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Pancreatic δ cells act locally to repress both insulin and glucagon secretion. Because they are a rare cell type, experimentation examining δ-cell function and control has lagged that of the more abundant α and ß cells. Emerging evidence, enabled partly by developing single-cell technology, demonstrates that δ-cell function is, in part, directed by δ cells but that δ cells also have intrinsic control. The contribution of these cells to overall glucose homeostasis and diabetes onset and progression is still unclear. However, they regulate both α and ß cells, both of which are dysfunctional in diabetes, and their numbers are disrupted in humans with diabetes and in multiple animal models of diabetes, suggesting δ cells are a pivotal character in both health and disease.

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Dysfunction of pancreatic δ cells contributes to the etiology of diabetes. Despite their important role, human δ cells are scarce, limiting physiological studies and drug discovery targeting δ cells. To date, no directed δ-cell differentiation method has been established. Here, we demonstrate that fibroblast growth factor (FGF) 7 promotes pancreatic endoderm/progenitor differentiation, whereas FGF2 biases cells towards the pancreatic δ-cell lineage via FGF receptor 1. We develop a differentiation method to generate δ cells from human stem cells by combining FGF2 with FGF7, which synergistically directs pancreatic lineage differentiation and modulates the expression of transcription factors and SST activators during endoderm/endocrine precursor induction. These δ cells display mature RNA profiles and fine secretory granules, secrete somatostatin in response to various stimuli, and suppress insulin secretion from in vitro co-cultured ß cells and mouse ß cells upon transplantation. The generation of human pancreatic δ cells from stem cells in vitro would provide an unprecedented cell source for drug discovery and cell transplantation studies in diabetes.

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OBJECTIVES: This study aimed to evaluate the efficacy of a purification method developed for isolating alpha, beta, and delta cells from pancreatic islets of adult mice, extending its application to islets from newborn and aged mice. Furthermore, it sought to examine transcriptome dynamics in mouse pancreatic endocrine islet cells throughout postnatal development and to validate age-related alterations within these cell populations. METHODS: We leveraged the high surface expression of CD71 on beta cells and CD24 on delta cells to FACS-purify alpha, beta, and delta cells from newborn (1-week-old), adult (12-week-old), and old (18-month-old) mice. Bulk RNA sequencing was conducted on these purified cell populations, and subsequent bioinformatic analyses included differential gene expression, overrepresentation, and intersection analysis. RESULTS: Alpha, beta, and delta cells from newborn and aged mice were successfully FACS-purified using the same method employed for adult mice. Our analysis of the age-related transcriptional changes in alpha, beta, and delta cell populations revealed a decrease in cell cycling and an increase in neuron-like features processes during the transition from newborn to adult mice. Progressing from adult to old mice, we identified an inflammatory gene signature related to aging (inflammaging) encompassing an increase in ß-2 microglobulin and major histocompatibility complex (MHC) Class I expression. CONCLUSIONS: Our study demonstrates the effectiveness of our cell sorting technique in purifying endocrine subsets from mouse islets at different ages. We provide a valuable resource for better understanding endocrine pancreas aging and identified an inflammaging gene signature with increased ß-2 microglobulin and MHC Class I expression as a common hallmark of old alpha, beta, and delta cells, with potential implications for immune response regulation and age-related diabetes.

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BACKGROUND AND PURPOSE: Pancreatic islets are modulated by cross-talk among different cell types and paracrine signalling plays important roles in maintaining glucose homeostasis. Urocortin 3 (UCN3) secreted by pancreatic ß cells activates the CRF2 receptor (CRF2R) and downstream pathways mediated by different G protein or arrestin subtypes in δ cells to cause somatostatin (SST) secretion, and constitutes an important feedback circuit for glucose homeostasis. EXPERIMENTAL APPROACH: Here, we used Arrb1-/-, Arrb2-/-, Gsfl/fl and Gqfl/fl knockout mice, the G11-shRNA-GFPfl/fl lentivirus, as well as functional assays and pharmacological characterization to study how the coupling of Gs, G11 and ß-arrestin1 to CRF2R contributed to UCN3-induced SST secretion in pancreatic δ cells. KEY RESULTS: Our study showed that CRF2R coupled to a panel of G protein and arrestin subtypes in response to UCN3 engagement. While RyR3 phosphorylation by PKA at the S156, S2706 and S4697 sites may underlie the Gs-mediated UCN3- CRF2R axis for SST secretion, the interaction of SYT1 with ß-arrestin1 is also essential for efficient SST secretion downstream of CRF2R. The specific expression of the transcription factor Stat6 may contribute to G11 expression in pancreatic δ cells. Furthermore, we found that different UCN3 concentrations may have distinct effects on glucose homeostasis, and these effects may depend on different CRF2R downstream effectors. CONCLUSIONS AND IMPLICATIONS: Collectively, our results provide a landscape view of signalling mediated by different G protein or arrestin subtypes downstream of paracrine UCN3- CRF2R signalling in pancreatic ß-δ-cell circuits, which may facilitate the understanding of fine-tuned glucose homeostasis networks.

