Final Report Summary - EVOLOME (Genetic and phenotypic precursors of antibiotic resistance in evolving bacterial populations: from single cell to population level analyses)
The ability of microorganisms to overcome antibiotic treatments is one of the top concerns of modern medicine. The effectiveness of many antibiotics has been reduced by bacteria's ability to rapidly evolve and develop strategies to resist antibiotics. Bacteria achieve this by specific mechanisms that are tailored to the molecular structure or function of a particular antibiotic. For example, bacteria would typically develop drug resistance by evolving a mutation that breaks down the drug. We set out to determine whether resistance occurs directly or whether other strategies evolve before resistance emerges, we followed in real time the evolution under antibiotic treatment. Using the quantitative approach of physicists, our team developed experimental tools to measure precisely the bacterial response to antibiotics and developed a mathematical model of the process. The model led to hypothesize that a daily three-hour dose would enable the bacteria to predict delivery of the drug, and go dormant for that period in order to survive. To test the hypothesis, We delivered antibiotics to bacterial populations in the lab for precisely three hours each day. After only ten days they were able to observe the bacteria using a new survival tactic. When exposed to these repeated cycles of antibiotic treatments, the bacteria evolved an adaptation to the duration of the antibiotic stress by remaining dormant for the treatment period.The results demonstrated that bacteria can evolve within days. Most significantly, it showed for the first time that bacteria can develop a biological clock timer to survive under antibiotic exposure. To further test their hypothesis, the antibiotics were delivered for different periods, exposing three different bacteria populations to repeated daily antibiotic exposures lasting 3, 5, or 8 hours. Remarkably, each of the populations adapted by prolonging their dormant stage to match the exposure duration.With this new understanding of how bacterial populations evolve survival strategies against antibiotics, scientists could develop new approaches for slowing the evolution of antibiotic resistance. More generally, the approach and tools developed in this project should enable to understand the importance of various forms of dormancy on the evolution of cells under stress.