The propensity of pathogens to evolve resistance to antibiotics used in clinical infectious disease therapeutics has been an increasing concern in recent decades. Acquisition of resistance often translates into treatment failure and puts patients at risk of serious adverse outcomes. Current laboratory testing of antibiotic susceptibility does not account for the different microenvironments that bacteria encounter within the human body, providing results that often do not translate into the clinic. Our goal is to better understand evolutionary strategies employed by in development of resistance in distinct environments.

We used adaptive laboratory evolution (ALE) to generate isogenic strains resistant to several antibiotics. Different media were used to mimic distinct environments and multi-omics approaches applied in the understanding of resistance mechanisms.

Evolved strains presented phenotypes similar to those observed in clinical resistant isolates. Mutational analysis indicated that resistance was specific and condition-dependent. Distinct mutations led to resistance phenotypes under a particular environmental condition, but these mutations did not necessarily translate into resistance under a different environmental condition. Furthermore, resistant strains possessed distinct transcriptional landscapes, even when the same systems were mutated, suggesting that similar evolutionary paths translate into distinct resistance mechanisms.

We identified several resistance mechanisms employed by that were not only environment-dependent, but also environment specific. Additionally, we showed that ALE can be applied in pathogens of interest to study antibiotic resistance evolution and prediction of clinical resistance mechanisms, as supported by the significant overlap of mutations identified via ALE and those reported in clinical isolates.

  • This is an open-access article distributed under the terms of the Creative Commons Attribution License.

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