Pan-pathogen deep sequencing of nosocomial bacterial pathogens in Italy in spring 2020: a prospective cohort study

IF 20.9 1区 生物学 Q1 INFECTIOUS DISEASES
Harry A Thorpe PhD , Maiju Pesonen PhD , Marta Corbella MSc , Henri Pesonen DSc , Stefano Gaiarsa PhD , Christine J Boinett PhD , Gerry Tonkin-Hill PhD , Tommi Mäklin PhD , Anna K Pöntinen PhD , Neil MacAlasdair PhD , Rebecca A Gladstone PhD , Sergio Arredondo-Alonso PhD , Teemu Kallonen PhD , Dorota Jamrozy PhD , Stephanie W Lo PhD , Chrispin Chaguza PhD , Grace A Blackwell PhD , Prof Antti Honkela PhD , Anita C Schürch PhD , Prof Rob J L Willems , Prof Jukka Corander PhD
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引用次数: 0

Abstract

Background

Nosocomial infections pose a considerable risk to patients who are susceptible, and this is particularly acute in intensive care units when hospital-associated bacteria are endemic. During the first wave of the COVID-19 pandemic, the surge of patients presented a significant obstacle to the effectiveness of infection control measures. We aimed to assess the risks and extent of nosocomial pathogen transmission under a high patient burden by designing a novel bacterial pan-pathogen deep-sequencing approach that could be integrated with standard clinical surveillance and diagnostics workflows.

Methods

We did a prospective cohort study in a region of northern Italy that was severely affected by the first wave of the COVID-19 pandemic. Inpatients on both ordinary and intensive care unit (ICU) wards at the San Matteo hospital, Pavia were sampled on multiple occasions to identify bacterial pathogens from respiratory, nasal, and rectal samples. Diagnostic samples collected between April 7 and May 10, 2020 were cultured on six different selective media designed to enrich for Acinetobacter baumannii, Escherichia coli, Enterococcus faecium, Enterococcus faecalis, Klebsiella pneumoniae, Pseudomonas aeruginosa, Staphylococcus aureus, and Streptococcus pneumoniae, and DNA from each plate with positive growth was deep sequenced en masse. We used mSWEEP and mGEMS to bin sequencing reads by sequence cluster for each species, followed by mapping with snippy to generate high quality alignments. Antimicrobial resistance genes were detected by use of ARIBA and CARD. Estimates of hospital transmission were obtained from pairwise bacterial single nucleotide polymorphism distances, partitioned by within-patient and between-patient samples. Finally, we compared the accuracy of our binned Acinetobacter baumannii genomes with those obtained by single colony whole-genome sequencing of isolates from the same hospital.

Findings

We recruited patients from March 1 to May 7, 2020. The pathogen population among the patients was large and diverse, with 2148 species detections overall among the 2418 sequenced samples from the 256 patients. In total, 55 sequence clusters from key pathogen species were detected at least five times. The antimicrobial resistance gene prevalence was correspondingly high, with key carbapenemase and extended spectrum ß-lactamase genes detected in at least 50 (40%) of 125 patients in ICUs. Using high-resolution mapping to infer transmission, we established that hospital transmission was likely to be a significant mode of acquisition for each of the pathogen species. Finally, comparison with single colony Acinetobacter baumannii genomes showed that the resolution offered by deep sequencing was equivalent to single-colony sequencing, with the additional benefit of detection of co-colonisation of highly similar strains.

Interpretation

Our study shows that a culture-based deep-sequencing approach is a possible route towards improving future pathogen surveillance and infection control at hospitals. Future studies should be designed to directly compare the accuracy, cost, and feasibility of culture-based deep sequencing with single colony whole-genome sequencing on a range of bacterial species.

Funding

Wellcome Trust, European Research Council, Academy of Finland Flagship program, Trond Mohn Foundation, and Research Council of Norway.
2020 年春季意大利医院内细菌病原体的泛病原体深度测序:一项前瞻性队列研究。
背景:非医院感染对易感患者构成相当大的风险,尤其是在医院相关细菌流行的重症监护病房。在 COVID-19 大流行的第一波期间,病人激增严重阻碍了感染控制措施的有效性。我们设计了一种新型细菌泛病原体深度测序方法,并将其与标准临床监测和诊断工作流程相结合,旨在评估高病人负担下医院内病原体传播的风险和程度:我们在受 COVID-19 第一波大流行严重影响的意大利北部地区开展了一项前瞻性队列研究。我们对帕维亚圣马特奥医院普通病房和重症监护病房 (ICU) 的住院病人进行了多次采样,以确定呼吸道、鼻腔和直肠样本中的细菌病原体。2020 年 4 月 7 日至 5 月 10 日期间采集的诊断样本在六种不同的选择性培养基上进行了培养,这些培养基旨在富集鲍曼不动杆菌、大肠埃希菌、粪肠球菌、粪肠球菌、肺炎克雷伯菌、铜绿假单胞菌、金黄色葡萄球菌和肺炎链球菌,并对每个阳性生长平板的 DNA 进行了集体深度测序。我们使用 mSWEEP 和 mGEMS 按序列群对每个物种的测序读数进行分类,然后用 snippy 进行映射,生成高质量的比对结果。使用 ARIBA 和 CARD 检测抗菌药耐药性基因。根据细菌单核苷酸多态性配对距离,按患者内和患者间样本划分,得出医院传播的估计值。最后,我们比较了鲍曼不动杆菌基因组与同一医院分离菌株的单菌落全基因组测序结果的准确性:我们从 2020 年 3 月 1 日至 5 月 7 日招募了患者。患者中的病原体数量庞大且种类繁多,在 256 名患者的 2418 份测序样本中,共检测到 2148 个物种。共有 55 个关键病原体物种的序列群至少被检测到 5 次。抗菌素耐药基因的流行率也相应较高,在重症监护室的125名患者中,至少有50人(40%)检测到了关键的碳青霉烯酶和广谱ß-内酰胺酶基因。利用高分辨率图谱推断传播途径,我们确定医院传播可能是每种病原体的重要获取方式。最后,与单菌落鲍曼不动杆菌基因组的比较表明,深度测序的分辨率与单菌落测序相当,而且还能检测到高度相似菌株的共定植:我们的研究表明,基于培养的深度测序方法是改善未来病原体监测和医院感染控制的一条可行途径。未来的研究应直接比较基于培养基的深度测序与单菌落全基因组测序在一系列细菌物种上的准确性、成本和可行性:惠康信托基金会、欧洲研究理事会、芬兰科学院旗舰项目、特隆德-莫恩基金会和挪威研究理事会。
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
Lancet Microbe
Lancet Microbe Multiple-
CiteScore
27.20
自引率
0.80%
发文量
278
审稿时长
6 weeks
期刊介绍: The Lancet Microbe is a gold open access journal committed to publishing content relevant to clinical microbiologists worldwide, with a focus on studies that advance clinical understanding, challenge the status quo, and advocate change in health policy.
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