Theoretical basis of the community effect in development

Peer reviewedPublisher PD

Modeling mammalian gastrulation with embryonic stem cells

Understanding cell fate patterning and morphogenesis in the mammalian embryo remains a formidable challenge. Recently, in vivo models based on embryonic stem cells (ESCs) have emerged as complementary methods to quantitatively dissect the physical and molecular processes that shape the embryo. Here we review recent developments in using embryonic stem cells to create both two and three-dimensional culture models that shed light on mammalian gastrulation.Comment: 18 pages, 1 figur

Mammalian Brain As a Network of Networks

Acknowledgements AZ, SG and AL acknowledge support from the Russian Science Foundation (16-12-00077). Authors thank T. Kuznetsova for Fig. 6.Peer reviewedPublisher PD

The Effect of GATA6 Expression and Its Neighborhood Impact Factor on Regulating Cell Fate

abstract: A genetically engineered line of human induced pluripotent stem cells was used to study the effects of gene expression on cell fate. These cells were designed to activate expression of the gene GATA6 when exposed to the small molecule doxycycline. This gene was chosen because it plays an important role in the developmental biology stages of liver formation. Because of the way the cells were engineered, a given population would have a heterogeneous expression of GATA6 because each cell could have a different copy number of the exogenous gene. This variation allows for the differentiation of multiple cell types, and is used to grow liver organoids. The early liver organoid samples were studied via immunofluorescent staining, imaging, and quantitative image analysis. It was originally hypothesized that absolute gene expression was not the most important factor in determining cell fate, but relative gene expression was. This meant that the spatial location of the cells and their local environment were critical in determining cell fate. In other words, the level of GATA6 of a cell is important, but so is the level of GATA6 in the surrounding cells, or neighborhood, of that cell. This hypothesis was analyzed with the creation of various Neighborhood Impact Factor (NIF) methods. Multiple time points of growth were analyzed to study the temporal effect, in addition to the gene expression and NIF influence on a cell’s fate. Direct gene expression level showed correlation with certain cell fate markers. In addition to GATA6 expression levels, NIF results from early and late time point experiments show statistical significance with relatively small neighborhood radii. The NIF analysis was useful for examining the effect of neighboring cells and determining the size of the neighborhood – how far cells influence one another. While these systems are complex, the NIF analysis provides a way to look at gene expression and its influence in spatial context.Dissertation/ThesisPowerpoint presentation used in the defense.Masters Thesis Bioengineering 201

