Metabolomics strategy for diagnosing urinary tract infections
Carly C.Y. Chan, Daniel B. Gregson, Spencer D. Wildman, Dominique Bihan, Ryan A. Groves, Raied Aburashed, Thomas Rydzak, Keir Pittman, Nicolas Van Bavel, Ian A. Lewis
Abstract
Metabolomics has emerged as a mainstream approach for investigating complex metabolic phenotypes but has yet to be integrated into routine clinical diagnostics. Metabolomics-based diagnosis of urinary tract infections (UTIs) is a logical application of this technology since microbial waste products are concentrated in the bladder and thus could be suitable markers of infection. We conducted an untargeted metabolomics screen of clinical specimens from patients with suspected UTIs and identified two metabolites, agmatine, and N6-methyladenine, that are predictive of culture-positive samples. We developed a 3.2-min LC-MS assay to quantify these metabolites and showed that agmatine and N6-methyladenine correctly identify UTIs caused by 13 Enterobacterales species and 3 non-Enterobacterales species, accounting for over 90% of infections (agmatine AUC > 0.95; N6-methyladenine AUC > 0.89). These markers were robust predictors across two blinded cohorts totaling 1629 patient samples. These findings demonstrate the potential utility of metabolomics in clinical diagnostics for rapidly detecting UTIs. Microbial catabolites in urine provide a rapid method for detecting urinary tract infections (UTIs). Here, the authors describe an LC-MS metabolomics approach for detecting two catabolites collectively produced by 90% of UTI microbes.