Community composition shapes microbial-specific phenotypes in a cystic fibrosis polymicrobial model system
- Geisel School of Medicine at Dartmouth, United States
- Dartmouth College, United States
- Institut National de la Recherche Scientifique, Canada
Abstract
Interspecies interactions can drive the emergence of unexpected microbial phenotypes that are not observed when studying monocultures. The cystic fibrosis (CF) lung consists of a complex environment where microbes, living as polymicrobial biofilm-like communities, are associated with negative clinical outcomes for persons with CF (pwCF). However, the current lack of in vitro models integrating the microbial diversity observed in the CF airway hampers our understanding of why polymicrobial communities are recalcitrant to therapy in this disease. Here, integrating computational approaches informed by clinical data, we built a mixed community of clinical relevance to the CF lung composed of Pseudomonas aeruginosa, Staphylococcus aureus, Streptococcus sanguinis and Prevotella melaninogenica. We developed and validated this model biofilm community with multiple isolates of these four genera. When challenged with tobramycin, a front-line antimicrobial used to treat pwCF, the microorganisms in the polymicrobial community show altered sensitivity to this antibiotic compared to monospecies biofilms. We observed that wild-type P. aeruginosa is sensitized to tobramycin in a mixed community versus monoculture, and this observation holds across a range of community relative abundances. We also report that LasR loss-of-function, a variant frequently detected in the CF airway, drives tolerance of P. aeruginosa to tobramycin specifically in the mixed community. Our data suggest that the molecular basis of this community-specific recalcitrance to tobramycin for the P. aeruginosa LasR mutant is increased production of phenazines. Our work support the importance of studying a clinically-relevant model polymicrobial biofilms to understand community-specific traits relevant to infections.
Data availability
Figure 1 - figure supplement 3 & Source Data 1 contains the numerical data used to generate the figure.Figure 1 - figure supplement 4 & Source Data 2 contains numerical data used to generate the figure.Source Code 1 contains the script used to generate Figure 1, Figure 1 - figure supplement 1 and Figure 1 - figure supplement 4.Source Code 2 contains the script used to generate the modeling data presented Figure 1 - figure supplement 1.
Article and author information
Author details
Fabrice Jean-Pierre
Funding
Cystic Fibrosis Foundation (JEAN21F0)
- Fabrice Jean-Pierre
National Institutes of Health (R01 AI155424)
- George A O'Toole
Canadian Institutes of Health Research (MOP-142466)
- Eric Déziel
National Institutes of Health (5 P20 GM130454)
- Daniel Schultz
Cystic Fibrosis Foundation (HOGAN19G0)
- Deborah A Hogan
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Vaughn S Cooper, University of Pittsburgh, United States
Version history
- Preprint posted: June 24, 2022 (view preprint)
- Received: July 4, 2022
- Accepted: January 19, 2023
- Accepted Manuscript published: January 20, 2023 (version 1)
- Accepted Manuscript updated: January 23, 2023 (version 2)
- Version of Record published: February 3, 2023 (version 3)
Copyright
© 2023, Jean-Pierre 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.
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Community composition shapes microbial-specific phenotypes in a cystic fibrosis polymicrobial model system
eLife 12:e81604.
https://doi.org/10.7554/eLife.81604
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