Nuclei on the Move - Physical Aspects of Interkinetic Nuclear Migration

Embryonic development is a highly complex procedure, leading from initial, unspecialised cell types - the stem cells - to ever more specialised ones. In part, this process is regulated by genes; but interactions between cells, such as mechanical contacts and the exchange of diffusive signalling molecules, also play pivotal roles for the correct execution of developmental programmes. Therefore, unravelling the rules of cell differentiation requires insights from both biology and physics. In this dissertation, we focus on the process of interkinetic nuclear migration (IKNM). IKNM takes place in cells of so-called pseudostratified epithelia (PSE) during development. In these tissues, the nuclei of cells move in a cell cycle dependent manner and position themselves in a specific region of the cells for each cell division. The correct nuclear positioning has been shown to be crucial for proper development in PSE. And because organs like the brain and the spinal cord develop from pseudostratified epithelial tissues, IKNM appears to be of paramount importance for the entire embryo. The work presented here concerns IKNM in the retina, an experimentally accessible outgrowth of the brain, and relies on experimental data obtained from zebrafish. However, the conclusions are likewise relevant for understanding the development of many other PSE tissues. Based on the experimental data, two previously posed hypotheses on how the majority of nuclear movements might be driven can be tested. The data is consistent with the idea that nuclear movements depend on the build-up of a gradient in nuclear packing density across the retinal tissue. Consequently, we develop the first mathematical model for the distribution of nuclei across the retinal tissue as a function of time. Underlying this model is the notion that individual nuclear trajectories phenomenologically resemble random walks during most of the cell cycle. Therefore, we model the time evolution of the nuclear density using a diffusion equation with an effective diffusion constant to be determined from the data. Furthermore, we specifically account for the fact that nuclear divisions always take place in a defined region of the cells - leading to the aforementioned gradient in nuclear packing density. Finally, we also pay attention to the spherical geometry of the retinal tissue. Although the simplest linear model describes well the data from early in the experiments, it fails to do so for data from later stages in which nuclei approach close-packing. We hypothesise that the reason for this mismatch between model and data might result from the neglect of crowding. Therefore, we present a second, nonlinear model which now takes the volume of nuclei into account by introducing a maximum possible packing density. This enables us to replicate the experimental nuclear distribution across the whole range of experimental time points. We finally employ this second model to make statements about the influence of experimental parameters, specifically incubation temperature, on the dynamics of IKNM. The result also provides some indications for possible microscopic mechanisms underlying the nuclear movements. Having studied the distribution of nuclei across the retinal tissue, we aim to investigate the significance of our obtained results on the level of individual cells. First, we compare the mobility of nuclei during IKNM with the expected mobility in the cases of Brownian motion and membrane-hindered Brownian motion. We find that IKNM appears to be both membrane-hindered and additionally driven throughout the entire cell cycle. Assuming a stochastic driving force and calculating its typical strength we deduce IKNM to be consistent with cytoskeletal transport. We then devise possible Langevin models for individual nuclear movements which are consistent with the model for the distribution of nuclei derived previously. The numerical simulation of each of these Langevin models enables us to distinguish between them; we identify the model which most likely reflects the biological process in each individual cell. This again leads to predictions about the potential microscopic underpinnings of nuclear movements during IKNM. The apparent importance of the cell membrane in restricting nuclear mobility prompts us to examine the shape of PSE cells in closer detail. We numerically solve the Helfrich elastic model for lipid bilayers for increasingly large cell aspect ratios. In the case of long, slender cells and high membrane tension, we recover shapes not unlike those previously reported for membrane tethers. In contrast, shorter cells are almost cylindrical. The results of this systematic investigation into cell shapes might explain the different geometries of cells in various types of PSE. Furthermore, they might also be of relevance for more generally understanding peculiar cell shapes, such as those of neurons.EPSRC; Helen Stone Scholarship at the University of Cambridge (through the Cambridge Commonwealth, European & International Trust); The Cambridge Philosophical Society Research Studentshi

