Mapping the cellular and molecular landscape of cardiac non-myocytes in murine diabetic cardiomyopathy

Figures

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  Figure 1. Analysis of the T2D (db/db) mouse heart cellulome (A and B) Schematic indicating the analyses conducted on the db/db and db/h mouse hearts. Single-cell RNA sequencing was performed in 17-week old male db/db (n = 4) and db/h (n = 3) mouse hearts, as previously described.15 (C) Merged t-SNE projection of all captured cardiac non-myocyte cells with adjacent split tSNE projections from db/h and db/db mice. (D) Barplot summarising relative abundances of major cell types represented in the single-cell RNA sequencing dataset. (E) Dot plot illustrating the top-5 most highly expressed genes within each cell cluster. Dot size indicates the relative proportions of cells expressing a given gene and dot color indicates the relative average expression level.

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  Figure 2. Differentially expressed genes in the db/db heart (A) Dot plot illustrating the top upregulated genes in db/db hearts relative to db/h counterparts. (B) Downregulated gene expression patterns within db/db hearts relative to db/h counterparts. Dot color is relative to the average expression within each cell cluster (green = upregulated, purple = downregulated). Dot size indicates fold change in db/db non-myocyte cells relative to db/h control cells. Points within the center of colored dots indicate a statistical difference in gene expression in db/db hearts relative to db/h controls (uncorrected p < 0.0001). (C) Representative cardiac cross-sections of db/db and db/h hearts (Scale bar = 475μm). (D and E) Quantified immunoreactivity of HSPA1A in db/db and db/h heart sections. (F and G) Dot plots illustrating the top-3 gene ontology (GO) terms for upregulated genes and downregulated genes, respectively, in each broad cell type (corrected p < 0.05). For GO terms, circle size indicates the number of genes corresponding to a given term and color intensity indicates statistical significance (p.adjust). See corresponding Tables S2 and S3 for additional information relating to…

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  Figure 3. Intercellular communication is increased in the db/db heart (A) Heatmap indicating the number of cell-cell interactions in db/db hearts, determined by CellphoneDB analysis. Color intensity and values within the boxes indicate the number of connections between individual cell populations. (B) Bar plot showing the net cellular interactions in each major cell type in db/h and db/db hearts. (C and D) GO terms enriched in genes corresponding to upregulated ligands (C) and upregulated receptors (D) in db/db hearts, relative to db/h controls. (E and F) GO terms enriched in genes corresponding to (E) downregulated ligands and (F) downregulated receptors, in db/db hearts relative to db/h controls. Circle size indicates the number of genes corresponding to a given GO term and color intensity indicates statistical significance (p < 0.01).

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  Figure 4. Analysis of cardiac fibroblasts in the db/db heart (A) Merged tSNE plot highlighting cardiac fibroblasts relative to other cardiac non-myocytes. (B) Number of cells within each cardiac fibroblast sub-cluster in db/h and db/db mice. (C) Flow cytometry gating strategies employed for the selection of fibroblasts and mural cells in an age-matched cohort of db/h and db/db mice. Quantified flow cytometry data corresponding to gating strategies above (n = 8/group). Flow cytometry data was analyzed statistically using the Wilcoxon rank-sum test to determine differences between groups. This data is presented as median ±SD, ∗∗p < 0.01. (D) Violin plot of distinct marker genes within each fibroblast sub-cluster. (E) Top-3 differentially expressed genes within each fibroblast cluster in db/db mice, relative to db/h controls. Dot color and size are proportional to average expression and fold change, respectively, within each cell cluster. Black points located within the center of some circles indicate a significant difference in gene expression in db/db mice compared to db/h mice (uncorrected p < 0.01).

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  Figure 5. A subset of cardiac resident macrophages are lost in db/db hearts (A) Merged tSNE plot highlighting cardiac macrophages, relative to other cardiac non-myocyte cells. (B) tSNE projection of in silico isolated macrophages, in db/h and db/db mouse hearts. (C) Flow cytometry gating strategy for selecting cardiac leukocytes with adjacent quantified results of various cardiac leukocyte subtypes analyzed. Flow cytometry data was analyzed statistically using the Wilcoxon rank-sum test to determine differences between the groups. This data is presented as median ±SD, ∗p < 0.05, ∗∗p < 0.01. Macs = macrophages, MHCIIhi = MHCII “high” macrophages, MHCIIlo = MHCII “low” macrophages, Gran. = granulocytes, Ly6Chi = Ly6C “high” monocytes. (D) Violin-plot mapping established macrophage markers, as well as critical reverse cholesterol/lipid transporters. (E) GO analysis of distinct genes in Macrophage clusters 1 and 2, relative to Macrophage 3. Bar plot lists the top 20 GO terms enriched in genes from Macrophage 1 and 2, compared to Macrophage 3. The x axis indicates the number of genes mapped to a given GO term, which themselves are displayed on the y axis. Bar color indicates the adjusted p…

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  Figure 6. Integration of unaffiliated bulk RNA sequencing datasets highlights common molecular pathways in the diabetic heart (A) Proportional Venn diagram illustrating unique and common differentially expressed genes in our scRNA-seq dataset relative to two publicly available bulk RNAseq datasets of the diabetic heart. (B) Between all datasets analyzed, there were 21 common genes. Gene lists were derived from each overlap and subsequently underwent GO enrichment analysis. GO analysis revealed the top 20 common biological functions (y axis) and the collection of genes corresponding to each GO term (x axis). (C) GO analysis of bulk RNA-seq genes in the T1D Akita mouse heart relative to our db/db scRNA-seq dataset. (D) GO analysis pertaining to common genes in the db/db bulk RNAseq dataset compared to the db/db scRNA-seq dataset, highlighting key non-myocyte differentially expressed genes. The hypergeometric p values displayed in B-D correspond to the statistical significance of the overlaps between gene sets (highlighted in red). Datasets were obtained from the Gene Expression Omnibus (GEO) repository. “Akita” dataset identifier: GSE66577. Bulk RNAseq db/db dataset identifier: GSE36875.