Simulating flow induced migration in vascular remodelling.

Shear stress induces directed endothelial cell (EC) migration in blood vessels leading to vessel diameter increase and induction of vascular maturation. Other factors, such as EC elongation and interaction between ECs and non-vascular areas are also important. Computational models have previously been used to study collective cell migration. These models can be used to predict EC migration and its effect on vascular remodelling during embryogenesis. We combined live time-lapse imaging of the remodelling vasculature of the quail embryo yolk sac with flow quantification using a combination of micro-Particle Image Velocimetry and computational fluid dynamics. We then used the flow and remodelling data to inform a model of EC migration during remodelling. To obtain the relation between shear stress and velocity in vitro for EC cells, we developed a flow chamber to assess how confluent sheets of ECs migrate in response to shear stress. Using these data as an input, we developed a multiphase, self-propelled particles (SPP) model where individual agents are driven to migrate based on the level of shear stress while maintaining appropriate spatial relationship to nearby agents. These agents elongate, interact with each other, and with avascular agents at each time-step of the model. We compared predicted vascular shape to real vascular shape after 4 hours from our time-lapse movies and performed sensitivity analysis on the various model parameters. Our model shows that shear stress has the largest effect on the remodelling process. Importantly, however, elongation played an especially important part in remodelling. This model provides a powerful tool to study the input of different biological processes on remodelling.

Intercellular Adhesion Stiffness Moderates Cell Decoupling as a Function of Substrate Stiffness.

The interplay between cell-cell and cell-substrate interactions is complex yet necessary for the formation and healthy functioning of tissues. The same mechanosensing mechanisms used by the cell to sense its extracellular matrix also play a role in intercellular interactions. We used the discrete element method to develop a computational model of a deformable cell that includes subcellular components responsible for mechanosensing. We modeled a three-dimensional cell pair on a patterned (two-dimensional) substrate, a simple laboratory setup to study intercellular interactions. We explicitly modeled focal adhesions and adherens junctions. These mechanosensing adhesions matured, becoming stabilized by force. We also modeled contractile stress fibers that bind the discrete adhesions. The mechanosensing fibers strengthened upon stalling. Traction exerted on the substrate was used to generate traction maps (along the cell-substrate interface). These simulated maps are compared to experimental maps obtained via traction force microscopy. The model recreates the dependence on substrate stiffness of the tractions' spatial distribution, contractile moment of the cell pair, intercellular force, and number of focal adhesions. It also recreates the phenomenon of cell decoupling, in which cells exert forces separately when substrate stiffness increases. More importantly, the model provides viable molecular explanations for decoupling: mechanosensing mechanisms are responsible for competition between different fiber-adhesion configurations present in the cell pair. The point at which an increasing substrate stiffness becomes as high as that of the cell-cell interface is the tipping point at which configurations that favor cell-substrate adhesion dominate over those favoring cell-cell adhesion. This competition is responsible for decoupling.

Modeling of Mechanosensing Mechanisms Reveals Distinct Cell Migration Modes to Emerge From Combinations of Substrate Stiffness and Adhesion Receptor-Ligand Affinity.

Mesenchymal cell migration is an integral process in development and healing. The process is regulated by both mechanical and biochemical properties. Mechanical properties of the environment are sensed through mechanosensing, which consists of molecular responses mediated by mechanical signals. We developed a computational model of a deformable 3D cell on a flat substrate using discrete element modeling. The cell is polarized in a single direction and thus moves along the long axis of the substrate. By modeling discrete focal adhesions and stress fibers, we implement two mechanosensing mechanisms: focal adhesion stabilization by force and stress fiber strengthening upon contraction stalling. Two substrate-associated properties, substrate (ligand) stiffness and adhesion receptor-ligand affinity (in the form of focal adhesion disassembly rate), were varied for different model setups in which the mechanosensing mechanisms are set as active or inactive. Cell displacement, focal adhesion number, and cellular traction were quantified and tracked in time. We found that varying substrate stiffness (a mechanical property) and adhesion receptor-ligand affinity (a biochemical property) simultaneously dictate the mode in which cells migrate; cells either move in a smooth manner reminiscent of keratocytes or in a cyclical manner reminiscent of epithelial cells. Mechanosensing mechanisms are responsible for the range of conditions in which a cell adopts a particular migration mode. Stress fiber strengthening, specifically, is responsible for cyclical migration due to build-up of enough force to elicit rupture of focal adhesions and retraction of the cellular rear. Together, both mechanisms explain bimodal dependence of cell migration on substrate stiffness observed in the literature.

The role of actin protrusion dynamics in cell migration through a degradable viscoelastic extracellular matrix: Insights from a computational model.

