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

Publication date: Jul 16, 2026

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.

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Concepts Keywords
Antimicrobial Resistance
Metagenomics
Microbiome
Resistome
Respiratory Symptoms

Semantics

Type Source Name
disease MESH Respiratory infections
disease MESH included
disease MESH infection
drug DRUGBANK Tetracycline
pathway REACTOME Reproduction
disease MESH Park
drug DRUGBANK Coenzyme M
disease MESH CEP
disease MESH ACDC
disease MESH COVID 19 pandemic
disease MESH respiratory diseases
disease MESH RP2
disease MESH coinfection
drug DRUGBANK Methylergometrine
disease MESH Parainfluenza
disease MESH headache
disease MESH sore throat
disease MESH rhinorrhea
disease MESH cough
disease MESH myalgia
disease MESH fever
disease MESH allergy
drug DRUGBANK Etoperidone
drug DRUGBANK Spinosad
disease MESH infectious diseases
disease MESH influenza
disease MESH Dis
disease MESH David
drug DRUGBANK Ribostamycin
disease MESH viral diseases
disease MESH sepsis
drug DRUGBANK Corynebacterium diphtheriae
drug DRUGBANK Tremella fuciformis whole
disease MESH Diarrhea
disease MESH Abdominal pain
disease MESH Rash
disease MESH Neoplasia

Original Article

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

Publication date: Jul 16, 2026

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.

Open Access PDF

Concepts Keywords
Antimicrobial Resistance
Metagenomics
Microbiome
Resistome
Respiratory Symptoms

Semantics

Type Source Name
disease MESH Respiratory infections
disease MESH included
disease MESH infection
drug DRUGBANK Tetracycline
pathway REACTOME Reproduction
disease MESH Park
drug DRUGBANK Coenzyme M
disease MESH CEP
disease MESH ACDC
disease MESH COVID 19 pandemic
disease MESH respiratory diseases
disease MESH RP2
disease MESH coinfection
drug DRUGBANK Methylergometrine
disease MESH Parainfluenza
disease MESH headache
disease MESH sore throat
disease MESH rhinorrhea
disease MESH cough
disease MESH myalgia
disease MESH fever
disease MESH allergy
drug DRUGBANK Etoperidone
drug DRUGBANK Spinosad
disease MESH infectious diseases
disease MESH influenza
disease MESH Dis
disease MESH David
drug DRUGBANK Ribostamycin
disease MESH viral diseases
disease MESH sepsis
drug DRUGBANK Corynebacterium diphtheriae
drug DRUGBANK Tremella fuciformis whole
disease MESH Diarrhea
disease MESH Abdominal pain
disease MESH Rash
disease MESH Neoplasia

Original Article

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