T2N as a new tool for robust electrophysiological modeling demonstrated for mature and adult-born dentate granule cells

  1. Marcel Beining  Is a corresponding author
  2. Lucas Alberto Mongiat
  3. Stephan Wolfgang Schwarzacher
  4. Hermann Cuntz
  5. Peter Jedlicka
  1. Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Germany
  2. Universidad Nacional del Comahue-CONICET, Argentina
  3. Goethe University, Germany

Abstract

Compartmental models are the theoretical tool of choice for understanding single neuron computations. However, many models are incomplete, built ad hoc and require tuning for each novel condition rendering them of limited usability. Here, we present T2N, a powerful interface to control NEURON with Matlab and TREES toolbox, which supports generating models stable over a broad range of reconstructed and synthetic morphologies. We illustrate this for a novel, highly-detailed active model of dentate granule cells (GCs) replicating a wide palette of experiments from various labs. By implementing known differences in ion channel composition and morphology, our model reproduces data from mouse or rat, mature or adult-born GCs as well as pharmacological interventions and epileptic conditions. This work sets a new benchmark for detailed compartmental modeling. T2N is suitable for creating robust models useful for large-scale networks that could lead to novel predictions. We discuss possible T2N application in degeneracy studies.

Article and author information

Author details

  1. Marcel Beining

    Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt, Germany
    For correspondence
    beining@fias.uni-frankfurt.de
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6577-2648
  2. Lucas Alberto Mongiat

    Instituto de Investigación en Biodiversidad y Medioambiente, Universidad Nacional del Comahue-CONICET, San Carlos de Bariloche, Argentina
    Competing interests
    The authors declare that no competing interests exist.
  3. Stephan Wolfgang Schwarzacher

    Institute of Clinical Neuroanatomy, Goethe University, Frankfurt, Germany
    Competing interests
    The authors declare that no competing interests exist.
  4. Hermann Cuntz

    Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5445-0507
  5. Peter Jedlicka

    Institute of Clinical Neuroanatomy, Goethe University, Frankfurt, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6571-5742

Funding

Deutsche Forschungsgemeinschaft (CRC1080)

  • Stephan Wolfgang Schwarzacher

Bundesministerium für Bildung und Forschung (01GQ1406)

  • Hermann Cuntz

Alzheimer Forschung Initiative (15038)

  • Peter Jedlicka

Bundesministerium für Bildung und Forschung (01GQ1203A)

  • Peter Jedlicka

Agencia Nacional de Promoción Científica y Tecnológica (PICT2013-2056)

  • Lucas Alberto Mongiat

Deutsche Forschungsgemeinschaft (JE 528/6-1)

  • Peter Jedlicka

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Frances K Skinner, Krembil Research Institute, University Health Network, Canada

Version history

  1. Received: March 10, 2017
  2. Accepted: November 21, 2017
  3. Accepted Manuscript published: November 22, 2017 (version 1)
  4. Accepted Manuscript updated: November 23, 2017 (version 2)
  5. Version of Record published: December 20, 2017 (version 3)

Copyright

© 2017, Beining et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 2,360
    views
  • 375
    downloads
  • 37
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Marcel Beining
  2. Lucas Alberto Mongiat
  3. Stephan Wolfgang Schwarzacher
  4. Hermann Cuntz
  5. Peter Jedlicka
(2017)
T2N as a new tool for robust electrophysiological modeling demonstrated for mature and adult-born dentate granule cells
eLife 6:e26517.
https://doi.org/10.7554/eLife.26517

Share this article

https://doi.org/10.7554/eLife.26517

Further reading

    1. Computational and Systems Biology
    2. Physics of Living Systems
    Taegon Chung, Iksoo Chang, Sangyeol Kim
    Research Article

    Locomotion is a fundamental behavior of Caenorhabditis elegans (C. elegans). Previous works on kinetic simulations of animals helped researchers understand the physical mechanisms of locomotion and the muscle-controlling principles of neuronal circuits as an actuator part. It has yet to be understood how C. elegans utilizes the frictional forces caused by the tension of its muscles to perform sequenced locomotive behaviors. Here, we present a two-dimensional rigid body chain model for the locomotion of C. elegans by developing Newtonian equations of motion for each body segment of C. elegans. Having accounted for friction-coefficients of the surrounding environment, elastic constants of C. elegans, and its kymogram from experiments, our kinetic model (ElegansBot) reproduced various locomotion of C. elegans such as, but not limited to, forward-backward-(omega turn)-forward locomotion constituting escaping behavior and delta-turn navigation. Additionally, ElegansBot precisely quantified the forces acting on each body segment of C. elegans to allow investigation of the force distribution. This model will facilitate our understanding of the detailed mechanism of various locomotive behaviors at any given friction-coefficients of the surrounding environment. Furthermore, as the model ensures the performance of realistic behavior, it can be used to research actuator-controller interaction between muscles and neuronal circuits.

    1. Computational and Systems Biology
    2. Genetics and Genomics
    Lauren Kuffler, Daniel A Skelly ... Gregory W Carter
    Research Article

    Gene expression is known to be affected by interactions between local genetic variation and DNA accessibility, with the latter organized into three-dimensional chromatin structures. Analyses of these interactions have previously been limited, obscuring their regulatory context, and the extent to which they occur throughout the genome. Here, we undertake a genome-scale analysis of these interactions in a genetically diverse population to systematically identify global genetic–epigenetic interaction, and reveal constraints imposed by chromatin structure. We establish the extent and structure of genotype-by-epigenotype interaction using embryonic stem cells derived from Diversity Outbred mice. This mouse population segregates millions of variants from eight inbred founders, enabling precision genetic mapping with extensive genotypic and phenotypic diversity. With 176 samples profiled for genotype, gene expression, and open chromatin, we used regression modeling to infer genetic–epigenetic interactions on a genome-wide scale. Our results demonstrate that statistical interactions between genetic variants and chromatin accessibility are common throughout the genome. We found that these interactions occur within the local area of the affected gene, and that this locality corresponds to topologically associated domains (TADs). The likelihood of interaction was most strongly defined by the three-dimensional (3D) domain structure rather than linear DNA sequence. We show that stable 3D genome structure is an effective tool to guide searches for regulatory elements and, conversely, that regulatory elements in genetically diverse populations provide a means to infer 3D genome structure. We confirmed this finding with CTCF ChIP-seq that revealed strain-specific binding in the inbred founder mice. In stem cells, open chromatin participating in the most significant regression models demonstrated an enrichment for developmental genes and the TAD-forming CTCF-binding complex, providing an opportunity for statistical inference of shifting TAD boundaries operating during early development. These findings provide evidence that genetic and epigenetic factors operate within the context of 3D chromatin structure.