Actin protrusion dynamics plays an important role in the regulation of three-dimensional (3D) cell migration. Cells form protrusions that adhere to the surrounding extracellular matrix (ECM), mechanically probe the ECM and contract in order to displace the cell body. This results in cell migration that can be directed by the mechanical anisotropy of the ECM. However, the subcellular processes that regulate protrusion dynamics in 3D cell migration are difficult to investigate experimentally and therefore not well understood. Here, we present a computational model of cell migration through a degradable viscoelastic ECM. This model is a 2D representation of 3D cell migration. The cell is modeled as an active deformable object that captures the viscoelastic behavior of the actin cortex and the subcellular processes underlying 3D cell migration. The ECM is regarded as a viscoelastic material, with or without anisotropy due to fibrillar strain stiffening, and modeled by means of the meshless Lagrangian smoothed particle hydrodynamics (SPH) method. ECM degradation is captured by local fluidization of the material and permits cell migration through the ECM. We demonstrate that changes in ECM stiffness and cell strength affect cell migration and are accompanied by changes in number, lifetime and length of protrusions. Interestingly, directly changing the total protrusion number or the average lifetime or length of protrusions does not affect cell migration. A stochastic variability in protrusion lifetime proves to be enough to explain differences in cell migration velocity. Force-dependent adhesion disassembly does not result in faster migration, but can make migration more efficient. We also demonstrate that when a number of simultaneous protrusions is enforced, the optimal number of simultaneous protrusions is one or two, depending on ECM anisotropy. Together, the model provides non-trivial new insights in the role of protrusions in 3D cell migration and can be a valuable contribution to increase the understanding of 3D cell migration mechanics.

Lifestyle and comorbid conditions as risk factors for community-acquired pneumonia in outpatient adults (NEUMO-ES-RISK project).

Introduction: Information about community-acquired pneumonia (CAP) risk in primary care is limited. We assess different lifestyle and comorbid conditions as risk factors (RF) for CAP in adults in primary care. Methods: A retrospective-observational-controlled study was designed. Adult CAP cases diagnosed at primary care in Spain between 2009 and 2013 were retrieved using the National Surveillance System of Primary Care Data (BiFAP). Age-matched and sex-matched controls were selected by incidence density sampling (ratio 2:1). Associations are presented as percentages and OR. Binomial regression models were constructed to avoid bias effects. Results: 51 139 patients and 102 372 controls were compared. Mean age (SD) was 61.4 (19.9) years. RF more significantly linked to CAP were: HIV (OR [95% CI]: 5.21 [4.35 to 6.27]), chronic obstructive pulmonary disease (COPD) (2.97 [2.84 to 3.12]), asthma (2.16 [2.07,2.26]), smoking (1.96 [1.91 to 2.02]) and poor dental hygiene (1.45 [1.41 to 1.49]). Average prevalence of any RF was 82.2% in cases and 69.2% in controls (2.05 [2.00 to 2.10]). CAP rate increased with the accumulation of RF and age: risk associated with 1RF was 1.42 (1.37 to 1.47) in 18-60-year-old individuals vs 1.57 (1.49 to 1.66) in >60 years of age, with 2RF 1.88 (1.80 to 1.97) vs 2.35 (2.23, 2.48) and with ≥ 3 RF 3.11 (2.95, 3.30) vs 4.34 (4.13 to 4.57). Discussion: Prevalence of RF in adult CAP in primary care is high. Main RFs associated are HIV, COPD, asthma, smoking and poor dental hygiene. Our risk stacking results could help clinicians identify patients at higher risk of pneumonia.

Spatiotemporal Analyses of Cellular Tractions Describe Subcellular Effect of Substrate Stiffness and Coating.

Cells interplay with their environment through mechanical and chemical interactions. To characterize this interplay, endothelial cells were cultured on polyacrylamide hydrogels of varying stiffness, coated with either fibronectin or collagen. We developed a novel analysis technique, complementary to traction force microscopy, to characterize the spatiotemporal evolution of cellular tractions: We identified subpopulations of tractions, termed traction foci, and tracked their magnitude and lifetime. Each focus consists of tractions associated with a local single peak of maximal traction. Individual foci were spread over a larger area in cells cultured on collagen relative to those on fibronectin and exerted higher tractions on stiffer hydrogels. We found that the trends with which forces increased with increasing hydrogel stiffness were different for foci and whole-cell measurements. These differences were explained by the number of foci and their average strength. While on fibronectin multiple short-lived weak foci contributed up to 30% to the total traction on hydrogels with intermediate stiffness, short-lived foci in such a number were not observed on collagen despite the higher tractions. Our approach allows for the use of existing traction force microscopy data to gain insight at the subcellular scale without molecular probes or spatial constraining of cellular tractions.

The Integrated Role of Wnt/ß-Catenin, N-Glycosylation, and E-Cadherin-Mediated Adhesion in Network Dynamics.

