Interrogating islets in health and disease with single-cell technologies

Delineating mouse β-cell identity during lifetime and in diabetes with a single cell atlas

Although multiple pancreatic islet single-cell RNA-sequencing (scRNA-seq) datasets have been generated, a consensus on pancreatic cell states in development, homeostasis and diabetes as well as the value of preclinical animal models is missing. Here, we present an scRNA-seq cross-condition mouse islet atlas (MIA), a curated resource for interactive exploration and computational querying. We integrate over 300,000 cells from nine scRNA-seq datasets consisting of 56 samples, varying in age, sex and diabetes models, including an autoimmune type 1 diabetes model (NOD), a glucotoxicity/lipotoxicity type 2 diabetes model (db/db) and a chemical streptozotocin β-cell ablation model. The β-cell landscape of MIA reveals new cell states during disease progression and cross-publication differences between previously suggested marker genes. We show that β-cells in the streptozotocin model transcriptionally correlate with those in human type 2 diabetes and mouse db/db models, but are less similar to human type 1 diabetes and mouse NOD β-cells. We also report pathways that are shared between β-cells in immature, aged and diabetes models. MIA enables a comprehensive analysis of β-cell responses to different stressors, providing a roadmap for the understanding of β-cell plasticity, compensation and demise.

Nutrient-dependent regulation of β-cell proinsulin content

Insulin is made from proinsulin, but the extent to which fasting/feeding controls the homeostatically regulated proinsulin pool in pancreatic β-cells remains largely unknown. Here, we first examined β-cell lines (INS1E and Min6, which proliferate slowly and are routinely fed fresh medium every 2-3 days) and found that the proinsulin pool size responds to each feeding within 1 to 2 h, affected both by the quantity of fresh nutrients and the frequency with which they are provided. We observed no effect of nutrient feeding on the overall rate of proinsulin turnover as quantified from cycloheximide-chase experiments. We show that nutrient feeding is primarily linked to rapid dephosphorylation of translation initiation factor eIF2α, presaging increased proinsulin levels (and thereafter, insulin levels), followed by its rephosphorylation during the ensuing hours that correspond to a fall in proinsulin levels. The decline of proinsulin levels is blunted by the integrated stress response inhibitor, ISRIB, or by inhibition of eIF2α rephosphorylation with a general control nonderepressible 2 (not PERK) kinase inhibitor. In addition, we demonstrate that amino acids contribute importantly to the proinsulin pool; mass spectrometry shows that β-cells avidly consume extracellular glutamine, serine, and cysteine. Finally, we show that in both rodent and human pancreatic islets, fresh nutrient availability dynamically increases preproinsulin, which can be quantified without pulse-labeling. Thus, the proinsulin available for insulin biosynthesis is rhythmically controlled by fasting/feeding cycles.

Pancreatic islet cell type-specific transcriptomic changes during pregnancy and postpartum

Pancreatic β-cell mass expands during pregnancy and regresses in the postpartum period in conjunction with dynamic metabolic demands on maternal glucose homeostasis. To understand transcriptional changes driving these adaptations in β-cells and other islet cell types, we performed single-cell RNA sequencing on islets from virgin, late gestation, and early postpartum mice. We identified transcriptional signatures unique to gestation and the postpartum in β-cells, including induction of the AP-1 transcription factor subunits and other genes involved in the immediate-early response (IEGs). In addition, we found pregnancy and postpartum-induced changes differed within each endocrine cell type, and in endothelial cells and antigen-presenting cells within islets. Together, our data reveal insights into cell type-specific transcriptional changes responsible for adaptations by islet cells to pregnancy and their resolution postpartum.

Molecular phenotyping of single pancreatic islet leader beta cells by "Flash-Seq"

AIMS

Spatially-organized increases in cytosolic Ca²⁺ within pancreatic beta cells in the pancreatic islet underlie the stimulation of insulin secretion by high glucose. Recent data have revealed the existence of subpopulations of beta cells including "leaders" which initiate Ca²⁺ waves. Whether leader cells possess unique molecular features, or localisation, is unknown.

MAIN METHODS

High speed confocal Ca²⁺ imaging was used to identify leader cells and connectivity analysis, running under MATLAB and Python, to identify highly connected "hub" cells. To explore transcriptomic differences between beta cell sub-groups, individual leaders or followers were labelled by photo-activation of the cryptic fluorescent protein PA-mCherry and subjected to single cell RNA sequencing ("Flash-Seq").

KEY FINDINGS

Distinct Ca²⁺ wave types were identified in individual islets, with leader cells present in 73 % (28 of 38 islets imaged). Scale-free, power law-adherent behaviour was also observed in 29 % of islets, though "hub" cells in these islets did not overlap with leaders. Transcripts differentially expressed (295; padj < 0.05) between leader and follower cells included genes involved in cilium biogenesis and transcriptional regulation. Providing some support for these findings, ADCY6 immunoreactivity tended to be higher in leader than follower cells, whereas cilia number and length tended to be lower in the former. Finally, leader cells were located significantly closer to delta, but not alpha, cells in Euclidian space than were follower cells.

