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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 ta...

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Autores principales: Perrone, Maria Rita, Romano, Salvatore, De Maria, Giuseppe, Tundo, Paolo, Bruno, Anna Rita, Tagliaferro, Luigi, Maffia, Michele, Fragola, Mattia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9408509/
https://www.ncbi.nlm.nih.gov/pubmed/36011742
http://dx.doi.org/10.3390/ijerph191610107
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author Perrone, Maria Rita
Romano, Salvatore
De Maria, Giuseppe
Tundo, Paolo
Bruno, Anna Rita
Tagliaferro, Luigi
Maffia, Michele
Fragola, Mattia
author_facet Perrone, Maria Rita
Romano, Salvatore
De Maria, Giuseppe
Tundo, Paolo
Bruno, Anna Rita
Tagliaferro, Luigi
Maffia, Michele
Fragola, Mattia
author_sort Perrone, Maria Rita
collection PubMed
description 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.
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spelling pubmed-94085092022-08-26 Compositional Data Analysis of 16S rRNA Gene Sequencing Results from Hospital Airborne Microbiome Samples Perrone, Maria Rita Romano, Salvatore De Maria, Giuseppe Tundo, Paolo Bruno, Anna Rita Tagliaferro, Luigi Maffia, Michele Fragola, Mattia Int J Environ Res Public Health Article 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. MDPI 2022-08-16 /pmc/articles/PMC9408509/ /pubmed/36011742 http://dx.doi.org/10.3390/ijerph191610107 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Perrone, Maria Rita
Romano, Salvatore
De Maria, Giuseppe
Tundo, Paolo
Bruno, Anna Rita
Tagliaferro, Luigi
Maffia, Michele
Fragola, Mattia
Compositional Data Analysis of 16S rRNA Gene Sequencing Results from Hospital Airborne Microbiome Samples
title Compositional Data Analysis of 16S rRNA Gene Sequencing Results from Hospital Airborne Microbiome Samples
title_full Compositional Data Analysis of 16S rRNA Gene Sequencing Results from Hospital Airborne Microbiome Samples
title_fullStr Compositional Data Analysis of 16S rRNA Gene Sequencing Results from Hospital Airborne Microbiome Samples
title_full_unstemmed Compositional Data Analysis of 16S rRNA Gene Sequencing Results from Hospital Airborne Microbiome Samples
title_short Compositional Data Analysis of 16S rRNA Gene Sequencing Results from Hospital Airborne Microbiome Samples
title_sort compositional data analysis of 16s rrna gene sequencing results from hospital airborne microbiome samples
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9408509/
https://www.ncbi.nlm.nih.gov/pubmed/36011742
http://dx.doi.org/10.3390/ijerph191610107
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