281 research outputs found

    Tip cell overtaking occurs as a side effect of sprouting in computational models of angiogenesis

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    During angiogenesis, endothelial cells compete for the tip position during angiogenesis: a phenomenon named tip cell overtaking. It is still unclear to what extent tip cell overtaking is a side effect of sprouting or to what extent a biological function. To address this question, we studied tip cell overtaking in two existing cellular Potts models of angiogenic sprouting. In these models angiogenic sprouting-like behavior emerges from a small set of plausible cell behaviors and the endothelial cells spontaneously migrate forwards and backwards within sprouts, suggesting that tip cell overtaking might occur as a side effect of sprouting. In accordance with experimental observations, in our simulations the cells' tendency to occupy the tip position can be regulated when two cell lines with different levels of Vegfr2 expression are contributing to sprouting (mosaic sprouting assay), where cell behavior is regulated by a simple VEGF-Dll4-Notch signaling network. Our modeling results suggest that tip cell overtaking occurs spontaneously due to the stochastic motion of cells during sprouting. Thus, tip cell overtaking and sprouting dynamics may be interdependent and should be studied and interpreted in combination. VEGF-Dll4-Notch can regulate the ability of cells to occupy the tip cell position, but only when cells in the simulation strongly differ in their levels of Vegfr2. We propose that VEGF-Dll4-Notch signaling might not regulate which cell ends up at the tip, but assures that the cell that randomly ends up at the tip position acquires the tip cell phenotype.Comment: 20 pages, 6 figures, 4 supplementary figure

    Computational screening of tip and stalk cell behavior proposes a role for apelin signaling in sprout progression

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    Angiogenesis involves the formation of new blood vessels by sprouting or splitting of existing blood vessels. During sprouting, a highly motile type of endothelial cell, called the tip cell, migrates from the blood vessels followed by stalk cells, an endothelial cell type that forms the body of the sprout. To get more insight into how tip cells contribute to angiogenesis, we extended an existing computational model of vascular network formation based on the cellular Potts model with tip and stalk differentiation, without making a priori assumptions about the differences between tip cells and stalk cells. To predict potential differences, we looked for parameter values that make tip cells (a) move to the sprout tip, and (b) change the morphology of the angiogenic networks. The screening predicted that if tip cells respond less effectively to an endothelial chemoattractant than stalk cells, they move to the tips of the sprouts, which impacts the morphology of the networks. A comparison of this model prediction with genes expressed differentially in tip and stalk cells revealed that the endothelial chemoattractant Apelin and its receptor APJ may match the model prediction. To test the model prediction we inhibited Apelin signaling in our model and in an in vitro model of angiogenic sprouting, and found that in both cases inhibition of Apelin or of its receptor APJ reduces sprouting. Based on the prediction of the computational model, we propose that the differential expression of Apelin and APJ yields a "self-generated" gradient mechanisms that accelerates the extension of the sprout

    Contact-inhibited chemotaxis in de novo and sprouting blood-vessel growth

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    Blood vessels form either when dispersed endothelial cells (the cells lining the inner walls of fully-formed blood vessels) organize into a vessel network (vasculogenesis), or by sprouting or splitting of existing blood vessels (angiogenesis). Although they are closely related biologically, no current model explains both phenomena with a single biophysical mechanism. Most computational models describe sprouting at the level of the blood vessel, ignoring how cell behavior drives branch splitting during sprouting. We present a cell-based, Glazier-Graner-Hogeweg-model simulation of the initial patterning before the vascular cords form lumens, based on plausible behaviors of endothelial cells. The endothelial cells secrete a chemoattractant, which attracts other endothelial cells. As in the classic Keller-Segel model, chemotaxis by itself causes cells to aggregate into isolated clusters. However, including experimentally-observed adhesion-driven contact inhibition of chemotaxis in the simulation causes randomly-distributed cells to organize into networks and cell aggregates to sprout, reproducing aspects of both de novo and sprouting blood-vessel growth. We discuss two branching instabilities responsible for our results. Cells at the surfaces of cell clusters attempting to migrate to the centers of the clusters produce a buckling instability. In a model variant that eliminates the surface-normal force, a dissipative mechanism drives sprouting, with the secreted chemical acting both as a chemoattractant and as an inhibitor of pseudopod extension. The branching instabilities responsible for our results, which result from contact inhibition of chemotaxis, are both generic developmental mechanisms and interesting examples of unusual patterning instabilities.Comment: Thoroughly revised version, now in press in PLoS Computational Biology. 53 pages, 13 figures, 2 supporting figures, 56 supporting movies, source code and parameters files for computer simulations provided. Supporting information: http://www.psb.ugent.be/~romer/ploscompbiol/ Source code: http://sourceforge.net/projects/tst