SIGNIFICANCE

The existence of both a discrete transcriptome and unique localisation implies a role for these features in defining the specialized function of leaders. These data also raise the possibility that localised signalling between delta and leader cells contributes to the initiation and propagation of islet Ca²⁺ waves.

Proteomic Profiling of Intra-Islet Features Reveals Substructure-Specific Protein Signatures

Despite their diminutive size, islets of Langerhans play a large role in maintaining systemic energy balance in the body. New technologies have enabled us to go from studying the whole pancreas to isolated whole islets, to partial islet sections, and now to islet substructures isolated from within the islet. Using a microfluidic nanodroplet-based proteomics platform coupled with laser capture microdissection and field asymmetric waveform ion mobility spectrometry, we present an in-depth investigation of protein profiles specific to features within the islet. These features include the islet-acinar interface vascular tissue, inner islet vasculature, isolated endocrine cells, whole islet with vasculature, and acinar tissue from around the islet. Compared to interface vasculature, unique protein signatures observed in the inner vasculature indicate increased innervation and intra-islet neuron-like crosstalk. We also demonstrate the utility of these data for identifying localized structure-specific drug-target interactions using existing protein/drug binding databases.

Targeting pancreatic β cells for diabetes treatment

Insulin is a life-saving drug for patients with type 1 diabetes; however, even today, no pharmacotherapy can prevent the loss or dysfunction of pancreatic insulin-producing β cells to stop or reverse disease progression. Thus, pancreatic β cells have been a main focus for cell-replacement and regenerative therapies as a curative treatment for diabetes. In this Review, we highlight recent advances toward the development of diabetes therapies that target β cells to enhance proliferation, redifferentiation and protection from cell death and/or enable selective killing of senescent β cells. We describe currently available therapies and their mode of action, as well as insufficiencies of glucagon-like peptide 1 (GLP-1) and insulin therapies. We discuss and summarize data collected over the last decades that support the notion that pharmacological targeting of β cell insulin signalling might protect and/or regenerate β cells as an improved treatment of patients with diabetes.

Small extracellular vesicles (exosomes) and their cargo in pancreatic cancer: Key roles in the hallmarks of cancer

Pancreatic cancer (PC) is a devastating disease, offering poor mortality rates for patients. The current challenge being faced is the inability to diagnose patients in a timely manner, where potentially curative resection provides the best chance of survival. Recently, small/nanosized extracellular vesicles (sEVs), including exosomes, have gained significant preclinical and clinical attention due to their emerging roles in cancer progression and diagnosis. Extracellular vesicles (EVs) possess endogenous properties that offer stability and facilitate crossing of biological barriers for delivery of molecular cargo to cells, acting as a form of intercellular communication to regulate function and phenotype of recipient cells. This review provides an overview of the role of EVs, their subtypes and their oncogenic cargo (as characterised by targeted studies as well as agnostic '-omics' analyses) in the pathobiology of pancreatic cancer. The discussion covers the progress of 'omics technology' that has enabled elucidation of the molecular mechanisms that mediate the role of EVs and their cargo in pancreatic cancer progression.

P2Y1 purinergic receptor identified as a diabetes target in a small-molecule screen to reverse circadian β-cell failure

The mammalian circadian clock drives daily oscillations in physiology and behavior through an autoregulatory transcription feedback loop present in central and peripheral cells. Ablation of the core clock within the endocrine pancreas of adult animals impairs the transcription and splicing of genes involved in hormone exocytosis and causes hypoinsulinemic diabetes. Here, we developed a genetically sensitized small-molecule screen to identify druggable proteins and mechanistic pathways involved in circadian β-cell failure. Our approach was to generate β-cells expressing a nanoluciferase reporter within the proinsulin polypeptide to screen 2640 pharmacologically active compounds and identify insulinotropic molecules that bypass the secretory defect in CRISPR-Cas9-targeted clock mutant β-cells. We validated hit compounds in primary mouse islets and identified known modulators of ligand-gated ion channels and G-protein-coupled receptors, including the antihelmintic ivermectin. Single-cell electrophysiology in circadian mutant mouse and human cadaveric islets revealed ivermectin as a glucose-dependent secretagogue. Genetic, genomic, and pharmacological analyses established the P2Y1 receptor as a clock-controlled mediator of the insulinotropic activity of ivermectin. These findings identify the P2Y1 purinergic receptor as a diabetes target based upon a genetically sensitized phenotypic screen.