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Glucagon-like peptide-1 receptor (GLP1R) and glucose-dependent insulinotropic polypeptide receptor (GIPR) are transmembrane receptors involved in insulin, glucagon and somatostatin secretion from the pancreatic islet. Therapeutic targeting of GLP1R and GIPR restores blood glucose levels in part by influencing beta cell, alpha cell and delta cell function. Despite the importance of the incretin-mimetics for diabetes therapy, our understanding of GLP1R and GIPR expression patterns and signaling within the islet remain incomplete. Here, we present the evidence for GLP1R and GIPR expression in the major islet cell types, before addressing signaling pathway(s) engaged, as well as their influence on cell survival and function. While GLP1R is largely a beta cell-specific marker within the islet, GIPR is expressed in alpha cells, beta cells, and (possibly) delta cells. GLP1R and GIPR engage Gs-coupled pathways in most settings, although the exact outcome on hormone release depends on paracrine communication and promiscuous signaling. Biased agonism away from beta-arrestin is an emerging concept for improving therapeutic efficacy, and is also relevant for GLP1R/GIPR dual agonism. Lastly, dual agonists exert multiple effects on islet function through GIPR > GLP1R imbalance, increased GLP1R surface expression and cAMP signaling, as well as beneficial alpha cell-beta cell-delta cell crosstalk.

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While pancreatic ß and α cells are considered the main drivers of blood glucose homeostasis through insulin and glucagon secretion, the contribution of δ cells and somatostatin (SST) secretion to glucose homeostasis remains unresolved. Here we provide a quantitative assessment of the physiological contribution of δ cells to the glycaemic set point in mice. Employing three orthogonal mouse models to remove SST signalling within the pancreas or transplanted islets, we demonstrate that ablating δ cells or SST leads to a sustained decrease in the glycaemic set point. This reduction coincides with a decreased glucose threshold for insulin response from ß cells, leading to increased insulin secretion to the same glucose challenge. Our data demonstrate that ß cells are sufficient to maintain stable glycaemia and reveal that the physiological role of δ cells is to provide tonic feedback inhibition that reduces the ß cell glucose threshold and consequently lowers the glycaemic set point in vivo.

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Cell instance segmentation (CIS) via light microscopy and artificial intelligence (AI) is essential to cell and gene therapy-based health care management, which offers the hope of revolutionary health care. An effective CIS method can help clinicians to diagnose neurological disorders and quantify how well these deadly disorders respond to treatment. To address the CIS task challenged by dataset characteristics such as irregular morphology, variation in sizes, cell adhesion, and obscure contours, we propose a novel deep learning model named CellT-Net to actualize effective cell instance segmentation. In particular, the Swin transformer (Swin-T) is used as the basic model to construct the CellT-Net backbone, as the self-attention mechanism can adaptively focus on useful image regions while suppressing irrelevant background information. Moreover, CellT-Net incorporating Swin-T constructs a hierarchical representation and generates multi-scale feature maps that are suitable for detecting and segmenting cells at different scales. A novel composite style named cross-level composition (CLC) is proposed to build composite connections between identical Swin-T models in the CellT-Net backbone and generate more representational features. The earth mover's distance (EMD) loss and binary cross entropy loss are used to train CellT-Net and actualize the precise segmentation of overlapped cells. The LiveCELL and Sartorius datasets are utilized to validate the model effectiveness, and the results demonstrate that CellT-Net can achieve better model performance for dealing with the challenges arising from the characteristics of cell datasets than state-of-the-art models.

