The application prospect of metagenomic next-generation sequencing technology in diagnosing suspected lower respiratory tract infections

ObjectiveLower respiratory tract infections present substantial diagnostic and therapeutic challenges, negatively impacting individual health. This study aims to utilize metagenomic next-generation sequencing (mNGS) technology to comprehensively explore the spectrum of pathogens, the detection of an...

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Main Authors: Wei Li, Mingming Zhao, Weiwei Wu, Gang Chen, Yanping Hang, Haixia Zheng, Zhenyun Gao, Jia Liu, Yuguo Zhao
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-04-01
Series:Frontiers in Cellular and Infection Microbiology
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Online Access:https://www.frontiersin.org/articles/10.3389/fcimb.2025.1494638/full
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author Wei Li
Mingming Zhao
Weiwei Wu
Gang Chen
Yanping Hang
Haixia Zheng
Zhenyun Gao
Jia Liu
Yuguo Zhao
author_facet Wei Li
Mingming Zhao
Weiwei Wu
Gang Chen
Yanping Hang
Haixia Zheng
Zhenyun Gao
Jia Liu
Yuguo Zhao
author_sort Wei Li
collection DOAJ
description ObjectiveLower respiratory tract infections present substantial diagnostic and therapeutic challenges, negatively impacting individual health. This study aims to utilize metagenomic next-generation sequencing (mNGS) technology to comprehensively explore the spectrum of pathogens, the detection of antibiotic resistance genes, and contributing factors associated with lung infections.MethodThe mNGS data of 217 patients with suspected lung infections attending the Respiratory Department of Nanjing Lishui People’s Hospital and Gaochun People’s Hospital from September 2022 to September 2023 were retrospectively analyzed. The study assessed the pathogenic spectrum of lung infections and compared the performance of patients with mNGS results from conventional microbiological techniques (CMT).ResultsThe overall positivity rate of mNGS was 95.20%, demonstrating superior sensitivity (97.01% vs. 41.79%) and accuracy (75.56% vs. 56.67%) compared to CMT. Bacterial infections were the most prevalent, accounting for 60.76% of cases. And the most prevalent bacteria, fungus and virus were Mycobacterium tuberculosis (14.41%), Candida albicans (15.72%), and EB virus (14.85%), respectively. The primary resistance genes detected were tetM (17, 8.29%), mel (6, 2.93%), and PC1 beta-lactamase (blaZ) (3, 1.46%). Notably, TEM-183, PDC-5 and PDC-3 were exclusively detected in the Chronic Obstructive Pulmonary Disease (COPD) group. The multivariate binary logistic regression analysis revealed that there was no significant association between gender, presence of hypertension, or COPD with the type of infection in patients (p=0.679, p=0.229, p=0.345). However, the immune status was found to be statistically significant (p=0.009).ConclusionWith the guidance of mNGS, patients with suspected respiratory tract infections can rapidly and accurately establish a pathogenic basis for their conditions. mNGS effectively identify mixed infections, enrich the pathogen spectrum of lung infections, and provide a large and reliable information base for the clinical realization of targeted medication.
