In the hippocampus, cyclic-adenosine monophosphate (cAMP) and cAMP-dependent protein kinase (PKA) form a critical signaling cascade required for long-lasting synaptic plasticity, learning and memory. Plasticity and memory are known to occur following pathway-specific changes in synaptic strength that are thought to result from spatially and temporally coordinated intracellular signaling events. To better understand how cAMP and PKA dynamically operate within the structural complexity of hippocampal neurons, we used live two-photon imaging and genetically-encoded fluorescent biosensors to monitor cAMP levels or PKA activity in CA1 neurons of acute hippocampal slices. Stimulation of β-adrenergic receptors (isoproterenol) or combined activation of adenylyl cyclase (forskolin) and inhibition of phosphodiesterase (IBMX) produced cAMP transients with greater amplitude and rapid on-rates in intermediate and distal dendrites compared to somata and proximal dendrites. In contrast, isoproterenol produced greater PKA activity in somata and proximal dendrites compared to intermediate and distal dendrites, and the on-rate of PKA activity did not differ between compartments. Computational models show that our observed compartmental difference in cAMP can be reproduced by a uniform distribution of PDE4 and a variable density of adenylyl cyclase that scales with compartment size to compensate for changes in surface to volume ratios. However, reproducing our observed compartmental difference in PKA activity required enrichment of protein phosphatase in small compartments; neither reduced PKA subunits nor increased PKA substrates were sufficient. Together, our imaging and computational results show that compartment diameter interacts with rate-limiting components like adenylyl cyclase, phosphodiesterase and protein phosphatase to shape the spatial and temporal components of cAMP and PKA signaling in CA1 neurons and suggests that small neuronal compartments are most sensitive to cAMP signals whereas large neuronal compartments accommodate a greater dynamic range in PKA activity.
Keywords: Computational modeling; FRET; PKA; Signaling dynamics; cAMP; β-adrenergic receptors.
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