Development of an ex vivo porcine lung model for studying growth, virulence, and signaling of Pseudomonas aeruginosaTools Harrison, Freya, Muruli, Aneesha, Higgins, Steven and Diggle, Stephen P. (2014) Development of an ex vivo porcine lung model for studying growth, virulence, and signaling of Pseudomonas aeruginosa. Infection and Immunity, 82 (8). pp. 3312-3323. ISSN 1098-5522 Full text not available from this repository.
Official URL: http://iai.asm.org/content/82/8/3312
AbstractResearch into chronic infection by bacterial pathogens, such as Pseudomonas aeruginosa, uses various in vitro and live host models. While these have increased our understanding of pathogen growth, virulence, and evolution, each model has certain limitations. In vitro models cannot recapitulate the complex spatial structure of host organs, while experiments on live hosts are limited in terms of sample size and infection duration for ethical reasons; live mammal models also require specialized facilities which are costly to run. To address this, we have developed an ex vivo pig lung (EVPL) model for quantifying Pseudomonas aeruginosa growth, quorum sensing (QS), virulence factor production, and tissue damage in an environment that mimics a chronically infected cystic fibrosis (CF) lung. In a first test of our model, we show that lasR mutants, which do not respond to 3-oxo-C12-homoserine lactone (HSL)-mediated QS, exhibit reduced virulence factor production in EVPL. We also show that lasR mutants grow as well as or better than a corresponding wild-type strain in EVPL. lasR mutants frequently and repeatedly arise during chronic CF lung infection, but the evolutionary forces governing their appearance and spread are not clear. Our data are not consistent with the hypothesis that lasR mutants act as social “cheats” in the lung; rather, our results support the hypothesis that lasR mutants are more adapted to the lung environment. More generally, this model will facilitate improved studies of mi- crobial disease, especially studies of how cells of the same and different species interact in polymicrobial infections in a spatially structured environment.
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