Pornchai Matangkasombut Center for Microbial Genomics, Department of Microbiology, Faculty of Science, Mahidol University, Bangkok 10400, Thailand.
Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA.
Microb Genom. 2021 Nov;7(11). doi: 10.1099/mgen.0.000697.
(Mtb) lineage 2 (L2) strains are present globally, contributing to a widespread tuberculosis (TB) burden, particularly in Asia where both prevalence of TB and numbers of drug resistant TB are highest. The increasing availability of whole-genome sequencing (WGS) data worldwide provides an opportunity to improve our understanding of the global genetic diversity of Mtb L2 and its association with the disease epidemiology and pathogenesis. However, existing L2 sublineage classification schemes leave >20 % of the Modern Beijing isolates unclassified. Here, we present a revised SNP-based classification scheme of L2 in a genomic framework based on phylogenetic analysis of >4000 L2 isolates from 34 countries in Asia, Eastern Europe, Oceania and Africa. Our scheme consists of over 30 genotypes, many of which have not been described before. In particular, we propose six main genotypes of Modern Beijing strains, denoted L2.2.M1-L2.2.M6. We also provide SNP markers for genotyping L2 strains from WGS data. This fine-scale genotyping scheme, which can classify >98 % of the studied isolates, serves as a basis for more effective monitoring and reporting of transmission and outbreaks, as well as improving genotype-phenotype associations such as disease severity and drug resistance. This article contains data hosted by Microreact.
(结核分枝杆菌)谱系 2 (L2)菌株在全球范围内存在,导致广泛的结核病(TB)负担,特别是在亚洲,那里的 TB 患病率和耐药性 TB 数量最高。全球范围内全基因组测序(WGS)数据的日益普及提供了一个机会,可以提高我们对结核分枝杆菌 L2 的全球遗传多样性及其与疾病流行病学和发病机制的关联的理解。然而,现有的 L2 亚谱系分类方案使超过 20%的现代北京分离株无法分类。在这里,我们在一个基因组框架中提出了一个基于 SNP 的 L2 修订分类方案,该方案基于来自亚洲、东欧、大洋洲和非洲的 34 个国家的 4000 多个 L2 分离株的系统发育分析。我们的方案包括 30 多种基因型,其中许多以前没有描述过。特别是,我们提出了六个主要的现代北京菌株基因型,分别命名为 L2.2.M1-L2.2.M6。我们还提供了用于从 WGS 数据对 L2 菌株进行基因分型的 SNP 标记。这种细粒度的基因分型方案可以对研究中超过 98%的分离株进行分类,为更有效地监测和报告传播和暴发提供了基础,以及改善基因型-表型关联,例如疾病严重程度和耐药性。本文包含由 Microreact 托管的数据。