Neuroepithelial cell-transforming 1 promotes cardiac fibrosis via the Wnt/β-catenin signaling pathway

Figures

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  Figure 1. NET1 expression is increased in the cardiac fibrosis model (A) Western blot was used to detect the changes of FN-1, α-SMA, and NET1 proteins, which were related to fibrosis in myocardial infarction tissue, and GAPDH was used as an internal reference. n = 5, ∗∗p = 0.0079, ∗p = 0.0476, ∗p = 0.0159 MI vs. Sham by Mann Whitney test. (B) qRT-PCR was used to detect the changes of NET1 mRNA in cardiac fibrosis. n = 4, ∗p = 0.0159 MI vs. Sham by Mann Whitney test. (C) Western blot was used to detect the changes of FN-1, α-SMA, and NET1 proteins in TGF-β1-treated group. n = 4, ∗p = 0.0286 TGF-β1 vs. Ctrl by Mann Whitney test. (D) Representative image of cardiac fibroblasts stained with α-SMA antibody (Red) and NET1 antibody (Green). The levels of NET1 and α-SMA were measured by quantitative immunofluorescence. Scale bar: 50 μm, magnification 200×. n = 5, ∗p = 0.0159 TGF-β1 vs. Ctrl (Left panel), ∗p = 0.0159 TGF-β1 vs. Ctrl (Right panel) by Mann Whitney test. For all statistical plots, the data are presented as mean ± SEM.

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  Figure 2. Effect of NET1 knockdown on TGF-β1-induced cardiac fibroblasts (A) mRNA change of NET1, n = 4, ∗p = 0.0286 TGF-β1 vs. Ctrl by Mann Whitney test. ∗∗p = 0.0084 TGF-β1 + si-NET1 vs. TGF-β1，∗p = 0.0360 vs. TGF-β1 + si-NET1 vs. TGF-β1 + NC by Kruskal-Wallis test. (B) mRNA of collagen I (COL1A1) was detected by qRT-PCR, n = 4, ∗p = 0.0286 TGF-β1 vs. Ctrl by Mann Whitney test. ∗p = 0.0360 TGF-β1 + si-NET1 vs. TGF-β1，∗p = 0.0140 TGF-β1 + si-NET1 vs. TGF-β1 + NC by Kruskal-Wallis test. (C) Representative image of cardiac fibroblasts stained with α-SMA antibody (Red) and NET1 antibody (Green). Scale bar: 50 μm, magnification 200×. (D) The migration of cardiac fibroblast was detected by scratch assay, n = 5, ∗p = 0.0452 TGF-β1 vs. Ctrl, ∗p = 0.0277 TGF-β1 + si-NET1 vs. TGF-β1, ∗p = 0.0452 TGF-β1 + si-NET1 vs. TGF-β1 + NC by Kruskal-Wallis test. (E) The proliferative ability of cardiac fibroblasts was detected by EdU kit. Scale bar: 50 μm, magnification 200×, n = 4, ∗p = 0.0313 TGF-β1 vs. Ctrl, ∗∗p = 0.0075 TGF-β1 + si-NET1 vs. TGF-β1, ∗p = 0.0143 TGF-β1 + si-NET1 vs. TGF-β1 + NC by Kruskal-Wallis test. (F) The viability of cardiac fibroblasts was detected by MTT assay, n = 9, ∗p = 0.0465…

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  Figure 3. Effect of NET1 overexpression on cardiac fibroblasts (A) Western blot was used to detect the protein expression levels of NET1, FN-1, and collagen I in cardiac fibroblasts transfected with NET1 overexpression plasmid, n = 4, ∗p = 0.0286 NET1 vs. Vector by Mann Whitney test. qRT-PCR was used to detect NET1, COL1A1 in fibroblasts and COL3A3 mRNA expression levels. n = 4–5, ∗p = 0.0286, ∗p = 0.0286, ∗∗p = 0.0079 NET1 vs. Vector by Mann Whitney test. (B) Fibroblast viability was detected by MTT assay, n = 9, ∗p = 0.0244 NET1 vs. Vector by Mann Whitney test. (C) The expression of myofibroblast marker α-SMA was detected by immunofluorescence (n = 5, ∗∗p = 0.0079) and western blot (n = 8, ∗∗p = 0.0019). NET1 vs. Vector by Mann Whitney test, Scale bar: 50 μm, magnification 200×. (D) Fibroblast migration was detected by cell scratch assay. n = 4, ∗p = 0.0286 NET1 vs. Vector by Mann Whitney test. (E) Fibroblast proliferation detected by Edu kit. Scale bar: 50 μm, magnification 200×, n = 3, p = 0.1000 NET1 vs. Vector by Mann Whitney test. (F) Western blot was used to detect the protein level of β-catenin. n = 4, ∗p = 0.0286 NET1 vs. Vector by Mann Whitney test. For all statistical plots,…

