Microbiome Profiles of Nebulizers in Hospital Use
Microbiome Profiles of Nebulizers in Hospital Use
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医院使用的雾化器的微生物组概况
DOI：
10.1089/jamp.2021.0032
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发表时间：
2022
影响因子：
3.4
通讯作者：
He, Qiang
中科院分区：
文献类型：
--
作者：
Swanson, Clifford S.;Dhand, Rajiv;Cao, Liu;Ferris, Jennifer;Elder, C. Scott;He, Qiang
背景：雾化器用于为呼吸系统患者提供治疗。由于对受污染的雾化器造成医院感染风险的担忧，迫切需要识别患者使用的雾化器中的所有微生物种群。然而，传统的依赖于培养的技术不足以仅识别特定的微生物种群。因此，本研究的目的是通过不依赖于培养的高通量测序来获取住院患者使用的雾化器中微生物组的完整概况，并确定微生物污染物的来源，以制定有效的做法来减少雾化器设备中的微生物污染。方法：本研究是在田纳西州诺克斯维尔的田纳西大学医学中心进行的。雾化器是在 2018 年 5 月至 2018 年 10 月期间从因肺炎或慢性阻塞性肺病恶化而入住的住院患者中收集的。对雾化器进行采样，进行基于 16S rRNA 基因的扩增子测序，以分析雾化器微生物组并进行系统发育分析。采用贝叶斯群落范围内的独立于培养物的微生物源追踪技术来量化与人类相关的微生物群作为雾化器污染潜在来源的贡献。结果：独立于培养物的测序检测到雾化器中存在多种微生物种群，以 18 个丰富的属为代表。寡养单胞菌被确定为最丰富的属，占雾化器微生物组的 12.4%，其次是由根瘤菌、葡萄球菌、链球菌和拉尔斯顿菌组成。系统发育分析揭示了与潜在病原体密切相关的多种系统发育型的存在。与人类相关的微生物群对雾化器微生物群的贡献高达 15%，但并未被确定为雾化器污染的主要来源。结论：独立于培养的测序被证明能够获取住院患者使用的雾化器中微生物群的全面概况。系统发育分析确定了密切相关的系统发育型之间的致病性差异。支持微生物组概况的社区范围内独立于培养物的微生物源追踪表明，作为雾化器微生物组的贡献者，环境源比人类源更重要，这为制定有效的雾化器设备监测和控制策略以减轻医院感染风险提供了重要的见解。
Background:Nebulizers are used to provide treatment to respiratory patients. Concerns over nosocomial infection risks from contaminated nebulizers raise the critical need to identify all microbial populations in nebulizers used by patients. However, conventional culture-dependent techniques are inadequate with the ability to identify specific microbial populations only. Therefore, the aims of this study were to acquire complete profiles of microbiomes in nebulizers used by in-patients with culture-independent high-throughput sequencing and identify sources of microbial contaminants for the development of effective practices to reduce microbial contamination in nebulizer devices.Methods:This study was conducted at the University of Tennessee Medical Center in Knoxville, TN. Nebulizers were collected between May 2018 and October 2018 from inpatients admitted to the floors for pneumonia or chronic obstructive pulmonary disease exacerbations. Nebulizers were sampled for 16S rRNA gene-based amplicon sequencing to profile nebulizer microbiomes and perform phylogenetic analysis. A Bayesian community-wide culture-independent microbial source tracking technique was used to quantify the contribution of human-associated microbiota as potential sources of nebulizer contamination.Results:Culture-independent sequencing detected diverse microbial populations in nebulizers, represented by 18 abundant genera.Stenotrophomonaswas identified as the most abundant genus, accounting for 12.4% of the nebulizer microbiome, followed byRhizobium,Staphylococcus,Streptococcus, andRalstonia. Phylogenetic analysis revealed the presence of multiple phylotypes with close relationship to potential pathogens. Contributing up to 15% to nebulizer microbiomes, human-associated microbiota was not identified as the primary sources of nebulizer contamination.Conclusion:Culture-independent sequencing was demonstrated to be capable of acquiring comprehensive profiles of microbiomes in nebulizers used by in-patients. Phylogenetic analysis identified differences in pathogenicity between closely related phylotypes. Microbiome profile-enabled community-wide culture-independent microbial source tracking suggested greater importance of environmental sources than human sources as contributors to nebulizer microbiomes, providing important insight for the development of effective strategies for the monitoring and control of nebulizer devices to mitigate infection risks in the hospital.