Complicated urinary tract infections are severe or life-threatening infections that extend beyond a simple bladderinfection and occur most frequently in hospitalized patients. There are over 2.8 million cases of complicatedurinary tract infections in the U.S. each year, with 20% of cases progressing to urosepsis, leading to nearly150,000 deaths each year. Effective management of complicated urinary tract infections requires the rapididentification of the causative bacterial pathogen(s) and the associated antibiotic resistance profile. The currentstandard of care, however, is urine culture, which requires 2-3 days from specimen collection until actionableinformation to guide patient treatment is generated. Hence, there is an urgent need for diagnostic tools that willallow for the rapid identification of uropathogens and their antimicrobial resistance/sensitivity profile(s). Toaddress this unmet need, Day Zero Diagnostics (DZD) is developing a diagnostic workflow that leverages wholegenome sequencing and machine learning to deliver high resolution species identification and antimicrobialresistance and susceptibility profiling from a patient sample without the need for urine culture. These data willguide evidence-based treatment decisions to improve patient care. The aims of this proposal are to (1)demonstrate ultra-high enrichment of bacterial DNA from a diverse range of species from urine samples and (2)optimize a sample preparation pipeline to deliver an actionable result in six hours or less, a clinically relevanttimeframe for complicated urinary tract infection. The proposed Specific Aims, with quantifiable target metrics,are designed to demonstrate proof-of-concept in advance of the development of a commercial in vitro diagnostic.Upon Phase I completion, Phase II will focus on optimizing the workflow, expanding test capabilities, andanalytical and clinical validation studies.
Public Health Relevance Statement: Complicated urinary tract infections can be deadly, but they are difficult to diagnose and treat. This project is
focused on demonstrating the feasibility of a novel urine test that can identify causative bacterial species and
inform targeted antibiotic treatment. This test holds promise to improve the standard-of-care for hospitalized
patients at risk for urosepsis, including reducing the morbidity, mortality, and economic burden of complicated
urinary tract infections.
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