Bacterial flagella grow through an injection-diffusion mechanism

  1. Thibaud T Renault
  2. Anthony O Abraham
  3. Tobias Bergmiller
  4. Guillaume Paradis
  5. Simon Rainville
  6. Emmanuelle Charpentier
  7. Călin C Guet
  8. Yuhai Tu
  9. Keiichi Namba
  10. James P Keener  Is a corresponding author
  11. Tohru Minamino
  12. Marc Erhardt  Is a corresponding author
  1. Helmholtz Centre for Infection Research, Germany
  2. Osaka University, Japan
  3. Institute of Science and Technology Austria, Austria
  4. Laval University, Canada
  5. Max Planck Institute for Infection Biology, Germany
  6. IBM Thomas J. Watson Research Center, United States
  7. University of Utah, United States

Abstract

The bacterial flagellum is a self-assembling nanomachine. The external flagellar filament, several times longer than a bacterial cell body, is made of a few tens of thousands subunits of a single protein: flagellin. A fundamental problem concerns the molecular mechanism of how the flagellum grows outside the cell, where no discernible energy source is available. Here, we monitored the dynamic assembly of individual flagella using in situ labelling and real-time immunostaining of elongating flagellar filaments. We report that the rate of flagellum growth, initially ∼1,700 amino acids per second, decreases with length and that the previously proposed chain mechanism does not contribute to the filament elongation dynamics. Inhibition of the proton motive force-dependent export apparatus revealed a major contribution of substrate injection in driving filament elongation. The combination of experimental and mathematical evidence demonstrates that a simple, injection-diffusion mechanism controls bacterial flagella growth outside the cell.

Article and author information

Author details

  1. Thibaud T Renault

    Junior Research Group Infection Biology of Salmonella, Helmholtz Centre for Infection Research, Braunschweig, Germany
    Competing interests
    The authors declare that no competing interests exist.
  2. Anthony O Abraham

    Graduate School of Frontier Biosciences, Osaka University, Osaka, Japan
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8710-1351
  3. Tobias Bergmiller

    Institute of Science and Technology Austria, Vienna, Austria
    Competing interests
    The authors declare that no competing interests exist.
  4. Guillaume Paradis

    Department of Physics, Engineering Physics and Optics, Laval University, Quebec City, Canada
    Competing interests
    The authors declare that no competing interests exist.
  5. Simon Rainville

    Department of Physics, Engineering Physics and Optics, Laval University, Quebec City, Canada
    Competing interests
    The authors declare that no competing interests exist.
  6. Emmanuelle Charpentier

    Max Planck Institute for Infection Biology, Berlin, Germany
    Competing interests
    The authors declare that no competing interests exist.
  7. Călin C Guet

    Institute of Science and Technology Austria, Klosterneuburg, Austria
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6220-2052
  8. Yuhai Tu

    IBM Thomas J. Watson Research Center, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Keiichi Namba

    Graduate School of Frontier Biosciences, Osaka University, Suita, Japan
    Competing interests
    The authors declare that no competing interests exist.
  10. James P Keener

    Department of Mathematics, University of Utah, Salt Lake City, United States
    For correspondence
    keener@math.utah.edu
    Competing interests
    The authors declare that no competing interests exist.
  11. Tohru Minamino

    Graduate School of Frontier Biosciences, Osaka University, Suita, Japan
    Competing interests
    The authors declare that no competing interests exist.
  12. Marc Erhardt

    Junior Research Group Infection Biology of Salmonella, Helmholtz Centre for Infection Research, Braunschweig, Germany
    For correspondence
    marc.erhardt@helmholtz-hzi.de
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6292-619X

Funding

Helmholtz-Gemeinschaft (VH-NG-932)

  • Marc Erhardt

Japan Society for the Promotion of Science (15H01640)

  • Tohru Minamino

Max-Planck-Gesellschaft

  • Emmanuelle Charpentier

National Institutes of Health (R01GM081747)

  • Yuhai Tu

European Commission (334030)

  • Marc Erhardt

Japan Society for the Promotion of Science (25000013)

  • Keiichi Namba

Natural Sciences and Engineering Research Council of Canada

  • Simon Rainville

Alexander von Humboldt-Stiftung

  • Thibaud T Renault

Japan Society for the Promotion of Science (26293097)

  • Tohru Minamino

Japan Society for the Promotion of Science (24117004)

  • Tohru Minamino

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

Copyright

© 2017, Renault 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

  • 6,414
    views
  • 1,153
    downloads
  • 76
    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. Thibaud T Renault
  2. Anthony O Abraham
  3. Tobias Bergmiller
  4. Guillaume Paradis
  5. Simon Rainville
  6. Emmanuelle Charpentier
  7. Călin C Guet
  8. Yuhai Tu
  9. Keiichi Namba
  10. James P Keener
  11. Tohru Minamino
  12. Marc Erhardt
(2017)
Bacterial flagella grow through an injection-diffusion mechanism
eLife 6:e23136.
https://doi.org/10.7554/eLife.23136

Share this article

https://doi.org/10.7554/eLife.23136

Further reading

    1. Structural Biology and Molecular Biophysics
    Mia L Abramsson, Robin A Corey ... Michael Landreh
    Research Article

    Integral membrane proteins carry out essential functions in the cell, and their activities are often modulated by specific protein-lipid interactions in the membrane. Here, we elucidate the intricate role of cardiolipin (CDL), a regulatory lipid, as a stabilizer of membrane proteins and their complexes. Using the in silico-designed model protein TMHC4_R (ROCKET) as a scaffold, we employ a combination of molecular dynamics simulations and native mass spectrometry to explore the protein features that facilitate preferential lipid interactions and mediate stabilization. We find that the spatial arrangement of positively charged residues as well as local conformational flexibility are factors that distinguish stabilizing from non-stabilizing CDL interactions. However, we also find that even in this controlled, artificial system, a clear-cut distinction between binding and stabilization is difficult to attain, revealing that overlapping lipid contacts can partially compensate for the effects of binding site mutations. Extending our insights to naturally occurring proteins, we identify a stabilizing CDL site within the E. coli rhomboid intramembrane protease GlpG and uncover its regulatory influence on enzyme substrate preference. In this work, we establish a framework for engineering functional lipid interactions, paving the way for the design of proteins with membrane-specific properties or functions.

    1. Structural Biology and Molecular Biophysics
    Giuseppe Deganutti, Ludovico Pipito ... Christopher Arthur Reynolds
    Research Article

    The structural basis for the pharmacology of human G protein-coupled receptors (GPCRs), the most abundant membrane proteins and the target of about 35% of approved drugs, is still a matter of intense study. What makes GPCRs challenging to study is the inherent flexibility and the metastable nature of interaction with extra- and intracellular partners that drive their effects. Here, we present a molecular dynamics (MD) adaptive sampling algorithm, namely multiple walker supervised molecular dynamics (mwSuMD), to address complex structural transitions involving GPCRs without energy input. We first report the binding and unbinding of the vasopressin peptide from its receptor V2. Successively, we present the complete transition of the glucagon-like peptide-1 receptor (GLP-1R) from inactive to active, agonist and Gs-bound state, and the guanosine diphosphate (GDP) release from Gs. To our knowledge, this is the first time the whole sequence of events leading from an inactive GPCR to the GDP release is simulated without any energy bias. We demonstrate that mwSuMD can address complex binding processes intrinsically linked to protein dynamics out of reach of classic MD.