Dietary bile acids supplementation protects against Salmonella Typhimurium infection via improving intestinal mucosal barrier and gut microbiota composition in broilers

Abstract

Background: Salmonella Typhimurium (S. Typhimurium) is a common pathogenic microorganism and poses a threat to the efficiency of poultry farms. As signaling molecules regulating the interaction between the host and gut microbiota, bile acids (BAs) play a protective role in maintaining gut homeostasis. However, the antibacterial effect of BAs on Salmonella infection in broilers has remained unexplored. Therefore, the aim of this study was to investigate the potential role of feeding BAs in protecting against S. Typhimurium infection in broilers.

Methods: A total of 144 1-day-old Arbor Acres male broilers were randomly assigned to 4 groups, including non-challenged birds fed a basal diet (CON), S. Typhimurium-challenged birds (ST), S. Typhimurium-challenged birds treated with 0.15 g/kg antibiotic after infection (ST-ANT), and S. Typhimurium-challenged birds fed a basal diet supplemented with 350 mg/kg of BAs (ST-BA).

Results: BAs supplementation ameliorated weight loss induced by S. Typhimurium infection and reduced the colonization of Salmonella in the liver and small intestine in broilers (P < 0.05). Compared to the ST group, broilers in ST-BA group had a higher ileal mucosal thickness and villus height, and BAs also ameliorated the increase of diamine oxidase (DAO) level in serum (P < 0.05). It was observed that the mucus layer thickness and the number of villous and cryptic goblet cells (GCs) were increased in the ST-BA group, consistent with the upregulation of MUC2 gene expression in the ileal mucosa (P < 0.05). Moreover, the mRNA expressions of Toll-like receptor 5 (TLR5), Toll-like receptor 4 (TLR4), and interleukin 1 beta (IL1b) were downregulated in the ileum by BAs treatment (P < 0.05). 16S rDNA sequencing analysis revealed that, compared to ST group, BAs ameliorated the decreases in Bacteroidota, Bacteroidaceae and Bacteroides abundances, which were negatively correlated with serum DAO activity, and the increases in Campylobacterota, Campylobacteraceae and Campylobacter abundances, which were negatively correlated with body weight but positively correlated with serum D-lactic acid (D-LA) levels (P < 0.05).

Conclusions: Dietary BAs supplementation strengthens the intestinal mucosal barrier and reverses dysbiosis of gut microbiota, which eventually relieves the damage to the intestinal barrier and weight loss induced by S. Typhimurium infection in broilers.

Keywords: Salmonella Typhimurium; Bile acid, Broiler; Gut microbiota; Intestinal barrier.

Fig. 1

Experimental design and growth performance of broilers. Schematic diagram of the experimental design (A). The change of feed intake (FI) of broilers at 4 days post infection (dpi) (B). The body weight (BW) of broilers at d 19 (C). The feed intake of broilers from 1 to d 19 (D). The feed conversion ratio (FCR) of broilers from d 1 to 19 (E). n = 8 per group. The data are presented as means ± SEM. ^a–cDifferent lowercase letters indicate that changes between groups are statistically significant. ^#Significant difference between the CON group and ST group. *Significant difference between the ST group and the ST-BA group

Fig. 2

The weight and relative weight of the organs of the broilers. The weight of the liver, spleen, and heart (A) and the relative weight to body weight of liver, spleen, and heart (B). n = 8 per group. The data are presented as the means ± SEM. ^a,bDifferent lowercase letters indicate that changes between groups are statistically significant

Fig. 3

The load of Salmonella in the tissues of broilers. The load of Salmonella in liver (A), jejunum (B) and ileum (C). n = 6 per group. The data are presented as the means ± SEM. ^a–cDifferent lowercase letters indicate that changes between groups are statistically significant

Fig. 4

Small intestinal development and morphology of broilers. The length (A), weight (B) and index (C) of the small intestine in broilers; n = 8 per group. H&E staining (D) and histopathological score of the ileum (E). Statistics of mucosal thickness (F), villus length (G), crypt depth (H) and the ratio of villus height to crypt depth (V/C) (I) in the ileum; n = 4 per group. ^a–cThe data are presented as the means ± SEM. Different lowercase letters indicate that changes between groups are statistically significant

Fig. 5

Intestinal barrier permeability and mucus barrier integrity in the ileum of broilers. D-Lactic acid (D-LA) concentration (A) and diamine oxidase activity (DAO) (B) in serum; n = 8 per group. Representative Alcian blue/periodic acid-Schiff (AB/PAS) images showing mucus layer thickness and the number of goblet cells (C–G); n = 4 per group. The data are presented as the means ± SEM. ^a–cDifferent lowercase letters indicate that changes between groups are statistically significant

Fig. 6

Expression of genes related to the ileal barrier and inflammation. The relative expression of barrier-related genes (A). The relative expression of inflammation-related genes (B). Spearman correlation analysis based on the network diagram (C) and the heatmap (D) at gene expression level (|R| > 0.6, P < 0.05). MUC2, mucin 2; ZO1, zonula occludens 1; CLDN1, claudin-1; JAM2, junctional adhesion molecule 2; TLR4, Toll-like receptor 4; TLR5, Toll-like receptor 5; MYD88, myeloid differentiation factor 88; IL1b, interleukin 1 beta; IL6, interleukin 6; IL8, interleukin 8. The data are presented as the means ± SEM of 8 replicates in each group (n = 8). ^a–cDifferent lowercase letters indicate that changes between groups are statistically significant. ^#P < 0.1, ^*P < 0.05, ^**P < 0.01, ^***P < 0.001

Fig. 7

Microbiota composition and diversity in cecum content of broilers. Venn diagram showing the number of operational taxonomic units (OTUs) (A). Alpha diversity including ACE (B), Chao1 (C), Shannon (D) and Simpson (E) diversity index on OTUs. Beta diversity analysis based on PLS-DA analysis on OTUs (F). Circos (G) and pie (H) graphs of microbiota composition in phylum level. Relative abundance of bacteria at the family (I) and genus level (J). n = 6 per group. The data are presented as means ± SEM

Fig. 8

Differentially abundant bacteria in the gut microbiota among groups. The differentially abundant bacteria among the groups are presented in the LDA cladogram generated via LEfSe analysis (P < 0.05, LDA > 3.0) (A and B). Bubble diagram showing significantly different microbiota at the phylum and family levels (C). Significantly different microbiota at the genus level (D–K). n = 6 per group. The data are presented as the means ± SEM. ^a,bDifferent lowercase letters indicate that changes between groups are statistically significant

Fig. 9

Correlation analysis. Spearman correlation analysis based on the network diagram (A) and the heatmap (B) between the microbiota and both growth performance and serum indices (|R| > 0.6, P < 0.05). Spearman correlation analysis based on a heatmap of the microbiota (|R| > 0.6, P < 0.05) (C). ^#P < 0.1, ^*P < 0.05, ^**P < 0.01, ^***P < 0.001