1. Microbiology and Infectious Disease
Download icon

A broadly distributed toxin family mediates contact-dependent antagonism between gram-positive bacteria

  1. John C Whitney
  2. S Brook Peterson
  3. Jungyun Kim
  4. Manuel Pazos
  5. Adrian J Verster
  6. Matthew C Radey
  7. Hemantha D Kulasekara
  8. Mary Q Ching
  9. Nathan P Bullen
  10. Diane Bryant
  11. Young Ah Goo
  12. Michael G Surette
  13. Elhanan Borenstein
  14. Waldemar Vollmer
  15. Joseph D Mougous  Is a corresponding author
  1. McMaster University, Canada
  2. University of Washington, United States
  3. Newcastle University, United Kingdom
  4. Advanced Light Source, United States
  5. Northwestern University, United States
Research Article
  • Cited 68
  • Views 5,144
  • Annotations
Cite this article as: eLife 2017;6:e26938 doi: 10.7554/eLife.26938

Abstract

The Firmicutes are a phylum of bacteria that dominate numerous polymicrobial habitats of importance to human health and industry. Although these communities are often densely colonized, a broadly distributed contact-dependent mechanism of interbacterial antagonism utilized by Firmicutes has not been elucidated. Here we show that proteins belonging to the LXG polymorphic toxin family present in Streptococus intermedius mediate cell contact- and Esx secretion pathway-dependent growth inhibition of diverse Firmicute species. The structure of one such toxin revealed a previously unobserved protein fold that we demonstrate directs the degradation of a uniquely bacterial molecule required for cell wall biosynthesis, lipid II. Consistent with our functional data linking LXG toxins to interbacterial interactions in S. intermedius, we show that LXG genes are prevalent in the human gut microbiome, a polymicrobial community dominated by Firmicutes. We speculate that interbacterial antagonism mediated by LXG toxins plays a critical role in shaping Firmicute-rich bacterial communities.

Article and author information

Author details

  1. John C Whitney

    Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, Canada
    Competing interests
    The authors declare that no competing interests exist.
  2. S Brook Peterson

    Department of Microbiology, School of Medicine, University of Washington, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Jungyun Kim

    Department of Microbiology, School of Medicine, University of Washington, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3793-4264
  4. Manuel Pazos

    Centre for Bacterial Cell Biology, Institute for Cell and Molecular Biosciences, Newcastle University, Newcastle, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  5. Adrian J Verster

    Department of Genome Sciences, University of Washington, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Matthew C Radey

    Department of Microbiology, School of Medicine, University of Washington, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Hemantha D Kulasekara

    Department of Microbiology, School of Medicine, University of Washington, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Mary Q Ching

    Department of Microbiology, School of Medicine, University of Washington, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Nathan P Bullen

    Michael DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Canada
    Competing interests
    The authors declare that no competing interests exist.
  10. Diane Bryant

    Experimental Systems Group, Advanced Light Source, Berkeley, United States
    Competing interests
    The authors declare that no competing interests exist.
  11. Young Ah Goo

    Northwestern Proteomics Core Facility, Northwestern University, Chicago, United States
    Competing interests
    The authors declare that no competing interests exist.
  12. Michael G Surette

    Michael DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Canada
    Competing interests
    The authors declare that no competing interests exist.
  13. Elhanan Borenstein

    Department of Genome Sciences, University of Washington, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
  14. Waldemar Vollmer

    Centre for Bacterial Cell Biology, Newcastle University, Newcastle, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  15. Joseph D Mougous

    Department of Microbiology, University of Washington, Seattle, United States
    For correspondence
    mougous@uw.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5417-4861

Funding

Canadian Institutes of Health Research

  • John C Whitney

Natural Sciences and Engineering Research Council of Canada

  • Adrian J Verster

Wellcome (101824/Z/13/Z)

  • Waldemar Vollmer

National Cancer Institute (CCSG P30 CA060553)

  • Young Ah Goo

National Institutes of Health (AI080609)

  • Joseph D Mougous

Howard Hughes Medical Institute

  • Joseph D Mougous

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

Reviewing Editor

  1. Michael T Laub, Massachusetts Institute of Technology, United States

Publication history

  1. Received: March 20, 2017
  2. Accepted: July 10, 2017
  3. Accepted Manuscript published: July 11, 2017 (version 1)
  4. Accepted Manuscript updated: July 12, 2017 (version 2)
  5. Version of Record published: August 14, 2017 (version 3)
  6. Version of Record updated: August 24, 2017 (version 4)

Copyright

This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Metrics

  • 5,144
    Page views
  • 967
    Downloads
  • 68
    Citations

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

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)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)

Further reading

    1. Microbiology and Infectious Disease
    2. Physics of Living Systems
    Prathitha Kar et al.
    Research Article

    Collection of high-throughput data has become prevalent in biology. Large datasets allow the use of statistical constructs such as binning and linear regression to quantify relationships between variables and hypothesize underlying biological mechanisms based on it. We discuss several such examples in relation to single-cell data and cellular growth. In particular, we show instances where what appears to be ordinary use of these statistical methods leads to incorrect conclusions such as growth being non-exponential as opposed to exponential and vice versa. We propose that the data analysis and its interpretation should be done in the context of a generative model, if possible. In this way, the statistical methods can be validated either analytically or against synthetic data generated via the use of the model, leading to a consistent method for inferring biological mechanisms from data. On applying the validated methods of data analysis to infer cellular growth on our experimental data, we find the growth of length in E. coli to be non-exponential. Our analysis shows that in the later stages of the cell cycle the growth rate is faster than exponential.

    1. Microbiology and Infectious Disease
    Katie A Lien et al.
    Research Article Updated

    Encapsulin nanocompartments are an emerging class of prokaryotic protein-based organelle consisting of an encapsulin protein shell that encloses a protein cargo. Genes encoding nanocompartments are widespread in bacteria and archaea, and recent works have characterized the biochemical function of several cargo enzymes. However, the importance of these organelles to host physiology is poorly understood. Here, we report that the human pathogen Mycobacterium tuberculosis (Mtb) produces a nanocompartment that contains the dye-decolorizing peroxidase DyP. We show that this nanocompartment is important for the ability of Mtb to resist oxidative stress in low pH environments, including during infection of host cells and upon treatment with a clinically relevant antibiotic. Our findings are the first to implicate a nanocompartment in bacterial pathogenesis and reveal a new mechanism that Mtb uses to combat oxidative stress.