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Regrowth of peripheral spiral ganglion neuron (SGN) fibers is a primary objective in efforts to improve cochlear implant outcomes and to potentially reinnervate regenerated hair cells. Cyclic adenosine monophosphate (cAMP) regulates neurite growth and guidance via activation of protein kinase A (PKA) and Exchange Protein directly Activated by Cylic AMP (Epac). Here we explored the effects of cAMP signaling on SGN neurite length in vitro. We find that the cAMP analog, cpt-cAMP, exerts a biphasic effect on neurite length; increasing length at lower concentrations and reducing length at higher concentrations. This biphasic response occurs in cultures plated on laminin, fibronectin, or tenascin C suggesting that it is not substrate dependent. cpt-cAMP also reduces SGN neurite branching. The Epac-specific agonist, 8-pCPT-2'-O-Me-cAMP, does not alter SGN neurite length. Constitutively active PKA isoforms strongly inhibit SGN neurite length similar to higher levels of cAMP. Chronic membrane depolarization activates PKA in SGNs and also inhibits SGN neurite length. However, inhibition of PKA fails to rescue neurite length in depolarized cultures implying that activation of PKA is not necessary for the inhibition of SGN neurite length by chronic depolarization. Expression of constitutively active phosphatidylinositol 3-kinase, but not c-Jun N-terminal kinase, isoforms partially rescues SGN neurite length in the presence of activated PKA. Taken together, these results suggest that activation of cAMP/PKA represents a potential strategy to enhance SGN fiber elongation following deafness; however such therapies will likely require careful titration so as to promote rather than inhibit nerve fiber regeneration.
Pubmed ID: 22154930
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NEURON is a simulation environment for modeling individual neurons and networks of neurons. It provides tools for conveniently building, managing, and using models in a way that is numerically sound and computationally efficient. It is particularly well-suited to problems that are closely linked to experimental data, especially those that involve cells with complex anatomical and biophysical properties. NEURON has benefited from judicious revision and selective enhancement, guided by feedback from the growing number of neuroscientists who have used it to incorporate empirically-based modeling into their research strategies. NEURON's computational engine employs special algorithms that achieve high efficiency by exploiting the structure of the equations that describe neuronal properties. It has functions that are tailored for conveniently controlling simulations, and presenting the results of real neurophysiological problems graphically in ways that are quickly and intuitively grasped. Instead of forcing users to reformulate their conceptual models to fit the requirements of a general purpose simulator, NEURON is designed to let them deal directly with familiar neuroscience concepts. Consequently, users can think in terms of the biophysical properties of membrane and cytoplasm, the branched architecture of neurons, and the effects of synaptic communication between cells. * helps users focus on important biological issues rather than purely computational concerns * has a convenient user interface * has a user-extendable library of biophysical mechanisms * has many enhancements for efficient network modeling * offers customizable initialization and simulation flow control * is widely used in neuroscience research by experimentalists and theoreticians * is well-documented and actively supported * is free, open source, and runs on (almost) everything
View all literature mentionsSoftware tool for data graphing and analysis by Systat Software, Inc.
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