High-throughput mycobacterial interspersed repetitive-unit-variable-number tandem-repeat genotyping for Mycobacterium tuberculosis epidemiological studies

用于结核分枝杆菌流行病学研究的高通量分枝杆菌散在重复单元可变数目串联重复序列基因分型

阅读:1

Abstract

The emergence of drug-resistant forms of tuberculosis (TB) represents a major public health concern. Understanding the transmission routes of the disease is a key factor for its control and for the implementation of efficient interventions. Mycobacterial interspersed repetitive-unit-variable-number tandem-repeat (MIRU-VNTR) marker typing is a well-described method for lineage identification and transmission tracking. However, the conventional manual genotyping technique is cumbersome and time-consuming and entails many risks for errors, thus hindering its implementation and dissemination. We describe here a new approach using the QIAxcel system, an automated high-throughput capillary electrophoresis system that also carries out allele calling. This automated method was assessed on 1,824 amplicons from 82 TB isolates and tested with sets of markers of 15 or 24 loci. Overall allele-calling concordance between the methods from 140 to 1,317 bp was 98.9%. DNA concentrations and repeatability and reproducibility performances showed no biases in allele calling. Furthermore, turnaround time using this automated system was reduced by 81% compared to the conventional manual agarose gel method. In sum, this new automated method facilitates MIRU-VNTR genotyping and provides reliable results. Therefore, it is well suited for field genotyping. The implementation of this method will help to achieve accurate and cost-effective epidemiological studies, especially in countries with a high prevalence of TB, where the high number of strains complicates the surveillance of circulating lineages and requires efficient interventions to be carried out in an urgent manner.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。