially for cell behaviors in post-embryonic tissues, measurements of some cell behavior parameters, such as the proliferation rate, could not be made directly. Hence, I developed mathematical models that are specifically designed to infer these parameters from indirect experimental data. To understand how cell behaviors shape tissues, I developed mechanistic models that causally connect the cell and tissue scales. Specifically, I first investigated the behaviors of neural stem cells that underlie the regenerative outgrowth of the spinal cord after tail amputation in the axolotl. To do so, I quantified all relevant cell behaviors. A detailed analysis of the proliferation pattern in space and time revealed that the cell cycle is accelerated between 3-4 days after amputation in a high-proliferation zone, initially spanning from 800 µm anterior to the amputation plane. The activation of quiescent stem cells and cell movements into the high-proliferation zone also contribute to spinal cord growth but I did not find contributions by cellular rearrangements or cell shape changes. I developed a mathematical model of spinal cord outgrowth involving all contributing cell behaviors which revealed that the acceleration of the cell cycle is the major driver of spinal cord outgrowth. To compare the behavior of neural stem cells with cell behaviors in the regenerating muscle tissue that surrounds the spinal cord, I also quantified proliferation of mesenchymal progenitor cells and found similar proliferation parameters. I showed that the zone of mesenchymal progenitors that gives rise to the regenerating muscle segments is at least 350 µm long, which is consistent with the length of the high-proliferation zone in the spinal cord. Second, I investigated shape changes in developing zebrafish muscle segments by quantifying time-lapse movies of developing zebrafish embryos. These data challenged or ruled out a number of previously proposed mechanisms. Motivated by reported cellular behaviors happening simultaneously in the anterior segments, I had previously proposed the existence of a simple tension-and-resistance mechanism that shapes the muscle segments. Here, I could verify the predictions of this mechanism for the final segment shape pattern. My results support the notion that a simple physical mechanism suffices to self-organize the observed spatiotemporal pattern in the muscle segments. Third, I corroborated and refined previous estimates of neuronal cell turnover rates in the adult human hippocampus. Previous work approached this question by combining quantitative data and mathematical modeling of the incorporation of the carbon isotope C-14. I reanalyzed published data using the published deterministic neuron turnover model but I extended the model by a better justified measurement error model. Most importantly, I found that human adult neurogenesis might occur at an even higher rate than currently believed. The tools I used throughout were (1) the careful quantification of the involved processes, mainly by image analysis, and (2) the derivation and application of mathematical models designed to integrate the data through (3) statistical inference. Mathematical models were used for different purposes such as estimating unknown parameters from indirect experiments, summarizing datasets with a few meaningful parameters, formalizing mechanistic hypotheses, as well as for model-guided experimental planning. I venture an outlook on how additional open questions regarding cell turnover measurements could be answered using my approach. Finally, I conclude that the mechanistic understanding of development and regeneration can be advanced by comparing quantitative data to the predictions of specifically designed mathematical models by means of statistical inference methods.

The present study focuses on the cardiac function of Drosophila melanogaster. Drosophila heart parameters are evolutionarily conserved, making Drosophila a useful human heart disease model. This model enables the in vivo investigation of physiological and genetic methods. This thesis is subdivided into four parts: parts 1-3 comprise the introductions of three publications, and part 4 presents unpublished data. The first publication is about the heart physiology of Drosophila. It explains how intracardiac valve cells work and proves their participation in blood flow directionality. A databased model shows the orientation of myofibrils within the valve cell. The myofibrils allow the valve cells to oscillate between a roundish and elongated cell shape. A toll-GFP enhancer line was shown to mediate strong reporter gene activity in the intracardiac valve of third instar larvae, pupae and adults. Transmission electron microscopy (TEM) analyses and immunohistochemical studies showed the differentiation of larval valve cells for the first time. The second publication focuses on the cardiac extracellular matrix (ECM), which contains two unique proteins - Lonely heart (Loh) and Pericardin (Prc). The study demonstrated that Loh is crucial for Prc recruitment to the developing matrix. Loh is anchored to the ECM by its thrombospondin type 1 repeat (TSR1-1) with its embedded putative glycosaminoglycan (GAG)-binding side. The N-terminus of Loh is proposed to face the plasma membrane. Prc is presumably recruited by two Loh TSR1 domains (TSR1-2 and TSR1-4). Nearly all Drosophila tissues, except salivary glands, create Prc networks through ectopic Loh expression. The study also found that the amount of Prc and Loh in the cardiac ECM influences heart function. The third publication investigated a set of neuropeptides and their ability to modulate cardiac function in third instar larvae. The results showed that 11 of the 19 tested peptides significantly affected the heart function in semi-intact larvae. Furthermore, the peptides’ in vivo relevance was tested through the knockdown of chronotropic peptide precursors. The study found that a RNAi mediated knockdown of all respective peptide precursors affected the heart rate. By combining semi-intact heart preparations and in vivo analyses, we identified several heartbeat-modulatory peptides in Drosophila. The unpublished data introduces a new software program called HIRO. It is written in Java, platform-independent and can easily detect the heart rhythm. Only mild anaesthesia and basic equipment are needed to record the Drosophila heartbeat. HIRO was used to show the influence of the RNAi-mediated downregulation of critical ECM proteins in Drosophila third instar larvae. The screen revealed Myospheroid and Laminin A as promising candidates that can significantly affect the heart parameters. HIRO is optimised for future applications and can be used as a high-throughput screening software with a simple setup. Taken together, this thesis provides new insights into the physiology and function of the Drosophila heart. The developed software HIRO comes with a user-friendly interface and a step-by-step introduction to easily conduct heart parameter measurements. HIRO will help to expand our knowledge of the fundamental processes in the model organism Drosophila melanogaster.

