• Jennifer M Dolan, Fraser J Sim, Hui Meng, and John Kolega.
• Toshiba Stroke Research Center, University at Buffalo, State University of New York, 14214, USA.
• Am. J. Physiol., Cell Physiol. 2012 Apr 15; 302 (8): C1109-18.

AbstractChronic high flow can induce arterial remodeling, and this effect is mediated by endothelial cells (ECs) responding to wall shear stress (WSS). To assess how WSS above physiological normal levels affects ECs, we used DNA microarrays to profile EC gene expression under various flow conditions. Cultured bovine aortic ECs were exposed to no-flow (0 Pa), normal WSS (2 Pa), and very high WSS (10 Pa) for 24 h. Very high WSS induced a distinct expression profile compared with both no-flow and normal WSS. Gene ontology and biological pathway analysis revealed that high WSS modulated gene expression in ways that promote an anti-coagulant, anti-inflammatory, proliferative, and promatrix remodeling phenotype. A subset of characteristic genes was validated using quantitative polymerase chain reaction: very high WSS upregulated ADAMTS1 (a disintegrin and metalloproteinase with thrombospondin motif-1), PLAU (urokinase plasminogen activator), PLAT (tissue plasminogen activator), and TIMP3, all of which are involved in extracellular matrix processing, with PLAT and PLAU also contributing to fibrinolysis. Downregulated genes included CXCL5 and IL-8 and the adhesive glycoprotein THBS1 (thrombospondin-1). Expressions of ADAMTS1 and uPA proteins were assessed by immunhistochemistry in rabbit basilar arteries experiencing increased flow after bilateral carotid artery ligation. Both proteins were significantly increased when WSS was elevated compared with sham control animals. Our results indicate that very high WSS elicits a unique transcriptional profile in ECs that favors particular cell functions and pathways that are important in vessel homeostasis under increased flow. In addition, we identify specific molecular targets that are likely to contribute to adaptive remodeling under elevated flow conditions.

33 keywords...

hide…