Data mining analysis of terminal restriction fragment length polymorphism shows geographical differences in the human gut microbiota

• Published in: Biomedical reports Vol. 1; no. 4; pp. 559 - 562
• Main Authors: ANDOH, AKIRA, KOBAYASHI, TOSHIO, KUZUOKA, HIROYUKI, SUZUKI, YASUO, MATSUI, TOSHIYUKI, NAKAMURA, SHIRO, MATSUMOTO, TAKAYUKI, FUJIYAMA, YOSHIHIDE, BAMBA, TADAO
• Format: Journal Article
• Language: English
• Published: England D.A. Spandidos 01.07.2013; Spandidos Publications; Spandidos Publications UK Ltd
• Subjects: Analysis; Classification; Cluster analysis; Computer simulation; Data mining; Data processing; Decision analysis; Decision trees; Deoxyribonucleic acid; DNA; Environmental factors; Feces; Genetic testing; Intestinal microflora; microbiota; Microbiota (Symbiotic organisms); Nodes; Noise; Polymorphism; Regression analysis; Restriction fragment length polymorphism; Software; Taxonomy; terminal-restriction fragment length polymorphism; United States > US; Japan; microbiota; terminal-restriction fragment length polymorphism; data mining
• DOI: 10.3892/br.2013.127
• ISSN: 2049-9434

Environmental factors are important for shaping the gut microbiota. In this study, terminal-restriction fragment length polymorphism (T-RFLP) analysis was performed, and data mining analysis was applied to investigate the geographical differences in the gut microbiota in Japan. A total of 121 healthy individuals living in four different districts (Shiga, Hyogo, Fukuoka and Chiba prefectures) in Japan were enrolled. Their gut microbiota profiles were evaluated by T-RFLP analysis, and data mining analysis using the Classification and Regression Tree (C&RT) approach was performed. Data mining analysis provided a decision tree that clearly identified the various groups of subjects (nodes). Some nodes characterized the subjects from the four geographically distinct regions. Overall, 21 of the 35 subjects from the Hyogo Prefecture were mainly included in Node 21, 11 of the 16 subjects from the Shiga Prefecture were mainly included in Node 19, 37 of 40 subjects from the Chiba Prefecture were mainly included in Node 6 and 28 of 30 subjects from the Fukuoka Prefecture were included in Node 3. Only eight operational taxonomic units (OTUs) of the total 100 OTUs contributed to the characterization of the gut microbiota of the four geographically distinct districts in Japan. Geographical differences in the human gut microbiota were identified in Japan. Data mining analysis appears to be one of the optimal tools for characterization of the human gut microbiota.