3D single cell migration driven by temporal correlation between oscillating force dipoles

  1. Amélie Luise Godeau
  2. Marco Leoni
  3. Jordi Comelles
  4. Tristan Guyomar
  5. Michele Lieb
  6. Hélène Delanoë-Ayari
  7. Albrecht Ott
  8. Sebastien Harlepp
  9. Pierre Sens  Is a corresponding author
  10. Daniel Riveline  Is a corresponding author
  1. University of Strasbourg, CNRS, IGBMC, France
  2. Institute Curie, France
  3. Univ. Lyon, Université Claude Bernard Lyon 1, CNRS UMR 5306, France
  4. Universität des Saarlandes, Germany
  5. INSERM UMR S1109, Institut d'Hématologie et d'Immunologie, France
  6. Institut Curie, CNRS UMR168, France

Abstract

Directional cell locomotion requires symmetry breaking between the front and rear of the cell. In some cells, symmetry breaking manifests itself in a directional flow of actin from the front to the rear of the cell. Many cells, especially in physiological 3D matrices do not show such coherent actin dynamics and present seemingly competing protrusion/retraction dynamics at their front and back. How symmetry breaking manifests itself for such cells is therefore elusive. We take inspiration from the scallop theorem proposed by Purcell for micro-swimmers in Newtonian fluids: self-propelled objects undergoing persistent motion at low Reynolds number must follow a cycle of shape changes that breaks temporal symmetry. We report similar observations for cells crawling in 3D. We quantified cell motion using a combination of 3D live cell imaging, visualization of the matrix displacement and a minimal model with multipolar expansion. We show that our cells embedded in a 3D matrix form myosin-driven force dipoles at both sides of the nucleus, that locally and periodically pinch the matrix. The existence of a phase shift between the two dipoles is required for directed cell motion which manifests itself as cycles with finite area in the dipole-quadrupole diagram, a formal equivalence to the Purcell cycle. We confirm this mechanism by triggering local dipolar contractions with a laser. This leads to directed motion. Our study reveals that these cells control their motility by synchronizing dipolar forces distributed at front and back. This result opens new strategies to externally control cell motion as well as for the design of micro-crawlers.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting file; Source Data files have been provided for Figures 1, 2, 3, 4 and 5.

Article and author information

Author details

  1. Amélie Luise Godeau

    Laboratory of Cell Physics, University of Strasbourg, CNRS, IGBMC, Illkirch, France
    Competing interests
    No competing interests declared.
  2. Marco Leoni

    Institute Curie, Paris, France
    Competing interests
    No competing interests declared.
  3. Jordi Comelles

    Laboratory of Cell Physics, University of Strasbourg, CNRS, IGBMC, Illkirch, France
    Competing interests
    No competing interests declared.
  4. Tristan Guyomar

    Laboratory of Cell Physics, University of Strasbourg, CNRS, IGBMC, Illkirch, France
    Competing interests
    No competing interests declared.
  5. Michele Lieb

    Laboratory of Cell Physics, University of Strasbourg, CNRS, IGBMC, Illkirch, France
    Competing interests
    No competing interests declared.
  6. Hélène Delanoë-Ayari

    Univ. Lyon, Université Claude Bernard Lyon 1, CNRS UMR 5306, LyonVilleurbanne Cedex, France
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8658-3942
  7. Albrecht Ott

    Universität des Saarlandes, Saarbrücken, Germany
    Competing interests
    No competing interests declared.
  8. Sebastien Harlepp

    INSERM UMR S1109, Institut d'Hématologie et d'Immunologie, Strasbourg, France
    Competing interests
    No competing interests declared.
  9. Pierre Sens

    Laboratoire Physico Chimie Curie, Institut Curie, CNRS UMR168, Paris, France
    For correspondence
    pierre.sens@curie.fr
    Competing interests
    Pierre Sens, Reviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4523-3791
  10. Daniel Riveline

