Endothelial Cell Capture of Heparin-Binding Growth Factors under Flow

Circulation is an important delivery method for both natural and synthetic molecules, but microenvironment interactions, regulated by endothelial cells and critical to the molecule's fate, are difficult to interpret using traditional approaches. In this work, we analyzed and predicted growth factor capture under flow using computer modeling and a three-dimensional experimental approach that includes pertinent circulation characteristics such as pulsatile flow, competing binding interactions, and limited bioavailability. An understanding of the controlling features of this process was desired. The experimental module consisted of a bioreactor with synthetic endothelial-lined hollow fibers under flow. The physical design of the system was incorporated into the model parameters. The heparin-binding growth factor fibroblast growth factor-2 (FGF-2) was used for both the experiments and simulations. Our computational model was composed of three parts: (1) media flow equations, (2) mass transport equations and (3) cell surface reaction equations. The model is based on the flow and reactions within a single hollow fiber and was scaled linearly by the total number of fibers for comparison with experimental results. Our model predicted, and experiments confirmed, that removal of heparan sulfate (HS) from the system would result in a dramatic loss of binding by heparin-binding proteins, but not by proteins that do not bind heparin. The model further predicted a significant loss of bound protein at flow rates only slightly higher than average capillary flow rates, corroborated experimentally, suggesting that the probability of capture in a single pass at high flow rates is extremely low. Several other key parameters were investigated with the coupling between receptors and proteoglycans shown to have a critical impact on successful capture. The combined system offers opportunities to examine circulation capture in a straightforward quantitative manner that should prove advantageous for biologicals or drug delivery investigations

COMPUTER SIMULATION OF A HOLLOW-FIBER BIOREACTOR: HEPARAN REGULATED GROWTH FACTORS-RECEPTORS BINDING AND DISSOCIATION ANALYSIS

This thesis demonstrates the use of numerical simulation in predicting the behavior of proteins in a flow environment. A novel convection-diffusion-reaction computational model is first introduced to simulate fibroblast growth factor (FGF-2) binding to its receptor (FGFR) on cell surfaces and regulated by heparan sulfate proteoglycan (HSPG) under flow in a bioreactor. The model includes three parts: (1) the flow of medium using incompressible Navier-Stokes equations; (2) the mass transport of FGF-2 using convection-diffusion equations; and (3) the cell surface binding using chemical kinetics. The model consists of a set of coupled nonlinear partial differential equations (PDEs) for flow and mass transport, and a set of coupled nonlinear ordinary differential equations (ODEs) for binding kinetics. To handle pulsatile flow, several assumptions are made including neglecting the entrance effects and an approximate analytical solution for axial velocity within the fibers is obtained. To solve the time-dependent mass transport PDEs, the second order implicit Euler method by finite volume discretization is used. The binding kinetics ODEs are stiff and solved by an ODE solver (CVODE) using Newton’s backward differencing formula. To obtain a reasonable accuracy of the biochemical reactions on cell surfaces, a uniform mesh is used. This basic model can be used to simulate any growth factor-receptor binding on cell surfaces on the wall of fibers in a bioreactor, simply by replacing binding kinetics ODEs. Circulation is an important delivery method for natural and synthetic molecules, but microenvironment interactions, regulated by endothelial cells and critical to the molecule’s fate, are difficult to interpret using traditional approaches. Growth factor capture under flow is analyzed and predicted using computer modeling mentioned above and a three-dimensional experimental approach that includes pertinent circulation characteristics such as pulsatile flow, competing binding interactions, and limited bioavailability. An understanding of the controlling features of this process is desired. The experimental module consists of a bioreactor with synthetic endotheliallined hollow fibers under flow. The physical design of the system is incorporated into the model parameters. FGF-2 is used for both the experiments and simulations. The computational model is based on the flow and reactions within a single hollow fiber and is scaled linearly by the total number of fibers for comparison with experimental results. The model predicts, and experiments confirm, that removal of heparan sulfate (HS) from the system will result in a dramatic loss of binding by heparin-binding proteins, but not by proteins that do not bind heparin. The model further predicts a significant loss of bound protein at flow rates only slightly higher than average capillary flow rates, corroborated experimentally, suggesting that the probability of capture in a single pass at high flow rates is extremely low. Several other key parameters are investigated with the coupling between receptors and proteoglycans shown to have a critical impact on successful capture. The combined system offers opportunities to examine circulation capture in a straightforward quantitative manner that should prove advantageous for biological or drug delivery investigations. For some complicated binding systems, where there are more growth factors or proteins with competing binding among them moving through hollow fibers of a bioreactor coupled with biochemical reactions on cell surfaces on the wall of fibers, a complex model is deduced from the basic model mentioned above. The fluid flow is also modeled by incompressible Navier-Stokes equations as mentioned in the basic model, the biochemical reactions in the fluid and on the cell surfaces are modeled by two distinctive sets of coupled nonlinear ordinary differential equations, and the mass transports of different growth factors or complexes are modeled separately by different sets of coupled nonlinear partial differential equations. To solve this computationally intensive system, parallel algorithms are devised, in which all the numerical computations are solved in parallel, including the discretization of mass transport equations and the linear system solver Stone’s Implicit Procedure (SIP). A parallel SIP solver is designed, in which pipeline technique is used for LU factorization and an overlapped Jacobi iteration technique is chosen for forward and backward substitutions. For solving binding equations ODEs in the fluid and on cell surfaces, a parallel scheme combined with a sequential CVODE solver is used. The simulation results are obtained to demonstrate the computational efficiency of the algorithms and further experiments need to be conducted to verify the predictions

Fibroblast growth factor 2-antagonist activity of a long-pentraxin 3-derived antiangiogenic pentapeptide.