Stochastic Effects in Quorum Sensing

[cat] En aquesta tesi, estudiem els efectes de la estocàsticitat en la aparició del comportament col·lectiu en poblacions de bacteris que comuniquen per quorum sensing (QS). Ens centrem en el interruptor genètic com a paradigma dels processos de decisió cel·lulars tant en sistemes de bacteris naturals com sintètics. El nostre mètode es basa en la modelització matemàtica i en les simulacions estocàstiques, tant a nivell d'una cèl·lula individual com a nivell d'una població de cèl·lules. A nivell d'una cèl·lula individual, mostrem que el soroll afavoreix l'estabilitat del fenotip de l'estat ``baix'' de l'interruptor genètic autoactivador i que la regió de biestabilitat s'estén quan creix la intensitat de les fluctuacions, un efecte que hem anomenat estabilització estocàstica. A nivell d'una població de cèl·lules, mostrem que el procés de difusió del mecanisme de QS modifica les fluctuacions i la dinàmica de la molècula autoinductora dins de la cèl·lula i interactua amb el soroll en la expressió genètica. En el sistema canònic de QS LuxR/LuxI, mostrem que el soroll en la expressió genètica de LuxR és el principal factor que controla la variabilitat transitòria de l'activació del QS. El soroll intrínsec disminueix la precisió de la coordinació de la població i modifica la dinàmica de la transició de QS. A més, presentem un model d'una població d'interruptors genètics de toggle switch que comuniquen per l'intercanvi de dos senyals difusius de QS. Mostrem que l'increment de la velocitat de difusió, que augmenta la força de l'acoblament entre les cèl·lules, porta a una transició de fase: va des d'una fase desordenada on les cèl·lules salten de manera aleatòria entre els dos estats de l'interruptor, fins a una fase ordenada amb totes les cèl·lules bloquejades en el mateix estat estable. La mateixa transició s'ha trobat en una població de cèl·lules que creixen exponencialment en un volum tancat, amb totes les cèl·lules entrant en l'estat ordenat quan arriben a una mida crítica del sistema. Els nostres resultats suggereixen un nou mecanisme per la decisió cel·lular col·lectiva basat en el fenomen de la transició de fase.[eng] Stochastic fluctuations, or noise, are ubiquitous in biological systems and play an important role in many cellular processes. Experimental evidences have shown that noise affects the reliability of cell coordination in populations of communicating cells. In this thesis, we study the effects of stochasticity in the emergence of collective behavior in populations of bacteria communicating by QS. We focus on the genetic switch as a paradigm of cellular decision making in both natural and synthetic bacterial systems. Our approach is based on mathematical modeling and stochastic simulations, both at the level of the single cell and at the level of the cell population. We focus on four main topics. In the first topic, we analyze the interplay between intracellular noise and the diffusion process of the QS signaling mechanism. We build a model describing the expression of the signaling molecule and its diffusion in a population of cells, focusing on the situation of very low constitutive expression rate. We show that varying the diffusion rate produces a repertoire of dynamics for the signaling molecule. Our results reveal the contribution of intrinsic noise and transcriptional noise (mRNA copy number fluctuations) in the fluctuations of the signaling molecule. We observe that the total noise exhibits a maximum as a function of the diffusion rate, in contrast to previous studies. Thus, the QS communication mechanism modifies the fluctuations of the signaling molecule inside the cell and interacts with the gene expression noise. In the second topic, we study the effects of gene expression noise on the precision of the population coordination in the QS activation of the LuxR/LuxI system. We analyze the response and dynamics of a population of cells to different levels of autoinducer. Our results show that gene expression noise in LuxR is the main factor that controls the transient variability of the QS activation. This study sheds light on the relation between the single cell stochastic dynamics and the collective behavior in a population of communicating cells. In the third topic, we analyze the effects of intrinsic noise in an autoactivating switch in an isolated single cell. We show that noise promotes the stability of the low-state phenotype of the switch and that the bistable region is extended when increasing the intensity of the fluctuations, an effect that we call stochastic stabilization. Our results show that intrinsic noise modifies the epigenetic landscape as well as the switching rate, which results in complex behavior of the stochastic switching dynamics when varying the intensity of noise. Thus, at the level of a single cell, intrinsic noise contributes to the cell-to-cell variability of the genetic switch and can modify its stable states and its dynamics. In the fourth topic, we build a model of a population of toggle switches communicating by the exchange of two diffusible QS signals. We show that increasing the diffusion rate, which increases the coupling strength between the cells, leads to a phase transition from an unordered phase where the cells randomly flip between the two states of the switch, to an ordered phase with all the cells locked into the same stable state. The same transition is found in a population of cells growing exponentially in a closed volume. Moreover, the response of the cells to a varying external signal exhibits a hysteresis loop. We show that the cell-cell coupling enhances the sensitivity of the population response to the external signal and suggest that this new mechanism could be used to increase the robustness and sensitivity of biosensors. Our results suggest a new mechanism for collective cell decision making based on the phenomenon of phase transition

Multicellular Systems Biology of Development

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

Investigating the Roles of Cell Identity Regulation and Eph/ephrin Signalling in Early Hindbrain Segmentation

During development of the vertebrate hindbrain, the neuroepithelium becomes subdivided into seven morphological units, known as rhombomeres. It is necessary that rhombomeres have sharp, well-defined boundaries, which are established from initially rough gene expression domains during early hindbrain segmentation. The mechanisms involved in early hindbrain segmentation that create sharp segment borders are not well understood. There is evidence to suggest that both regulation of cell identity and Eph/ephrin-mediated cell sorting are required for establishing sharp interfaces between rhombomeres. This thesis investigates the extent to which identity regulation contributes to hindbrain border sharpening in zebrafish. I created a new zebrafish reporter line by CRISPR/Cas9-mediated reporter integration at the egr2b locus, which enables cell identity and cell intermingling to be visualised in live embryos during border sharpening. This new reporter line indicates a contribution of cell identity regulation to border sharpening. I also demonstrate that the contribution of cell identity switching to border refinement is greater in cases where cell intermingling is increased by perturbed Eph/ephrin signalling. To help study the role of Eph/ephrin signalling in border sharpening, I have also created a novel EphrinB3b mutant. The thesis also investigates the mechanisms of identity regulation by community effects and discusses their contribution to border refinement by identity respecification; community effects are suspected to help overcome noise in early gene induction through spatial averaging and thus help establish regions of homogeneous gene expression. The ability of candidate genes to non cell-autonomously regulate the identity of neighbouring cells in the hindbrain is investigated. Of particular focus is the potential involvement of retinoic acid (a morphogen involved in specification of anteroposterior identity) and segmentally-expressed Cyp26 enzymes involved in its metabolism. Analysis of mosaic embryos is used to compare the ability of isolated cells and clustered groups of cells to maintain a different identity to their surroundings. Results presented here are consistent with segmental regulation of retinoic acid signalling contributing to border sharpening

