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Exploring the Impact of m6A Methyltransferase Mettl3 on MASLD through Multi-Omics Analysis

ABSTRACT: Background: N6-methyladenosine (m6A) RNA modification plays a crucial role in various biological events and is implicated in various metabolic-related diseases. However, its role in MASLD remains unclear. This study aims to investigate the impact of Mettl3 on MASLD through multi-omics analysis, with a focus on exploring its potential mechanisms of action. Methods: MASLD mouse models were established by feeding a high-fat diet for 12 weeks, and Mettl3 stable overexpression AML12 cell models were constructed via lentiviral transfection. Subsequent transcriptomic and proteomic analyses, as well as integrated analysis between different omics datasets, were conducted. Results: Mettl3 expression significantly increased in MASLD mouse models. In the transcriptomic and proteomic analyses, we identified 848 genes with significant inconsistencies between transcriptomic and proteomic datasets. GO/KEGG enrichment terms may involve post-transcriptional modifications, particularly Mettl3-mediated m6A modification. Subsequently, through integrated proteomic analysis of Mettl3-overexpressed AML12 cell models and MASLD mouse models, we selected the top 20 co-upregulated and co-downregulated GO/KEGG terms as the main biological processes influenced by Mettl3 in MASLD. By intersecting with pathways obtained from previous integrated analyses, we identified GO/KEGG terms affected by Mettl3-induced m6A modification. Protein-protein interaction analysis of proteins involved in these pathways highlighted GAPDH, ENO1, and TPI1 as three key hub genes. Conclusion: In MASLD, Mettl3 regulates the glycolytic pathway through m6A modification, influencing the occurrence and development of the disease via the key hub genes GAPDH, ENO1, and TPI1. These findings expand our understanding of MASLD and provide strong evidence for potential therapeutic targets and drug development.

INSTRUMENT(S): Orbitrap Exploris 480

ORGANISM(S): Mus Musculus (mouse)

TISSUE(S): Aml-12 Cell

SUBMITTER: Shuowen Wang

LAB HEAD: Shuowen Wang

PROVIDER: PXD050565 | Pride | 2024-09-20

REPOSITORIES: Pride

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Project description:METTL3-mediated RNA N6-methyladenosine (m6A) is the most prevalent modification participates in tumor initiation and progression via regulating expression of their target genes in cancers. However, its role in tumor cell metabolism remains poorly appreciated. In this study, we conducted a multi-omics analysis including m6A microarray and quantitative proteomics to explore the potential effect and mechanism of METTL3 on the metabolism in gastric cancer cells. Our results found that significant alterations in the protein and m6A modification profile which induced by METTL3 overexpression in GC cells. Gene Ontology (GO) enrichment results showed that down-regulated proteins were significantly enriched in intracellular mitochondrial oxidative phosphorylation (OXPHOS), and the Protein-Protein Interaction (PPI) network analysis found that these differentially expressed proteins were significantly associated with OXPHOS. Subsequently, a prognostic model constructed based on the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and the high-risk group showed a worse prognosis in GC patients. Meanwhile, the Gene Set Enrichment Analysis (GSEA) showed a significant enrichment in the energy metabolism signaling pathway. Then, combined with the results of the m6A microarray analysis, the intersection molecules of DEPs and differential methylation genes (DMGs) were significantly correlated with the genes involved in OXPHOS. Besides, there were also significant differences in prognosis and GSEA enrichment between the two clusters of GC patients classified according to consensus clustering algorithm. Finally, we focused on highly expressed, highly methylated molecules regulated by METTL3 and identified three (AVEN, DAZAP2, DNAJB1) genes that were significantly associated with poor prognosis in patients with GC. These results indicated that METTL3-regulated DEPs in GC cells were significantly associated with OXPHOS. After combined with m6A microarray analysis, the results suggested that these proteins might be involved in cell energy metabolism through m6A modifications thus influencing the prognosis of GC patients. Overall, our study revealed that METTL3 involved in cell metabolism through an m6A-dependent mechanism in GC cells, and indicated a potential biomarker for prognostic prediction in GC.

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Exploring the Impact of m6A Methyltransferase Mettl3 on MASLD through Multi-Omics Analysis

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