Endothelial cell diversity revealed by global expression profiling

Abstract

The vascular system is locally specialized to accommodate widely varying blood flow and pressure and the distinct needs of individual tissues. The endothelial cells (ECs) that line the lumens of blood and lymphatic vessels play an integral role in the regional specialization of vascular structure and physiology. However, our understanding of EC diversity is limited. To explore EC specialization on a global scale, we used DNA microarrays to determine the expression profile of 53 cultured ECs. We found that ECs from different blood vessels and microvascular ECs from different tissues have distinct and characteristic gene expression profiles. Pervasive differences in gene expression patterns distinguish the ECs of large vessels from microvascular ECs. We identified groups of genes characteristic of arterial and venous endothelium. Hey2, the human homologue of the zebrafish gene gridlock, was selectively expressed in arterial ECs and induced the expression of several arterial-specific genes. Several genes critical in the establishment of left/right asymmetry were expressed preferentially in venous ECs, suggesting coordination between vascular differentiation and body plan development. Tissue-specific expression patterns in different tissue microvascular ECs suggest they are distinct differentiated cell types that play roles in the local physiology of their respective organs and tissues.

Fig. 1.

Diversity of EC gene expression patterns. (A) Gene expression patterns of cultured ECs organized by unsupervised hierarchical clustering. The global gene expression patterns of 53 cultured ECs were sorted based on similarity by hierarchical clustering. Approximately 6,900 genes were selected from the total data set, based on variations in expression relative to the mean expression level across all samples >3-fold in at least two cell samples. The sites of origin of each EC culture are indicated and color-coded. The anatomic origins of skin EC are indicated. The apparent order in the grouping of EC gene expression patterns is indicated to the right of the dendrogram. (B) Overview of gene expression patterns of all EC samples. The variations in gene expression described in A are shown in matrix format (5). The scale extends from 0.25- to 4-fold over mean (–2 to +2 in log2 space) as indicated on the left. Gray represents missing data. The gene clusters characteristic of large vessel and microvascular ECs are indicated on the right. Complete data can be found at http://microarray-pubs.stanford.edu/endothelial and in the Stanford Microarray Database (http://genome-www5.stanford.edu/MicroArray/SMD).

Fig. 2.

Large vessel and microvascular EC gene expression programs. (A) Identification of large vessel vs. microvascular ECs gene expression programs. Dendrogram representing the result of hierarchical clustering of EC samples, based on the similarities in their pattern of expression of the genes selected by Wilcoxon rank-sum test. (B) Features of large vessels and microvascular EC gene expression programs. A total of 521 large vessel-specific and 2,521 microvascular EC-specific genes are shown in ascending order of P values. Genes involved in ECM biosynthesis and interaction (blue), neuroglial signaling and migration (orange), angiogenesis (red), and lipid metabolism (black) are labeled by the indicated colors. (C) Validation of gene expression data by flow cytometry. Fluorescence-activated cell sorting analysis of surface expression of mannose receptor and α1 integrin on two ECs from dermal microcirculation (green, n = 2), one umbilical artery (red, n = 1), and one umbilical vein (blue, n = 1). Complete data can be found at http://microarray-pubs.stanford.edu/endothelial and in the Stanford Microarray Database (http://genome-www5.stanford.edu/MicroArray/SMD).

Fig. 3.

Artery and vein EC-specific gene expression programs. (A) Artery- or vein-specific genes identified by a Wilcoxon rank-sum test are shown in ascending order of P value within each gene list, and names of select artery-specific genes (red) and vein-specific genes (blue) are shown. Complete data can be found at http://microarray-pubs.stanford.edu/endothelial and in the Stanford Microarray Database (http://genome-www5.stanford.edu/MicroArray/SMD). (B) Strategy for identification of Hey2 target genes. HUVECs were infected by retrovirus expressing GFP or Hey2-IRES-GFP. The GPF-positive cells (labeled black bar) were sorted by fluorescence-activated cell sorting, and RNA from the sorted cells was reverse-transcribed with either Cy3 (GFP) or Cy5 (Hey2_GFP) and used for competitive hybridization to cDNA microarrays. (C) Induction of artery-specific genes by Hey2. Genes exhibiting >2-fold variation in expression in two of three independent experiments as described in B are shown. Genes previously identified as artery-specific in A are colored red, and vein-specific genes are colored blue. As an internal positive control, Hey2 expression was always higher in cells infected with Hey2_GFP retrovirus compared with cells infected with GFP retrovirus.

Fig. 4.

Identification of tissue-specific EC genes. (A) The expression patterns of tissue-specific genes as identified by Significance Analysis of Microarrays among all of the tissue microvascular ECs are shown. The clusters of genes with unique tissue expression in nasal polyps (pink), skin (brown), intestine (orange), lung (blue), and uterus (black) are marked by the indicated color and expanded on the right (B) with selected gene names. Complete data can be found at http://microarray-pubs.stanford.edu/endothelial and in the Stanford Microarray Database (http://genome-www5.stanford.edu/MicroArray/SMD).