Effect of PPARgamma inhibition on pulmonary endothelial cell gene expression: gene profiling in pulmonary hypertension

Abstract

Peroxisome proliferator-activated receptor type gamma (PPARgamma) is a subgroup of the PPAR transcription factor family. Recent studies indicate that loss of PPARgamma is associated with the development of pulmonary hypertension (PH). We hypothesized that the endothelial dysfunction associated with PPARgamma inhibition may play an important role in the disease process by altering cellular gene expression and signaling cascades. We utilized microarray analysis to determine if PPARgamma inhibition induced changes in gene expression in pulmonary arterial endothelial cells (PAEC). We identified 100 genes and expressed sequence tags (ESTs) that were upregulated by >1.5-fold and 21 genes and ESTs that were downregulated by >1.3-fold (P < 0.05) by PPARgamma inhibition. The upregulated genes can be broadly classified into four functional groups: cell cycle, angiogenesis, ubiquitin system, and zinc finger proteins. The genes with the highest fold change in expression: hyaluronan-mediated motility receptor (HMMR), VEGF receptor 2 (Flk-1), endothelial PAS domain protein 1 (EPAS1), basic fibroblast growth factor (FGF-2), and caveolin-1 in PAEC were validated by real time RT-PCR. We further validated the upregulation of HMMR, Flk-1, FGF2, and caveolin-1 by Western blot analysis. In keeping with the microarray results, PPARgamma inhibition led to re-entry of cell cycle at G(1)/S phase and cyclin C upregulation. PPARgamma inhibition also exacerbated VEGF-induced endothelial barrier disruption. Finally we confirmed the downregulation of PPARgamma and the upregulation of HMMR, Flk-1, FGF2, and Cav-1 proteins in the peripheral lung tissues of an ovine model of PH. In conclusion, we have identified an array of endothelial genes modulated by attenuated PPARgamma signaling that may play important roles in the development of PH.

Figures

Fig. 1.

Ovine pulmonary arterial endothelial cells (PAEC) and bovine aortic endothelial cells have similar basal gene expression patterns. The log ratios of gene expression fold change between ovine PAEC and bovine aortic endothelial cells (BAEC) were plotted continuously on the x-/y-axes. The log ratios of gene expression fold change between ovine PAEC and BAEC centered on 0, indicating a similar gene expression pattern between ovine PAEC and BAEC.

Fig. 2.

GW9662 inhibits peroxisome proliferator-activated receptor (PPAR)γ transcription factor binding in ovine PAEC. Ovine PAEC were treated with vehicle (DMSO) or GW9662 (5 μM) for 24 h, and nuclear extracts were prepared, loaded onto a 96-well plate precoated with dsDNA of PPRE, and detected by the PPARγ antibody. PPARγ transcription factor binding was significantly decreased in GW9662-treated PAEC. Data are means ± SE, n = 4, *P < 0.05 vs. Vehicle.

Fig. 3.

Heat map analysis of the significantly (P < 0.05) regulated genes in GW9662-treated ovine pulmonary arterial endothelial cells. 1, GW9662 vs. vehicle upregulated genes (1.5 fold cut-off); 2, GW9662 vs. vehicle downregulated genes (1.3 fold cut-off).

Fig. 4.

