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Endothelial cell capture of heparin-binding growth factors under flow.

Zhao B, Zhang C, Forsten-Williams K, Zhang J, Fannon M - PLoS Comput. Biol. (2010)

Bottom Line: 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.Several other key parameters were investigated with the coupling between receptors and proteoglycans shown to have a critical impact on successful capture.

View Article: PubMed Central - PubMed

Affiliation: Department of Ophthalmology and Visual Sciences, University of Kentucky, Lexington, Kentucky, United States of America.

ABSTRACT
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.

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Simulations predict cell surface density impacts FGF-2 retention.Simulations were run for FGF-2 (1ng) added to the system (30% non-specific loss) at 0.63 mL/min pulsatile flow (1.26 mm/sec) for 5 min. (A) Cells expressed either 1×104 FGFR/cell and variable densities of HSPG (○) or 2.5×105 HSPG/cell and variable densities of FGFR (•) on the cell-lined hollow fibers. The amount retained within the system (bound, internalized, and fluid phase FGF-2) is shown. (B) Cells expressed 1×104 FGFR/cell and 2×103 (•,○), 2×104 (▪,□), or 2×105 (▴,▵) HSPG/cell on the cell-lined hollow fibers and simulation results correspond to entrance cell value at a given time. Filled symbols correspond to % of FGF-2 bound to FGFR which are simultaneously bound to HSPG and open symbols correspond to the #/cell of FGF-2 bound to FGFR and HSPG.
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pcbi-1000971-g011: Simulations predict cell surface density impacts FGF-2 retention.Simulations were run for FGF-2 (1ng) added to the system (30% non-specific loss) at 0.63 mL/min pulsatile flow (1.26 mm/sec) for 5 min. (A) Cells expressed either 1×104 FGFR/cell and variable densities of HSPG (○) or 2.5×105 HSPG/cell and variable densities of FGFR (•) on the cell-lined hollow fibers. The amount retained within the system (bound, internalized, and fluid phase FGF-2) is shown. (B) Cells expressed 1×104 FGFR/cell and 2×103 (•,○), 2×104 (▪,□), or 2×105 (▴,▵) HSPG/cell on the cell-lined hollow fibers and simulation results correspond to entrance cell value at a given time. Filled symbols correspond to % of FGF-2 bound to FGFR which are simultaneously bound to HSPG and open symbols correspond to the #/cell of FGF-2 bound to FGFR and HSPG.

Mentions: Cells typically express significantly more HSPG than FGFR and we next asked how varying the cell surface densities of these binding sites would impact FGF-2 capture. In the absence of FGFR, a typical density of HSPG in our cartridge (2.5×105 #/cell) resulted in significant binding of FGF-2 in the absence of FGFR that is essentially doubled when FGFR density is 1×106 #/cell, a two-fold increase in binding sites (Figure 11A). FGFR typically are expressed at densities of approximately 1×104 #/cell thereby keeping the primary signaling receptor at a controlled level. This is predicted to result in an order of magnitude less overall FGF-2 binding than that found at typical HSPG levels but which is increased in a similar way when HSPG are present. The combination of the two surface binding sites (FGFR and HSPG) is critical. For example, when 1.0×104 FGFR are present, the retained FGF-2 is increased to ∼0.25ng from a value of ∼0.14ng without the FGFR. Looking at cell binding at the entrance of the cell-lined hollow fiber as a function of time after FGF-2 has been introduced with constant FGFR (1×104 #/cell) and variable HSPG, we found that there was a significant increase in bound FGF-2 at the higher HSPG (1×105 #/cell) when compared to the lower values and that the FGFR binding was essentially all coupled to HSPG (Figure 11B). When there are fewer HSPG, there is a lower percentage of coupled binding at least at earlier times as well as lower overall FGFR complexes.


Endothelial cell capture of heparin-binding growth factors under flow.

Zhao B, Zhang C, Forsten-Williams K, Zhang J, Fannon M - PLoS Comput. Biol. (2010)

Simulations predict cell surface density impacts FGF-2 retention.Simulations were run for FGF-2 (1ng) added to the system (30% non-specific loss) at 0.63 mL/min pulsatile flow (1.26 mm/sec) for 5 min. (A) Cells expressed either 1×104 FGFR/cell and variable densities of HSPG (○) or 2.5×105 HSPG/cell and variable densities of FGFR (•) on the cell-lined hollow fibers. The amount retained within the system (bound, internalized, and fluid phase FGF-2) is shown. (B) Cells expressed 1×104 FGFR/cell and 2×103 (•,○), 2×104 (▪,□), or 2×105 (▴,▵) HSPG/cell on the cell-lined hollow fibers and simulation results correspond to entrance cell value at a given time. Filled symbols correspond to % of FGF-2 bound to FGFR which are simultaneously bound to HSPG and open symbols correspond to the #/cell of FGF-2 bound to FGFR and HSPG.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC2965741&req=5

pcbi-1000971-g011: Simulations predict cell surface density impacts FGF-2 retention.Simulations were run for FGF-2 (1ng) added to the system (30% non-specific loss) at 0.63 mL/min pulsatile flow (1.26 mm/sec) for 5 min. (A) Cells expressed either 1×104 FGFR/cell and variable densities of HSPG (○) or 2.5×105 HSPG/cell and variable densities of FGFR (•) on the cell-lined hollow fibers. The amount retained within the system (bound, internalized, and fluid phase FGF-2) is shown. (B) Cells expressed 1×104 FGFR/cell and 2×103 (•,○), 2×104 (▪,□), or 2×105 (▴,▵) HSPG/cell on the cell-lined hollow fibers and simulation results correspond to entrance cell value at a given time. Filled symbols correspond to % of FGF-2 bound to FGFR which are simultaneously bound to HSPG and open symbols correspond to the #/cell of FGF-2 bound to FGFR and HSPG.
Mentions: Cells typically express significantly more HSPG than FGFR and we next asked how varying the cell surface densities of these binding sites would impact FGF-2 capture. In the absence of FGFR, a typical density of HSPG in our cartridge (2.5×105 #/cell) resulted in significant binding of FGF-2 in the absence of FGFR that is essentially doubled when FGFR density is 1×106 #/cell, a two-fold increase in binding sites (Figure 11A). FGFR typically are expressed at densities of approximately 1×104 #/cell thereby keeping the primary signaling receptor at a controlled level. This is predicted to result in an order of magnitude less overall FGF-2 binding than that found at typical HSPG levels but which is increased in a similar way when HSPG are present. The combination of the two surface binding sites (FGFR and HSPG) is critical. For example, when 1.0×104 FGFR are present, the retained FGF-2 is increased to ∼0.25ng from a value of ∼0.14ng without the FGFR. Looking at cell binding at the entrance of the cell-lined hollow fiber as a function of time after FGF-2 has been introduced with constant FGFR (1×104 #/cell) and variable HSPG, we found that there was a significant increase in bound FGF-2 at the higher HSPG (1×105 #/cell) when compared to the lower values and that the FGFR binding was essentially all coupled to HSPG (Figure 11B). When there are fewer HSPG, there is a lower percentage of coupled binding at least at earlier times as well as lower overall FGFR complexes.

Bottom Line: 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.Several other key parameters were investigated with the coupling between receptors and proteoglycans shown to have a critical impact on successful capture.

View Article: PubMed Central - PubMed

Affiliation: Department of Ophthalmology and Visual Sciences, University of Kentucky, Lexington, Kentucky, United States of America.

ABSTRACT
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.

Show MeSH