The molecular mechanisms responsible for sepsis-induced endothelial dysfunction leading to an elevated risk of cardiovascular diseases remain undefined. Endotoxic or septic shock is a potentially lethal complication of systemic infection by Gram-negative bacteria. Lipopolysaccharide (LPS) is a critical glycolipid component of the outer wall of Gram-negative bacteria, and many of the sepsis-associated cellular signals by Gram-negative bacteria are attributed to LPS. Given that LPS has an established role in the pathophysiology of sepsis and long non-coding RNAs (lncRNAs) have been reported to critically regulate vascular homeostasis, researchers from St. Michael’s Hospital conducted a systematic transcriptional survey to evaluate the impact of LPS stimulation on human endothelial lncRNAs and protein-coding transcripts (mRNAs). LncRNAs and mRNAs from LPS-treated (100 ng/mL; 24 h) human umbilical vein endothelial cells (HUVECs) were profiled with the Arraystar Human lncRNA Expression Microarray V3.0. Of the 30,584 lncRNAs screened, 871 were significantly upregulated and 1068 significantly downregulated (p < 0.05) in response to LPS. In the same HUVEC samples, 733 of the 26,106 mRNAs screened were upregulated and 536 were downregulated. Among the differentially expressed lncRNAs, AL132709.5 was the most upregulated (~70 fold) and CTC-459I6.1 the most downregulated (~28 fold). Bioinformatics analyses indicated that the differentially expressed upregulated mRNAs are primarily enriched in cytokine-cytokine receptor interaction, infectious diseases, TNF signaling pathway, FoxO signaling pathway, and pathways in cancer. This is the first lncRNA and mRNA transcriptome profile of LPS-mediated changes in human endothelial cells. These observations may reveal novel endothelial targets of LPS that may be involved in the vascular pathology of sepsis.
Heat map and hierarchical clustering of differences in lncRNA and mRNA
expression from HUVECs treated with LPS (100 ng/mL) vs. control.
A, B. The dendrogram shows the relationships among the expression levels of samples. Hierarchical clustering that was performed based on ‘differentially expressed lncRNAs and mRNAs’, shows a distinguishable lncRNA and mRNA expression profiling among samples.