Polar pattern formation induced by contact following locomotion in a multicellular system

  1. Masayuki Hayakawa
  2. Tetsuya Hiraiwa
  3. Yuko Wada
  4. Hidekazu Kuwayama
  5. Tatsuo Shibata  Is a corresponding author
  1. RIKEN Center for Biosystems Dynamics Research, Japan
  2. National University of Singapore, Singapore
  3. University of Tsukuba, Japan

Abstract

Biophysical mechanisms underlying collective cell migration of eukaryotic cells have been studied extensively in recent years. One mechanism that induces cells to correlate their motions is contact inhibition of locomotion, by which cells migrating away from the contact site. Here, we report that tail-following behavior at the contact site, termed contact following locomotion (CFL), can induce a non-trivial collective behavior in migrating cells. We show the emergence of a traveling band showing polar order in a mutant Dictyostelium cell that lacks chemotactic activity. We find that CFL is the cell–cell interaction underlying this phenomenon, enabling a theoretical description of how this traveling band forms. We further show that the polar order phase consists of subpopulations that exhibit characteristic transversal motions with respect to the direction of band propagation. These findings describe a novel mechanism of collective cell migration involving cell–cell interactions capable of inducing traveling band with polar order.

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 Figure 1, 2, 3 and 4.

Article and author information

Author details

  1. Masayuki Hayakawa

    Laboratory for Physical Biology, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
    Competing interests
    The authors declare that no competing interests exist.
  2. Tetsuya Hiraiwa

    Mechanobiology Institute, National University of Singapore, Singapore, Singapore
    Competing interests
    The authors declare that no competing interests exist.
  3. Yuko Wada

    Laboratory for Physical Biology, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
    Competing interests
    The authors declare that no competing interests exist.
  4. Hidekazu Kuwayama

    Faculty of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Japan
    Competing interests
    The authors declare that no competing interests exist.
  5. Tatsuo Shibata

    Laboratory for Physical Biology, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
    For correspondence
    tatsuo.shibata@riken.jp
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9294-9998

Funding

Japan Society for the Promotion of Science (JP17J05667)

  • Masayuki Hayakawa

Japan Society for the Promotion of Science (JP16K17777)

  • Tetsuya Hiraiwa

Japan Society for the Promotion of Science (JP19K03764)

  • Tetsuya Hiraiwa

Japan Society for the Promotion of Science (JP26610129)

  • Hidekazu Kuwayama

Japan Society for the Promotion of Science (JP19H00996)

  • Tatsuo Shibata

Japan Science and Technology Agency (JPMJCR1852)

  • Tatsuo Shibata

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

Reviewing Editor

  1. Tâm Mignot, CNRS-Aix Marseille University, France

Publication history

  1. Received: November 14, 2019
  2. Accepted: April 15, 2020
  3. Accepted Manuscript published: April 30, 2020 (version 1)
  4. Version of Record published: May 11, 2020 (version 2)
  5. Version of Record updated: May 14, 2020 (version 3)

Copyright

© 2020, Hayakawa 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. Masayuki Hayakawa
  2. Tetsuya Hiraiwa
  3. Yuko Wada
  4. Hidekazu Kuwayama
  5. Tatsuo Shibata
(2020)
Polar pattern formation induced by contact following locomotion in a multicellular system
eLife 9:e53609.
https://doi.org/10.7554/eLife.53609

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    Background:

    Postoperative knee instability is one of the major reasons accounting for unsatisfactory outcomes, as well as a major failure mechanism leading to total knee arthroplasty (TKA) revision. Nevertheless, subjective knee instability is not well defined clinically, plausibly because the relationships between instability and implant kinematics during functional activities of daily living remain unclear. Although muscles play a critical role in supporting the dynamic stability of the knee joint, the influence of joint instability on muscle synergy patterns is poorly understood. Therefore, this study aimed to understand the impact of self-reported joint instability on tibiofemoral kinematics and muscle synergy patterns after TKA during functional gait activities of daily living.

    Methods:

    Tibiofemoral kinematics and muscle synergy patterns were examined during level walking, downhill walking, and stair descent in eight self-reported unstable knees after TKA (3M:5F, 68.9 ± 8.3 years, body mass index [BMI] 26.1 ± 3.2 kg/m2, 31.9 ± 20.4 months postoperatively), and compared against 10 stable TKA knees (7M:3F, 62.6 ± 6.8 years, 33.9 ± 8.5 months postoperatively, BMI 29.4 ± 4.8 kg/m2). For each knee joint, clinical assessments of postoperative outcome were performed, while joint kinematics were evaluated using moving video-fluoroscopy, and muscle synergy patterns were recorded using electromyography.

    Results:

    Our results reveal that average condylar A-P translations, rotations, as well as their ranges of motion were comparable between stable and unstable groups. However, the unstable group exhibited more heterogeneous muscle synergy patterns and prolonged activation of knee flexors compared to the stable group. In addition, subjects who reported instability events during measurement showed distinct, subject-specific tibiofemoral kinematic patterns in the early/mid-swing phase of gait.

    Conclusions:

    Our findings suggest that accurate movement analysis is sensitive for detecting acute instability events, but might be less robust in identifying general joint instability. Conversely, muscle synergy patterns seem to be able to identify muscular adaptation associated with underlying chronic knee instability.

    Funding:

    This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.