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. 2024 Dec 28;14(1):31072.
doi: 10.1038/s41598-024-82150-y.

Effects of moderate intensity exercise on liver metabolism in mice based on multi-omics analysis

Fang Wang  1 , Wanyu Wu  1 , Xuejia He  1   2 , Ping Qian  3 , Jiahui Chang  1   4 , Zhaoxu Lu  1 , Jin Guo  1 , Yihua Bao  1 , Hongyan Guan  5 , Ting Zhang  6
Affiliations

Effects of moderate intensity exercise on liver metabolism in mice based on multi-omics analysis

Fang Wang et al. Sci Rep. .

Abstract

Physical exercise is beneficial to keep physical and mental health. The molecular mechanisms underlying exercise are still worth exploring. The healthy adult mice after six weeks of moderate-intensity exercise (experimental group) and sedentary mice (control group) were used to perform transcriptomic, proteomic, lactylation modification, and metabolomics analysis. In addition, gene sets related to hypoxia, glycolysis, and fatty acid metabolism were used to aid in the screening of hub genes. The mMCP-counter was employed to evaluate infiltration of immune cells in murine liver tissues. Transcriptomics analysis revealed 82 intersection genes related to hypoxia, glycolysis, and fatty acid metabolism. Proteomics and lactylation modification analysis identified 577 proteins and 141 differentially lactylation modification proteins. By overlapping 82 intersection genes with 577 differentially expressed proteins and 141 differentially lactylation modification proteins, three hub genes (Aldoa, Acsl1, and Hadhb) were obtained. The immune infiltration analysis revealed a decreased score for monocytes/macrophages and an increased score for endothelial cells in the experimental group. Then, 459 metabolites in positive mode and 181 metabolites in negative mode were identified. The "Metabolic pathways" (mmu01100) was a common pathway between intersection genes-enriched pathways and metabolites-enriched pathways. These findings highlight the pivotal roles of hub genes in the glycolysis and fatty acid metabolism under the context of chronic exercise.

Keywords: Chronic exercise; Lactylation; Liver; Metabolome; Multi-omics; Proteome.

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Conflict of interest statement

Declarations. Competing interests: The authors declare no competing interests. Statement of ethics: The study was conducted according to the guidelines of the management and utility of experimental animals, and approved by the Ethics Committee of Capital institute of Pediatrics and all animal manipulations were strictly performed following the relevant laws of China.

Figures

Fig. 1
Fig. 1
Identification of intersection genes. (A) Volcano and Venn plots of the DEGs. (B) Venn diagram displaying the DEGs and HRGs/GRGs/FRGs. DEG, differentially expressed genes; HRG, hypoxia-related gene; GRG, glycolysis-related gene; FRG, fatty acid metabolism-related gene.
Fig. 2
Fig. 2
Functional enrichment of intersection genes. (A) GO analysis for intersection genes. (B) KEGG enrichment analysis for intersection genes. GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes.
Fig. 3
Fig. 3
PPI network of intersection genes. Node size and color depth are proportional to degree.
Fig. 4
Fig. 4
Proteomics and lactylation modification analyses. (A) Volcano plot of the DEPs. (B) Heatmap of the DEPs. (C) Volcano plot of the DLSs. (D) Heatmap of the DLSs. DEP, differentially expressed protein; DLS, differentially lactylated site.
Fig. 5
Fig. 5
Characterization of hub genes. (A) Gene expression levels of hub genes. (B) Protein levels of hub genes. (C) Lactylation modification levels of hub genes. ns indicated not significant, *indicated p < 0.05, **indicated p < 0.01, ***indicated p < 0.001, ****indicated p < 0.0001.
Fig. 6
Fig. 6
Analysis of immune microenvironment. (A) The immune infiltration levels of two immune cells. (B) The correlation analysis between gene expression levels of hub genes and two immune cells. (C) The correlation analysis between protein expression levels of hub genes and two immune cells. (D) The correlation analysis between lactylation modification levels of hub genes and two immune cells. * indicated p < 0.05, ** indicated p < 0.01.
Fig. 7
Fig. 7
Metabolomics analysis in positive mode. (A) Volcano plot of the DEMs in positive mode (B) Heatmap of the DEMs in positive mode. (C) KEGG pathway annotation for DEMs in positive mode. (D) The correlation analysis between gene expression levels of hub genes and DEMs in Metabolic pathways. (E) The correlation analysis between protein expression levels of hub genes and DEMs in Metabolic pathways. DEM, Differential metabolite.
Fig. 8
Fig. 8
Metabolomics analysis in negative mode. (A) Volcano plot of the DEMs in negative mode. (B) Heatmap of the DEMs in negative mode. (C) KEGG pathway annotation for DEMs in negative mode. (D) The correlation analysis between gene expression levels of hub genes and DEMs in Metabolic pathways. (E) The correlation analysis between protein expression levels of hub genes and DEMs in Metabolic pathways. DEM, Differential metabolite.
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