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Refinement of microbiota analysis of specimens from patients with respiratory infections using next-generation sequencing

Next-generation sequencing (NGS) technologies have been applied in bacterial flora analysis. However, there is no standardized protocol, and the optimal clustering threshold for estimating bacterial species in respiratory infection specimens is unknown. This study was conducted to investigate the op...

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Autores principales: Ikegami, Hiroaki, Noguchi, Shingo, Fukuda, Kazumasa, Akata, Kentaro, Yamasaki, Kei, Kawanami, Toshinori, Mukae, Hiroshi, Yatera, Kazuhiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8486753/
https://www.ncbi.nlm.nih.gov/pubmed/34599245
http://dx.doi.org/10.1038/s41598-021-98985-8
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author Ikegami, Hiroaki
Noguchi, Shingo
Fukuda, Kazumasa
Akata, Kentaro
Yamasaki, Kei
Kawanami, Toshinori
Mukae, Hiroshi
Yatera, Kazuhiro
author_facet Ikegami, Hiroaki
Noguchi, Shingo
Fukuda, Kazumasa
Akata, Kentaro
Yamasaki, Kei
Kawanami, Toshinori
Mukae, Hiroshi
Yatera, Kazuhiro
author_sort Ikegami, Hiroaki
collection PubMed
description Next-generation sequencing (NGS) technologies have been applied in bacterial flora analysis. However, there is no standardized protocol, and the optimal clustering threshold for estimating bacterial species in respiratory infection specimens is unknown. This study was conducted to investigate the optimal threshold for clustering 16S ribosomal RNA gene sequences into operational taxonomic units (OTUs) by comparing the results of NGS technology with those of the Sanger method, which has a higher accuracy of sequence per single read than NGS technology. This study included 45 patients with pneumonia with aspiration risks and 35 patients with lung abscess. Compared to Sanger method, the concordance rates of NGS technology (clustered at 100%, 99%, and 97% homology) with the predominant phylotype were 78.8%, 71.3%, and 65.0%, respectively. With respect to the specimens dominated by the Streptococcus mitis group, containing several important causative agents of pneumonia, Bray Curtis dissimilarity revealed that the OTUs obtained at 100% clustering threshold (versus those obtained at 99% and 97% thresholds; medians of 0.35, 0.69, and 0.71, respectively) were more similar to those obtained by the Sanger method, with statistical significance (p < 0.05). Clustering with 100% sequence identity is necessary when analyzing the microbiota of respiratory infections using NGS technology.
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spelling pubmed-84867532021-10-04 Refinement of microbiota analysis of specimens from patients with respiratory infections using next-generation sequencing Ikegami, Hiroaki Noguchi, Shingo Fukuda, Kazumasa Akata, Kentaro Yamasaki, Kei Kawanami, Toshinori Mukae, Hiroshi Yatera, Kazuhiro Sci Rep Article Next-generation sequencing (NGS) technologies have been applied in bacterial flora analysis. However, there is no standardized protocol, and the optimal clustering threshold for estimating bacterial species in respiratory infection specimens is unknown. This study was conducted to investigate the optimal threshold for clustering 16S ribosomal RNA gene sequences into operational taxonomic units (OTUs) by comparing the results of NGS technology with those of the Sanger method, which has a higher accuracy of sequence per single read than NGS technology. This study included 45 patients with pneumonia with aspiration risks and 35 patients with lung abscess. Compared to Sanger method, the concordance rates of NGS technology (clustered at 100%, 99%, and 97% homology) with the predominant phylotype were 78.8%, 71.3%, and 65.0%, respectively. With respect to the specimens dominated by the Streptococcus mitis group, containing several important causative agents of pneumonia, Bray Curtis dissimilarity revealed that the OTUs obtained at 100% clustering threshold (versus those obtained at 99% and 97% thresholds; medians of 0.35, 0.69, and 0.71, respectively) were more similar to those obtained by the Sanger method, with statistical significance (p < 0.05). Clustering with 100% sequence identity is necessary when analyzing the microbiota of respiratory infections using NGS technology. Nature Publishing Group UK 2021-10-01 /pmc/articles/PMC8486753/ /pubmed/34599245 http://dx.doi.org/10.1038/s41598-021-98985-8 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Ikegami, Hiroaki
Noguchi, Shingo
Fukuda, Kazumasa
Akata, Kentaro
Yamasaki, Kei
Kawanami, Toshinori
Mukae, Hiroshi
Yatera, Kazuhiro
Refinement of microbiota analysis of specimens from patients with respiratory infections using next-generation sequencing
title Refinement of microbiota analysis of specimens from patients with respiratory infections using next-generation sequencing
title_full Refinement of microbiota analysis of specimens from patients with respiratory infections using next-generation sequencing
title_fullStr Refinement of microbiota analysis of specimens from patients with respiratory infections using next-generation sequencing
title_full_unstemmed Refinement of microbiota analysis of specimens from patients with respiratory infections using next-generation sequencing
title_short Refinement of microbiota analysis of specimens from patients with respiratory infections using next-generation sequencing
title_sort refinement of microbiota analysis of specimens from patients with respiratory infections using next-generation sequencing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8486753/
https://www.ncbi.nlm.nih.gov/pubmed/34599245
http://dx.doi.org/10.1038/s41598-021-98985-8
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