Quantifying the real-world impact of antibiotic use and genetic determinants of resistance on gonococcal dynamics
David Helekal, Tatum D. Mortimer, Aditi Mukherjee, Gabriella Gentile, Adriana Le Van, Sofia Blomqvist, Robert A. Nicholas, Ann E. Jerse, Samantha G. Palace, Yonatan H. Grad
TL;DR
This study uses a new model to show how antibiotic use and genetic changes affect the spread of antibiotic-resistant gonorrhea bacteria.
Contribution
A novel hierarchical Bayesian phylodynamic model is developed to quantify real-world fitness impacts of resistance determinants and antibiotic use.
Findings
Fitness contributions of resistance determinants varied with antibiotic use over 20 years.
Genetic pathways leading to the same resistance phenotype had distinct fitness effects.
In vitro and mouse experiments validated the model's findings on lineage dynamics.
Abstract
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…
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Taxonomy
TopicsEvolution and Genetic Dynamics · Reproductive tract infections research · Bacterial Infections and Vaccines