Multi-level regulation of hindgut homeostasis by volatile fatty acid administration in dairy goats: linking microbial metabolism to epithelial inflammation and barrier function

Abstract

This study provided a comprehensive exploration of the nutritional regulation of volatile fatty acids (VFAs) on hindgut microbial metabolism and epithelial homeostasis in dairy goats. Twenty-four goats were orally administered sodium acetate (SA) at 0.8 g/kg of body weight (BW), propionate (SP) at 0.8 g/kg of BW, butyrate (SB) at 0.5 g/kg of BW, or saline (CON) before morning feeding for 12 days (n = 6/group). Serum and hindgut epithelial tissues were collected to measure antioxidant capacity, inflammatory cytokines, and tight junctions. Cecal contents were collected for 16S rRNA sequencing and metabolome analysis, and colonic epithelial cells were harvested for transcriptome sequencing. The data demonstrated that VFAs positively affected hindgut homeostasis. SB reduced serum malondialdehyde levels (P = 0.042), while SA and SP increased intestinal interleukin-10 concentration compared with CON (P < 0.001). All three VFAs enhanced gut barrier functions by increasing tight junctions compared with CON (P < 0.05). The data revealed distinct bacterial abundances and diversities associated with VFA administration, with notable responders including Rikenellaceae dgA-11 gut group, Christensenellaceae R-7 group, and Bacteroides. Metabolome analysis indicated significant changes in metabolic processes, such as purine, arachidonic acid, tyrosine, and tryptophan metabolism. Transcriptome analysis showed that SA and SP influenced endocrine and digestive functions, metal ion homeostasis, and muscle development in the colonic epithelium, with specific immune response pathways enriched in SB. Correlation analysis suggested interactions between hindgut bacteria and derived metabolites and epithelial homeostasis. In short, our study suggested potential strategies for improving gut health and overall well-being in goats through dietary interventions.

Importance: The volatile fatty acids (VFAs), mainly produced by rumen microbiota, play an important role in ruminal metabolic functions and epithelial health, but their impact on the hindgut has received limited attention. Our study highlighted the significant role of VFAs in hindgut bacterial metabolism and homeostasis, providing novel insights into the role of VFAs in regulating hindgut metabolism and physiological homeostasis beyond the rumen.

Keywords: dairy goats; gut bacteria; gut homeostasis; hindgut; volatile fatty acids.

Fig 1

The schematic representation of experimental design, and the bacterial beta diversity and abundance in cecal contents. (A) The schematic representation of experimental design; (B) bacterial beta diversity using principal coordinate analysis (PCoA) plot calculated by unweighted UniFrac distances; (C) component proportions of cecal bacteria at phylum, family, and genus levels of four groups; n = 6 for 16S rRNA sequencing.

Fig 2

Selection of candidate cecal bacteria in response to VFA administration and different bacterial taxonomy. (A) LEfSe analysis of candidate cecal bacteria and different bacterial taxonomy in response to VFA administration at the genus level, only LDA score greater than 3 was marked; (B) cluster heatmap of candidate cecal bacteria of four groups.

Fig 3

The LC-MS metabolome profiles in cecal contents and selection of differential metabolites. (A) The distributions of all metabolites using PCA and OPLS-DA score plots of groups and QC samples; (B) the number of differential metabolites between each VFA and CON in cecal contents; (C) the VIP and log₂(FC) of differential metabolites; (D) the cluster heatmap of differential metabolites of four groups in cecal contents; n = 3 for LC-MS metabolome analysis.

Fig 4

Correlation analysis between differential metabolites and candidate bacteria, and functional enrichment analysis of differential metabolites. (A) Correlation analysis between differential metabolites and candidate bacteria. The analysis is based on the Spearman correlation coefficient. *P < 0.05; ⁺P < 0.01; and ^#P < 0.001; (B) functional enrichment analysis of all differential metabolites using KEGG database of four groups; (C) heatmaps of the abundances of differential metabolites in metabolic pathways of four groups; (D) functional enrichment analysis of differential metabolites of each comparison using KEGG database.

Fig 5

The transcriptome sequencing profiles in colonic epithelium. (A) The PCA using a combined data set of all genes of four groups; (B) the number of up- and downregulated DEGs between each VFA and CON; (C) Venn diagram of the number of single- and co-expressed DEGs between each VFA and CON; (D) heatmap of the expression level of the co-expressed DEGs in four groups; n = 3 for transcriptome sequencing analysis.

Fig 6

The KEGG and GO functional enrichment analyses of DEGs. (A) The functional enrichment analysis of DEGs using the KEGG database; (B) the functional enrichment analysis of DEGs using the GO database.

Fig 7

The interactions between candidate bacteria and homeostasis status, metabolome, and transcriptome sequencing data. (A) Correlation analysis between SA and CON; (B) correlation analysis between SP and CON; (C) correlation analysis between SB and CON; the correlation analysis of candidate bacteria was calculated using Pearson’s correlation coefficient. *P < 0.05; **P < 0.01; and ***P < 0.001. The correlation analysis between candidate bacteria and homeostasis status, metabolome, and transcriptome sequencing data was performed using Mantel’s test. Blue line indicates Mantel’s P < 0.05, red line indicates Mantel’s P < 0.01, and the gray line indicates Mantel’s P > 0.05.