Botulinum neurotoxin accurately separates tonic vs phasic transmission and reveals heterosynaptic plasticity rules in Drosophila

  1. Yifu Han
  2. Chun Chien
  3. Pragya Goel
  4. Kaikai He
  5. Cristian Pinales
  6. Christopher Buser
  7. Dion K Dickman  Is a corresponding author
  1. University of Southern California, United States
  2. Oak Crest Institute of Science, United States

Abstract

In developing and mature nervous systems, diverse neuronal subtypes innervate common targets to establish, maintain, and modify neural circuit function. A major challenge towards understanding the structural and functional architecture of neural circuits is to separate these inputs and determine their intrinsic and heterosynaptic relationships. The Drosophila larval neuromuscular junction is a powerful model system to study these questions, where two glutamatergic motor neurons, the strong phasic-like <strong>Is</strong> and weak tonic-like <strong>Ib</strong>, co-innervate individual muscle targets to coordinate locomotor behavior. However, complete neurotransmission from each input has never been electrophysiologically separated. We have employed a botulinum neurotoxin, BoNT-C, that eliminates both spontaneous and evoked neurotransmission without perturbing synaptic growth or structure, enabling the first approach that accurately isolates input-specific neurotransmission. Selective expression of BoNT-C in Is or Ib motor neurons disambiguates the functional properties of each input. Importantly, the blended values of Is+Ib neurotransmission can be fully recapitulated by isolated physiology from each input. Finally, selective silencing by BoNT-C does not induce heterosynaptic structural or functional plasticity at the convergent input. Thus, BoNT-C establishes the first approach to accurately separate neurotransmission between tonic vs phasic neurons and defines heterosynaptic plasticity rules in a powerful model glutamatergic circuit.

Data availability

All data generated or analyzed during this study are included in the manuscript and supporting files. In particular, full details of the data are included in Supplemental files 1 and 2.

Article and author information

Author details

  1. Yifu Han

    Department of Neurobiology, University of Southern California, Los Angeles, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1201-654X
  2. Chun Chien

    Department of Neurobiology, University of Southern California, Los Angeles, United States
    Competing interests
    No competing interests declared.
  3. Pragya Goel

    Department of Neurobiology, University of Southern California, Los Angeles, United States
    Competing interests
    No competing interests declared.
  4. Kaikai He

    Department of Neurobiology, University of Southern California, Los Angeles, United States
    Competing interests
    No competing interests declared.
  5. Cristian Pinales

    Oak Crest Institute of Science, Monrovia, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0826-5308
  6. Christopher Buser

    Oak Crest Institute of Science, Monrovia, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4379-3878
  7. Dion K Dickman

    Department of Neurobiology, University of Southern California, Los Angeles, United States
    For correspondence
    dickman@usc.edu
    Competing interests
    Dion K Dickman, Reviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1884-284X

Funding

National Institutes of Health (NS091546)

  • Dion K Dickman

National Institutes of Health (NS111414)

  • Dion K Dickman

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

Copyright

© 2022, Han 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

  • 2,596
    views
  • 447
    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. Yifu Han
  2. Chun Chien
  3. Pragya Goel
  4. Kaikai He
  5. Cristian Pinales
  6. Christopher Buser
  7. Dion K Dickman
(2022)
Botulinum neurotoxin accurately separates tonic vs phasic transmission and reveals heterosynaptic plasticity rules in Drosophila
eLife 11:e77924.
https://doi.org/10.7554/eLife.77924

Share this article

https://doi.org/10.7554/eLife.77924

Further reading

    1. Neuroscience
    Geoffrey W Meissner, Allison Vannan ... FlyLight Project Team
    Research Article

    Techniques that enable precise manipulations of subsets of neurons in the fly central nervous system (CNS) have greatly facilitated our understanding of the neural basis of behavior. Split-GAL4 driver lines allow specific targeting of cell types in Drosophila melanogaster and other species. We describe here a collection of 3060 lines targeting a range of cell types in the adult Drosophila CNS and 1373 lines characterized in third-instar larvae. These tools enable functional, transcriptomic, and proteomic studies based on precise anatomical targeting. NeuronBridge and other search tools relate light microscopy images of these split-GAL4 lines to connectomes reconstructed from electron microscopy images. The collections are the result of screening over 77,000 split hemidriver combinations. Previously published and new lines are included, all validated for driver expression and curated for optimal cell-type specificity across diverse cell types. In addition to images and fly stocks for these well-characterized lines, we make available 300,000 new 3D images of other split-GAL4 lines.

    1. Neuroscience
    Hyun Jee Lee, Jingting Liang ... Hang Lu
    Research Advance

    Cell identification is an important yet difficult process in data analysis of biological images. Previously, we developed an automated cell identification method called CRF_ID and demonstrated its high performance in Caenorhabditis elegans whole-brain images (Chaudhary et al., 2021). However, because the method was optimized for whole-brain imaging, comparable performance could not be guaranteed for application in commonly used C. elegans multi-cell images that display a subpopulation of cells. Here, we present an advancement, CRF_ID 2.0, that expands the generalizability of the method to multi-cell imaging beyond whole-brain imaging. To illustrate the application of the advance, we show the characterization of CRF_ID 2.0 in multi-cell imaging and cell-specific gene expression analysis in C. elegans. This work demonstrates that high-accuracy automated cell annotation in multi-cell imaging can expedite cell identification and reduce its subjectivity in C. elegans and potentially other biological images of various origins.