Continuous odor profile monitoring to study olfactory navigation in small animals

  1. Kevin S Chen
  2. Rui Wu
  3. Marc H Gershow  Is a corresponding author
  4. Andrew Michael Leifer  Is a corresponding author
  1. Princeton University, United States
  2. New York University, United States

Abstract

Olfactory navigation is observed across species and plays a crucial role in locating resources for survival. In the laboratory, understanding the behavioral strategies and neural circuits underlying odor-taxis requires a detailed understanding of the animal's sensory environment. For small model organisms like C. elegans and larval D. melanogaster, controlling and measuring the odor environment experienced by the animal can be challenging, especially for airborne odors, which are subject to subtle effects from airflow, temperature variation, and from the odor's adhesion, adsorption or reemission. Here we present a method to control and measure airborne odor concentration in an arena compatible with an agar substrate. Our method allows continuous controlling and monitoring of the odor profile while imaging animal behavior. We construct stationary chemical landscapes in an odor flow chamber through spatially patterned odorized air. The odor concentration is measured with a spatially distributed array of digital gas sensors. Careful placement of the sensors allows the odor concentration across the arena to be continuously inferred in space and monitored through time. We use this approach to measure the odor concentration that each animal experiences as it undergoes chemotaxis behavior and report chemotaxis strategies for C. elegans and D. melanogaster larvae populations as they navigate spatial odor landscapes.

Data availability

Recordings for odor flow control, concentration measurements, and behavioral tracking data are publicly available: https://doi.org/10.6084/m9.figshare.21737303. Compressed 'zip' archive Chen_flow_20222.zip contains raw data. Compressed 'zip' archive flow_chamber_machined_components.zip contains CAD and other design files related to the hardware.

Article and author information

Author details

  1. Kevin S Chen

    Princeton Neuroscience Institute, Princeton University, Princeton, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Rui Wu

    Department of Physics, New York University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Marc H Gershow

    Department of Physics, New York University, New York, United States
    For correspondence
    marc.gershow@nyu.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7528-6101
  4. Andrew Michael Leifer

    Princeton Neuroscience Institute, Princeton University, Princeton, United States
    For correspondence
    leifer@princeton.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5362-5093

Funding

National Institute of Neurological Disorders and Stroke (DP2-NS116768)

  • Andrew Michael Leifer

National Institute of Neurological Disorders and Stroke (DP2-EB022359)

  • Marc H Gershow

Simons Foundation (SCGB #543003)

  • Andrew Michael Leifer

National Science Foundation (1455015)

  • Marc H Gershow

National Science Foundation (IOS-1845137)

  • Andrew Michael Leifer

National Science Foundation (PHY-1748958)

  • Marc H Gershow
  • Andrew Michael Leifer

National Science Foundation (PHY-1734030)

  • Andrew Michael Leifer

Gordon and Betty Moore Foundation (2919.02)

  • Marc H Gershow
  • Andrew Michael Leifer

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

Reviewing Editor

  1. Matthieu Louis, University of California, Santa Barbara, United States

Version history

  1. Received: January 3, 2023
  2. Preprint posted: January 14, 2023 (view preprint)
  3. Accepted: July 21, 2023
  4. Accepted Manuscript published: July 25, 2023 (version 1)
  5. Version of Record published: August 11, 2023 (version 2)

Copyright

© 2023, Chen 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.

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  1. Kevin S Chen
  2. Rui Wu
  3. Marc H Gershow
  4. Andrew Michael Leifer
(2023)
Continuous odor profile monitoring to study olfactory navigation in small animals
eLife 12:e85910.
https://doi.org/10.7554/eLife.85910

Share this article

https://doi.org/10.7554/eLife.85910

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