Chloride-dependent mechanisms of multimodal sensory discrimination and nociceptive sensitization in Drosophila

Abstract

Individual sensory neurons can be tuned to many stimuli, each driving unique, stimulus-relevant behaviors, and the ability of multimodal nociceptor neurons to discriminate between potentially harmful and innocuous stimuli is broadly important for organismal survival. Moreover, disruptions in the capacity to differentiate between noxious and innocuous stimuli can result in neuropathic pain. Drosophila larval Class III (CIII) neurons are peripheral noxious cold nociceptors and innocuous touch mechanosensors; high levels of activation drive cold-evoked contraction (CT) behavior, while low levels of activation result in a suite of touch-associated behaviors. However, it is unknown what molecular factors underlie CIII multimodality. Here, we show that the TMEM16/anoctamins subdued and white walker (wwk; CG15270) are required for cold-evoked CT, but not for touch-associated behavior, indicating a conserved role for anoctamins in nociception. We also evidence that CIII neurons make use of atypical depolarizing chloride currents to encode cold, and that overexpression of ncc69-a fly homologue of NKCC1-results in phenotypes consistent with neuropathic sensitization, including behavioral sensitization and neuronal hyperexcitability, making Drosophila CIII neurons a candidate system for future studies of the basic mechanisms underlying neuropathic pain

Data availability

All data generated or analyzed during this study are included in the manuscript. We have plotted all data such that individual data points can be seen. Additionally, we have included heatmap representations of cold-evoked larval behavior for every single larva used in this study (see supplemental figures). Class III neuron-specific transcriptomic data has been deposited in GEO under accession number GSE69353. Accession numbers for sequences used in phylogenetic analysis are presented in the relevant figure. Raw data and sequence files are available in Dryad.

The following previously published data sets were used

Article and author information

Author details

  1. Nathaniel J Himmel

    Neuroscience Institute, Georgia State University, Atlanta, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7876-6960
  2. Akira Sakurai

    Neuroscience Institute, Georgia State University, Atlanta, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2858-1620
  3. Atit A Patel

    Neuroscience Institute, Georgia State University, Atlanta, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Shatabdi Bhattacharjee

    Neuroscience Institute, Georgia State University, Atlanta, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Jamin M Letcher

    Neuroscience Institute, Georgia State University, Atlanta, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3077-0615
  6. Maggie N Benson

    Neuroscience Institute, Georgia State University, Atlanta, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Thomas R Gray

    Neuroscience Institute, Georgia State University, Atlanta, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6176-005X
  8. Gennady S Cymbalyuk

    Neuroscience Institute, Georgia State University, Atlanta, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1889-5397
  9. Daniel N Cox

    Neuroscience Institute, Georgia State University, Atlanta, United States
    For correspondence
    dcox18@gsu.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9191-9212

Funding

National Institutes of Health (NS115209)

  • Gennady S Cymbalyuk
  • Daniel N Cox

National Institutes of Health (NS117087)

  • Nathaniel J Himmel

Georgia State University (Honeycutt Fellowship)

  • Nathaniel J Himmel
  • Atit A Patel

Georgia State University (Brains & Behavior Fellowship)

  • Nathaniel J Himmel
  • Atit A Patel
  • Jamin M Letcher

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

Reviewing Editor

  1. Ishmail Abdus-Saboor, Columbia University, United States

Version history

  1. Preprint posted: December 11, 2021 (view preprint)
  2. Received: January 7, 2022
  3. Accepted: January 19, 2023
  4. Accepted Manuscript published: January 23, 2023 (version 1)
  5. Version of Record published: February 7, 2023 (version 2)

Copyright

© 2023, Himmel 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

  • 1,114
    views
  • 175
    downloads
  • 6
    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. Nathaniel J Himmel
  2. Akira Sakurai
  3. Atit A Patel
  4. Shatabdi Bhattacharjee
  5. Jamin M Letcher
  6. Maggie N Benson
  7. Thomas R Gray
  8. Gennady S Cymbalyuk
  9. Daniel N Cox
(2023)
Chloride-dependent mechanisms of multimodal sensory discrimination and nociceptive sensitization in Drosophila
eLife 12:e76863.
https://doi.org/10.7554/eLife.76863

Share this article

https://doi.org/10.7554/eLife.76863

Further reading

    1. Neuroscience
    Zahid Padamsey, Danai Katsanevaki ... Nathalie L Rochefort
    Research Article

    Mammals have evolved sex-specific adaptations to reduce energy usage in times of food scarcity. These adaptations are well described for peripheral tissue, though much less is known about how the energy-expensive brain adapts to food restriction, and how such adaptations differ across the sexes. Here, we examined how food restriction impacts energy usage and function in the primary visual cortex (V1) of adult male and female mice. Molecular analysis and RNA sequencing in V1 revealed that in males, but not in females, food restriction significantly modulated canonical, energy-regulating pathways, including pathways associated waith AMP-activated protein kinase, peroxisome proliferator-activated receptor alpha, mammalian target of rapamycin, and oxidative phosphorylation. Moreover, we found that in contrast to males, food restriction in females did not significantly affect V1 ATP usage or visual coding precision (assessed by orientation selectivity). Decreased serum leptin is known to be necessary for triggering energy-saving changes in V1 during food restriction. Consistent with this, we found significantly decreased serum leptin in food-restricted males but no significant change in food-restricted females. Collectively, our findings demonstrate that cortical function and energy usage in female mice are more resilient to food restriction than in males. The neocortex, therefore, contributes to sex-specific, energy-saving adaptations in response to food restriction.

    1. Neuroscience
    Jack W Lindsey, Elias B Issa
    Research Article

    Object classification has been proposed as a principal objective of the primate ventral visual stream and has been used as an optimization target for deep neural network models (DNNs) of the visual system. However, visual brain areas represent many different types of information, and optimizing for classification of object identity alone does not constrain how other information may be encoded in visual representations. Information about different scene parameters may be discarded altogether (‘invariance’), represented in non-interfering subspaces of population activity (‘factorization’) or encoded in an entangled fashion. In this work, we provide evidence that factorization is a normative principle of biological visual representations. In the monkey ventral visual hierarchy, we found that factorization of object pose and background information from object identity increased in higher-level regions and strongly contributed to improving object identity decoding performance. We then conducted a large-scale analysis of factorization of individual scene parameters – lighting, background, camera viewpoint, and object pose – in a diverse library of DNN models of the visual system. Models which best matched neural, fMRI, and behavioral data from both monkeys and humans across 12 datasets tended to be those which factorized scene parameters most strongly. Notably, invariance to these parameters was not as consistently associated with matches to neural and behavioral data, suggesting that maintaining non-class information in factorized activity subspaces is often preferred to dropping it altogether. Thus, we propose that factorization of visual scene information is a widely used strategy in brains and DNN models thereof.