Dynamics and diversity of vaginal microbiota in bacterial vaginosis among Thai patients treated with metronidazole.

J Infect Public Health

Department of Microbiology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand; Research and Diagnostic Center for Emerging Infectious Diseases (RCEID), Khon Kaen University, Khon Kaen, Thailand.

Published: January 2025

Background: Bacterial vaginosis (BV) is a significant global public health issue due to its high recurrence rate and association with various adverse health effects. Understanding the composition and dynamics of the vaginal microbiota (VMB) is essential for better understanding of vaginal health and for developing effective strategies to improve BV management. The study aimed to determine the composition and diversity of the VMB in Thai women with BV before and after metronidazole (MTZ) treatment, and in healthy women.

Methods: Vaginal samples were collected from 20 women with BV (each sampled at three time points: pre-MTZ treatment, post-MTZ treatment and follow-up) and from 20 healthy women (each sampled once). The VMB was analyzed using 16S rRNA gene sequencing via next-generation sequencing on the Ion Torrent PGM platform.

Results: The VMB in Thai women with BV was predominantly composed of Gardnerella, Prevotella and Fannyhessea (formerly Atopobium), while Lactobacillus dominated in healthy controls. Women with BV exhibited greater bacterial diversity and higher prevalence of anaerobic species compared to healthy women. There was higher diversity and abundance in the VMB from pre-MTZ samples, while post-MTZ and follow-up samples displayed lower diversity. In the follow-up stage, the VMB was divided into two subgroups: the larger cured subgroup, which shifted towards a Lactobacillus-dominated composition resembling healthy controls, and the small treatment-failure subgroup, which exhibited a Gardnerella-dominated profile similar to pre-MTZ.

Conclusions: This study provides valuable insights into the structure and dynamics of the VMB in Thai women with BV before and after treatment, offering potential markers for predicting treatment outcomes.

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Source
http://dx.doi.org/10.1016/j.jiph.2024.102646DOI Listing

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