High metabolic potential may contribute to the success of ST131 uropathogenic Escherichia coli.

Uropathogenic Escherichia coli (UPEC) is the predominant cause of urinary tract infection in both hospital and community settings. The recent emergence of multidrug-resistant clones like the O25b:H4-ST131 lineage represents a significant threat to health, and numerous studies have explored the virulence potential of these organisms. Members of the ST131 clone have been described as having variable carriage of key virulence factors, and it has been suggested that additional unidentified factors contribute to virulence. Here we demonstrated that ST131 isolates have high metabolic potential and biochemical profiles that distinguish them from isolates of many other sequence types (STs). A collection of 300 UPEC isolates recovered in 2007 and 2009 in the Northwest region of England were subjected to metabolic profiling using the Vitek2 Advanced Expert System (AES). Of the 47 tests carried out, 30 gave a positive result with at least one of the 300 isolates examined. ST131 isolates demonstrated significant association with eight tests, including those for peptidase, decarboxylase, and alkalinization activity. Metabolic activity also correlated with antibiotic susceptibility profiles, with resistant organisms displaying the highest metabolic potential. This is the first comprehensive study of metabolic potential in the ST131 lineage, and we suggest that high metabolic potential may have contributed to the fitness of members of the ST131 clone, which are able to exploit the available nutrients in both the intestinal and urinary tract environments

Implementation of Fourier transform infrared spectroscopy for the rapid typing of uropathogenic Escherichia coli.

In this paper, we demonstrate that Fourier transform infrared (FT-IR) spectroscopy is able to discriminate rapidly between uropathogenic Escherichia coli (UPEC) of key lineages with only relatively simple sample preparation. A total of 95 bacteria from six different epidemiologically important multilocus sequence types (ST10, ST69, ST95, ST73, ST127 and ST131) were used in this project and principal component-discriminant function analysis (PC-DFA) of these samples produced clear separate clustering of isolates, based on the ST. Analysis of data using partial least squares-discriminant analysis (PLS-DA), incorporating cross-validation, indicated a high prediction accuracy of 91.19% for ST131. These results suggest that FT-IR spectroscopy could be a useful method for the rapid identification of members of important UPEC STs