Transcriptome Analysis Reveals Nonfoamy Rather Than Foamy Plaque Macrophages Are Proinflammatory in Atherosclerotic Murine Models

Abstract

Rationale: Monocyte infiltration into the subintimal space and their intracellular lipid accumulation are the most prominent features of atherosclerosis. To understand the pathophysiology of atherosclerotic disease, we need to understand the characteristics of lipid-laden foamy macrophages in the subintimal space during atherosclerosis. Objective: We sought to examine the transcriptomic profiles of foamy and non-foamy macrophages isolated from atherosclerotic intima. Methods and Results: Single-cell RNA-sequencing analysis of CD45+ leukocytes from murine atherosclerotic aorta revealed that there are macrophage subpopulations with distinct differentially expressed genes involved in various functional pathways. To specifically characterize the intimal foamy macrophages of plaque, we developed a lipid staining-based flow cytometric method for analyzing the lipid-laden foam cells of atherosclerotic aortas. We employed the fluorescent lipid probe BODIPY493/503 and assessed side-scattered light (SSC) as an indication of cellular granularity. BODIPYhiSSChi foamy macrophages were found residing in intima and expressing CD11c. Foamy macrophage accumulation determined by flow cytometry was positively correlated with the severity of atherosclerosis. Bulk RNA-seq analysis showed that compared with non-foamy macrophages, foamy macrophages expressed few inflammatory genes but many lipid-processing genes. Intimal non-foamy macrophages formed the major population expressing interleukin-1β and many other inflammatory transcripts in atherosclerotic aorta. Conclusions: RNA-seq analysis of intimal macrophages from atherosclerotic aorta revealed that lipid-loaded plaque macrophages are not likely the plaque macrophages that drive lesional inflammation.

Alterations of multiple alveolar macrophage states in chronic obstructive pulmonary disease

“…In addition, the investigation of orthologous gene signatures derived from murine lipid-associated macrophages (LAM), which were shown to be monocyte-derived by lineage tracing and also detected in human adipose tissue (Jaitin et al, 2019), again revealed the strongest enrichment in mono-like and C1Q + AMs ( Figure 7B). The same was also true for orthologous genes derived from Trem2 + foam cells of atherosclerotic plaques in mice (Kim et al, 2018) (Figure 7B), which were found by Lin et al to originate from monocytes (Lin et al, 2019), supporting the hypothesis that mono-like and C1Q + AMs are actually derived from monocytes.…”

Alzheimer’s patient brain myeloid cells exhibit enhanced aging and unique transcriptional activation

“…3b), though the genes involved are completely distinct between species 1 . Second, an emerging theme in recent mouse DAM literature is the role of lipid and lysosomal biology: many mouse DAM genes such as apoe , Ch25h , Lpl , Ctsb and Atp6v0d2 are known to function in lipid and lysosomal biology and can be induced by lipid pathologies including demyelination 16 and atherosclerosis 17,18 . In our data, in addition to APOE , we found that the lipoprotein receptor LSR and the lysosomal enzyme ARSA —homozygous mutations in which cause metachromatic leukodystrophy 19 —are elevated in myeloid cells from AD patients.…”

Time-resolved single-cell transcriptomics uncovers dynamics of cardiac neutrophil diversity in murine myocardial infarction

“…The recent development of single-cell RNA-sequencing (scRNA-seq) in highthroughput allows investigating immune cell transcriptional states in disease models with high resolution, and has recently been employed to uncover novel immune cell transcriptional states in e.g. myocardial infarction (13), (14) or atherosclerosis (15), (16). Furthermore, novel methods of oligonucleotide-barcoded antibody labeling of cells prior to their processing for scRNA-seq allows a multimodal measurement of the expression of cell surface epitopes in addition to transcripts expression (17), (18) and the multiplexing of several biological samples in a single scRNA-seq library (19).…”