Analysis of the vaginal microbiome by next-generation sequencing and evaluation of its performance as a clinical diagnostic tool in vaginitis

Abstract

Introduction: Changes in the vaginal microbiome are associated with vaginal symptoms and diseases. These changes are usually identified through microscopic examination and microbiological culture. Next-generation sequencing (NGS) can detect many more microorganisms in the vaginal microbiome than these traditional methods. Several studies have analyzed vaginal microbiomes with NGS

however, short read lengths and the exclusion of microorganisms other than bacteria are common limitations of these studies. The aim of this study was to analyze the vaginal microbiomes of Korean women using NGS with long read lengths and the inclusion of bacteria as well as other microorganisms. This study also compared NGS with other assays and evaluated its feasibility for vaginitis prediction.

Methods: In total, 89 vaginal swab specimens were collected. Of these, 67 specimens were microscopically examined by Gram-staining and microbiological culture. A GS Junior (454 Life Sciences, Branford, CT, USA) system was used for NGS. The 16S rRNA, internal transcribed spacer (ITS), and Tvk genes were used to detect bacteria, fungi, and Trichomonas vaginalis. Data processing, operational taxonomic unit (OTU) table construction, and chimeric sequence removal were performed with Usearch software. Taxonomic assignment was performed using the Ribosomal Database Project (RDP) website and Basic Local Alignment Search Tool (BLAST) database. A DNA probe assay for Candida spp., Gardnerella vaginalis, and T. vaginalis was performed.

Results: In total, 202,958 reads of the 16S rRNA gene and 7,600 reads of the internal transcribed spacer (ITS) gene were obtained from NGS of 89 specimens. ITS sequences were obtained in the majority of specimens (56.2%). The 16S rRNA sequences and ITS sequences were clustered into 3,259 and 112 OTUs, respectively. The compositions of the intermediate Nugent score group and vaginitis Nugent score group differed from those of the normal score group

however, they were similar to each other. Shannon diversity indices, the number of species, and the fraction of Lactobacillus spp. were significantly different among the three groups. From the NGS data, various predictors of diversity were analyzed to predict vaginitis, and a fraction of Lactobacillus spp. was associated with the highest area under curve (AUC) value (0.8559). NGS and DNA probe assay showed good agreement. NGS and microbiological culture showed 73.1% agreement (range, 86.2–89.7%).

Conclusions: The intermediate Nugent score group and vaginitis group were not significantly different in the microbiome analysis. ITS sequences were common in normal specimens. NGS is a promising tool for examining vaginal microbiomes and diagnosing vaginitis.