Antoine‐Emmanuel Saliba

Phenotypically identical cells can dramatically vary with respect to behavior during their lifespan and this variation is reflected in their molecular composition such as the transcriptomic landscape. Single-cell transcriptomics using next-generation transcript sequencing (RNA-seq) is now emerging as a powerful tool to profile cell-to-cell variability on a genomic scale. Its application has already greatly impacted our conceptual understanding of diverse biological processes with broad implications for both basic and clinical research. Different single-cell RNA-seq protocols have been introduced and are reviewed here-each one with its own strengths and current limitations. We further provide an overview of the biological questions single-cell RNA-seq has been used to address, the major findings obtained from such studies, and current challenges and expected future developments in this booming field.

Rationale: It is assumed that atherosclerotic arteries contain several macrophage subsets endowed with specific functions. The precise identity of these subsets is poorly characterized as they have been defined by the expression of a restricted number of markers. Objective: We have applied single-cell RNA sequencing as an unbiased profiling strategy to interrogate and classify aortic macrophage heterogeneity at the single-cell level in atherosclerosis. Method and Results: We performed single-cell RNA sequencing of total aortic CD45 + cells extracted from the nondiseased (chow fed) and atherosclerotic (11 weeks of high-fat diet) aorta of low-density lipoprotein receptor–deficient ( Ldlr −/− ) mice. Unsupervised clustering singled out 13 distinct aortic cell clusters. Among the myeloid cell populations, resident-like macrophages with a gene expression profile similar to aortic resident macrophages were found in healthy and diseased aortas, whereas monocytes, monocyte-derived dendritic cells, and 2 populations of macrophages were almost exclusively detectable in atherosclerotic aortas, comprising inflammatory macrophages showing enrichment in Il1b and previously undescribed TREM2 hi (triggered receptor expressed on myeloid cells 2) macrophages showing enrichment in Trem2 . Differential gene expression and gene ontology enrichment analyses revealed specific gene expression patterns distinguishing these 3 macrophage subsets and monocyte-derived dendritic cells and uncovered putative functions of each cell type. Notably, TREM2 hi macrophages seemed to be endowed with specialized functions in lipid metabolism and catabolism and presented a gene expression signature reminiscent of osteoclasts, suggesting a role in lesion calcification. TREM2 expression was moreover detected in human lesional macrophages. Importantly, these macrophage populations were present also in advanced atherosclerosis and in Apoe −/− aortas, indicating relevance of our findings in different stages of atherosclerosis and mouse models. Conclusions: These data unprecedentedly uncovered the transcriptional landscape and phenotypic heterogeneity of aortic macrophages and monocyte-derived dendritic cells in atherosclerotic and identified previously unrecognized macrophage populations and their gene expression signature, suggesting specialized functions. Our findings will open up novel opportunities to explore distinct myeloid cell populations and their functions in atherosclerosis.

Rationale: Atherosclerosis is a chronic inflammatory disease that is driven by the interplay of pro- and anti-inflammatory leukocytes in the aorta. Yet, the phenotypic and transcriptional diversity of aortic leukocytes is poorly understood. Objective: We characterized leukocytes from healthy and atherosclerotic mouse aortas in-depth by single-cell RNA-sequencing and mass cytometry (cytometry by time of flight) to define an atlas of the immune cell landscape in atherosclerosis. Methods and Results: Using single-cell RNA-sequencing of aortic leukocytes from chow diet– and Western diet–fed Apoe −/− and Ldlr −/− mice, we detected 11 principal leukocyte clusters with distinct phenotypic and spatial characteristics while the cellular repertoire in healthy aortas was less diverse. Gene set enrichment analysis on the single-cell level established that multiple pathways, such as for lipid metabolism, proliferation, and cytokine secretion, were confined to particular leukocyte clusters. Leukocyte populations were differentially regulated in atherosclerotic Apoe −/− and Ldlr −/− mice. We confirmed the phenotypic diversity of these clusters with a novel mass cytometry 35-marker panel with metal-labeled antibodies and conventional flow cytometry. Cell populations retrieved by these protein-based approaches were highly correlated to transcriptionally defined clusters. In an integrated screening strategy of single-cell RNA-sequencing, mass cytometry, and fluorescence-activated cell sorting, we detected 3 principal B-cell subsets with alterations in surface markers, functional pathways, and in vitro cytokine secretion. Leukocyte cluster gene signatures revealed leukocyte frequencies in 126 human plaques by a genetic deconvolution strategy. This approach revealed that human carotid plaques and microdissected mouse plaques were mostly populated by macrophages, T-cells, and monocytes. In addition, the frequency of genetically defined leukocyte populations in carotid plaques predicted cardiovascular events in patients. Conclusions: The definition of leukocyte diversity by high-dimensional analyses enables a fine-grained analysis of aortic leukocyte subsets, reveals new immunologic mechanisms and cell-type–specific pathways, and establishes a functional relevance for lesional leukocytes in human atherosclerosis.