Journal
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
Volume 24, Issue 14, Pages -Publisher
MDPI
DOI: 10.3390/ijms241411839
Keywords
Trichomonas vaginalis; ITS; mycobiome; amplicon; molBV; molecular diagnosis
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This study presents a bioinformatics approach to detecting prevalent Trichomonas vaginalis infections using ITS1 amplicon next-generation sequencing. This method allows for high-throughput testing of DNA from large-scale epidemiological studies.
Trichomoniasis, caused by Trichomonas vaginalis (TV), is the most common non-viral sexually transmitted infection (STI) worldwide, affecting over 174 million people annually and is frequently associated with reproductive co-morbidities. However, its detection can be time-consuming, subjective, and expensive for large cohort studies. This case-control study, conducted at the Mount Sinai Adolescent Health Center in New York City, involved 36 women with prevalent TV infections and 36 controls. The objective was to examine Internal Transcribed Spacer region-1 (ITS1) amplicon-derived communities for the detection of prevalent TV infections with the same precision as clinical microscopy and the independent amplification of the TV-specific TVK3/7 gene. DNA was isolated from clinician-collected cervicovaginal samples and amplified using ITS1 primers in a research laboratory. Results were compared to microscopic wet-mount TV detection of concurrently collected cervicovaginal samples and confirmed against TV-specific TVK3/7 gene PCR. The area under the receiver operating characteristics curve (AUC) for diagnosing TV using ITS1 communities was 0.92. ITS1 amplicons displayed an intra-class correlation coefficient (ICC) of 0.96 (95% CI: 0.93-0.98) compared to TVK3/7 PCR fragment testing. TV cases showed an increased risk of bacterial vaginosis (BV) compared to the TV-negative controls (OR = 8.67, 95% CI: 2.24-48.54, p-value = 0.0011), with no significant differences regarding genital yeast or chlamydia infections. This study presents a bioinformatics approach to ITS1 amplicon next-generation sequencing that is capable of detecting prevalent TV infections. This approach enables high-throughput testing for TV in stored DNA from large-scale epidemiological studies.
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