A muscle-epidermis-glia signaling axis sustains synaptic specificity during allometric growth in C. elegans

Abstract

Synaptic positions underlie precise circuit connectivity. Synaptic positions can be established during embryogenesis and sustained during growth. The mechanisms that sustain synaptic specificity during allometric growth are largely unknown. We performed forward genetic screens in C. elegans for regulators of this process and identified mig-17, a conserved ADAMTS metalloprotease. Proteomic mass spectrometry, cell biological and genetic studies demonstrate that MIG-17 is secreted from cells like muscles to regulate basement membrane proteins. In the nematode brain, the basement membrane does not directly contact synapses. Instead, muscle-derived basement membrane coats one side of the glia, while glia contact synapses on their other side. MIG-17 modifies the muscle-derived basement membrane to modulate epidermal-glial crosstalk and sustain glia location and morphology during growth. Glia position in turn sustains the synaptic pattern established during embryogenesis. Our findings uncover a muscle-epidermis-glia signaling axis that sustains synaptic specificity during the organism’s allometric growth.

Data availability

All data is presented in the figures or supplementary figures

Article and author information

Author details

  1. Jiale Fan

    Department of Neurosurgery, State Key Laboratory of Medical Neurobiology, Collaborative Innovation Center for Brain Science and the Institutes of Brain Science, Zhongshan Hospital, Fudan University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  2. Tingting Ji

    Department of Neurosurgery, State Key Laboratory of Medical Neurobiology, Collaborative Innovation Center for Brain Science and the Institutes of Brain Science, Zhongshan Hospital, Fudan University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  3. Kai Wang

    Department of Neurosurgery, State Key Laboratory of Medical Neurobiology, Collaborative Innovation Center for Brain Science and the Institutes of Brain Science, Zhongshan Hospital, Fudan University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  4. Jichang Huang

    State Key Laboratory of Genetic Engineering, Department of Biochemistry, School of Life Sciences, Fudan University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  5. Mengqing Wang

    Department of Neurosurgery, State Key Laboratory of Medical Neurobiology, Collaborative Innovation Center for Brain Science and the Institutes of Brain Science, Zhongshan Hospital, Fudan University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  6. Laura Manning

    Program in Cellular Neuroscience, Neurodegeneration and Repair, Department of Neuroscience and Department of Cell Biology, Yale University School of Medicine, New Haven, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Xiaohua Dong

    Department of Neurosurgery, State Key Laboratory of Medical Neurobiology, Collaborative Innovation Center for Brain Science and the Institutes of Brain Science, Zhongshan Hospital, Fudan University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  8. Yanjun Shi

    Department of Neurosurgery, State Key Laboratory of Medical Neurobiology, Collaborative Innovation Center for Brain Science and the Institutes of Brain Science, Zhongshan Hospital, Fudan University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  9. Xumin Zhang

    State Key Laboratory of Genetic Engineering, Department of Biochemistry, School of Life Sciences, Fudan University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  10. Zhiyong Shao

    Department of Neurosurgery, State Key Laboratory of Medical Neurobiology, Collaborative Innovation Center for Brain Science and the Institutes of Brain Science, Zhongshan Hospital, Fudan University, Shanghai, China
    For correspondence
    shaozy@fudan.edu.cn
    Competing interests
    The authors declare that no competing interests exist.
  11. Daniel A Colón-Ramos

    Program in Cellular Neuroscience, Neurodegeneration and Repair, Department of Neuroscience and Department of Cell Biology, Yale University School of Medicine, New Haven, United States
    For correspondence
    daniel.colon-ramos@yale.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0223-7717

Funding

National Natural Science Foundation of China (31471026,31872762)

  • Jiale Fan
  • Tingting Ji
  • Kai Wang
  • Jichang Huang
  • Mengqing Wang
  • Xiaohua Dong
  • Yanjun Shi
  • Xumin Zhang
  • Zhiyong Shao

NIH Office of the Director (DP1NS111778)

  • Laura Manning
  • Daniel A Colón-Ramos

National Institutes of Health (R01NS076558)

  • Laura Manning
  • Daniel A Colón-Ramos

Howard Hughes Medical Institute (Faculty Scholar)

  • Daniel A Colón-Ramos

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

Copyright

© 2020, Fan 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

  • 1,777
    views
  • 343
    downloads
  • 10
    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. Jiale Fan
  2. Tingting Ji
  3. Kai Wang
  4. Jichang Huang
  5. Mengqing Wang
  6. Laura Manning
  7. Xiaohua Dong
  8. Yanjun Shi
  9. Xumin Zhang
  10. Zhiyong Shao
  11. Daniel A Colón-Ramos
(2020)
A muscle-epidermis-glia signaling axis sustains synaptic specificity during allometric growth in C. elegans
eLife 9:e55890.
https://doi.org/10.7554/eLife.55890

Share this article

https://doi.org/10.7554/eLife.55890

Further reading

    1. Neuroscience
    Célian Bimbard, Flóra Takács ... Philip Coen
    Tools and Resources

    Electrophysiology has proven invaluable to record neural activity, and the development of Neuropixels probes dramatically increased the number of recorded neurons. These probes are often implanted acutely, but acute recordings cannot be performed in freely moving animals and the recorded neurons cannot be tracked across days. To study key behaviors such as navigation, learning, and memory formation, the probes must be implanted chronically. An ideal chronic implant should (1) allow stable recordings of neurons for weeks; (2) allow reuse of the probes after explantation; (3) be light enough for use in mice. Here, we present the ‘Apollo Implant’, an open-source and editable device that meets these criteria and accommodates up to two Neuropixels 1.0 or 2.0 probes. The implant comprises a ‘payload’ module which is attached to the probe and is recoverable, and a ‘docking’ module which is cemented to the skull. The design is adjustable, making it easy to change the distance between probes, the angle of insertion, and the depth of insertion. We tested the implant across eight labs in head-fixed mice, freely moving mice, and freely moving rats. The number of neurons recorded across days was stable, even after repeated implantations of the same probe. The Apollo implant provides an inexpensive, lightweight, and flexible solution for reusable chronic Neuropixels recordings.

    1. Neuroscience
    Georgin Jacob, RT Pramod, SP Arun
    Research Article

    Most visual tasks involve looking for specific object features. But we also often perform property-based tasks where we look for specific property in an image, such as finding an odd item, deciding if two items are same, or if an object has symmetry. How do we solve such tasks? These tasks do not fit into standard models of decision making because their underlying feature space and decision process is unclear. Using well-known principles governing multiple object representations, we show that displays with repeating elements can be distinguished from heterogeneous displays using a property we define as visual homogeneity. In behavior, visual homogeneity predicted response times on visual search, same-different and symmetry tasks. Brain imaging during visual search and symmetry tasks revealed that visual homogeneity was localized to a region in the object-selective cortex. Thus, property-based visual tasks are solved in a localized region in the brain by computing visual homogeneity.