Revealing the Critical Regulators of Modulated Smooth Muscle Cells in Atherosclerosis in Mice

Abstract

Background: There are still residual risks for atherosclerosis (AS)-associated cardiovascular diseases to be resolved. Considering the vital role of phenotypic switching of smooth muscle cells (SMCs) in AS, especially in calcification, targeting SMC phenotypic modulation holds great promise for clinical implications. Methods: To perform an unbiased and systematic analysis of the molecular regulatory mechanism of phenotypic switching of SMCs during AS in mice, we searched and included several publicly available single-cell datasets from the GEO database, resulting in an inclusion of more than 80,000 cells. Algorithms implemented in the Seurat package were used for cell clustering and cell atlas depiction. The pySCENIC and SCENIC packages were used to identify master regulators of interested cell groups. Monocle2 was used to perform pseudotime analysis. clusterProfiler was used for Gene Ontology enrichment analysis. Results: After dimensionality reduction and clustering, reliable annotation was performed. Comparative analysis between cells from normal artery and AS lesions revealed that three clusters emerged as AS progression, designated as mSMC1, mSMC2, and mSMC3. Transcriptional and functional enrichment analysis established a continuous transitional mode of SMCs' transdifferentiation to mSMCs, which is further supported by pseudotime analysis. A total of 237 regulons were identified with varying activity scores across cell types. A potential core regulatory network was constructed for SMC and mSMC subtypes. In addition, module analysis revealed a coordinate regulatory mode of regulons for a specific cell type. Intriguingly, consistent with gain of ossification-related transcriptional and functional characteristics, a corresponding small set of regulators contributing to osteochondral reprogramming was identified in mSMC3, including Dlx5, Sox9, and Runx2. Conclusion: Gene regulatory network inference indicates a hierarchical organization of regulatory modules that work together in fine-tuning cellular states. The analysis here provides a valuable resource that can provide guidance for subsequent biological experiments.

Keywords: atherosclerosis; gene regulatory network; phenotypic modulation; single-cell RNA sequencing; smooth muscle cells.

FIGURE 1

Identification of cell types and functional characterization of each cell type in plaques in mice. (A) UMAP visualization of all cells (right) and cells from normal tissue (left). Normal tissue is defined as aorta dissected from wild-type mice treated with a chow diet. (B) Violin plot of representative classic markers for each identified cell type. (C) Heatmap of top 100 DEGs for each cell type. Scaled log-normalized data were used for visualization. (D–G) Top 10 enriched GO biological process terms for SMC, mSMC1, mSMC2, and mSMC3, respectively. The number of DEGs for each cell type and involved genes for each GO term was designated in the brackets with g-representing genes. (H) Heatmap of genes enriched in an extracellular matrix organization in mSMC subtypes. Scaled log-normalized data were used for visualization. SMCs, smooth muscle cells; mSMCs, phenotypically modulated SMCs; DEGs, differentially expressed genes.

FIGURE 2

Construction of gene regulatory networks in SMC-derived cells in atherosclerosis in mice. (A) Identified regulons were ranked based on their cell-type specificity scores in SMCs and mSMC subtypes. Key TFs of the top six specific regulons for each cell type were designated. (B) Left panel shows distribution of AUC scores of the top six specific regulons for SMCs. The panel in the middle represents the proportion of corresponding TF-positive cells in SMCs and mSMC subtypes. The right panel displays binding motifs for representative TFs for SMCs. (C) Same as (B) but for mSMC1. (D) Same as (B) but for mSMC3. Considering mSMC2 shares top specific regulons with mSMC1 or mSMC3, the top 6 mSMC2-specific regulons were highlighted in light red in (C,D). SMCs, smooth muscle cells; mSMCs, phenotypically modulated SMCs; DEGs, differentially expressed genes; AUC, area under the curve.

FIGURE 3

Module analysis of identified regulons in atherosclerosis in mice. (A) Heatmap displays clustered regulon modules based on the CSI matrix along with the included regulons being shown in the right. (B) Heatmap in the right panel shows the average activity scores of each identified module in each cell type. The left panel displays the UMAP visualization of the average scores of eight identified modules in each single cell. (C) Sankey plot demonstrates the distribution pattern of top 20 specific regulons for each cell type in the representative regulon modules. CSI, connection specificity index.