Single-cell reconstruction of the adult human heart during heart failure and recovery reveals the cellular landscape underlying cardiac function

Abstract

Owing to the prevalence and high mortality rates of cardiac diseases, a more detailed characterization of the human heart is necessary; however, this has been largely impeded by the cellular diversity of cardiac tissue and limited access to samples. Here, we show transcriptome profiling of 21,422 single cells—including cardiomyocytes (CMs) and non-CMs (NCMs)—from normal, failed and partially recovered (left ventricular assist device treatment) adult human hearts. Comparative analysis of atrial and ventricular cells revealed pronounced inter- and intracompartmental CM heterogeneity as well as compartment-specific utilization of NCM cell types as major cell-communication hubs. Systematic analysis of cellular compositions and cell–cell interaction networks showed that CM contractility and metabolism are the most prominent aspects that are correlated with changes in heart function. We also uncovered active engagement of NCMs in regulating the behaviour of CMs, exemplified by ACKR1+-endothelial cells, injection of which preserved cardiac function after injury. Beyond serving as a rich resource, our study provides insights into cell-type-targeted intervention of heart diseases.

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Fig. 1: Overview of the cell composition of the normal adult human heart.
Fig. 2: Heterogeneity of inter- and intracompartmental CMs.
Fig. 3: AV CMs are present in both LV and LA normal human myocardium.
Fig. 4: Functional diversity and compartment-specific roles of NCM subtypes.
Fig. 5: Compartment- and aetiology-specific alterations of CMs in HF.
Fig. 6: The cellular basis of HF caused by coronary heart disease (cHF).
Fig. 7: Active engagement of NCMs in HF.
Fig. 8: Single-cell characterization of the recovery of cardiac function.

Data availability

scRNA-seq data that support the findings of this study have been deposited in the Gene Expression Omnibus (GEO) under accession codes GSE109816 and GSE121893. All other data supporting the findings of this study are available from the corresponding authors on reasonable request.

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Acknowledgements

This work was supported by the National Key R&D Program of China (2016YFC1300900 and 2017YFA0103700), the CAMS Initiative for Innovative Medicine (2017-I2M-1-003, 2018-I2M-3-002 and 2016-I2M-1-015) and the National Natural Science Foundation of China (grant numbers 91639107, 31671542 and 81722006 to L.W.; 81700337 to B.Z.).

Author information

L.W., B.Z., J.S. and S.H. designed the experiments. B.Z., G.G., Y.W. and J.S. isolated cells for scRNA-seq. Z.L., Y.W. and X.C. performed immunostaining. L.W. and Z.L. performed scRNA-seq library generation and sequencing. M.Z. performed animal experiments. P.Y. and L.H. performed bioinformatics analyses. L.W., P.Y., B.Z. and S.H. interpreted data. L.W., B.Z. and S.H. wrote the manuscript.

Correspondence to Li Wang or Shengshou Hu.

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The authors declare no competing interests.

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Extended data

Extended Data Fig. 1 Quality metrics and marker gene expression in single cells of the normal adult human heart.

a-c, Quality metrics for single-cell RNA-Seq data showing distributions of number of reads per cell (a), alignment rate per cell (b), and number of genes detected per cell (c). d, Gene expression of specific markers in a designated cell type (the mean logTPM of known markers). e, Correlation between detected and expected ERCC (spike-in) RNAs. Each dot represents one spike-in RNA.

Extended Data Fig. 2 Donor contribution to cell clustering and comparison between left and right ventricles.

a, Contribution of each individual donor to each cell cluster. Each color represents a donor. b, t-SNE clustering of CMs isolated from both LV and LA of the same donor (N13 and N14). c, Donor information and numbers of cells from the right ventricles sequenced via single-cell RNA-Seq. d,e, t-SNE clustering of CMs isolated from both left ventricle (LV) and right ventricle (RV) marked by tissue source (d) or cluster number (e). f, Heatmap showing DEGs between LV-CMs and LA-CMs. g, Selected top KEGG categories of DEGs in LV-CMs and RV-CMs.

Extended Data Fig. 3 Aging trajectory of CMs from left atria and left ventricles.

a,b, Monocle analyses showing the ordering of CMs from LA (a) or LV (b) along pseudotime trajectories. CMs are color-labeled by donor age. c, Heatmap of different blocks of DEGs along the pseudotime trajectory of LV-CMs (b). Right, representative genes in each gene cluster. d, Selected top KEGG terms related to corresponding DEGs in c.

