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Exploring the Hospital Microbiome by High-Resolution 16S rRNA Profiling

The aim of this work was to analyze and compare the bacterial communities of 663 samples from a Brazilian hospital by using high-throughput sequencing of the 16S rRNA gene. To increase taxonomic profiling and specificity of 16S-based identification, a strict sequence quality filtering process was ap...

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Autores principales: Rampelotto, Pabulo H., Sereia, Aline F.R., de Oliveira, Luiz Felipe V., Margis, Rogério
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6696720/
https://www.ncbi.nlm.nih.gov/pubmed/31242612
http://dx.doi.org/10.3390/ijms20123099
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author Rampelotto, Pabulo H.
Sereia, Aline F.R.
de Oliveira, Luiz Felipe V.
Margis, Rogério
author_facet Rampelotto, Pabulo H.
Sereia, Aline F.R.
de Oliveira, Luiz Felipe V.
Margis, Rogério
author_sort Rampelotto, Pabulo H.
collection PubMed
description The aim of this work was to analyze and compare the bacterial communities of 663 samples from a Brazilian hospital by using high-throughput sequencing of the 16S rRNA gene. To increase taxonomic profiling and specificity of 16S-based identification, a strict sequence quality filtering process was applied for the accurate identification of clinically relevant bacterial taxa. Our results indicate that the hospital environment is predominantly inhabited by closely related species. A massive dominance of a few taxa in all taxonomic levels down to the genera was observed, where the ten most abundant genera in each facility represented 64.4% of all observed taxa, with a major predominance of Acinetobacter and Pseudomonas. The presence of several nosocomial pathogens was revealed. Co-occurrence analysis indicated that the present hospital microbial network had low connectedness, forming a clustered topology, but not structured among groups of nodes (i.e., modules). Furthermore, we were able to detect ecologically relevant relationships between specific microbial taxa, in particular, potential competition between pathogens and non-pathogens. Overall, these results provide new insight into different aspects of a hospital microbiome and indicate that 16S rRNA sequencing may serve as a robust one-step tool for microbiological identification and characterization of a wide range of clinically relevant bacterial taxa in hospital settings with a high resolution.
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spelling pubmed-66967202019-09-05 Exploring the Hospital Microbiome by High-Resolution 16S rRNA Profiling Rampelotto, Pabulo H. Sereia, Aline F.R. de Oliveira, Luiz Felipe V. Margis, Rogério Int J Mol Sci Article The aim of this work was to analyze and compare the bacterial communities of 663 samples from a Brazilian hospital by using high-throughput sequencing of the 16S rRNA gene. To increase taxonomic profiling and specificity of 16S-based identification, a strict sequence quality filtering process was applied for the accurate identification of clinically relevant bacterial taxa. Our results indicate that the hospital environment is predominantly inhabited by closely related species. A massive dominance of a few taxa in all taxonomic levels down to the genera was observed, where the ten most abundant genera in each facility represented 64.4% of all observed taxa, with a major predominance of Acinetobacter and Pseudomonas. The presence of several nosocomial pathogens was revealed. Co-occurrence analysis indicated that the present hospital microbial network had low connectedness, forming a clustered topology, but not structured among groups of nodes (i.e., modules). Furthermore, we were able to detect ecologically relevant relationships between specific microbial taxa, in particular, potential competition between pathogens and non-pathogens. Overall, these results provide new insight into different aspects of a hospital microbiome and indicate that 16S rRNA sequencing may serve as a robust one-step tool for microbiological identification and characterization of a wide range of clinically relevant bacterial taxa in hospital settings with a high resolution. MDPI 2019-06-25 /pmc/articles/PMC6696720/ /pubmed/31242612 http://dx.doi.org/10.3390/ijms20123099 Text en © 2019 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Rampelotto, Pabulo H.
Sereia, Aline F.R.
de Oliveira, Luiz Felipe V.
Margis, Rogério
Exploring the Hospital Microbiome by High-Resolution 16S rRNA Profiling
title Exploring the Hospital Microbiome by High-Resolution 16S rRNA Profiling
title_full Exploring the Hospital Microbiome by High-Resolution 16S rRNA Profiling
title_fullStr Exploring the Hospital Microbiome by High-Resolution 16S rRNA Profiling
title_full_unstemmed Exploring the Hospital Microbiome by High-Resolution 16S rRNA Profiling
title_short Exploring the Hospital Microbiome by High-Resolution 16S rRNA Profiling
title_sort exploring the hospital microbiome by high-resolution 16s rrna profiling
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6696720/
https://www.ncbi.nlm.nih.gov/pubmed/31242612
http://dx.doi.org/10.3390/ijms20123099
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