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.