Abstract

BackgroundVaginal microbiome studies frequently report diversity metrics and communities of microbiomes associated with reproductive health outcomes. Reports of Streptococcus agalactiae (also known as Group B Streptococcus or GBS), the leading cause of neonatal infectious morbidity and mortality, are notably lacking from the studies of the vaginal microbiome, despite being a known contributor to preterm birth and other complications. Therefore, the purpose of this systematic review was to explore the frequency of GBS reporting in vaginal microbiome literature pertaining to pregnancy and to examine methodological bias that contributes to differences in species and genus-level microbiome reporting. Lack of identification of GBS via sequencing-based approaches due to methodologic or reporting bias may result incomplete understanding of bacterial composition during pregnancy and subsequent birth outcomes.MethodologyA systematic review was conducted following the PRISMA guideline. Three databases (PubMed, CINAHL, and Web of Science) were used to identify papers for review based on the search terms “vaginal microbiome”, “pregnancy”, and “16S rRNA sequencing”. Articles were evaluated for methods of DNA extraction and sequencing, 16S region, taxonomy classification database, number of participants or vaginal specimens, and pregnancy trimester.ResultsForty-five research articles reported employing a metagenomic approach or 16S approach for vaginal microbiome analysis during pregnancy that explicitly reported taxonomic composition and were included in this review. Less than 30% of articles reported the presence of GBS (N = 13). No significant differences in methodology were identified between articles that reported versus did not report GBS. However, there was large variability across research methods used for vaginal microbiome analysis and species-level bacterial community reporting.ConclusionConsiderable differences in study design and data formatting methods may contribute to underrepresentation of GBS, and other known pathogens, in existing vaginal microbiome literature. Previous studies have identified considerable variation in methodology across vaginal microbiome studies. This study adds to this body of work because in addition to laboratory or statistical methods, how results and data are shared (e.g., only analyzing genus level data or 20 most abundant microbes), may hinder reproducibility and limit our understanding of the influence of less abundant microbes. Sharing detailed methods, analysis code, and raw data may improve reproducibility and ability to more accurately compare microbial communities across studies.

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