Organisation of the feather periodic pattern through propagating molecular waves

Members of the class Aves possess integumentary structures which distinguish them from other vertebrate lineages. The characteristic integumentary structure that defines the Aves from other vertebrates are the feathers, whose functions include insulation, camouflage, visual display, gliding, and powered flight. The recent discoveries of theropod dinosaur fossils displaying feather-like structures have led to interest in the morphological innovations of the feathers, which are associated with the evolution of flight in Aves. Most modern birds, display a highly ordered, hexagonal arrangement of feather follicles, which aids in the streamlining of the body to increase aerodynamic efficiency. Using the chicken embryo as a developmental model, I address the cellular and molecular processes involved in the initiation and formation of a high fidelity periodic pattern of feather primordia. From my studies, I propose a model in which the induction of individual feather primordia begins with the activation of FGF20 expression. This gene encodes a protein that serves as a chemoattractant. Aggregation of cells towards sources of FGF20 stimulates and reinforces FGF20 expression and also induces the expression of BMP4. Via a reaction-diffusion-like mechanism, BMP4 acts to limit the growth of the cell aggregate and promotes lateral inhibition to prevent fusions between neighbouring feather primordia through transcriptional regulation of FGF20. In order to achieve a high fidelity periodic pattern of feather primordia, three components are required; 1) a competent epidermis displaying β-Catenin and EDAR expression, 2) wave-like propagation of EDA expression, which acts synergistically with β-Catenin expression to activate FGF20 expression at the β-Catenin/EDA junction, 3) and a dermis of sufficient cell density. The spatiotemporal wave-like propagation of EDA expression, specifically, promotes the sequential induction of new feather primordium rows and is associated with the formation of a high fidelity periodic pattern. The importance of these three components appears to be evolutionarily conserved among the Aves and differences in the periodic pattern of feather primordia between species can be explained by how the three components are expressed or regulated in individual species. Independent losses of flight in ratites, such as ostriches and emus, are associated with the loss of feather pattern fidelity. In emus, this loss of pattern fidelity results from the delayed formation of a dermis of sufficient cell density, which prevents the induction of feather primordium formation within the dorsal tract, despite the presence of a fully primed and competent epidermis. These studies demonstrate how the precise feather pattern arises during embryonic development in birds, and how feather patterns can be modified through differential regulation of the molecular and cellular toolkit involved in feather primordium induction in different bird species

Heterotypic cell-cell interactions between KrasG12D cells and normal neighbours in early pancreatic cancer

At the initial stages of tumourigenesis, transformation occurs in a single cell within a healthy epithelial sheet. Competitive interactions between normal and Ras-transformed cells can drive the elimination of mutant cells from tissues to protect from carcinogenesis. Moreover, we have previously demonstrated that normal cells detect and eliminate Ras-transformed cells via differential EphA2 signalling. KrasG12D expressing cells (KrasG12D cells) initiate and drive the earliest stages of pancreatic cancer yet it is unclear if normal pancreatic cells can eliminate oncogenic cells. Here we use low level, stochastic induction of KrasG12D mutations in the pancreas to model the interaction of normal and transformed epithelial cells. We show that Ras-transformed cells adopt a contractile morphology and are eliminated from healthy tissue when present at low numbers. When surrounded by normal cells, KrasG12D cells become segregated, increase in compactness and are often extruded. We find that E-cadherin-based cell-cell contacts are downregulated and internalised in mutant cells when surrounded by normal neighbours in an EphA2-dependent manner. Our evidence also suggests that normal cells suppress progression of Ras-transformed cells to an early disease state. Together, this study suggests that non-transformed pancreatic epithelial cells can eliminate KrasG12D cells from the tissue via EphA2 signalling. These data identify a novel putative tumour-suppressive mechanism in the adult pancreas that mutant cells must first overcome to drive tumourigenesis. Understanding the earliest stages of pancreatic carcinogenesis will provide insight into how risk factors promote disease and may elucidate how pancreatic cancer spreads around the body