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Spatial transcriptomic modeling of vascular remodeling in aortic aneurysm using integrated single-cell RNA sequencing
Shaodong Xiong1, Ludong Liang1, Tao Liu2
1Department of Cardiothoracic Surgery, Baise People's Hospital, 533000, Baise City, Guangxi province, China; Department of Cardiothoracic Surgery, Affiliated Southwest Hospital of Youjiang Medical University for Nationalities, Baise, 533000, Guangxi province, China.
This study models vascular remodeling using single-cell RNA sequencing and computational methods. It reveals how diet impacts vascular smooth muscle cell (VSMC) phenotypes and spatial distribution, offering insights into aortic aneurysm formation.
Area of Science:
- Cardiovascular Biology
- Computational Biology
- Genomics
Background:
- Vascular smooth muscle cell (VSMC) phenotypic plasticity is crucial in aortic aneurysm development.
- The spatial and transcriptional dynamics of VSMCs in this process are not fully understood.
Purpose of the Study:
- To develop a computational framework for modeling vascular remodeling at cellular resolution.
- To investigate the impact of high-fat diet on VSMC phenotypes and spatial distribution in the aorta.
Main Methods:
- Integrated single-cell RNA sequencing (scRNA-seq) with pseudo-spatial transcriptomic inference.
- Utilized Seurat, Tangram, and Monocle3 on mouse aortic scRNA-seq data.
- Performed differential expression and spatial variability analyses.
Main Results:
- Identified 25 distinct cell populations, including 5 VSMC and 4 fibroblast subtypes with region-specific patterns.
- High-fat diet increased synthetic VSMC and monocyte populations while decreasing contractile VSMCs.
- Pseudo-spatial reconstruction showed compartmentalized VSMC states and identified genes involved in phenotypic transitions.
Conclusions:
- Publicly available scRNA-seq data can generate hypotheses for spatial modeling of vascular disease.
- The study reveals cell-type-specific transcriptional programs and phenotypic transitions in VSMCs.
- Findings warrant experimental validation using techniques like immunohistochemistry and spatial transcriptomics.