Fibroblast growth factor-2 (FGF2) plays a major role in angiogenesis. The pattern recognition receptor long-pentraxin 3 (PTX3) inhibits the angiogenic activity of FGF2. To identify novel FGF2-antagonistic peptide(s), four acetylated (Ac) synthetic peptides overlapping the FGF2-binding region PTX3-(97-110) were assessed for their FGF2-binding capacity. Among them, the shortest pentapeptide Ac-ARPCA-NH(2) (PTX3-[100-104]) inhibits the interaction of FGF2 with PTX3 immobilized to a BIAcore sensorchip and suppresses FGF2-dependent proliferation in endothelial cells, without affecting the activity of unrelated mitogens. Also, Ac-ARPCA-NH(2) inhibits angiogenesis triggered by FGF2 or by tumorigenic FGF2-overexpressing murine endothelial cells in chick and zebrafish embryos, respectively. Accordingly, the peptide hampers the binding of FGF2 to Chinese Hamster ovary cells overexpressing the tyrosine-kinase FGF receptor-1 (FGFR1) and to recombinant FGFR1 immobilized to a BIAcore sensorchip without affecting heparin interaction. In all the assays the mutated Ac-ARPSA-NH(2) peptide was ineffective. In keeping with the observation that hydrophobic interactions dominate the interface between FGF2 and the FGF-binding domain of the Ig-like loop D2 of FGFR1, amino acid substitutions in Ac-ARPCA-NH(2) and saturation transfer difference-nuclear magnetic resonance analysis of its mode of interaction with FGF2 implicate the hydrophobic methyl groups of the pentapeptide in FGF2 binding. These results will provide the basis for the design of novel PTX3-derived anti-angiogenic FGF2 antagonists

Fibroblast growth factor-2 interaction with vascular cells and basement membrane under physiological fluid flow and diabetic hyperglycemia

Diabetes is a debilitating disease with a significant impact on global health. People with diabetes experience early and accelerated atherosclerosis and are at increased risk of restenosis. Though the pathogenesis of atherosclerosis and restenosis are complex, endothelial cells (EC), smooth muscle cells (SMC), and basement membrane (BM) play important roles in lesion development. Healthy EC regulate SMC function, but EC become dysfunctional in hyperglycemia or on glycated collagen, which may alter SMC regulation. Fibroblast growth factor-2 (FGF2), which is produced and released by EC and binds to heparan sulfate proteoglycans in the endothelial BM, may be critical to loss of vascular homeostasis.Experimental and computational models of BM-FGF2 binding kinetics under static conditions are well established in the literature but remain largely unexplored under flow. To investigate BM-FGF2 binding kinetics under fluid flow, BM-FGF2 equilibrium and associative binding were measured at various shear stresses. Surprisingly, BM-bound FGF2 increased up to a physiological arterial shear stress of 25 dynes/cm2, after which it decreased. These data suggest that FGF2 binding varies with shear stress possibly by a catch-slip mechanism, where applied force changes the dissociation constant to either promote (―catch‖) or reduce (―slip‖) binding. A computational model of BM-FGF2 interaction incorporating convective-diffusive transport and a surface binding reaction was also created.BM-bound FGF2 is released over time, after which FGF2 affects both EC and SMC. EC and SMC proliferation and intracellular signaling in response to FGF2 were investigated under hyperglycemic conditions, including for cells grown on glycated collagen or in high glucose media. Glycated collagen did not change EC proliferation or pERK signaling, however pAkt signaling decreased on glycated collagen. This suggests that glycated collagen may decrease FGF2 promotion of EC survival. SMC proliferation decreased on glycated collagen, while SMC cultured with FGF2 showed no difference in growth.Improved understanding of BM-FGF2 binding with flow serves as an initial step in a comprehensive model of FGF2 binding to BM and cells under fluid flow. Together with the observed altered FGF2 effects on vascular cells, these data motivate the development of improved growth factor treatments under physiological and disease conditions.M.S., Biomedical Engineering -- Drexel University, 201

Computational Model of Vascular Endothelial Growth Factor Spatial Distribution in Muscle and Pro-Angiogenic Cell Therapy

