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本文引用的文献

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J Clin Microbiol. 2023 Nov 21;61(11):e0026023. doi: 10.1128/jcm.00260-23. Epub 2023 Oct 25.
2
WHO's Global Tuberculosis Report 2022.世界卫生组织《2022年全球结核病报告》。
Lancet Microbe. 2023 Jan;4(1):e20. doi: 10.1016/S2666-5247(22)00359-7. Epub 2022 Dec 12.
3
A data compendium associating the genomes of 12,289 Mycobacterium tuberculosis isolates with quantitative resistance phenotypes to 13 antibiotics.一个关联了 12289 株结核分枝杆菌分离株基因组与 13 种抗生素定量耐药表型的数据集。
PLoS Biol. 2022 Aug 9;20(8):e3001721. doi: 10.1371/journal.pbio.3001721. eCollection 2022 Aug.
4
The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2022 update.Galaxy 平台:用于可访问、可重复和协作的生物医学分析:2022 更新。
Nucleic Acids Res. 2022 Jul 5;50(W1):W345-W351. doi: 10.1093/nar/gkac247.
5
The 2021 WHO catalogue of complex mutations associated with drug resistance: A genotypic analysis.《2021年世界卫生组织与耐药性相关的复杂突变目录:基因型分析》
Lancet Microbe. 2022 Apr;3(4):e265-e273. doi: 10.1016/S2666-5247(21)00301-3.
6
Evaluation of WGS performance for bacterial pathogen characterization with the Illumina technology optimized for time-critical situations.评估 Illumina 技术在时间紧迫情况下进行细菌病原体特征描述的 WGS 性能。
Microb Genom. 2021 Nov;7(11). doi: 10.1099/mgen.0.000699.
7
Mutations and Effects on Rifampin Resistance in .突变及其对利福平耐药性的影响 于…… (原文此处不完整)
Infect Drug Resist. 2021 Oct 5;14:4119-4128. doi: 10.2147/IDR.S333433. eCollection 2021.
8
Rapid and accurate SNP genotyping of clonal bacterial pathogens with BioHansel.利用 BioHansel 对克隆细菌病原体进行快速准确的 SNP 基因分型。
Microb Genom. 2021 Sep;7(9). doi: 10.1099/mgen.0.000651.
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Foundational Statistical Principles in Medical Research: Sensitivity, Specificity, Positive Predictive Value, and Negative Predictive Value.医学研究中的基本统计学原理:灵敏度、特异性、阳性预测值和阴性预测值。
Medicina (Kaunas). 2021 May 16;57(5):503. doi: 10.3390/medicina57050503.
10
New definitions of pre-extensively and extensively drug-resistant tuberculosis: update from the World Health Organization.广泛耐药结核病和极度耐药结核病的新定义:世界卫生组织的更新内容
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基于全基因组测序的结核病一线药物耐药性预测评估:5 年数据的经验教训。

Evaluation of Whole Genome Sequencing-Based Predictions of Antimicrobial Resistance to TB First Line Agents: A Lesson from 5 Years of Data.

机构信息

National Reference Centre for Mycobacteriology, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB R3E 3R2, Canada.

Department of Medical Microbiology & Infectious Diseases, University of Manitoba, Winnipeg, MB R3E 0J9, Canada.

出版信息

Int J Mol Sci. 2024 Jun 6;25(11):6245. doi: 10.3390/ijms25116245.

DOI:10.3390/ijms25116245
PMID:38892433
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11172968/
Abstract

Phenotypic susceptibility testing of the complex (MTBC) isolate requires culture growth, which can delay rapid detection of resistant cases. Whole genome sequencing (WGS) and data analysis pipelines can assist in predicting resistance to antimicrobials used in the treatment of tuberculosis (TB). This study compared phenotypic susceptibility testing results and WGS-based predictions of antimicrobial resistance (AMR) to four first-line antimicrobials-isoniazid, rifampin, ethambutol, and pyrazinamide-for MTBC isolates tested between the years 2018-2022. For this 5-year retrospective analysis, the WGS sensitivity for predicting resistance for isoniazid, rifampin, ethambutol, and pyrazinamide using Mykrobe was 86.7%, 100.0%, 100.0%, and 47.8%, respectively, and the specificity was 99.4%, 99.5%, 98.7%, and 99.9%, respectively. The predictive values improved slightly using Mykrobe corrections applied using TB Profiler, i.e., the WGS sensitivity for isoniazid, rifampin, ethambutol, and pyrazinamide was 92.31%, 100%, 100%, and 57.78%, respectively, and the specificity was 99.63%. 99.45%, 98.93%, and 99.93%, respectively. The utilization of WGS-based testing addresses concerns regarding test turnaround time and enables analysis for MTBC member identification, antimicrobial resistance prediction, detection of mixed cultures, and strain genotyping, all through a single laboratory test. WGS enables rapid resistance detection compared to traditional phenotypic susceptibility testing methods using the WHO TB mutation catalog, providing an insight into lesser-known mutations, which should be added to prediction databases as high-confidence mutations are recognized. The WGS-based methods can support TB elimination efforts in Canada and globally by ensuring the early start of appropriate treatment, rapidly limiting the spread of TB outbreaks.

摘要

复杂(MTBC)分离株的表型药敏试验需要培养生长,这可能会延迟耐药病例的快速检测。全基因组测序 (WGS) 和数据分析管道可协助预测用于治疗结核病 (TB) 的抗生素的耐药性。本研究比较了 2018 年至 2022 年间测试的 MTBC 分离株对异烟肼、利福平、乙胺丁醇和吡嗪酰胺这四种一线抗生素的表型药敏试验结果和基于 WGS 的抗生素耐药性 (AMR) 预测结果。在这项为期 5 年的回顾性分析中,Mykrobe 用于预测异烟肼、利福平、乙胺丁醇和吡嗪酰胺耐药性的 WGS 敏感性分别为 86.7%、100.0%、100.0%和 47.8%,特异性分别为 99.4%、99.5%、98.7%和 99.9%。使用 TB Profiler 应用 Mykrobe 校正后,预测值略有提高,即异烟肼、利福平、乙胺丁醇和吡嗪酰胺的 WGS 敏感性分别为 92.31%、100%、100%和 57.78%,特异性分别为 99.63%、99.45%、98.93%和 99.93%。基于 WGS 的检测方法的使用解决了对测试周转时间的担忧,并通过单次实验室测试即可实现 MTBC 成员鉴定、抗生素耐药性预测、混合培养物检测和菌株基因分型分析。与使用世卫组织 TB 突变目录的传统表型药敏试验方法相比,WGS 可实现快速耐药检测,提供对鲜为人知突变的深入了解,这些突变应在预测数据库中添加,因为随着高可信度突变的确认,这些突变将被视为高可信度突变。基于 WGS 的方法可以通过确保及早开始适当的治疗,快速限制 TB 爆发的传播,从而支持加拿大和全球的结核病消除工作。