Abstract
武洁,唐利红,杨崇广,严慧琴,孙华,沈鑫.全基因组测序技术在结核病流行病学调查中的应用[J].Chinese journal of Epidemiology,2016,37(12):1644-1646
全基因组测序技术在结核病流行病学调查中的应用
Application of whole genome sequencing technology in the epidemiology of tuberculosis
Received:June 29, 2016  
DOI:10.3760/cma.j.issn.0254-6450.2016.12.017
KeyWord: 结核病  耐多药  全基因组测序
English Key Word: Tuberculosis  Multidrug-resistance  Whole-genome sequencing
FundProject:国家科技重大专项(2013ZX10004903);上海市第四轮公共卫生三年行动计划(15GWZK0801,GWTD2015S02)
Author NameAffiliationE-mail
Wu Jie Shanghai Municipal Center for Disease Control and Prevention, Shanghai 100336, China  
Tang Lihong Shanghai Minhang Center for Disease Control and Prevention, Shanghai 201101, China  
Yang Chongguang Fudan University, Shanghai 200032, China Wu Jie and Tang Lihong are the first authors who contributed equally to the article  
Yan Huiqin Shanghai Minhang Center for Disease Control and Prevention, Shanghai 201101, China  
Sun Hua Shanghai Minhang Center for Disease Control and Prevention, Shanghai 201101, China  
Shen Xin Shanghai Municipal Center for Disease Control and Prevention, Shanghai 100336, China shenxin@scdc.sh.cn 
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Abstract:
      目的 评估全基因组测序技术在结核病分子流行病学调查中的应用。方法 对2008-2012年在上海市两家结核病定点医院发现9名耐多药患者中分离的结核分枝杆菌具有相同的可变数目串联重复序列,本研究对此进行流行学调查,并对9株结核分枝杆菌进行全基因组测序,分析其传播关系。结果 全基因组序列分析将9株结核分枝杆菌分为两个有传播关系的网络,一个为包括7株结核分枝杆菌(5例和2例患者分别来自不同的医院)的大簇,一个为只有2株结核分枝杆菌的小簇。两个簇之间相差15个单核苷酸多态性(SNP)位点,提示两个簇的遗传距离相对较远,基于菌株SNP差异构建的传播链显示了每个簇内菌株的传播方向和耐药突变积累的过程。结论 基于全基因组测序数据研究耐药结核病的传播网络,能准确判断传播路径和方向,识别传染源和传播缺失环节。
English Abstract:
      Objective To delineate the application of whole genome sequencing technology in the epidemiology of tuberculosis. Methods From 2009 to 2012, nine Mycobacterium tuberculosis that sharing identical variable number of tandem repeats genotype (VNTR) patterns were reported from two TB cases designated hospitals. Both whole-genome sequencing analysis (WGS) and epidemiologic investigations were performed to describe the transmission patterns of these Mycobacterium tuberculosis. Results By WGS analysis, two genomic clusters including 7 and 2 Mycobacterium tuberculosis were noticed, respectively. The cluster of 2 cases possessed more than 15 single nucleotide polymorphisms (SNPs) when compared to the cluster of 7 cases and suggesting that the transmission route was independent. The transmission chain based on the SNPs difference showed the process of the propagation direction and the accumulation of drug resistance mutations in each cluster. Conclusion Using a WGS-based genomic epidemiologic approach, we were able to reconstruct the tuberculosis transmission network, tracing the putative source of the transmission and determining the transmission direction or the missing links.
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