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  Figure 4. NET1 may be involved in cardiac fibrosis through β-catenin (A) Cardiac fibroblasts were transfected with si-β-catenin and NC, and the protein level of β-catenin was detected by western blot. n = 5,∗p = 0.0175 si-β-catenin1 vs. NC, ∗p = 0.0327 si-β-catenin2 vs. NC by Kruskal-Wallis test. (B and C) Fibrosis marker protein FN-1 (n = 4, ∗∗p = 0.0011 NET1 + si-β-catenin vs. NET1 by Kruskal-Wallis test) and (C) collagen I expression was detected by western blot. n = 4, ∗∗p = 0.0075 NET1 vs. Ctrl, ∗p = 0.0259 NET1 + si-β-catenin vs. NET1 by Kruskal-Wallis test. (D) MTT method was used for detection of fibroblast viability. n = 7, ∗∗p = 0.0093 Ctrl vs. NET1, ∗∗p = 0.0063 NET1 + si-β-catenin vs. NET1 by Kruskal-Wallis test. (E) Fibroblast migration ability was detected by cell scratch method. n = 4, ∗p = 0.0166 Ctrl vs. NET1, ∗∗p = 0.0003 NET1 + si-β-catenin vs. NET1 by Kruskal-Wallis test. For all statistical plots, the data are presented as mean ± SEM. (F) Co-immunoprecipitation (Co-IP) was performed to verify GSK3β protein interaction with NET1 and β-catenin.

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  Figure 5. Effects of overexpression or knockdown of NET1 on β-catenin signaling pathways (A) IF staining of β-catenin and quantitative analysis of β-catenin treated with or without si-NET1. n = 6, ∗∗p = 0.0037 TGF-β1 + NC vs. NC by Kruskal-Wallis test, ∗∗p = 0.0022 TGF-β1 + si-NET1 vs. TGF-β1 + NC by Mann Whitney test, Scale bar: 20 μm. (B) IF staining of β-catenin and quantitative analysis of β-catenin treated with or without overexpression NET1. n = 6, ∗p = 0.0179 OE-NET1 vs. NC, ∗p = 0.0305 TGF-β1 + NC vs. NC, ∗∗p < 0.0001 TGF-β1 + OE-NET1 vs. NC, ∗p = 0.0338 TGF-β1 + OE-NET1 vs. TGF-β1 + NC, Scale bar: 10 μm. For all statistical plots, the data are presented as mean ± SEM.

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  Figure 6. Effects of GSK3β knockdown on TGF-β1-induced cardiac fibrosis (A and B) Expression level of NET1 (n = 3, ∗∗p = 0.0092 TGF-β1 vs. Ctrl, ∗p = 0.0127 TGF-β1 + siNC vs. Ctrl by Kruskal-Wallis test) (B) collagen I (n = 3, ∗p = 0.0415 TGF-β1 vs. Ctrl, ∗p = 0.0315 TGF-β1 + siNC vs. Ctrl, ∗p = 0.0415 TGF-β1 + siGSK3β vs. TGF-β1 + siNC) and hydroxyproline (n = 4, ∗∗p = 0.0014 TGF-β1 vs. Ctrl, ∗p = 0.0213 TGF-β1 + siNC vs. Ctrl, ∗p = 0.0143 TGF-β1 + siGSK3β vs. TGF-β1 by Kruskal-Wallis test. (C) α-SMA after knockdown GSK3β in cardiac fibroblasts. Scale bar: 20 μm, magnification, 200×. (D) EdU staining was used to detect fibroblast proliferation. Scale bar: 20 μm, magnification, 200×. n = 6, ∗∗p = 0.0005 TGF-β1 vs. Ctrl, ∗∗p = 0.0004 TGF-β1 + siNC vs. Ctrl, ∗p = 0.0160 TGF-β1 + siGSK3β vs. TGF-β1 + siNC by Kruskal-Wallis test. (E) The migration of fibroblasts was detected by scratch experiment. n = 3, ∗∗p = 0.0046, TGF-β1 + siGSK3β vs. TGF-β1, ∗p = 0.0235, TGF-β1 + siGSK3β vs. TGF-β1 + siNC by Kruskal-Wallis test. (F) Expression level of GSK3β after knockdown GSK3β in cardiac fibroblasts. n = 3, ∗∗p = 0.0055, TGF-β1 + siGSK3β vs. TGF-β1, ∗p = 0.0201, TGF-β1 + siGSK3β vs. TGF-β1 + siNC by…

