Emergent mechanical control of vascular morphogenesis.

Vascularization is driven by morphogen signals and mechanical cues that coordinately regulate cellular force generation, migration, and shape change to sculpt the developing vascular network. However, it remains unclear whether developing vasculature actively regulates its own mechanical properties to achieve effective vascularization. We engineered tissue constructs containing endothelial cells and fibroblasts to investigate the mechanics of vascularization. Tissue stiffness increases during vascular morphogenesis resulting from emergent interactions between endothelial cells, fibroblasts, and ECM and correlates with enhanced vascular function. Contractile cellular forces are key to emergent tissue stiffening and synergize with ECM mechanical properties to modulate the mechanics of vascularization. Emergent tissue stiffening and vascular function rely on mechanotransduction signaling within fibroblasts, mediated by YAP1. Mouse embryos lacking YAP1 in fibroblasts exhibit both reduced tissue stiffness and develop lethal vascular defects. Translating our findings through biology-inspired vascular tissue engineering approaches will have substantial implications in regenerative medicine.

On-chip human microvasculature assay for visualization and quantification of tumor cell extravasation dynamics.

Distant metastasis, which results in >90% of cancer-related deaths, is enabled by hematogenous dissemination of tumor cells via the circulation. This requires the completion of a sequence of complex steps including transit, initial arrest, extravasation, survival and proliferation. Increased understanding of the cellular and molecular players enabling each of these steps is key to uncovering new opportunities for therapeutic intervention during early metastatic dissemination. As a protocol extension, this article describes an adaptation to our existing protocol describing a microfluidic platform that offers additional applications. This protocol describes an in vitro model of the human microcirculation with the potential to recapitulate discrete steps of early metastatic seeding, including arrest, transendothelial migration and early micrometastases formation. The microdevice features self-organized human microvascular networks formed over 4-5 d, after which the tumor can be perfused and extravasation events are easily tracked over 72 h via standard confocal microscopy. Contrary to most in vivo and in vitro extravasation assays, robust and rapid scoring of extravascular cells, combined with high-resolution imaging, can be easily achieved because of the confinement of the vascular network to one plane close to the surface of the device. This renders extravascular cells clearly distinct and allows tumor cells of interest to be identified quickly as compared with those in thick tissues. The ability to generate large numbers of devices (∼36) per experiment further allows for highly parametric studies, which are required when testing multiple genetic or pharmacological perturbations. This is coupled with the capability for live tracking of single-cell extravasation events, allowing both tumor and endothelial morphological dynamics to be observed in high detail with a moderate number of data points.

Cell Invasion Dynamics into a Three Dimensional Extracellular Matrix Fibre Network.

The dynamics of filopodia interacting with the surrounding extracellular matrix (ECM) play a key role in various cell-ECM interactions, but their mechanisms of interaction with the ECM in 3D environment remain poorly understood. Based on first principles, here we construct an individual-based, force-based computational model integrating four modules of 1) filopodia penetration dynamics; 2) intracellular mechanics of cellular and nuclear membranes, contractile actin stress fibers, and focal adhesion dynamics; 3) structural mechanics of ECM fiber networks; and 4) reaction-diffusion mass transfers of seven biochemical concentrations in related with chemotaxis, proteolysis, haptotaxis, and degradation in ECM to predict dynamic behaviors of filopodia that penetrate into a 3D ECM fiber network. The tip of each filopodium crawls along ECM fibers, tugs the surrounding fibers, and contracts or retracts depending on the strength of the binding and the ECM stiffness and pore size. This filopodium-ECM interaction is modeled as a stochastic process based on binding kinetics between integrins along the filopodial shaft and the ligands on the surrounding ECM fibers. This filopodia stochastic model is integrated into migratory dynamics of a whole cell in order to predict the cell invasion into 3D ECM in response to chemotaxis, haptotaxis, and durotaxis cues. Predicted average filopodia speed and that of the cell membrane advance agreed with experiments of 3D HUVEC migration at r(2) > 0.95 for diverse ECMs with different pore sizes and stiffness.

