Summary
Background
Microbial contamination of aerosol facemasks could be a source of nosocomial infections
during nebulization therapy in hospital, prompting efforts to identify these contaminants.
Identification of micro-organisms in medical devices has traditionally relied on culture-dependent
methods, which are incapable of detecting the majority of these microbial contaminants.
This challenge could be overcome with culture-independent sequencing-based techniques
that are suited for the profiling of complex microbiomes.
Aim
To characterize the microbial contaminants in aerosol facemasks used for nebulization
therapy, and identify factors influencing the composition of these microbial contaminants
with the acquisition and analysis of comprehensive microbiome-scale profiles using
culture-independent high-throughput sequencing.
Methods
Used aerosol facemasks collected from hospitalized patients were analysed with culture-independent
16S rRNA gene-based amplicon sequencing to acquire microbiome-scale comprehensive
profiles of the microbial contaminants. Microbiome-based analysis was performed to
identify potential sources of microbial contamination in facemasks.
Findings
Culture-independent high-throughput sequencing was demonstrated for the capacity to
acquire microbiome-scale profiles of microbial contaminants on aerosol facemasks.
Microbial source identification enabled by the microbiome-scale profiles linked microbial
contamination on aerosol facemasks to the human skin and oral microbiota. Antibiotic
treatment with levofloxacin was found to reduce contamination of the facemasks by
oral microbiota.
Conclusion
Sequencing-based microbiome-scale analysis is capable of providing comprehensive characterization
of microbial contamination in aerosol facemasks. Insight gained from microbiome-scale
analysis facilitates the development of effective strategies for the prevention and
mitigation of the risk of nosocomial infections arising from exposure to microbial
contamination of aerosol facemasks, such as targeted elimination of potential sources
of contamination.
Keywords
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Article info
Publication history
Published online: January 20, 2023
Accepted:
January 17,
2023
Received:
October 10,
2022
Identification
Copyright
© 2023 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.
