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采用多重杂交捕获目标富集技术,高灵敏度检测医院废水中的抗生素耐药基因。

Highly sensitive detection of antimicrobial resistance genes in hospital wastewater using the multiplex hybrid capture target enrichment.

机构信息

Department of Infectious Diseases, Internal Medicine, Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan.

Pathogen Genomics Center, National Institute of Infectious Diseases, Tokyo, Japan.

出版信息

mSphere. 2023 Aug 24;8(4):e0010023. doi: 10.1128/msphere.00100-23. Epub 2023 May 24.

Abstract

Wastewater can be useful in monitoring the spread of antimicrobial resistance (AMR) within a hospital. The abundance of antibiotic resistance genes (ARGs) in hospital effluent was assessed using metagenomic sequencing (mDNA-seq) and hybrid capture (xHYB). mDNA-seq analysis and subsequent xHYB targeted enrichment were conducted on two effluent samples per month from November 2018 to May 2021. Reads per kilobase per million (RPKM) values were calculated for all 1,272 ARGs in the constructed database. The monthly numbers of patients with presumed extended-spectrum β-lactamase (ESBL)-producing and metallo-β-lactamase (MBL)-producing bacteria, methicillin-resistant (MRSA), and vancomycin-resistant enterococci (VRE) were compared with the monthly RPKM values of , , , , and by xHYB. The average RPKM value for all ARGs detected by xHYB was significantly higher than that of mDNA-seq (665, 225, and 328, respectively, and < 0.05). The average number of patients with ESBL producers and RPKM values of genes in 2020 were significantly higher than that in 2019 (17 and 13 patients per month and 921 vs 232 per month, respectively, both < 0.05). The average numbers of patients with MBL-producers, MRSA, and VRE were 1, 28, and 0 per month, respectively, while the average RPKM values of , , , and were 6,163, 6, 0, and 126 per month, respectively. Monitoring ARGs in hospital effluent using xHYB was found to be more useful than conventional mDNA-seq in detecting ARGs including , and , which are important for infection control.IMPORTANCEEnvironmental ARGs play a crucial role in the emergence and spread of AMR that constitutes a significant global health threat. One major source of ARGs is effluent from healthcare facilities, where patients are frequently administered antimicrobials. Culture-independent methods, including metagenomics, can detect environmental ARGs carried by non-culturable bacteria and extracellular ARGs. mDNA-seq is one of the most comprehensive methods for environmental ARG surveillance; however, its sensitivity is insufficient for wastewater surveillance. This study demonstrates that xHYB appropriately monitors ARGs in hospital effluent for sensitive identification of nosocomial AMR dissemination. Correlations were observed between the numbers of inpatients with antibiotic-resistant bacteria and the ARG RPKM values in hospital effluent over time. ARG surveillance in hospital effluent using the highly sensitive and specific xHYB method could improve our understanding of the emergence and spread of AMR within a hospital.

摘要

污水在监测医院内抗生素耐药性(AMR)的传播方面具有重要作用。本研究采用宏基因组测序(mDNA-seq)和杂交捕获(xHYB)技术评估医院污水中抗生素耐药基因(ARGs)的丰度。从 2018 年 11 月至 2021 年 5 月,每月采集两份污水样本进行 mDNA-seq 分析和随后的 xHYB 靶向富集。对构建的数据库中的 1272 个 ARGs 进行计算每个碱基每百万读数(RPKM)值。通过 xHYB 比较每月推定产超广谱β-内酰胺酶(ESBL)和产金属β-内酰胺酶(MBL)的细菌、耐甲氧西林金黄色葡萄球菌(MRSA)和耐万古霉素肠球菌(VRE)的患者数量与 、 、 、 和 的每月 RPKM 值。通过 xHYB 检测到的所有 ARGs 的平均 RPKM 值明显高于 mDNA-seq(分别为 665、225 和 328,均 < 0.05)。2020 年每月 ESBL 产生者和 基因的 RPKM 值明显高于 2019 年(每月分别为 17 名和 13 名患者和 921 名与 232 名患者,均 < 0.05)。MBL 产生者、MRSA 和 VRE 的患者人数分别为每月 1 名、28 名和 0 名,而 、 、 、 的平均 RPKM 值分别为每月 6163、6、0 和 126。使用 xHYB 监测医院污水中的 ARGs 比传统的 mDNA-seq 更能检测到 、 和 等重要的 ARGs,这些基因对抗感染控制至关重要。

重要性:环境 ARGs 在构成重大全球健康威胁的抗生素耐药性(AMR)的出现和传播中发挥着关键作用。ARGs 的一个主要来源是医疗机构的污水,因为患者经常接受抗生素治疗。包括宏基因组学在内的无培养方法可以检测到非培养细菌携带的环境 ARGs 和细胞外 ARGs。mDNA-seq 是用于环境 ARG 监测的最全面的方法之一;然而,其灵敏度不足以进行废水监测。本研究表明,xHYB 可适当监测医院污水中的 ARGs,以敏感识别医院内 AMR 的传播。随着时间的推移,观察到住院患者中具有抗生素耐药性的细菌数量与医院污水中 ARG 的 RPKM 值之间存在相关性。使用高度敏感和特异的 xHYB 方法监测医院污水中的 ARG 可能会提高我们对医院内 AMR 出现和传播的理解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7035/10449491/ed16443779b1/msphere.00100-23.f001.jpg

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