Antibiotic dose and nutrient availability differentially drive the evolution of antibiotic resistance and persistence

Author:

Windels Etthel M1234,Cool Lloyd125,Persy Eline2,Swinnen Janne2,Matthay Paul12,Van den Bergh Bram12,Wenseleers Tom5,Michiels Jan12

Affiliation:

1. VIB Center for Microbiology, Flanders Institute for Biotechnology , Kasteelpark Arenberg 20, 3001 Leuven , Belgium

2. Centre of Microbial and Plant Genetics, KU Leuven , 3001 Leuven , Belgium

3. Department of Biosystems Science and Engineering, ETH Zürich , 4056 Basel , Switzerland

4. Swiss Institute of Bioinformatics , 1015 Lausanne , Switzerland

5. Laboratory of Socioecology and Social Evolution, KU Leuven , 3000 Leuven , Belgium

Abstract

Abstract Effective treatment of bacterial infections proves increasingly challenging due to the emergence of bacterial variants that endure antibiotic exposure. Antibiotic resistance and persistence have been identified as two major bacterial survival mechanisms, and several studies have shown a rapid and strong selection of resistance or persistence mutants under repeated drug treatment. Yet, little is known about the impact of the environmental conditions on resistance and persistence evolution and the potential interplay between both phenotypes. Based on the distinct growth and survival characteristics of resistance and persistence mutants, we hypothesized that the antibiotic dose and availability of nutrients during treatment might play a key role in the evolutionary adaptation to antibiotic stress. To test this hypothesis, we combined high-throughput experimental evolution with a mathematical model of bacterial evolution under intermittent antibiotic exposure. We show that high nutrient levels during antibiotic treatment promote selection of high-level resistance, but that resistance mainly emerges independently of persistence when the antibiotic concentration is sufficiently low. At higher doses, resistance evolution is facilitated by the preceding or concurrent selection of persistence mutants, which ensures survival of populations in harsh conditions. Collectively, our experimental data and mathematical model elucidate the evolutionary routes toward increased bacterial survival under different antibiotic treatment schedules, which is key to designing effective antibiotic therapies.

Funder

Research Foundation Flanders

KU Leuven

Flemish Institute for Biotechnology

Publisher

Oxford University Press (OUP)

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