A transcriptional cross species map of pancreatic islet cells

Abstract

Objective: Pancreatic islets of Langerhans secrete hormones to regulate systemic glucose levels. Emerging evidence suggests that islet cells are functionally heterogeneous to allow a fine-tuned and efficient endocrine response to physiological changes. A precise description of the molecular basis of this heterogeneity, in particular linking animal models to human islets, is an important step towards identifying the factors critical for endocrine cell function in physiological and pathophysiological conditions.

Methods: In this study, we used single-cell RNA sequencing to profile more than 50'000 endocrine cells isolated from healthy human, pig and mouse pancreatic islets and characterize transcriptional heterogeneity and evolutionary conservation of those cells across the three species. We systematically delineated endocrine cell types and α- and β-cell heterogeneity through prior knowledge- and data-driven gene sets shared across species, which altogether capture common and differential cellular properties, transcriptional dynamics and putative driving factors of state transitions.

Results: We showed that global endocrine expression profiles correlate, and that critical identity and functional markers are shared between species, while only approximately 20% of cell type enriched expression is conserved. We resolved distinct human α- and β-cell states that form continuous transcriptional landscapes. These states differentially activate maturation and hormone secretion programs, which are related to regulatory hormone receptor expression, signaling pathways and different types of cellular stress responses. Finally, we mapped mouse and pig cells to the human reference and observed that the spectrum of human α- and β-cell heterogeneity and aspects of such functional gene expression are better recapitulated in the pig than mouse data.

Conclusions: Here, we provide a high-resolution transcriptional map of healthy human islet cells and their murine and porcine counterparts, which is easily queryable via an online interface. This comprehensive resource informs future efforts that focus on pancreatic endocrine function, failure and regeneration, and enables to assess molecular conservation in islet biology across species for translational purposes.

Keywords: Cross species conservation; Pancreatic islets; Single-cell RNAseq; Translation; α-Cell; β-Cell.

Figure 1

Conservation of endocrine signatures in human, pig, and mouse islets. A) UMAP plots of scRNA-seq data of human, pig and mouse pancreatic islets capturing all 4 major endocrine populations. Barplots show cell type compositions, which reflect islet composition in vivo. B) Expression of islet hormones and known endocrine and lineage transcription factors in human, pig and mouse endocrine cell types. Color intensity indicates mean expression in a cluster, dot size indicates the proportion of cells in a cluster expressing the gene. Expression is scaled per gene. N. a. means genes were not detected. C) Overview of gene orthologue mapping between species to assess conservation of the human transcriptional signature. Explained variance is the fraction of the total variance captured by the subset of mappable genes. D) Correlation matrix of gene expression indicates global conservation of transcriptional profiles of endocrine cell types across species. Cell types are grouped by hierarchical clustering. Pairwise correlation is computed in the principal component analysis space after excluding the top two variance components, which are entirely driven by cross-species variation (see also Figure S1C). α-, β- and δ-cells were subsampled to 2000 cells to balance cell type representation. E) Conservation of endocrine gene and marker expression. Top: Venn diagram showing overlap between species of enriched marker genes for each endocrine cell type. Only marker genes that are mappable across species are shown. Selected known overlapping cell type markers and number of genes with conserved expression are indicated. Enriched marker genes are defined as genes expressed in >5% of the cells of the corresponding cell type and showing increased expression versus all other cell types (log2-fold change>0.5). Bottom: Conservation of human enriched marker genes in pig and mouse cell types. % of human enriched marker genes expressed/detected is indicated. Conserved: enriched marker in same cell type as human; loss: detected but not an enriched marker; switch: enriched marker in different cell type than human. F) Expression of enriched and conserved transcription factors for each endocrine cell type in human, pig and mouse. Color intensity indicates mean expression in a cluster, dot size indicates the proportion of cells in a cluster expressing the gene. Expression is scaled per gene.

Figure 2

Transcriptional β-cell heterogeneity and states in human islets. A) UMAP plot of 11′923 human β-cells. Colors highlight clustering into six different β-cell states. B) Cell densities in UMAP space for five human donors shows that all β-cell clusters are represented by all donors. ID indicates donor ID for ADI IsletCore (see also Figure S1A). C) Fraction of cells per β-cell cluster. Error bar indicates donor variation. D) Expression of selected known β-cell identity and maturity markers. Color intensity indicates mean expression in a cluster, dot size indicates the proportion of cells in a cluster expressing the gene. Expression is scaled per gene. E) Gene sets capturing variation in human β-cells that describe biological processes. Gene sets are groups of highly correlated and/or anti-correlated genes identified using hierarchical clustering on the correlation matrix of the top 3000 variable genes. Left: Scaled mean score for each gene set per β-cell cluster. For each gene set selected known β-cell identity or functional marker genes are indicated. Right: Summary of selected enriched pathways for each gene set indicating biological processes associated to gene sets. Coloring indicates the highest scoring β-cell cluster. F–H) Expression of genes encoding MHC class I components and β-cell autoantigens (F), members of the three canonical ER stress response arms (G), and insulin synthesis and secretion pathways (H). Color intensity indicates mean expression in a cluster, dot size indicates the proportion of cells in a cluster expressing the gene. Expression is scaled per gene. I) Expression of receptors for the majority of circulating hormones in human β-cell clusters. The tissue or organ origin and the type of hormone are indicated. Only receptors detected in >5% of cells of any cluster are shown. Color intensity indicates mean expression in a cluster, dot size indicates the proportion of cells in a cluster expressing the gene. Expression is scaled per gene.

