提示: 手机请竖屏浏览!

利用DNA测序预测对一线结核药物的敏感性
Prediction of Susceptibility to First-Line Tuberculosis Drugs by DNA Sequencing


The CRyPTIC Consortium and the 100 ... 呼吸系统疾病 • 2018.10.11
相关阅读
• 通过基因型测序确定合适的结核病疗法 • 结核病的快速分子药物敏感性测试方法评价 • 针对TB的快速抗生素药敏试验正在进行中

DNA测序让结核分枝杆菌检测变得更灵敏和准确

 

范齐文,殷杏,吴炯,侯琦*

上海嘉会国际医院检验科

*通讯作者

 

目前世界上致死人数最多的病原体是什么?

查看更多

摘要


背景

世界卫生组织建议对所有结核病患者进行结核分枝杆菌复合群的药敏试验,以指导治疗决策并改善结局。DNA测序能否准确预测对一线抗结核药物的敏感谱一直不清楚。

 

方法

我们获得了来自六大洲16个国家的分离株的全基因组序列,以及对一线抗结核药物异烟肼、利福平、乙胺丁醇和吡嗪酰胺的耐药性或敏感性的相关表型。对于每个分离株,在9个基因中鉴定了与耐药性和药物敏感性相关的突变,并且预测了各表型,除非还存在未知关联的突变。为了确定全基因组测序如何指导一线药物治疗,我们预测了完整的敏感谱。如果预测分离株对异烟肼和其他药物敏感,或者如果在影响对其他药物敏感性的基因中含有未知关联的突变,则预测这些分离株对所有四种药物敏感(即全敏感[pansusceptible])。我们模拟了阴性预测值随着耐药率发生的变化。

 

结果

本研究共分析了10,209个分离株。针对利福平的表型的预测率最高(9,660/10,130 [95.4%]),针对乙胺丁醇的表型的预测率最低(8,794/9,794 [89.8%])。本研究分别以97.1%、97.5%、94.6%和91.3%的灵敏度正确预测出对异烟肼、利福平、乙胺丁醇和吡嗪酰胺耐药,分别以99.0%、98.8%、93.6%和96.8%的特异度正确预测出对上述药物敏感。在有完整药物敏感谱表型的7,516个分离株中,5,865个(78.0%)有完整的基因型预测结果,其中5,250个(89.5%)的敏感谱得到了正确的预测。在预测全敏感的4,037个表型敏感谱中,3,952个(97.9%)得到了正确的预测。

 

结论

结核分枝杆菌对一线药物敏感性的基因型预测结果与对这些药物的敏感性表型相关(由比尔和梅林达·盖茨基金会[Bill and Melinda Gates Foundation]等资助)。





作者信息

The CRyPTIC Consortium and the 100,000 Genomes Project
The members of the writing group (Timothy M. Walker, D.Phil., A. Sarah Walker, Ph.D., and Tim E.A. Peto, D.Phil.) assume responsibility for the overall content and integrity of this article. The authors’ full names and academic degrees are listed in the Appendix. The authors’ affiliations are listed in the Supplementary Appendix, available at NEJM.org. Address reprint requests to Dr. Timothy Walker at the Department of Microbiology, Level 7, John Radcliffe Hospital, Headley Way, Headington, Oxford, OX3 9DU, United Kingdom, or at timothy.walker@ndm.ox.ac.uk.

 

参考文献

1. Global tuberculosis report 2017. Geneva: World Health Organization, 2017 (http://www.who.int/tb/publications/global_report/gtbr2017_main_text.pdf).

2. Shah NS, Auld SC, Brust JCM, et al. Transmission of extensively drug-resistant tuberculosis in South Africa. N Engl J Med 2017;376:243-253.

3. Boehme CC, Nicol MP, Nabeta P, et al. Feasibility, diagnostic accuracy, and effectiveness of decentralised use of the Xpert MTB/RIF test for diagnosis of tuberculosis and multidrug resistance: a multicentre implementation study. Lancet 2011;377:1495-1505.

