National Food Institute, Technical University of Denmark, Research Group for Global Capacity Building, European Union Reference Laboratory for Antimicrobial Resistance, Kongens Lyngby, Denmark.
Wageningen Bioveterinary Research part of Wageningen University and Research, Lelystad, the Netherlands.
mSystems. 2024 Sep 17;9(9):e0016024. doi: 10.1128/msystems.00160-24. Epub 2024 Aug 6.
As antimicrobial resistance (AMR) surveillance shifts to genomics, ensuring the quality of whole-genome sequencing (WGS) data produced across laboratories is critical. Participation in genomic proficiency tests (GPTs) not only increases individual laboratories' WGS capacity but also provides a unique opportunity to improve species-specific thresholds for WGS quality control (QC) by repeated resequencing of distinct isolates. Here, we present the results of the EU Reference Laboratory for Antimicrobial Resistance (EURL-AR) network GPTs of 2021 and 2022, which included 25 EU national reference laboratories (NLRs). A total of 392 genomes from 12 AMR-bacteria were evaluated based on WGS QC metrics. Two percent ( = 9) of the data were excluded, due to contamination, and 11% ( = 41) of the remaining genomes were identified as outliers in at least one QC metric and excluded from computation of the adjusted QC thresholds (AQT). Two QC metric correlation groups were identified through linear regression. Eight percent ( = 28) of the submitted genomes, from 11 laboratories, failed one or more of the AQTs. However, only three laboratories (12%) were identified as underperformers, failing across AQTs for uncorrelated QC metrics in at least two genomes. Finally, new species-specific thresholds for "N50" and "number of contigs > 200 bp" are presented for guidance in routine laboratory QC. The continued participation of NRLs in GPTs will reveal WGS workflow flaws and improve AMR surveillance data. GPT data will continue to contribute to the development of reliable species-specific thresholds for routine WGS QC, standardizing sequencing data QC and ensure inter- and intranational laboratory comparability.IMPORTANCEIllumina next-generation sequencing is an integral part of antimicrobial resistance (AMR) surveillance and the most widely used whole-genome sequencing (WGS) platform. The high-throughput, relative low-cost, high discriminatory power, and rapid turnaround time of WGS compared to classical biochemical methods means the technology will likely remain a fundamental tool in AMR surveillance and public health. In this study, we present the current level of WGS capacity among national reference laboratories in the EU Reference Laboratory for AMR network, summarizing applied methodology and statistically evaluating the quality of the obtained sequence data. These findings provide the basis for setting new and revised thresholds for quality metrics used in routine WGS, which have previously been arbitrarily defined. In addition, underperforming participants are identified and encouraged to evaluate their workflows to produce reliable results.
随着抗生素耐药性（AMR）监测向基因组学转移，确保实验室之间产生的全基因组测序（WGS）数据的质量至关重要。参与基因组能力验证测试（GPT）不仅可以提高各个实验室的 WGS 能力，还为通过对不同分离株的重复重测序来提高 WGS 质量控制（QC）的特定物种阈值提供了独特的机会。在这里，我们展示了欧盟抗生素耐药性参考实验室（EURL-AR）网络 2021 年和 2022 年 GPT 的结果，其中包括 25 个欧盟国家参考实验室（NLR）。根据 WGS QC 指标，对来自 12 种 AMR 细菌的 392 个基因组进行了评估。由于污染，有 2%（=9）的数据被排除在外，其余 11%（=41）的基因组在至少一个 QC 指标中被确定为异常值，并被排除在调整后的 QC 阈值（AQT）计算之外。通过线性回归确定了两个 QC 度量相关组。在提交的基因组中，有 11 个实验室的 8%（=28）个不符合一个或多个 AQT。然而，只有三个实验室（12%）被确定为表现不佳，在至少两个基因组中，不相关的 QC 指标的 AQT 都未通过。最后，提出了用于常规实验室 QC 的“N50”和“>200bp 碱基对的碱基对数”的新的特定物种阈值。国家参考实验室继续参与 GPT 将揭示 WGS 工作流程中的缺陷并改善 AMR 监测数据。GPT 数据将继续为常规 WGS QC 的可靠特定物种阈值的制定做出贡献，从而标准化测序数据 QC，并确保实验室之间和国家之间的可比性。
重要性：Illumina 下一代测序是抗生素耐药性（AMR）监测的重要组成部分，也是最广泛使用的全基因组测序（WGS）平台。与传统生化方法相比，WGS 具有高通量、相对低成本、高区分能力和快速周转时间的特点，这意味着该技术仍将是 AMR 监测和公共卫生的基本工具。在这项研究中，我们展示了欧盟抗生素耐药性参考实验室网络中国家参考实验室的当前 WGS 能力水平，总结了应用方法，并从统计学上评估了获得的序列数据的质量。这些发现为设定常规 WGS 中使用的质量指标的新的和修订的阈值提供了基础，这些阈值以前是任意定义的。此外，确定了表现不佳的参与者，并鼓励他们评估其工作流程以产生可靠的结果。
