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Over the last decade, it has become clear that the bladder and lower urinary tract are not sterile environments, but host a community of microbes like many other body sites. The bacteria, fungi, and viruses that reside in the urinary tract, commonly called the urinary microbiome, appear to play a role in bladder health and are altered in common bladder disorders such as urgency urinary incontinence. However, our knowledge of this unique microbial community is stunted by the difficulties in obtaining accurate measurements. This proposal aims to enhance, harden, and validate a framework for accurately measuring the mixture of microbes that make up the urinary microbiome directly from urine specimens. This framework includes integrating sequencing data with measures of microbial load after adjusting for external contaminant DNA and individual bacterial sequencing efficiencies. Methods developed will enable urinary microbiome researchers to better design future experiments and re-evaluate previously collected data to obtain a more accurate, quantitative measure of individual microbes. In addition to supporting a robust representation of the microbes in the lower urinary tract, this will enable integration with other omics data for a systems-level understanding of the urinary microbiome and is a critical step towards integrating information from the urinary microbiome into clinical care.
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