基于长线程测序的耐多药生物基因组监控。

IF 10.4 1区 生物学 Q1 GENETICS & HEREDITY
Fabian Landman, Casper Jamin, Angela de Haan, Sandra Witteveen, Jeroen Bos, Han G J van der Heide, Leo M Schouls, Antoni P A Hendrickx
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引用次数: 0

摘要

背景:耐多药生物(MDRO)对全球公共卫生构成重大威胁。识别抗菌药耐药性决定因素、评估分子类型变化和检测传播的能力对于监测和预防 MDRO 感染至关重要。基于长读程测序的分子特征描述已成为短读程测序的一种有前途的替代方法。本研究的目的是仅根据长读程测序来描述 MDRO 的特征,以便进行监测和传播研究:方法:使用 Maxwell-RSC48 自动提取了 356 个 MDRO 的基因组 DNA。MDRO 包括 106 个肺炎克雷伯菌分离株、85 个大肠埃希菌、15 个复合泄殖腔肠杆菌、10 个弗氏柠檬杆菌、34 个铜绿假单胞菌、16 个鲍曼不动杆菌和 69 个耐甲氧西林金黄色葡萄球菌(MRSA),其中 24 个来自疫情爆发。MDRO 的测序采用短线程(Illumina NextSeq 550)和长线程(Nanopore Rapid Barcoding Kit-24-V14, R10.4.1)全基因组测序(WGS)。使用 Dorado-0.3.2 双工模式对两种不同的模型进行了基线定位。使用 Flye、Canu、Miniasm、Unicycler、Necat、Raven 和 Redbean 组装器组装长读数数据。覆盖率大于 40 × 的长线程 WGS 数据被用于多焦点序列分型(MLST)、全基因组 MLST(wgMLST)、全基因组单核苷酸多态性(wgSNP)、MRSA 的硅学多位点可变串联重复数分析(iMLVA)和抗性基因鉴定(ABRicate):结果:比较基于长读数和短读数 WGS 数据的 wgMLST 图谱发现,除铜绿假单胞菌外,超过 95% 的 wgMLST 图谱在物种特异性聚类截断范围内。对于肺炎克氏菌、大肠杆菌、泄殖腔大肠杆菌复合体、弗氏酵母菌、鲍曼酵母菌复合体和 MRSA,长读取 WGS 和短读取 WGS 所获得的 wgMLST 图谱只有一到九个 wgMLST 等位基因或 SNPs 的差异。对于铜绿假单胞菌,长读取 wgMLST 等位基因与短读取 wgMLST 等位基因的差异高达 27 个,SNPs 为 0-10 个。长读取和短读取 WGS 数据与传统 MLVA 分型之间的 MLST 序列类型和 iMLVA 类型一致。长线程测序数据检测到的抗菌药耐药基因具有很高的灵敏度/特异性(92%-100%/99%-100%)。长读数测序能够对 MRSA 疫情进行分析:我们证明,与短线程测序相比,自动提取 DNA 后进行长线程测序的分子特征描述同样准确,适合作为 MDRO 基因组监测的一部分进行分型和疫情分析。不过,铜绿假单胞菌的分析还需要进一步改进,这可以通过其他基数调用算法来实现。MDRO 长读程测序的实施成本低、文库制备快,因此适用于全球资源有限的环境和低收入国家。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Genomic surveillance of multidrug-resistant organisms based on long-read sequencing.

Background: Multidrug-resistant organisms (MDRO) pose a significant threat to public health worldwide. The ability to identify antimicrobial resistance determinants, to assess changes in molecular types, and to detect transmission are essential for surveillance and infection prevention of MDRO. Molecular characterization based on long-read sequencing has emerged as a promising alternative to short-read sequencing. The aim of this study was to characterize MDRO for surveillance and transmission studies based on long-read sequencing only.

Methods: Genomic DNA of 356 MDRO was automatically extracted using the Maxwell-RSC48. The MDRO included 106 Klebsiella pneumoniae isolates, 85 Escherichia coli, 15 Enterobacter cloacae complex, 10 Citrobacter freundii, 34 Pseudomonas aeruginosa, 16 Acinetobacter baumannii, and 69 methicillin-resistant Staphylococcus aureus (MRSA), of which 24 were from an outbreak. MDRO were sequenced using both short-read (Illumina NextSeq 550) and long-read (Nanopore Rapid Barcoding Kit-24-V14, R10.4.1) whole-genome sequencing (WGS). Basecalling was performed for two distinct models using Dorado-0.3.2 duplex mode. Long-read data was assembled using Flye, Canu, Miniasm, Unicycler, Necat, Raven, and Redbean assemblers. Long-read WGS data with > 40 × coverage was used for multi-locus sequence typing (MLST), whole-genome MLST (wgMLST), whole-genome single-nucleotide polymorphisms (wgSNP), in silico multiple locus variable-number of tandem repeat analysis (iMLVA) for MRSA, and identification of resistance genes (ABRicate).

Results: Comparison of wgMLST profiles based on long-read and short-read WGS data revealed > 95% of wgMLST profiles within the species-specific cluster cut-off, except for P. aeruginosa. The wgMLST profiles obtained by long-read and short-read WGS differed only one to nine wgMLST alleles or SNPs for K. pneumoniae, E. coli, E. cloacae complex, C. freundii, A. baumannii complex, and MRSA. For P. aeruginosa, differences were up to 27 wgMLST alleles between long-read and short-read wgMLST and 0-10 SNPs. MLST sequence types and iMLVA types were concordant between long-read and short-read WGS data and conventional MLVA typing. Antimicrobial resistance genes were detected in long-read sequencing data with high sensitivity/specificity (92-100%/99-100%). Long-read sequencing enabled analysis of an MRSA outbreak.

Conclusions: We demonstrate that molecular characterization of automatically extracted DNA followed by long-read sequencing is as accurate compared to short-read sequencing and suitable for typing and outbreak analysis as part of genomic surveillance of MDRO. However, the analysis of P. aeruginosa requires further improvement which may be obtained by other basecalling algorithms. The low implementation costs and rapid library preparation for long-read sequencing of MDRO extends its applicability to resource-constrained settings and low-income countries worldwide.

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来源期刊
Genome Medicine
Genome Medicine GENETICS & HEREDITY-
CiteScore
20.80
自引率
0.80%
发文量
128
审稿时长
6-12 weeks
期刊介绍: Genome Medicine is an open access journal that publishes outstanding research applying genetics, genomics, and multi-omics to understand, diagnose, and treat disease. Bridging basic science and clinical research, it covers areas such as cancer genomics, immuno-oncology, immunogenomics, infectious disease, microbiome, neurogenomics, systems medicine, clinical genomics, gene therapies, precision medicine, and clinical trials. The journal publishes original research, methods, software, and reviews to serve authors and promote broad interest and importance in the field.
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