Quantifying the impact of treatment history on plasmid-mediated resistance evolution in human gut microbiota.

ABSTRACT: To understand how antibiotic use affects the risk of a resistant infection, we present a computational model of the population dynamics of gut microbiota including antibiotic resistance-conferring plasmids. We then describe how this model is parameterized based on published microbiota data. Finally, we investigate how treatment history affects the prevalence of resistance among opportunistic enterobacterial pathogens. We simulate treatment histories and identify which properties of prior antibiotic exposure are most influential in determining the prevalence of resistance. We find that resistance prevalence can be predicted by 3 properties, namely the total days of drug exposure, the duration of the drug-free period after last treatment, and the center of mass of the treatment pattern. Over

SUBMITTER: Tepekule B 

PROVIDER: S-EPMC6859334 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature