Distal Spike Initiation Zone Location Estimation by Morphological Simulation of Ionic Current Filtering Demonstrated in a Novel Model of an Identified Drosophila Motoneuron

• Type of Material: Article
• Authors: Cengiz Gunay, Emory University; Fred H. Sieling, Emory University; Logesh Dharmar, Emory University; Wei-Hsiang Lin, University of Manchester; Richard Marley, University of Manchester; Richard Baines, University of Manchester; Astrid A Prinz, Emory University
• Language: English
• Date: 2015-05-15
• Publisher: Public Library of Science
• Publication Version: Final Published Version
• Copyright Statement: © 2015 Günay et al.
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1371/journal.pcbi.1004189
• Title of Journal or Parent Work: PLoS Computational Biology
• Volume: 11
• Issue: 5
• Start Page: e1004189
• End Page: e1004189
• Grant/Funding Information: This work was supported by awarding of an Epilepsy Foundation (http://www.epilepsy.com/) Post-Doctoral Research Training Fellowship to CG, a Burroughs Wellcome Fund (http://www.bwfund.org/) Career Award to AAP, and funding from the Wellcome Trust (http://www.wellcome.ac.uk/) (090798) to RAB.; This project benefited from the Manchester Fly Facility, established by the University of Manchester and Wellcome Trust (087742).
• Research Categories: Biology, General; Engineering, Biomedical

Abstract

Studying ion channel currents generated distally from the recording site is difficult because of artifacts caused by poor space clamp and membrane filtering. A computational model can quantify artifact parameters for correction by simulating the currents only if their exact anatomical location is known. We propose that the same artifacts that confound current recordings can help pinpoint the source of those currents by providing a signature of the neuron’s morphology. This method can improve the recording quality of currents initiated at the spike initiation zone (SIZ) that are often distal to the soma in invertebrate neurons. Drosophila being a valuable tool for characterizing ion currents, we estimated the SIZ location and quantified artifacts in an identified motoneuron, aCC/MN1-Ib, by constructing a novel multicompartmental model. Initial simulation of the measured biophysical channel properties in an isopotential Hodgkin-Huxley type neuron model partially replicated firing characteristics. Adding a second distal compartment, which contained spike-generating Na+ and K+ currents, was sufficient to simulate aCC’s in vivo activity signature. Matching this signature using a reconstructed morphology predicted that the SIZ is on aCC’s primary axon, 70 μm after the most distal dendritic branching point. From SIZ to soma, we observed and quantified selective morphological filtering of fast activating currents. Non-inactivating K+ currents are filtered ∼3 times less and despite their large magnitude at the soma they could be as distal as Na+ currents. The peak of transient component (NaT) of the voltage-activated Na+ current is also filtered more than the magnitude of slower persistent component (NaP), which can contribute to seizures. The corrected NaP/NaT ratio explains the previously observed discrepancy when the same channel is expressed in different cells. In summary, we used an in vivo signature to estimate ion channel location and recording artifacts, which can be applied to other neurons.