Abstract
Obesity and atherosclerosis are the most prevalent metabolic diseases. ApoE-/- and ob/ob mice are widely used as models to study the pathogenesis of these diseases. However, how gut microbes, gut bacteriophages, and metabolites change in these two disease models is unclear. Here, we used wild-type C57BL/6J (Wt) mice as normal controls to analyze the intestinal archaea, bacteria, bacteriophages, and microbial metabolites of ob/ob and ApoE-/- mice through metagenomics and metabolomics. Analysis of the intestinal archaea showed that the abundances of Methanobrevibacter and Halolamina were significantly increased and decreased, respectively, in the ob/ob group compared with those in the Wt and ApoE-/- groups (p < 0.05). Compared with those of the Wt group, the relative abundances of the bacterial genera Enterorhabdus, Alistipes, Bacteroides, Prevotella, Rikenella, Barnesiella, Porphyromonas, Riemerella, and Bifidobacterium were significantly decreased (p < 0.05) in the ob/ob mice, and the relative abundance of Akkermansia was significantly decreased in the ApoE-/- group. The relative abundances of A. muciniphila and L. murinus were significantly decreased and increased, respectively, in the ob/ob and ApoE-/- groups compared with those of the Wt group (p < 0.05). Lactobacillus_ prophage_ Lj965 and Lactobacillus _ prophage _ Lj771 were significantly more abundant in the ob/ob mice than in the Wt mice. Analysis of the aminoacyl-tRNA biosynthesis metabolic pathway revealed that the enriched compounds of phenylalanine, glutamine, glycine, serine, methionine, valine, alanine, lysine, isoleucine, leucine, threonine, tryptophan, and tyrosine were downregulated in the ApoE-/- mice compared with those of the ob/ob mice. Aminoacyl-tRNA synthetases are considered manifestations of metabolic diseases and are closely associated with obesity, atherosclerosis, and type 2 diabetes. These data offer new insight regarding possible causes of these diseases and provide a foundation for studying the regulation of various food nutrients in metabolic disease models.
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