The Human Islet: Mini-Organ With Mega-Impact

This review focuses on the human pancreatic islet-including its structure, cell composition, development, function, and dysfunction. After providing a historical timeline of key discoveries about human islets over the past century, we describe new research approaches and technologies that are being used to study human islets and how these are providing insight into human islet physiology and pathophysiology. We also describe changes or adaptations in human islets in response to physiologic challenges such as pregnancy, aging, and insulin resistance and discuss islet changes in human diabetes of many forms. We outline current and future interventions being developed to protect, restore, or replace human islets. The review also highlights unresolved questions about human islets and proposes areas where additional research on human islets is needed.

Importance of Both Imprinted Genes and Functional Heterogeneity in Pancreatic Beta Cells: Is There a Link?

Diabetes mellitus now affects more than 400 million individuals worldwide, with significant impacts on the lives of those affected and associated socio-economic costs. Although defects in insulin secretion underlie all forms of the disease, the molecular mechanisms which drive them are still poorly understood. Subsets of specialised beta cells have, in recent years, been suggested to play critical roles in "pacing" overall islet activity. The molecular nature of these cells, the means through which their identity is established and the changes which may contribute to their functional demise and "loss of influence" in both type 1 and type 2 diabetes are largely unknown. Genomic imprinting involves the selective silencing of one of the two parental alleles through DNA methylation and modified imprinted gene expression is involved in a number of diseases. Loss of expression, or loss of imprinting, can be shown in mouse models to lead to defects in beta cell function and abnormal insulin secretion. In the present review we survey the evidence that altered expression of imprinted genes contribute to loss of beta cell function, the importance of beta cell heterogeneity in normal and disease states, and hypothesise whether there is a direct link between the two.

Normal and defective pathways in biogenesis and maintenance of the insulin storage pool

Both basal and glucose-stimulated insulin release occur primarily by insulin secretory granule exocytosis from pancreatic β cells, and both are needed to maintain normoglycemia. Loss of insulin-secreting β cells, accompanied by abnormal glucose tolerance, may involve simple exhaustion of insulin reserves (which, by immunostaining, appears as a loss of β cell identity), or β cell dedifferentiation, or β cell death. While various sensing and signaling defects can result in diminished insulin secretion, somewhat less attention has been paid to diabetes risk caused by insufficiency in the biosynthetic generation and maintenance of the total insulin granule storage pool. This Review offers an overview of insulin biosynthesis, beginning with the preproinsulin mRNA (translation and translocation into the ER), proinsulin folding and export from the ER, and delivery via the Golgi complex to secretory granules for conversion to insulin and ultimate hormone storage. All of these steps are needed for generation and maintenance of the total insulin granule pool, and defects in any of these steps may, weakly or strongly, perturb glycemic control. The foregoing considerations have obvious potential relevance to the pathogenesis of type 2 diabetes and some forms of monogenic diabetes; conceivably, several of these concepts might also have implications for β cell failure in type 1 diabetes.

Mass cytometry and type 1 diabetes research in the age of single-cell data science

PURPOSE OF REVIEW

New single-cell tec. hnologies developed over the past decade have considerably reshaped the biomedical research landscape, and more recently have found their way into studies probing the pathogenesis of type 1 diabetes (T1D). In this context, the emergence of mass cytometry in 2009 revolutionized immunological research in two fundamental ways that also affect the T1D world: first, its ready embrace by the community and rapid dissemination across academic and private science centers alike established a new standard of analytical complexity for the high-dimensional proteomic stratification of single-cell populations; and second, the somewhat unexpected arrival of mass cytometry awoke the flow cytometry field from its seeming sleeping beauty stupor and precipitated substantial technological advances that by now approach a degree of analytical dimensionality comparable to mass cytometry.

RECENT FINDINGS

Here, we summarize in detail how mass cytometry has thus far been harnessed for the pursuit of discovery studies in T1D science; we provide a succinct overview of other single-cell analysis platforms that already have been or soon will be integrated into various T1D investigations; and we briefly consider how effective adoption of these technologies requires an adjusted model for expense allocation, prioritization of experimental questions, division of labor, and recognition of scientific contributions.

SUMMARY

The introduction of contemporary single-cell technologies in general, and of mass cytometry, in particular, provides important new opportunities for current and future T1D research; the necessary reconfiguration of research strategies to accommodate implementation of these technologies, however, may both broaden research endeavors by fostering genuine team science, and constrain their actual practice because of the need for considerable investments into infrastructure and technical expertise.

