Jinju Guk1, Antoine Bridier‐Nahmias1, Aude Bernheim1, Nathalie Grall2,1, Xavier Duval3,1, Olivier Clermont1, Étienne Ruppé2,1, Camille d’Humières2,1, Olivier Tenaillon1, Érick Denamur4,1, France Mentré5,1, Jérémie Guedj1, Charles Burdet5,1
1Université de Paris, IAME, INSERM, Paris, France
2AP‐HP, Hôpital Bichat, Laboratoire de Bactériologie Paris France
3AP‐HP, Hôpital Bichat, Centre d'Investigation Clinique, Inserm CIC 1425 Paris France
4AP‐HP, Hôpital Bichat, Laboratoire de Génétique Moléculaire Paris France
5Département d'Épidémiologie AP‐HP, Hôpital Bichat, Biostatistique et Recherche Clinique Paris France
Tóm tắt
AbstractRecent 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.