Danfeng Zhang , Ali Yang , Kai Sheng , Shuyu Fang , Liang Zhou
{"title":"第二代元基因组测序技术在检测呼吸道患者病原体中的应用。","authors":"Danfeng Zhang , Ali Yang , Kai Sheng , Shuyu Fang , Liang Zhou","doi":"10.1016/j.mimet.2024.107021","DOIUrl":null,"url":null,"abstract":"<div><h3>Objective</h3><p>To explore the application value of the second-generation metagenomic next-generation sequencing (mNGS) in the detection of pathogens in patients with pulmonary infection.</p></div><div><h3>Methods</h3><p>We conducted a retrospective analysis of 65 pulmonary infection cases treated at our institution and the Fifth People's Hospital of Shanghai between January 2021 and May 2023. All subjects were subjected to mNGS, targeted next-generation sequencing (tNGS), and conventional microbiological culture. A comparative analysis was performed to evaluate the diversity and quantity of pathogens identified by these methodologies and to appraise their respective diagnostic capabilities in pulmonary infection diagnostics.</p></div><div><h3>Results</h3><p>The mNGS successfully identified etiological agents in 60 of the 65 cases, compared to tNGS, which yielded positive results in 42 cases, and conventional laboratory cultures, which detected pathogens in 24 cases. At the bacterial genus level, mNGS discerned 9 genera, 11 species, and 92 isolates of pathogenic bacteria, whereas tNGS identified 8 genera, 8 species, and 71 isolates. Conventional methods were less sensitive, detecting only 6 genera, 7 species, and 33 isolates. In terms of fungal detection, mNGS identified 4 fungal species, tNGS detected 4 isolates of the Candida genus, and conventional methods identified 2 isolates of the same genus. Viral detection at the species level revealed 10 species and 46 isolates by mNGS, whereas tNGS detected only 3 species and 7 isolates. The area under the receiver operating characteristic curve (AUC) with 95% confidence intervals for diagnosing pulmonary infections was 0.818 (0.671 to 0.966) for mNGS, 0.668 (0.475 to 0.860) for tNGS, and 0.721 (0.545 to 0.897) for conventional culture.The mNGS demonstrates superior diagnostic efficacy and pathogen detection breadth in critically ill patients with respiratory infections, offering a significant advantage by reducing the time to diagnosis. The enhanced sensitivity and comprehensive pathogen profiling of mNGS underscore its potential as a leading diagnostic tool in clinical microbiology.</p></div>","PeriodicalId":16409,"journal":{"name":"Journal of microbiological methods","volume":"225 ","pages":"Article 107021"},"PeriodicalIF":1.7000,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0167701224001337/pdfft?md5=76785589bd399a508377d26423988ea4&pid=1-s2.0-S0167701224001337-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Application of the second-generation sequencing technology of metagenomics in the detection of pathogens in respiratory patients\",\"authors\":\"Danfeng Zhang , Ali Yang , Kai Sheng , Shuyu Fang , Liang Zhou\",\"doi\":\"10.1016/j.mimet.2024.107021\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objective</h3><p>To explore the application value of the second-generation metagenomic next-generation sequencing (mNGS) in the detection of pathogens in patients with pulmonary infection.</p></div><div><h3>Methods</h3><p>We conducted a retrospective analysis of 65 pulmonary infection cases treated at our institution and the Fifth People's Hospital of Shanghai between January 2021 and May 2023. All subjects were subjected to mNGS, targeted next-generation sequencing (tNGS), and conventional microbiological culture. A comparative analysis was performed to evaluate the diversity and quantity of pathogens identified by these methodologies and to appraise their respective diagnostic capabilities in pulmonary infection diagnostics.</p></div><div><h3>Results</h3><p>The mNGS successfully identified etiological agents in 60 of the 65 cases, compared to tNGS, which yielded positive results in 42 cases, and conventional laboratory cultures, which detected pathogens in 24 cases. At the bacterial genus level, mNGS discerned 9 genera, 11 species, and 92 isolates of pathogenic bacteria, whereas tNGS identified 8 genera, 8 species, and 71 isolates. Conventional methods were less sensitive, detecting only 6 genera, 7 species, and 33 isolates. In terms of fungal detection, mNGS identified 4 fungal species, tNGS detected 4 isolates of the Candida genus, and conventional methods identified 2 isolates of the same genus. Viral detection at the species level revealed 10 species and 46 isolates by mNGS, whereas tNGS detected only 3 species and 7 isolates. The area under the receiver operating characteristic curve (AUC) with 95% confidence intervals for diagnosing pulmonary infections was 0.818 (0.671 to 0.966) for mNGS, 0.668 (0.475 to 0.860) for tNGS, and 0.721 (0.545 to 0.897) for conventional culture.The mNGS demonstrates superior diagnostic efficacy and pathogen detection breadth in critically ill patients with respiratory infections, offering a significant advantage by reducing the time to diagnosis. The enhanced sensitivity and comprehensive pathogen profiling of mNGS underscore its potential as a leading diagnostic tool in clinical microbiology.</p></div>\",\"PeriodicalId\":16409,\"journal\":{\"name\":\"Journal of microbiological methods\",\"volume\":\"225 \",\"pages\":\"Article 107021\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2024-08-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0167701224001337/pdfft?md5=76785589bd399a508377d26423988ea4&pid=1-s2.0-S0167701224001337-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of microbiological methods\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0167701224001337\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BIOCHEMICAL RESEARCH METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of microbiological methods","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167701224001337","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
Application of the second-generation sequencing technology of metagenomics in the detection of pathogens in respiratory patients
Objective
To explore the application value of the second-generation metagenomic next-generation sequencing (mNGS) in the detection of pathogens in patients with pulmonary infection.
