The impact of antibiotic exposure on antibiotic resistance gene dynamics in the gut microbiota of inflammatory bowel disease patients

Abstract

Background: While antibiotics are commonly used to treat inflammatory bowel disease (IBD), their widespread application can disturb the gut microbiota and foster the emergence and spread of antibiotic resistance. However, the dynamic changes to the human gut microbiota and direction of resistance gene transmission under antibiotic effects have not been clearly elucidated.

Methods: Based on the Human Microbiome Project, a total of 90 fecal samples were collected from 30 IBD patients before, during and after antibiotic treatment. Through the analysis workflow of metagenomics, we described the dynamic process of changes in bacterial communities and resistance genes pre-treatment, during and post-treatment. We explored potential consistent relationships between gut microbiota and resistance genes, and established gene transmission networks among species before and after antibiotic use.

Results: Exposure to antibiotics can induce alterations in the composition of the gut microbiota in IBD patients, particularly a reduction in probiotics, which gradually recovers to a new steady state after cessation of antibiotics. Network analyses revealed intra-phylum transfers of resistance genes, predominantly between taxonomically close organisms. Specific resistance genes showed increased prevalence and inter-species mobility after antibiotic cessation.

Conclusion: This study demonstrates that antibiotics shape the gut resistome through selective enrichment and promotion of horizontal gene transfer. The findings provide insights into ecological processes governing resistance gene dynamics and dissemination upon antibiotic perturbation of the microbiota. Optimizing antibiotic usage may help limit unintended consequences like increased resistance in gut bacteria during IBD management.

Keywords: antibiotics resistance genes; drug resistance; gut microbiome; horizontal gene transfer; metagenomics.

Figure 1

Impact of antibiotics on fecal microbiota diversity and composition in IBD patients. (A) NMDS based on the Bray–Curtis distance metric transformed species abundance matrix. Each point represents the bacterial microbiome of an individual sample. Colors indicate different time points. Ellipses represent 95% confidence intervals (CI) around the group clustered centroid. (B) Subtraction of relative abundance of dominant bacteria before and after medication. (C) Relative abundance of differential bacteria in three periods.

Figure 2

The association network of intestinal bacteria in pre-antibiotic usage (A), during antibiotic usage (B), and post-antibiotic cessation (C). Each circle (node) represents a bacterial species, its color represents the bacterial phylum it belongs to and its size represents the number of direct edges that it has. The gray edge is positively correlated and the red edge is negatively correlated. Only significant correlations (−0.7 < r < 0.9, p < 0.05) are displayed.

Figure 3

(A) Box plots showing the relative abundance measured as Transcript per Kilobase per Million mapped reads (TPM) of drug resistance gene (ARG) classes across all samples, stratified by time points. The center horizontal line of box is median, box limits are upper and lower quartiles, whiskers are 1.5× interquartile ranges. (B) NMDS based on the Bray–Curtis distance metric transformed gene TPM matrix. Each point represents the bacterial microbiome of an individual sample. Colors indicate different time points. Ellipses represent 95% confidence intervals (CI) around the group clustered centroid. (C) Procrustes analysis of resistome composition (filled triangles) and species composition (filled circles) of ibd patients at three time points using PCoA ordination. The points are colored based on sampling time points in both groups. The length of line connecting two points indicates the degree of dissimilarity or distance between microbiome and resistome composition of the same sample. (D) The network of ARGs shared among species.

Figure 4

(A) Transmission network of ARGs in species. Each circle (node) represents a bacterial species, its color represents the bacterial phylum it belongs to and its size represents the number of direct edges that it has. (B) Distribution of Bray–Curtis dissimilarity of individual bacteria.