PPARγ inhibition or depletion increases hyaluronan-mediated motility receptor (HMMR),VEGF receptor 2 (Flk-1), endothelial PAS domain protein 1 (EPAS1), basic fibroblast growth factor (FGF-2), and caveolin-1 mRNA levels in ovine and human PAEC. To pharmacologically inhibit PPARγ signaling, ovine PAEC were treated with vehicle (DMSO) or GW9662 (5 μM) for 24 h. Total RNA was isolated and the levels of HMMR (A), FLK-1 (B), EPAS1 (C), FGF2 (D), and caveolin-1 (E), SERPINE1 (F), and STAP2 (G) were quantified by SYBR Green real-time RT-PCR analyses. HMMR mRNA was upregulated by 1.9-fold (A); Flk-1 mRNA was upregulated by 4.4-fold (B); EPAS1 mRNA was upregulated by 1.3-fold (C); FGF2 mRNA was upregulated by 1.4-fold (D); Cav-1 mRNA was upregulated by 2.3-fold (E), SERPINE1 mRNA was downregulated by 1.4-fold (F), and STAP2 mRNA was downregulated by 2.2-fold (G). To deplete PPARγ expression, HMVEC were transfected with a PPARγ siRNA or a scrambled siRNA (Scra siRNA) for 48 h, and Western blot analysis (H) and transcription factor binding assays (I) were then utilized to confirm the decrease in PPARγ expression and binding respectively. Data are means ± SE, n = 6 for the Western blot assays and N + 4 for the transcription assays, *P < 0.05 vs. Scra siRNA. In the Western blot assays, protein loading was normalized by reprobing the blot with β-actin. Total RNA was the isolated from the PPARγ-depleted cells, and the levels of HMMR (J), FLK-1 (K), EPAS1 (L), FGF2 (M), and caveolin-1 (N) quantified by SYBR Green real-time RT-PCR analyses. HMMR mRNA was upregulated by 3-fold (J); Flk-1 mRNA was upregulated by 1.8-fold (K); EPAS1 mRNA was upregulated by 1.9-fold (L); FGF2 mRNA was upregulated by 1.8-fold (M); and Cav-1 mRNA was upregulated by 1.4-fold (N). Data are means ± SE, n = 6, *P < 0.05 vs. Scra siRNA. All mRNA data was normalized to β-actin mRNA levels.

Fig. 5.

PPARγ inhibition or depletion increases HMMR, FLK-1, EPAS1, FGF2, and caveolin-1 protein levels in ovine and human PAEC. To pharmacologically inhibit PPARγ signaling, ovine PAEC were treated with vehicle (DMSO) or GW9662 (5 μM) for 24 h. To deplete PPARγ expression, HMVEC were transfected with a PPARγ siRNA or a Scra siRNA for 48 h. In each case, whole cell extracts (20 μg) were then subjected to Western blot analysis to determine changes in HMMR, FLK-1, FGF2, and caveolin-1 protein levels. A representative image is shown for each Western blot. In ovine PAEC, HMMR protein was upregulated by 1.6-fold (A); Flk-1 protein was upregulated by 1.9-fold (B); FGF2 protein was upregulated by 2.3-fold (C); and caveolin-1 protein was upregulated by 1.8-fold (D). In HMVEC, HMMR protein was upregulated by 2.8-fold (E); Flk-1 protein was upregulated by 1.5-fold (F); FGF2 protein was upregulated by 2.1-fold (G); and caveolin-1 protein was upregulated by 1.8-fold (H). Data are means ± SE, n = 6, *P < 0.05 vs. vehicle. All protein levels were normalized by reprobing with β-actin.

Fig. 6.

PPARγ inhibition increases the number of cells in S phase and cyclin C expression in ovine PAEC, while PPARγ depletion increases cell proliferation in human PAEC. Ovine PAEC were treated with vehicle (DMSO) or GW9662 (5 μm) for 24 h. The cells were then harvested and labeled with propidium iodide (75 μM). Cell flow cytometry was then used to identify changes in cell cycle progression. PPARγ inhibition significantly increased the percentage of cells in S phase (A). However, PPARγ inhibition did not alter the percentage of cells in the G0/G1 phase (B) or the G2/M phase (C); n = 6, *P < 0.05 vs. vehicle-treated PAEC. In addition, Western blot analysis identified that PPARγ inhibition significantly increased cyclin C expression in ovine PAEC (D). Shown is a representative image with protein loading normalized by reprobing with β-actin. Data are means ± SE, n = 3, *P < 0.05 vs. vehicle. Furthermore, PPARγ depletion with a PPARγ-specific siRNA significantly increased human pulmonary microvascular endothelial cell (HMVEC) proliferation (E). Data are means ± SD, n = 4, *P < 0.05 vs. Scra siRNA, and this correlated with increased cyclin C protein levels in HMVEC (F). HMVEC were transiently transfected with a PPARγ siRNA or Scra siRNA as a control for 48 h, and the proteins were quantified as described above; a representative image is shown. Data are means ± SE, n = 4, *P < 0.05 vs. Scra siRNA.

