Control of neurotransmitter release by two distinctmembrane-binding faces of the Munc13-1 C­1C2B region

  1. Marcial Camacho
  2. Bradley Quade
  3. Thorsten Trimbuch
  4. Junjie Xu
  5. Levent Sari
  6. Josep Rizo  Is a corresponding author
  7. Christian Rosenmund  Is a corresponding author
  1. Charité-Universitätsmedizin Berlin, Germany
  2. University of Texas Southwestern Medical Center, United States
  3. Charité Universitätsmedizin Berlin, Germany
  4. The University of Texas Southwestern Medical Center, United States

Abstract

Munc13-1 plays a central role in neurotransmitter release through its conserved C-terminal region, which includes a diacyglycerol (DAG)-binding C1 domain, a Ca2+/PIP2-binding C2B domain, a MUN domain and a C2C domain. Munc13-1 was proposed to bridge synaptic vesicles to the plasma membrane through distinct interactions of the C­1C2B region with the plasma membrane: i) one involving a polybasic face that is expected to yield a perpendicular orientation of Munc13-1 and hinder release; and ii) another involving the DAG-Ca2+-PIP2-binding face that is predicted to result in a slanted orientation and facilitate release. Here we have tested this model and investigated the role of the C­1C2B region in neurotransmitter release. We find that K603E or R769E point mutations in the polybasic face severely impair Ca2+-independent liposome bridging and fusion in in vitro reconstitution assays, and synaptic vesicle priming in primary murine hippocampal cultures. A K720E mutation in the polybasic face and a K706E mutation in the C2B domain Ca2+-binding loops have milder effects in reconstitution assays and do not affect vesicle priming, but enhance or impair Ca2+-evoked release, respectively. The phenotypes caused by combining these mutations are dominated by the K603E and R769E mutations. Our results show that the C1-C2B region of Munc13-1 plays a central role in vesicle priming and support the notion that two distinct faces of this region control neurotransmitter release and short-term presynaptic plasticity.

Data availability

Source data files are provided for all data figure panels.

Article and author information

Author details

  1. Marcial Camacho

    Department of Neurophysiology, Charité-Universitätsmedizin Berlin, Berlin, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2367-1259
  2. Bradley Quade

    Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5330-1355
  3. Thorsten Trimbuch

    Department of Neurophysiology, Charité Universitätsmedizin Berlin, Berlin, Germany
    Competing interests
    The authors declare that no competing interests exist.
  4. Junjie Xu

    Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Levent Sari

    Green Center for Molecular, Computational, and Systems Biology, The University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Josep Rizo

    Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, United States
    For correspondence
    Jose.Rizo-Rey@UTSouthwestern.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1773-8311
  7. Christian Rosenmund

    Institut für Neurophysiologie, Charité Universitätsmedizin Berlin, Berlin, Germany
    For correspondence
    christian.rosenmund@charite.de
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3905-2444

Funding

National Institute of Neurological Disorders and Stroke (R35 NS097333)

  • Josep Rizo

Welch Foundation (I-1304)

  • Josep Rizo

German Research Council (958)

  • Christian Rosenmund

Reinhart Koselleck project

  • Christian Rosenmund

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

Ethics

Animal experimentation: Animal Welfare Committee of Charité - Universitätsmedizin Berlin and the Berlin state government agency for Health and Social Services approved all protocols for animal maintenance and experiments (license no. G106/20).

Reviewing Editor

  1. Reinhard Jahn, Max Planck Institute for Biophysical Chemistry, Germany

Publication history

  1. Received: July 7, 2021
  2. Accepted: November 14, 2021
  3. Accepted Manuscript published: November 15, 2021 (version 1)
  4. Version of Record published: December 6, 2021 (version 2)

Copyright

© 2021, Camacho 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

  • 603
    Page views
  • 143
    Downloads
  • 8
    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)

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. Marcial Camacho
  2. Bradley Quade
  3. Thorsten Trimbuch
  4. Junjie Xu
  5. Levent Sari
  6. Josep Rizo
  7. Christian Rosenmund
(2021)
Control of neurotransmitter release by two distinctmembrane-binding faces of the Munc13-1 C­1C2B region
eLife 10:e72030.
https://doi.org/10.7554/eLife.72030

Further reading

    1. Computational and Systems Biology
    2. Neuroscience
    Roshan Prakash Rane et al.
    Research Article Updated

    Alcohol misuse during adolescence (AAM) has been associated with disruptive development of adolescent brains. In this longitudinal machine learning (ML) study, we could predict AAM significantly from brain structure (T1-weighted imaging and DTI) with accuracies of 73 -78% in the IMAGEN dataset (n∼1182). Our results not only show that structural differences in brain can predict AAM, but also suggests that such differences might precede AAM behavior in the data. We predicted 10 phenotypes of AAM at age 22 using brain MRI features at ages 14, 19, and 22. Binge drinking was found to be the most predictable phenotype. The most informative brain features were located in the ventricular CSF, and in white matter tracts of the corpus callosum, internal capsule, and brain stem. In the cortex, they were spread across the occipital, frontal, and temporal lobes and in the cingulate cortex. We also experimented with four different ML models and several confound control techniques. Support Vector Machine (SVM) with rbf kernel and Gradient Boosting consistently performed better than the linear models, linear SVM and Logistic Regression. Our study also demonstrates how the choice of the predicted phenotype, ML model, and confound correction technique are all crucial decisions in an explorative ML study analyzing psychiatric disorders with small effect sizes such as AAM.

    1. Neuroscience
    Samantha S Cohen et al.
    Research Article

    How does the representation of naturalistic life events change with age? Here we analyzed fMRI data from 414 children and adolescents (5 - 19 years) as they watched a narrative movie. In addition to changes in the degree of inter-subject correlation (ISC) with age in sensory and medial parietal regions, we used a novel measure (between-group ISC) to reveal age-related shifts in the responses across the majority of the neocortex. Over the course of development, brain responses became more discretized into stable and coherent events and shifted earlier in time to anticipate upcoming perceived event transitions, measured behaviorally in an age-matched sample. However, hippocampal responses to event boundaries actually decreased with age, suggesting a shifting division of labor between episodic encoding processes and schematic event representations between the ages of 5 and 19.