Glycosaminoglycans affect endothelial to mesenchymal transformation, proliferation, and calcification in a 3D model of aortic valve disease

Abstract

Calcific nodules form in the fibrosa layer of the aortic valve in calcific aortic valve disease (CAVD). Glycosaminoglycans (GAGs), which are normally found in the valve spongiosa, are located local to calcific nodules. Previous work suggests that GAGs induce endothelial to mesenchymal transformation (EndMT), a phenomenon described by endothelial cells' loss of the endothelial markers, gaining of migratory properties, and expression of mesenchymal markers such as alpha smooth muscle actin (α-SMA). EndMT is known to play roles in valvulogenesis and may provide a source of activated fibroblast with a potential role in CAVD progression. In this study, a 3D collagen hydrogel co-culture model of the aortic valve fibrosa was created to study the role of EndMT-derived activated valvular interstitial cell behavior in CAVD progression. Porcine aortic valve interstitial cells (PAVIC) and porcine aortic valve endothelial cells (PAVEC) were cultured within collagen I hydrogels containing the GAGs chondroitin sulfate (CS) or hyaluronic acid (HA). The model was used to study alkaline phosphatase (ALP) enzyme activity, cellular proliferation and matrix invasion, protein expression, and calcific nodule formation of the resident cell populations. CS and HA were found to alter ALP activity and increase cell proliferation. CS increased the formation of calcified nodules without the addition of osteogenic culture medium. This model has applications in the improvement of bioprosthetic valves by making replacements more micro-compositionally dynamic, as well as providing a platform for testing new pharmaceutical treatments of CAVD.

Keywords: calcific aortic valve disease; chondroitin sulfate; fibrosa layer; hyaluronic acid; mechanobiology.

FIGURE 1

Chondroitin sulfate promotes calcific nodule formation and glycosaminoglycans (GAGs) do not produce increased alkaline phosphatase (ALP) activity. (A) ALP quantification in mg p-nitrophenol per mg protein (mg/mg) of digested hydrogels. n = 12. (B) Quantification of ARS-stained digested hydrogel samples. n = 11. (C) ARS stain area processed with ImageJ. n = 5. Data represented as mean ± SEM. (D–G) Brightfield images of intact ARS-stained hydrogels using a Nikon Eclipse Ts2 at 20×. Statistical significance was determined with a non-parametric Kruskal–Wallis test with Dunn’s post-hoc test. *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001. Scale bars = 20 μm.

FIGURE 2

Glycosaminoglycans (GAGs) conditions express higher α-SMA per unit DNA than controls. (A–D) Confocal images of intact hydrogels co-stained for α-SMA (green), PECAM-1 (red), and DNA (blue) after 14 days of growth. Scale bars = 50 μm. (E) α-SMA expression quantified using a MATLAB script, represented as pixels of α-SMA (green signal) per pixels DNA (blue signal). Data represented as mean ± SEM. Statistical significance was determined with a non-parametric Kruskal–Wallis test with Dunn’s post-hoc test. *p < 0.05 and **p < 0.01. n = 5.

FIGURE 3

Flow cytometry analysis of protein expression shows an increase in transformed cells in glycosaminoglycans (GAGs) conditions, and an increase in activated interstitial cells in the presence of chondroitin sulfate (CS). Following 14 days of growth, hydrogels were degraded, and isolated cells were processed using a BD FACS Aria II flow cytometer. Cells were stained with α-SMA (Alexa Fluor^® 488) and PECAM-1 (Alexa Fluor^® 647). (A) Endothelial cells (positive for PECAM-1 and negative for α-SMA). (B) Cells that have undergone transformation (positive for both PECAM-1 and α-SMA). (C) Interstitial cells (negative for PECAM-1 and α-SMA) and (D) Activated interstitial cells (negative for PECAM-1 and positive for a-SMA). Data represented as mean ± SEM. Statistical significance was determined with a non-parametric Kruskal–Wallis test with Dunn’s post-hoc test. *p < 0.05. n = 3.

FIGURE 4

Glycosaminoglycans (GAGs) conditions promote cellular invasion. (A–D) Z-stack confocal images taken with a Zeiss LSM 880 Two-Photon confocal microscope. Interstitial cells were stained with CellTrace CSFE-Green (green) and endothelial cells with CellTrace Far-Red (red) prior to hydrogel seeding. Red cells that have migrated from the cell monolayer are classified as invaded. (E–H) Examples of MATLAB processed z-stack images used to quantify (I) the number of invaded cells and (J) the average distance each cell travelled. Data represented as mean ± SEM. n = 4. Statistical significance was determined with a non-parametric Kruskal–Wallis test with Dunn’s post hoc test. *p < 0.05, ^**p < 0.01, ^***p < 0.001, ^****p < 0.0001. (K) Average distance invaded plotted against the number of cells invaded. Non-parametric Spearman’s correlation was estimated to evaluate if there was linear association (Spearman’s r = 0.63, with P-value = 0.009). (L) Example of the invasion analysis and centroid tracking. Blue stars are identified cells, and red circles are cells that are counted as invaded cells. Average distance is calculated as distance the cell has deviated from the monolayer.

FIGURE 5

Glycosaminoglycans (GAGs) conditions promote higher levels of cellular proliferation in endothelial and interstitial cells. Interstitial cells were stained with CellTrace CSFE-Green and endothelial cells with CellTrace Far-Red prior to hydrogel seeding. Flow cytometry processing (BC FACS Aria II) was used to measure fluorescence of cells extracted from digested hydrogels after 14 days of growth. FlowJo’s proliferation toolbox was used for analysis. (A–D) Generational activity for endothelial cells stained with CellTrace Far-Red across four conditions. (E–H) Generational activity for interstitial cells stained with CellTrace CSFE across four conditions. (I) Population percentages of each generation and each condition for endothelial cells. (J) Population percentages of each generation and each condition for interstitial cells. Data represented as mean ± SEM. *p < 0.05 and **p < 0.01.