Heterogeneity in surface sensing suggests a division of labor in Pseudomonas aeruginosa populations

  1. Catherine R Armbruster
  2. Calvin K Lee
  3. Jessica Parker-Gilham
  4. Jaime de Anda
  5. Aiguo Xia
  6. Kun Zhao
  7. Boo Shan Tseng
  8. Lucas R Hoffman
  9. Fan Jin
  10. Caroline S Harwood
  11. Gerard C L Wong
  12. Matthew R Parsek  Is a corresponding author
  1. University of Washington, United States
  2. University of California, Los Angeles, United States
  3. University of Science and Technology of China, China
  4. Tianjin University, China
  5. University of Nevada, Las Vegas, United States

Abstract

The second messenger signaling molecule cyclic diguanylate monophosphate (c-di-GMP) drives the transition from planktonic to biofilm growth in many bacterial species. Pseudomonas aeruginosa has two surface sensing systems that produce c-di-GMP in response to surface adherence. The current thinking in the field is that once cells attach to a surface, they uniformly respond with elevated c-di-GMP. Here, we describe how the Wsp system generates heterogeneity in surface sensing, resulting in two physiologically distinct subpopulations of cells. One subpopulation has elevated c-di-GMP and produces biofilm matrix, serving as the founders of initial microcolonies. The other subpopulation has low c-di-GMP and engages in surface motility, allowing for exploration of the surface. We also show that this heterogeneity strongly correlates to surface behavior for descendent cells. Together, our results suggest that after surface attachment, P. aeruginosa engages in a division of labor that persists across generations, accelerating early biofilm formation and surface exploration.

Data availability

Source data files and/or MATLAB code have been provided for Figures 3, 4, and 5.

Article and author information

Author details

  1. Catherine R Armbruster

    Department of Microbiology, 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:" 0000-0003-0795-802X
  2. Calvin K Lee

    Department of Bioengineering, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Jessica Parker-Gilham

    Department of Microbiology, University of Washington, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Jaime de Anda

    Department of Bioengineering, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Aiguo Xia

    Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei, China
    Competing interests
    The authors declare that no competing interests exist.
  6. Kun Zhao

    Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin, China
    Competing interests
    The authors declare that no competing interests exist.
  7. Boo Shan Tseng

    School of Life Sciences, University of Nevada, Las Vegas, Las Vegas, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7563-0232
  8. Lucas R Hoffman

    Department of Microbiology, University of Washington, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Fan Jin

    Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei, China
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2313-0388
  10. Caroline S Harwood

    Deptartment of Microbiology, University of Washington, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
  11. Gerard C L Wong

    Department of Bioengineering, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    The authors declare that no competing interests exist.
  12. Matthew R Parsek

    Department of Microbiology, University of Washington, Seattle, United States
    For correspondence
    parsem@uw.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2932-7966

Funding

National Institutes of Health (T32GM007270)

  • Catherine R Armbruster

National Natural Science Foundation of China (21774117)

  • Fan Jin

National Natural Science Foundation of China (21522406)

  • Fan Jin

Fundamental Research Funds for the Central Universities (WK3450000003)

  • Fan Jin

Charlie Moore Endowed Fellowship

  • Catherine R Armbruster

Army Research Office (W911NF1810254)

  • Matthew R Parsek

National Institutes of Health (K22AI121097)

  • Boo Shan Tseng

National Institute of General Medical Sciences (GM56665)

  • Caroline S Harwood

National Natural Science Foundation of China (21474098)

  • Fan Jin

Fundamental Research Funds for the Central Universities (WK2340000066)

  • Fan Jin

National Institutes of Health (K24HL141669)

  • Lucas R Hoffman

National Institutes of Health (5R01AI077628)

  • Matthew R Parsek

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

Copyright

© 2019, Armbruster 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

  • 5,641
    views
  • 884
    downloads
  • 107
    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. Catherine R Armbruster
  2. Calvin K Lee
  3. Jessica Parker-Gilham
  4. Jaime de Anda
  5. Aiguo Xia
  6. Kun Zhao
  7. Boo Shan Tseng
  8. Lucas R Hoffman
  9. Fan Jin
  10. Caroline S Harwood
  11. Gerard C L Wong
  12. Matthew R Parsek
(2019)
Heterogeneity in surface sensing suggests a division of labor in Pseudomonas aeruginosa populations
eLife 8:e45084.
https://doi.org/10.7554/eLife.45084

Share this article

https://doi.org/10.7554/eLife.45084

Further reading

    1. Immunology and Inflammation
    2. Microbiology and Infectious Disease
    Bin Li, Jin Zhang ... Chao Wu
    Research Article

    Adjuvants can affect APCs function and boost adaptive immune responses post-vaccination. However, whether they modulate the specificity of immune responses, particularly immunodominant epitope responses, and the mechanisms of regulating antigen processing and presentation remain poorly defined. Here, using overlapping synthetic peptides, we screened the dominant epitopes of Th1 responses in mice post-vaccination with different adjuvants and found that the adjuvants altered the antigen-specific CD4+ T-cell immunodominant epitope hierarchy. MHC-II immunopeptidomes demonstrated that the peptide repertoires presented by APCs were significantly altered by the adjuvants. Unexpectedly, no novel peptide presentation was detected after adjuvant treatment, whereas peptides with high binding stability for MHC-II presented in the control group were missing after adjuvant stimulation, particularly in the MPLA- and CpG-stimulated groups. The low-stability peptide present in the adjuvant groups effectively elicited robust T-cell responses and formed immune memory. Collectively, our results suggest that adjuvants (MPLA and CpG) inhibit high-stability peptide presentation instead of revealing cryptic epitopes, which may alter the specificity of CD4+ T-cell-dominant epitope responses. The capacity of adjuvants to modify peptide–MHC (pMHC) stability and antigen-specific T-cell immunodominant epitope responses has fundamental implications for the selection of suitable adjuvants in the vaccine design process and epitope vaccine development.