    Development and stem cells, University of Strasbourg, CNRS, IGBMC, Illkirch, France
    For correspondence
    riveline@unistra.fr
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4632-011X

Funding

Deutsch-Französische Hochschule (CDFA-01-13)

  • Albrecht Ott
  • Daniel Riveline

Agence Nationale de la Recherche (ANR-10-IDEX-0002-02)

  • Daniel Riveline

ICAM Branch Contributions

  • Marco Leoni
  • Pierre Sens

Agence Nationale de la Recherche (ANR-10-LBX-0038)

  • Marco Leoni
  • Pierre Sens

Agence Nationale de la Recherche (ANR-10-IDEX-0001-02)

  • Marco Leoni
  • Pierre Sens

Deutsche Forschungsgemeinschaft (SFB 1027)

  • Albrecht Ott

Centre National de la Recherche Scientifique

  • Daniel Riveline

ciFRC Strasbourg

  • Daniel Riveline

University of 'Strasbourg

  • Daniel Riveline

Labex IGBMC

  • Daniel Riveline

Foundation Cino del Duca

  • Daniel Riveline

Region Alsace

  • Daniel Riveline

Saarland University

  • Daniel Riveline

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

Copyright

© 2022, Godeau 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

  • 3,538
    views
  • 528
    downloads
  • 8
    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. Amélie Luise Godeau
  2. Marco Leoni
  3. Jordi Comelles
  4. Tristan Guyomar
  5. Michele Lieb
  6. Hélène Delanoë-Ayari
  7. Albrecht Ott
  8. Sebastien Harlepp
  9. Pierre Sens
  10. Daniel Riveline
(2022)
3D single cell migration driven by temporal correlation between oscillating force dipoles
eLife 11:e71032.
https://doi.org/10.7554/eLife.71032

Share this article

https://doi.org/10.7554/eLife.71032

Further reading

    1. Cell Biology
    2. Physics of Living Systems
    Deb Sankar Banerjee, Shiladitya Banerjee
    Research Article

    Accurate regulation of centrosome size is essential for ensuring error-free cell division, and dysregulation of centrosome size has been linked to various pathologies, including developmental defects and cancer. While a universally accepted model for centrosome size regulation is lacking, prior theoretical and experimental works suggest a centrosome growth model involving autocatalytic assembly of the pericentriolar material. Here, we show that the autocatalytic assembly model fails to explain the attainment of equal centrosome sizes, which is crucial for error-free cell division. Incorporating latest experimental findings into the molecular mechanisms governing centrosome assembly, we introduce a new quantitative theory for centrosome growth involving catalytic assembly within a shared pool of enzymes. Our model successfully achieves robust size equality between maturing centrosome pairs, mirroring cooperative growth dynamics observed in experiments. To validate our theoretical predictions, we compare them with available experimental data and demonstrate the broad applicability of the catalytic growth model across different organisms, which exhibit distinct growth dynamics and size scaling characteristics.

    1. Cell Biology
    2. Physics of Living Systems
    Marta Urbanska, Yan Ge ... Jochen Guck
    Research Article

    Cell mechanical properties determine many physiological functions, such as cell fate specification, migration, or circulation through vasculature. Identifying factors that govern the mechanical properties is therefore a subject of great interest. Here, we present a mechanomics approach for establishing links between single-cell mechanical phenotype changes and the genes involved in driving them. We combine mechanical characterization of cells across a variety of mouse and human systems with machine learning-based discriminative network analysis of associated transcriptomic profiles to infer a conserved network module of five genes with putative roles in cell mechanics regulation. We validate in silico that the identified gene markers are universal, trustworthy, and specific to the mechanical phenotype across the studied mouse and human systems, and demonstrate experimentally that a selected target, CAV1, changes the mechanical phenotype of cells accordingly when silenced or overexpressed. Our data-driven approach paves the way toward engineering cell mechanical properties on demand to explore their impact on physiological and pathological cell functions.