Speaker
Description
Antimicrobial resistance (AMR) is a rapidly worsening global health issue, with an increasing number of bacterial infections becoming impossible to treat with most drugs. Of serious concern is Acinetobacter baumannii, a nosocomial and highly multidrug resistant (MDR) pathogen. Although resistance is often attained through common mechanisms, such as increased drug efflux and modifications to the drug target, it remains unclear how genetic background affects the evolution of AMR. History (such as, but not limited to, previous antibiotic exposure) is an underappreciated force influencing evolution and can have lasting effects on the genome that alter or constrain paths available for adaptation to antibiotic stress. The force of history in evolving populations likely reduces parallelism and predictability between samples. We are testing the effect of history on the evolution of AMR by utilizing strains with different backgrounds. A. baumannii ATCC 17978 is a highly laboratory adapted strain whereas A. baumannii AB5075-UW is a MDR clinically derived strain. To study the effect of strain genetic background on AMR adaptation we propagated both strains in the presence and absence of tigecycline – a last resort antibiotic used to treat MDR infections. Both strains survived the antibiotic stress and evolved increased antimicrobial resistance. Whole population, whole genome sequencing revealed that the individual mutations and the population dynamics differed between the strains, while the broad mechanism for drug resistance was congruent between them. These differences indicate that even under the strong selective force of antibiotics, history influences the course of evolution. The influence of history could have implications for the predictability of AMR evolution and clinical translatability.