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MOTIVATION: Single cell segmentation is critical in the processing of spatial omics data to accurately perform cell type identification and analyze spatial expression patterns. Segmentation methods often rely on semi-supervised annotation or labeled training data which are highly dependent on user expertise. To ensure the quality of segmentation, current evaluation strategies quantify accuracy by assessing cellular masks or through iterative inspection by pathologists. While these strategies each address either the statistical or biological aspects of segmentation, there lacks a unified approach to evaluating segmentation accuracy. RESULTS: In this article, we present ESQmodel, a Bayesian probabilistic method to evaluate single cell segmentation using expression data. By using the extracted cellular data from segmentation and a prior belief of cellular composition as input, ESQmodel computes per cell entropy to assess segmentation quality by how consistent cellular expression profiles match with cell type expectations. AVAILABILITY AND IMPLEMENTATION: Source code is available on Github at: https://github.com/Roth-Lab/ESQmodel.

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BACKGROUND: High throughput sequencing has enabled the interrogation of the transcriptomic landscape of glucagon-secreting alpha cells, insulin-secreting beta cells, and somatostatin-secreting delta cells. These approaches have furthered our understanding of expression patterns that define healthy or diseased islet cell types and helped explicate some of the intricacies between major islet cell crosstalk and glucose regulation. All three endocrine cell types derive from a common pancreatic progenitor, yet alpha and beta cells have partially opposing functions, and delta cells modulate and control insulin and glucagon release. While gene expression signatures that define and maintain cellular identity have been widely explored, the underlying epigenetic components are incompletely characterized and understood. However, chromatin accessibility and remodeling is a dynamic attribute that plays a critical role to determine and maintain cellular identity. RESULTS: Here, we compare and contrast the chromatin landscape between mouse alpha, beta, and delta cells using ATAC-Seq to evaluate the significant differences in chromatin accessibility. The similarities and differences in chromatin accessibility between these related islet endocrine cells help define their fate in support of their distinct functional roles. We identify patterns that suggest that both alpha and delta cells are poised, but repressed, from becoming beta-like. We also identify patterns in differentially enriched chromatin that have transcription factor motifs preferentially associated with different regions of the genome. Finally, we not only confirm and visualize previously discovered common endocrine- and cell specific- enhancer regions across differentially enriched chromatin, but identify novel regions as well. We compiled our chromatin accessibility data in a freely accessible database of common endocrine- and cell specific-enhancer regions that can be navigated with minimal bioinformatics expertise. CONCLUSIONS: Both alpha and delta cells appear poised, but repressed, from becoming beta cells in murine pancreatic islets. These data broadly support earlier findings on the plasticity in identity of non-beta cells under certain circumstances. Furthermore, differential chromatin accessibility shows preferentially enriched distal-intergenic regions in beta cells, when compared to either alpha or delta cells.

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AIMS/HYPOTHESIS: Transcriptome analyses revealed insulin-gene-derived transcripts in non-beta endocrine islet cells. We studied alternative splicing of human INS mRNA in pancreatic islets. METHODS: Alternative splicing of insulin pre-mRNA was determined by PCR analysis performed on human islet RNA and single-cell RNA-seq analysis. Antisera were generated to detect insulin variants in human pancreatic tissue using immunohistochemistry, electron microscopy and single-cell western blot to confirm the expression of insulin variants. Cytotoxic T lymphocyte (CTL) activation was determined by MIP-1ß release. RESULTS: We identified an alternatively spliced INS product. This variant encodes the complete insulin signal peptide and B chain and an alternative C-terminus that largely overlaps with a previously identified defective ribosomal product of INS. Immunohistochemical analysis revealed that the translation product of this INS-derived splice transcript was detectable in somatostatin-producing delta cells but not in beta cells; this was confirmed by light and electron microscopy. Expression of this alternatively spliced INS product activated preproinsulin-specific CTLs in vitro. The exclusive presence of this alternatively spliced INS product in delta cells may be explained by its clearance from beta cells by insulin-degrading enzyme capturing its insulin B chain fragment and a lack of insulin-degrading enzyme expression in delta cells. CONCLUSIONS/INTERPRETATION: Our data demonstrate that delta cells can express an INS product derived from alternative splicing, containing both the diabetogenic insulin signal peptide and B chain, in their secretory granules. We propose that this alternative INS product may play a role in islet autoimmunity and pathology, as well as endocrine or paracrine function or islet development and endocrine destiny, and transdifferentiation between endocrine cells. INS promoter activity is not confined to beta cells and should be used with care when assigning beta cell identity and selectivity. DATA AVAILABILITY: The full EM dataset is available via www.nanotomy.org (for review: http://www.nanotomy.org/OA/Tienhoven2021SUB/6126-368/ ). Single-cell RNA-seq data was made available by Segerstolpe et al [13] and can be found at https://sandberglab.se/pancreas . The RNA and protein sequence of INS-splice was uploaded to GenBank (BankIt2546444 INS-splice OM489474).

