| Project/Area Number |
18592281
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Social dentistry
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| Research Institution | Kyushu University |
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Principal Investigator |
NAKANO Yoshio Kyushu University, Faculty of Dental Science, Associate professor (80253459)
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| Project Period (FY) |
2006 – 2007
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| Project Status |
Completed (Fiscal Year 2007)
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| Budget Amount *help |
¥3,950,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2007: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2006: ¥2,000,000 (Direct Cost: ¥2,000,000)
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| Keywords | T-RFLP / oral flora / 16S rRNA / Support vector machine / 16SrRN / サポートベクターマシン |
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| Research Abstract |
We developed a new approach for calculating data from multiple T-RFLP samples by estimating T-RF combinations, applying a correlation analysis using two different fluorescent dyes generated simultaneously from all samples. This calculation is based on the expectation that the proportions of two T-RFs from one full-length PCR fragment would be nearly the same in each analysis. Using this method, oral microflorae in saliva were analyzed and the concentrations of methyl mercaptan, a volatile-sulfur compound that causes oral malodor, in mouth air were predicted using a support vector machine (SVM) from the apparent abundances of species in oral microflora and weighted by coefficients based on the peak frequency. Using this program, the oral microflorae in 220 human saliva samples were analyzed, and 24 bacterial groups were identified. The apparent abundances of bacterial groups weighted by the ISF in 110 samples were used in train a SVM to predict the presence of methyl mercaptan above the threshold concentration of oral malodor, and the results were tested using the remaining 110 samples. Based on the bacterial composition patterns calculated by the program, the concentration of methyl mercaptan was predicted at an accuracy of 90%.
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