    A multiscale hybrid model for pro-angiogenic calcium signals in a vascular endothelial cell

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    Cytosolic calcium machinery is one of the principal signaling mechanisms by which endothelial cells (ECs) respond to external stimuli during several biological processes, including vascular progression in both physiological and pathological conditions. Low concentrations of angiogenic factors (such as VEGF) activate in fact complex pathways involving, among others, second messengers arachidonic acid (AA) and nitric oxide (NO), which in turn control the activity of plasma membrane calcium channels. The subsequent increase in the intracellular level of the ion regulates fundamental biophysical properties of ECs (such as elasticity, intrinsic motility, and chemical strength), enhancing their migratory capacity. Previously, a number of continuous models have represented cytosolic calcium dynamics, while EC migration in angiogenesis has been separately approached with discrete, lattice-based techniques. These two components are here integrated and interfaced to provide a multiscale and hybrid Cellular Potts Model (CPM), where the phenomenology of a motile EC is realistically mediated by its calcium-dependent subcellular events. The model, based on a realistic 3-D cell morphology with a nuclear and a cytosolic region, is set with known biochemical and electrophysiological data. In particular, the resulting simulations are able to reproduce and describe the polarization process, typical of stimulated vascular cells, in various experimental conditions.Moreover, by analyzing the mutual interactions between multilevel biochemical and biomechanical aspects, our study investigates ways to inhibit cell migration: such strategies have in fact the potential to result in pharmacological interventions useful to disrupt malignant vascular progressio

    Quantitative predictions on auxin-induced polar distribution of PIN proteins during vein formation in leaves

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    The dynamic patterning of the plant hormone auxin and its efflux facilitator the PIN protein are the key regulator for the spatial and temporal organization of plant development. In particular auxin induces the polar localization of its own efflux facilitator. Due to this positive feedback auxin flow is directed and patterns of auxin and PIN arise. During the earliest stage of vein initiation in leaves auxin accumulates in a single cell in a rim of epidermal cells from which it flows into the ground meristem tissue of the leaf blade. There the localized auxin supply yields the successive polarization of PIN distribution along a strand of cells. We model the auxin and PIN dynamics within cells with a minimal canalization model. Solving the model analytically we uncover an excitable polarization front that triggers a polar distribution of PIN proteins in cells. As polarization fronts may extend to opposing directions from their initiation site we suggest a possible resolution to the puzzling occurrence of bipolar cells, such we offer an explanation for the development of closed, looped veins. Employing non-linear analysis we identify the role of the contributing microscopic processes during polarization. Furthermore, we deduce quantitative predictions on polarization fronts establishing a route to determine the up to now largely unknown kinetic rates of auxin and PIN dynamics.Comment: 9 pages, 4 figures, supplemental information included, accepted for publication in Eur. Phys. J.

    A multiscale spatiotemporal model explains succession in the early infant gut microbiota as a switch from aerobic to anaerobic metabolism

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    The human intestinal microbiome starts to form immediately after birth, and can greatly influence the health of the infant. During the first days facultative anaerobic species generally dominate, followed by a dominance of strictly anaerobic species, particularly Bifidobacterium species. An early transition to Bifidobacterium is associated with health benefits. To study the mechanisms of this transition and its hypothesised relation to oxygen, we introduce a multiscale mathematical model that considers metabolism, spatial bacterial population dynamics and resource sharing. Based on publicly available metabolic network data, the model predicts that differences in oxygen availability explain some of the observed individual variation in succession to anaerobic species. The model also predicts that anaerobic Bifidobacterium species become dominant through metabolizing lactose with a suboptimal yield, but a higher anaerobic growth rate than its competitors. The current work is the first step towards a more comprehensive understanding of the formation of a steady state adult colonic microbiota.Analysis and StochasticsMicrobial BiotechnologyAnimal science
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