Quantitatively defining spatial patterns of myoendothelial junctions in the arterial wall

Abstract

The regulation of vasoconstriction and vasodilatory pathways is essential in resistance arteries, and can be modulated by heterocellular communication between the endothelial and smooth muscle cells. This can occur via direct endothelial‐smooth muscle cell contact at myoendothelial junctions (MEJs) through fenestrations in the internal elastic lamina (IEL). While it has been demonstrated that MEJs do not occupy every fenestration, their spatial distribution throughout the endothelium has not yet been defined and could reveal localization tendencies to cellular landmarks. We hypothesized that the MEJ and IEL fenestration spatial distribution would exhibit a non‐random distribution pattern throughout the endothelium with respect to various cellular landmarks, including the interendothelial junctions. In order to quantify this relationship, the spatial distributions of both holes and MEJs with respect to various cellular landmarks were examined. Third order mesenteric resistance arteries isolated from C57Bl6 male mice were prepared en face to view the endothelium and detect the IEL, nuclei, myoendothelial junctions, and interendothelial junctions (e.g., claudin‐5). A Matlab based analysis pipeline was developed to calculate the proximity of IEL fenestrations to cellular landmarks, such as interendothelial junctions. En face views of the IEL often have patches of varying signal intensity, posing a challenge for detecting fenestrations through basic thresholding methods. To overcome this, parameters within Image Processing Toolbox documentation were optimized for each image prior to thresholding. This allowed for accurate assignment of XY coordinates to fenestration boundaries (bwboundaries documentation) and calculation of center points. En face views of claudin‐5 were similarly thresholded and their boundaries also defined by XY coordinate matrix. Next, Euclidean distance was calculated between each fenestration center point and all claudin‐5 XY coordinates and plotted as a probability distribution. Monte Carlo simulations were also performed as a negative control. In the simulation, the fenestrations are replaced by randomly generated circles that mimic the number and radii of fenestrations in the original image. This is compared to the original distribution to assess if identified patterns are random. Our analysis of >100 simulations indicate that IEL fenestrations appear to be randomly distributed across the IEL. However, we find the MEJs within the IEL fenestrations may be strategically placed near interendothelial junctions. Preliminary data indicates that this particular MEJ localization pattern may be opportunistic because of the cytoskeletal components at interendothelial junction that can be recruited to support the signaling microdomains within MEJs.Support or Funding InformationThis work supported by 1F31HL149228‐01 (CAR) and HL088554 (BEI).