Novel protocol for the transcriptomic analysis of endothelial extracellular vesicles in atherosclerosis

Despite the key role of the endothelium in atherosclerosis, there are no direct techniques for its analysis. The study of extracellular vesicles of endothelial origin (EEVs), might lead to the identification of molecular signatures and early biomarkers of atherosclerosis. The aim of this work was to set up the methods for EEVs separation and transcriptomic analysis.

We adapted an antibody-magnetic-bead based immunocapture protocol for plasma EEVs separation from control (G1), subclinical atherosclerosis (G2) and peripheral artery disease subjects (PAD) (G3), and modified an ultra-low input RNASeq method (n=5/group). By bioinformatics analysis we compared the transcriptome of plasma EEVs with that of human aortic endothelial cells (TeloHAECs), and then, searched for differentially expressed genes (DEG) among EEVs of G1, G2 and G3. From those DEG, UCP2 was selected for further validation in plasma EVs (qPCR), and in vitro, in stimulated TeloHAECs (IL-1β, TNFα, oxLDL and hypoxia).

The RNASeq analysis of plasma EEVs rendered 1667 genes enriched in transcripts expressed by TeloHAECs (NES: 1.93, p adjust=1.4^e-73). One hundred seventy DEGs were identified between G2 vs G1, and 180 between G3 vs G1, of which 17 were similarly expressed in G2 and G3 vs control, including UCP2. IL-1β and TNFα (10ng/mL, p<0.05), hypoxia (1% O₂, p=0.05) and oxLDL (100μg/mL, p=0.055) reduced UCP2 expression in TeloHAECs.

We set up a protocol for EEVs separation and sequencing that might be useful for the identification of early markers of endothelial dysfunction in atherosclerosis.