Effects of rearing systems (cage versus floor) on the microbial composition and transcriptome of goose ileum.

There is a gradual transition from water to dryland rearing of geese. In this study, we performed 16S rRNA sequencing (16S rRNA-seq) and transcriptome sequencing (RNA-seq) to reveal the effects of cage rearing (CR) and floor rearing (FR) systems on the microbial composition and transcriptome of the goose ileum. Through 16S rRNA-seq, Linear Discriminant Analysis Effect Size (LEfSe) analysis identified 2 ( hgcI&#95;clade and Faecalibacterium ) and 14 ( Bacteroides , Proteiniphilum , Proteiniclasticum , etc.) differential microbiota in CR and FR, respectively. The rearing system influenced 4 pathways including biosynthesis of amino acids in ileal microbiota. Moreover, we identified 1,198 differentially expressed genes (DEGs) in the ileum mucosa, with 957 genes up-regulated in CR and 241 genes up-regulated in FR. In CR, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed the significant enrichment ( p < 0.05) of 28 KEGG pathways, most of which were associated with amino acid metabolism. In FR, up-regulated DEGs were mainly enriched in KEGG pathways associated with cellular processes, including apoptosis, necroptosis, and cellular senescence. Spearman correlation analysis of differential microbiota and amino acid metabolism-related DEGs in CR showed a significant positive correlation. Additionally, differential microbiota of FR, Phascolarctobacterium and Sutterella , were positively correlated with FGF10 ( p < 0.05) and PIK3R1 ( p < 0.01), respectively. In conclusion, there might be differences in ileal amino acid metabolism levels between CR and FR geese, and the observed increase in harmful bacterial species in FR might impact the activity of ileal cells.
Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
(Copyright © 2024 He, Li, Zhang, Ouyang, Hu, Hu, He, Li, Liu and Wang.)