Abstracts (first author)


Direct benefit of the SOS response vanishes after long term evolution in P. aeruginosa

Author(s): Torres-Barceló C, Moxon R, McWilliam M, MacLean R


Exposure to stressors, such as antibiotics, induces the expression of response pathways that could provide bacteria with a direct fitness benefit, stemming from increased protection against stress, and an indirect fitness benefit, stemming from increased evolvability due to elevated mutagenesis. We have quite a good understanding of the molecular mechanisms of stress response pathways, but quantitative measurements of the direct and indirect fitness benefits and costs associated with stress response pathway expression are lacking. By measuring the competitive fitness of wildtype and LexA mutant (SOS response blocked) strains of P. aeruginosa we show that the SOS response provides with a direct benefit across a range of sub-lethal concentrations of the antibiotic ciprofloxacin. Interestingly, in the absence of the antibiotic, the LexA mutation confers an advantage in the competitive ability and demonstrates the existence of a cost for the cells owning this complex pathway. We also analyse important parameters like cell viability, cell size and growth rate to explain the higher fitness of wildtype during selection with antibiotic. However, we find that the SOS pathway produces no indirect fitness benefit, as demonstrated by the fact that the LexA mutant shows a comparable ability to adapt to ciprofloxacin over a 600 generation selection experiment. Our study clearly demonstrates that natural selection favours the evolution of stress-induced mutagenesis pathways as a result of direct selection for increased stress tolerance and not indirect selection to favour evolvability. Altogether, we contribute with experimental evidence crucial to disentangle if bacterial stress responses play a role in accelerating adaptation to stressors such as antibiotics.


Chairman: Octávio S. Paulo
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XIV Congress of the European Society for Evolutionary Biology

Organization Team
Department of Animal Biology (DBA)
Faculty of Sciences of the University of Lisbon
P-1749-016 Lisbon


Computational Biology & Population Genomics Group