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Spatiotemporal Dynamics of Collective Antibiotic Resistance in an Opportunistic Pathogen
[摘要] Antibiotic resistance is a critical obstacle that threatens our ability to successfully treat bacterial infections. While a great deal is known about the molecular mechanisms that underlie resistance, much less is known about how these localized molecular events contribute to dynamics and evolution at the scale of the microbial community. In this work, I combine quantitative laboratory experiments on bacterial communities with mathematical modeling to investigate the effects of antibiotic exposure on populations of textit{E. faecalis}, an opportunistic human pathogen, across multiple length scales. In spatially-extended, surface associated communities (biofilms), I find that subinhibitory concentrations of lysis-inducing antibiotics can promote biofilm formation, a counterintuitive phenomenon driven by an interplay between inhibitory effects of antibiotics and drug-induced cell lysis, which enhances biofilm formation through the release of extracellular DNA (eDNA). As drug concentration is increased to inhibitory levels, biofilms are characterized by micron-scale spatial organization, with drug-sensitive ancestral cells surrounded by protective sub-populations of enzyme-producing resistant cells. This cooperative resistance— where genetically resistant cells promote survival of neighboring drug-sensitive cells— leads to rich dynamical behavior on longer length scales. Specifically, in planktonic populations of sensitive and resistant cells, we observe bistability between population survival and extinction, quasi-stable co-existence at otherwise inhibitory drug concentrations, and damped oscillations due to ecological feedback between the population and the environment. Furthermore, I show that temporally varying dosing regimens can be used to minimize population size without requiring more total drug. My results highlight the important roles of intercellular cooperation, spatial heterogeneity, and environmental dynamics in shaping the growth and evolution of microbial communities exposed to antibiotics.
[发布日期]  [发布机构] University of Michigan
[效力级别] Population Dynamics [学科分类] 
[关键词] Bacterial Cooperation;Population Dynamics;Antibiotic Resistance;Biofilms;Microbiology and Immunology;Physics;Science;Biophysics [时效性] 
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