Figure 3

Predicted transcriptional dynamics in human β-cell maturation and insulin secretion. A) Cellular dynamics revealing areas of high induction and or repression of gene expression in β-cells of one human donor (R-ID 266). Left: Cell transitions are inferred from estimated RNA velocities and the direction of inferred movement plotted as streamlines on the UMAP. Colors indicate β-cell clusters. Circles highlight two areas of high velocity. Disconnected mtDNA deficient cluster was excluded. Right: UMAP showing the velocity of selected genes with increased velocity in the corresponding circled area. Top genes indicate induction of transcription of genes involved in β-cell function and insulin secretion. Bottom genes are associated with β-cell maturation. B) Velocity (top) and expression (bottom) of genes showing high velocity in immature β-cells along the cellular transition from immature to mature β-cells inferred from velocities. Cells were ordered by velocity pseudotime. Velocities and expression were scaled per gene. C) Left: Gene-resolved velocities of factors driving the transition from immature to the mature β-cell cluster. Purple lines indicate dynamics fitted with a full dynamical model. Right: Dotplot showing mean velocity per β-cell cluster. Selected known genes involved in β-cell maturation and potential novel genes important for maturation are shown. D) UMAP indicating two clusters of mature β-cells with high or low velocity. E) Selected top enriched Gene Ontology (GO) terms in high velocity genes of mature β-cells indicate induction of genes involved in insulin secretion. Gene enrichment was performed with EnrichR using a modification of the Fisher's exact test. F) Expression of two known markers of β-cell heterogeneity, CD9 and NPY, separates the two mature clusters in D). G) Expression of genes previously described to separate CD9+ and CD9- β-cells in high and low velocity mature β-cells. Color intensity indicates mean expression in a cluster, dot size indicates the proportion of cells in a cluster expressing the gene. Expression is scaled per gene.

Figure 4

Transcriptional α-cell heterogeneity and states in human islets. A) UMAP plot of 11′541 human α-cells. Colors highlight clustering into four different α-cell states. B) Cell densities in UMAP space for five human donors shows that all α-cell clusters are represented by all donors. ID indicates donor ID for ADI IsletCore (see also Figure S1A). C) Fraction of cells per α-cell clusters. Error bar indicates donor variation. D-G) Characterization of α-cell clusters. D-E, G-H) Expression of selected known α-cell identity and maturity markers (D), functional markers (E), adaptive stress response genes (G) and genes involved in pathways describing immature α-cells (H). Color intensity indicates mean expression in a cluster, dot size indicates the proportion of cells in a cluster expressing the gene. Expression is scaled per gene. F) Gene sets capturing variation in human α-cells that describe biological processes. Gene sets are groups of highly correlated and or anti-correlated genes identified using hierarchical clustering on the correlation matrix of the top 3000 variable genes. Left: Scaled mean score for each gene set per α-cell cluster. For each gene set selected α-cell identity or functional marker genes are indicated. Right: Summary of selected enriched pathways for each gene set indicating biological processes associated to gene sets. Coloring indicates the highest scoring α-cell cluster.

Figure 5

Cross-species mapping of α- and β-cell states. A-D) Cross-species mapping of α- and β-cell states. A,C) Representation and cross-species mapping of β- (A) and α-cells (C) by gene set activation scores. UMAP plot (left) shows human cells, where each cell is represented by an activation score of the corresponding cell gene sets. Pig and mouse cells were mapped to the human reference data through projecting on the human gene set representation. Embedding and labels are mapped using the Scanpy ingest functionality (see Methods). The barplot indicates the frequencies of mapped clusters for pig and mouse. B, D) Graph showing global transcriptome correlation of β-(B) and α-(D) cell clusters across species. Edge weights indicate pearson correlation coefficient (see also Figure S4B). Nodes are colored by β-cell clusters. E) Pairwise correlation of the expression pattern across endocrine cell states computed using detected hormone or hormone-like receptors (top) or ion channels (bottom). α- And β-cells were subset to mature state. List of hormone receptors was manually curated. List of ion channels contains calcium, sodium, potassium and transient receptor potential ion channels. Pearson correlation is computed using the harmonic average of mean expression and fraction of cells expressing a gene in a group across all cell types (see Methods). Pearson correlation coefficient is indicated. F) Expression of selected hormone receptors (left) and ion channels (right) showing differential expression patterns in endocrine cell states across species. α- And β-cells were subset to mature state. Hormone and peptide ligands for receptors are indicated. Color intensity indicates mean expression in a cluster, dot size indicates the proportion of cells in a cluster expressing the gene. Expression is scaled per gene.