Extended Data Fig. 4 Characterization of CM subtypes in left ventricle and left atria.

a,c, Heatmaps showing differentially expressed genes (DEGs) among CM subclusters in LA (a) and LV (c). Right: representative genes in each subcluster. For numerical source data, see Source Data Extended Data Fig. 4. b,d, Selected top GO enrichment categories of DEGs in a and c. e, Heatmap to show regulon activities of top factors in LA-CMs, LV-CMs, and AV-CMs, respectively. f, Scatter plots to show the expression changes of representative genes in the HSF2 regulon or NFIL3 regulon in LA-CMs versus LV-CMs, respectively. The blue line is the smoothed mean line by LOESS method and the grey shade represents 95% confidence interval. g, Box plots to show the expression levels of DOCK6 and SMARCA4 in AV-CMs, LA-CMs, and LV-CMs. Each box represents the median and the lower and upper quantiles, and the whiskers indicate 1.5 times of the interquartile range. LA: n=1630 cells, LV: n=1706 cells, AV: n=558 cells. Source data

Extended Data Fig. 5 Characterization of CM subtypes in left ventricle and left atria.

a,b, t-SNE clustering of all MPs, FBs, and SMCs identified in Fig. 1c based on their marker genes. Cells are color-labeled by subcluster (a) or tissue source (b). c, Contribution of each individual donor to each cell cluster.

Extended Data Fig. 6 Putative cell-cell interactions in LA and LV.

a,b, Statistical analysis of cell-cell communication counts in each cell type based on the putative ligand-receptor interactions in LA (a) or LV (b). c,d, Statistical analysis of counts of ligand usage in LA (c) or LV(d) in their interaction with other cell types. Top 10 are shown. e,f, Statistical analysis of counts of receptor usage in LA (e) or LV (f) in their interactions with other cell types, respectively. Top 10 are shown. For numerical source data, see Source Data Extended Data Fig. 6. Source data

Extended Data Fig. 7 Alterations of cardiomyocytes in heart failure.

a, Donor information and numbers of cells sequenced via single-cell RNA-Seq. b-d, Quality metrics for single-cell RNA-Seq data showing distributions of number of reads per cell (b), alignment rate per cell (c), and number of genes detected per cell (d). e,f, Monocle analyses showing the ordering of CMs along pseudotime marked by heart condition (e) or CM subcluster (f).

Extended Data Fig. 8 Compartment- and aetiology-specific alterations of cardiomyocytes in heart failure.

a,b, Monocle analyses showing the ordering of CMs along pseudotime marked by heart condition (a) or CM state (b). c, Distribution of CMs from different heart conditions (N_CM, cHF_CM, and dHF_CM) in each defined CM state (Normal, cHF, dHF) based on a. d, Heatmap of different blocks of DEGs along the pseudotime trajectory. Right, representative genes in each gene cluster. For numerical source data, see Source Data Extended Data Fig. 8. e, Selected top GO terms related to corresponding DEGs in d. f-h, Co-staining of ACTN2 and S100A6 (f), DKK3 (g), or ROCK (h) in heart sections from normal, cHF and dHF hearts, respectively. Scale bar = 25 μm. Data are representative of 6 independent experiments yielding similar results. i, Regulon activities of NR1H2, KLF4, XBP1, CREB5, EGR1, and JUN, in normal, cHF, and dHF. Each box represents the median and the lower and upper quantiles, and the whiskers indicate 1.5 times of the interquartile range. Normal LV: n=400 cells, cHF_LV: n=429 cells and dHF_LV: n=305 cells. Two-tailed Wilcoxon rank sum test was used. Source data

Extended Data Fig. 9 Cellular basis of heart failure caused by dilated cardiomyopathy (dHF).

a, Ratio changes of cell clusters in dHF versus normal heart. Only cell clusters with ratio changes above the median number are shown. b, Correlation analysis of potentially matched pairs between the ligands secreted by changed cell clusters (a) and enriched biological behaviors of CMs in dHF. c, Heatmap displaying the expression of genes indicated in correlation analysis (b) across changed cell clusters (a). For numerical source data, see Source Data Extended Data Fig. 9. d, Sum of all matched ligands (c) expressed in different cell clusters. Source data

Extended Data Fig. 10 Contributions of non-cardiomyocytes (NCMs) in heart failure.

a-d, Ratio changes of cell subclusters in major cell types, including FB (a), EC (b), MP (c), and SMC (d), in normal versus failed hearts. Only cell clusters with ratio changes above the median are shown. e,f, Statistical analysis of ligand (e) or receptor (f) usage based on the putative ligand-receptor interactions (Fig. 7b). Top 10 are shown. For numerical source data, see Source Data Extended Data Fig. 10. g, Violin plot displaying transcriptome similarities among different cell types in the normal heart. A boxplot is shown on the inside (center line, median; box limits, upper and lower quartiles; whiskers, 1.5x interquartile range; n = 7,495 cells). h, Gating strategy of flow cytometry. P1: all sorted ECs; P2: ACKR1--ECs; P3: ACKR1+-ECs. Source data

Supplementary information

Reporting Summary

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Healthy donor information.

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Wang, L., Yu, P., Zhou, B. et al. Single-cell reconstruction of the adult human heart during heart failure and recovery reveals the cellular landscape underlying cardiac function. Nat Cell Biol 22, 108–119 (2020). https://doi.org/10.1038/s41556-019-0446-7

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