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BioMed Research International
Volume 2014, Article ID 906168, 10 pages
http://dx.doi.org/10.1155/2014/906168
Research Article

Systematic Analysis of the Association between Gut Flora and Obesity through High-Throughput Sequencing and Bioinformatics Approaches

1Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu 300, Taiwan
2Department of Obstetrics and Gynecology, Hsinchu Mackay Memorial Hospital, Hsinchu 300, Taiwan
3Mackay Medicine, Nursing and Management College, Taipei 104, Taiwan
4Department of Medicine, Mackay Medical College, New Taipei City 251, Taiwan
5Tseng Han-Chi General Hospital, Nantou 542, Taiwan
6Health GeneTech Corporation, Taoyuan 330, Taiwan
7Graduate Institute of Biomedical Informatics, Taipei Medical University, Taipei 110, Taiwan
8Department of Biological Science and Technology, National Chiao Tung University, Hsinchu 300, Taiwan
9Center for Bioinformatics Research, National Chiao Tung University, Hsinchu 300, Taiwan
10Department of Biomedical Science and Environmental Biology, Kaohsiung Medical University, Kaohsiung 807, Taiwan

Received 11 April 2014; Accepted 27 June 2014; Published 14 August 2014

Academic Editor: Li-Ching Wu

Copyright © 2014 Chih-Min Chiu et al. 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.

Abstract

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 ). 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.