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.

Metrics

  • 825
    Page views
  • 154
    Downloads
  • 0
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

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. 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

Further reading

    1. Cell Biology
    2. Structural Biology and Molecular Biophysics
    Bronwyn A Lucas, Benjamin A Himes, Nikolaus Grigorieff
    Research Advance

    Previously we showed that 2D template matching (2DTM) can be used to localize macromolecular complexes in images recorded by cryogenic electron microscopy (cryo-EM) with high precision, even in the presence of noise and cellular background (Lucas et al., 2021; Lucas et al., 2022). Here, we show that once localized, these particles may be averaged together to generate high-resolution 3D reconstructions. However, regions included in the template may suffer from template bias, leading to inflated resolution estimates and making the interpretation of high-resolution features unreliable. We evaluate conditions that minimize template bias while retaining the benefits of high-precision localization, and we show that molecular features not present in the template can be reconstructed at high resolution from targets found by 2DTM, extending prior work at low-resolution. Moreover, we present a quantitative metric for template bias to aid the interpretation of 3D reconstructions calculated with particles localized using high-resolution templates and fine angular sampling.

    1. Plant Biology
    2. Structural Biology and Molecular Biophysics
    Jinping Lu, Ingo Dreyer ... Rainer Hedrich
    Research Article

    To fire action-potential-like electrical signals, the vacuole membrane requires the two-pore channel TPC1, formerly called SV channel. The TPC1/SV channel functions as a depolarization-stimulated, non-selective cation channel that is inhibited by luminal Ca2+. In our search for species-dependent functional TPC1 channel variants with different luminal Ca2+ sensitivity, we found in total three acidic residues present in Ca2+ sensor sites 2 and 3 of the Ca2+-sensitive AtTPC1 channel from Arabidopsis thaliana that were neutral in its Vicia faba ortholog and also in those of many other Fabaceae. When expressed in the Arabidopsis AtTPC1-loss-of-function background, wild-type VfTPC1 was hypersensitive to vacuole depolarization and only weakly sensitive to blocking luminal Ca2+. When AtTPC1 was mutated for these VfTPC1-homologous polymorphic residues, two neutral substitutions in Ca2+ sensor site 3 alone were already sufficient for the Arabidopsis At-VfTPC1 channel mutant to gain VfTPC1-like voltage and luminal Ca2+ sensitivity that together rendered vacuoles hyperexcitable. Thus, natural TPC1 channel variants exist in plant families which may fine-tune vacuole excitability and adapt it to environmental settings of the particular ecological niche.