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Hirschsprung disease (HSCR) is a complex congenital disorder caused by defects in the development of the enteric nervous system (ENS). It is attributed to failures of the enteric neural crest stem cells (ENCCs) to proliferate, differentiate and/or migrate, leading to the absence of enteric neurons in the distal colon, resulting in colonic motility dysfunction. Due to the oligogenic nature of the disease, some HSCR conditions could not be phenocopied in animal models. Building the patient-based disease model using human induced pluripotent stem cells (hPSC) has opened up a new opportunity to untangle the unknowns of the disease. The expanding armamentarium of hPSC-based therapies provides needed new tools for developing cell-replacement therapy for HSCR. Here we summarize the recent studies of hPSC-based models of ENS in 2-D and 3-D culture systems. These studies have highlighted how hPSC-based models complement the population-based genetic screens and bioinformatic approaches for the discovery of new HSCR susceptibility genes and provide a human model for the close-to-physiological functional studies. We will also discuss the potential applications of these hPSC-based models in translational medicines and their advantages and limitations. The use of these hPSC-based models for drug discovery or cell replacement therapy likely leads to new treatment strategies for HSCR in the future. Further improvements in incorporating hPSC-based models with the human-mouse chimera model and organ-on-a-chip system for establishing a better disease model of HSCR and for drug discovery will further propel us to success in the development of an efficacious treatment for HSCR.

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Type 1 diabetes is an autoimmune disease that emerges with the destruction of beta cells of pancreatic Langerhans islets. Three different therapeutical approaches have been developed so far; pancreas transplantation, islet transplantation, and cell-based therapies. Bioengineering cell sheets for tissue generating is one of the latest approaches that have been used to construct cell-sheets instead of single cells so that it mimics the in vivo environments more. In this study, extra-hepatic functional islet tissue was constructed by transferring the 3-D beta cells and GFP labelled MSCs MSC sheets to the subcutaneous site of rats with STZ-induced diabetes. rBM-MSCs and beta cells were cultured on the 6-well PIPAAm culture dishes. Obtained rBM-MSCs as two-cell sheets and beta cells cultured in droplets with matrigel has transplanted into the dorsal subcutaneous area of diabetic rats. Fasting blood glucose levels and body weights were evaluated for 30 days after transplantation. Immunocytochemistry analysis for the anti-apoptotic, anti-inflammatory, and angiogenetic effects of MSCs on the 30th day of subcutaneous cell transplantation. All recipient rats transplanted with beta-cells with MSCs returned toward normoglycemia by day 5 and remained at this level for 30 days. Immunocytochemical analyses supported that the MSCs and beta cells preserved their viability and function. MSCs secrete cytokines and growth factors TGF-ß and IL-6; MSCs of the important features of the anti-apoptotic and anti-inflammatory properties, thanks to apoptosis of beta cells preserve graft explained by inhibition. In transplantation of MSCs induced angiogenesis and neovascularization, PECAM-1 and GFP positive simultaneously determining endothelial cells was observed indicating. Subcutaneous 3D beta-cell transplantation would be possible with the MSC-sheets as a feeder layer of beta cells. The beta-cell line is glucose-sensitive and has a high insulin release potential, and can be used as an alternative to islets in in vivo transplant studies.

