SUMMARY Uropathogenic Escherichia coli secrete siderophores during human infections. Although siderophores are classically defined by their ability to bind ferric ions, the virulence-associated siderophore yersiniabactin was recently found to bind divalent copper ions during urinary tract infections. Here we use a mass spectrometric approach to determine the extent of non-ferric metal interactions by yersiniabactin and its TonB-dependent outer membrane importer FyuA. In addition to copper, iron and gallium ions, yersiniabactin was also observed to form stable nickel, cobalt, and chromium ion complexes. In E. coli, copper(II) and all other non-ferric yersiniabactin complexes were imported by FyuA in a TonB-dependent manner. Among metal-yersiniabactin complexes, copper(II) yersiniabactin is predicted to be structurally distinctive and was the only complex not to competitively inhibit ferric yersiniabactin import. These results are consistent with yersiniabactin as part of a metallophore system able to prioritize ferric complex uptake in high copper environments.

We describe the rapid and ongoing emergence across multiple US cities of a new multidrug-resistant Escherichia coli clonesequence type (ST) 1193-resistant to fluoroquinolones (100%), trimethoprim-sulfamethoxazole (55%), and tetracycline (53%). ST1193 is associated with younger adults (age <40 years) and currently comprises a quarter of fluoroquinolone-resistant clinical E. coli urine isolates.

Increasing antibiotic resistance among uropathogenic Escherichia coli (UPEC) is driving interest in therapeutic targeting of nonconserved virulence factor (VF) genes. The ability to formulate efficacious combinations of antivirulence agents requires an improved understanding of how UPEC deploy these genes. To identify clinically relevant VF combinations, we applied contemporary network analysis and biclustering algorithms to VF profiles from a large, previously characterized inpatient clinical cohort. These mathematical approaches identified four stereotypical VF combinations with distinctive relationships to antibiotic resistance and patient sex that are independent of traditional phylogenetic grouping. Targeting resistance- or sex-associated VFs based upon these contemporary mathematical approaches may facilitate individualized anti-infective therapies and identify synergistic VF combinations in bacterial pathogens.