Optogenetic dissection of descending behavioral control in Drosophila

  1. Jessica Cande
  2. Shigehiro Namiki
  3. Jirui Qiu
  4. Wyatt Korff
  5. Gwyneth M Card
  6. Josh W Shaevitz
  7. David L Stern  Is a corresponding author
  8. Gordon J Berman  Is a corresponding author
  1. Janelia Research Campus, Howard Hughes Medical Institute, United States
  2. Emory University, United States
  3. Princeton University, United States

Abstract

In most animals, the brain makes behavioral decisions that are transmitted by descending neurons to the nerve cord circuitry that produces behaviors. In insects, only a few descending neurons have been associated with specific behaviors. To explore how descending neurons control an insect's movements, we developed a novel method to systematically assay the behavioral effects of activating individual neurons on freely behaving terrestrial D. melanogaster. We calculated a two-dimensional representation of the entire behavior space explored by these flies and we associated descending neurons with specific behaviors by identifying regions of this space that were visited with increased frequency during optogenetic activation. Applying this approach across a large collection of descending neurons, we found that (1) activation of most of the descending neurons drove stereotyped behaviors, (2) in many cases multiple descending neurons activated similar behaviors, and (3) optogenetically-activated behaviors were often dependent on the behavioral state prior to activation.

Data availability

Videos including one second before until one second after activation for all flies during all treatments have been uploaded to Dryad (doi:10.5061/dryad.fr89c0c). We slowed down these movies 4X to allow easier examination.

The following data sets were generated

Article and author information

Author details

  1. Jessica Cande

    Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Shigehiro Namiki

    Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1559-799X
  3. Jirui Qiu

    Department of Physics, Emory University, Atlanta, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Wyatt Korff

    Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8396-1533
  5. Gwyneth M Card

    Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7679-3639
  6. Josh W Shaevitz

    Department of Physics, Princeton University, Princeton, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. David L Stern

    Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
    For correspondence
    sternd@janelia.hhmi.org
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1847-6483
  8. Gordon J Berman

    Department of Physics, Emory University, Atlanta, United States
    For correspondence
    gordon.berman@emory.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3588-7820

Funding

Howard Hughes Medical Institute

  • Jessica Cande
  • Shigehiro Namiki
  • Wyatt Korff
  • Gwyneth M Card
  • David L Stern

National Institutes of Health

  • Josh W Shaevitz
  • Gordon J Berman

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

Copyright

© 2018, Cande 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

  • 7,341
    views
  • 933
    downloads
  • 135
    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. Jessica Cande
  2. Shigehiro Namiki
  3. Jirui Qiu
  4. Wyatt Korff
  5. Gwyneth M Card
  6. Josh W Shaevitz
  7. David L Stern
  8. Gordon J Berman
(2018)
Optogenetic dissection of descending behavioral control in Drosophila
eLife 7:e34275.
https://doi.org/10.7554/eLife.34275

Share this article

https://doi.org/10.7554/eLife.34275

Further reading

    1. Neuroscience
    Matthieu Louis, Julie H Simpson
    Insight

    The neurons that connect the brain and ventral nerve cord in fruit flies have been mapped in unprecedented detail.

    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.