Ventilation-Associated Particulate Matter Is a Potential Reservoir of Multidrug-Resistant Organisms in Health Facilities

Simultaneous monitoring of SARS-CoV-2 and bacterial profiles from the air of hospital environments with COVID-19-affected patients

The SARS-CoV-2 presence and the bacterial community profile in air samples collected at the Intensive Care Unit (ICU) of the Operational Unit of Infectious Diseases of Santa Caterina Novella Hospital in Galatina (Lecce, Italy) have been evaluated in this study. Air samplings were performed in different rooms of the ICU ward with and without COVID-19 patients. No sample was found positive to SARS-CoV-2, according to Allplex 2019-nCoV Assay. The airborne bacterial community profiles determined by the 16S rRNA gene metabarcoding approach up to the species level were characterized by richness and biodiversity indices, Spearman correlation coefficients, and Principal Coordinate Analysis. Pathogenic and non-pathogenic bacterial species, also detected in outdoor air samples, were found in all collected indoor samples. Staphylococcus pettenkoferi, Corynebacterium tuberculostearicum, and others coagulase-negative staphylococci, detected at high relative abundances in all the patients' rooms, were the most abundant pathogenic species. The highest mean relative abundance of S. pettenkoferi and C. tuberculostearicum suggested that they were likely the main pathogens of COVID-19 patients at the ICU ward of this study. The identification of nosocomial pathogens representing potential patients' risks in ICU COVID-19 rooms and the still controversial airborne transmission of the SARS-CoV-2 are the main contributions of this study.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10453-022-09754-7.

Compositional Data Analysis of 16S rRNA Gene Sequencing Results from Hospital Airborne Microbiome Samples

The compositional analysis of 16S rRNA gene sequencing datasets is applied to characterize the bacterial structure of airborne samples collected in different locations of a hospital infection disease department hosting COVID-19 patients, as well as to investigate the relationships among bacterial taxa at the genus and species level. The exploration of the centered log-ratio transformed data by the principal component analysis via the singular value decomposition has shown that the collected samples segregated with an observable separation depending on the monitoring location. More specifically, two main sample clusters were identified with regards to bacterial genera (species), consisting of samples mostly collected in rooms with and without COVID-19 patients, respectively. Human pathogenic genera (species) associated with nosocomial infections were mostly found in samples from areas hosting patients, while non-pathogenic genera (species) mainly isolated from soil were detected in the other samples. Propionibacterium acnes, Staphylococcus pettenkoferi, Corynebacterium tuberculostearicum, and jeikeium were the main pathogenic species detected in COVID-19 patients' rooms. Samples from these locations were on average characterized by smaller richness/evenness and diversity than the other ones, both at the genus and species level. Finally, the ρ metrics revealed that pairwise positive associations occurred either between pathogenic or non-pathogenic taxa.