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Development of a time-series shotgun metagenomics database for monitoring microbial communities at the Pacific coast of Japan

Although numerous metagenome, amplicon sequencing-based studies have been conducted to date to characterize marine microbial communities, relatively few have employed full metagenome shotgun sequencing to obtain a broader picture of the functional features of these marine microbial communities. More...

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Autores principales: Yoshitake, Kazutoshi, Kimura, Gaku, Sakami, Tomoko, Watanabe, Tsuyoshi, Taniuchi, Yukiko, Kakehi, Shigeho, Kuwata, Akira, Yamaguchi, Haruyo, Kataoka, Takafumi, Kawachi, Masanobu, Ikeo, Kazuho, Tan, Engkong, Igarashi, Yoji, Ohtsubo, Masafumi, Watabe, Shugo, Suzuki, Yutaka, Asakawa, Shuichi, Ishino, Sonoko, Tashiro, Kosuke, Ishino, Yoshizumi, Kobayashi, Takanori, Mineta, Katsuhiko, Gojobori, Takashi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8190148/
https://www.ncbi.nlm.nih.gov/pubmed/34108585
http://dx.doi.org/10.1038/s41598-021-91615-3
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author Yoshitake, Kazutoshi
Kimura, Gaku
Sakami, Tomoko
Watanabe, Tsuyoshi
Taniuchi, Yukiko
Kakehi, Shigeho
Kuwata, Akira
Yamaguchi, Haruyo
Kataoka, Takafumi
Kawachi, Masanobu
Ikeo, Kazuho
Tan, Engkong
Igarashi, Yoji
Ohtsubo, Masafumi
Watabe, Shugo
Suzuki, Yutaka
Asakawa, Shuichi
Ishino, Sonoko
Tashiro, Kosuke
Ishino, Yoshizumi
Kobayashi, Takanori
Mineta, Katsuhiko
Gojobori, Takashi
author_facet Yoshitake, Kazutoshi
Kimura, Gaku
Sakami, Tomoko
Watanabe, Tsuyoshi
Taniuchi, Yukiko
Kakehi, Shigeho
Kuwata, Akira
Yamaguchi, Haruyo
Kataoka, Takafumi
Kawachi, Masanobu
Ikeo, Kazuho
Tan, Engkong
Igarashi, Yoji
Ohtsubo, Masafumi
Watabe, Shugo
Suzuki, Yutaka
Asakawa, Shuichi
Ishino, Sonoko
Tashiro, Kosuke
Ishino, Yoshizumi
Kobayashi, Takanori
Mineta, Katsuhiko
Gojobori, Takashi
author_sort Yoshitake, Kazutoshi
collection PubMed
description Although numerous metagenome, amplicon sequencing-based studies have been conducted to date to characterize marine microbial communities, relatively few have employed full metagenome shotgun sequencing to obtain a broader picture of the functional features of these marine microbial communities. Moreover, most of these studies only performed sporadic sampling, which is insufficient to understand an ecosystem comprehensively. In this study, we regularly conducted seawater sampling along the northeastern Pacific coast of Japan between March 2012 and May 2016. We collected 213 seawater samples and prepared size-based fractions to generate 454 subsets of samples for shotgun metagenome sequencing and analysis. We also determined the sequences of 16S rRNA (n = 111) and 18S rRNA (n = 47) gene amplicons from smaller sample subsets. We thereafter developed the Ocean Monitoring Database for time-series metagenomic data (http://marine-meta.healthscience.sci.waseda.ac.jp/omd/), which provides a three-dimensional bird’s-eye view of the data. This database includes results of digital DNA chip analysis, a novel method for estimating ocean characteristics such as water temperature from metagenomic data. Furthermore, we developed a novel classification method that includes more information about viruses than that acquired using BLAST. We further report the discovery of a large number of previously overlooked (TAG)n repeat sequences in the genomes of marine microbes. We predict that the availability of this time-series database will lead to major discoveries in marine microbiome research.