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  Figure 7. Effects of GSK3β knockdown on cardiac fibrosis induced by NET1 overexpression (A) Expression level of NET1 after overexpression NET1 and knockdown GSK3β in cardiac fibroblasts. n = 3, ∗∗p = 0.0022 NET1 vs. NC + siGSK3β, n = 3, by Kruskal-Wallis test. (B) Expression level of collagen I (n = 3, ∗∗p = 0.0022 NET1 vs. NC + siGSK3β) and hydroxyproline (n = 3, ∗p = 0.0415 NC vs. NET1, ∗∗p = 0.0022 NET1 vs. NC + siGSK3β, ∗p = 0.0415 NET1+ siGSK3β vs. NC + siGSK3β) after overexpression NET1 and knockdown GSK3β in cardiac fibroblasts. (C) Expression level of α-SMA after overexpression NET1 and knockdown GSK3β in cardiac fibroblasts. Scale bar: 20 μm, magnification, 200×. (D) EdU staining was used to detect fibroblast proliferation, Scale bar: 20 μm, magnification, 200×. n = 3. ∗p = 0.0415 NC vs. NET1, ∗∗p = 0.0022 siGSK3β vs. NET1, ∗p = 0.0415 NET1 + siGSK3β vs. siGSK3β by Kruskal-Wallis test. (E) The migration of fibroblasts was detected by scratch experiment. n = 3, ∗p = 0.0134 siGSK3β vs. NET1 by Kruskal-Wallis test. (F) Expression level of β-catenin after overexpression NET1 and knockdown GSK3β in cardiac fibroblasts. n = 3, ∗p = 0.0280 NC vs. NET1, ∗∗p = 0.0029 NET1 vs. NC + siGSK3β,…

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  Figure 8. The role of NET1 in myocardial infarction in mice (A) The protein level of α-SMA in mouse model. n = 5, ∗∗p = 0.0088 Sham vs. MI, ∗∗p < 0.0001 MI vs. KO, ∗∗p = 0.0088 KO vs. KO + MI, by Kruskal-Wallis test, ∗∗p = 0.0079 KO + MI vs. MI by Mann Whitney test. (B) The protein level of collagen I (n = 3, ∗p = 0.0415 Sham vs. MI, ∗∗p = 0.0022 MI vs. KO, ∗p = 0.0415 KO vs. KO + MI) and hydroxyproline in mouse model (n = 6, ∗∗p = 0.0013 Sham vs. MI, ∗∗p = 0.0046 MI vs. KO, ∗p = 0.0479 MI vs. KO + MI by Kruskal-Wallis test). (C and D) The protein level of NET1 in mouse model. n = 3, ∗∗p = 0.0032 MI vs. KO, ∗p = 0.0415 MI vs. KO + MI. (D) The protein level of β-catenin in mouse MI model. n = 4, ∗p = 0.0143 Sham vs. MI, ∗∗p = 0.0005 MI vs. KO, ∗p = 0.0213 KO vs. KO + MI by Kruskal-Wallis test. ∗p = 0.0286 KO + MI vs. MI by Mann Whitney test. (E) The protein level of GSK3β-S389 in mouse MI model. n = 3, ∗p = 0.0022 MI vs. KO by Kruskal-Wallis test. The protein level of GSK3β-S9 in mouse MI model. n = 3∗p = 0.0022 MI vs. KO by Kruskal-Wallis test. For all statistical plots, the data are presented as mean ± SEM. (F) Changes of myocardial ultrastructure in each group. The ultrastructure of…