Human vascular tissue models formed from human induced pluripotent stem cell derived endothelial cells.

Here we describe a strategy to model blood vessel development using a well-defined induced pluripotent stem cell-derived endothelial cell type (iPSC-EC) cultured within engineered platforms that mimic the 3D microenvironment. The iPSC-ECs used here were first characterized by expression of endothelial markers and functional properties that included VEGF responsiveness, TNF-α-induced upregulation of cell adhesion molecules (MCAM/CD146; ICAM1/CD54), thrombin-dependent barrier function, shear stress-induced alignment, and 2D and 3D capillary-like network formation in Matrigel. The iPSC-ECs also formed 3D vascular networks in a variety of engineering contexts, yielded perfusable, interconnected lumen when co-cultured with primary human fibroblasts, and aligned with flow in microfluidics devices. iPSC-EC function during tubule network formation, barrier formation, and sprouting was consistent with that of primary ECs, and the results suggest a VEGF-independent mechanism for sprouting, which is relevant to therapeutic anti-angiogenesis strategies. Our combined results demonstrate the feasibility of using a well-defined, stable source of iPSC-ECs to model blood vessel formation within a variety of contexts using standard in vitro formats.

Generation of 3D functional microvascular networks with human mesenchymal stem cells in microfluidic systems.

The generation of functional microvascular networks is critical for the development of advanced in vitro models to replicate pathophysiological conditions. Mural cells provide structural support to blood vessels and secrete biomolecules contributing to vessel stability and functionality. We investigated the role played by two endothelium-related molecules, angiopoietin (Ang-1) and transforming growth factor (TGF-ß1), on bone marrow-derived human mesenchymal stem cell (BM-hMSC) phenotypic transition toward a mural cell lineage, both in monoculture and in direct contact with human endothelial cells (ECs), within 3D fibrin gels in microfluidic devices. We demonstrated that the effect of these molecules is dependent on direct heterotypic cell-cell contact. Moreover, we found a significant increase in the amount of α-smooth muscle actin in microvascular networks with added VEGF and TGF-ß1 or VEGF and Ang-1 compared to networks with added VEGF alone. However, the addition of TGF-ß1 generated a non-interconnected microvasculature, while Ang-1 promoted functional networks, confirmed by microsphere perfusion and permeability measurements. The presence of mural cell-like BM-hMSCs coupled with the addition of Ang-1 increased the number of network branches and reduced mean vessel diameter compared to EC only vasculature. This system has promising applications in the development of advanced in vitro models to study complex biological phenomena involving functional and perfusable microvascular networks.

Control of perfusable microvascular network morphology using a multiculture microfluidic system.

The mechanical and biochemical microenvironment influences the morphological characteristics of microvascular networks (MVNs) formed by endothelial cells (ECs) undergoing the process of vasculogenesis. The objective of this study was to quantify the role of individual factors in determining key network parameters in an effort to construct a set of design principles for engineering vascular networks with prescribed morphologies. To achieve this goal, we developed a multiculture microfluidic platform enabling precise control over paracrine signaling, cell-seeding densities, and hydrogel mechanical properties. Human umbilical vein endothelial cells (HUVECs) were seeded in fibrin gels and cultured alongside human lung fibroblasts (HLFs). The engineered vessels formed in our device contained patent, perfusable lumens. Communication between the two cell types was found to be critical in avoiding network regression and maintaining stable morphology beyond 4 days. The number of branches, average branch length, percent vascularized area, and average vessel diameter were found to depend uniquely on several input parameters. Importantly, multiple inputs were found to control any given output network parameter. For example, the vessel diameter can be decreased either by applying angiogenic growth factors--vascular endothelial growth factor (VEGF) and sphingosine-1-phsophate (S1P)--or by increasing the fibrinogen concentration in the hydrogel. These findings introduce control into the design of MVNs with specified morphological properties for tissue-specific engineering applications.

