Long noncoding RNA expression analysis reveals the regulatory effects of nitinol-based nanotubular coatings on human coronary artery endothelial cells

Abstract

Background: Cardiovascular disease (CVD) is the leading cause of mortality all over the world. Vascular stents are used to ameliorate vascular stenosis and recover vascular function. The application of nanotubular coatings has been confirmed to promote endothelial cell (EC) proliferation and function. However, the regulatory mechanisms involved in cellular responses to the nanotubular topography have not been defined. In the present study, a microarray analysis was performed to explore the expression patterns of long noncoding RNAs (lncRNAs) in human coronary artery endothelial cells (HCAECs) that were differentially expressed in response to nitinol-based nanotubular coatings. Materials and methods: First, anodization was performed to synthesize nitinol-based nanotubular coatings. Then, HCAECs were cultured on the samples for 24 h to evaluate cell cytoskeleton organization. Next, total RNA was extracted and synthesized into cRNA, which was hybridized onto the microarray. GO analysis and KEGG pathway analysis were performed to investigate the roles of differentially expressed messenger RNAs (mRNAs). Quantitative real-time reverse-transcription polymerase chain reaction (qRT-PCR) was performed to validate the expression of randomly selected lncRNAs. Coexpression networks were created to identify the interactions among lncRNAs and the protein-coding genes involved in nanotubular topography-induced biological and molecular pathways. Independent Student's t-test was applied for comparisons between two groups with statistical significance set at p<0.05. Results: 1085 lncRNAs and 227 mRNAs were significantly differentially expressed in the nitinol-based nanotubular coating group. Bioinformatics analysis revealed that extracellular matrix receptor interactions and cell adhesion molecules play critical roles in the sensing of nitinol-based nanotubular coatings by HCAECs. The TATA-binding protein (TBP) and TBP-associated transfactor 1 (TAF1) are important molecules in EC responses to substrate topography. Conclusion: This study suggests that nanotubular substrate topography regulates ECs by differentially expressed lncRNAs involved extracellular matrix receptor interactions and cell adhesion molecules.

Keywords: RNA sequencing; long noncoding RNA; molecular networks; nanotopography; nitinol titanium dioxide nanotubes.

Figure 1

SEM images of the planar control nitinol (A) and the upright nanotubular coating (B). Scale bars: 100nm. (C) The decreased water contact angle of the nanotubular coating (NT) compared with that of the planar control nitinol (CK). The data are expressed as the mean ± standard deviation (n=4, ***p<0.001, compared with Student’s t-test.)

Figure 2

F-actin (green) and nuclear (blue) stains of HCAECs grown for 24h on (A) planar surfaces versus (B) nitinol-based nanotubular coatings. (C) Elongation of HCAECs as measured by the aspect ratio. The data are presented as the mean ± standard deviation (n=10). **p<0.01 significantly different from the CK group, Student’s t-test (two tailed).

Figure 3

Scatter plot of the variation in lncRNA (A) and mRNA (B) expression between the NT and control samples. The values shown on the x-axis and y-axis are the normalized signal values of each sample (log 2 scale). The green lines represent FCs (the default fold change value was 2.0). The lncRNAs and mRNAs above the top green line and below the bottom green line had FC values >2.0 between the 2 compared samples.

Figure 4

(A) Hierarchical clustering analysis of 1085 differentially expressed lncRNA probe sets. (B) Hierarchical clustering analysis of 227 differentially expressed mRNA probe sets. The samples are in the columns, and the probe sets are in the rows.

Figure 5

qRT-PCR validation results of four randomly selected lncRNAs. The target lncRNA expression levels were normalized to the internal control GAPDH. The data are presented as the mean ± standard deviation (n=3).*p<0.05,**p<0.01 significantly different from the CK group, Student’s t-test (two tailed).

Figure 6

The mRNA expression levels of three genes involved in "ECM-receptor interaction" pathway. The target mRNA expression levels were normalized to the internal control GAPDH. The data are presented as the mean ± standard deviation (n=3).*p<0.05 significantly different from the CK group, Student’s t-test (two tailed).

Figure 7

Top-ranking TFs associated with the differently expressed lncRNAs according to p-value.

Figure 8

lncRNA-TF network visualized by hypergeometric distribution analysis. The top 100 lncRNA-TF relationships sorted by p-value were selected to construct a dyadic relationship network. The blue and red nodes represent the TFs and lncRNAs, respectively.

Figure 9

lncRNA-TF-mRNA core network consisting of the 996 pairs of lncRNAs, TFs, and mRNAs with the most relevance. The red nodes represent the lncRNAs, the blue rectangles represent the TFs, and the green circles represent the mRNAs.

Figure 10

miRNA-lncRNA-mRNA coexpression network. The red rectangles represent the mRNAs, the blue rectangles represent the miRNAs, and the green rectangles represent the lncRNAs.