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Single-Cell Analysis of the Normal Mouse Aorta Reveals Functionally Distinct Endothelial Cell Populations
Name
nihms-1534854.pdf
Description
Accepted version
Size
4.89 MB
Format
Adobe PDF
Checksum (MD5)
7213e871088c7c8a240456ceb5bdb027
Author(s)
Kalluri, Aditya S
Vellarikkal, Shamsudheen K
Edelman, Elazer R
Nguyen, Lan
Subramanian, Ayshwarya
Ellinor, Patrick T
Regev, Aviv
Kathiresan, Sekar
Gupta, Rajat M
Date Issued
2019
Journal
Circulation
Publisher
Ovid Technologies (Wolters Kluwer Health)
Version
Author's final manuscript
Abstract
Background: The cells that form the arterial wall contribute to multiple vascular diseases. The extent of cellular heterogeneity within these populations has not been fully characterized. Recent advances in single-cell RNA-sequencing make it possible to identify and characterize cellular subpopulations. Methods: We validate a method for generating a droplet-based single-cell atlas of gene expression in a normal blood vessel. Enzymatic dissociation of 4 whole mouse aortas was followed by single-cell sequencing of >10 000 cells. Results: Clustering analysis of gene expression from aortic cells identified 10 populations of cells representing each of the main arterial cell types: fibroblasts, vascular smooth muscle cells, endothelial cells (ECs), and immune cells, including monocytes, macrophages, and lymphocytes. The most significant cellular heterogeneity was seen in the 3 distinct EC populations. Gene set enrichment analysis of these EC subpopulations identified a lymphatic EC cluster and 2 other populations more specialized in lipoprotein handling, angiogenesis, and extracellular matrix production. These subpopulations persist and exhibit similar changes in gene expression in response to a Western diet. Immunofluorescence for Vcam1 and Cd36 demonstrates regional heterogeneity in EC populations throughout the aorta. Conclusions: We present a comprehensive single-cell atlas of all cells in the aorta. By integrating expression from >1900 genes per cell, we are better able to characterize cellular heterogeneity compared with conventional approaches. Gene expression signatures identify cell subpopulations with vascular disease-relevant functions.
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
10.1161/CIRCULATIONAHA.118.038362
