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Evolution of Antibiotic Resistance through a Multi-Peaked Fitness Landscape
Antibiotic resistance is a growing public health problem. Prolonged treatment times due to drug resistant pathogens increase human suffering and health care costs. Understanding the genetic changes responsible for elevated drug resistance can inform novel strategies for combating drug resistance. In my talk, I will introduce a novel automated microbial selection device, the “morbidostat”, which we developed to study the long-term evolution of antibiotic resistance. The morbidostat dynamically adjusts drug concentrations to maintain nearly constant inhibition of bacterial growth even as bacterial populations become more and more resistant. Using the morbidostat and whole genome sequencing, we investigated the genetic trajectories underlying the evolution of resistance to three clinically important drugs: chloramphenicol, doxycycline and trimethoprim. Chloramphenicol and doxycycline resistance evolved smoothly through diverse sets of mutations. Conversely, trimethoprim resistance evolved in a stepwise manner, through mutations almost exclusively restricted to the gene encoding the target enzyme dihydrofolate reductase (DHFR). The evolution of trimethoprim resistance displayed three striking properties: (1) a limited set of mutations were acquired repeatedly in similar orders; (2) multiple resistant endpoints with different combinations of mutations existed; and (3) some genetic trajectories included reversion and conversion of mutations. Finally, I will summarize the synthetic construction and analysis of all possible combinations of trimethoprim resistance conferring mutations targeting DHFR. Our study demonstrates that trimethoprim resistance evolves through an extremely rugged fitness landscape with direct and indirect paths leading to multiple resistance peaks. |
Erdal Toprak
Southwestern University |