For women in the United States, urinary tract infections (UTIs) are the most frequent diagnosis in emergency departments, comprising 21.3% of total visits. Uropathogenic Escherichia coli (UPEC) causes ~80% of uncomplicated UTIs. To combat this public health issue, it is vital to characterize UPEC strains as well as to differentiate them from commensal strains to reduce the overuse of antibiotics. It has been challenging to determine a consistent genetic signature that clearly distinguishes UPEC from other E. coli strains. Therefore, we examined whether phenotypic data could be predictive of uropathogenic potential. We screened 13 clinical strains of UPEC, isolated from cases of uncomplicated UTI in young otherwise healthy women, in a series of microbiological phenotypic assays using UPEC prototype strain CFT073 and nonpathogenic E. coli strain MG1655 K-12 as controls. Phenotypes included adherence, iron acquisition, biofilm formation, human serum resistance, motility, and stress resistance. By use of a well-established experimental mouse model of UTI, these data were able to predict the severity of the bacterial burden in both the urine and bladders. Multiple linear regression using three different phenotypic assays, i.e., growth in minimal medium, siderophore production, and type 1 fimbrial expression, was predictive of bladder colonization (adjusted R2 = 0.6411). Growth in ex vivo human urine, hemagglutination of red blood cells, and motility modeled urine colonization (adjusted R2 = 0.4821). These results showcase the utility of phenotypic characterization to predict the severity of infection that these strains may cause. We predict that these methods will also be applicable to other complex, genetically redundant, pathogens. IMPORTANCE Urinary tract infections are the second leading infectious disease worldwide, occurring in over half of the female population during their lifetime. Most infections are caused by uropathogenic Escherichia coli (UPEC) strains. These strains can establish a reservoir in the gut, in which they do not cause disease but, upon introduction to the urinary tract, can infect the host and elicit pathogenesis. Clinically, it would be beneficial to screen patient E. coli strains to understand their pathogenic potential, which may lead to the administration of prophylactic antibiotic treatment for those with increased risk. Others have proposed the use of PCR-based genetic screening methods to detect UPEC strains and differentiate them from other E. coli pathotypes; however, this method has not yielded a consistent uropathogenic genetic signature. Here, we used phenotypic characteristics such as growth rate, siderophore production, and expression of fimbriae to better predict uropathogenic potential.
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