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spelling pubmed-81901482021-06-10 Development of a time-series shotgun metagenomics database for monitoring microbial communities at the Pacific coast of Japan Yoshitake, Kazutoshi Kimura, Gaku Sakami, Tomoko Watanabe, Tsuyoshi Taniuchi, Yukiko Kakehi, Shigeho Kuwata, Akira Yamaguchi, Haruyo Kataoka, Takafumi Kawachi, Masanobu Ikeo, Kazuho Tan, Engkong Igarashi, Yoji Ohtsubo, Masafumi Watabe, Shugo Suzuki, Yutaka Asakawa, Shuichi Ishino, Sonoko Tashiro, Kosuke Ishino, Yoshizumi Kobayashi, Takanori Mineta, Katsuhiko Gojobori, Takashi Sci Rep Article Although numerous metagenome, amplicon sequencing-based studies have been conducted to date to characterize marine microbial communities, relatively few have employed full metagenome shotgun sequencing to obtain a broader picture of the functional features of these marine microbial communities. Moreover, most of these studies only performed sporadic sampling, which is insufficient to understand an ecosystem comprehensively. In this study, we regularly conducted seawater sampling along the northeastern Pacific coast of Japan between March 2012 and May 2016. We collected 213 seawater samples and prepared size-based fractions to generate 454 subsets of samples for shotgun metagenome sequencing and analysis. We also determined the sequences of 16S rRNA (n = 111) and 18S rRNA (n = 47) gene amplicons from smaller sample subsets. We thereafter developed the Ocean Monitoring Database for time-series metagenomic data (http://marine-meta.healthscience.sci.waseda.ac.jp/omd/), which provides a three-dimensional bird’s-eye view of the data. This database includes results of digital DNA chip analysis, a novel method for estimating ocean characteristics such as water temperature from metagenomic data. Furthermore, we developed a novel classification method that includes more information about viruses than that acquired using BLAST. We further report the discovery of a large number of previously overlooked (TAG)n repeat sequences in the genomes of marine microbes. We predict that the availability of this time-series database will lead to major discoveries in marine microbiome research. Nature Publishing Group UK 2021-06-09 /pmc/articles/PMC8190148/ /pubmed/34108585 http://dx.doi.org/10.1038/s41598-021-91615-3 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
Yoshitake, Kazutoshi
Kimura, Gaku
Sakami, Tomoko
Watanabe, Tsuyoshi
Taniuchi, Yukiko
Kakehi, Shigeho
Kuwata, Akira
Yamaguchi, Haruyo
Kataoka, Takafumi
Kawachi, Masanobu
Ikeo, Kazuho
Tan, Engkong
Igarashi, Yoji
Ohtsubo, Masafumi
Watabe, Shugo
Suzuki, Yutaka
Asakawa, Shuichi
Ishino, Sonoko
Tashiro, Kosuke
Ishino, Yoshizumi
Kobayashi, Takanori
Mineta, Katsuhiko
Gojobori, Takashi
Development of a time-series shotgun metagenomics database for monitoring microbial communities at the Pacific coast of Japan
title Development of a time-series shotgun metagenomics database for monitoring microbial communities at the Pacific coast of Japan
title_full Development of a time-series shotgun metagenomics database for monitoring microbial communities at the Pacific coast of Japan
title_fullStr Development of a time-series shotgun metagenomics database for monitoring microbial communities at the Pacific coast of Japan
title_full_unstemmed Development of a time-series shotgun metagenomics database for monitoring microbial communities at the Pacific coast of Japan
title_short Development of a time-series shotgun metagenomics database for monitoring microbial communities at the Pacific coast of Japan
title_sort development of a time-series shotgun metagenomics database for monitoring microbial communities at the pacific coast of japan
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8190148/
https://www.ncbi.nlm.nih.gov/pubmed/34108585
http://dx.doi.org/10.1038/s41598-021-91615-3
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