Impact of Antibiotic Gut Exposure on the Temporal Changes in Microbiome Diversity

Abstract

Although the global deleterious impact of antibiotics on the intestinal microbiota is well known, temporal changes in microbial diversity during and after an antibiotic treatment are still poorly characterized. We used plasma and fecal samples collected frequently during treatment and up to one month after from 22 healthy volunteers assigned to a 5-day treatment by moxifloxacin (n = 14) or no intervention (n = 8). Moxifloxacin concentrations were measured in both plasma and feces, and bacterial diversity was determined in feces by 16S rRNA gene profiling and quantified using the Shannon index and number of operational taxonomic units (OTUs). Nonlinear mixed effect models were used to relate drug pharmacokinetics and bacterial diversity over time. Moxifloxacin reduced bacterial diversity in a concentration-dependent manner, with a median maximal loss of 27.5% of the Shannon index (minimum [min], 17.5; maximum [max], 27.7) and 47.4% of the number of OTUs (min, 30.4; max, 48.3). As a consequence of both the long fecal half-life of moxifloxacin and the susceptibility of the gut microbiota to moxifloxacin, bacterial diversity indices did not return to their pretreatment levels until days 16 and 21, respectively. Finally, the model characterized the effect of moxifloxacin on bacterial diversity biomarkers and provides a novel framework for analyzing antibiotic effects on the intestinal microbiome.

Keywords: diversity; dysbiosis; intestinal microbiome; metagenomics; moxifloxacin; nonlinear mixed-effect modelling.

FIG 1

Final compartmental model for plasma and fecal moxifloxacin pharmacokinetics (red) and for bacterial diversity indices (orange). k_tr is the transfer rate between each compartment for the absorption delay; k_a is the absorption rate to the central compartment; k_e is the extraintestinal elimination rate from the central compartment; k₁₂ and k₂₁ are the transfer rates between the central compartment and the peripheral compartment; k_ct1 is the elimination rate from the central compartment to the intestinal tract; k_fc is the transfer rate between the lower gastrointestinal tract and the central compartment; k_t is the transfer rate between the intestinal transit compartments; k_f is the elimination rate from the lower gastrointestinal tract; R_in is the zero-order constant for production of the diversity index; k_out is the first-order elimination rate of the diversity index from the lower gastrointestinal tract. C_f is the concentration in the feces; E_max is the maximal effect of moxifloxacin on the elimination rate of the diversity index; and EC₅₀ is the concentration of moxifloxacin leading to 50% of the maximal effect. Data were available for the 3 compartments with bold boxes. GIT, gastrointestinal tract.

FIG 2

Visual predictive checks for pharmacokinetic model. (A) Plasma concentrations; (B) fecal concentrations. Blue and red lines indicate the observed percentiles (10th, 50th, and 90th percentiles); blue and red ribbons indicate the corresponding 95% confidence intervals. The dashed black lines indicate predicted percentiles. Black points indicate the individual observations.

FIG 3

Visual predictive checks for pharmacodynamic model. The Shannon index is depicted for (A) moxifloxacin-treated subjects and (B) untreated subjects, and the number of OTUs is depicted for (C) moxifloxacin-treated subjects and (D) untreated subjects. Blue and red lines indicate the observed percentiles (10th, 50th, and 90th percentiles); blue and red ribbons indicate the corresponding 95% confidence intervals. The dashed black lines indicate predicted percentiles. Black points indicate the individual observations.

FIG 4

Estimated impact of moxifloxacin on intestinal microbiome in the 14 subjects treated with moxifloxacin. The impact was measured as the area under the curve (AUC) of the change of the Shannon index (A) or number of OTUs (B) from baseline over time, between days 0 and 42 (AUC_D0D24). The AUC is a metric which allows a global view of antibiotic impact on the microbiota, as it takes into account both the extent and the duration of dysbiosis. ID, identifier.