1. Neuroscience
Download icon

Essential role for InSyn1 in dystroglycan complex integrity and cognitive behaviors in mice

Research Article
  • Cited 3
  • Views 1,445
  • Annotations
Cite this article as: eLife 2019;8:e50712 doi: 10.7554/eLife.50712

Abstract

Human mutations in the dystroglycan complex (DGC) result in not only muscular dystrophy but also cognitive impairments. However, the molecular architecture critical for the synaptic organization of the DGC in neurons remains elusive. Here we report Inhibitory Synaptic protein 1 (InSyn1) is a critical component of the DGC whose loss alters the composition of the GABAergic synapses, excitatory/inhibitory balance in vitro and in vivo, and cognitive behavior. Association of InSyn1 with DGC subunits is required for InSyn1 synaptic localization. InSyn1 null neurons also show a significant reduction in DGC and GABA receptor distribution as well as abnormal neuronal network activity. Moreover, InSyn1 null mice exhibit elevated neuronal firing patterns in the hippocampus and deficits in fear conditioning memory. Our results support the dysregulation of the DGC at inhibitory synapses and altered neuronal network activity and specific cognitive tasks via loss of a novel component, InSyn1.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files.

Article and author information

Author details

  1. Akiyoshi Uezu

    Department of Cell Biology, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8478-4460
  2. Erin Hisey

    Department of Cell Biology, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Yoshihiko Kobayashi

    Department of Cell Biology, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7031-1478
  4. Yudong Gao

    Department of Cell Biology, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Tyler WA Bradshaw

    Department of Cell Biology, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Patrick Devlin

    Department of Cell Biology, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0359-4620
  7. Ramona Rodriguiz

    Department of Psychiatry and Behavioral Sciences, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Purushothama Rao Tata

    Department of Cell Biology, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4837-0337
  9. Scott Soderling

    Department of Cell Biology, Duke University, Durham, United States
    For correspondence
    scott.soderling@duke.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7808-197X

Funding

National Institute of Neurological Disorders and Stroke (NS102456)

  • Scott Soderling

National Heart, Lung, and Blood Institute (HL127181)

  • Purushothama Rao Tata

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

Ethics

Animal experimentation: All procedures were conducted with a protocol (#A224-17-09) approved by the Duke University Institutional Animal Care and Use Committee (IACUC) in accordance with the US National Institutes of Health guidelines.

Reviewing Editor

  1. Graeme W Davis, University of California, San Francisco, United States

Publication history

  1. Received: July 30, 2019
  2. Accepted: December 11, 2019
  3. Accepted Manuscript published: December 12, 2019 (version 1)
  4. Version of Record published: January 6, 2020 (version 2)

Copyright

© 2019, Uezu 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

  • 1,445
    Page views
  • 254
    Downloads
  • 3
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

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)

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

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

Further reading

    1. Neuroscience
    Justin W Kenney et al.
    Tools and Resources Updated

    Zebrafish have made significant contributions to our understanding of the vertebrate brain and the neural basis of behavior, earning a place as one of the most widely used model organisms in neuroscience. Their appeal arises from the marriage of low cost, early life transparency, and ease of genetic manipulation with a behavioral repertoire that becomes more sophisticated as animals transition from larvae to adults. To further enhance the use of adult zebrafish, we created the first fully segmented three-dimensional digital adult zebrafish brain atlas (AZBA). AZBA was built by combining tissue clearing, light-sheet fluorescence microscopy, and three-dimensional image registration of nuclear and antibody stains. These images were used to guide segmentation of the atlas into over 200 neuroanatomical regions comprising the entirety of the adult zebrafish brain. As an open source, online (azba.wayne.edu), updatable digital resource, AZBA will significantly enhance the use of adult zebrafish in furthering our understanding of vertebrate brain function in both health and disease.

    1. Neuroscience
    Cédric Foucault, Florent Meyniel
    Research Article

    From decision making to perception to language, predicting what is coming next is crucial. It is also challenging in stochastic, changing, and structured environments; yet the brain makes accurate predictions in many situations. What computational architecture could enable this feat? Bayesian inference makes optimal predictions but is prohibitively difficult to compute. Here, we show that a specific recurrent neural network architecture enables simple and accurate solutions in several environments. This architecture relies on three mechanisms: gating, lateral connections, and recurrent weight training. Like the optimal solution and the human brain, such networks develop internal representations of their changing environment (including estimates of the environment's latent variables and the precision of these estimates), leverage multiple levels of latent structure, and adapt their effective learning rate to changes without changing their connection weights. Being ubiquitous in the brain, gated recurrence could therefore serve as a generic building block to predict in real-life environments.