Evolutionary dynamics of combinational antimicrobial treatments

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Evolutionary dynamics of combinational antimicrobial treatments Abstract Due to over-prescription and misuse, antibiotics are losing their efficacy due to emergence and rapid rise of antibiotic-resistant bacteria. Of different types of antibiotics, β-lactams have been prescribed to treat the majority of infections since the discovery of penicillin. Since then, bacterial resistance to β-lactams, mediated by the production of extended spectrum β-lactamase (ESBL) enzymes, has become widespread. Using β-lactamase (Bla) inhibitors can restore the efficacy of β-lactams against resistant bacteria, a strategy which is necessary to preserve existing antibiotics in the face of declining investment in new antibiotics. However, the effect of combination treatment on selection for β-lactam resistance is not well understood. Since Bla production benefits both resistant cells and growth-advantaged sensitive cells, and these benefits may be differentially impacted by the introduction of Bla inhibitor, leading to non-intuitive evolutionary dynamics. Our preliminary work suggests that the evolutionary impact of combination treatment depends on three strain-specific factors: the extent to which producing cells are resistant to the antibiotic at the individual cell level, the extent to which the inhibitor can suppress this resistance, and the burden of Bla production. In particular, for Bla variants that offer a greater degree of private benefit (for the producing cells), the combination treatment can substantially select for the resistant fraction. However, for variants that primarily serve as a public good, the combination treatment will be highly effective in selecting against the resistant cells. Our proposed research will examine these evolutionary dynamics in depth using a combination of mathematical modeling and quantitative experiments. In particular, we will use engineered bacteria as well-controlled model systems to test the predicted evolutionary dynamics. Then, we will test the predicted evolutionary dynamics by using microbial communities consisting of both resistant pathogens and sensitive bacteria. Insights learned from the proposed work have implications for guiding effective design of combination treatments against β-lactam-resistant bacterial pathogens.