The structure of the endogenous ESX-3 secretion system

  1. Nicole Poweleit
  2. Nadine Czudnochowski
  3. Rachel Nakagawa
  4. Donovan Trinidad
  5. Kenan C Murphy
  6. Christopher M Sassetti
  7. Oren S Rosenberg  Is a corresponding author
  1. University of California, San Francisco, United States
  2. University of Massachusetts Medical School, United States

Abstract

The ESX (or Type VII) secretion systems are protein export systems in mycobacteria and many Gram-positive bacteria that mediate a broad range of functions including virulence, conjugation, and metabolic regulation. These systems translocate folded dimers of WXG100-superfamily protein substrates across the cytoplasmic membrane. We report the cryo-electron microscopy structure of an ESX-3 system, purified using an epitope tag inserted with recombineering into the chromosome of the model organism Mycobacterium smegmatis. The structure reveals a stacked architecture that extends above and below the inner membrane of the bacterium. The ESX-3 protomer complex is assembled from a single copy of the EccB3, EccC3, and EccE3 and two copies of the EccD3 protein. In the structure, the protomers form a stable dimer that is consistent with assembly into a larger oligomer. The ESX-3 structure provides a framework for further study of these important bacterial transporters.

Data availability

The map files have been deposited at the EMDB with code 20820. The entry is online at https://www.ebi.ac.uk/pdbe/entry/emdb/EMD-20820.The model has been deposited at the PDB with the code 6UMM. It is online at http://www.rcsb.org/structure/6UMM

The following data sets were generated

Article and author information

Author details

  1. Nicole Poweleit

    Department of Medicine, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Nadine Czudnochowski

    Department of Medicine, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Rachel Nakagawa

    Department of Medicine, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Donovan Trinidad

    Department of Medicine, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Kenan C Murphy

    Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Christopher M Sassetti

    Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Oren S Rosenberg

    Department of Medicine, University of California, San Francisco, San Francisco, United States
    For correspondence
    oren.rosenberg@ucsf.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5736-4388

Funding

National Institutes of Health (1RO1AI128214)

  • Oren S Rosenberg

National Institutes of Health (1U19AI135990-01)

  • Oren S Rosenberg

National Institutes of Health (P01AI095208)

  • Oren S Rosenberg

National Institutes of Health (5T32AI060537)

  • Nicole Poweleit

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

Copyright

© 2019, Poweleit 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

  • 4,186
    views
  • 520
    downloads
  • 69
    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. Nicole Poweleit
  2. Nadine Czudnochowski
  3. Rachel Nakagawa
  4. Donovan Trinidad
  5. Kenan C Murphy
  6. Christopher M Sassetti
  7. Oren S Rosenberg
(2019)
The structure of the endogenous ESX-3 secretion system
eLife 8:e52983.
https://doi.org/10.7554/eLife.52983

Share this article

https://doi.org/10.7554/eLife.52983

Further reading

    1. Structural Biology and Molecular Biophysics
    Bradley P Clarke, Alexia E Angelos ... Yi Ren
    Research Article

    In eukaryotes, RNAs transcribed by RNA Pol II are modified at the 5′ end with a 7-methylguanosine (m7G) cap, which is recognized by the nuclear cap binding complex (CBC). The CBC plays multiple important roles in mRNA metabolism, including transcription, splicing, polyadenylation, and export. It promotes mRNA export through direct interaction with a key mRNA export factor, ALYREF, which in turn links the TRanscription and EXport (TREX) complex to the 5′ end of mRNA. However, the molecular mechanism for CBC-mediated recruitment of the mRNA export machinery is not well understood. Here, we present the first structure of the CBC in complex with an mRNA export factor, ALYREF. The cryo-EM structure of CBC-ALYREF reveals that the RRM domain of ALYREF makes direct contact with both the NCBP1 and NCBP2 subunits of the CBC. Comparing CBC-ALYREF with other cellular complexes containing CBC and/or ALYREF components provides insights into the coordinated events during mRNA transcription, splicing, and export.

    1. Structural Biology and Molecular Biophysics
    Julia Belyaeva, Matthias Elgeti
    Review Article

    Under physiological conditions, proteins continuously undergo structural fluctuations on different timescales. Some conformations are only sparsely populated, but still play a key role in protein function. Thus, meaningful structure–function frameworks must include structural ensembles rather than only the most populated protein conformations. To detail protein plasticity, modern structural biology combines complementary experimental and computational approaches. In this review, we survey available computational approaches that integrate sparse experimental data from electron paramagnetic resonance spectroscopy with molecular modeling techniques to derive all-atom structural models of rare protein conformations. We also propose strategies to increase the reliability and improve efficiency using deep learning approaches, thus advancing the field of integrative structural biology.