Date of Award
Fall 9-5-2025
Degree Type
Thesis
Degree Name
Master of Science (MS)
Department
Bioinformatics & Computational Biology
First Advisor
Catherine Putonti
Abstract
The human urinary microbiome—once thought to be sterile—is now recognized as a dynamic, low-biomass microbial community with potential implications for urinary tract health. Conventional short-read 16S rRNA gene sequencing targeting individual variable regions often lacks the taxonomic resolution needed to distinguish closely related species, while culture-based methods may miss fastidious or low-abundance taxa. We applied full-length 16S rRNA gene sequencing across all nine variable regions to daily urine samples collected from asymptomatic premenopausal female participants. Sequence data were processed with a modified DADA2 pipeline optimized for long reads to generate exact sequence variants. We compared species-level community profiles against both short-read (V4 region) Illumina sequencing and expanded quantitative urine culture (EQUC). Full-length sequencing markedly improved species-level resolution, allowing discrimination of taxa such as Lactobacillus crispatus versus L. iners. It also allowed for the identification and discrimination of species within the same genus, like Gardnerella, Streptococcus, and Ureaplasma—species under-represented or undetected by short-read and culture-based approaches. Long-read profiles revealed resilient community dynamics: despite transient disruptions associated with menstruation or sexual activity, individual microbiomes tended to revert to baseline composition. Full-length 16S rRNA gene sequencing provides enhanced taxonomic resolution and greater sensitivity for profiling the urinary microbiome in low-biomass samples. By offering high‐resolution, longitudinal insights into urinary microbiome fluctuations, this strategy lays the foundation for precision diagnostics and personalized interventions aimed at preserving and restoring urinary tract health.
Recommended Citation
John, Jerrin, "Insights into Female Urinary Microbiota through Long-Read 16S rRNA Sequencing" (2025). Dissertations. 4241.
https://ecommons.luc.edu/luc_diss/4241
