Comprehensive 16S rRNA and metagenomic data from the gut microbiome of aging and rejuvenation mouse models

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dc.contributor.authorJ Shin-
dc.contributor.authorJung Ran Noh-
dc.contributor.authorD Choe-
dc.contributor.authorN Lee-
dc.contributor.authorY Song-
dc.contributor.authorS Cho-
dc.contributor.authorEun Jung Kang-
dc.contributor.authorMin-Jeong Go-
dc.contributor.authorSeok-Kyun Ha-
dc.contributor.authorJae-Hoon Kim-
dc.contributor.authorYong-Hoon Kim-
dc.contributor.authorKyoung Shim Kim-
dc.contributor.authorByoung Chan Kim-
dc.contributor.authorChul-Ho Lee-
dc.contributor.authorB KCho-
dc.date.accessioned2022-05-11T15:31:28Z-
dc.date.available2022-05-11T15:31:28Z-
dc.date.issued2022-
dc.identifier.issn2052-4463-
dc.identifier.urihttps://oak.kribb.re.kr/handle/201005/25987-
dc.description.abstractThe gut microbiota is associated with the health and longevity of the host. A few methods, such as fecal microbiota transplantation and oral administration of probiotics, have been applied to alter the gut microbiome and promote healthy aging. The changes in host microbiomes still remain poorly understood. Here, we characterized both the changes in gut microbial communities and their functional potential derived from colon samples in mouse models during aging. We achieved this through four procedures including co-housing, serum injection, parabiosis, and oral administration of Akkermansia muciniphila as probiotics using bacterial 16 S rRNA sequencing and shotgun metagenomic sequencing. The dataset comprised 16 S rRNA sequencing (36,249,200 paired-end reads, 107 sequencing data) and metagenomic sequencing data (307,194,369 paired-end reads, 109 sequencing data), characterizing the taxonomy of bacterial communities and their functional potential during aging and rejuvenation. The generated data expand the resources of the gut microbiome related to aging and rejuvenation and provide a useful dataset for research on developing therapeutic strategies to achieve healthy active aging.-
dc.publisherSpringer-Nature Pub Group-
dc.titleComprehensive 16S rRNA and metagenomic data from the gut microbiome of aging and rejuvenation mouse models-
dc.title.alternativeComprehensive 16S rRNA and metagenomic data from the gut microbiome of aging and rejuvenation mouse models-
dc.typeArticle-
dc.citation.titleScientific Data-
dc.citation.number0-
dc.citation.endPage197-
dc.citation.startPage197-
dc.citation.volume9-
dc.contributor.affiliatedAuthorJung Ran Noh-
dc.contributor.affiliatedAuthorEun Jung Kang-
dc.contributor.affiliatedAuthorMin-Jeong Go-
dc.contributor.affiliatedAuthorSeok-Kyun Ha-
dc.contributor.affiliatedAuthorJae-Hoon Kim-
dc.contributor.affiliatedAuthorYong-Hoon Kim-
dc.contributor.affiliatedAuthorKyoung Shim Kim-
dc.contributor.affiliatedAuthorByoung Chan Kim-
dc.contributor.affiliatedAuthorChul-Ho Lee-
dc.contributor.alternativeName신종오-
dc.contributor.alternativeName노정란-
dc.contributor.alternativeName최동희-
dc.contributor.alternativeName이남일-
dc.contributor.alternativeName송요셉-
dc.contributor.alternativeName조수형-
dc.contributor.alternativeName강은정-
dc.contributor.alternativeName고민정-
dc.contributor.alternativeName하석균-
dc.contributor.alternativeName김재훈-
dc.contributor.alternativeName김용훈-
dc.contributor.alternativeName김경심-
dc.contributor.alternativeName김병찬-
dc.contributor.alternativeName이철호-
dc.contributor.alternativeName조병관-
dc.identifier.bibliographicCitationScientific Data, vol. 9, pp. 197-197-
dc.identifier.doi10.1038/s41597-022-01308-3-
dc.description.journalClassY-
Appears in Collections:
Ochang Branch Institute > Division of National Bio-Infrastructure > Laboratory Animal Resource & Research Center > 1. Journal Articles
Division of Biomedical Research > Microbiome Convergence Research Center > 1. Journal Articles
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