Effect of Single Dose of Antimicrobial Administration at Birth on Fecal Microbiota Development and Prevalence of Antimicrobial Resistance Genes in Piglets

Abstract

Optimization of antimicrobial use in swine management systems requires full understanding of antimicrobial-induced changes on the developmental dynamics of gut microbiota and the prevalence of antimicrobial resistance genes (ARGs). The purpose of this study was to evaluate the impacts of early life antimicrobial intervention on fecal microbiota development, and prevalence of selected ARGs (ermB, tetO, tetW, tetC, sulI, sulII, and blaC _TX-M) in neonatal piglets. A total of 48 litters were randomly allocated into one of six treatment groups soon after birth. Treatments were as follows: control (CONT), ceftiofur crystalline free acid (CCFA), ceftiofur hydrochloride (CHC), oxytetracycline (OTC), procaine penicillin G (PPG), and tulathromycin (TUL). Fecal swabs were collected from piglets at days 0 (prior to treatment), 5, 10, 15, and 20 post treatment. Sequencing analysis of the V3-V4 hypervariable region of the 16S rRNA gene and selected ARGs were performed using the Illumina Miseq platform. Our results showed that, while early life antimicrobial prophylaxis had no effect on individual weight gain, or mortality, it was associated with minor shifts in the composition of fecal microbiota and noticeable changes in the abundance of selected ARGs. Unifrac distance metrics revealed that the microbial communities of the piglets that received different treatments (CCFA, CHC, OTC, PPG, and TUL) did not cluster distinctly from CONT piglets. Compared to CONT group, PPG-treated piglets exhibited a significant increase in the relative abundance of ermB and tetW at day 20 of life. Tulathromycin treatment also resulted in a significant increase in the abundance of tetW at days 10 and 20, and ermB at day 20. Collectively, these results demonstrate that the shifts in fecal microbiota structure caused by perinatal antimicrobial intervention are modest and limited to particular groups of microbial taxa. However, early life PPG and TUL intervention could promote the selection of ARGs in herds. While additional investigations are required to explore the consistency of these findings across larger populations, these results could open the door to new perspectives on the utility of early life antimicrobial administration to healthy neonates in swine management systems.

Keywords: antimicrobial; fecal; microbiota; neonatal piglets; resistance genes.

FIGURE 1

Taxonomic classification of 16S rRNA gene sequences at the phylum level for control (CONT, n = 4), ceftiofur crystalline free acid (CCFA, n = 4), ceftiofur hydrochloride (CHC, n = 4), oxytetracycline (OTC, n = 4), procaine penicillin G (PPG, n = 4) and tulathromycin (TUL, n = 4) treated piglets at each sampling time points. Only those bacterial phyla that averaged more than 1% of the relative abundance across all samples are displayed.

FIGURE 2

Heatmap cluster analysis of the most relatively abundant genera for control (CONT, n = 4), ceftiofur crystalline free acid (CCFA, n = 4), ceftiofur hydrochloride (CHC, n = 4), oxytetracycline (OTC, n = 4), procaine penicillin G (PPG, n = 4) and tulathromycin (TUL, n = 4) treated piglets at each sampling time point. Only those bacterial genera that averaged more than 1% of the relative abundance across all samples are displayed.

FIGURE 3

Bacterial diversity indices by treatment groups control (CONT, n = 4), ceftiofur crystalline free acid (CCFA, n = 4), ceftiofur hydrochloride (CHC, n = 4), oxytetracycline (OTC, n = 4), procaine penicillin G (PPG, n = 4), and tulathromycin (TUL, n = 4) at different time points (days 0, 5, 10, 15, and 20).

FIGURE 4

Principal coordinate analysis (PCoA) plot of the weighted Unifrac distances by treatment groups [control (CONT, n = 4), ceftiofur crystalline free acid (CCFA, n = 4), ceftiofur hydrochloride (CHC, n = 4), oxytetracycline (OTC, n = 4), procaine penicillin G (PPG, n = 4) and tulathromycin (TUL, n = 4)] at different sampling days. The percent of variation explained by each coordinate is indicated on the axes. Significance between groups was analyzed using analysis of similarity (ANOISM) with 9999 permutations and Bonferroni corrected P-values.

FIGURE 5

(A) Multiple group similarities tree was constructed using weighted Unifrac distances metrics to identify the similarities and differences among antimicrobial treatment groups. (B) Discriminant analysis of the overall fecal microbiota composition in different treatment groups [control (CONT, n = 4), ceftiofur crystalline free acid (CCFA, n = 4), ceftiofur hydrochloride (CHC, n = 4), oxytetracycline (OTC, n = 4), procaine penicillin G (PPG, n = 4) and tulathromycin (TUL, n = 4)] across all the time points. Different mean relative abundances of bacterial genera in fecal microbiota were used as covariates, and sampling groups were used as categorical variables. Differences in fecal microbial profiles of different treatment groups are illustrated by canonical 1 and 2.

FIGURE 6

Heatmap cluster analysis of predicted functional pathways (level 2 KEGG) based on differentially abundant functional features between different treatment groups, and at different sampling days.

FIGURE 7

Stacked bar chart showing the relative abundance of antimicrobial resistance genes (ermB, sulI, sulII, tetC, tetO, bla_CTX–M, and tetW) of each treatment group at each sampling day.

FIGURE 8

(A,B) Line graphs illustrating the difference in relative abundance of ermB and tetW between the control (CONT, n = 4) group, and tulathromycin (TUL, n = 4) group at different sampling days. (C,D) Line graphs illustrating the difference in abundance of antimicrobial resistance genes (ermB and tetW) between the control (CONT, n = 4) group, and procaine penicillin G (PPG, n = 4) treated piglets at each sampling day. ^∗P < 0.05.