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Comprehensive analysis of transcriptomics and metabolomics to understand chronic ethanol induced murine cardiotoxicity

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Abstract

Alcohol abuse has attracted public attention and long-term alcohol exposure can lead to alcohol-featured non-ischemic dilated cardiomyopathy. However, the precise underlying mechanisms of alcoholic cardiomyopathy remain to be elucidated. This study aimed to comprehensively characterize alcohol abuse-mediated effects on downstream metabolites and genes transcription using a multi-omics strategy. We established chronic ethanol intoxication model in adult male C57BL/6 mice through 8 weeks of 95% alcohol vapor administration and performed metabolomics analysis, mRNA-seq and microRNA-seq analysis with myocardial tissues. Firstly, ethanol markedly induced ejection fraction reductions, cardiomyocyte hypertrophy, and myocardial fibrosis in mice with myocardial oxidative injury. In addition, the omics analysis identified a total of 166 differentially expressed metabolites (DEMs), 241 differentially expressed genes (DEGs) and 19 differentially expressed microRNAs (DEmiRNAs), respectively. The results highlighted that alcohol abuse mainly interfered with endogenous lipids, amino acids and nucleotides production and the relevant genes transcription in mice hearts. Based on KEGG database, the affected signaling pathways are primarily mapped to the antigen processing and presentation, regulation of actin cytoskeleton, AMPK signaling pathway, tyrosine metabolism and PPAR signaling pathway, etc. Furthermore, 9 hub genes related to oxidative stress from DEGs were selected based on function annotation, and potential alcoholic cardiotoxic oxidative stress biomarkers were determined through establishing PPI network and DEmiRNAs-DEGs cross-talk. Altogether, our data strongly supported the conclusion that ethanol abuse characteristically affected amino acid and energy metabolism, nucleotide metabolism and especially lipids metabolism in mice hearts, and underlined the values of lipids signaling and oxidative stress in the treatment strategies.

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Data availability

The datasets obtained and analyzed in this study are available from the corresponding author on reasonable request.

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Funding

This work was supported by the National Natural Science Foundation of China [Grant Nos. 81871525].

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Authors and Affiliations

  1. Department of Forensic Medicine, School of Basic Medical Sciences, Fudan University, Shanghai, 200032, China

    Qiupeng Xue, Xiaochen Liu, Rongzhe Zhu, Tianyi Zhang, Xiaoru Dong & Yan Jiang

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  1. Qiupeng Xue
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  2. Xiaochen Liu
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  3. Rongzhe Zhu
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  4. Tianyi Zhang
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  5. Xiaoru Dong
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Contributions

Qiupeng Xue, Xiaochen Liu, Rongzhe Zhu and Xiaoru Dong concepted and designed the experiments; Qiupeng Xue, Rongzhe Zhu and Tianyi Zhang wrote the main manuscript text; Qiupeng Xue prepared figures and tables. All authors reviewed and approved the manuscript. Miss Liu has contributed to the conception and design of our experiments, and she has reviewed and approved the manuscript.

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Correspondence to Yan Jiang.

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The authors declare that they have no conflict of interest.

Ethical approval

All experimental procedures were conducted according to the protocols for animal experiments approved by the Ethical Review Committee at the School of Basic Medical Sciences, Fudan University, Shanghai, China (Approval No. 20180302–024).

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11010_2022_4592_MOESM1_ESM.docx

Supplementary file1: Fig. S1 A. QC results of samples processed for metabolomics. B. Hierarchical clustering analysis (HCA) of DEGs. Fig. S2 A. KEGG Enrichment Top 20 pathways of DEMs. B. Top 30 GO terms of DEmiRNAs-targeted genes. Fig. S3 A. qRT-PCR results of selected genes and miRNAs. (*p<0.0332, **p<0.0021, ***p<0.0002 vs CtrL, n≥3). B. GO term mitochondrial respiratory chain complex I gene set displayed in Gene Set Enrichment Analysis (GSEA). Fig. S4 Top 20 DEMs and DEGs correlation diagram.

Supplementary file2: The detailed information for metabolomics and transcriptomics analysis.

Supplementary file3: Table S1 The primer sequences used in quantitative RT-PCR experiments.

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Xue, Q., Liu, X., Zhu, R. et al. Comprehensive analysis of transcriptomics and metabolomics to understand chronic ethanol induced murine cardiotoxicity. Mol Cell Biochem 478, 1345–1359 (2023). https://doi.org/10.1007/s11010-022-04592-0

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