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Cdk-mediated phosphorylation of the Kvβ2 auxiliary subunit regulates Kv1 channel axonal targeting.

Kv1 channels are concentrated at specific sites in the axonal membrane, where they regulate neuronal excitability. Establishing these distributions requires regulated dissociation of Kv1 channels from the neuronal trafficking machinery and their subsequent insertion into the axonal membrane. We find that the auxiliary Kvβ2 subunit of Kv1 channels purified from brain is phosphorylated on serine residues 9 and 31, and that cyclin-dependent kinase (Cdk)-mediated phosphorylation at these sites negatively regulates the interaction of Kvβ2 with the microtubule plus end-tracking protein EB1. Endogenous Cdks, EB1, and Kvβ2 phosphorylated at serine 31 are colocalized in the axons of cultured hippocampal neurons, with enrichment at the axon initial segment (AIS). Acute inhibition of Cdk activity leads to intracellular accumulation of EB1, Kvβ2, and Kv1 channel subunits within the AIS. These studies reveal a new regulatory mechanism for the targeting of Kv1 complexes to the axonal membrane through the reversible Cdk phosphorylation-dependent binding of Kvβ2 to EB1.

Pubmed ID: 21357749 RIS Download

Mesh terms: Amino Acid Sequence | Animals | Axons | Chromatography, Liquid | Cyclin-Dependent Kinases | Hippocampus | Humans | Mice | Microtubule-Associated Proteins | Microtubules | Molecular Sequence Data | Neurons | Phosphorylation | Potassium Channels, Voltage-Gated | Protein Subunits | Protein Transport | Rats | Sciatic Nerve | Serine | Shaker Superfamily of Potassium Channels | Tandem Mass Spectrometry

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Associated grants

  • Agency: NINDS NIH HHS, Id: R01 NS034383
  • Agency: NINDS NIH HHS, Id: R01 NS034383-15
  • Agency: NINDS NIH HHS, Id: R37 NS034383
  • Agency: NINDS NIH HHS, Id: NS34383

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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

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