Fig. 7.

PPARγ inhibition or depletion exacerbates VEGF-induced endothelial barrier disruption in ovine PAEC and HMVEC. A: ovine PAEC were plated on gold microelectrodes and grown until there was a plateau of impedance for at least 6 h. PAEC were then treated with either vehicle (DMSO) or GW9662 (5 μM) for 24 h, after which cells were exposed or not to VEGF (100 ng), and transendothelial resistance (TER) was monitored for 24 h. Alone GW9662 did not alter basal TER; however, it significantly decreased TER acutely (at 0.5 h) and chronically (24 h) in the presence of VEGF. Data are means ± SD, n = 6, †VEGF vs. vehicle at 0.5 h; ‡GW9662 + VEGF vs. VEGF at 0.5 h; *VEGF vs. vehicle at 24 h; *†GW9662 + VEGF vs. VEGF at 24 h, †, ‡, *, *† indicate P < 0.05. B: HMVEC were plated on gold microelectrodes and grown until 70% confluence then transfected with a PPARγ siRNA or a Scra siRNA. After 48 h the cells were exposed or not to VEGF (100 ng), and TER was monitored for 24 h. Alone PPARγ knock-down did not alter basal TER; however, it significantly decreased TER acutely (at 0.3 h) and chronically (24 h) in the presence of VEGF. Data are means ± SD, n = 6. †Scra siRNA + VEGF vs. Scra siRNA at 0.3 h; ‡PPARγ siRNA + VEGF vs. Scra siRNA + VEGF at 0.3 h; *Scra siRNA + VEGF vs. Scra siRNA at 24 h; *†PPARγ siRNA +VEGF vs. Scra siRNA + VEGF at 24 h, †, ‡, *, *† indicate P < 0.05. C: ovine PAECs were transiently transfected with a Flk-1 siRNA or Scra siRNA as a control for 48 h, and the proteins were harvested for Western blot analysis. The Flk-1 siRNA significantly reduces Flk-1 protein levels (a representative image is shown). Data are means ± SE, n = 4. *P < 0.05. D: ovine PAECs were transiently transfected with a Flk-1 siRNA or Scra siRNA as a control for 24 h, followed by treatment with either DMSO or GW9662 (5 μM) for a further 24 h. The cells were then exposed or not to VEGF (100 ng), and the TER was monitored over 24 h. The Flk-1 siRNA significantly attenuates the effect of GW9662 on VEGF-induced barrier disruption (both acutely and chronically). *Flk-1 siRNA + Vehicle + VEGF vs. Scra siRNA + Vehicle + VEGF; †Scra siRNA + GW9662 + VEGF vs. Scra siRNA + Vehicle + VEGF.

Fig. 8.

Expression of PPARγ, HMMR, Flk-1, FGF2, and caveolin-1 in a lamb model of pulmonary hypertension. PPARγ (A), HMMR (B), Flk-1 (C), FGF2 (D), and caveolin-1 (E) protein levels were determined by Western blot analysis in extracts prepared from peripheral lung tissue of 2-wk old Shunt and control lambs. A representative image is shown for each Western blot. PPARγ protein is significantly decreased in the Shunt lamb (2.7-fold, A), while the protein levels of HHMR (2.8-fold, B), Flk-1 (3-fold, C), FGF2 (2.1-fold, D), and caveolin-1 (4.6-fold, E) were all significantly increased. Data are means ± SE, n = 4, *P < 0.05 vs. control. All protein levels were normalized by reprobing with β-actin.