Identification of Heavy Smokers through Their Intestinal Microbiota by Data Mining Analysis

• Published in: Bioscience of Microbiota, Food and Health Vol. 32; no. 2; pp. 77 - 80
• Main Authors: KOBAYASHI, Toshio, FUJIWARA, Kenji
• Format: Journal Article
• Language: English
• Published: Japan BMFH Press 01.01.2013; Bioscience of Microbiota, Food and Health
• Subjects: data mining analysis; decision tree; heavy smoker; human intestinal microbiota; operational taxonomic unit; restriction enzyme; smoking habit; data mining analysis; smoking habit; decision tree; operational taxonomic unit; heavy smoker; human intestinal microbiota; restriction enzyme
• ISSN: 2186-3342; 2186-6953; 2186-3342
• DOI: 10.12938/bmfh.32.77

The intestinal microbiota compositions of 92 Japanese men were identified following consumption of identical meals for 3 days, and collected feces were analyzed through terminal restriction fragment length polymorphism. The obtained operational taxonomic units and smoking habits of subjects were analyzed by a data mining software. The constructed decision tree was able to identify explicitly the groups of smokers and nonsmokers. In particular, 4 smokers, who smoked 20 cigarettes/day, i.e., heavy smokers, were gathered in the same group of the decision tree and were clearly identified. Related operational taxonomic unit were traced to understand the species of bacteria, but all were found to be uncultured bacteria.