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Mandatory potency testing of Leptospira vaccine batches relies partially on in vivo procedures, requiring large numbers of laboratory animals. Cell-based assays could replace in vivo tests for vaccine quality control if biomarkers indicative of Leptospira vaccine potency are identified. We investigated innate immune responsiveness induced by inactivated L. interrogans serogroups Canicola and Icterohaemorrhagiae, and two bivalent, non-adjuvanted canine Leptospira vaccines containing the same serogroups. First, the transcriptome and proteome analysis of a canine monocyte/macrophage 030-D cell line stimulated with Leptospira strains, and vaccine B revealed more than 900 DEGs and 23 DEPs in common to these three stimuli. Second, comparison of responses induced by vaccine B and vaccine D revealed a large overlap in DEGs and DEPs as well, suggesting potential to identify biomarkers indicative of Leptospira vaccine quality. Because not many common DEPs were identified, we selected seven molecules from the identified DEGs, associated with pathways related to innate immunity, of which CXCL-10, IL-1ß, SAA, and complement C3 showed increased secretion upon stimulation with both Leptospira vaccines. These molecules could be interesting targets for development of biomarker-based assays for Leptospira vaccine quality control in the future. Additionally, this study contributes to the understanding of the mechanisms by which Leptospira vaccines induce innate immune responses in the dog.

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Type 1 diabetes results from the autoimmune-mediated loss of insulin-producing beta-cells. Accordingly, important research efforts aim at regenerating these lost beta-cells by converting pre-existing endogenous cells. Following up on previous results demonstrating the conversion of pancreatic somatostatin delta-cells into beta-like cells upon Pax4 misexpression and acknowledging that somatostatin-expressing cells are highly represented in the gastrointestinal tract, one could wonder whether this Pax4-mediated conversion could also occur in the GI tract. We made use of transgenic mice misexpressing Pax4 in somatostatin cells (SSTCrePOE) to evaluate a putative Pax4-mediated D-to-beta-like cell conversion. Additionally, we implemented an ex vivo approach based on mice-derived gut organoids to assess the functionality of these neo-generated beta-like cells. Our results outlined the presence of insulin+ cells expressing several beta-cell markers in gastrointestinal tissues of SSTCrePOE animals. Further, using lineage tracing, we established that these cells arose from D cells. Lastly, functional tests on mice-derived gut organoids established the ability of neo-generated beta-like cells to release insulin upon stimulation. From this study, we conclude that the misexpression of Pax4 in D cells appears sufficient to convert these into functional beta-like cells, thus opening new research avenues in the context of diabetes research.

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Structural properties of pancreatic islets are key for the functional response of insulin, glucagon, and somatostatin-secreting cells, due to their implications in intraislet communication via electric, paracrine, and autocrine signaling. In this protocol, the three-dimensional architecture of a pancreatic islet is firstly reconstructed from experimental data using a novel computational algorithm. Next, the morphological and connectivity properties of the reconstructed islet, such as the number and percentages of the different type of cells, cellular volume, and cell-to-cell contacts, are obtained. Then, network theory is used to describe the connectivity properties of the islet through network-derived metrics such as average degree, clustering coefficient, density, diameter, and efficiency. Finally, all these properties are functionally evaluated through computational simulations using a model of coupled oscillators. Overall, here we describe a step-by-step workflow, implemented in IsletLab, a multiplatform application developed specifically for the study and simulation of pancreatic islets, to apply a novel computational methodology to characterize and analyze pancreatic islets as a complement to the experimental work.

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In vivo administration of dopamine (DA) receptor (DR)-related drugs modulate gastric pepsinogen secretion. However, DRs on gastric pepsinogen-secreting chief cells and DA D2 receptor (D2R) on somatostatin-secreting D cells were subsequently acquired. In this study, we aimed to further investigate the local effect of DA on gastric pepsinogen secretion through DRs expressed on chief cells or potential D2Rs expressed on D cells. To elucidate the modulation of DRs in gastric pepsinogen secretion, immunofluorescence staining, ex vivo incubation of gastric mucosa isolated from normal and D2R-/- mice were conducted, accompanied by measurements of pepsinogen or somatostatin levels using biochemical assays or enzyme-linked immunosorbent assays. D1R, D2R, and D5R-immunoreactivity (IR) were observed on chief cells in mouse gastric mucosa. D2R-IR was widely distributed on D cells from the corpus to the antrum. Ex vivo incubation results showed that DA and the D1-like receptor agonist SKF38393 increased pepsinogen secretion, which was blocked by the D1-like receptor antagonist SCH23390. However, D2-like receptor agonist quinpirole also significantly increased pepsinogen secretion, and D2-like receptor antagonist sulpiride blocked the promotion of DA. Besides, D2-like receptors exerted an inhibitory effect on somatostatin secretion, in contrast to their effect on pepsinogen secretion. Furthermore, D2R-/- mice showed much lower basal pepsinogen secretion but significantly increased somatostatin release and an increased number of D cells in gastric mucosa. Only SKF38393, not quinpirole, increased pepsinogen secretion in D2R-/- mice. DA promotes gastric pepsinogen secretion directly through D1-like receptors on chief cells and indirectly through D2R-mediated suppression of somatostatin release.

