Jinadatha Chetan, Choi Hosoon, Dhar Sorabh, Kaye Keith S, Hwang Munok, Xu Jing, Navarathna Thanuri, Coppin John David, Chatterjee Piyali
Department of Medicine, Central Texas Veterans Health Care System, Temple, TX, USA.
Department of Research, Central Texas Veterans Health Care System, Temple, TX, USA.
Antimicrob Steward Healthc Epidemiol. 2025 Aug 8;5(1):e173. doi: 10.1017/ash.2025.10092. eCollection 2025.
is known to cause global outbreaks and routine surveillance to prevent nosocomial transmission has historically been limited. A longitudinal surveillance study of isolates using whole genome sequencing (WGS) and whole genome multilocus sequence typing (wgMLST) was performed to map the distribution of sequence types (STs) and intrahospital transmission.
All clinical isolates were collected in two hospitals (H1, H2) from fifteen units between 2017 and 2021 in Southeast Michigan and analyzed. The isolates were subjected to WGS using the NextSeq instrument (Illumina). The contigs were assembled using SPAdes (v3.7.1) and wgMLST analysis was performed using BioNumerics software v7.6. Minimum spanning tree (MST) and dendrograms were created to map distribution of STs and putative transmissions.
ST2 was the most prevalent in both hospitals (H1:47.2% and H2:59.7%), followed by ST406 (H1:11.1%, H2:8%). ST15 (H1:9.7%) was only found in H1. Transmission was mapped for ST2, ST406 (H1, H2), and ST15 for H1 and mainly located in the ICU settings.
Presence of several STs (ST2, ST406, and ST15) prevalent from both hospitals suggest that these are common circulating strains in the area. Sporadic transmission events mainly in the ICU settings in both hospitals (H1 and H2) were noted indicating attention to enhanced infection prevention and control measures. Given that r infections are predominantly hospital acquired, an effective surveillance plan incorporating WGS and wgMLST may improve the ability to identify and track trends rapidly, implement effective infection control intervention, and reduce healthcare-associated infections (HAIs).
已知会引发全球疫情,而以往用于预防医院内传播的常规监测一直很有限。开展了一项对分离株的纵向监测研究,采用全基因组测序(WGS)和全基因组多位点序列分型(wgMLST)来绘制序列类型(STs)的分布及医院内传播情况。
2017年至2021年期间,从密歇根州东南部的两家医院(H1、H2)的15个科室收集了所有临床分离株并进行分析。使用NextSeq仪器(Illumina)对分离株进行WGS。使用SPAdes(v3.7.1)组装重叠群,并使用BioNumerics软件v7.6进行wgMLST分析。创建最小生成树(MST)和树状图以绘制STs的分布及推定传播情况。
ST2在两家医院中最为常见(H1:47.2%,H2:59.7%),其次是ST406(H1:11.1%,H2:8%)。ST15(H1:9.7%)仅在H1中发现。绘制了ST2、ST406(H1、H2)以及H1的ST15的传播情况,且主要位于重症监护病房。
两家医院中均存在几种常见的STs(ST2、ST406和ST15),表明这些是该地区常见的流行菌株。注意到两家医院(H1和H2)主要在重症监护病房发生了散发传播事件,这表明需要加强感染预防和控制措施。鉴于感染主要是医院获得性的,纳入WGS和wgMLST的有效监测计划可能会提高快速识别和跟踪趋势、实施有效的感染控制干预以及减少医疗相关感染(HAIs)的能力。