A common outcome of antibiotic exposure in patients and in vitro is the evolution of a hypermutator phenotype that enables rapid adaptation by pathogens. While hypermutation is a robust mechanism for rapid adaptation, it requires trade-offs between the adaptive mutations and the more common “hitchhiker” mutations that accumulate from the increased mutation rate. Using quantitative experimental evolution, we examined the role of hypermutation in driving adaptation of Pseudomonas aeruginosa to colistin. Metagenomic deep sequencing revealed 2,657 mutations at > 5% frequency in 1,197 genes and 761 mutations in 29 end point isolates. By combining genomic information, phylogenetic analyses, and statistical tests, we showed that evolutionary trajectories leading to resistance could be reliably discerned. In addition to known alleles such as pmrB, hypermutation allowed identification of additional adaptive alleles with epistatic relationships. Although hypermutation provided a short-term fitness benefit, it was detrimental to overall fitness. Alarmingly, a small fraction of the colistin adapted population remained colistin susceptible and escaped hypermutation. In a clinical population, such cells could play a role in re-establishing infection upon withdrawal of colistin. We present here a framework for evaluating the complex evolutionary trajectories of hypermutators that applies to both current and emerging pathogen populations.ImportanceBacteria can increase mutation rates in response to stress as an evolutionary strategy to avoid extinction. However, the complex mutational landscape of hypermutators makes it difficult to distinguish truly adaptive mutations from hitchhikers that follow similar evolutionary trajectories. We provide a framework for evaluating the complex evolutionary trajectories of hypermutators that can be applied to both current and emerging pathogen populations. Using Pseudomonas aeruginosa evolving to colistin as a model system, we examine the essential role of hypermutation in the evolution of resistance. Additionally, our results highlight the presence of a subset of cells that survive and remain susceptible during colistin exposure which can serve as a reservoir for re-infection upon withdrawal of the drug in clinical infections. This study provides a broad understanding of hypermutation during adaptation and describes a series of analyses that will be useful in identifying adaptive mutations in well annotated and novel bacterial mutator populations.
