ArticlePeerJ2026
Insights into microbiome and ARGs diversity in patients with upper and lower respiratory tract infections by targeted next-generation sequencing.
Article in PeerJ, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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8 authors.
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Abstract
Respiratory tract infections (RTIs) cause substantial global morbidity and mortality, with antimicrobial resistance presenting an increasing challenge to the effective management. Characterizing the differences in microbiome composition and antimicrobial resistance genes (ARGs) between upper respiratory tract infections (URTIs) and lower respiratory tract infections (LRTIs) may inform site-specific diagnostic and therapeutic strategies. We retrospectively analyzed 1,340 URTIs samples (nasopharyngeal swab) and 699 LRTIs samples (bronchoalveolar lavage fluid) admitted to a single medical center to characterize the epidemiology of the respiratory microbes and ARGs using targeted next-generation sequencing (tNGS). Microbiome diversity, ARGs profiles, and coinfection patterns were compared between LRTIs and URTIs groups. Random forest machine learning was employed to identify discriminating species. LRTIs patients exhibited significantly higher microbiome abundance and ARGs diversity than URTIs patients (
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