Integrated single-cell analysis-based classification of vascular mononuclear phagocytes in mouse and human atherosclerosis

Abstract

Aims: Accumulation of mononuclear phagocytes [monocytes, macrophages, and dendritic cells (DCs)] in the vessel wall is a hallmark of atherosclerosis. Using integrated single-cell analysis of mouse and human atherosclerosis, we here aimed to refine the nomenclature of mononuclear phagocytes in atherosclerotic vessels and to compare their transcriptomic profiles in mouse and human disease.

Methods and results: We integrated 12 single-cell RNA-sequencing (scRNA-seq) datasets of immune cells isolated from healthy or atherosclerotic mouse aortas, and data from 11 patients (n = 4 coronary vessels, n = 7 carotid endarterectomy specimens) from two studies. Integration of mouse data identified subpopulations with discrete transcriptomic signatures within previously described populations of aortic resident (Lyve1), inflammatory (Il1b), as well as foamy (Trem2hi) macrophages. We identified unique transcriptomic features distinguishing aortic intimal resident macrophages from atherosclerosis-associated Trem2hi macrophages. Also, populations of Xcr1+ Type 1 classical DCs (cDC1), Cd209a+ cDC2, and mature DCs (Ccr7, Fscn1) with a 'mreg-DC' signature were detected. In humans, we uncovered macrophage and DC populations with gene expression patterns similar to those observed in mice. In particular, core transcripts of the foamy/Trem2hi signature (TREM2, SPP1, GPNMB, CD9) mapped to a specific population of macrophages in human lesions. Comparison of mouse and human data and direct cross-species data integration suggested transcriptionally similar macrophage and DC populations in mice and humans.

Conclusions: We refined the nomenclature of mononuclear phagocytes in mouse atherosclerotic vessels, and show conserved transcriptomic features of macrophages and DCs in atherosclerosis in mice and humans, emphasizing the relevance of mouse models to study mononuclear phagocytes in atherosclerosis.

Keywords: Atherosclerosis; Macrophage; Single-cell RNA-seq.

Figure 1

Integrated scRNA-seq analysis of vascular inflammation in mouse atherosclerotic aortas. (A) UMAP representation of integrated scRNA-seq gene expression data in 22 852 cells from mouse atherosclerotic aortas with identification of the major immune cell lineages (DC, dendritic cells; gdT, gammadelta T cells) and (B) projection of single cells in the UMAP space according to dataset and experimental condition of origin. (C) Expression of the indicated transcripts projected onto the UMAP plot.

Figure 2

Characterization of mononuclear phagocyte subpopulations in the atherosclerotic mouse aorta. (A) Expression of the indicated transcripts projected onto the mononuclear phagocyte UMAP plot; (B) projection of cells corresponding to steady state C57BL6 aortic Mac-AIR cells (Williams et al. 2020) on the UMAP plot and (C) high-resolution re-clustering identifying an independent cluster with a Mac-AIR signature; (D) average expression of selected differentially expressed genes in each mononuclear phagocyte population; (E) proportion of the indicated populations among total aortic mononuclear phagocytes (MPCs) in mouse single-cell RNA-seq datasets (see Table 1). For consistency, not all datasets were used in E: datasets from Apoe^–/− mice (Winkels et al. 2018) were excluded as chow fed Apoe^–/− mice do not represent real non-atherosclerotic controls; the ‘Kim Foam Cell’ dataset was excluded as it is technically enriched for foam cells; the 21 days HFD dataset from Williams et al. 2020 was excluded as it represents a very early time point of lesion formation. Each data point represents an individual single-cell RNA-seq dataset. (F) Heatmap showing the mean top rank of transcription factors predicted by ChEA3 in each cluster (heatmap generated from the top 3 ranked transcription factors for each cluster), (G) expression of the indicated transcripts, encoding selected transcription factors, projected onto the mononuclear phagocyte UMAP plot.

Figure 3

Characterization of subpopulations within Trem2^hi macrophages and comparison to Mac-AIR. (A) Expression of shared markers of MAC-AIR, Trem2^hiGpnmb and Trem2^hi-Slamf9 macrophages shown across all mononuclear phagocyte subsets; (B) heatmap showing scaled average expression of marker transcripts for the indicated macrophage subsets; (C) expression of selected markers of MAC-AIR, Trem2^hiGpnmb and Trem2^hi-Slamf9 macrophages shown across these clusters (violin plots) and projected onto the UMAP plot of total mononuclear phagocytes; (D) Gene Ontology analysis for enriched biological processes for MAC-AIR, Trem2^hiGpnmb and Trem2^hi-Slamf9 macrophages. Selected overlapping and unique biological processes for each macrophage population were selected to generate the data visualization, the full analysis can be found in Supplementary material online, Excel Table S2.

Figure 4

scRNA-seq data-based classification of mouse aortic mononuclear phagocytes in atherosclerosis. (A) Violin plot showing expression of the indicated macrophage/dendritic cell markers; (B-C) heatmaps showing scaled average expression of mononuclear phagocyte defining marker transcripts in (B) dendritic cell subsets and (C) macrophage subsets; (D) proposed updated, scRNA-seq data-based classification of mononuclear phagocyte subpopulations and their markers in the atherosclerotic mouse aorta.

Figure 5

Integrated scRNA-seq analysis of macrophages in human atherosclerosis. (A) UMAP representation and clustering analysis of integrated scRNA-seq gene expression data in 2890 human mononuclear phagocytes from atherosclerotic lesions; (B) expression of selected genes projected onto the UMAP plot; (C) heatmap of averaged gene expression (top 10 genes ordered by fold change) in the clusters (Inflamm = Inflammatory); (D) DotPlot showing the expression of transcripts enriched in human inflammatory-Mφ, foamy-Mφ and LYVE1-Mφ that are also enriched in their putative mouse counterparts (i.e. mouse inflammatory-Mφ, foamy/Trem2^hi-Mφ, and resident/resident-like-Mφ respectively). (E) Heatmap showing the mean top rank of transcription factors predicted by ChEA3 in each cluster (heatmap generated from the top 3 ranked transcription factors for each cluster).

Figure 6

Cross-species scRNA-seq integrated analysis of macrophages in murine and human atherosclerosis. (A) Median genes detected per single cell in the mouse dataset used for cross-species integration before and after conversion to human gene symbols; (B) UMAP plot and clustering analysis (with annotation) of the mouse/human integrated data; (C) cell species of origin projected onto the UMAP plot; (D) heatmap of enriched genes in the integrated cluster (top 5 ordered by fold change); and (E) expression of characteristic conserved marker transcripts of macrophage subsets projected onto the UMAP plot, split by species of origin.