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. 2022 Apr 6;12(1):5807.
doi: 10.1038/s41598-022-09616-9.

Naturally occurring combinations of receptors from single cell transcriptomics in endothelial cells

Sergii Domanskyi  1 , Alex Hakansson  2 , Michelle Meng  2 , Benjamin K Pham  2 , Joshua S Graff Zivin  3 , Carlo Piermarocchi  4 , Giovanni Paternostro  5 , Napoleone Ferrara  6
Affiliations

Naturally occurring combinations of receptors from single cell transcriptomics in endothelial cells

Sergii Domanskyi et al. Sci Rep. .

Abstract

VEGF inhibitor drugs are part of standard care in oncology and ophthalmology, but not all patients respond to them. Combinations of drugs are likely to be needed for more effective therapies of angiogenesis-related diseases. In this paper we describe naturally occurring combinations of receptors in endothelial cells that might help to understand how cells communicate and to identify targets for drug combinations. We also develop and share a new software tool called DECNEO to identify them. Single-cell gene expression data are used to identify a set of co-expressed endothelial cell receptors, conserved among species (mice and humans) and enriched, within a network, of connections to up-regulated genes. This set includes several receptors previously shown to play a role in angiogenesis. Multiple statistical tests from large datasets, including an independent validation set, support the reproducibility, evolutionary conservation and role in angiogenesis of these naturally occurring combinations of receptors. We also show tissue-specific combinations and, in the case of choroid endothelial cells, consistency with both well-established and recent experimental findings, presented in a separate paper. The results and methods presented here advance the understanding of signaling to endothelial cells. The methods are generally applicable to the decoding of intercellular combinations of signals.

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Conflict of interest statement

CP and GP own shares of Salgomed, Inc. SD, AH, MM, BKP, JGZ and NF declare no potential conflict of interest.

Figures

Figure 1
Figure 1
Flowchart with details and rationale of the main steps followed by our process. Additional features not mentioned in the flowchart are: Visualization: As shown in Fig. 2, the DECNEO software provides visualizations of the dendrogram and panels that plot the measures described above. It also highlights the location in the dendrogram of the known angiogenesis receptors and allows users to inspect individual measures and to identify cases when they are not concordant. Statistical analysis and validation: Multiple validations and statistical tests are performed, including a permutation test, validations with independent datasets, the use of a set of receptors with known function (which includes VEGF receptors and other receptors previously shown to play a role in angiogenesis) and interface with other common functional enrichment methods using DAVID and Metascape. Application to intercellular communication: An extension of the method, shown in Fig. 5, can be used to analyze ligands and receptor for a pair of cells. Further evidence for the functional importance of naturally occurring combinations of receptors is obtained by identifying the corresponding naturally occurring combinations of ligands.
Figure 2
Figure 2
Dendrogram analysis identifies naturally occurring combinations of angiogenesis receptors in endothelial cells. The top of panels (A) and (B) displays the dendrogram ordering by single cell co-expression of receptors in endothelial cells for: (A) Mus musculus and (B) Homo sapiens. Receptors that are co-expressed in individual cells are closer to each other in the dendrogram order. Known angiogenesis receptors are labeled under the dendrogram. The red pointer indicates KDR, the main VEGFA receptor. The panels immediately below the dendrogram show three measures: Expression fraction, Network enrichment and Evolutionary conservation. The lowest panel shows the combination of these three measures. The solid orange line in each panel is a moving window average. The largest peak in the combination of measures panel, representing the main comberon (abbreviation for naturally occurring combination) is shown with a red background.
Figure 3
Figure 3
Analysis of endothelial cells from selected studies in PanglaoDB database annotated by DCS. Clustering of Pearson correlation of the largest peak bootstrap frequencies for the combination of measures. Studies from almost all similar tissues group together.
Figure 4
Figure 4
Comberons of endothelial cells of specific tissues from PanglaoDB and choroid. Under All we include the global analysis shown in Table 1 for comparison. The 13 receptors to the left of the red line are the 13 top receptors from Table 1 (with a boostrap frequency higher than 0.9). The rest of the receptors are within the top-10 tissue-specific genes for at least one set.
Figure 5
Figure 5
Two-dimensional matrix of receptor co-expression in human choroid endothelial cells and of the corresponding ligands co-expression in human choroid fibroblasts . Ligands or receptors co-expressed in individual cells are closer to each other in the dendrogram order. The peaks represent the combination of measures, as in the dendrograms of Fig. 2. Endothelial receptors are on the x-axis and fibroblasts ligands on the y-axis. Known choroid endothelial receptors labels are shown on the horizontal axis and the corresponding ligands are shown on the vertical axis. The box indicates the region with the highest combinatorial communication measures.
Figure 6
Figure 6
Summary of the analysis pipeline. Normalized single cell transcriptomics datasets are processed in steps depicted in panel (A). The principal steps of the pipeline are outlined in panels (B), (C) and (D). An analysis report is generated at the end of the pipeline.
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