Methods
We conducted a retrospective analysis of 65 pulmonary infection cases treated at our institution and the Fifth People's Hospital of Shanghai between January 2021 and May 2023. All subjects were subjected to mNGS, targeted next-generation sequencing (tNGS), and conventional microbiological culture. A comparative analysis was performed to evaluate the diversity and quantity of pathogens identified by these methodologies and to appraise their respective diagnostic capabilities in pulmonary infection diagnostics.
Results
The mNGS successfully identified etiological agents in 60 of the 65 cases, compared to tNGS, which yielded positive results in 42 cases, and conventional laboratory cultures, which detected pathogens in 24 cases. At the bacterial genus level, mNGS discerned 9 genera, 11 species, and 92 isolates of pathogenic bacteria, whereas tNGS identified 8 genera, 8 species, and 71 isolates. Conventional methods were less sensitive, detecting only 6 genera, 7 species, and 33 isolates. In terms of fungal detection, mNGS identified 4 fungal species, tNGS detected 4 isolates of the Candida genus, and conventional methods identified 2 isolates of the same genus. Viral detection at the species level revealed 10 species and 46 isolates by mNGS, whereas tNGS detected only 3 species and 7 isolates. The area under the receiver operating characteristic curve (AUC) with 95% confidence intervals for diagnosing pulmonary infections was 0.818 (0.671 to 0.966) for mNGS, 0.668 (0.475 to 0.860) for tNGS, and 0.721 (0.545 to 0.897) for conventional culture.The mNGS demonstrates superior diagnostic efficacy and pathogen detection breadth in critically ill patients with respiratory infections, offering a significant advantage by reducing the time to diagnosis. The enhanced sensitivity and comprehensive pathogen profiling of mNGS underscore its potential as a leading diagnostic tool in clinical microbiology.
期刊介绍:
The Journal of Microbiological Methods publishes scholarly and original articles, notes and review articles. These articles must include novel and/or state-of-the-art methods, or significant improvements to existing methods. Novel and innovative applications of current methods that are validated and useful will also be published. JMM strives for scholarship, innovation and excellence. This demands scientific rigour, the best available methods and technologies, correctly replicated experiments/tests, the inclusion of proper controls, calibrations, and the correct statistical analysis. The presentation of the data must support the interpretation of the method/approach.
All aspects of microbiology are covered, except virology. These include agricultural microbiology, applied and environmental microbiology, bioassays, bioinformatics, biotechnology, biochemical microbiology, clinical microbiology, diagnostics, food monitoring and quality control microbiology, microbial genetics and genomics, geomicrobiology, microbiome methods regardless of habitat, high through-put sequencing methods and analysis, microbial pathogenesis and host responses, metabolomics, metagenomics, metaproteomics, microbial ecology and diversity, microbial physiology, microbial ultra-structure, microscopic and imaging methods, molecular microbiology, mycology, novel mathematical microbiology and modelling, parasitology, plant-microbe interactions, protein markers/profiles, proteomics, pyrosequencing, public health microbiology, radioisotopes applied to microbiology, robotics applied to microbiological methods,rumen microbiology, microbiological methods for space missions and extreme environments, sampling methods and samplers, soil and sediment microbiology, transcriptomics, veterinary microbiology, sero-diagnostics and typing/identification.