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Systematic Analysis of the Association between Gut Flora and Obesity through High-Throughput Sequencing and Bioinformatics Approaches
Eighty-one stool samples from Taiwanese were collected for analysis of the association between the gut flora and obesity. The supervised analysis showed that the most, abundant genera of bacteria in normal samples (from people with a body mass index (BMI) ≤ 24) were Bacteroides (27.7%), Prevotella (...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4150407/ https://www.ncbi.nlm.nih.gov/pubmed/25202708 http://dx.doi.org/10.1155/2014/906168 |
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author | Chiu, Chih-Min Huang, Wei-Chih Weng, Shun-Long Tseng, Han-Chi Liang, Chao Wang, Wei-Chi Yang, Ting Yang, Tzu-Ling Weng, Chen-Tsung Chang, Tzu-Hao Huang, Hsien-Da |
author_facet | Chiu, Chih-Min Huang, Wei-Chih Weng, Shun-Long Tseng, Han-Chi Liang, Chao Wang, Wei-Chi Yang, Ting Yang, Tzu-Ling Weng, Chen-Tsung Chang, Tzu-Hao Huang, Hsien-Da |
author_sort | Chiu, Chih-Min |
collection | PubMed |
description | Eighty-one stool samples from Taiwanese were collected for analysis of the association between the gut flora and obesity. The supervised analysis showed that the most, abundant genera of bacteria in normal samples (from people with a body mass index (BMI) ≤ 24) were Bacteroides (27.7%), Prevotella (19.4%), Escherichia (12%), Phascolarctobacterium (3.9%), and Eubacterium (3.5%). The most abundant genera of bacteria in case samples (with a BMI ≥ 27) were Bacteroides (29%), Prevotella (21%), Escherichia (7.4%), Megamonas (5.1%), and Phascolarctobacterium (3.8%). A principal coordinate analysis (PCoA) demonstrated that normal samples were clustered more compactly than case samples. An unsupervised analysis demonstrated that bacterial communities in the gut were clustered into two main groups: N-like and OB-like groups. Remarkably, most normal samples (78%) were clustered in the N-like group, and most case samples (81%) were clustered in the OB-like group (Fisher's P value = 1.61E − 07). The results showed that bacterial communities in the gut were highly associated with obesity. This is the first study in Taiwan to investigate the association between human gut flora and obesity, and the results provide new insights into the correlation of bacteria with the rising trend in obesity. |
format | Online Article Text |
id | pubmed-4150407 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-41504072014-09-08 Systematic Analysis of the Association between Gut Flora and Obesity through High-Throughput Sequencing and Bioinformatics Approaches Chiu, Chih-Min Huang, Wei-Chih Weng, Shun-Long Tseng, Han-Chi Liang, Chao Wang, Wei-Chi Yang, Ting Yang, Tzu-Ling Weng, Chen-Tsung Chang, Tzu-Hao Huang, Hsien-Da Biomed Res Int Research Article Eighty-one stool samples from Taiwanese were collected for analysis of the association between the gut flora and obesity. The supervised analysis showed that the most, abundant genera of bacteria in normal samples (from people with a body mass index (BMI) ≤ 24) were Bacteroides (27.7%), Prevotella (19.4%), Escherichia (12%), Phascolarctobacterium (3.9%), and Eubacterium (3.5%). The most abundant genera of bacteria in case samples (with a BMI ≥ 27) were Bacteroides (29%), Prevotella (21%), Escherichia (7.4%), Megamonas (5.1%), and Phascolarctobacterium (3.8%). A principal coordinate analysis (PCoA) demonstrated that normal samples were clustered more compactly than case samples. An unsupervised analysis demonstrated that bacterial communities in the gut were clustered into two main groups: N-like and OB-like groups. Remarkably, most normal samples (78%) were clustered in the N-like group, and most case samples (81%) were clustered in the OB-like group (Fisher's P value = 1.61E − 07). The results showed that bacterial communities in the gut were highly associated with obesity. This is the first study in Taiwan to investigate the association between human gut flora and obesity, and the results provide new insights into the correlation of bacteria with the rising trend in obesity. Hindawi Publishing Corporation 2014 2014-08-14 /pmc/articles/PMC4150407/ /pubmed/25202708 http://dx.doi.org/10.1155/2014/906168 Text en Copyright © 2014 Chih-Min Chiu et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Chiu, Chih-Min Huang, Wei-Chih Weng, Shun-Long Tseng, Han-Chi Liang, Chao Wang, Wei-Chi Yang, Ting Yang, Tzu-Ling Weng, Chen-Tsung Chang, Tzu-Hao Huang, Hsien-Da Systematic Analysis of the Association between Gut Flora and Obesity through High-Throughput Sequencing and Bioinformatics Approaches |
title | Systematic Analysis of the Association between Gut Flora and Obesity through High-Throughput Sequencing and Bioinformatics Approaches |
title_full | Systematic Analysis of the Association between Gut Flora and Obesity through High-Throughput Sequencing and Bioinformatics Approaches |
title_fullStr | Systematic Analysis of the Association between Gut Flora and Obesity through High-Throughput Sequencing and Bioinformatics Approaches |
title_full_unstemmed | Systematic Analysis of the Association between Gut Flora and Obesity through High-Throughput Sequencing and Bioinformatics Approaches |
title_short | Systematic Analysis of the Association between Gut Flora and Obesity through High-Throughput Sequencing and Bioinformatics Approaches |
title_sort | systematic analysis of the association between gut flora and obesity through high-throughput sequencing and bioinformatics approaches |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4150407/ https://www.ncbi.nlm.nih.gov/pubmed/25202708 http://dx.doi.org/10.1155/2014/906168 |
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