1. Neuroscience
Download icon

Restoration of Mecp2 expression in GABAergic neurons is sufficient to rescue multiple disease features in a mouse model of Rett Syndrome

Research Article
  • Cited 51
  • Views 3,155
  • Annotations
Cite this article as: eLife 2016;5:e14198 doi: 10.7554/eLife.14198

Abstract

The postnatal neurodevelopmental disorder Rett syndrome, caused by mutations in MECP2, produces a diverse array of symptoms, including loss of language, motor, and social skills and the development of hand stereotypies, anxiety, tremor, ataxia, respiratory dysrhythmias, and seizures. Surprisingly, despite the diversity of these features, we have found that deleting Mecp2 only from GABAergic inhibitory neurons in mice replicates most of this phenotype. Here we show that genetically restoring Mecp2 expression only in GABAergic neurons of male Mecp2 null mice enhanced inhibitory signaling, extended lifespan, and rescued ataxia, apraxia, and social abnormalities but did not rescue tremor or anxiety. Female Mecp2+/- mice showed a less dramatic but still substantial rescue. These findings highlight the critical regulatory role of GABAergic neurons in certain behaviors and suggest that modulating the excitatory/inhibitory balance through GABAergic neurons could prove a viable therapeutic option in Rett syndrome.

Article and author information

Author details

  1. Kerstin Ure

    Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, United States
    Competing interests
    No competing interests declared.
  2. Hui Lu

    Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, United States
    Competing interests
    No competing interests declared.
  3. Wei Wang

    Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, United States
    Competing interests
    No competing interests declared.
  4. Aya Ito-Ishida

    Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, United States
    Competing interests
    No competing interests declared.
  5. Zhenyu Wu

    Department of Pediatrics, Baylor College of Medicine, Houston, United States
    Competing interests
    No competing interests declared.
  6. Ling-jie He

    Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, United States
    Competing interests
    No competing interests declared.
  7. Yehezkel Sztainberg

    Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, United States
    Competing interests
    No competing interests declared.
  8. Wu Chen

    Department of Neuroscience, Baylor College of Medicine, Houston, United States
    Competing interests
    No competing interests declared.
  9. Jianrong Tang

    Department of Pediatrics, Baylor College of Medicine, Houston, United States
    Competing interests
    No competing interests declared.
  10. Huda Y Zoghbi

    Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, United States
    For correspondence
    hzoghbi@bcm.edu
    Competing interests
    Huda Y Zoghbi, Senior editor, eLife.

Ethics

Animal experimentation: All mouse care and manipulation was approved by the Baylor College of Medicine Institutional Animal Care and Use Committee (IACUC, Protocol AN-1013). Every effort was made to minimize suffering.

Reviewing Editor

  1. Catherine Dulac, Howard Hughes Medical Institute, Harvard University, United States

Publication history

  1. Received: January 4, 2016
  2. Accepted: June 9, 2016
  3. Accepted Manuscript published: June 21, 2016 (version 1)
  4. Version of Record published: July 15, 2016 (version 2)

Copyright

© 2016, Ure 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

  • 3,155
    Page views
  • 925
    Downloads
  • 51
    Citations

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

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
    Toshihide W Yoshioka et al.
    Research Article

    The division of labor between the dorsal and ventral visual pathways has been well studied, but not often with direct comparison at the single-neuron resolution with matched stimuli. Here we directly compared how single neurons in MT and V4, mid-tier areas of the two pathways, process binocular disparity, a powerful cue for 3D perception and actions. We found that MT neurons transmitted disparity signals more quickly and robustly, whereas V4 or its upstream neurons transformed the signals into sophisticated representations more prominently. Therefore, signaling speed and robustness were traded for transformation between the dorsal and ventral pathways. The key factor in this tradeoff was disparity-tuning shape: V4 neurons had more even-symmetric tuning than MT neurons. Moreover, the tuning symmetry predicted the degree of signal transformation across neurons similarly within each area, implying a general role of tuning symmetry in the stereoscopic processing by the two pathways.

    1. Computational and Systems Biology
    2. Neuroscience
    Shivesh Chaudhary et al.
    Research Article

    Although identifying cell names in dense image stacks is critical in analyzing functional whole-brain data enabling comparison across experiments, unbiased identification is very difficult, and relies heavily on researchers' experiences. Here we present a probabilistic-graphical-model framework, CRF_ID, based on Conditional Random Fields, for unbiased and automated cell identification. CRF_ID focuses on maximizing intrinsic similarity between shapes. Compared to existing methods, CRF_ID achieves higher accuracy on simulated and ground-truth experimental datasets, and better robustness against challenging noise conditions common in experimental data. CRF_ID can further boost accuracy by building atlases from annotated data in highly computationally efficient manner, and by easily adding new features (e.g. from new strains). We demonstrate cell annotation in C. elegans images across strains, animal orientations, and tasks including gene-expression localization, multi-cellular and whole-brain functional imaging experiments. Together, these successes demonstrate that unbiased cell annotation can facilitate biological discovery, and this approach may be valuable to annotation tasks for other systems.