Urinary tract infections (UTIs) are associated with a high rate of treatment failure, indicating that current antibiotic treatment strategies are not optimal. This project investigates the unexplored hypothesis that urine, the infection microenvironment in UTIs, may lead to distinctly different responses of bacterial pathogens to antibiotic treatments. We will perform unique translational experiments to evaluate to what extent urine can alter antibiotic treatment effects or affect the risk of developing antibiotic resistance. Results from these experiments are then used to design adapted antibiotic treatment strategies for UTIs to reduce treatment failure using mathematical modeling.