Large vesicle extrusions from C. elegans neurons are consumed and stimulated by glial-like phagocytosis activity of the neighboring cell

Abstract

C. elegans neurons under stress can produce giant vesicles, several microns in diameter, called exophers. Current models suggest that exophers are neuroprotective, providing a mechanism for stressed neurons to eject toxic protein aggregates and organelles. However, little is known of the fate of the exopher once it leaves the neuron. We found that exophers produced by mechanosensory neurons in C. elegans are engulfed by surrounding hypodermal skin cells and are then broken up into numerous smaller vesicles that acquire hypodermal phagosome maturation markers, with vesicular contents gradually degraded by hypodermal lysosomes. Consistent with the hypodermis acting as an exopher phagocyte, we found that exopher removal requires hypodermal actin and Arp2/3, and the hypodermal plasma membrane adjacent to newly formed exophers accumulates dynamic F-actin during budding. Efficient fission of engulfed exopher-phagosomes to produce smaller vesicles and degrade their contents requires phagosome maturation factors SAND-1/Mon1, GTPase RAB-35, the CNT-1 ARF-GAP, and microtubule motor associated GTPase ARL-8, suggesting a close coupling of phagosome fission and phagosome maturation. Lysosome activity was required to degrade exopher contents in the hypodermis but not for exopher-phagosome resolution into smaller vesicles. Importantly, we found that GTPase ARF-6 and effector SEC-10/Exocyst activity in the hypodermis, along with the CED-1 phagocytic receptor, is required for efficient production of exophers by the neuron. Our results indicate that the neuron requires specific interaction with the phagocyte for an efficient exopher response, a mechanistic feature potentially conserved with mammalian exophergenesis, and similar to neuronal pruning by phagocytic glia that influences neurodegenerative disease.

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 Figures 1-8 and S2-S6.

Article and author information

Author details

  1. Yu Wang

    Department of Molecular Biology and Biochemistry, Rutgers, The State University of New Jersey, Piscataway, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Meghan Lee Arnold

    Department of Molecular Biology and Biochemistry, Rutgers, The State University of New Jersey, Piscataway, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Anna Joelle Smart

    Department of Molecular Biology and Biochemistry, Rutgers, The State University of New Jersey, Piscataway, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Guoqiang Wang

    Department of Molecular Biology and Biochemistry, Rutgers, The State University of New Jersey, Piscataway, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3694-7103
  5. Rebecca J Androwski

    Department of Molecular Biology and Biochemistry, Rutgers, The State University of New Jersey, Piscataway, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Andres Morera

    Department of Molecular Biology and Biochemistry, Rutgers, The State University of New Jersey, Piscataway, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Ken CQ Nguyen

    Department of Neuroscience, Albert Einstein College of Medicine, Bronx, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Peter J Schweinsberg

    Department of Molecular Biology and Biochemistry, Rutgers, The State University of New Jersey, Piscataway, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Ge Bai

    Department of Molecular Biology and Biochemistry, Rutgers, The State University of New Jersey, Piscataway, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. Jason Cooper

    Department of Molecular Biology and Biochemistry, Rutgers, The State University of New Jersey, Piscataway, United States
    Competing interests
    The authors declare that no competing interests exist.
  11. David H Hall

    Department of Neuroscience, Albert Einstein College of Medicine, Bronx, United States
    Competing interests
    The authors declare that no competing interests exist.
  12. Monica Driscoll

    Department of Molecular Biology and Biochemistry, Rutgers, The State University of New Jersey, Piscataway, United States
    Competing interests
    The authors declare that no competing interests exist.
  13. Barth D Grant

    Department of Molecular Biology and Biochemistry, Rutgers, The State University of New Jersey, Piscataway, United States
    For correspondence
    barthgra@dls.rutgers.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5943-8336

Funding

National Institutes of Health (R01AG047101)

  • David H Hall
  • Monica Driscoll
  • Barth D Grant

National Institutes of Health (R24OD090143)

  • David H Hall

National Institutes of Health (F31AG066405)

  • Meghan Lee Arnold

National Institutes of Health (F31NS101969)

  • Anna Joelle Smart

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

Copyright

© 2023, Wang 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

  • 3,284
    views
  • 494
    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. Yu Wang
  2. Meghan Lee Arnold
  3. Anna Joelle Smart
  4. Guoqiang Wang
  5. Rebecca J Androwski
  6. Andres Morera
  7. Ken CQ Nguyen
  8. Peter J Schweinsberg
  9. Ge Bai
  10. Jason Cooper
  11. David H Hall
  12. Monica Driscoll
  13. Barth D Grant
(2023)
Large vesicle extrusions from C. elegans neurons are consumed and stimulated by glial-like phagocytosis activity of the neighboring cell
eLife 12:e82227.
https://doi.org/10.7554/eLife.82227

Share this article

https://doi.org/10.7554/eLife.82227

Further reading

    1. Cell Biology
    Erli Jin, Jennifer K Briggs ... Matthew J Merrins
    Research Article

    Oscillations in insulin secretion, driven by islet Ca2+ waves, are crucial for glycemic control. Prior studies, performed with single-plane imaging, suggest that subpopulations of electrically coupled β-cells have privileged roles in leading and coordinating the propagation of Ca2+ waves. Here, we used three-dimensional (3D) light-sheet imaging to analyze the location and Ca2+ activity of single β-cells within the entire islet at >2 Hz. In contrast with single-plane studies, 3D network analysis indicates that the most highly synchronized β-cells are located at the islet center, and remain regionally but not cellularly stable between oscillations. This subpopulation, which includes ‘hub cells’, is insensitive to changes in fuel metabolism induced by glucokinase and pyruvate kinase activation. β-Cells that initiate the Ca2+ wave (leaders) are located at the islet periphery, and strikingly, change their identity over time via rotations in the wave axis. Glucokinase activation, which increased oscillation period, reinforced leader cells and stabilized the wave axis. Pyruvate kinase activation, despite increasing oscillation frequency, had no effect on leader cells, indicating the wave origin is patterned by fuel input. These findings emphasize the stochastic nature of the β-cell subpopulations that control Ca2+ oscillations and identify a role for glucokinase in spatially patterning ‘leader’ β-cells.

    1. Cell Biology
    Marjan Slak Rupnik
    Insight

    Functional subpopulations of β-cells emerge to control pulsative insulin secretion in the pancreatic islets of mice through calcium oscillations.