Die Kardiogenese kann speziesübergreifend in eine distinkte Abfolge von dynamischen Entwicklungsphasen unterteilt werden. In frühen Stadien der Vertebraten-Herzentwicklung wie auch bei Drosophila melanogaster beginnt die Organogenese des Herzens mit der Selektion und Spezifizierung der Herzvorläuferzellen aus bilateral angelegtem, mesodermalem Gewebe. Anschließend resultiert die Differenzierung der determinierten Herzvorläuferzellen in bilateralen Reihen spezifischer Herzzellgruppen. Die Herzzellen migrieren in dorsale Richtung aufeinander zu und assemblieren zu einem Herzrohr. Diese dynamischen Prozesse unterliegen einem komplexen Netzwerk an hoch konservierten Regulationsmechanismen. In der vorliegenden Dissertation konnte gezeigt werden, dass die Metalloprotease Kuzbanian/ADAM10 eine Rolle während der Kardiogenese von Drosophila spielt, in dem sie die Selektion der Herzzellvorläufer aus dem kardialen Mesoderm steuert. Durch die unterbleibende Prozessierung des Notch-Rezeptors in kuzbanian Mutanten wird eine Überzahl an Herzvorläuferzellen determiniert. Weiterhin ist die Notch-abhängige asymmetrische Zellteilung in kuzbanian Mutanten fehlreguliert. Die perikardialen Herzzelllinien verschieben sich zu Gunsten der kardialen Herzzellen und resultieren in einer Hyperplasie der Kardiomyozyten. Eine weitere Phase der Kardiogenese in Drosophila ist die korrekte Ausbildung des Herzrohres und die damit einhergehenden Herzlumenbildung. Durch das Herzlumen kann die Hämolymphe durch das Herzrohr in den Körper des Tieres gepumpt werden. Die Bildung des Lumens bedingt eine stereotype Zellformänderung der Kardiomyozyten. Diese Modulierung der Zellform resultiert in halbmondförmigen Kardiomyozyten, die dorsal und ventral miteinander in Kontakt treten und so einen zentralen, luminalen Bereich umschließen – das Herzlumen. Das Rezeptor/Liganden-Paar Uncoordinated 5 (Unc5) und NetrinB ist für die korrekte Ausbildung der luminalen Kardiomyozytenseite notwendig. Es konnte gezeigt werden, dass ein Fehlen von Unc5 oder NetrinB die Kardiomyozyten in einer runden Zellform verbleiben lässt. Die Kardiomyozyten lagern sich entlang ihrer gesamten Kontaktfläche aneinander ohne dass ein Lumen entsteht. Lebendbeobachtungen an unc5 Mutanten zeigten, dass das Fehlen des Herzlumens zu einem kompletten Verlust des Hämolymphstroms führt.

No description available.

No description available.

No description available.

No description available.