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Restoring damaged ß-cells in diabetic patients by harnessing the plasticity of other pancreatic cells raises the questions of the efficiency of the process and of the functionality of the new Insulin-expressing cells. To overcome the weak regenerative capacity of mammals, we used regeneration-prone zebrafish to study ß-cells arising following destruction. We show that most new insulin cells differ from the original ß-cells as they coexpress Somatostatin and Insulin. These bihormonal cells are abundant, functional and able to normalize glycemia. Their formation in response to ß-cell destruction is fast, efficient, and age-independent. Bihormonal cells are transcriptionally close to a subset of δ-cells that we identified in control islets and that are characterized by the expression of somatostatin 1.1 (sst1.1) and by genes essential for glucose-induced Insulin secretion in ß-cells such as pdx1, slc2a2 and gck. We observed in vivo the conversion of monohormonal sst1.1-expressing cells to sst1.1+ ins + bihormonal cells following ß-cell destruction. Our findings support the conclusion that sst1.1 δ-cells possess a pro-ß identity enabling them to contribute to the neogenesis of Insulin-producing cells during regeneration. This work unveils that abundant and functional bihormonal cells benefit to diabetes recovery in zebrafish.

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Regeneration-competent species possess the ability to reverse the progression of severe diseases by restoring the function of the damaged tissue. However, the cellular dynamics underlying this capability remain unexplored. Here, we have used single-cell transcriptomics to map de novo ß-cell regeneration during induction and recovery from diabetes in zebrafish. We show that the zebrafish has evolved two distinct types of somatostatin-producing δ-cells, which we term δ1- and δ2-cells. Moreover, we characterize a small population of glucose-responsive islet cells, which share the hormones and fate-determinants of both ß- and δ1-cells. The transcriptomic analysis of ß-cell regeneration reveals that ß/δ hybrid cells provide a prominent source of insulin expression during diabetes recovery. Using in vivo calcium imaging and cell tracking, we further show that the hybrid cells form de novo and acquire glucose-responsiveness in the course of regeneration. The overexpression of dkk3, a gene enriched in hybrid cells, increases their formation in the absence of ß-cell injury. Finally, interspecies comparison shows that plastic δ1-cells are partially related to PP cells in the human pancreas. Our work provides an atlas of ß-cell regeneration and indicates that the rapid formation of glucose-responsive hybrid cells contributes to the resolution of diabetes in zebrafish.

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Islet transplantation is a type of cellular replacement therapy for severe diabetes that is limited by compromising effect on engrafted islets. Trials aiming to improve the function of transplanted islets have also been challenging. This study attempted to elucidate whether regulation of growth hormone secretagogue receptor-1a (GHS-R1a), one of the ghrelin receptors, improve the therapeutic effects of islet transplantation using [D-Lys3]-GHRP-6 (DLS), a specific GHS-R1a antagonist. The therapeutic effects of DLS were assessed in terms of the expression/production of endocrine genes/proteins, insulin-releasing function under glucose stimulation of mouse islets, and outcomes of syngeneic murine islet transplantation with systemic DLS administration. DLS treatment promoted insulin production and suppressed somatostatin production, suggesting that cancelation of the binding between ghrelin and GHS-R1a on ß or δ cells improved insulin expression. DLS also promoted the glucose-dependent insulin-releasing function of ß cells. However, the therapeutic effect of DLS in islet transplantation was fractional. In conclusion, the GHS-R1a antagonist showed preferable effects in improving the therapeutic outcomes of islet transplantation, including the promotion of insulin-releasing function.

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