Novel Hyperspectral imaging approaches allow 3D measurement of cAMP signals in localized subcellular domains of human airway smooth muscle cells

Studies of the cAMP signaling pathway have led to the hypothesis that localized cAMP signals regulate distinct cellular responses. Much of this work focused on measurement of localized cAMP signals using cAMP sensors based upon F.rster resonance energy transfer (FRET). FRET-based probes are comprised of a cAMP binding domain sandwiched between donor and acceptor fluorophores. Binding of cAMP triggers a conformational change which alters FRET efficiency. In order to study localized cAMP signals, investigators have targeted FRET probes to distinct subcellular domains. This approach allows detection of cAMP signals at distinct subcellular locations. However, these approaches do not measure localized cAMP signals per se, rather they measure cAMP signals at specific locations and typically averaged throughout the cell. To address these concerns, our group implemented hyperspectral imaging approaches for measuring highly multiplexed signals in cells and tissues. We have combined these approaches with custom analysis software implemented in MATLAB and Python. Images were filtered both spatially and temporally, prior to adaptive thresholding (OTSU) to detect cAMP signals. These approaches were used to interrogate the distributions of isoproterenol and prostaglandintriggered cAMP signals in human airway smooth muscle cells (HASMCs). Results demonstrate that cAMP signals are spatially and temporally complex. We observed that isoproterenol- and prostaglandin-induced cAMP signals are triggered at the plasma membrane and in the cytosolic space. We are currently implementing analysis approaches to better quantify and visualize the complex distributions of cAMP signals. This work was supported by NIH P01HL066299, R01HL058506, and S10RR027535.