Introduction
Antimicrobial resistance (AMR) poses a significant threat to global health, with Escherichia coli being a prominent pathogen responsible for urinary tract infections, bloodstream infections, and other clinical conditions. Accurate surveillance and prediction of antimicrobial resistance are critical for guiding effective treatment strategies. While databases catalog resistance genes and mutations, understanding their quantitative impact on drug susceptibility remains incomplete. This study aims to quantify the effects of acquiring specific resistance genes on the minimum inhibitory concentrations (MICs) for various antibiotics, providing a more precise interpretative framework.
