ArticleJournal of breath research2018
Volatile fingerprinting of Pseudomonas aeruginosa and respiratory syncytial virus infection in an in vitro cystic fibrosis co-infection model.
Article in Journal of breath research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- Molecular Analysis of Volatile Metabolites Synthesized byBiomolecules · 2024Article
- Modern approaches for detection of volatile organic compounds in metabolic studies focusing on pathogenic bacteria: Current state of the art.Journal of pharmaceutical analysis · 2024Review
- Real-time detection of volatile metabolites enabling species-level discrimination of bacterial biofilms associated with wound infection.Journal of applied microbiology · 2022Article
- Bacterial and Viral Coinfections with the Human Respiratory Syncytial Virus.Microorganisms · 2021Review
- Panel 4: Recent advances in understanding the natural history of the otitis media microbiome and its response to environmental pressures.International journal of pediatric otorhinolaryngology · 2020Review
- Modeling cellular metabolomic effects of oxidative stress impacts from hydrogen peroxide and cigarette smoke on human lung epithelial cells.Journal of breath research · 2019Article
- Viral-Bacterial Co-infections in the Cystic Fibrosis Respiratory Tract.Frontiers in immunology · 2018Review
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Volatile molecules in exhaled breath represent potential biomarkers in the setting of infectious diseases, particularly those affecting the respiratory tract. In particular, Pseudomonas aeruginosa is a critically important respiratory pathogen in specific subsets of the population, such as those with cystic fibrosis (CF). Infections caused by P. aeruginosa can be particularly problematic when co-infection with respiratory syncytial virus (RSV) occurs, as this is correlated with the establishment of chronic P. aeruginosa infection. In the present study, we evaluate the volatile metabolites produced by P. aeruginosa (PAO1)-infected, RSV-infected, co-infected, or uninfected CF bronchial epithelial (CFBE) cells, in vitro. We identified a volatile metabolic signature that could discriminate between P. aeruginosa-infected and non-P. aeruginosa-infected CFBE with an area under the receiver operating characteristic curve (AUROC) of 0.850, using the machine learning algorithm random forest (RF). Although we could not discriminate between RSV-infected and non-RSV-infected CFBE (AUROC = 0.431), we note that sample classification probabilities for RSV-infected cell, generated using RF, were between those of uninfected CFBE and P. aeruginosa-infected CFBE, suggesting that RSV infection may result in a volatile metabolic profile that shares attributes with both of these groups. To more precisely elucidate the biological origins of the volatile metabolites that were discriminatory between P. aeruginosa-infected and non-P. aeruginosa-infected CFBE, we measured the volatile metabolites produced by P. aeruginosa grown in the absence of CFBE. Our findings suggest that the discriminatory metabolites produced likely result from the interaction of P. aeruginosa with the CFBE cells, rather than the metabolism of media components by the bacterium. Taken together, our findings support the notion that P. aeruginosa interacting with CFBE yields a particular volatile metabolic signature. Such a signature may have clinical utility in the monitoring of individuals with CF.
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