Pleiotropy complicates a trade-off between phage resistance and antibiotic resistance

多效性使噬菌体抗性和抗生素抗性之间的权衡变得复杂

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作者:Alita R Burmeister, Abigail Fortier, Carli Roush, Adam J Lessing, Rose G Bender, Roxanna Barahman, Raeven Grant, Benjamin K Chan, Paul E Turner

Abstract

Bacteria frequently encounter selection by both antibiotics and lytic bacteriophages. However, the evolutionary interactions between antibiotics and phages remain unclear, in particular, whether and when phages can drive evolutionary trade-offs with antibiotic resistance. Here, we describe Escherichia coli phage U136B, showing it relies on two host factors involved in different antibiotic resistance mechanisms: 1) the efflux pump protein TolC and 2) the structural barrier molecule lipopolysaccharide (LPS). Since TolC and LPS contribute to antibiotic resistance, phage U136B should select for their loss or modification, thereby driving a trade-off between phage resistance and either of the antibiotic resistance mechanisms. To test this hypothesis, we used fluctuation experiments and experimental evolution to obtain phage-resistant mutants. Using these mutants, we compared the accessibility of specific mutations (revealed in the fluctuation experiments) to their actual success during ecological competition and coevolution (revealed in the evolution experiments). Both tolC and LPS-related mutants arise readily during fluctuation assays, with tolC mutations becoming more common during the evolution experiments. In support of the trade-off hypothesis, phage resistance via tolC mutations occurs with a corresponding reduction in antibiotic resistance in many cases. However, contrary to the hypothesis, some phage resistance mutations pleiotropically confer increased antibiotic resistance. We discuss the molecular mechanisms underlying this surprising pleiotropic result, consideration for applied phage biology, and the importance of ecology in evolution of phage resistance. We envision that phages may be useful for the reversal of antibiotic resistance, but such applications will need to account for unexpected pleiotropy and evolutionary context.

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