The cellular network composed of the evolutionarily conserved metabolic pathways of protein N-glycosylation, Wnt/ß-catenin signaling pathway, and E-cadherin-mediated cell-cell adhesion plays pivotal roles in determining the balance between cell proliferation and intercellular adhesion during development and in maintaining homeostasis in differentiated tissues. These pathways share a highly conserved regulatory molecule, ß-catenin, which functions as both a structural component of E-cadherin junctions and as a co-transcriptional activator of the Wnt/ß-catenin signaling pathway, whose target is the N-glycosylation-regulating gene, DPAGT1. Whereas these pathways have been studied independently, little is known about the dynamics of their interaction. Here we present the first numerical model of this network in MDCK cells. Since the network comprises a large number of molecules with varying cell context and time-dependent levels of expression, it can give rise to a wide range of plausible cellular states that are difficult to track. Using known kinetic parameters for individual reactions in the component pathways, we have developed a theoretical framework and gained new insights into cellular regulation of the network. Specifically, we developed a mathematical model to quantify the fold-change in concentration of any molecule included in the mathematical representation of the network in response to a simulated activation of the Wnt/ ß-catenin pathway with Wnt3a under different conditions. We quantified the importance of protein N-glycosylation and synthesis of the DPAGT1 encoded enzyme, GPT, in determining the abundance of cytoplasmic ß-catenin. We confirmed the role of axin in ß-catenin degradation. Finally, our data suggest that cell-cell adhesion is insensitive to E-cadherin recycling in the cell. We validate the model by inhibiting ß-catenin-mediated activation of DPAGT1 expression and predicting changes in cytoplasmic ß-catenin concentration and stability of E-cadherin junctions in response to DPAGT1 inhibition. We show the impact of pathway dysregulation through measurements of cell migration in scratch-wound assays. Collectively, our results highlight the importance of numerical analyses of cellular networks dynamics to gain insights into physiological processes and potential design of therapeutic strategies to prevent epithelial cell invasion in cancer.

Collective motion of mammalian cell cohorts in 3D.

Collective cell migration is ubiquitous in biology, from development to cancer; it occurs in complex systems comprised of heterogeneous cell types, signals and matrices, and requires large scale regulation in space and time. Understanding how cells achieve organized collective motility is crucial to addressing cellular and tissue function and disease progression. While current two-dimensional model systems recapitulate the dynamic properties of collective cell migration, quantitative three-dimensional equivalent model systems have proved elusive. To establish such a model system, we study cell collectives by tracking individuals within cell cohorts embedded in three dimensional collagen scaffolding. We develop a custom algorithm to quantify the temporal and spatial heterogeneity of motion in cell cohorts during motility events. In the absence of external driving agents, we show that these cohorts rotate in short bursts, <2 hours, and translate for up to 6 hours. We observe, track, and analyze three dimensional motion of cell cohorts composed of 3-31 cells, and pave a path toward understanding cell collectives in 3D as a complex emergent system.

Computational model to probe cellular mechanics during epithelial-mesenchymal transition.

During the epithelial to mesenchymal transition (EMT), polarized cells in the epithelium can undergo a transformation characterized by the loss of cell-cell junctions and increased migratory activity into nonpolarized invasive cells. These cells adopt a mesenchymal shape and migrate into the basal lamina. Such transitions have been observed in developmental processes and have been linked to cancer cell metastasis. Most experimental studies on EMT search for molecular markers indicating an epithelial or mesenchymal conformation, focussing on afferent signaling pathways received by cells undergoing this transformation; however, these approaches are unable to track mechanical changes in the cell and the possible role this plays in EMT. In order to address this gap in our understanding, we have used a quantitative approach to study population level effects of single cell changes typically occurring during EMT. We have developed a computational model making use of the advantages of both single cell migratory models and agent-based cell population models to study the effect of cellular molecular processes in EMT. The disruption of a cell sheet representing the epithelium over a dense extracellular matrix (ECM) is simulated using interaction forces between different cells and between cells and discrete fibers representing the ECM. In our study, two different parameters were varied: protrusion force magnitude and E-cadherin (cell-cell junction) concentration. The cell population was tracked for 3 days and the number of cells that leave the layer, the depth of invasion, and the percentage of initial number of cells that remain in the layer (a measure of epithelium disruption) were monitored. Our studies suggest that having a high protrusion force or a reduction in cell-cell attachments is enough to cause EMT. Our results also demonstrate that the morphological progression in membrane disruption has an effect on the number of cells becoming invasive, with epithelial layers broken into clusters hindering the further exodus of cells. The results reveal the quantitative interplay between two key parameters involved in EMT and suggest potential avenues for further exploration of a systems level understanding of EMT.

Computational model for migration of a cell cluster in three-dimensional matrices.

This paper presents a first forced-based dynamics computer model of a cell cluster moving collectively in a 3D environment mimicking the extracellular matrix. In general, collective cell migration is a relevant part of the mechanisms for tissue repair, morphogenesis, and cancer invasion. Particularly in cancer, invasion occurs through multicellular 3D strands as well as collective cell clusters. Because cancer is a slow process, these clusters have not been carefully observed. However, the prevalence of this mechanism of cell locomotion makes it a target for study. Due to the different molecular mechanisms involved in this movement and the complex relations among them, a computer model would be of great use. The model presented here takes into account ligand concentration, matrix metalloproteinase activity, and cluster geometry based on experimental findings and experimentally validated single cell computer models; thus incorporating implicitly different underlying molecular properties. The velocity profiles of the cell clusters were recorded and analyzed. In particular seven different profiles are observed based on different participation of ligands, proteinases, and mechanical forces involved. The model is successful in showing potential effects of altering single variables in a system of cells in motion. Special emphasis is made on future directions for improvement and the variables to be potentially modulated to simulate particular physiological conditions.