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Comparison of Database Search Methods for the Detection of Legionella pneumophila in Water Samples Using Metagenomic Analysis

Metagenomic analysis has become a powerful tool to analyze bacterial communities in environmental samples. However, the detection of a specific bacterial species using metagenomic analysis remains difficult due to false positive detections of sequences shared between different bacterial species. In...

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Autores principales: Borthong, Jednipit, Omori, Ryosuke, Sugimoto, Chihiro, Suthienkul, Orasa, Nakao, Ryo, Ito, Kimihito
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6018159/
https://www.ncbi.nlm.nih.gov/pubmed/29971047
http://dx.doi.org/10.3389/fmicb.2018.01272
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author Borthong, Jednipit
Omori, Ryosuke
Sugimoto, Chihiro
Suthienkul, Orasa
Nakao, Ryo
Ito, Kimihito
author_facet Borthong, Jednipit
Omori, Ryosuke
Sugimoto, Chihiro
Suthienkul, Orasa
Nakao, Ryo
Ito, Kimihito
author_sort Borthong, Jednipit
collection PubMed
description Metagenomic analysis has become a powerful tool to analyze bacterial communities in environmental samples. However, the detection of a specific bacterial species using metagenomic analysis remains difficult due to false positive detections of sequences shared between different bacterial species. In this study, 16S rRNA amplicon and shotgun metagenomic analyses were conducted on samples collected along a stream and ponds in the campus of Hokkaido University. We compared different database search methods for bacterial detection by focusing on Legionella pneumophila. In this study, we used L. pneumophila-specific nested PCR as a gold standard to evaluate the results of the metagenomic analysis. Comparison with the results from L. pneumophila-specific nested PCR indicated that a blastn search of shotgun reads against the NCBI-NT database led to false positive results and had problems with specificity. We also found that a blastn search of shotgun reads against a database of the catalase-peroxidase (katB) gene detected L. pneumophila with the highest area under the receiver operating characteristic curve among the tested search methods; indicating that a blastn search against the katB gene database had better diagnostic ability than searches against other databases. Our results suggest that sequence searches targeting long genes specifically associated with the bacterial species of interest is a prerequisite to detecting the bacterial species in environmental samples using metagenomic analyses.
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spelling pubmed-60181592018-07-03 Comparison of Database Search Methods for the Detection of Legionella pneumophila in Water Samples Using Metagenomic Analysis Borthong, Jednipit Omori, Ryosuke Sugimoto, Chihiro Suthienkul, Orasa Nakao, Ryo Ito, Kimihito Front Microbiol Microbiology Metagenomic analysis has become a powerful tool to analyze bacterial communities in environmental samples. However, the detection of a specific bacterial species using metagenomic analysis remains difficult due to false positive detections of sequences shared between different bacterial species. In this study, 16S rRNA amplicon and shotgun metagenomic analyses were conducted on samples collected along a stream and ponds in the campus of Hokkaido University. We compared different database search methods for bacterial detection by focusing on Legionella pneumophila. In this study, we used L. pneumophila-specific nested PCR as a gold standard to evaluate the results of the metagenomic analysis. Comparison with the results from L. pneumophila-specific nested PCR indicated that a blastn search of shotgun reads against the NCBI-NT database led to false positive results and had problems with specificity. We also found that a blastn search of shotgun reads against a database of the catalase-peroxidase (katB) gene detected L. pneumophila with the highest area under the receiver operating characteristic curve among the tested search methods; indicating that a blastn search against the katB gene database had better diagnostic ability than searches against other databases. Our results suggest that sequence searches targeting long genes specifically associated with the bacterial species of interest is a prerequisite to detecting the bacterial species in environmental samples using metagenomic analyses. Frontiers Media S.A. 2018-06-19 /pmc/articles/PMC6018159/ /pubmed/29971047 http://dx.doi.org/10.3389/fmicb.2018.01272 Text en Copyright © 2018 Borthong, Omori, Sugimoto, Suthienkul, Nakao and Ito. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Microbiology
Borthong, Jednipit
Omori, Ryosuke
Sugimoto, Chihiro
Suthienkul, Orasa
Nakao, Ryo
Ito, Kimihito
Comparison of Database Search Methods for the Detection of Legionella pneumophila in Water Samples Using Metagenomic Analysis
title Comparison of Database Search Methods for the Detection of Legionella pneumophila in Water Samples Using Metagenomic Analysis
title_full Comparison of Database Search Methods for the Detection of Legionella pneumophila in Water Samples Using Metagenomic Analysis
title_fullStr Comparison of Database Search Methods for the Detection of Legionella pneumophila in Water Samples Using Metagenomic Analysis
title_full_unstemmed Comparison of Database Search Methods for the Detection of Legionella pneumophila in Water Samples Using Metagenomic Analysis
title_short Comparison of Database Search Methods for the Detection of Legionella pneumophila in Water Samples Using Metagenomic Analysis
title_sort comparison of database search methods for the detection of legionella pneumophila in water samples using metagenomic analysis
topic Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6018159/
https://www.ncbi.nlm.nih.gov/pubmed/29971047
http://dx.doi.org/10.3389/fmicb.2018.01272
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