Gut microbiota-derived LCA mediates the protective effect of PEDV infection in piglets

Abstract

Background: The gut microbiota is a critical factor in the regulation of host health, but the relationship between the differential resistance of hosts to pathogens and the interaction of gut microbes is not yet clear. Herein, we investigated the potential correlation between the gut microbiota of piglets and their disease resistance using single-cell transcriptomics, 16S amplicon sequencing, metagenomics, and untargeted metabolomics.

Results: Porcine epidemic diarrhea virus (PEDV) infection leads to significant changes in the gut microbiota of piglets. Notably, Landrace pigs lose their resistance quickly after being infected with PEDV, but transplanting the fecal microbiota of Min pigs to Landrace pigs alleviated the infection status. Macrogenomic and animal protection models identified Lactobacillus reuteri and Lactobacillus amylovorus in the gut microbiota as playing an anti-infective role. Moreover, metabolomic screening of the secondary bile acids' deoxycholic acid (DCA) and lithocholic acid (LCA) correlated significantly with Lactobacillus reuteri and Lactobacillus amylovorus, but only LCA exerted a protective function in the animal model. In addition, LCA supplementation altered the distribution of intestinal T-cell populations and resulted in significantly enriched CD8⁺ CTLs, and in vivo and in vitro experiments showed that LCA increased SLA-I expression in porcine intestinal epithelial cells via FXR receptors, thereby recruiting CD8⁺ CTLs to exert antiviral effects.

Conclusions: Overall, our findings indicate that the diversity of gut microbiota influences the development of the disease, and manipulating Lactobacillus reuteri and Lactobacillus amylovorus, as well as LCA, represents a promising strategy to improve PEDV infection in piglets. Video Abstract.

Keywords: Gut microbiota; Infection resistance; Macrogenomic; Metabolomic; T cell response.

Fig. 1

Differences in PEDV infection between Min pigs and Landrace pigs. A PEDV infection model in Min pigs and Landrace pigs (n=10/group) (M-CON, Min pigs challenged with PBS; M-PEDV, Min pigs challenged with PEDV; L-CON, Landrace pigs challenged with PBS; L-PEDV, Landrace pigs challenged with PEDV). Comparative analysis of survival (B), weight loss (C), and diarrhea (D) in each group of piglets. E Comparison of histopathological changes (H&E staining) and PEDV viral load in the jejunum of piglets on day 8 post-infection. The left image is scanned at a magnification of 40×, and the right image is scanned at a magnification of 200×. F Analysis of average fluorescence intensity. G Histopathological scoring of tissues. The results are presented as the means ± SD, and statistical significance was calculated by t tests for two groups and one-way ANOVA for four groups. *P < 0.05; **P < 0.01; ****P < 0.0001

Fig. 2

Differences in the gut microbes of Min pigs and Landrace pigs. A Comparative analysis of intestinal microbial OTUs of M-CON, M-PEDV, L-CON, and L-PEDV pigs. B PCoA analysis based on weighted UniFrac distances to identify microbial structural changes. Comparative analysis of Chao1 (C), Shannon (D), observed species (E), and Simpson (F) indices among different groups. The top 10 species at the phylum (H) and genus (I) levels among different groups. G LEfSe counted species with LDA scores greater than 4 between groups and screened for statistically significant differences in biomarkers. J Analysis of LEfSe evolutionary branches using differential biomarkers. The results are presented as the means ± SD, and statistical significance was calculated by one-way ANOVA. *P < 0.05; **P < 0.01; ***P <0.001; ****P < 0.0001

Fig. 3

Gut microbes mediate the protective effect of PEDV in Min pigs. A FMT model in Min pigs and Landrace pigs (NC, Landrace pigs without FMT treatment, n=5; L donor, Landrace pigs treated with FMT from Landrace pigs, n=8; M donor, Landrace pigs treated with FMT from Min pigs, n=8). Comparative analysis of survival (D), weight loss (B), and diarrhea (C) in each group of piglets. (G) Comparison of histopathological changes (H&E staining) and PEDV viral load in the jejunum of piglets on day 8 post-infection. The left image is scanned at a magnification of 40×, and the right image is scanned at a magnification of 200×. E Analysis of average fluorescence intensity. F Histopathological scoring of tissues. The results are presented as the means ± SD, and statistical significance was calculated by t tests for two groups and one-way ANOVA for four groups. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001

Fig. 4

Metagenomic analysis of gut microbiota in M-CON and M-PEDV piglets. A Gene number distribution of M-CON pig and M-PEDV pig gut microbes (n=8/group). B Analysis of significantly upregulated (top 4) and downregulated (top 4) species in the abundance table. C Species comparison analysis (top 10). D LEfSe analysis (LDA score > 4). Functional annotation and abundance information of the samples in the KEGG (E) and eggNOG (G) databases and clustering at the level of functional differences. F Functional annotation and statistics of samples in the CAZy database. The results are presented as the means ± SD, and statistical significance was calculated by one-way ANOVA. ****P < 0.0001

