Characterization of the Airborne Microbiome in Different Indoor and Outdoor Locations of a University Building Using an Innovative Compositional Data Analysis Approach

Abstract

In this work, we investigated the structure of the airborne bacterial community obtained by 16S rRNA gene sequencing performed on aerosol samples from different indoor and outdoor locations. The 48-h aerosol samples were collected in two laboratories, in the corridors, and on the roof of the Mathematics and Physics Department of the University of Salento (Italy). The investigation was carried out through the application of an innovative compositional data analysis approach, mainly based on a centered log-ratio transformation as a standardization procedure, the Aitchison distance for data ordination, and the principal component analysis via singular value decomposition for data clustering. This methodology allowed us to explore the main relationships among samples, identifying different results between indoor and outdoor samples both at the genus level and at the species level. Bacillus and Pseudomonas represented the most abundant genera identified in the analyzed samples. Out of the 21 identified bacterial species with the highest abundances in the collected aerosol samples, Acinetobacter lwoffii, Propionibacterium acnes, Diplorickettsia massiliensis, and Corynebacterium tuberculostearicum were the only four commonly classified as human opportunistic pathogens. Among the genera mostly associated with indoor environments, Hymenobacter and Arthrobacter could be noted as including many species that are unique in being radiation resistant.

Keywords

• compositional data
• airborne microbiome
• indoor aerosols
• particulate matter
• metagenomics approach
• 16S rRNA gene sequencing