Vaginitis is a widespread issue for women worldwide, yet current diagnostic tools are lacking. Bacterial vaginosis (BV) is the most prevalent type of vaginitis, found in 10–50% of reproductive-aged women. Current diagnostic methods for BV rely on clinical criteria, microscopy, or the detection of a few microbes by qPCR. However, many vaginal infections lack a single etiological agent and are characterized by changes in the vaginal microbiome community structure (e.g., BV is defined as a loss of protective lactobacilli resulting in an overgrowth of anaerobic bacteria). Shotgun metagenomic sequencing provides a comprehensive view of all the organisms present in the vaginal microbiome (VMB), allowing for a better understanding of all potential etiologies. Here, we describe a robust VMB metagenomics sequencing test with a sensitivity of 93.1%, a specificity of 90%, a negative predictive value of 93.4%, and a positive predictive value of 89.6% certified by Clinical Laboratory Improvement Amendments (CLIA), the College of American Pathologist (CAP), and the Clinical Laboratory Evaluation Program (CLEP). We sequenced over 7000 human vaginal samples with this pipeline and described general findings and comparisons to US census data.

Vaginitis is a widespread issue for women worldwide, yet current diagnostic tools are lacking. Bacterial vaginosis (BV) is the most prevalent type of vaginitis, found in 10-50% of reproductive aged women. Current diagnostic methods for BV rely on clinical criteria, microscopy, or detection of a few microbes by qPCR. However, many vaginal infections lack a single etiological agent and are characterized by changes in the vaginal microbiome community structure (e.g. BV is defined as a loss of protective lactobacilli resulting in an overgrowth of anaerobic bacteria). Shotgun metagenomic sequencing provides a comprehensive view of all the organisms present in the vaginal microbiome (VMB) allowing for a better understanding of all potential etiologies. Here, we describe a robust VMB metagenomics sequencing test with a sensitivity of 93.1%, specificity of 90%, a negative predictive value of 93.4%, and a positive predictive value of 89.6% certified by Clinical Laboratory Improvement Amendments (CLIA), the College of American Pathologist (CAP) and the Clinical Laboratory Evaluation Program (CLEP). We sequenced over 7,000 human vaginal samples with this pipeline and described general findings and comparison to US census data.

Bacterial vaginosis (BV) affects approximately 30% of women annually, with recurrence rates of 50% within 3-6 months despite initial antibiotic treatment. This study evaluates outcomes from a metagenomic-based vaginal microbiome (VMB) test used to personalize BV treatment. A total of 1,159 patients diagnosed with BV received tailored treatment, including antibiotics and adjunctive therapies. Vaginal swabs and symptom data were collected before and after treatment (average 4.4 months). Patients were categorized as responders (symptom improvement) or non-responders (no change or worsening symptoms) based on post-treatment questionnaires. Personalized treatment resulted in a 75.5% response rate, with a recurrence rate of 29.7%. Responders showed a significant reduction in symptom scores (5.2 to 2.4, p< 0.0001). Both groups experienced increased Lactobacillus abundance (responders: 31.1% to 49.9%, p< 0.0001; non-responders: 38.5% to 44.0%, p< 0.05), and decreased BV-associated genera (responders: Gardnerella from 45.1% to 35.2%, p< 0.0001; non-responders: from 43.8% to 37.3%, p< 0.001). Treatment adherence was linked to positive outcomes, with mild adverse events. This study demonstrates that personalized, microbiome-informed therapy improves symptoms and restores vaginal microbiome balance in BV management.