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Genetic and phenotypic precursors of antibiotic resistance in evolving bacterial populations: from single cell to population level analyses

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'Soon after new antibiotics are introduced, bacterial strains resistant to their action emerge. Recently, non-specific factors that promote the later appearance of specific mechanisms of resistance have been found. Some of these so-called global factors (as opposed to specific resistance mechanisms) emerge as major players in shaping the rate of evolution of resistance. For example, a mutation in the mismatch repair system is a global genetic factor that increases the mutation rate and therefore leads to an increased probability to evolve resistance. In addition to global genetic factors, it is becoming clear that global phenotypic factors play a crucial role in resistance evolution. For example, activation of stress responses can also result in an elevated mutation rate and accelerated evolution of drug resistance. A natural question which arises in this context is how sub-populations of phenotypic variants differ in their evolutionary potential, and how that, in turn, affects the rate at which an entire population adapts to antibiotic stress.

I propose a multidisciplinary approach to the systematic and quantitative study of the non-specific factors that affect the mode and tempo of evolution towards antibiotic resistance. Our preliminary results indicate that the presence of dormant bacteria that survive antibiotic treatment affects the rate of resistance evolution in bacterial populations. I will exploit the established expertise of my lab using microfluidic devices for single cell analyses to track the emergence of resistance at the single-cell level, in real-time, and to study the correlation between the phenotype of single bacteria and the probability to evolve resistance. My second approach will take advantage of the recent developments in experimental evolution and high throughput sequencing and combine those with single cells observations for the systematic search of E.coli genes that affect the rate of resistance evolution. We will study replicate populations of E.coli, founded by either laboratory strains or clinical isolates, as they evolve in parallel, under antibiotic stress. Evolved populations will be compared with ancestral populations in order to identify genes and phenotypes that have changed during the evolution of antibiotic resistance. Finally, in silico evolution that simulates the experimental conditions will be developed to analyze the contribution of global factors on resistance evolution.

The evolution of antibiotic resistance is not only a fascinating demonstration of the power of evolution but also represents one of the major health threats today. I anticipate that this multidisciplinary study of the global factors that influence the evolution of resistance, from the single cell to the population level, will shed light on the mechanisms used by bacteria to accelerate evolution in general, as well as provide clues as to how to prevent the emergence of antibiotic resistance.'