標題: Systematic Analysis of the Association between Gut Flora and Obesity through High-Throughput Sequencing and Bioinformatics Approaches
作者: 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
生物科技學系
生物資訊及系統生物研究所
Department of Biological Science and Technology
Institude of Bioinformatics and Systems Biology
公開日期: 2014
摘要: 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.
URI: http://hdl.handle.net/11536/25107
http://dx.doi.org/10.1155/2014/906168
ISSN: 2314-6133
DOI: 10.1155/2014/906168
期刊: BIOMED RESEARCH INTERNATIONAL
Appears in Collections:Articles


Files in This Item:

  1. 000340765100001.pdf

If it is a zip file, please download the file and unzip it, then open index.html in a browser to view the full text content.