National Food Institute, Research Group of Genomic Epidemiology, Technical University of Denmark, Kgs. Lyngby, Denmark.
Department of Plant and Environmental Sciences, Section for Organismal Biology, Faculty of Science, University of Copenhagen, Copenhagen, Denmark.
Microb Genom. 2023 Aug;9(8). doi: 10.1099/mgen.0.001076.
The global surveillance and outbreak investigation of antimicrobial resistance (AMR) is amidst a paradigm shift from traditional biology to bioinformatics. This is due to developments in whole-genome-sequencing (WGS) technologies, bioinformatics tools, and reduced costs. The increased use of WGS is accompanied by challenges such as standardization, quality control (QC), and data sharing. Thus, there is global need for inter-laboratory WGS proficiency test (PT) schemes to evaluate laboratories' capacity to produce reliable genomic data. Here, we present the results of the first iteration of the Genomic PT (GPT) organized by the Global Capacity Building Group at the Technical University of Denmark in 2020. Participating laboratories sequenced two isolates and corresponding DNA of , and , using WGS methodologies routinely employed at their laboratories. The participants' ability to obtain consistently good-quality WGS data was assessed based on several QC WGS metrics. A total of 21 laboratories from 21 European countries submitted WGS and meta-data. Most delivered high-quality sequence data with only two laboratories identified as overall underperforming. The QC metrics, N50 and number of contigs, were identified as good indicators for high-sequencing quality. We propose QC thresholds for N50 greater than 20 000 and 25 000 for and respectively, and number of contigs >200 bp greater than 225, 265 and 100 for , and , respectively. The GPT2020 results confirm the importance of systematic QC procedures, ensuring the submission of reliable WGS data for surveillance and outbreak investigation to meet the requirements of the paradigm shift in methodology.
全球抗菌药物耐药性(AMR)监测和暴发调查正处于从传统生物学向生物信息学转变的过程中。这是由于全基因组测序(WGS)技术、生物信息学工具的发展以及成本的降低。WGS 的广泛应用伴随着标准化、质量控制(QC)和数据共享等挑战。因此,全球需要建立实验室间 WGS 能力验证(PT)计划,以评估实验室生成可靠基因组数据的能力。在这里,我们介绍了丹麦技术大学全球能力建设小组于 2020 年组织的第一次基因组 PT(GPT)的结果。参与实验室使用其实验室常规使用的 WGS 方法对 2 个分离株和相应的 DNA 进行测序。根据几个 QC WGS 指标评估参与者获得一致高质量 WGS 数据的能力。来自 21 个欧洲国家的 21 个实验室提交了 WGS 和元数据。大多数实验室提供了高质量的序列数据,只有两个实验室被确定为整体表现不佳。QC 指标 N50 和 contig 数量被认为是高质量测序的良好指标。我们提出了 N50 大于 20000 和 25000 分别为 和 的 QC 阈值,contig 数量>200bp 分别大于 225、265 和 100 分别为 、 和 。GPT2020 的结果证实了系统 QC 程序的重要性,以确保提交可靠的 WGS 数据用于监测和暴发调查,以满足方法学转变的要求。