Developmental biologists try to elucidate how it is possible for cells, all originating from the same egg, to develop into a variety of highly specialized structures, such as muscles, skin, brain and limbs. What organizes the behavior of these cells, and how can the information encoded in the DNA account for the observed patterns and developmental processes? Cell movements and tissue flow during embryogenesis constitute a beautiful problem of bridging scales: On the microscopic scale, cells are expressing particular genes which determine their identities and also their fate during morphogenesis. These molecular determinants then lead to the macroscopic phenomena of cell movements and tissue arrangements, for which one needs a continuum description in terms of active fluids. Taking into account that the number of cells is fairly small, a complete coarse graining is not possible, and a characterization of both mesoscopic (individual cell motion) and macroscopic (flow) behavior is required for a full description. In the here presented work, a set of different experimental methods was applied to investigate the mechanical and dynamical properties of zebrafish embryonic cells and tissues. This thesis is structured as follows: In chapter 2, we introduce the fundamental concepts that are important for the study of cell motion during zebrafish embryonic development. In chapter 3, the materials and methods applied in this work are described. The experimental results of my thesis-work are presented in chapters 4-8: Chapter 4 concentrates on the physical properties of whole tissues. It is shown that tissues are viscoelastic materials. Tissue viscoelasticity is not a new concept, but this study is the first one to quantify the mechanical properties of tissues that are in actual contact in a developing embryo. In chapter 5, cell rearrangements in culture, such as cell sorting and tissue wetting are discussed. These experiments show that tissue interactions are largely determined by tissue surface and interfacial tensions. In chapter 6, an optical stretcher device is applied to measure, solely by means of laser light, the material properties of individual cells. Hereby it is shown that single cells from the two investigated tissue types differ in their mechano-physical properties. After the study of cell and tissue mechanics, the dynamics of cell migration in three dimensions in tissue aggregates and in developing zebrafish embryos is addressed: In chapter 7, 3D-cell migration in multicellular aggregates is analyzed quantitatively by studying the mean square displacement, cell velocity distribution and velocity autocorrelation. In chapter 8, we study the cell motion within the developing zebrafish embryo. By following the motion of many cells in four dimensions, we are able to generate a velocity flow profile for this cell-flow. Chapter 9 gives a brief summary of the obtained results and an outlook to future projects motivated by the presented study. The final part of this thesis are four appendices. Appendix A contains protocols and additional methods. Appendix B contains several calculations, whose results were used in the main part of this work. Appendix C contains additional data and discussions, which were excluded from the main part due to space limitations. Finally, Appendix D consists of a compact disc with 11 movies and a movie description, which serves as supplemental material to the presented data. (Die Druckexemplare enthalten jeweils eine CD-ROM als Anlagenteil: 650 MB: Movies - Nutzung: Referat Informationsservice der SLUB)

No description available.

Embryonic development depends on the precise coordination of cell fate specification, patterning and morphogenesis. Although great strides have been made in the molecular understanding of each of these processes, how their interplay governs the formation of complex tissues remains poorly understood. New techniques for experimental manipulation and image quantification enable the study of development in unprecedented detail, resulting in new hypotheses on the interactions between known components. By expressing these hypotheses in terms of rules and equations, computational modeling and simulation allows one to test their consistency against experimental data. However, new computational methods are required to represent and integrate the network of interactions between gene regulation, signaling and biomechanics that extend over the molecular, cellular and tissue scales. In this thesis, I present a framework that facilitates computational modeling of multiscale multicellular systems and apply it to investigate pancreatic development and the formation of vascular networks. This framework is based on the integration of discrete cell-based models with continuous models for intracellular regulation and intercellular signaling. Specifically, gene regulatory networks are represented by differential equations to analyze cell fate regulation; interactions and distributions of signaling molecules are modeled by reaction-diffusion systems to study pattern formation; and cell-cell interactions are represented in cell-based models to investigate morphogenetic processes. A cell-centered approach is adopted that facilitates the integration of processes across the scales and simultaneously constrains model complexity. The computational methods that are required for this modeling framework have been implemented in the software platform Morpheus. This modeling and simulation environment enables the development, execution and analysis of multi-scale models of multicellular systems. These models are represented in a new domain-specific markup language that separates the biological model from the computational methods and facilitates model storage and exchange. Together with a user-friendly graphical interface, Morpheus enables computational modeling of complex developmental processes without programming and thereby widens its accessibility for biologists. To demonstrate the applicability of the framework to problems in developmental biology, two case studies are presented that address different aspects of the interplay between cell fate specification, patterning and morphogenesis. In the first, I focus on the interplay between cell fate stability and intercellular signaling. Specifically, two studies are presented that investigate how mechanisms of cell-cell communication affect cell fate regulation and spatial patterning in the pancreatic epithelium. Using bifurcation analysis and simulations of spatially coupled differential equations, it is shown that intercellular communication results in a multistability of gene expression states that can explain the scattered spatial distribution and low cell type ratio of nascent islet cells. Moreover, model analysis shows that disruption of intercellular communication induces a transition between gene expression states that can explain observations of in vitro transdifferentiation from adult acinar cells into new islet cells. These results emphasize the role of the multicellular context in cell fate regulation during development and may be used to optimize protocols for cellular reprogramming. The second case study focuses on the feedback between patterning and morphogenesis in the context of the formation of vascular networks. Integrating a cell-based model of endothelial chemotaxis with a reaction-diffusion model representing signaling molecules and extracellular matrix, it is shown that vascular network patterns with realistic morphometry can arise when signaling factors are retained by cell-modified matrix molecules. Through the validation of this model using in vitro assays, quantitative estimates are obtained for kinetic parameters that, when used in quantitative model simulations, confirm the formation of vascular networks under measured biophysical conditions. These results demonstrate the key role of the extracellular matrix in providing spatial guidance cues, a fact that may be exploited to enhance vascularization of engineered tissues. Together, the modeling framework, software platform and case studies presented in this thesis demonstrate how cell-centered computational modeling of multi-scale and multicellular systems provide powerful tools to help disentangle the complex interplay between cell fate specification, patterning and morphogenesis during embryonic development.