Members of the vascular endothelial growth factor (VEGF) family of proteins are critical regulators of angiogenesis. VEGF concentration gradients are important for activation and chemotactic guidance of capillary sprouting, but measurement of these gradients in vivo is not currently possible. We have constructed a biophysically and molecularly detailed computational model to study microenvironmental transport of two isoforms of VEGF in rat extensor digitorum longus skeletal muscle under in vivo conditions. Using parameters based on experimental measurements, the model includes: VEGF secretion from muscle fibers; binding to the extracellular matrix; binding to and activation of endothelial cell surface VEGF receptors; and internalization. For 2-D cross sections of tissue, we analyzed predicted VEGF distributions, gradients, and receptor binding. Significant VEGF gradients (up to 12% change in VEGF concentration over 10 μm) were predicted in resting skeletal muscle with uniform VEGF secretion, due to non-uniform capillary distribution. These relative VEGF gradients were not sensitive to extracellular matrix composition, or to the overall VEGF expression level, but were dependent on VEGF receptor density and affinity, and internalization rate parameters. VEGF upregulation in a subset of fibers increased VEGF gradients, simulating transplantation of pro-angiogenic myoblasts, a possible therapy for ischemic diseases. The number and relative position of overexpressing fibers determined the VEGF gradients and distribution of VEGF receptor activation. With total VEGF expression level in the tissue unchanged, concentrating overexpression into a small number of adjacent fibers can increase the number of capillaries activated. The VEGF concentration gradients predicted for resting muscle (average 3% VEGF/10 μm) is sufficient for cellular sensing; the tip cell of a vessel sprout is approximately 50 μm long. The VEGF gradients also result in heterogeneity in the activation of blood vessel VEGF receptors. This first model of VEGF tissue transport and heterogeneity provides a platform for the design and evaluation of therapeutic approaches

Quantifying the Proteolytic Release of Extracellular Matrix-Sequestered VEGF with a Computational Model

BACKGROUND: VEGF proteolysis by plasmin or matrix metalloproteinases (MMPs) is believed to play an important role in regulating vascular patterning in vivo by releasing VEGF from the extracellular matrix (ECM). However, a quantitative understanding of the kinetics of VEGF cleavage and the efficiency of cell-mediated VEGF release is currently lacking. To address these uncertainties, we develop a molecular-detailed quantitative model of VEGF proteolysis, used here in the context of an endothelial sprout. METHODOLOGY AND FINDINGS: To study a cell's ability to cleave VEGF, the model captures MMP secretion, VEGF-ECM binding, VEGF proteolysis from VEGF165 to VEGF114 (the expected MMP cleavage product of VEGF165) and VEGF receptor-mediated recapture. Using experimental data, we estimated the effective bimolecular rate constant of VEGF165 cleavage by plasmin to be 328 M(-1) s(-1) at 25 degrees C, which is relatively slow compared to typical MMP-ECM proteolysis reactions. While previous studies have implicated cellular proteolysis in growth factor processing, we show that single cells do not individually have the capacity to cleave VEGF to any appreciable extent (less than 0.1% conversion). In addition, we find that a tip cell's receptor system will not efficiently recapture the cleaved VEGF due to an inability of cleaved VEGF to associate with Neuropilin-1. CONCLUSIONS: Overall, VEGF165 cleavage in vivo is likely to be mediated by the combined effect of numerous cells, instead of behaving in a single-cell-directed, autocrine manner. We show that heparan sulfate proteoglycans (HSPGs) potentiate VEGF cleavage by increasing the VEGF clearance time in tissues. In addition, we find that the VEGF-HSPG complex is more sensitive to proteases than is soluble VEGF, which may imply its potential relevance in receptor signaling. Finally, according to our calculations, experimentally measured soluble protease levels are approximately two orders of magnitude lower than that needed to reconcile levels of VEGF cleavage seen in pathological situations

Module-based multiscale simulation of angiogenesis in skeletal muscle

<p>Abstract</p> <p>Background</p> <p>Mathematical modeling of angiogenesis has been gaining momentum as a means to shed new light on the biological complexity underlying blood vessel growth. A variety of computational models have been developed, each focusing on different aspects of the angiogenesis process and occurring at different biological scales, ranging from the molecular to the tissue levels. Integration of models at different scales is a challenging and currently unsolved problem.</p> <p>Results</p> <p>We present an object-oriented module-based computational integration strategy to build a multiscale model of angiogenesis that links currently available models. As an example case, we use this approach to integrate modules representing microvascular blood flow, oxygen transport, vascular endothelial growth factor transport and endothelial cell behavior (sensing, migration and proliferation). Modeling methodologies in these modules include algebraic equations, partial differential equations and agent-based models with complex logical rules. We apply this integrated model to simulate exercise-induced angiogenesis in skeletal muscle. The simulation results compare capillary growth patterns between different exercise conditions for a single bout of exercise. Results demonstrate how the computational infrastructure can effectively integrate multiple modules by coordinating their connectivity and data exchange. Model parameterization offers simulation flexibility and a platform for performing sensitivity analysis.</p> <p>Conclusions</p> <p>This systems biology strategy can be applied to larger scale integration of computational models of angiogenesis in skeletal muscle, or other complex processes in other tissues under physiological and pathological conditions.</p

Functional studies on sulphation status of heparan sulphate in breast non-tumourigenic epithelial and cancer cells

Ph.DDOCTOR OF PHILOSOPH