Spatially resolved multiomics of human cardiac niches

Abstract

A cell's 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.

Spatial multiomics map of trophoblast development in early pregnancy

“…The analysis was done on an updated version of CellPhoneDB-database (v4.1) which includes novel intercellular interactions from refs. 64,65 . Only bona fide manually curated interactions were considered in the analysis.…”

scDrugPrio: A framework for the analysis of single-cell transcriptomics to address multiple problems in precision medicine in immune-mediated inflammatory diseases

“…The main problem in therapeutics, which serves as the basis for this study, is the large number of IMID patients who do not respond to treatment (2,3,29). Previous virtual drug screening methods for inflammatory diseases are based on genetic variance or bulk RNA sequencing (15,30,31) Recent efforts for drug toxicity screening (8,32) support the feasibility of scRNA-seq to capture relevant cellular information. However, systematic solutions for drug prioritisation for IMIDs based on scRNA-seq remain to be devised.…”

Multi‐omic analyses and network biology in cardiovascular disease

“…Even more recently, at the transcriptomic level, Kanemaru et al. used multi‐omic profiling of scRNA‐seq, snRNA‐seq, snATAC‐seq, and spatial transcriptomics data from eight anatomical regions of the adult human heart to identify distinct cellular niches within the microanatomical structures of the heart [158]. A recent preclinical study monitored the molecular changes associated with post‐ischemic remodeling at the transcript, protein, and glycan level with distinct profiles in the non‐ST‐segment elevation MI heart [159].…”