Emergence of social cluster by collective pairwise encounters in Drosophila

  1. Lifen Jiang
  2. Yaxin Cheng
  3. Shan Gao
  4. Yincheng Zhong
  5. Chengrui Ma
  6. Tianyu Wang
  7. Yan Zhu  Is a corresponding author
  1. University of Science and Technology of China, China
  2. Institute of Biophysics, Chinese Academy of Sciences, China

Abstract

Many animals exhibit an astonishing ability to form groups of large numbers of individuals. The dynamic properties of such groups have been the subject of intensive investigation. The actual grouping processes and underlying neural mechanisms, however, remain elusive. Here, we established a social clustering paradigm in Drosophila to investigate the principles governing social group formation. Fruit flies spontaneously assembled into a stable cluster mimicking a distributed network. Social clustering was exhibited as a highly dynamic process including all individuals, which participated in stochastic pair-wise encounters mediated by appendage touches. Depriving sensory inputs resulted in abnormal encounter responses and a high failure rate of cluster formation. Furthermore, the social distance of the emergent network was regulated by ppk-specific neurons, which were activated by contact-dependent social grouping. Taken together, these findings revealed the development of an orderly social structure from initially unorganised individuals via collective actions.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files.

Article and author information

Author details

  1. Lifen Jiang

    School of Life Science, University of Science and Technology of China, Hefei, China
    Competing interests
    The authors declare that no competing interests exist.
  2. Yaxin Cheng

    State Key Laboratory of Brain and Cognitive Sciences, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  3. Shan Gao

    State Key Laboratory of Brain and Cognitive Sciences, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  4. Yincheng Zhong

    State Key Laboratory of Brain and Cognitive Sciences, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  5. Chengrui Ma

    State Key Laboratory of Brain and Cognitive Sciences, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  6. Tianyu Wang

    State Key Laboratory of Brain and Cognitive Sciences, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4169-8268
  7. Yan Zhu

    State Key Laboratory of Brain and Cognitive Sciences, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
    For correspondence
    zhuyan@ibp.ac.cn
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9858-9129

Funding

National Natural Science Foundation of China (9163210042)

  • Yan Zhu

Chinese Academy of Sciences (QYZDY-SSW-SMC015)

  • Yan Zhu

Bill and Melinda Gates Foundation (OPP1119434)

  • Yan Zhu

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

Reviewing Editor

  1. Mani Ramaswami, Trinity College Dublin, Ireland

Publication history

  1. Received: September 17, 2019
  2. Accepted: December 30, 2019
  3. Accepted Manuscript published: January 21, 2020 (version 1)
  4. Version of Record published: January 29, 2020 (version 2)

Copyright

© 2020, Jiang 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. Lifen Jiang
  2. Yaxin Cheng
  3. Shan Gao
  4. Yincheng Zhong
  5. Chengrui Ma
  6. Tianyu Wang
  7. Yan Zhu
(2020)
Emergence of social cluster by collective pairwise encounters in Drosophila
eLife 9:e51921.
https://doi.org/10.7554/eLife.51921

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