Analysis of single-cell RNA-Seq reveals dynamic changes during macrophage state transition in atherosclerosis mouse model

Background: Atherosclerosis is an arterial inflammation that causes ischemic heart disease, which is the first leading cause of death worldwide. Macrophages play major roles during disease development by having pro-inflammatory and anti-inflammatory functions. Lack of effective treatment is mainly due to incomplete understanding of the molecular mechanisms underlying disease progression and regression. Materials and methods: The transcripts of the macrophages from two aortic samples from atherosclerotic region during disease progression and regression were analyzed using previously published dataset (GEO Accession GSE123587). Pre-processing, clustering of cells and identification of unique markers for each cluster were done using Seurat package implemented in R programming language. Monocle package was used to order the cells in pseudotime and to detect the key molecules that changed dramatically during comparison between distinct macrophages states (pro-inflammatory and anti-inflammatory). Ingenuity Pathway Analysis (IPA) software was used to analyze the pathways activity across macrophage states along the trajectory and to retrieve the transcriptional regulatory network between the genes determining the final states. Prediction of the miRNAs that might be involved in the disease progression was performed using TargetScan and GSEA (Gene Set Enrichment Analysis). Cytoscape application was used to visualize the regulatory network between the differentially regulated genes across macrophages states. Results: Clustering analysis of macrophages revealed their presence in distinct 11 states. In addition, Two states were found to be dominant in the progression group macrophages, and one state was found to be dominant in the regression group macrophages. Moreover, trajectory analysis showed a bifurcation point near the end of the trajectory, where macrophages fates were destined to be either pro-inflammatory or anti-inflammatory. Macrophages unique to the disease progression branch were found to activate STAT cascade, induce acute inflammatory response and upregulate inflammatory cytokines, denoting M1 polarization. In contrast, regression-branch specific macrophages were found to activate cholesterol efflux pathways and upregulate anti-inflammatory cytokines such as TSLP and CCL24. The transcription regulatory network between differentially regulated genes in both branches revealed changes in the transcriptional dynamics acquired during macrophage states transition. STAT1 (Signal transducer and activator of transcription 1) and IRF7 (Interferon Regulatory Factor 7) were found to be upregulated in the progression branch to maintain an inflammatory module resulting in production of distinct inflammatory cytokines. On the other hand, MAFB (MAF BZIP Transcription Factor B) and IGF1 (Insulin-like growth factor 1) were found to be upregulated in the regression branch to interrupt the inflammatory module at different levels. In addition, 10 miRNAs were predicted to be unregulated in progression-branch specific macrophages such as miR-344, miR-346 and miR-485. Conclusion: Inflammatory sites in atherosclerosis lesions contain both pro-inflammatory and anti-inflammatory macrophages. Each subset of macrophage activates unique transcriptional program. Certain transcription factors and growth factors have potential to alter the whole transcriptional regulatory network, thereby shifting the macrophages from inflammatory to anti-inflammatory state. Understanding how macrophage state transition occurs from inflammatory to anti-inflammatory state will be a key step to better understanding and treating atherosclerosis