Fig. 5

Efects of Lactobacillus reuteri and Lactobacillus amylovorus on PEDV infection in piglets. Lactobacillus reuteri and Lactobacillus amylovorus alleviate PEDV infection. A Protective model of Lactobacillus reuteri and Lactobacillus amylovorus in piglets (Am, Min pigs gavaged with Lactobacillus amylovorus; Re, Min pigs gavaged with Lactobacillus reuteri; Am/Re, Min pigs gavaged with Lactobacillus amylovorus and Lactobacillus reuteri; PBS, Min pigs gavaged with PBS; NC, normal control group). Comparative analysis of survival (B), weight loss (C), and diarrhea (D) in each group of piglets. E Analysis of average fluorescence intensity. F Comparison of histopathological changes (H&E staining) and PEDV viral load in the jejunum of piglets on day 8 post-infection. The left image is scanned at a magnification of 40×, and the right image is scanned at a magnification of 200×. G Histopathological scoring of tissues. The results are presented as the means ± SD, and statistical significance was calculated by one-way ANOVA. *P < 0.05; **P < 0.01; ****P < 0.0001

Fig. 6

Untargeted metabolomic analysis of M-CON and M-PEDV piglet gut contents. A Partial least squares discrimination analysis (PLS-DA) (n=8/group). B Correlation of differentially abundant metabolites (top 30) with a significance of P<0.05. C Volcano plot analysis of differentially abundant metabolites with a threshold of VIP > 1.0, FC > 1.5, or FC < 0.667, and P-value < 0.05. D Metastats analysis counted the significantly up and downregulated differential metabolites (top 8). E Functional comparative analysis of metabolic components in the KEGG database (top 20). F Hierarchical clustering analysis of metabolic expression patterns. G Correlation analysis between macrogenomics and metabolomics based on Pearson correlation coefficient. The results are presented as the means ± SD, and statistical significance was calculated by one-way ANOVA. ****P < 0.0001

Fig. 7

Efects of DCA and LCA on PEDV infection in piglets. A Protective model of DCA and LCA in piglets. Comparative analysis of survival (B), weight loss (C), and diarrhea (D) in each group of piglets. E Analysis of average fluorescence intensity. F Comparison of histopathological changes (H&E staining) and PEDV viral load in the jejunum of piglets on day 8 post-infection. The left image is scanned at a magnification of 40×, and the right image is scanned at a magnification of 200×. G Histopathological scoring of tissues. The results are presented as the means ± SD, and statistical significance was calculated by one-way ANOVA. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001

Fig. 8

Single-cell RNA sequencing analysis of piglet intestines. A Workflow for single-cell and RNA-seq of isolated T cells from pigs. B Dimensionality reduction analysis based on the UMAP algorithm, with the number of clusters corresponding to those listed in C. C Heatmap clustering data from single-cell analysis of LCA-treated or untreated groups, where the cell clusters are indicated by the upper color block. The signature genes that were differentially expressed in each cluster are shown on the far right, and the names of the subgroups of cell clusters are shown on the far left. D Percentage of cells in the LCA-treated or untreated group in the cluster. E Volcano plot for differential genetic screening of cells in the LCA-treated or untreated groups. Analysis of the expression of the marker genes CD8A, CD8B, GZMA, PRF1, CCL5, and GNLY in cells from LCA-treated or untreated groups by UMAP (F) and cytogenetic enrichment (G) methods. Differential gene function analysis of the CD8⁺ CTL cluster in the KEGG (H) and GO (I) databases

Fig. 9

Mechanistic analysis of the protective effect of LCA. GZMB (A), GZMA (E), and PRF (G) expression in CD3⁺CD8⁺ T cells was measured by flow cytometry on day 8 after PEDV infection in piglets, and the proportions of GZMB (B), GZMA (C), and PRF (D) cells were statistically analyzed (n=3). F Cell proliferation assay of CD8⁺ cells treated with 10/20 μM LCA and anti-CD3/28 for 12/24/48 h using CFSE labeling (n=3). H Cell proliferation ratio of CD8⁺ cells at 12/24/48 h (n=3). I SLA-I expression was analyzed by flow cytometry after 10/20 μM LCA treatment of IPEC-J2 cells for 12 h and was statistically analyzed (N) (n=3). O IPEC-J2 cells were treated with 10/20 μM LCA for 12 h before cell lysis and subsequent ELISA for SLA-I expression (n=3). M The expression of SLA-I was analyzed by flow cytometry in the presence and absence of SBI-115 and Gly-β-MCA in IPEC-J2 cells treated with 20 μM LCA for 12 h, and was statistically analyzed (Q) (n=3). P SLA-I expression was analyzed by flow cytometry in the presence and absence of CCDC and GW4064 in IPEC-J2 cells treated with 20 μM LCA for 12 h, and was statistically analyzed (R) (n=3). The results are presented as the means ± SD, and statistical significance was calculated by one-way ANOVA. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001

Fig. 10

Mechanisms of PEDV infection alleviation by the gut microbes. Bile acids are produced in the liver and enter the intestine via the digestive system. Once in the intestine, primary bile acids may be broken down into LCA by the bacteria Lactobacillus amylovorus and Lactobacillus reuteri by increasing their expression of 7-alpha-hydroxylsteroid dehydrogenase and choloylglycine hydrolase to thus catabolize bile acids to LCA. LCA increases SLA-I expression in porcine intestinal epithelial cells via FXR, which allows accelerated recruitment of CD8⁺ CTLs to PEDV-infected target cells, followed by efficient clearance of target cells by releasing killing factors such as granzyme and perforin, thereby alleviating PEDV infection. The mechanisms diagram was created using BioRender.com