Systematic analysis of the association between gut flora and obesity through high-throughput sequencing and bioinformatics approaches

Chih Min Chiu, Wei Chih Huang, Shun Long Weng, Han Chi Tseng, Chao Liang, Wei Chi Wang, Ting Yang, Tzu Ling Yang, Chen Tsung Weng, Tzu Hao Chang, Hsien Da Huang

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39 Citations (Scopus)

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 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.

Original languageEnglish
Article number906168
JournalBioMed Research International
Volume2014
DOIs
Publication statusPublished - 2014

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Bioinformatics
Computational Biology
Bacteria
Obesity
Throughput
Prevotella
Escherichia
Bacteroides
Body Mass Index
Eubacterium
Taiwan
Gastrointestinal Microbiome

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Medicine(all)

Cite this

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.

In: BioMed Research International, Vol. 2014, 906168, 2014.

Research output: Contribution to journalArticle

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. In: BioMed Research International. 2014 ; Vol. 2014.
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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 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.",
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