Quantifying the real-world impact of antibiotic use and genetic determinants of resistance on gonococcal dynamics

The dynamics of antimicrobial resistance in bacterial populations are influenced by the fitness impact of genetic determinants of resistance and antibiotic pressure. However, estimates of real-world fitness impact have been lacking. To address this gap, we developed a hierarchical Bayesian phylodynamic model to quantify contributions of resistance determinants to strain success in a 20-year collection of Neisseria gonorrhoeae isolates. Fitness contributions varied with antibiotic use, which over this period included ciprofloxacin, cefixime, ceftriaxone and azithromycin, and genetic pathways to phenotypically identical resistance conferred distinct fitness effects. These findings were supported by competition experiments both in vitro and in the mouse model of gonococcal infection. Quantifying these fitness contributions to lineage dynamics reveals opportunities for investigation into other genetic and environmental drivers of fitness. This work thus establishes a method for linking pathogen genomics and antibiotic use to define factors shaping ecological trends.