Bayesian Image Analysis of Dexamethasone and Shear Stress-Induced Glucocorticoid Receptor Intracellular Movement

Abstract

Endothelial cells are continuously exposed to hemodynamic shear stress, which has been shown to induce an array of physiological responses at the cellular and molecular levels. Uniform high shear stress is protective against vascular diseases such as atherosclerosis which preferentially occur at regions of disturbed flow and low shear. The glucocorticoid receptor (GR), a member of the steroid nuclear receptors with anti-inflammatory functions, has been shown to be activated by shear stress. Using a unique expectation-maximization (EM) algorithm based on Bayesian statistics, we have developed an image analysis algorithm to quantitatively assess GR nuclear translocation based on time-lapse images of green fluorescence protein-tagged GR (GFP-GR) under continuous exposure to a shear stress of 10 or 25 dynes/cm(2) as well as to Dexamethasone, a GR agonist. Average fluorescence brightness is generated for nucleus and cytoplasm. Real-time imaging of sheared cells revealed a steady and significant nuclear GFP-GR increase of approximately 20% within 2 h, compared to a rapid 60% increase in Dexamethasone-treated cells within 30 min. Furthermore, we found that that GFP-GR nuclear translocation under shear is not dependent on an intact cytoskeleton. Our image analysis algorithm provides a novel quantitative method to further study shear-sensitive mechanotransduction pathways in endothelial cells.