NatureGenomicsPeer-reviewed journal article
Spatially resolved multiomics of human cardiac niches
Kazumasa KanemaruiD, James J. CranleyiD, Daniele MuraroiD, Antonio M. A. MirandaiD, Siew Yen HoiD, Anna Wilbrey-ClarkiD, J. Patrick PettiD, Krzysztof PolańskiiD, Laura RichardsoniD, Monika LitviňukováiD, Natsuhiko KumasakaiD, Yue QiniD, Zuzanna JablonskaiD, Claudia I. SemprichiD, Lukáš MachiD, Monika H. Dabrowska, Nathan RichoziD, Liam BoltiD, Lira MamanovaiD, Rakeshlal KapugeiD, Sam N. BarnettiD, Shani PereraiD, Carlos N. Talavera-LópeziD, Ilaria MulasiD, Krishnaa T. A. MahbubaniiD, , Sarah Amalia TeichmanniD
Abstract
A cells function is defined by its intrinsic characteristics and its niche: the tissue microenvironment in which it dwells. Here, we combine single-cell and spatial transcriptomic data to discover cellular niches within eight regions of the human heart. We map cells to micro-anatomic locations and integrate knowledge-based and unsupervised structural annotations. For the first time, we profile the cells of the human cardiac conduction system, revealing their distinctive repertoire of ion channels, G-protein coupled receptors, and cell interactions using a custom CellPhoneDB.org module. We show that the sinoatrial node is compartmentalised, with a core of pacemaker cells, fibroblasts and glial cells supporting paracrine glutamatergic signalling. We introduce a druggable target prediction tool, drug2cell, which leverages single-cell profiles and drug-target interactions, providing unexpected mechanistic insights into the chronotropic effects of drugs, including GLP-1 analogues. In the epicardium, we show enrichment of both IgG+ and IgA+ plasma cells forming immune niches which may contribute to infection defence. We define a ventricular myocardial-stress niche enriched for activated fibroblasts and stressed cardiomyocytes, cell states that are expanded in cardiomyopathies. Overall, we provide new clarity to cardiac electro-anatomy and immunology, and our suite of computational approaches can be deployed to other tissues and organs.
- organism: human
- assay: scRNA-seq
- assay: spatial transcriptomics
- research focus: cell type annotation
- research focus: cell-cell communication
- research focus: drug response / drug discovery
- approach: statistical model
- approach: machine learning (classical)
- Citations
- 427
- FWCI
- 38.96
- Field percentile
- top 1%
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