Mechanisms of tumor cell extravasation in an in vitro microvascular network platform.

A deeper understanding of the mechanisms of tumor cell extravasation is essential in creating therapies that target this crucial step in cancer metastasis. Here, we use a microfluidic platform to study tumor cell extravasation from in vitro microvascular networks formed via vasculogenesis. We demonstrate tight endothelial cell-cell junctions, basement membrane deposition and physiological values of vessel permeability. Employing our assay, we demonstrate impaired endothelial barrier function and increased extravasation efficiency with inflammatory cytokine stimulation, as well as positive correlations between the metastatic potentials of MDA-MB-231, HT-1080, MCF-10A and their extravasation capabilities. High-resolution time-lapse microscopy reveals the highly dynamic nature of extravasation events, beginning with thin tumor cell protrusions across the endothelium followed by extrusion of the remainder of the cell body through the formation of small (~1 µm) openings in the endothelial barrier which grows in size (~8 µm) to allow for nuclear transmigration. No disruption to endothelial cell-cell junctions is discernible at 60×, or by changes in local barrier function after completion of transmigration. Tumor transendothelial migration efficiency is significantly higher in trapped cells compared to non-trapped adhered cells, and in cell clusters versus single tumor cells.

Engineering of in vitro 3D capillary beds by self-directed angiogenic sprouting.

In recent years, microfluidic systems have been used to study fundamental aspects of angiogenesis through the patterning of single-layered, linear or geometric vascular channels. In vivo, however, capillaries exist in complex, three-dimensional (3D) networks, and angiogenic sprouting occurs with a degree of unpredictability in all x,y,z planes. The ability to generate capillary beds in vitro that can support thick, biological tissues remains a key challenge to the regeneration of vital organs. Here, we report the engineering of 3D capillary beds in an in vitro microfluidic platform that is comprised of a biocompatible collagen I gel supported by a mechanical framework of alginate beads. The engineered vessels have patent lumens, form robust ~1.5 mm capillary networks across the devices, and support the perfusion of 1 µm fluorescent beads through them. In addition, the alginate beads offer a modular method to encapsulate and co-culture cells that either promote angiogenesis or require perfusion for cell viability in engineered tissue constructs. This laboratory-constructed vascular supply may be clinically significant for the engineering of capillary beds and higher order biological tissues in a scalable and modular manner.

Confidence intervals for concentration and brightness from fluorescence fluctuation measurements.

The theory of photon count histogram (PCH) analysis describes the distribution of fluorescence fluctuation amplitudes due to populations of fluorophores diffusing through a focused laser beam and provides a rigorous framework through which the brightnesses and concentrations of the fluorophores can be determined. In practice, however, the brightnesses and concentrations of only a few components can be identified. Brightnesses and concentrations are determined by a nonlinear least-squares fit of a theoretical model to the experimental PCH derived from a record of fluorescence intensity fluctuations. The χ(2) hypersurface in the neighborhood of the optimum parameter set can have varying degrees of curvature, due to the intrinsic curvature of the model, the specific parameter values of the system under study, and the relative noise in the data. Because of this varying curvature, parameters estimated from the least-squares analysis have varying degrees of uncertainty associated with them. There are several methods for assigning confidence intervals to the parameters, but these methods have different efficacies for PCH data. Here, we evaluate several approaches to confidence interval estimation for PCH data, including asymptotic standard error, likelihood joint-confidence region, likelihood confidence intervals, skew-corrected and accelerated bootstrap (BCa), and Monte Carlo residual resampling methods. We study these with a model two-dimensional membrane system for simplicity, but the principles are applicable as well to fluorophores diffusing in three-dimensional solution. Using simulated fluorescence fluctuation data, we find the BCa method to be particularly well-suited for estimating confidence intervals in PCH analysis, and several other methods to be less so. Using the BCa method and additional simulated fluctuation data, we find that confidence intervals can be reduced dramatically for a specific non-Gaussian beam profile.