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 Fӧrster
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 prostaglandin triggered
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.
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