ArticleJournal of cystic fibrosis : official journal of the European Cystic Fibrosis Society2025
Shallow metagenomic shotgun sequencing improves detection of pathogenic species in cystic fibrosis respiratory samples.
Article in Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- DNA sequencing for microbial surveillance in cystic fibrosis airways: advances, challenges, and clinical translation.Clinical microbiology reviews · 2026Review
- The Unified Human Virome Database: A toolkit for expanded human virome analysis.bioRxiv : the preprint server for biology · 2026Article
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9 authors.
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Abstract
backgroundChronic infection and inflammation of the lungs contribute significantly to disease progression in persons with cystic fibrosis (pwCF). Treatment regimens are largely based on isolating the putative causative pathogen(s) from respiratory samples using basic culturing methods. While this strategy has shown to be highly valuable in the management of CF, the approach is time-consuming and often misses detection of pathogenic microbes that are more difficult to culture, including Mycobacterium spp.
methodsIn our proof-of-concept study, we evaluated shallow metagenomic shotgun sequencing to detect potential infection-causing pathogens at species level in sputum, oropharyngeal and salivary samples of pwCF (n = 13), and compared it to culture results from the clinic and standard 16S rRNA V4 amplicon sequencing.
resultsShallow shotgun sequencing improved the detection of pathogenic species in respiratory samples compared to culture methods. In particular, shallow shotgun sequencing could detect pathogenic species associated with CF, specifically Staphylococcus aureus, Pseudomonas aeruginosa, Stenotrophomonas maltophilia, Achromobacter xylosoxidans, Haemophilus influenzae and Mycobacterium spp. in sputum, oropharyngeal and/or salivary samples. Notably, Mycobacterium spp. was not detected based on 16S rRNA amplicon sequencing. Moreover, our approach was able to distinguish S. aureus from S. epidermidis and H. influenzae from H. parainfluenzae. This is not possible with 16S amplicon sequencing, but highly valuable in a clinical setting.
conclusionsThe improved detection of CF pathogens and other critical microbiome members as well as insights into their relative abundance within the community, could provide more knowledge on patient's disease status leading to more personalized medicine and ultimately benefit patient care.
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