Biological condensates form percolated networks with molecular motion properties distinctly different from dilute solutions

  1. Zeyu Shen
  2. Bowen Jia
  3. Yang Xu
  4. Jonas Wessén
  5. Tanmoy Pal
  6. Hue Sun Chan
  7. Shengwang Du
  8. Mingjie Zhang  Is a corresponding author
  1. Hong Kong University of Science and Technology, China
  2. University of Toronto, Canada
  3. Southern University of Science and Technology, China

Abstract

Formation of membraneless organelles or biological condensates via phase separation and related processes hugely expands the cellular organelle repertoire. Biological condensates are dense and viscoelastic soft matters instead of canonical dilute solutions. To date, numerous different biological condensates have been discovered; but mechanistic understanding of biological condensates remains scarce. In this study, we developed an adaptive single molecule imaging method that allows simultaneous tracking of individual molecules and their motion trajectories in both condensed and dilute phases of various biological condensates. The method enables quantitative measurements of concentrations, phase boundary, motion behavior and speed of molecules in both condensed and dilute phases as well as the scale and speed of molecular exchanges between the two phases. Notably, molecules in the condensed phase do not undergo uniform Brownian motion, but instead constantly switch between a (class of) confined state(s) and a random diffusion-like motion state. Transient confinement is consistent with strong interactions associated with large molecular networks (i.e., percolation) in the condensed phase. In this way, molecules in biological condensates behave distinctly different from those in dilute solutions. The methods and findings described herein should be generally applicable for deciphering the molecular mechanisms underlying the assembly, dynamics and consequently functional implications of biological condensates.

Data availability

The home-written codes and use of the codes for data analysis described in this manuscript have been uploaded in the GitHub database with unrestricted access:https://github.com/NeoLShen/Code-for-phase-simulation-and-HMM-analysis.git

Article and author information

Author details

  1. Zeyu Shen

    Division of Life Science, Hong Kong University of Science and Technology, Hong Kong, China
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1057-7191
  2. Bowen Jia

    Division of Life Science, Hong Kong University of Science and Technology, Hong Kong, China
    Competing interests
    The authors declare that no competing interests exist.
  3. Yang Xu

    Division of Life Science, Hong Kong University of Science and Technology, Hong Kong, China
    Competing interests
    The authors declare that no competing interests exist.
  4. Jonas Wessén

    Department of Biochemistry, University of Toronto, Toronto, Canada
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5904-8442
  5. Tanmoy Pal

    Department of Biochemistry, University of Toronto, Toronto, Canada
    Competing interests
    The authors declare that no competing interests exist.
  6. Hue Sun Chan

    Department of Biochemistry, University of Toronto, Toronto, Canada
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1381-923X
  7. Shengwang Du

    Department of Physics, Hong Kong University of Science and Technology, Hong Kong, China
    Competing interests
    The authors declare that no competing interests exist.
  8. Mingjie Zhang

    School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
    For correspondence
    zhangmj@sustech.edu.cn
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9404-0190

Funding

National Natural Science Foundation of China ((82188101)

  • Mingjie Zhang

Ministry of Science and Technology (2019YFA0508402)

  • Mingjie Zhang

Shenzhen Bay Laboratory (S201101002)

  • Mingjie Zhang

University Grants Committee (AoE-M09-12,16104518 and 16101419)

  • Mingjie Zhang

Human Frontier Science Program (RGP0020/2019)

  • Mingjie Zhang

Canadian Institutes of Health Research (PJT-155930)

  • Hue Sun Chan

Natural Sciences and Engineering Research Council of Canada (RGPIN-2018-04351)

  • Hue Sun Chan

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

Reviewing Editor

  1. Rohit V Pappu, Washington University in St Louis, United States

Version history

  1. Received: July 15, 2022
  2. Preprint posted: July 22, 2022 (view preprint)
  3. Accepted: May 31, 2023
  4. Accepted Manuscript published: June 1, 2023 (version 1)
  5. Version of Record published: June 13, 2023 (version 2)

Copyright

© 2023, Shen 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. Zeyu Shen
  2. Bowen Jia
  3. Yang Xu
  4. Jonas Wessén
  5. Tanmoy Pal
  6. Hue Sun Chan
  7. Shengwang Du
  8. Mingjie Zhang
(2023)
Biological condensates form percolated networks with molecular motion properties distinctly different from dilute solutions
eLife 12:e81907.
https://doi.org/10.7554/eLife.81907

Share this article

https://doi.org/10.7554/eLife.81907

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