{'fraction_non_alphanumeric': 0.027011494252873563, 'fraction_numerical': 0.0, 'mean_word_length': 5.262589928057554, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Assessment of vaginal microbiota in Brazilian women with and without bacterial vaginosis and comparison with Nugent score.

INTRODUCTION
Bacterial vaginosis (BV) is characterized by the depletion of Lactobacillus spp. population and increase of other species, especially Gardnerella vaginalis and Atopobium vaginae. This study aimed to investigate the vaginal microbiota structure of Brazilian women with and without BV according to Nugent Score and to assess the correlation among Nugent score and the quantification of BV-associated bacteria.


METHODOLOGY
Polymerase Chain Reaction-Denaturing Gradient Gel Electrophoresis (PCR-DGGE) assay was employed to characterize the vaginal microbiota structure. Quantification of Lactobacillus spp., G. vaginalis, A. vaginae, Mobiluncus sp. and M. hominis were determined by quantitative real-time PCR (qPCR).


RESULTS
Clustering by PCR-DGGE revealed differences in microbial structure of the different patient groups. Gardnerella vaginalis, A. vaginae, M. hominis and Mobiluncus sp. were detected at high loads in BV-associated microbiota. Quantification of Lactobacillus spp. showed an inverse correlation with Nugent score while the loads of G. vaginalis, A. vaginae, M. hominis and Mobiluncus sp. indicated a direct correlation with this method.


CONCLUSIONS
Despite Nugent score is considered the gold standard for BV diagnosis, qPCR stands out as a useful tool for bacteria quantification and an alternative for BV diagnosis. Vaginal microbiota is a complex microbial community although there is a common core among BV and non-BV women. Investigation of vaginal microbiota structure may contribute to the development of tools for diagnosis improvement and therapeutic regimen optimization.