Sharma Meenu K, Janella Debra, McGurran Alisa, Corbett Cindi, Adam Heather, Akochy Pierre-Marie, Haldane David, MacKenzie Hope, Minion Jessica, Needle Robert, Newberry Caroline, Patterson Michael, Sekirov Inna, Tyrrell Gregory, Soualhine Hafid
National Reference Centre for Mycobacteriology, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Canada.
Department of Medical Microbiology, University of Manitoba, Winnipeg, Canada.
Can J Infect Dis Med Microbiol. 2022 Aug 22;2022:3505142. doi: 10.1155/2022/3505142. eCollection 2022.
Tuberculosis is a significant cause of morbidity worldwide and is a priority at the provincial and federal levels in Canada. It is known that tuberculosis transmission networks are complex and span many years as well as different jurisdictions and countries. MIRU-VNTR is a universal tuberculosis genotyping method that utilizes a 24-loci pattern and it has shown promise in identifying inter and intrajurisdictional clusters within Canada. MIRU-VNTR data collected over 10 years from the National Reference Centre for Mycobacteriology (NRCM) were analyzed in this study. Some clusters were unique to a single province/territory, while others spanned multiple provinces and/or territories in Canada. The use of a universal laboratory test can enhance contact tracing, provide geographical information on circulating genotypes, and hence, aid in tuberculosis investigation by public health. The housing of all data on one platform, technical ease of the method, easy exchange of data between jurisdictions, and strong collaboration with laboratories and surveillance units at the provincial and federal levels have the potential to identify possible outbreaks in real time.
结核病是全球发病的一个重要原因,在加拿大省级和联邦层面都是优先关注的问题。众所周知,结核病传播网络复杂,跨越多年以及不同司法管辖区和国家。多位点可变数目串联重复序列分型(MIRU-VNTR)是一种通用的结核病菌株基因分型方法,采用24个位点模式,在识别加拿大境内不同司法管辖区内和司法管辖区间的聚类方面已显示出前景。本研究分析了从国家分枝杆菌病参考中心(NRCM)收集的10多年的MIRU-VNTR数据。一些聚类是单个省/地区特有的,而其他聚类跨越加拿大的多个省和/或地区。使用通用实验室检测可加强接触者追踪,提供有关传播基因型的地理信息,从而有助于公共卫生部门进行结核病调查。将所有数据存储在一个平台上、该方法技术简便、不同司法管辖区之间数据易于交换以及与省级和联邦层面的实验室及监测单位密切合作,有可能实时识别可能的疫情暴发。