利用新一代测序技术监测医院室内不可培养的致病细菌

Nor Husna Mat Hussin , Darren Dean Tay , Ummu Afeera Zainulabid , Mohd Norhafsam Maghpor , Hajar Fauzan Ahmad
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摘要

在 COVID-19 大流行的背景下,医院室内空气微生物群(一种多样化的微生物)的重要性日益凸显。人们对这一问题的进一步认识凸显了其对患者和员工健康的影响。由于长期暴露于室内,人们对室内空气质量风险的担忧持续存在,因此有必要对医院环境中的特定威胁进行进一步研究。在这项研究中,我们采用了一种基于独立培养的方法来分析医院环境中存在的核心微生物群基线,利用下一代测序技术的扩增子测序,以 16S rRNA 基因的 V3 区域为目标。从病房和门诊分离出的主要细菌门为固着菌门、变形菌门和放线菌门,它们的丰度依次不同;固着菌门在门诊中较多,放线菌门在病房中较多。门诊区主要是 Niallia taxi、Methyloversatilis universalis、未分类的 Rummeliibacillus、未分类的 Clostridium 和未分类的 Sphingomonadaceae 细菌,而病房区报告的前五大特征是 Pseudonocardia bannensis、Rubrobacter aplysinae、未分类的 Brachybacterium、未分类的 Bradyrhizobium 和未分类的 Mycobacterium。虽然α-多样性指数没有显示出显著差异,但β-多样性分析表明诊所和病房区域之间存在显著差异(p<0.05)。在所有样本中还发现了与机会性病原体和正常皮肤菌群相关的某些细菌种类,如甲基分支杆菌属、切割杆菌属、未分类的鞘氨单胞菌科和 Anoxybacillus B 菌属。本研究中描述的方法旨在建立一种快速、灵敏的筛查程序,该程序可用于医疗环境中的疾病监测,揭示医院微生物组对人类疾病的潜在影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Harnessing next-generation sequencing to monitor unculturable pathogenic bacteria in the indoor hospital building

The hospital indoor air microbiome, a diverse range of microorganisms, gains prominence amid the COVID-19 pandemic. Elevated awareness underscores implications for patient and staff well-being. Concerns about risks to indoor air quality persist due to prolonged indoor exposure, necessitating further research on specific threats within the hospital environment. In this study, an independent culture-based approach was used to analyze the baseline core microbiome present in hospital environments, utilizing amplicon sequencing on the next-generation sequencing technology to target the V3 region of the 16S rRNA gene. Firmicutes, Proteobacteria, and Actinobacteria were the main bacterial phyla that were most isolated from the wards and clinics with different orders of abundance; Firmicutes being associated more in clinics and Actinobacteriota in wards. The bacteria Niallia taxi, Methyloversatilis universalis, unclassified Rummeliibacillus, unclassified Clostridium, and unclassified Sphingomonadaceae dominated the clinic area while ward areas reported Pseudonocardia bannensis, Rubrobacter aplysinae, unclassified Brachybacterium, unclassified Bradyrhizobium, and unclassified Mycobacterium to be the top five features. While the alpha-diversity index showed no significant differences, the beta-diversity analysis showed a significant difference between clinic and ward areas (p<0.05). Certain bacterial species associated with opportunistic pathogens as well as normal skin flora such as Methylobacterium spp., Cutibacterium spp., unclassified Sphingomonadaceae, and Anoxybacillus B spp., were also identified across all samples. The methods described in this research aim to establish a rapid and sensitive screening process that could be valuable for disease surveillance within the healthcare setting, shedding light on the potential impacts of the hospital microbiome on human illness.

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