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We have developed a new approach for the estimation of bacterial proportional compositions in microbiota based on terminal restriction length polymorphism (T-RFLP) data and a Monte Carlo algorithm. This program estimates proportional compositions by minimizing distances between peak values and the relative abundance of each group, containing several species, estimated from peak areas of capillary electrophoresis for T-RFLP analysis. Oral bacteria in 36 saliva samples obtained from three individuals were analyzed using the program. Upon comparison, the estimated proportional composition obtained from one of the samples matched that from a clone library. Additionally, comparisons among the bacterial proportional compositions of saliva samples obtained from three individuals four times per day for 3 days revealed that the types of microbiota present in each individual did not change within each 24-h time period and were distinguishable from those in other individuals.

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.