TY - JOUR
T1 - Development and application of a T-RFLP data analysis method using correlation coefficient matrices
AU - Nakano, Yoshio
AU - Takeshita, Toru
AU - Kamio, Noriaki
AU - Shiota, Susumu
AU - Shibata, Yukie
AU - Yasui, Masaki
AU - Yamashita, Yoshihisa
N1 - Funding Information:
This research was partially supported by the Ministry of Education, Science, Sports and Culture, Grant-in-Aid for Scientific Research 19390541 (Y. Y.) and a Research Fellowship from the Japan Society for the Promotion of Science for Young Scientists 1910886 (T. T.).
PY - 2008/12
Y1 - 2008/12
N2 - Environmental microbiology studies commonly use terminal restriction fragment length polymorphism (T-RFLP) of 16S rRNA genes, for example, to analyze changes in community structure in relation to changing physicochemical and biological conditions over space and time. Although T-RFLP is most useful for comparing samples from different environments, a large number of samples makes effective analysis difficult using the Web-based tools that are currently available. To resolve this dilemma, we used a new approach for calculating data from multiple T-RFLP samples by estimating terminal fragment combinations, then applying a correlation analysis using two different fluorescent dyes generated simultaneously from all samples. This calculation was based on the expectation that the proportions of two terminal fragments from one full-length polymerase chain reaction fragment would be nearly the same in each analysis. Using this program, the oral microflora in 73 human saliva samples were analyzed, and 24 bacterial groups, with peak areas of at least 0.5% and correlation coefficients of 0.55 or greater, were identified from the T-RFs within 40 s.
AB - Environmental microbiology studies commonly use terminal restriction fragment length polymorphism (T-RFLP) of 16S rRNA genes, for example, to analyze changes in community structure in relation to changing physicochemical and biological conditions over space and time. Although T-RFLP is most useful for comparing samples from different environments, a large number of samples makes effective analysis difficult using the Web-based tools that are currently available. To resolve this dilemma, we used a new approach for calculating data from multiple T-RFLP samples by estimating terminal fragment combinations, then applying a correlation analysis using two different fluorescent dyes generated simultaneously from all samples. This calculation was based on the expectation that the proportions of two terminal fragments from one full-length polymerase chain reaction fragment would be nearly the same in each analysis. Using this program, the oral microflora in 73 human saliva samples were analyzed, and 24 bacterial groups, with peak areas of at least 0.5% and correlation coefficients of 0.55 or greater, were identified from the T-RFs within 40 s.
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U2 - 10.1016/j.mimet.2008.08.002
DO - 10.1016/j.mimet.2008.08.002
M3 - Article
C2 - 18775752
AN - SCOPUS:55149091559
SN - 0167-7012
VL - 75
SP - 501
EP - 505
JO - Journal of Microbiological Methods
JF - Journal of Microbiological Methods
IS - 3
ER -