A modelling framework to characterize the impact of antibiotics on the gut microbiota diversity

Abstract

Metagenomic sequencing deepened our knowledge about the role of the intestinal microbiota in human health, and several studies with various methodologies explored its dynamics during antibiotic treatments. We compared the impact of four widely used antibiotics on the gut bacterial diversity. We used plasma and fecal samples collected during and after treatment from healthy volunteers assigned to a 5-day treatment either by ceftriaxone (1 g every 24 h through IV route), ceftazidime/avibactam (2 g/500 mg every 8 h through IV route), piperacillin/tazobactam (1 g/500 mg every 8 h through IV route) or moxifloxacin (400 mg every 24 h through oral route). Antibiotic concentrations were measured in plasma and feces, and bacterial diversity was assessed by the Shannon index from 16S rRNA gene profiling. The relationship between the evolutions of antibiotic fecal exposure and bacterial diversity was modeled using non-linear mixed effects models. We compared the impact of antibiotics on gut microbiota diversity by simulation, using various reconstructed pharmacodynamic indices. Piperacillin/tazobactam was characterized by the highest impact in terms of intensity of perturbation (maximal [IQR] loss of diversity of 27.3% [1.9; 40.0]), while moxifloxacin had the longest duration of perturbation, with a time to return to 95% of baseline value after the last administration of 13.2 d [8.3; 19.1]. Overall, moxifloxacin exhibited the highest global impact, followed by piperacillin/tazobactam, ceftazidime/avibactam and ceftriaxone. Their AUC between day 0 and day 42 of the change of diversity indices from day 0 were, respectively, -13.2 Shannon unit.day [-20.4; -7.9], -10.9 Shannon unit.day [-20.4; -0.6] and -10.1 Shannon unit.day [-18.3; -4.6]. We conclude that antibiotics alter the intestinal diversity to varying degrees, both within and between antibiotics families. Such studies are needed to help antibiotic stewardship in using the antibiotics with the lowest impact on the intestinal microbiota.

Keywords: Human gut microbiota; antibiotics; metagenomics; nonlinear mixed effect modeling; pharmacodynamics; pharmacokinetics.