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。

IF 1.7 4区 生物学 Q4 BIOCHEMICAL RESEARCH METHODS
Danfeng Zhang , Ali Yang , Kai Sheng , Shuyu Fang , Liang Zhou
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引用次数: 0

摘要

目的探讨第二代元基因组新一代测序(mNGS)在肺部感染患者病原体检测中的应用价值:我们对 2021 年 1 月至 2023 年 5 月期间在我院和上海市第五人民医院接受治疗的 65 例肺部感染病例进行了回顾性分析。所有受试者均接受了 mNGS、靶向新一代测序(tNGS)和传统微生物培养。对比分析评估了这些方法鉴定的病原体的多样性和数量,并评价了它们各自在肺部感染诊断中的诊断能力:结果:在 65 个病例中,mNGS 在 60 个病例中成功鉴定出病原体,而 tNGS 在 42 个病例中鉴定出阳性结果,传统实验室培养在 24 个病例中检测出病原体。在细菌属一级,mNGS 鉴别出 9 个属、11 个种和 92 个病原菌分离物,而 tNGS 鉴别出 8 个属、8 个种和 71 个分离物。传统方法的灵敏度较低,只能检测到 6 个属、7 个种和 33 个分离物。在真菌检测方面,mNGS 发现了 4 个真菌物种,tNGS 发现了 4 个念珠菌属分离物,传统方法发现了 2 个同属分离物。mNGS 在物种水平上的病毒检测发现了 10 个物种和 46 个分离物,而 tNGS 仅检测到 3 个物种和 7 个分离物。mNGS 诊断肺部感染的接收者操作特征曲线下面积(AUC)(95% 置信区间)为 0.818(0.671-0.966),tNGS 为 0.668(0.475-0.860),传统培养为 0.721(0.545-0.897)。mNGS 灵敏度的提高和病原体图谱的全面性凸显了它作为临床微生物学主要诊断工具的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.

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来源期刊
Journal of microbiological methods
Journal of microbiological methods 生物-生化研究方法
CiteScore
4.30
自引率
4.50%
发文量
151
审稿时长
29 days
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.
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