bioRxivGenomicsPreprint
Single-cell multimodal profiling of monocytes reveals diverse phenotypes and alterations linked to cardiovascular disease risks
Alexander C. BashoreiD, Chenyi XueiD, Eunyoung KimiD, Hanying YaniD, Lucie Y. ZhuiD, Huize PaniD, Michael D. KissneriD, Leila Saxby RossiD, Hanrui ZhangiD, Mingyao LiiD, Muredach P. ReillyiD
Abstract
Monocytes are a critical innate immune system cell type that serves homeostatic and immunoregulatory functions. The Cell surface expression of CD14 and CD16 has historically identified them, however, recent single-cell studies have uncovered that they are much more heterogeneous than previously realized. We utilized cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) and single-cell RNA sequencing (scRNA-seq) to describe the comprehensive transcriptional and phenotypic landscape of 437,126 monocytes. This high-dimensional multimodal approach identified vast phenotypic diversity and functionally distinct subsets, including IFN-responsive, MHCIIhi, monocyte-platelet aggregates, and non-classical, as well as several subpopulations of classical monocytes. Using flow cytometry, we validated the existence of MHCII+CD275+ MHCIIhi, CD42b+ monocyte-platelet aggregates, CD16+CD99- non-classical monocytes, and CD99+ classical monocytes. Each subpopulation exhibited unique functions, developmental trajectories, transcriptional regulation, and tissue distribution. Moreover, we revealed alterations associated with cardiovascular disease (CVD) risk factors, including race, smoking, and hyperlipidemia, and the effect of hyperlipidemia was recapitulated in mouse models of elevated cholesterol. This integrative and cross-species comparative analysis provides a unique resource to compare alterations in monocytes in pathological conditions and offers insights into monocyte-driven mechanisms in CVD and the potential for targeted therapies. SummaryMultimodal profiling provides a comprehensive phenotypic and transcriptional understanding of monocytes in health and cardiovascular disease risk states.
- organism: human
- organism: mouse
- assay: scRNA-seq
- assay: CITE-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: cell-cell communication
- research focus: benchmarking
- approach: statistical model
- approach: experimental assay
- Citations
- 0
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