National Reference Laboratory for Mycobacteria, Department of Infectious Diseases, National Institute of Health, 1649-016 Lisbon, Portugal.
Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health, 1649-016 Lisbon, Portugal.
Tuberculosis (Edinb). 2019 Mar;115:81-88. doi: 10.1016/j.tube.2019.02.006. Epub 2019 Feb 25.
Whole-genome sequencing (WGS) offers unprecedented resolution for tracking Mycobacterium tuberculosis transmission and antibiotic-resistance spread. Still, the establishment of standardized WGS-based pipelines and the definition of epidemiological clusters based on genetic relatedness are under discussion. We aimed to implement a dynamic gene-by-gene approach, fully relying on freely available software, for prospective WGS-based tuberculosis surveillance, demonstrating its application for detecting transmission chains by retrospectively analysing all M/XDR strains isolated in 2013-2017 in Portugal. We observed a good correlation between genetic relatedness and epidemiological links, with strongly epilinked clusters displaying mean pairwise allele differences (AD) always below 0.3% (ratio of mean AD over the total number of shared loci between same-cluster strains). This data parallels the genetic distances acquired by the core-SNV analysis, while providing higher resolution and epidemiological concordance than MIRU-VNTR genotyping. The dynamic analysis of strain sub-sets (i.e., increasing the number of shared loci within each sub-set) also strengthens the confidence in detecting epilinked clusters. This gene-by-gene strategy also offers several practical benefits (e.g., reliance on freely-available software, scalability and low computational requirements) that further consolidated its suitability for a timely and robust prospective WGS-based laboratory surveillance of M/XDR-TB cases.
全基因组测序 (WGS) 为追踪结核分枝杆菌传播和抗生素耐药性扩散提供了前所未有的分辨率。然而,基于 WGS 的标准化管道的建立以及基于遗传相关性的流行病学聚类的定义仍在讨论中。我们旨在实施一种动态的逐基因方法,完全依赖于免费提供的软件,进行前瞻性的基于 WGS 的结核病监测,通过回顾性分析 2013-2017 年在葡萄牙分离的所有 M/XDR 菌株来证明其在检测传播链方面的应用。我们观察到遗传相关性与流行病学联系之间存在良好的相关性,具有强烈连锁关系的聚类显示平均等位基因差异 (AD) 始终低于 0.3%(同一聚类菌株之间共享基因座总数的平均 AD 比值)。该数据与核心-SNV 分析获得的遗传距离相吻合,同时提供了比 MIRU-VNTR 基因分型更高的分辨率和流行病学一致性。菌株子集的动态分析(即在每个子集中增加共享基因座的数量)也增强了检测连锁聚类的信心。这种逐基因策略还具有几个实际优势(例如,依赖免费提供的软件、可扩展性和低计算要求),进一步巩固了其在及时和稳健的基于 WGS 的 M/XDR-TB 病例实验室监测中的适用性。