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dc.contributor.authorLiang, Chaoen_US
dc.contributor.authorTseng, Han-Chien_US
dc.contributor.authorChen, Hui-Meien_US
dc.contributor.authorWang, Wei-Chien_US
dc.contributor.authorChiu, Chih-Minen_US
dc.contributor.authorChang, Jen-Yunen_US
dc.contributor.authorLu, Kuan-Yien_US
dc.contributor.authorWeng, Shun-Longen_US
dc.contributor.authorChang, Tzu-Haoen_US
dc.contributor.authorChang, Chao-Hsiangen_US
dc.contributor.authorWeng, Chen-Tsungen_US
dc.contributor.authorWang, Hwei-Mingen_US
dc.contributor.authorHuang, Hsien-Daen_US
dc.date.accessioned2019-04-02T05:59:59Z-
dc.date.available2019-04-02T05:59:59Z-
dc.date.issued2017-01-01en_US
dc.identifier.issn1471-2164en_US
dc.identifier.urihttp://dx.doi.org/10.1186/s12864-016-3261-6en_US
dc.identifier.urihttp://hdl.handle.net/11536/147854-
dc.description.abstractBackground: Gastrointestinal microbiota, particularly gut microbiota, is associated with human health. The biodiversity of gut microbiota is affected by ethnicities and environmental factors such as dietary habits or medicine intake, and three enterotypes of the human gut microbiome were announced in 2011. These enterotypes are not significantly correlated with gender, age, or body weight but are influenced by long-term dietary habits. However, to date, only two enterotypes (predominantly consisting of Bacteroides and Prevotella) have shown these characteristics in previous research; the third enterotype remains ambiguous. Understanding the enterotypes can improve the knowledge of the relationship between microbiota and human health. Results: We obtained 181 human fecal samples from adults in Taiwan. Microbiota compositions were analyzed using next-generation sequencing (NGS) technology, which is a culture-independent method of constructing microbial community profiles by sequencing 16S ribosomal DNA (rDNA). In these samples, 17,675,898 sequencing reads were sequenced, and on average, 215 operational taxonomic units (OTUs) were identified for each sample. In this study, the major bacteria in the enterotypes identified from the fecal samples were Bacteroides, Prevotella, and Enterobacteriaceae, and their correlation with dietary habits was confirmed. A microbial interaction network in the gut was observed on the basis of the amount of short-chain fatty acids, pH value of the intestine, and composition of the bacterial community (enterotypes). Finally, a decision tree was derived to provide a predictive model for the three enterotypes. The accuracies of this model in training and independent testing sets were 97.2 and 84.0%, respectively. Conclusions: We used NGS technology to characterize the microbiota and constructed a predictive model. The most significant finding was that Enterobacteriaceae, the predominant subtype, could be a new subtype of enterotypes in the Asian population.en_US
dc.language.isoen_USen_US
dc.subjectEnterotypeen_US
dc.subject16S rDNAen_US
dc.subjectNext-generation sequencingen_US
dc.subjectGut microbiomeen_US
dc.subjectPredictive modelen_US
dc.titleDiversity and enterotype in gut bacterial community of adults in Taiwanen_US
dc.typeArticleen_US
dc.identifier.doi10.1186/s12864-016-3261-6en_US
dc.identifier.journalBMC GENOMICSen_US
dc.citation.volume18en_US
dc.citation.issue1en_US
dc.contributor.department生物科技學系zh_TW
dc.contributor.department生物資訊及系統生物研究所zh_TW
dc.contributor.departmentDepartment of Biological Science and Technologyen_US
dc.contributor.departmentInstitude of Bioinformatics and Systems Biologyen_US
dc.identifier.wosnumberWOS:000410191300001en_US
dc.citation.woscount0en_US
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