TY - JOUR
T1 - Modeling the bacterial dynamics in the gut microbiota following an antibiotic-induced perturbation
AU - for the CEREMI study group
AU - Guk, Jinju
AU - Bridier-Nahmias, Antoine
AU - Magnan, Mélanie
AU - Grall, Nathalie
AU - Duval, Xavier
AU - Clermont, Olivier
AU - Ruppé, Etienne
AU - d'Humières, Camille
AU - Tenaillon, Olivier
AU - Denamur, Erick
AU - Mentré, France
AU - Guedj, Jérémie
AU - Burdet, Charles
N1 - Publisher Copyright:
© 2022 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.
PY - 2022/7/1
Y1 - 2022/7/1
N2 - Recent studies have highlighted the importance of ecological interactions in dysbiosis of gut microbiota, but few focused on their role in antibiotic-induced perturbations. We used the data from the CEREMI trial in which 22 healthy volunteers received a 3-day course of ceftriaxone or cefotaxime antibiotics. Fecal samples were analyzed by 16S rRNA gene profiling, and the total bacterial counts were determined in each sample by flux cytometry. As the gut exposure to antibiotics could not be experimentally measured despite a marked impact on the gut microbiota, it was reconstructed using the counts of susceptible Escherichia coli. The dynamics of absolute counts of bacterial families were analyzed using a generalized Lotka–Volterra equations and nonlinear mixed effect modeling. Bacterial interactions were studied using a stepwise approach. Two negative and three positive interactions were identified. Introducing bacterial interactions in the modeling approach better fitted the data, and provided different estimates of antibiotic effects on each bacterial family than a simple model without interaction. The time to return to 95% of the baseline counts was significantly longer in ceftriaxone-treated individuals than in cefotaxime-treated subjects for two bacterial families: Akkermansiaceae (median [range]: 11.3 days [0; 180.0] vs. 4.2 days [0; 25.6], p = 0.027) and Tannerellaceae (13.7 days [6.1; 180.0] vs. 6.2 days [5.4; 17.3], p = 0.003). Taking bacterial interaction as well as individual antibiotic exposure profile into account improves the analysis of antibiotic-induced dysbiosis.
AB - Recent studies have highlighted the importance of ecological interactions in dysbiosis of gut microbiota, but few focused on their role in antibiotic-induced perturbations. We used the data from the CEREMI trial in which 22 healthy volunteers received a 3-day course of ceftriaxone or cefotaxime antibiotics. Fecal samples were analyzed by 16S rRNA gene profiling, and the total bacterial counts were determined in each sample by flux cytometry. As the gut exposure to antibiotics could not be experimentally measured despite a marked impact on the gut microbiota, it was reconstructed using the counts of susceptible Escherichia coli. The dynamics of absolute counts of bacterial families were analyzed using a generalized Lotka–Volterra equations and nonlinear mixed effect modeling. Bacterial interactions were studied using a stepwise approach. Two negative and three positive interactions were identified. Introducing bacterial interactions in the modeling approach better fitted the data, and provided different estimates of antibiotic effects on each bacterial family than a simple model without interaction. The time to return to 95% of the baseline counts was significantly longer in ceftriaxone-treated individuals than in cefotaxime-treated subjects for two bacterial families: Akkermansiaceae (median [range]: 11.3 days [0; 180.0] vs. 4.2 days [0; 25.6], p = 0.027) and Tannerellaceae (13.7 days [6.1; 180.0] vs. 6.2 days [5.4; 17.3], p = 0.003). Taking bacterial interaction as well as individual antibiotic exposure profile into account improves the analysis of antibiotic-induced dysbiosis.
U2 - 10.1002/psp4.12806
DO - 10.1002/psp4.12806
M3 - Article
C2 - 35583200
AN - SCOPUS:85130225506
SN - 2163-8306
VL - 11
SP - 906
EP - 918
JO - CPT: Pharmacometrics and Systems Pharmacology
JF - CPT: Pharmacometrics and Systems Pharmacology
IS - 7
ER -