Rep-PCR has been introduced to genomic analysis with numerous benefits over PFGE and AP-PCR. PFGE, which uses restriction enzymes to digest the genome, gel electrophoresis, and pattern analysis by direct DNA staining or DNA hybridization, requires long run times and thus is best only when there are limited sample numbers (Louws et al., 1999
). AP-PCR has been utilized to demonstrate the diversity of bacterial genotypes in several scientific fields using arbitrary primers that amplify variable sizes of PCR products, but, due to problems with reproducibility, AP-PCR is not practical for a large longitudinal population study to verify genotype characteristics (Bou et al., 2000
; Moser et al., 2010
). However, rep-PCR effectively and consistently generates genotypic profiles using a nanogram scale of genomic DNA and is able to compare data longitudinally and potentially between laboratories (Louws et al., 1999
; Healy et al., 2005
). The findings presented herein demonstrated the usefulness of rep-PCR in identifying genotypic differences of MS (S. mutans
) isolated from plaque from children and adults.
The primary objective of this study was to determine the minimal number of isolates required per
individual for rep-PCR analysis to demonstrate diversity of MS in a population at a time-point and be confident that more types are not missed. The first approach to this study focused on using 20 isolates per
individual to screen the pertinent number of genotypes. From probability computations, assuming 5 or fewer genotypes per
individual, 20 isolates were considered to be oversampling of this group of individuals. By oversampling (i.e.
, 20 isolates), adults were found to have more diversity than children, with a range of 1-5 genotypes and a mean of 2.4 genotypes per
person. Therefore, 20-isolate analyses found that, at most, 5 genotypes (adults) were distinguished, but, on average, fewer than 3 were distinguished in children and adults. Had there been 6 genotypes, there was nearly an 85% probability of all 6 being detected. Upon oversampling, analysis of 20 isolates per
individual demonstrated an average of fewer than 2 and 3 MS genotypes, respectively for children and adults. This finding is similar to (Li and Caufield, 1995
; Kozai et al., 1999
) or less than the number of genotypes reported in other studies (i.e.
, fewer than 3 and 4, respectively, for children and adults) (Emanuelsson et al., 1998
; Mattos-Graner et al., 2001
; Kohler et al., 2003
; Redmo Emanuelsson et al., 2003
; Napimoga et al., 2005
; Lembo et al., 2007
; Liu et al., 2007
; Mitchell et al., 2009
). These differences may be due to the population of study or the method we used. In this regard, the population that participated in the study was from a high-caries-risk, ‘poor access to dental care’ group of African-Americans. Therefore, the representativeness of this study to other populations, including previous studies that focused on MS genotypes, may explain the differences observed.
The initial pilot data functioned as a model to estimate the power calculation to optimize effective numbers of isolates for an individual. Using the data obtained and referring to the probability figure, we determined that 7-10 isolates was a reasonable number (and more practical than 20 isolates) for testing additional samples. In this regard, 7 isolates would provide 83% power of identifying up to 3 genotypes, while 10 isolates would have 78% power of identifying 4 genotypes; therefore, we continued our analysis with a group of samples from 35 children and 10 adult samples with 7-10 isolates to observe how well the genotypes were identified. The adult samples that had 7 to 10 isolates exhibited a genotype numbers similar to those of both child groups, with 83 to 95% probability of detecting 3 genotypes. Although the data were not statistically different for comparison of 20 and 7-10 isolates, for the adult sets of isolates, there were fewer genotypes identified with the 7-10 isolates as compared with the 20-isolate sampling. Therefore, analysis of the data suggests that sample sizes of 7-10 are sufficient numbers of isolates from younger (i.e., the children in this study) individuals at a single time-point for genetic diversity to be determined. However, further analysis may be indicated to better establish diversity in older individuals (i.e., adults).
In conclusion, MS genotypes within individuals were efficiently analyzed by highly integrated rep-PCR and the microfluidics LabChip® assay to obtain representative genotypes from the oral microflora. By oversampling (20 isolates), the findings support the notion that representative genotypes are also detected by collecting 7-10 MS isolates per sample, especially in 5- to 6-year-old children. These results provide information that will be used in future longitudinal studies as a database of MS genotypes and establishment of a library of genotypes in children and family households. Additionally, the methods using probability estimates provide a useful model for other microbiological studies involving the genetic diversity of indigenous micro-organisms in nature.