Male pheromones modulate synaptic transmission at the C. elegans neuromuscular junction in a sexually dimorphic manner

  1. Kang-Ying Qian
  2. Wan-Xin Zeng
  3. Yue Hao
  4. Xian-Ting Zeng
  5. Haowen Liu
  6. Lei Li
  7. Lili Chen
  8. Fu-min Tian
  9. Cindy Chang
  10. Qi Hall
  11. Chun-Xue Song
  12. Shangbang Gao
  13. Zhi-Tao Hu
  14. Josh M Kaplan
  15. Qian Li  Is a corresponding author
  16. Xia-Jing Tong  Is a corresponding author
  1. ShanghaiTech University, China
  2. The University of Queensland, Australia
  3. College of Life Science and Technology, China
  4. Massachusetts General Hospital, United States
  5. Shanghai Jiao Tong University School of Medicine, China

Abstract

The development of functional synapses in the nervous system is important for animal physiology and behaviors, and its disturbance has been linked with many neurodevelopmental disorders. The synaptic transmission efficacy can be modulated by the environment to accommodate external changes, which is crucial for animal reproduction and survival. However, the underlying plasticity of synaptic transmission remains poorly understood. Here we show that in C. elegans, the male environment increases the hermaphrodite cholinergic transmission at the neuromuscular junction (NMJ), which alters hermaphrodites' locomotion velocity and mating efficiency. We identify that the male-specific pheromones mediate this synaptic transmission modulation effect in a developmental stage-dependent manner. Dissection of the sensory circuits reveals that the AWB chemosensory neurons sense those male pheromones and further transduce the information to NMJ using cGMP signaling. Exposure of hermaphrodites to the male pheromones specifically increases the accumulation of presynaptic CaV2 calcium channels and clustering of postsynaptic acetylcholine receptors at cholinergic synapses of NMJ, which potentiates cholinergic synaptic transmission. Thus, our study demonstrates a circuit mechanism for synaptic modulation and behavioral flexibility by sexual dimorphic pheromones.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files. Source data files have been provided. For other information (such as primers), we already included them in the methods.

Article and author information

Author details

  1. Kang-Ying Qian

    School of Life Science and Technology, ShanghaiTech University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  2. Wan-Xin Zeng

    School of Life Science and Technology, ShanghaiTech University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  3. Yue Hao

    School of Life Science and Technology, ShanghaiTech University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  4. Xian-Ting Zeng

    School of Life Science and Technology, ShanghaiTech University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  5. Haowen Liu

    Clem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of Queensland, Brisbane, Australia
    Competing interests
    The authors declare that no competing interests exist.
  6. Lei Li

    Clem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of Queensland, Brisbane, Australia
    Competing interests
    The authors declare that no competing interests exist.
  7. Lili Chen

    Huazhong University of Science and Tehcnology, College of Life Science and Technology, Wuhan, China
    Competing interests
    The authors declare that no competing interests exist.
  8. Fu-min Tian

    School of Life Science and Technology, ShanghaiTech University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  9. Cindy Chang

    Department of Molecular Biology, Massachusetts General Hospital, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. Qi Hall

    Department of Molecular Biology, Massachusetts General Hospital, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  11. Chun-Xue Song

    Center for Brain Science, Shanghai Children's Medical Center, Department of Anatomy and Physiology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  12. Shangbang Gao

    Huazhong University of Science and Tehcnology, College of Life Science and Technology, Wuhan, China
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5431-4628
  13. Zhi-Tao Hu

    Clem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of Queensland, Brisbane, Australia
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2948-3339
  14. Josh M Kaplan

    Department of Molecular Biology, Massachusetts General Hospital, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7418-7179
  15. Qian Li

    Center for Brain Science, Shanghai Children's Medical Center, Department of Anatomy and Physiology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
    For correspondence
    liqian@shsmu.edu.cn
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1300-3377
  16. Xia-Jing Tong

    School of Life Science and Technology, ShanghaiTech University, Shanghai, China
    For correspondence
    tongxj@shanghaitech.edu.cn
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5634-1136

Funding

Basic Research Project from the Science and Technology Commission (19JC1414100)

  • Xia-Jing Tong

Shanghai Pujiang Program (18PJ1407600)

