Background
Although reperfusion therapy can reduce the mortality of myocardial infarction, it results in myocardial ischemia-reperfusion injury (MIRI). The molecular mechanism by which the interferon-γ pathway affects MIRI is unclear, so we addressed this problem by mining transcriptome and single-cell sequencing data.
Methods
The GSE160516 and GSE83472 datasets, single cell RNA sequencing (scRNA-seq) data of GSE227088 dataset and 182 interferon-γ pathway related genes (IRGs) were retrieved and incorporated into this study. The differentially expressed genes (DEGs) between MIRI and control samples were searched, the candidate genes were obtained by intersecting DEGs with IRGs. The protein-protein interaction (PPI) analysis was utilized for selecting key genes from candidate genes. Moreover, key genes with significant expression and consistent trend in GSE160516 and GSE83472 datasets were selected as biomarkers. The biological functions and regulatory mechanism of biomarkers were investigated by enrichment analysis and predicting the upstream molecules targeting them. Ulteriorly, cell clusters were identified via unsupervised cluster analysis and merged into different cell types by cell annotation. Cell types in which biomarkers observably and differentially expressed were selected as crucial cell types. Finally, cell communication and pseudo-time analysis were implemented based on crucial cell types.
Results
Totally 34 candidate genes were searched by overlapping 1,930 DEGs with 182 IRGs. Nine key genes were singled out from candidate genes, of which Myd88 and Trp53 were significantly upregulated in the MIRI samples of GSE160516 and GSE83472 datasets, so they were identified as biomarkers. Besides, they participated in pathways such as ribosome, spliceosome and cell cycle. Myd88 might be simultaneously regulated by mmu-miR-361-3p and mmu-miR-421-3p, and Trp53 could be regulated by Abl1 and Tead2. Totally 25 cell clusters were merged into six cell types, of which three crucial cell types (cardiomyocyte, fibroblast and macrophage) could interact with each other through receptor-ligand. Pseudo-time analysis revealed states 1, 2 and 5 of macrophages might be associated with MIRI.
Conclusion
Two biomarkers (Myd88 and Trp53) related to IRGs in MIRI were mined, providing a reference for elucidating the mechanism of interferon-γ pathway on MIRI.
