Effect of a probiotic and an antibiotic on the mobilome of the porcine microbiota

Abstract

Introduction: To consider the growing health issues caused by antibiotic resistance from a "one health" perspective, the contribution of meat production needs to be addressed. While antibiotic resistance is naturally present in microbial communities, the treatment of farm animals with antibiotics causes an increase in antibiotic resistance genes (ARG) in the gut microbiome. Pigs are among the most prevalent animals in agriculture; therefore, reducing the prevalence of antibiotic-resistant bacteria in the pig gut microbiome could reduce the spread of antibiotic resistance. Probiotics are often studied as a way to modulate the microbiome and are, therefore, an interesting way to potentially decrease antibiotic resistance. Methods: To assess the efficacy of a probiotic to reduce the prevalence of ARGs in the pig microbiome, six pigs received either treatment with antibiotics (tylvalosin), probiotics (Pediococcus acidilactici MA18/5M; Biopower^® PA), or a combination of both. Their faeces and ileal digesta were collected and DNA was extracted for whole genome shotgun sequencing. The reads were compared with taxonomy and ARG databases to identify the taxa and resistance genes in the samples. Results: The results showed that the ARG profiles in the faeces of the antibiotic and combination treatments were similar, and both were different from the profiles of the probiotic treatment (p < 0.05). The effects of the treatments were different in the digesta and faeces. Many macrolide resistance genes were detected in a higher proportion in the microbiome of the pigs treated with antibiotics or the combination of probiotics and antibiotics. Resistance-carrying conjugative plasmids and horizontal transfer genes were also amplified in faeces samples for the antibiotic and combined treatments. There was no effect of treatment on the short chain fatty acid content in the digesta or the faeces. Conclusion: There is no positive effect of adding probiotics to an antibiotic treatment when these treatments are administered simultaneously.

Keywords: antibiotics resistance; digesta; faeces; gut microbiome; metagenomics; plasmids; swine.

FIGURE 1

Schematic representation of the crossover experimental design. T1, T2, and T3 refer to the treatment periods. The treatments were a macrolide antibiotic (tylvalosin; 250 g/ton of feed), a commercial probiotic (Pediococcus acidilactici MA18/5M, 10⁸ CFUs/day), and a combination of both treatments at the same concentrations as the individual treatments. During the control periods (Ctl0, Ctl1, and Ctl2), the animals were fed the same diet without treatment. Each period lasted 3 weeks.

FIGURE 2

Alpha diversity using Shannon index of the digesta (A) and the faeces (B) and alpha diversity using the Simpson index of the digesta (C) and the faeces (D) for animals treated with the commercial probiotic Pediococcus acidilactici MA18/5M (blue), a macrolide antibiotic (tylvalosin, red), or a combination of both (purple). Data from samples taken before the animals received treatments (Ctl0) are shown in black. Box plots show means and quartiles. No comparison was significant (p > 0.05, Kruskal–Wallis test).

FIGURE 3

Beta diversity represented by a principal coordinate analysis plot using Bray-Curtis dissimilarities of bacterial taxa from the digesta (A), the faeces (B), and all samples (C) for animals treated with the commercial probiotic Pediococcus acidilactici MA18/5M (blue), a macrolide antibiotic (tylvalosin, red), or a combination of both (purple). Data from samples taken before the animals received treatments (Ctl0) are shown in black. Each point represents a sample. The distance between points reflects the difference in microbial composition between samples; closer points indicate higher similarity. The principal axes represent dimensions that maximize variance among samples. Percentages indicate the proportion of variance explained by each axis. The ellipses represent a 95% confidence interval.

FIGURE 4

Antibiotic resistance gene (ARG) score change between the treatments (antibiotics, probiotics, or a combination of both) and their preceding recuperation period in the digesta (A) and the faeces (B) and ARG score change between recuperation periods and the following treatment period in the digesta (C) and the faeces (D). The ARG score, computed using MetaProtMiner (Galiot et al., 2023), for a sample corresponds to the sum of reads aligned to each antibiotic resistance gene, divided by the total gene length and the number of reads for the dataset, multiplied by one million. Only p-values less than 0.05 (Tukey test) are shown.

FIGURE 5

PCoA of the resistome based on the antibiotic resistance gene (ARG) scores during the first recuperation period (Ctl0) and the treatment periods (antibiotics, probiotics, or a combination of both) of the digesta (A), the faeces (B), and all samples (C). The ARG score, computed using MetaProtMiner (Galiot et al., 2023), for a sample corresponds to the sum of reads aligned to each antibiotic resistance gene, divided by the total gene length and the number of reads for the dataset, multiplied by one million. Each point represents a sample. The distance between points reflects the difference in resistance genes composition between samples; closer points indicate higher similarity. The principal axes represent dimensions that maximize variance among samples. Percentages indicate the proportion of variance explained by each axis. The ellipses represent a 95% confidence interval.

FIGURE 6

Hierarchical clustering of the whole-resistome changes caused by the treatments, and a heatmap of the marker genes between probiotic, antibiotic, and a combination of both treatments for samples taken from the digesta (A) and the faeces (B). The samples names correspond to the treatment period of the samples: T1, T2, or T3; the nature of the samples: faeces (F) or digesta (D); and the pig from which the sample was taken: pig 1 to 6. Blue corresponds to probiotic treatment, red to antibiotic treatment, and purple to a combination of both treatments.

FIGURE 7

Linear discriminant analysis (LDA) plot of the marker function, as defined in the Pfam database, in the digesta (A) and the faeces (B). For the digesta, only samples from animals fed with the probiotic had markers (score ≥2 and a p < 0.05).

FIGURE 8

Quantity (mg/mL) of acetic (A), lactic (B), propionic (C), and butyric (D) acid in the digesta and the faeces (****, p < 0.0001, Kruskal–Wallis test). Box plots show means and quartiles.

FIGURE 9

Heatmap of the similarity score between correlated short chain fatty acids and taxa in the digesta (A) and the faeces (B).