Single-cell gene profiling and lineage tracing analyses revealed novel mechanisms of endothelial repair by progenitors.
Jiacheng DengZhichao NiWenduo GuQishan ChenWitold Norbert NowakTing ChenShirin Issa BhalooZhongyi ZhangYanhua HuBin ZhouLi ZhangQingbo XuPublished in: Cellular and molecular life sciences : CMLS (2020)
Stem/progenitor cells (SPCs) have been implicated to participate in vascular repair. However, the exact role of SPCs in endothelial repair of large vessels still remains controversial. This study aimed to delineate the cellular heterogeneity and possible functional role of endogenous vascular SPCs in large vessels. Using single-cell RNA-sequencing (scRNA-seq) and genetic lineage tracing mouse models, we uncovered the cellular heterogeneity of SPCs, i.e., c-Kit+ cells in the mouse aorta, and found that endogenous c-Kit+ cells acquire endothelial cell fate in the aorta under both physiological and pathological conditions. While c-Kit+ cells contribute to aortic endothelial turnover in the atheroprone regions during homeostasis, recipient c-Kit+ cells of nonbone marrow source replace both luminal and microvessel endothelial cells in transplant arteriosclerosis. Single-cell pseudotime analysis of scRNA-seq data and in vitro cell experiments suggest that vascular SPCs display endothelial differentiation potential and undergo metabolic reprogramming during cell differentiation, in which AKT/mTOR-dependent glycolysis is critical for endothelial gene expression. These findings demonstrate a critical role for c-Kit lineage cells in aortic endothelial turnover and replacement, and may provide insights into therapeutic strategies for vascular diseases.
Keyphrases
- single cell
- rna seq
- endothelial cells
- induced apoptosis
- cell cycle arrest
- high throughput
- gene expression
- stem cells
- aortic valve
- cell death
- signaling pathway
- pulmonary artery
- genome wide
- cell proliferation
- mouse model
- coronary artery
- oxidative stress
- left ventricular
- mesenchymal stem cells
- copy number
- machine learning
- cell therapy
- bone mineral density
- high glucose
- bone marrow
- electronic health record
- artificial intelligence
- atrial fibrillation