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spelling doaj-art-3a43466b6d3f48c3be2f40c8b7fb91672025-08-20T02:26:59ZengFrontiers Media S.A.Frontiers in Cellular and Infection Microbiology2235-29882025-04-011510.3389/fcimb.2025.14946381494638The application prospect of metagenomic next-generation sequencing technology in diagnosing suspected lower respiratory tract infectionsWei Li0Mingming Zhao1Weiwei Wu2Gang Chen3Yanping Hang4Haixia Zheng5Zhenyun Gao6Jia Liu7Yuguo Zhao8Department of Respiratory Medicine, Nanjing Lishui People's Hospital, Zhongda Hospital Lishui Branch, Southeast University, Nanjing, Jiangsu, ChinaDepartment of Pulmonary and Critical Care Medicine, Nanjing Gaochun People’s Hospital, Nanjing, Jiangsu, ChinaDinfectome Inc., Nanjing, Jiangsu, ChinaDepartment of Pulmonary and Critical Care Medicine, Nanjing Gaochun People’s Hospital, Nanjing, Jiangsu, ChinaDepartment of Pulmonary and Critical Care Medicine, Nanjing Gaochun People’s Hospital, Nanjing, Jiangsu, ChinaDepartment of Pulmonary and Critical Care Medicine, Nanjing Gaochun People’s Hospital, Nanjing, Jiangsu, ChinaDepartment of Respiratory Medicine, Nanjing Lishui People's Hospital, Zhongda Hospital Lishui Branch, Southeast University, Nanjing, Jiangsu, ChinaDinfectome Inc., Nanjing, Jiangsu, ChinaDepartment of Respiratory Medicine, Nanjing Lishui People's Hospital, Zhongda Hospital Lishui Branch, Southeast University, Nanjing, Jiangsu, ChinaObjectiveLower respiratory tract infections present substantial diagnostic and therapeutic challenges, negatively impacting individual health. This study aims to utilize metagenomic next-generation sequencing (mNGS) technology to comprehensively explore the spectrum of pathogens, the detection of antibiotic resistance genes, and contributing factors associated with lung infections.MethodThe mNGS data of 217 patients with suspected lung infections attending the Respiratory Department of Nanjing Lishui People’s Hospital and Gaochun People’s Hospital from September 2022 to September 2023 were retrospectively analyzed. The study assessed the pathogenic spectrum of lung infections and compared the performance of patients with mNGS results from conventional microbiological techniques (CMT).ResultsThe overall positivity rate of mNGS was 95.20%, demonstrating superior sensitivity (97.01% vs. 41.79%) and accuracy (75.56% vs. 56.67%) compared to CMT. Bacterial infections were the most prevalent, accounting for 60.76% of cases. And the most prevalent bacteria, fungus and virus were Mycobacterium tuberculosis (14.41%), Candida albicans (15.72%), and EB virus (14.85%), respectively. The primary resistance genes detected were tetM (17, 8.29%), mel (6, 2.93%), and PC1 beta-lactamase (blaZ) (3, 1.46%). Notably, TEM-183, PDC-5 and PDC-3 were exclusively detected in the Chronic Obstructive Pulmonary Disease (COPD) group. The multivariate binary logistic regression analysis revealed that there was no significant association between gender, presence of hypertension, or COPD with the type of infection in patients (p=0.679, p=0.229, p=0.345). However, the immune status was found to be statistically significant (p=0.009).ConclusionWith the guidance of mNGS, patients with suspected respiratory tract infections can rapidly and accurately establish a pathogenic basis for their conditions. mNGS effectively identify mixed infections, enrich the pathogen spectrum of lung infections, and provide a large and reliable information base for the clinical realization of targeted medication.https://www.frontiersin.org/articles/10.3389/fcimb.2025.1494638/fullsuspected lower respiratory tract infectionmetagenomic next-generation sequencingCOPDpathogen spectrumresistance genes
spellingShingle Wei Li
Mingming Zhao
Weiwei Wu
Gang Chen
Yanping Hang
Haixia Zheng
Zhenyun Gao
Jia Liu
Yuguo Zhao
The application prospect of metagenomic next-generation sequencing technology in diagnosing suspected lower respiratory tract infections
Frontiers in Cellular and Infection Microbiology
suspected lower respiratory tract infection
metagenomic next-generation sequencing
COPD
pathogen spectrum
resistance genes
title The application prospect of metagenomic next-generation sequencing technology in diagnosing suspected lower respiratory tract infections
title_full The application prospect of metagenomic next-generation sequencing technology in diagnosing suspected lower respiratory tract infections
title_fullStr The application prospect of metagenomic next-generation sequencing technology in diagnosing suspected lower respiratory tract infections
title_full_unstemmed The application prospect of metagenomic next-generation sequencing technology in diagnosing suspected lower respiratory tract infections
title_short The application prospect of metagenomic next-generation sequencing technology in diagnosing suspected lower respiratory tract infections
title_sort application prospect of metagenomic next generation sequencing technology in diagnosing suspected lower respiratory tract infections
topic suspected lower respiratory tract infection
metagenomic next-generation sequencing
COPD
pathogen spectrum
resistance genes
url https://www.frontiersin.org/articles/10.3389/fcimb.2025.1494638/full
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