4.8 Article

Aortic heterogeneity across segments and under high fat/salt/glucose conditions at the single-cell level

期刊

NATIONAL SCIENCE REVIEW
卷 7, 期 5, 页码 881-896

出版社

OXFORD UNIV PRESS
DOI: 10.1093/nsr/nwaa038

关键词

aorta; single-cell RNA sequencing; cardiovascular disease

资金

  1. National Natural Science Foundation of China [81622007, 81870362, 81960662, 91939301]
  2. Chang Jiang Scholars Program [Q2015106]
  3. Fundamental Research Funds for the Central Universities [JUSRP51704A]
  4. National First-Class Discipline Program of Food Science and Technology [JUFSTR20180101]
  5. Foundation of Yunnan Provincial Science and Technology Department [2019FE001(-133)]

向作者/读者索取更多资源

The aorta, with ascending, arch, thoracic and abdominal segments, responds to the heartbeat, senses metabolites and distributes blood to all parts of the body. However, the heterogeneity across aortic segments and how metabolic pathologies change it are not known. Here, a total of 216 612 individual cells from the ascending aorta, aortic arch, and thoracic and abdominal segments of mouse aortas under normal conditions or with high blood glucose levels, high dietary salt, or high fat intake were profiled using single-cell RNA sequencing. We generated a compendium of 10 distinct cell types, mainly endothelial (EC), smooth muscle (SMC), stromal and immune cells. The distributions of the different cells and their intercommunication were influenced by the hemodynamic microenvironment across anatomical segments, and the spatial heterogeneity of ECs and SMCs may contribute to differential vascular dilation and constriction that were measured by wire myography. Importantly, the composition of aortic cells, their gene expression profiles and their regulatory intercellular networks broadly changed in response to high fat/salt/glucose conditions. Notably, the abdominal aorta showed the most dramatic changes in cellular composition, particularly involving ECs, fibroblasts and myeloid cells with cardiovascular risk factor-related regulons and gene expression networks. Our study elucidates the nature and range of aortic cell diversity, with implications for the treatment of metabolic pathologies.

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