Nasopharyngeal metagenomics of symptomatic healthcare workers provides insights into the respiratory microbiome and antimicrobial resistance.

Respiratory infections represent a significant risk for healthcare workers (HCWs), particularly during viral outbreaks. This study applied metagenomic sequencing to characterize microbial communities and antimicrobial resistance (AMR) genes in nasopharyngeal swabs from HCWs presenting respiratory symptoms. Samples from 161 HCWs collected at a tertiary hospital in 2020-2021 were screened using FilmArray; negative samples were analyzed by metagenomic sequencing. After removal of human reads, sequences were taxonomically classified into viral, bacterial, and eukaryotic groups, and AMR genes were identified. On average, samples consisted of 5% viral reads, 89% bacterial, and 6% eukaryotic. Detected viruses included Enterovirus, human bocavirus(HBoV1), Alphaherpesvirus, and Coronavirus OC43, with one OC43 infection identified exclusively by metagenomic. Bacteria commonly associated with respiratory infections, such as Streptococcus pneumoniae, Haemophilus influenzae, and Moraxella catarrhalis, were frequently observed. Fungi included Schizophyllum commune, Cryptococcus wingfieldii, Pneumocystis murina, and Cryptococcus neoformans. AMR analysis revealed that 65% of samples harbored at least one resistance gene, totaling 112 distinct genes; ermC was the most prevalent, detected in 28% of samples. Predominant classes included macrolide-lincosamide-streptogramin, beta-lactam, aminoglycoside, and tetracycline. These findings demonstrate the utility of metagenomic sequencing for comprehensive pathogen detection and AMR profiling, supporting improved infection control and clinical management in healthcare settings.