4. Sanchez-Padilla E, Merker M, Beckert P, et al. Detection of drug-resistant tuberculosis by Xpert MTB/RIF in Swaziland. N Engl J Med 2015;372:1181-1182.

5. Pankhurst LJ, Del Ojo Elias C, Votintseva AA, et al. Rapid, comprehensive, and affordable mycobacterial diagnosis with whole-genome sequencing: a prospective study. Lancet Respir Med 2016;4:49-58.

6. Walker TM, Kohl TA, Omar SV, et al. Whole-genome sequencing for prediction of Mycobacterium tuberculosis drug susceptibility and resistance: a retrospective cohort study. Lancet Infect Dis 2015;15:1193-1202.

7. High-priority target product profiles for new tuberculosis diagnostics: report of a consensus meeting. Geneva: World Health Organization, 2014 (http://www.who.int/tb/publications/tpp_report/en/).

8. The 100,000 Genomes Project Protocol v3. London: Genomics England, 2017 (https://www.genomicsengland.co.uk/100000-genomes-project-protocol/).

9. Lunter G, Goodson M. Stampy: a statistical algorithm for sensitive and fast mapping of Illumina sequence reads. Genome Res 2011;21:936-939.

10. Li H, Handsaker B, Wysoker A, et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 2009;25:2078-2079.

11. Iqbal Z, Caccamo M, Turner I, Flicek P, McVean G. De novo assembly and genotyping of variants using colored de Bruijn graphs. Nat Genet 2012;44:226-232.

12. Miotto P, Tessema B, Tagliani E, et al. A standardised method for interpreting the association between mutations and phenotypic drug resistance in Mycobacterium tuberculosis. Eur Respir J 2017;50(6):pii:1701354-pii:1701354.

13. Yadon AN, Maharaj K, Adamson JH, et al. A comprehensive characterization of PncA polymorphisms that confer resistance to pyrazinamide. Nat Commun 2017,8:588-588.

14. Casali N, Nikolayevskyy V, Balabanova Y, et al. Evolution and transmission of drug-resistant tuberculosis in a Russian population. Nat Genet 2014;46:279-286.

15. Manson AL, Cohen KA, Abeel T, et al. Genomic analysis of globally diverse Mycobacterium tuberculosis strains provides insights into the emergence and spread of multidrug resistance. Nat Genet 2017;49:395-402.

16. Schön T, Miotto P, Köser CU, Viveiros M, Böttger E, Cambau E. Mycobacterium tuberculosis drug-resistance testing: challenges, recent developments and perspectives. Clin Microbiol Infect 2017;23:154-160.

17. Nikolayevskyy V, Hillemann D, Richter E, et al. External quality assessment for tuberculosis diagnosis and drug resistance in the European Union: a five year multicentre implementation study. PLoS One 2016;11(4):e0152926-e0152926.

18. Rigouts L, Gumusboga M, de Rijk WB, et al. Rifampin resistance missed in automated liquid culture system for Mycobacterium tuberculosis isolates with specific rpoB mutations. J Clin Microbiol 2013;51:2641-2645.

19. André E, Goeminne L, Colmant A, Beckert P, Niemann S, Delmee M. Novel rapid PCR for the detection of Ile491Phe rpoB mutation of Mycobacterium tuberculosis, a rifampicin-resistance-conferring mutation undetected by commercial assays. Clin Microbiol Infect 2017;23(4):267.e5-267.e7.

20. Sreevatsan S, Stockbauer KE, Pan X, et al. Ethambutol resistance in Mycobacterium tuberculosis: critical role of embB mutations. Antimicrob Agents Chemother 1997;41:1677-1681.

21. Miotto P, Cabibbe AM, Feuerriegel S, et al. Mycobacterium tuberculosis pyrazinamide resistance determinants: a multicenter study. MBio 2014;5(5):e01819-e14.

22. Coronel J, Roper M, Mitchell S, et al. MODS accreditation process for regional reference laboratories in Peru: validation by GenoType® MTBDRplus. Int J Tuberc Lung Dis 2010;14:1475-1480.

服务条款 | 隐私政策 | 联系我们