Sushi domain-containing protein 4 controls synaptic plasticity and motor learning

Abstract

Fine control of protein stoichiometry at synapses underlies brain function and plasticity. How proteostasis is controlled independently for each type of synaptic protein in a synapse-specific and activity-dependent manner remains unclear. Here we show that Susd4, a gene coding for a complement-related transmembrane protein, is expressed by many neuronal populations starting at the time of synapse formation. Constitutive loss-of-function of Susd4 in the mouse impairs motor coordination adaptation and learning, prevents long-term depression at cerebellar synapses, and leads to misregulation of activity-dependent AMPA receptor subunit GluA2 degradation. We identified several proteins with known roles in the regulation of AMPA receptor turnover, in particular ubiquitin ligases of the NEDD4 subfamily, as SUSD4 binding partners. Our findings shed light on the potential role of SUSD4 mutations in neurodevelopmental diseases.

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. Inés Gonzalez-Calvo

    CIRB, Collège de France, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  2. Keerthana Iyer

    CIRB, Collège de France, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  3. Mélanie Carquin

    CIRB, Collège de France, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  4. Anouar Khayachi

    CIRB, Collège de France, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  5. Fernando A Giuliani

    Institut de Neurosciences Cellulaires et Intégratives, CNRS, Strasbourg, France
    Competing interests
    The authors declare that no competing interests exist.
  6. Séverine M Sigoillot

    CIRB, Collège de France, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  7. Jean Vincent

    Institut Biology Paris Seine, Sorbonne University, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  8. Martial Séveno

    BioCampus Montpellier, CNRS, Montpellier, France
    Competing interests
    The authors declare that no competing interests exist.
  9. Maxime Veleanu

    CIRB, Collège de France, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  10. Sylvana Tahraoui

    CIRB, Collège de France, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  11. Mélanie Albert

    CIRB, Collège de France, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  12. Oana Vigy

    BioCampus Montpellier, CNRS, Montpellier, France
    Competing interests
    The authors declare that no competing interests exist.
  13. Célia Bosso-Lefèvre

    CIRB, Collège de France, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  14. Yann Nadjar

    IBENS, École Normale Supérieure, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  15. Andréa Dumoulin

    IBENS - Biologie, École Normale Supérieure, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  16. Antoine Triller

    IBENS - Biologie, École Normale Supérieure, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  17. JeanLouis Bessereau

    Institut NeuroMyoGene, University of Lyon - INSERM - CNRS, Lyon, France
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3088-7621
  18. Laure Rondi-Reig

    Institut de Biologie Paris Seine (IBPS) - Neuroscience, Université Pierre et Marie Curie (UPMC), Paris, France
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1006-0501
  19. Philippe Isope

    Institut de Neurosciences Cellulaires et Intégratives, CNRS, Strasbourg, France
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0630-5935
  20. Fekrije Selimi

    CIRB, Collège de France, Paris, France
    For correspondence
    fekrije.selimi@college-de-france.fr
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7704-5897

Funding

ATIP-AVENIR (RSE11005JSA)

  • Fekrije Selimi

Labex MEMOLIFE (ANR-10-LABX-54 MEMO LIFE)

  • Keerthana Iyer

Ecole des Neurosciences de Paris

  • Keerthana Iyer

Labex BIOPSY (ANR-11-IDEX-0004-02)

  • Laure Rondi-Reig

Idex PSL (ANR-10-IDEX-0001-02 PSL*)

  • Fekrije Selimi

Agence Nationale de la Recherche (ANR 9139SAMA90010901)

  • Fekrije Selimi

Agence Nationale de la Recherche (ANR 9139SAMA90010901)

  • Philippe Isope

Agence Nationale de la Recherche (ANR-15-CE37-0001-01 CeMod)

  • Fekrije Selimi

Agence Nationale de la Recherche (ANR-15-CE37-0001-01 CeMod)

  • Philippe Isope

Fondation pour la Recherche Médicale (DEQ20150331748)

  • Fekrije Selimi

Fondation pour la Recherche Médicale (DEQ20140329514)

  • Philippe Isope

H2020 European Research Council (SynID 724601)

  • Fekrije Selimi

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 animal protocols were approved by the Comité Regional d'Ethique en Experimentation Animale (no. 00057.01) and animals were housed in authorized facilities of the CIRB (# C75 05 12).

Copyright

© 2021, Gonzalez-Calvo 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

  • 2,514
    views
  • 299
    downloads
  • 18
    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. Inés Gonzalez-Calvo
  2. Keerthana Iyer
  3. Mélanie Carquin
  4. Anouar Khayachi
  5. Fernando A Giuliani
  6. Séverine M Sigoillot
  7. Jean Vincent
  8. Martial Séveno
  9. Maxime Veleanu
  10. Sylvana Tahraoui
  11. Mélanie Albert
  12. Oana Vigy
  13. Célia Bosso-Lefèvre
  14. Yann Nadjar
  15. Andréa Dumoulin
  16. Antoine Triller
  17. JeanLouis Bessereau
  18. Laure Rondi-Reig
  19. Philippe Isope
  20. Fekrije Selimi
(2021)
Sushi domain-containing protein 4 controls synaptic plasticity and motor learning
eLife 10:e65712.
https://doi.org/10.7554/eLife.65712

Share this article

https://doi.org/10.7554/eLife.65712

Further reading

    1. Computational and Systems Biology
    2. Neuroscience
    Anna Cattani, Don B Arnold ... Nancy Kopell
    Research Article

    The basolateral amygdala (BLA) is a key site where fear learning takes place through synaptic plasticity. Rodent research shows prominent low theta (~3–6 Hz), high theta (~6–12 Hz), and gamma (>30 Hz) rhythms in the BLA local field potential recordings. However, it is not understood what role these rhythms play in supporting the plasticity. Here, we create a biophysically detailed model of the BLA circuit to show that several classes of interneurons (PV, SOM, and VIP) in the BLA can be critically involved in producing the rhythms; these rhythms promote the formation of a dedicated fear circuit shaped through spike-timing-dependent plasticity. Each class of interneurons is necessary for the plasticity. We find that the low theta rhythm is a biomarker of successful fear conditioning. The model makes use of interneurons commonly found in the cortex and, hence, may apply to a wide variety of associative learning situations.

    1. Neuroscience
    Bharath Krishnan, Noah Cowan
    Insight

    Mice can generate a cognitive map of an environment based on self-motion signals when there is a fixed association between their starting point and the location of their goal.