PLoS ONE (Jan 2015)
Acinetobacter baumannii Repeatedly Evolves a Hypermutator Phenotype in Response to Tigecycline That Effectively Surveys Evolutionary Trajectories to Resistance.
Abstract
The evolution of hypermutators in response to antibiotic treatment in both clinical and laboratory settings provides a unique context for the study of adaptive evolution. With increased mutation rates, the number of hitchhiker mutations within an evolving hypermutator population is remarkably high and presents substantial challenges in determining which mutations are adaptive. Intriguingly however, hypermutators also provide an opportunity to explore deeply the accessible evolutionary trajectories that lead to increased organism fitness, in this case the evolution of antibiotic resistance to the clinically relevant antibiotic tigecycline by the hospital pathogen Acinetobacter baumannii. Using a continuous culture system, AB210M, a clinically derived strain of A. baumannii, was evolved to tigecycline resistance. Analysis of the adapted populations showed that nearly all the successful lineages became hypermutators via movement of a mobile element to inactivate mutS. In addition, metagenomic analysis of population samples revealed another 896 mutations that occurred at a frequency greater than 5% in the population, while 38 phenotypically distinct individual colonies harbored a total of 1712 mutations. These mutations were scattered throughout the genome and affected ~40% of the coding sequences. The most highly mutated gene was adeS, a known tigecycline-resistance gene; however, adeS was not solely responsible for the high level of TGC resistance. Sixteen other genes stood out as potentially relevant to increased resistance. The five most prominent candidate genes (adeS, rpsJ, rrf, msbA, and gna) consistently re-emerged in subsequent replicate population studies suggesting they are likely to play a role in adaptation to tigecycline. Interestingly, the repeated evolution of a hypermutator phenotype in response to antibiotic stress illustrates not only a highly adaptive strategy to resistance, but also a remarkably efficient survey of successful evolutionary trajectories.