 tree for oligotypes using Bayesian inference, we used UniFrac to quantify similarities between samples based on their oligotype composition. Hierarchical clustering analysis on the UniFrac distance matrix of GS-defined BV and GS-defined normal vaginal samples grouped separately based on GS definition (Figure 2). Analogous comparison of urethral and penile skin samples from male partners of women with GS-defined BV or GS-defined normal vaginal flora did not show a similar separation (Figure S2).
It is well known that bacterial species with identical 16S rRNA genes can represent different ecotypes with differences in virulence properties and other phenotypic traits . In this sense, the sensitivity of the 16S rRNA gene is limited, but it is specific; it has been shown that even one nucleotide difference at the level of the 16S rRNA gene may be an indicator of an ecologically distinct strain . Moreover, there is a correlation between 16S rRNA gene divergence and the overall gene content , and the evolutionary distances of 16S rRNA genes can be used to discern genomic differences between species even with short pyrosequencing tag reads .
With the availability and affordability of massively parallel high-throughput sequencing technologies it is now possible to collect vast amounts of sequence data that cover a great deal of bacterial diversity within an environmental sample without the need for cultivation . However, due to the nature of pyrosequencing, sequences contain biologically irrelevant random sequencing errors, rendering them imprecise and noisy for inferring diversity at very low levels of taxonomy with high confidence. For instance, the two 16S rRNA genes of two G. vaginalis strains used in a genomic comparison study  differed by only 6 nucleotides at the 16S rRNA gene level, which was equivalent to 0.38% variation. Nevertheless, these two strains with very low level of variation at the 16S rRNA gene level were significantly different from each other in respect to their whole genomes. However, 0.38% variation is lower than the expected 1% random error rate of pyrosequencing , and very close to the expected 0.25% random error rate of pyrosequencing reads after stringent quality filtering . As a result of this, such low levels of variation are beyond the capacity of commonly available computational methods to separate these variants confidently, resulting in strains that are similar at the 16S rRNA gene level to receive the same taxonomical assignment, or to be collected in one OTU group. Similarly, variation across the sequences we analyzed in this study ranged from 0.2% to 1.66% over the 481 nucleotide-long pyrosequencing reads obtained from the V4–V6 region of the 16S rRNA gene. Therefore, due to the very high similarity among sequences, all would have been considered G. vaginalis, or clustered in one 3% OTU group. In spite of this, we observed a remarkable amount of G. vaginalis diversity, and were able to detect a high degree of correlation between oligotype profiles of many sexual partnerships (see Figure 3).
This relatively large scale study of variation in G. vaginalis 16S rRNA gene sequences supports previous cultivation-based studies that suggest G. vaginalis is sexually transmissible and that male and female partners share similar G. vaginalis strains , . Moreover, results of this study show that the usual approaches used to analyze 454 pyrosequencing data derived from human genitourinary tract samples miss important diversity that may be ecologically, clinically and/or epidemiologically significant.
The UniFrac analysis results appear to suggest that there may be a unique, closely related group of G. vaginalis oligotypes found among GS-defined normal and some GS-defined intermediate women. However, the relatively limited number of GS-defined normal and GS-defined intermediate women included in this study, require these results to be corroborated by additional studies. Nonetheless, results presented here suggest that the oligotyping approach could be used to identify and separate very similar strains at 16