Current medicinal chemistry · 2026
Characterization of Pathogens in Respiratory Tract Infection Using Targeted Next-Generation Sequencing: A Population-Based Study in Foshan City from 2022 to 2024.
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Chen Yonghua, Deng Yunqi, Xian Xiaoling, Deng Junli, Guo Xiaolei, Yang Dongmei, Zeng Yunxiang
Аннотация
INTRODUCTION: Respiratory Tract Infection (RTI) is a leading cause of mortality worldwide and represents one of the major complications in patients with respiratory syndrome.
MATERIALS AND METHODS: A total of 3,836 RTI patients in Foshan City between 2022 and 2024 were enrolled. Specimens, including alveolar lavage fluid, sputum, pleural effusion, and throat swab, were collected. Pathogen identification was performed using the t-NGS technology. Raw sequencing data were processed via Fastp software, and human host sequences were removed by alignment to the hg19 reference genome using BWA-mem. Microbial sequences were aligned against the NCBI RefSeq/nt and FDA ARGOS databases for pathogen identification. Pathogens, contaminants, and commensal bacteria were distinguished according to the Pathogen Pathogenicity Classification Table. Chi-square test was applied to compare pathogen distributions across genders, age groups, and sample types, and to assess the trend of mixed and single infection. Additionally, 23S rRNA mutations were analyzed, and the response of the known pathogenic bacteria to the antibiotics was determined.
RESULTS: A total of 129 potential pathogens were identified, predominantly including bacteria (57.28%) and RNA viruses (24.65%). The most frequently detected pathogenic bacteria were Haemophilus influenzae (11.56%), Mycoplasma pneumoniae (9.57%), and Streptococcus pneumoniae (6.31%), while the predominant viruses included Rhinovirus (6.6%), human respiratory syncytial virus (4.07%), and Influenza A virus (3.57%). Pathogen profiles varied across age groups, such as Mycoplasma pneumoniae and Haemophilus influenzae were more common in children (1- to 12-year-olds), while Candida albicans and Epstein-Barr virus were more frequently detected in the elderly (≥ 60 years old). Furthermore, Moraxella catarrhalis and Rhinovirus were more frequently detected in throat swabs, whilst Epstein-Barr virus, Candida albicans, and Pseudomonas aeruginosa were more commonly detected in alveolar lavage fluid samples. Mixed infections were relatively frequent, with a higher incidence observed in spring and winter. The macrolide resistance mutation rate in 23S rRNA reached 96.79%, predominantly involving the A2063G mutation, with higher rates observed in children and the elderly. Additionally, known pathogenic bacteria also exhibited varying levels of resistance to different antibiotics.
DISCUSSION: While numerous studies have demonstrated the utility of t-NGS in identifying RTI pathogens, our study provided detailed epidemiological data from a retrospective cohort in Foshan city.
CONCLUSION: The application of t-NGS effectively revealed the pathogenic characteristics of RTI patients with respiratory syndrome. Overall, these data provided valuable insights into the clinical diagnosis and management of RTI.
MATERIALS AND METHODS: A total of 3,836 RTI patients in Foshan City between 2022 and 2024 were enrolled. Specimens, including alveolar lavage fluid, sputum, pleural effusion, and throat swab, were collected. Pathogen identification was performed using the t-NGS technology. Raw sequencing data were processed via Fastp software, and human host sequences were removed by alignment to the hg19 reference genome using BWA-mem. Microbial sequences were aligned against the NCBI RefSeq/nt and FDA ARGOS databases for pathogen identification. Pathogens, contaminants, and commensal bacteria were distinguished according to the Pathogen Pathogenicity Classification Table. Chi-square test was applied to compare pathogen distributions across genders, age groups, and sample types, and to assess the trend of mixed and single infection. Additionally, 23S rRNA mutations were analyzed, and the response of the known pathogenic bacteria to the antibiotics was determined.
RESULTS: A total of 129 potential pathogens were identified, predominantly including bacteria (57.28%) and RNA viruses (24.65%). The most frequently detected pathogenic bacteria were Haemophilus influenzae (11.56%), Mycoplasma pneumoniae (9.57%), and Streptococcus pneumoniae (6.31%), while the predominant viruses included Rhinovirus (6.6%), human respiratory syncytial virus (4.07%), and Influenza A virus (3.57%). Pathogen profiles varied across age groups, such as Mycoplasma pneumoniae and Haemophilus influenzae were more common in children (1- to 12-year-olds), while Candida albicans and Epstein-Barr virus were more frequently detected in the elderly (≥ 60 years old). Furthermore, Moraxella catarrhalis and Rhinovirus were more frequently detected in throat swabs, whilst Epstein-Barr virus, Candida albicans, and Pseudomonas aeruginosa were more commonly detected in alveolar lavage fluid samples. Mixed infections were relatively frequent, with a higher incidence observed in spring and winter. The macrolide resistance mutation rate in 23S rRNA reached 96.79%, predominantly involving the A2063G mutation, with higher rates observed in children and the elderly. Additionally, known pathogenic bacteria also exhibited varying levels of resistance to different antibiotics.
DISCUSSION: While numerous studies have demonstrated the utility of t-NGS in identifying RTI pathogens, our study provided detailed epidemiological data from a retrospective cohort in Foshan city.
CONCLUSION: The application of t-NGS effectively revealed the pathogenic characteristics of RTI patients with respiratory syndrome. Overall, these data provided valuable insights into the clinical diagnosis and management of RTI.