  • Xia-Jing Tong

Shanghai Pujiang Program (17PJ1405400)

  • Qian Li

Shanghai Brain-Intelligence Project from the Science and Technology Commission of Shanghai Municipality (18JC1420302)

  • Qian Li

Program for Special Appointment at Shanghai Institutions of Higher Learning (QD2018017)

  • Qian Li

Innovative research team of high-level local universities in Shanghai, National Institute of Neurological Disorder and Stroke (NS32196)

  • Josh M Kaplan

National Institutes of Health research grant (NEI 1R21EY029450-01)

  • Josh M Kaplan

National Health and Medical Research Council (APP1122351)

  • Zhi-Tao Hu

National Natural Science Foundation of China (31741054)

  • Xia-Jing Tong

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

Copyright

© 2021, Qian 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

  • 1,996
    views
  • 311
    downloads
  • 13
    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. Kang-Ying Qian
  2. Wan-Xin Zeng
  3. Yue Hao
  4. Xian-Ting Zeng
  5. Haowen Liu
  6. Lei Li
  7. Lili Chen
  8. Fu-min Tian
  9. Cindy Chang
  10. Qi Hall
  11. Chun-Xue Song
  12. Shangbang Gao
  13. Zhi-Tao Hu
  14. Josh M Kaplan
  15. Qian Li
  16. Xia-Jing Tong
(2021)
Male pheromones modulate synaptic transmission at the C. elegans neuromuscular junction in a sexually dimorphic manner
eLife 10:e67170.
https://doi.org/10.7554/eLife.67170

Share this article

https://doi.org/10.7554/eLife.67170

Further reading

    1. Neuroscience
    Claire Meissner-Bernard, Friedemann Zenke, Rainer W Friedrich
    Research Article

    Biological memory networks are thought to store information by experience-dependent changes in the synaptic connectivity between assemblies of neurons. Recent models suggest that these assemblies contain both excitatory and inhibitory neurons (E/I assemblies), resulting in co-tuning and precise balance of excitation and inhibition. To understand computational consequences of E/I assemblies under biologically realistic constraints we built a spiking network model based on experimental data from telencephalic area Dp of adult zebrafish, a precisely balanced recurrent network homologous to piriform cortex. We found that E/I assemblies stabilized firing rate distributions compared to networks with excitatory assemblies and global inhibition. Unlike classical memory models, networks with E/I assemblies did not show discrete attractor dynamics. Rather, responses to learned inputs were locally constrained onto manifolds that ‘focused’ activity into neuronal subspaces. The covariance structure of these manifolds supported pattern classification when information was retrieved from selected neuronal subsets. Networks with E/I assemblies therefore transformed the geometry of neuronal coding space, resulting in continuous representations that reflected both relatedness of inputs and an individual’s experience. Such continuous representations enable fast pattern classification, can support continual learning, and may provide a basis for higher-order learning and cognitive computations.

    1. Neuroscience
    Cristina Gil Avila, Elisabeth S May ... Markus Ploner
    Research Article

    Chronic pain is a prevalent and debilitating condition whose neural mechanisms are incompletely understood. An imbalance of cerebral excitation and inhibition (E/I), particularly in the medial prefrontal cortex (mPFC), is believed to represent a crucial mechanism in the development and maintenance of chronic pain. Thus, identifying a non-invasive, scalable marker of E/I could provide valuable insights into the neural mechanisms of chronic pain and aid in developing clinically useful biomarkers. Recently, the aperiodic component of the electroencephalography (EEG) power spectrum has been proposed to represent a non-invasive proxy for E/I. We, therefore, assessed the aperiodic component in the mPFC of resting-state EEG recordings in 149 people with chronic pain and 115 healthy participants. We found robust evidence against differences in the aperiodic component in the mPFC between people with chronic pain and healthy participants, and no correlation between the aperiodic component and pain intensity. These findings were consistent across different subtypes of chronic pain and were similarly found in a whole-brain analysis. Their robustness was supported by preregistration and multiverse analyses across many different methodological choices. Together, our results suggest that the EEG aperiodic component does not differentiate between people with chronic pain and healthy individuals. These findings and the rigorous methodological approach can guide future studies investigating non-invasive, scalable markers of cerebral dysfunction in people with chronic pain and beyond.