2018年4月1日
Habitability analyses of aquatic bacteria
Journal of Oceanography
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- 巻
- 74
- 号
- 2
- 開始ページ
- 197
- 終了ページ
- 207
- 記述言語
- 英語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.1007/s10872-017-0449-6
- 出版者・発行元
- Springer Tokyo
Habitability is defined as an ability of an organism to inhabit different environments. Habitability of organisms, however, cannot be inferred from analyses such as a whole genome or community structures. A recently developed database, the MetaMetaDB, gives us information from what kind of environments one particular 16S rRNA sequence data has ever been obtained, and thus enables us to infer the habitability of the bacterium in question. In order to check the applicability of this database to study the habitability of aquatic bacteria, samples collected at two Naka River stations, one estuarine station from Naka River Estuary, two coastal stations at Oarai in Ibaraki Prefecture, Japan and one station in the Kuroshio Current of the western North Pacific were examined. The phylotypes were tracked against the MetaMetaDB and it was reasonably found that the low-salinity stations were dominated by sequences with “freshwater and groundwater”, “human” and “wastewater” habitat identities, while the high-salinity stations were dominated by those with a “marine” identity. The phylotypes of low-salinity stations with a particular habitat identity were absent or rare in the high-salinity stations and vice versa. The MetaMetaDB also showed that sequences of Cyanobacteria or related phylogenetic groups may be present in the human gut, as well as the probable distribution of the relatives (ancestors/descendants/siblings) of some bacteria. These overall findings proved that the MetaMetaDB is useful as a new tool to infer microbial habitability and it gives us new information on the possible origin and ecology of microorganisms in the environments.
Web of Science ® 被引用回数 : 4
Web of Science ® の 関連論文(Related Records®)ビュー
- リンク情報
- ID情報
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- DOI : 10.1007/s10872-017-0449-6
- ISSN : 1573-868X
- ISSN : 0916-8370
- SCOPUS ID : 85031804683
- Web of Science ID : WOS:000426283100005