Whole-genome sequencing for antimicrobial surveillance: species-specific quality thresholds and data evaluation from the network of the European Union Reference Laboratory for Antimicrobial Resistance genomic proficiency tests of 2021 and 2022.

IF 5 2区 生物学 Q1 MICROBIOLOGY
mSystems Pub Date : 2024-09-17 Epub Date: 2024-08-06 DOI:10.1128/msystems.00160-24
Lauge Holm Sørensen, Susanne Karlsmose Pedersen, Jacob Dyring Jensen, Niamh Lacy-Roberts, Athina Andrea, Michael S M Brouwer, Kees T Veldman, Yan Lou, Maria Hoffmann, Rene S Hendriksen
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引用次数: 0

Abstract

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 (n = 9) of the data were excluded, due to contamination, and 11% (n = 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 (n = 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.

用于抗菌素监测的全基因组测序:2021 年和 2022 年欧盟抗菌素耐药性参考实验室基因组能力测试网络的特定物种质量阈值和数据评估。
随着抗菌药耐药性 (AMR) 监控向基因组学转变,确保各实验室生成的全基因组测序 (WGS) 数据的质量至关重要。参加基因组能力测试(GPT)不仅能提高单个实验室的 WGS 能力,还能提供一个独特的机会,通过反复对不同的分离物进行重新测序来提高 WGS 质量控制(QC)的物种特异性阈值。在此,我们介绍了欧盟抗菌药物耐药性参考实验室(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 细菌的共 392 个基因组进行了评估。由于污染,2%(n = 9)的数据被排除在外,其余基因组中的 11%(n = 41)在至少一个 QC 指标中被确定为异常值,并在计算调整后的 QC 阈值 (AQT) 时被排除在外。通过线性回归确定了两个 QC 指标相关组。11个实验室提交的基因组中有8%(n = 28)未能通过一个或多个AQT。不过,只有 3 个实验室(12%)被认定为表现不佳,至少有两个基因组的非相关 QC 指标在所有 AQTs 中均不合格。最后,提出了 "N50 "和 "等位基因数 > 200 bp "的新物种特定阈值,以指导实验室的常规质量控制。NRL 继续参与 GPT 将揭示 WGS 工作流程的缺陷并改进 AMR 监测数据。GPT 数据将继续促进为 WGS 常规质控制定可靠的物种特异性阈值,使测序数据质控标准化,并确保实验室间和实验室内的可比性。重要意义Illumina 下一代测序是抗菌素耐药性 (AMR) 监控不可或缺的一部分,也是应用最广泛的全基因组测序 (WGS) 平台。与传统的生化方法相比,WGS 具有高通量、相对低成本、高分辨力和快速周转时间等特点,这意味着该技术很可能继续成为 AMR 监测和公共卫生的基本工具。在本研究中,我们介绍了欧盟 AMR 参考实验室网络中各国参考实验室目前的 WGS 能力水平,总结了应用方法并对所获序列数据的质量进行了统计评估。这些发现为设定常规 WGS 质量指标的新阈值和修订阈值提供了依据,而这些阈值以前都是任意定义的。此外,还发现了表现不佳的参与者,并鼓励他们评估自己的工作流程,以产生可靠的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
mSystems
mSystems Biochemistry, Genetics and Molecular Biology-Biochemistry
CiteScore
10.50
自引率
3.10%
发文量
308
审稿时长
13 weeks
期刊介绍: mSystems™ will publish preeminent work that stems from applying technologies for high-throughput analyses to achieve insights into the metabolic and regulatory systems at the scale of both the single cell and microbial communities. The scope of mSystems™ encompasses all important biological and biochemical findings drawn from analyses of large data sets, as well as new computational approaches for deriving these insights. mSystems™ will welcome submissions from researchers who focus on the microbiome, genomics, metagenomics, transcriptomics, metabolomics, proteomics, glycomics, bioinformatics, and computational microbiology. mSystems™ will provide streamlined decisions, while carrying on ASM''s tradition of rigorous peer review.
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