Network pharmacology and experimental analysis to reveal the mechanism of Dan-Shen-Yin against endothelial to mesenchymal transition in atherosclerosis

Abstract

Atherosclerosis is a chronic inflammatory disease characterized by the formation of plaque and endothelial dysfunction. Under pro-inflammatory conditions, endothelial cells adopt a mesenchymal phenotype by a process called endothelial-to-mesenchymal transition (EndMT) which plays an important role in the pathogenesis of atherosclerosis. Dan-Shen-Yin (DSY) is a well-known traditional Chinese medicine used in the treatment of cardiovascular disease. However, the molecular mechanism whereby DSY mitigates atherosclerosis remains unknown. Therefore, we employed a network pharmacology-based strategy in this study to determine the therapeutic targets of DSY, and in vitro experiments to understand the molecular pharmacology mechanism. The targets of the active ingredients of DSY related to EndMT and atherosclerosis were obtained and used to construct a protein-protein interaction (PPI) network followed by network topology and functional enrichment analysis. Network pharmacology analysis revealed that the PI3K/AKT pathway was the principal signaling pathway of DSY against EndMT in atherosclerosis. Molecular docking simulations indicated strong binding capabilities of DSY's bioactive ingredients toward PI3K/AKT pathway molecules. Experimentally, DSY could efficiently modify expression of signature EndMT genes and decrease expression of PI3K/AKT pathway signals including integrin αV, integrin β1, PI3K, and AKT1 in TGF-β2-treated HUVECs. LASP1, which is upstream of the PI3K/AKT pathway, had strong binding affinity to the majority of DSY's bioactive ingredients, was induced by EndMT-promoting stimuli involving IL-1β, TGF-β2, and hypoxia, and was downregulated by DSY. Knock-down of LASP1 attenuated the expression of integrin αV, integrin β1, PI3K, AKT1 and EndMT-related genes induced by TGF-β2, and minimized the effect of DSY. Thus, our study showed that DSY potentially exerted anti-EndMT activity through the LASP1/PI3K/AKT pathway, providing a possible new therapeutic intervention for atherosclerosis.

Keywords: Dan-Shen-Yin; LASP1; PI3K/AKT signaling; atherosclerosis; endothelial to mesenchymal transition; network pharmacology.

FIGURE 1

Functional enrichment analysis of the PPI network. (A) The shared targets of PPI with regard to DSY, EndMT and AS. (B) The PPI network of DSY regulating EndMT in treating AS. (C) GO ontology analysis of biological process, molecular functions, and cellular components. (D) KEGG enrichment analysis. The X-axis indicated the counts of the target symbols in each pathway; the Y-axis represented the main pathways (p < 0.05).

FIGURE 2

Screening of PI3K/AKT signaling pathway for regulation of EndMT in AS. (A) network of bioactive ingredients with PI3K/AKT targets extracted from directly intersected and PPI core targets. (B) The specific position and function of PI3K/AKT targets in signaling pathways. The red nodes and the yellow nodes represent the specific position of targets screened from PPI and from directly intersected targets respectively in the pathways.

FIGURE 3

(A) HPLC chromatographic fingerprints of DSY. (1) and (2) represent cryptotanshinone and tanshinone IIA individually. S1: mixture of tanshinone IIA and cryptotanshinone; S2: DSY; S3: tanshinone IIA; S4: cryptotanshinone. (B) HUVECs were treated with different doses of DSY for 24 h followed by CCK-8 analysis. IC50 was calculated by linear-regression. (C) Cell viability influenced by DSY in the presence of TGF-β2 was determined by CCK-8 analysis.

FIGURE 4

The effect of DSY on EndMT. (A–E) HUVECs pretreated with 10 ng/ml TGF-β2 for 2 days were incubated with different doses of DSY for another 2 d. (A) Representative phase contrast microscopy images. (B) RT-qPCR analysis of SM22α, calponin, vimentin, COL1A1, and Snail. (C) Western blot analysis was conducted to detect SM22α and VE-cadherin expression in DSY-treated cells. (D, right panel) Representative confocal images of HUVECs immune labeled with SM22α and VE-cadherin. (D, left panel) Relative intensities of SM22α and VE-cadherin were quantified by Fiji software. (E) HUVECs were pretreated with TGF-β2 for 3, 2, and 1 day followed by stimulation with 2.5 μg/ml DSY for another 1, 2, and 3 days. RT-qPCR analysis of SM22α, calponin and N-cadherin was demonstrated. (F) HUVECs pretreated with 10 ng/ml TGF-β2 for 2 days were treated with 2.5 μg/ml DSY, Salvia miltiorrhiza, fructus amomi and sandalwood for another 2 days. RT-PCR analysis of SM22α, calponin, COL1A1, and Snail was shown.

FIGURE 5

Impact of DSY on PI3K/AKT signaling. (A) Docking simulations of bioactive ingredients with PI3K/AKT molecules. Heat map of docking scores of binding affinity is shown. (B) HUVECs pretreated with 10 ng/ml TGF-β2 were subsequently stimulated with 2.5 μg/ml DSY. RT-qPCR analysis of PI3K, AKT1, AKT2, eNOS, integrin αV, and integrin β1.

FIGURE 6

Docking simulations of bioactive ingredients with LASP1 molecule. (A) The binding affinities and the hydrogen bonding residues are shown. (B) The docking graph is shown.

FIGURE 7

LASP1 mediated DSY down-regulation of integrin expression in TGF-β2-treated cells. (A) HUVECs were treated with 10 ng/ml IL-1β, TGF-β2 for 3 days or stimulated with hypoxia for 12 h. RT-qPCR analysis was then performed to detect LASP1 expression. (B) RT-qPCR comparison of LASP1 expression in HUVECs and HVSMCs. (C,D) LASP1 expression in TGF-β2-pretreated cells supplemented with different doses of DSY measured by (C) RT-qPCR and (D) immunofluorescence assay. (E, upper panel) RT-qPCR analysis of LASP1 expression after transfection with different siRNAs. (E, lower panel) LASP1 expression after transfection with siLASP-446 was checked by western blot. (F) HUVECs were transfected with siLASP1-446 followed by treatment with TGF-β2. One day later, 2.5 μg/ml DSY was added for another 2 d. (F) Analysis of integrin αV, integrin β1, PI3K, and AKT1 and (G) SM22α, calponin, and VEGFR2 expression by RT-qPCR analysis. (H) Western blot analysis of p-AKT, AKT1, SM22α and LASP1.