Coronary artery endothelial transcriptome in vivo: identification of endoplasmic reticulum stress and enhanced reactive oxygen species by gene connectivity network analysis

Abstract

Background: Endothelial function is central to the localization of atherosclerosis. The in vivo endothelial phenotypic footprints of arterial bed identity and site-specific atherosusceptibility are addressed.

Methods and results: Ninety-eight endothelial cell samples from 13 discrete coronary and noncoronary arterial regions of varying susceptibilities to atherosclerosis were isolated from 76 normal swine. Transcript profiles were analyzed to determine the steady-state in vivo endothelial phenotypes. An unsupervised systems biology approach using weighted gene coexpression networks showed highly correlated endothelial genes. Connectivity network analysis identified 19 gene modules, 12 of which showed significant association with circulatory bed classification. Differential expression of 1300 genes between coronary and noncoronary artery endothelium suggested distinct coronary endothelial phenotypes, with highest significance expressed in gene modules enriched for biological functions related to endoplasmic reticulum (ER) stress and unfolded protein binding, regulation of transcription and translation, and redox homeostasis. Furthermore, within coronary arteries, comparison of endothelial transcript profiles of susceptible proximal regions to protected distal regions suggested the presence of ER stress conditions in susceptible sites. Accumulation of reactive oxygen species throughout coronary endothelium was greater than in noncoronary endothelium consistent with coronary artery ER stress and lower endothelial expression of antioxidant genes in coronary arteries.

Conclusions: Gene connectivity analyses discriminated between coronary and noncoronary endothelial transcript profiles and identified differential transcript levels associated with increased ER and oxidative stress in coronary arteries consistent with enhanced susceptibility to atherosclerosis.

Figure 1

Arterial regions of endothelial isolation. ECs were gently scraped from multiple athero-susceptible and athero-protected regions for transcript and protein analysis. Representative images showing regions of isolation. Regional description is outlined in Table 1. Scale bar=1 cm.

Figure 2

Weighted gene co-expression network of arterial endothelial genes. Topological overlap matrix was calculated based on the biweight midcorrelation strengths of all pairs of 5,579 reporters in all samples. Gene co-expression modules (assigned unique colors) were identified using the topological overlap similarity measure and average linkage hierarchical clustering. Each module represents a group of genes with high topological overlap over all arterial endothelial samples.

Figure 3

Arterial endothelium gene co-expression network. Genes were partitioned into modules of similar expression profiles using the WGCNA algorithm. An interaction network was constructed using the topological overlap measure as the distance between two genes (nodes). The colors indicate different modules. Enriched biological functions and the enrichment p-value (Fisher’s Exact test) for selected modules are indicated in the module color.

Figure 4

Coronary artery gene modules. Modules with high significance to arterial bed classification were used to construct interaction networks. The size of each node indicates the intramodular connectivity for each gene. Genes with larger nodes have stronger connectivity with neighboring genes. Modules are colored with the same colors as assigned by the WGCNA algorithm (as in Figure 2). The hub genes of each module are colored yellow.

Figure 5

Anti-oxidant gene expression in different arterial beds. Transcript expression from 12 coronary and 20 non-coronary samples were measured by quantitative RT-PCR and normalized to GAPDH levels. Data represent means±SEM. p-values were calculated by two-sided Student’s t-Test with equal variance.

Figure 6

Endothelial ROS detection. Freshly-harvested normal swine arteries were incubated with dihydroethidium (oxidized product red) and isolectin B₄ (endothelial identity; green). They were imaged en face using confocal microscopy under identical conditions. Percentages of endothelial cells with high ROS were determined by counting the red nuclei. This percentage was used to calculate a ratio for each pair of athero-susceptible and athero-protected samples. Data represent mean+SEM. p-values were calculated by one-sample, one-sided, paired Wilcoxon test. Scale bar=25 µm. **p<0.01, N.S. = not significant.