Metatranscriptomic-based metabolic modeling elucidates patient-specific differences in the urinary tract microbiome during infection

Urinary tract infections (UTIs) pose significant health and economic burdens, driving substantial antibiotic use and contributing to antibiotic resistance. To combat antibiotic-resistant UTIs, we adopt a patient-specific metabolic approach to devise treatment strategies. By analyzing pathogens' metabolic traits, we aim to uncover their metabolic dependencies for targeted therapies. Utilizing patient-specific metatranscriptomic data and genome-scale metabolic modeling, we investigate UTIs' metabolic dynamics, creating models that reflect the unique metabolic profiles of patients' urinary microbiomes. Through analyzing bacterial gene expressions and interactions, we identify metabolic markers of UTI pathology, pinpointing metabolites that could inspire new therapeutic directions. Our study highlights the value of a systems biology approach in understanding UTIs' metabolic mechanisms and informing treatments for antibiotic-resistant infections, potentially reducing reliance on antibiotics by exploiting specific metabolic vulnerabilities of pathogens.