Application of 16S rRNA metagenomics to analyze bacterial communities at a respiratory care centre in Taiwan View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2015-03

AUTHORS

Chuan Yi Tang, Siu-Ming Yiu, Han-Yueh Kuo, Te-Sheng Tan, Ki-Hok Liao, Chih-Chin Liu, Wing-Kai Hon, Ming-Li Liou

ABSTRACT

In this study, we applied a 16S ribosomal RNA (rRNA) metagenomics approach to survey inanimate hospital environments (IHEs) in a respiratory care center (RCC). A total of 16 samples, including 9 from medical devices and 7 from workstations, were analyzed. Besides, clinical isolates were retrospectively analyzed during the sampling period in the RCC. A high amount of microbial diversity was detected, with an average of 1,836 phylotypes per sample. In addition to Acinetobacter, more than 60 % of the bacterial communities present among the top 25 abundant genera were dominated by skin-associated bacteria. Differences in bacterial profiles were restricted to individual samples. Furthermore, compliance with hand hygiene guidelines may be unsatisfactory among hospital staff according to a principal coordinate analysis that indicated clustering of bacterial communities between devices and workstations for most of the sampling sites. Compared to the high incidence of clinical isolates in the RCC, only Staphylococcus and Acinetobacter were highly abundant in the IHEs. Despite Acinetobacter was the most abundant genus present in IHEs of the RCC, potential pathogens, e.g., Acinetobacter baumannii, might remain susceptible to carbapenem. This study is the first in Taiwan to demonstrate a high diversity of human-associated bacteria in the RCC via 16S rRNA metagenomics, which allows for new assessment of potential health risks in RCCs, aids in the evaluation of existing sanitation protocols, and furthers our understanding of the development of healthcare-associated infections. More... »

PAGES

2871-2881

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00253-014-6176-7

DOI

http://dx.doi.org/10.1007/s00253-014-6176-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1020816336

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/25359480


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