Dynamic action of the Sec machinery during initiation, protein translocation and termination

Abstract

Protein translocation across cell membranes is a ubiquitous process required for protein secretion and membrane protein insertion. In bacteria, this is mostly mediated by the conserved SecYEG complex, driven through rounds of ATP hydrolysis by the cytoplasmic SecA, and the trans-membrane proton motive force. We have used single molecule techniques to explore SecY pore dynamics on multiple timescales in order to dissect the complex reaction pathway. The results show that SecA, both the signal sequence and mature components of the pre-protein, and ATP hydrolysis each have important and specific roles in channel unlocking, opening and priming for transport. After channel opening, translocation proceeds in two phases: a slow phase independent of substrate length, and a length-dependent transport phase with an intrinsic translocation rate of ~40 amino acids per second for the proOmpA substrate. Broad translocation rate distributions reflect the stochastic nature of polypeptide transport.

Data availability

Compressed data are available together with the relevant scripts as Supplementary Source Data and Code

Article and author information

Author details

  1. Tomas Fessl

    Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  2. Daniel Watkins

    School of Biochemistry, University of Bristol, Bristol, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  3. Peter Oatley

    Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  4. William John Allen

    School of Biochemistry, University of Bristol, Bristol, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9513-4786
  5. Robin Adam Corey

    School of Biochemistry, University of Bristol, Bristol, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  6. Jim Horne

    Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  7. Steve A Baldwin

    Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  8. Sheena E Radford

    Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3079-8039
  9. Ian Collinson

    School of Biochemistry, University of Bristol, Bristol, United Kingdom
    For correspondence
    ian.collinson@bristol.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3931-0503
  10. Roman Tuma

    Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds, United Kingdom
    For correspondence
    r.tuma@leeds.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0047-0013

Funding

Biotechnology and Biological Sciences Research Council (BB/N017307/1)

  • Tomas Fessl
  • Sheena E Radford
  • Roman Tuma

Biotechnology and Biological Sciences Research Council (BB/I008675/1)

  • Daniel Watkins

Biotechnology and Biological Sciences Research Council (BB/M003604/I)

  • Robin Adam Corey

Wellcome (104632)

  • William John Allen
  • Ian Collinson

Seventh Framework Programme (32240)

  • Sheena E Radford

European Regional Development Fund (CZ.02.1.01/0.0/0.0/15_003/0000441)

  • Tomas Fessl
  • Roman Tuma

Biotechnology and Biological Sciences Research Council (BB/N015126/1)

  • Daniel Watkins
  • Ian Collinson

Biotechnology and Biological Sciences Research Council (BB/I008675/1)

  • Peter Oatley
  • Steve A Baldwin
  • Sheena E Radford
  • Roman Tuma

Biotechnology and Biological Sciences Research Council (BB/M011151/1)

  • Jim Horne

Biotechnology and Biological Sciences Research Council (BB/I006737/1)

  • William John Allen
  • Ian Collinson

Biotechnology and Biological Sciences Research Council (BBSRC South West Bioscience Doctoral Training Partnership)

  • Robin Adam Corey

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

Copyright

© 2018, Fessl 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

  • 3,029
    views
  • 510
    downloads
  • 58
    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. Tomas Fessl
  2. Daniel Watkins
  3. Peter Oatley
  4. William John Allen
  5. Robin Adam Corey
  6. Jim Horne
  7. Steve A Baldwin
  8. Sheena E Radford
  9. Ian Collinson
  10. Roman Tuma
(2018)
Dynamic action of the Sec machinery during initiation, protein translocation and termination
eLife 7:e35112.
https://doi.org/10.7554/eLife.35112

Share this article

https://doi.org/10.7554/eLife.35112

Further reading

    1. Biochemistry and Chemical Biology
    2. Structural Biology and Molecular Biophysics
    Joar Esteban Pinto Torres, Mathieu Claes ... Yann G-J Sterckx
    Research Article

    African trypanosomes are the causative agents of neglected tropical diseases affecting both humans and livestock. Disease control is highly challenging due to an increasing number of drug treatment failures. African trypanosomes are extracellular, blood-borne parasites that mainly rely on glycolysis for their energy metabolism within the mammalian host. Trypanosomal glycolytic enzymes are therefore of interest for the development of trypanocidal drugs. Here, we report the serendipitous discovery of a camelid single-domain antibody (sdAb aka Nanobody) that selectively inhibits the enzymatic activity of trypanosomatid (but not host) pyruvate kinases through an allosteric mechanism. By combining enzyme kinetics, biophysics, structural biology, and transgenic parasite survival assays, we provide a proof-of-principle that the sdAb-mediated enzyme inhibition negatively impacts parasite fitness and growth.

    1. Structural Biology and Molecular Biophysics
    Manming Xu, Sarath Chandra Dantu ... Shozeb Haider
    Research Article

    The relationship between protein dynamics and function is essential for understanding biological processes and developing effective therapeutics. Functional sites within proteins are critical for activities such as substrate binding, catalysis, and structural changes. Existing computational methods for the predictions of functional residues are trained on sequence, structural, and experimental data, but they do not explicitly model the influence of evolution on protein dynamics. This overlooked contribution is essential as it is known that evolution can fine-tune protein dynamics through compensatory mutations either to improve the proteins’ performance or diversify its function while maintaining the same structural scaffold. To model this critical contribution, we introduce DyNoPy, a computational method that combines residue coevolution analysis with molecular dynamics simulations, revealing hidden correlations between functional sites. DyNoPy constructs a graph model of residue–residue interactions, identifies communities of key residue groups, and annotates critical sites based on their roles. By leveraging the concept of coevolved dynamical couplings—residue pairs with critical dynamical interactions that have been preserved during evolution—DyNoPy offers a powerful method for predicting and analysing protein evolution and dynamics. We demonstrate the effectiveness of DyNoPy on SHV-1 and PDC-3, chromosomally encoded β-lactamases linked to antibiotic resistance, highlighting its potential to inform drug design and address pressing healthcare challenges.