Spatially resolved multiomics of human cardiac niches

The function of a cell is defined by its intrinsic characteristics and its niche: the tissue microenvironment in which it dwells. Here we combine single-cell and spatial transcriptomics data to discover cellular niches within eight regions of the human heart. We map cells to microanatomical locations and integrate knowledge-based and unsupervised structural annotations. We also profile the cells of the human cardiac conduction system1. The results revealed their distinctive repertoire of ion channels, G-protein-coupled receptors (GPCRs) and regulatory networks, and implicated FOXP2 in the pacemaker phenotype. We show that the sinoatrial node is compartmentalized, with a core of pacemaker cells, fibroblasts and glial cells supporting glutamatergic signalling. Using a custom CellPhoneDB.org module, we identify trans-synaptic pacemaker cell interactions with glia. We introduce a druggable target prediction tool, drug2cell, which leverages single-cell profiles and drug–target interactions to provide 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 that may contribute to infection defence. Overall, we provide new clarity to cardiac electro-anatomy and immunology, and our suite of computational approaches can be applied to other tissues and organs.

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March 2021
Data Policy information about availability of data All manuscripts must include a data availability statement. This statement should provide the following information, where applicable: -Accession codes, unique identifiers, or web links for publicly available datasets -A description of any restrictions on data availability -For clinical datasets or third party data, please ensure that the statement adheres to our policy Open access datasets are available from ArrayExpress (www.ebi.ac.uk/arrayexpress), with accession numbers E-MTAB-12916 (Multiome snRNA-seq), E-MTAB-12919 (Multiome snATAC-seq), and XX (Visium). Processed data of sc/snRNAseq and Visium data are available for browsing gene expression and download via heartcellatlas.org (https://www.heartcellatlas.org/ #ver2)(User: heart, Password: ver2, the link will be publically available at the time of publication). A CellTypist model trained on this atlas is available for download from https://www.heartcellatlas.org/#ver2 for automated cell type annotation of other cardiac sc/snRNA-seq datasets. CellPhoneDB NeuroGPCR expansion module is available from Supp. Note that full information on the approval of the study protocol must also be provided in the manuscript.

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Sample size were determined by availability of donors within the sampling time-frame. No statistical methods were used to calculate appropriate sample size. We followed standards in the field and Human Cell Atlas criteria.
Data exclusions For the final count matrix, we excluded cells and spots of spatial transcriptomics samples based on pre-established criteria. Cells or nuclei for each sample were filtered for more than 200 genes and less than 20% (cells) or 5% (nuclei) mitochondrial and ribosomal reads. A Scrublet (v.0.2.3) score cut-off 0.3 of was applied to remove doublets. Visium spots of each sample were filtered for more than 500 UMI counts and 300 genes.
Multiome (paired single-nuclei RNA and ATAC sequencing) was performed on the 8 regions of heart tissue from 10 adult donors, with comparable results among the donors. Visium spatial transcriptomics was performed on the 8 regions of heart tissue from 12 adult donors, with consistencies of the results between donors.
For in-vitro iPCS-CM, experiments were performed using three independent differentiation batches with similar results.
Randomization Randomization was not relevant due to the study design where sample collection was based on availability of transplant donors.

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For the sequencing samples, we made no comparison between discreet groups for human participants, thus blinding of investigators was not necessary.
Reporting for specific materials, systems and methods We require information from authors about some types of materials, experimental systems and methods used in many studies. Here, indicate whether each material, system or method listed is relevant to your study. If you are not sure if a list item applies to your research, read the appropriate section before selecting a response. HCN1 (APC-056): validated with WB, IF, and immunocytochemistry against human, mouse, and rat HCN1. The specificity has been validated in a knockout or knockdown system. The data shown on the supplier website. HCN4 (APC-052): validated with WB, IF, and immunocytochemistry against human, mouse, and rat HCN4. The specificity has been validated in a knockout or knockdown system. The data shown on the supplier website. cTnT (MA5-12960): validated with WB, IF, and IHC against dog, hamster, human, mouse, pig, rat, xenopus, zebrafish cTnT. This Antibody was verified by Cell treatment to ensure that the antibody binds to the antigen. The data shown on the supplier website. GLP1R (AGR-021): validated with WB, IF, and IHC against human, mouse, and rat GLP1R. The data shown on the supplier website. HCN1 (ab84816): validated with WB, IHC, and flow cytometry against human, mouse, and rat HCN1. The data shown on the supplier website. PLP1 (ab254363): validated with WB, IF, IHC, and immunocytochemistry against human, mouse, and rat PLP1. The data shown on the supplier website.