Role of METTL3 Protein in Asthma: Insights from Transcriptomic Profiling and Molecular Docking Analysis
Abstract
Asthma is a chronic inflammatory disease characterized byimmune dysregulation. This study aimed to perform unbiased analysis of transcriptomic data to identify differentially expressed m6A-related genes in asthma, with a focus on exploring their potential as biomarkers and therapeutic targets.
Gene Expression Omnibus (GEO) (GSE134544) dataset was analyzed to identify differentially expressed m6A-related genes. Functional enrichment analysis was performed clusterProfiler, immune infiltration profiling was conducted with CIBERSORT, and a competing endogenous RNA (ceRNA, including microRNA [miR] and lncRNA) network was constructed. Drug enrichment analysis was carried out using DSigDB, and molecular docking was utilized to assess the interaction between dabigatran and the METTL3 protein.
From 192 differentially expressed genes, four m6A-related genes (METTL3, HNRNPC, IGFBP2, and RBMX) were identified as the intersecting genes between the m6A-related gene set and differentially expressed genes (DEGs) from the GSE134544 dataset. Gene Ontology (GO) analysis revealed significant enrichment in biological processes related to RNA metabolic processes and post-transcriptional regulation, while Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis identified important pathways such as spliceosome and p53 signaling pathways. METTL3 and HNRNPC were central in the ceRNA network, interacting with miRs such as hsa-miR-93-3p and lncRNAs like LINC01529. Drug enrichment analysis identified dabigatran as a potential METTL3 inhibitor, with molecular docking confirming a stable binding affinity (−5.9 kcal/mol).
This study emphasizes the critical role of m6A-related genes, particularly METTL3 and HNRNPC, as macromolecules in asthma pathophysiology, and provides insights into their potential as biomarkers and therapeutic targets for asthma treatment.
2. Agache I, Eguiluz-Gracia I, Cojanu C, Popescu FD, Rogozea L, Akdis CA, et al. Advances and highlights in asthma in 2021. Allergy. 2021;76(11):3390-7.
3. Mims JW. Asthma: definitions and pathophysiology. Int Forum Allergy Rhinol. 2015;5 Suppl 1:S2-6.
4. Tattersall MC, Jarjour NN, Busse PJ. Systemic inflammation in asthma: what are the risks and impacts outside the airway? J Allergy Clin Immunol Pract. 2024;12(4):849-62.
5. Miller RL, Grayson MH, Strothman K. Advances in asthma: new understandings of asthma’s natural history, risk factors, underlying mechanisms, and clinical management. J Allergy Clin Immunol. 2021;148(6):1430-41.
6. Thien F, Beggs PJ, Csutoros D, Webb K, Stewart G, Hew M, et al. The Melbourne epidemic thunderstorm asthma event 2016: an investigation of environmental triggers, effect on health services, and patient risk factors. Lancet Planet Health. 2018;2(6):e255-e263.
7. He L, Li H, Wu A, Peng Y, Shu G, Yin G. Functions of N6-methyladenosine and its role in cancer. Mol Cancer. 2019;18(1):176.
8. Teng F, Tang W, Wuniqiemu T, Zhang C, Zhang F, Xu Z, et al. N(6)-methyladenosine methylomic landscape of lung tissues in murine acute allergic asthma. Front Immunol. 2021;12:740571.
9. Abdel-Aziz MI, Neerincx AH, Vijverberg SJ, Kraneveld AD, Maitland-van der Zee AH. Omics for the future in asthma. Semin Immunopathol. 2020;42(1):111-26.
10. Sun D, Cai X, Shen F, Li Z, Yang H, Wang Z, et al. Transcriptome-wide m6A methylome and m6A-modified gene analysis in asthma. Front Cell Dev Biol. 2022;10:799459.
11. Lertnimitphun P, Zhang W, Fu W, Wu H, Zhou Q, Lin S, et al. Safranal alleviated OVA-induced asthma model and inhibits mast cell activation. Front Immunol. 2021;12(5):585595.
12. Du Y, Hou G, Zhang H, Li X, Wu J, Sun W, et al. SUMOylation of the m6A-RNA methyltransferase METTL3 modulates its function. Nucleic Acids Res. 2018;46(10):5195-208.
13. Merkestein M, Laber S, McMurray F, He X, Barg S, Carr C, et al. FTO influences adipogenesis by regulating mitotic clonal expansion. Nat Commun. 2015;6:6792.
14. Sun D, Yang H, Fan L, Shen F, Wang Z. m6A regulator-mediated RNA methylation modification patterns and immune microenvironment infiltration characterization in severe asthma. J Cell Mol Med. 2021;25(21):10236-47.
15. Wang X, Feng J, Xue Y, Guan Z, Zhang D, Liu Z, et al. Structural basis of N(6)-adenosine methylation by the METTL3-METTL14 complex. Nature. 2016;534(7608):575-8.
