早期识别一个病房的Clostridioides difficile的疫情使用潜在的多部位序列类型基于牛津纳米孔基因组监测
Max Bloomfield1,2, Samantha Hutton1, Megan Burton1
1Awanui Labs Wellington, Department of Microbiology and Molecular Pathology, Wellington, New Zealand.
Infection control and hospital epidemiology
|May 6, 2024
概括
使用牛津纳米孔技术的基因组监测发现了一个Clostridioides difficile (CDI) 爆发. 该系统在血液瘤病房中检测出序列2型CDI病例,使得有针对性的干预措施成为可能.
科学领域:
- 传染病流行病学 传染病流行病学
- 基因组监测是指基因组的监测.
- 微生物基因组学 微生物基因组学
背景情况:
- 困难菌感染 (CDI) 构成了医疗保健方面的重大挑战.
- 传统的监测方法可能无法有效地检测局部疫情.
- 新兴的基因组技术为实时病原体跟踪提供了新的可能性.
研究的目的:
- 描述一个Clostridioides困难感染 (CDI) 疫情.
- 通过牛津纳米孔技术 (ONT) 和多位置序列类型 (MLST) 评估潜在的基因组监测系统.
- 为了确定疫情中涉及的特定序列类型 (ST).
主要方法:
- 来自使用ONT MinION的住院患者的所有C. difficile分离物的未来测序.
- 实时生成MLST的个人资料.
- 使用床位移动数据构建ST特异性发病率图.
- 对疫情相关病例的回顾性遗传学分析.
主要成果:
- 在2022年2月至10月期间,118个CDI病例中有76个 (64.4%) 被测序.
- 在血液瘤病房暴露的患者中发现ST2 CDI病例的占主导地位.
- 十个ST2CDI病例与血液瘤病房有关.
- 在全医院范围内没有检测到CDI发病率的总体增加.
- 遗传学分析证实了疫情病例的聚类,但不包括两例.
- 干预措施,包括清洁产品的改变,导致新的ST2病例停止.
结论:
- 用ONT测序进行前性基因组监测成功发现了未被检测到的ST2 CDI爆发.
- 基于MLST的系统使得疫情的快速检测和描述成为可能.
- 基因组监测是控制医疗保健相关感染的宝贵工具.
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