Role of the urinary microbiome in overactive bladder

This study investigates the fungal component of the urinary microbiome in individuals diagnosed with overactive bladder, a chronic urological condition characterized by urgency, frequency, and nocturia, with or without incontinence. While bacterial dysbiosis in the urinary tract has been increasingly studied in relation to lower urinary tract symptoms, the role of fungal communities (mycobiome) remains poorly understood. This project aims to characterize and compare the diversity, composition, and potential clinical associations of urinary fungal taxa in individuals with OAB versus asymptomatic controls.Urine samples were collected under sterile conditions from adult participants enrolled in a clinical protocol that included detailed symptom profiling and exclusion of active infections via standard culture methods. DNA was extracted using validated methods optimized for low-biomass urine samples. The internal transcribed spacer region of fungal rRNA genes, a widely accepted marker for fungal community profiling, was amplified using ITS1F and ITS2 primers to target the ITS1 region, providing taxonomic resolution across a broad range of fungi. Libraries were prepared with dual-index barcoding and sequenced using high-throughput Illumina MiSeq technology with paired-end reads.Raw reads were subjected to quality control, adapter trimming, and denoising to generate high-resolution amplicon sequence variants. Taxonomic classification was performed using the UNITE fungal ITS database. Analyses included alpha and beta diversity metrics, differential abundance testing, and multivariate modeling to identify fungal signatures associated with OAB diagnosis and symptom severity.The data generated in this study contribute to a growing body of research exploring the non-bacterial components of the human urinary microbiome and may offer insights into novel fungal biomarkers or therapeutic targets for OAB. All sequences have been deposited to the Sequence Read Archive (SRA) to support reproducibility and future meta-analyses.