Growing a Cystic Fibrosis-Relevant Polymicrobial Biofilm to Probe Community Phenotypes.


Journal

Journal of visualized experiments : JoVE
ISSN: 1940-087X
Titre abrégé: J Vis Exp
Pays: United States
ID NLM: 101313252

Informations de publication

Date de publication:
19 Apr 2024
Historique:
medline: 6 5 2024
pubmed: 6 5 2024
entrez: 6 5 2024
Statut: epublish

Résumé

Most in vitro models lack the capacity to fully probe bacterial phenotypes emerging from the complex interactions observed in real-life environments. This is particularly true in the context of hard-to-treat, chronic, and polymicrobial biofilm-based infections detected in the airways of individuals living with cystic fibrosis (CF), a multiorgan genetic disease. While multiple microbiome studies have defined the microbial compositions detected in the airway of people with CF (pwCF), no in vitro models thus far have fully integrated critical CF-relevant lung features. Therefore, a significant knowledge gap exists in the capacity to investigate the mechanisms driving the pathogenesis of mixed species CF lung infections. Here, we describe a recently developed four-species microbial community model, including Pseudomonas aeruginosa, Staphylococcus aureus, Streptococcus sanguinis, and Prevotella melaninogenica grown in CF-like conditions. Through the utilization of this system, clinically relevant phenotypes such as antimicrobial recalcitrance of several pathogens were observed and explored at the molecular level. The usefulness of this in vitro model resides in its standardized workflow that can facilitate the study of interspecies interactions in the context of chronic CF lung infections.

Identifiants

pubmed: 38709077
doi: 10.3791/66785
doi:

Types de publication

Journal Article Video-Audio Media Research Support, Non-U.S. Gov't Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Sarah Poirier (S)

Département de Biologie, Université de Sherbrooke.

Fabrice Jean-Pierre (F)

Département de Biologie, Université de Sherbrooke; fabrice.jean.pierre@usherbrooke.ca.

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Classifications MeSH