16. Choe J, Lin S, Zhang W, Liu Q, Wang L, Ramirez-Moya J, et al. mRNA circularization by METTL3-eIF3h enhances translation and promotes oncogenesis. Nature. 2018;561(7724):556-60.
17. Wang P, Doxtader KA, Nam Y. Structural basis for cooperative function of Mettl3 and Mettl14 methyltransferases. Mol Cell. 2016;63(2):306-17.
18. Liu N, Dai Q, Zheng G, He C, Parisien M, Pan T. N(6)-methyladenosine-dependent RNA structural switches regulate RNA-protein interactions. Nature. 2015;518(7540):560-4.
19. Patil DP, Chen CK, Pickering BF, Chow A, Jackson C, Guttman M, et al. m(6)A RNA methylation promotes XIST-mediated transcriptional repression. Nature. 2016;537(7620):369-73.
20. Hornegger H, Anisimova AS, Muratovic A, Kujala K, Jabs M, Henkel L, et al. IGF2BP1 phosphorylation in the disordered linkers regulates ribonucleoprotein condensate formation and RNA metabolism. Nat Commun. 2024;15(1):9054.
21. Hao H, Hao S, Chen H, Li Y, Huang Y, Zhang L, et al. N6-methyladenosine modification and METTL3 modulate enterovirus 71 replication. Nucleic Acids Res. 2019;47(1):362-74.
22. Chen Z, Shang Y, Zhang X, Yu X, Yang J, Wu Z, et al. METTL3 mediates SOX5 m6A methylation in bronchial epithelial cells to attenuate Th2 cell differentiation in T2 asthma. Heliyon. 2024;10(7):e28884.
23. Batista PJ. The RNA modification N(6)-methyladenosine and its implications in human disease. Genomics Proteomics Bioinformatics. 2017;15(3):154-63.
24. Yankova E, Blackaby W, Albertella M, Rak J, De Braekeleer E, Tsagkogeorga G, et al. Small-molecule inhibition of METTL3 as a strategy against myeloid leukaemia. Nature. 2021;593(7860):597-601.
25. Han X, Liu L, Huang S, Luo Y, Yang J, Wang H, et al. RNA m(6)A methylation modulates airway inflammation in allergic asthma via PTX3-dependent macrophage homeostasis. Nat Commun. 2023;14(1):7328.
26. Peng L, Li M, Xiao L, Liu S, Li X, Wu X, et al. The impact of m6A methyltransferase METTL3 on airway remodeling in bronchial asthma. J Asthma. 2025;1-14.
27. Vazquez-Mera S, Martelo-Vidal L, Miguens-Suarez P, Vazquez-Mera A, Varela-Centelles P, Taboada-Vazquez M, et al. Serum exosome inflamma-miRs are surrogate biomarkers for asthma phenotype and severity. Allergy. 2023;78(1):141-55.
28. Park S, Yang HD, Seo JW, Nam JW, Nam SW. hnRNPC induces isoform shifts in miR-21-5p leading to cancer development. Exp Mol Med. 2022;54(6):812-24.
29. Ran MY, Yuan Z, Fan CT, Liu LY, Zhang C, Zhang YQ, et al. Multiplex-heterogeneous network-based capturing potential SNP “switches” of pathways associating with diverse disease characteristics of asthma. Front Cell Dev Biol. 2021;9:744932.
30. Ding DX, Li Q, Shi K, Li H, Guo Q, Zhang YQ. LncRNA NEAT1-miR-101-3p/miR-335-5p/miR-374a-3p/miR-628-5p-TRIM6 axis identified as the prognostic biomarker for lung adenocarcinoma via bioinformatics and meta-analysis. Transl Cancer Res. 2021;10(11):4870-83.
31. Yang Y, Wang F, Huang H, Zhang Y, Xie H, Men T. lncRNA SLCO4A1-AS1 promotes growth and invasion of bladder cancer through sponging miR-335-5p to upregulate OCT4. Onco Targets Ther. 2019;12:1351-8.
32. Specjalski K, Jassem E. MicroRNAs: potential biomarkers and targets of therapy in allergic diseases? Arch Immunol Ther Exp (Warsz). 2019;67(4):213-23.
33. Liao Z, Ye Z, Xue Z, Zeng X, Li L, Hu C, et al. Identification of renal long non-coding RNA RP11-2B6.2 as a positive regulator of type I interferon signaling pathway in lupus nephritis. Front Immunol. 2019;10:975.
| Files | ||
| Issue | Articles in Press | |
| Section | Original Article(s) | |
| Keywords | ||
| Asthma Biomarker ceRNA Therapeutic targets | ||
| Rights and permissions | |
|
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
