High-throughput analysis of the impact of antibiotics on the human intestinal microbiota composition

J Microbiol Methods. 2013 Mar;92(3):387-97. doi: 10.1016/j.mimet.2012.12.011. Epub 2012 Dec 22.


Antibiotic treatments can lead to a disruption of the human microbiota. In this in-vitro study, the impact of antibiotics on adult intestinal microbiota was monitored in a new high-throughput approach: a fermentation screening-platform was coupled with a phylogenetic microarray analysis (Intestinal-chip). Fecal inoculum from healthy adults was exposed in a fermentation screening-platform to seven widely-used antibiotics during 24h in-vitro fermentation and the microbiota composition was subsequently determined with the Intestinal-chip. Phylogenetic microarray analysis was first verified to be reliable with respect to variations in the total number of bacteria and presence of dead (or inactive) cells. Intestinal-chip analysis was then used to identify and compare shifts in the intestinal microbial composition after exposure to low and high dose (1μgml(-1) and 10μgml(-1)) antibiotics. Observed shifts on family, genus and species level were both antibiotic and dose dependent. Stronger changes in microbiota composition were observed with higher doses. Shifts mainly concerned the bacterial groups Bacteroides, Bifidobacterium, Clostridium, Enterobacteriaceae, and Lactobacillus. Within bacterial groups, specific antibiotics were shown to differentially impact related species. The combination of the in-vitro fermentation screening platform with the phylogenetic microarray read-outs has shown to be reliable to simultaneously analyze the effects of several antibiotics on intestinal microbiota.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Anti-Bacterial Agents / pharmacology*
  • Bacteriological Techniques / methods
  • Biota*
  • Feces / microbiology*
  • Female
  • High-Throughput Screening Assays / methods
  • Humans
  • Male
  • Metagenome / drug effects*
  • Microarray Analysis / methods
  • Middle Aged
  • Models, Theoretical
  • Phylogeny


  • Anti-Bacterial Agents