Journal of Shanghai Jiao Tong University (Medical Science) ›› 2024, Vol. 44 ›› Issue (2): 169-182.doi: 10.3969/j.issn.1674-8115.2024.02.003

• Basic research • Previous Articles    

Study on intercellular communication and key genes of smooth muscle cells in human coronary atherosclerosis based on single cell sequencing technology

SI Chunying1,2(), WANG Jianru2, LI Xiaohui2(), WANG Yongxia1,2, GUAN Huaimin2   

  1. 1.The First Clinical Medical College (College of Integrated Traditional Chinese and Western Medicine), Henan University of Chinese Medicine, Zhengzhou 450003, China
    2.Heart Center/National Regional (Traditional Chinese Medicine) Cardiovascular Diagnosis and Treatment Center, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou 450003, China
  • Received:2023-05-19 Accepted:2023-12-11 Online:2024-02-28 Published:2024-03-25
  • Contact: LI Xiaohui E-mail:chunyingsi1987@163.com;478103511@qq.com
  • Supported by:
    Henan Natural Science Foundation Youth Fund Project(232300420273);Henan Province Medical Science and Technology Research Plan Jointly Construction Project(LHGJ20230690);Youth Fund Project of National Natural Science Foundation of China(82205021);Henan Province Science and Technology Research Project(212102311083);Research Nursery Engineering Project of Henan University of Chinese Medicine(MP2020-16)

Abstract:

Objective ·To use single-cell RNA sequencing (scRNA-Seq) technology to interpret the cellular communication landscape of coronary atherosclerosis (CA), and to explore the dominant cell subsets and their key genes. Methods ·The GSE131778 data set was downloaded and preprocessed, and quality controlling, dimension reduction clustering and annotation were carried out. Then cell communication analysis was conducted by using CellChat package to identify dominant cell subsets. The FindAllMarker function was used to screen differentially expressed genes (DEGs) between the dominant cell subpopulation and other cell subpopulations, and its protein-protein interaction (PPI) network was constructed. The DEGs ranked in the top five of the Degree algorithm were taken as key genes. Then, the key genes were matched and mined with the cell communication network analyzed by CellChat to obtain the ligand-receptor pairs (L-R) and the signal pathways mediated by the key genes, and the results were visualized. At the same time, the atherosclerosis mouse model was constructed and RT-PCR was used to detect the expression of key genes in carotid atherosclerosis lesions. Results ·A total of 11 cell subsets were identified in CA lesions, including smooth muscle cells, endothelial cells, macrophages, monocytes, etc. Cell communication results showed that CellChat detected 70 significant L-R and 26 related signal pathways in 11 cell subsets. Smooth muscle cell was the dominant cell subgroup with the most significant interaction frequency and intensity with other cell subgroups in the active state of communication. The results of DEGs screening showed that there were 206 DEGs between smooth muscle cell subsets and other cell subsets, among which ITGB2, PTPRC, CCL2, DCN and IGF1 were identified as key genes. The results of cell communication mediated by key genes showed that CCL2 and ACKR1 formed L-R and participated in the communication network between smooth muscle cells and endothelial cells through mediating CCL signaling pathway. ITGB2 formed receptor complexes withITGAM and ITGAX respectively, and then formed L-R with C3 to mediate the complement signal pathway, participating in the communication network among smooth muscle cells, macrophages and monocytes. The validation results of hub genes in animal experiments were consistent with the results of bioinformatics analysis. Conclusion ·Smooth muscle cells are the dominant cells in the pathological process of CA, and have extensive communication networks with other cells. They can construct cellular communication networks with endothelial cells, macrophages and monocytes through CCL and complement signaling pathways mediated by CCL2-ACKR1, C3-(ITGAM+ITGB2) and C3-(ITGAX+ITGB2).

Key words: coronary atherosclerosis, single-cell RNA sequencing (scRNA-Seq), smooth muscle cell, cellular communication

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