Pancreatic β-cells in type 1 and type 2 diabetes mellitus: different pathways to failure

Loss of functional β-cell mass is the key mechanism leading to the two main forms of diabetes mellitus - type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM). Understanding the mechanisms behind β-cell failure is critical to prevent or revert disease. Basic pathogenic differences exist in the two forms of diabetes mellitus; T1DM is immune mediated and T2DM is mediated by metabolic mechanisms. These mechanisms differentially affect early β-cell dysfunction and eventual fate. Over the past decade, major advances have been made in the field, mostly delivered by studies on β-cells in human disease. These advances include studies of islet morphology and human β-cell gene expression in T1DM and T2DM, the identification and characterization of the role of T1DM and T2DM candidate genes at the β-cell level and the endoplasmic reticulum stress signalling that contributes to β-cell failure in T1DM (mostly IRE1 driven) and T2DM (mostly PERK-eIF2α dependent). Here, we review these new findings, focusing on studies performed on human β-cells or on samples obtained from patients with diabetes mellitus.

Discovery of 318 new risk loci for type 2 diabetes and related vascular outcomes among 1.4 million participants in a multi-ancestry meta-analysis

We investigated type 2 diabetes (T2D) genetic susceptibility via multi-ethnic meta-analysis of 228,499 cases and 1,178,783 controls in the Million Veteran Program, DIAMANTE, Biobank Japan, and other studies. We report 568 associations, including 286 autosomal, 7 X chromosomal, and 25 identified in ancestry-specific analyses that were previously unreported. Transcriptome-wide association analysis detected 3,568 T2D-associations with genetically predicted gene expression in 687 novel genes; of these, 54 are known to interact with FDA-approved drugs. A polygenic risk score was strongly associated with increased risk of T2D-related retinopathy and modestly associated with chronic kidney disease (CKD), peripheral artery disease (PAD), and neuropathy. We investigated the genetic etiology of T2D-related vascular outcomes in MVP and observed statistical SNP-T2D interactions at 13 variants, including coronary heart disease, CKD, PAD, and neuropathy. These findings may help to identify potential therapeutic targets for T2D and genomic pathways that link T2D to vascular outcomes.

Cell Type Purification by Single-Cell Transcriptome-Trained Sorting

Much of current molecular and cell biology research relies on the ability to purify cell types by fluorescence-activated cell sorting (FACS). FACS typically relies on the ability to label cell types of interest with antibodies or fluorescent transgenic constructs. However, antibody availability is often limited, and genetic manipulation is labor intensive or impossible in the case of primary human tissue. To date, no systematic method exists to enrich for cell types without a priori knowledge of cell-type markers. Here, we propose GateID, a computational method that combines single-cell transcriptomics with FACS index sorting to purify cell types of choice using only native cellular properties such as cell size, granularity, and mitochondrial content. We validate GateID by purifying various cell types from zebrafish kidney marrow and the human pancreas to high purity without resorting to specific antibodies or transgenes.

Advances of single-cell genomics and epigenomics in human disease: where are we now?

Cellular heterogeneity is revolutionizing the way to study, monitor and dissect complex diseases. This has been possible with the technological and computational advances associated to single-cell genomics and epigenomics. Deeper understanding of cell-to-cell variation and its impact on tissue function will open new avenues for early disease detection, accurate diagnosis and personalized treatments, all together leading to the next generation of health care. This review focuses on the recent discoveries that single-cell genomics and epigenomics have facilitated in the context of human health. It highlights the potential of single-cell omics to further advance the development of personalized treatments and precision medicine in cancer, diabetes and chronic age-related diseases. The promise of single-cell technologies to generate new insights about the differences in function between individual cells is just emerging, and it is paving the way for identifying biomarkers and novel therapeutic targets to tackle age, complex diseases and understand the effect of life style interventions and environmental factors.

Understanding generation and regeneration of pancreatic β cells from a single-cell perspective

Understanding the mechanisms that underlie the generation and regeneration of β cells is crucial for developing treatments for diabetes. However, traditional research methods, which are based on populations of cells, have limitations for defining the precise processes of β-cell differentiation and trans-differentiation, and the associated regulatory mechanisms. The recent development of single-cell technologies has enabled re-examination of these processes at a single-cell resolution to uncover intermediate cell states, cellular heterogeneity and molecular trajectories of cell fate specification. Here, we review recent advances in understanding β-cell generation and regeneration, in vivo and in vitro, from single-cell technologies, which could provide insights for optimization of diabetes therapy strategies.

Paracrine signaling in islet function and survival

The pancreatic islet is a dense cellular network comprised of several cell types with endocrine function vital in the control of glucose homeostasis, metabolism, and feeding behavior. Within the islet, endocrine hormones also form an intricate paracrine network with supportive cells (endothelial, neuronal, immune) and secondary signaling molecules regulating cellular function and survival. Modulation of these signals has potential consequences for diabetes development, progression, and therapeutic intervention. Beta cell loss, reduced endogenous insulin secretion, and dysregulated glucagon secretion are hallmark features of both type 1 and 2 diabetes that not only impact systemic regulation of glucose, but also contribute to the function and survival of cells within the islet. Advancing research and technology have revealed new islet biology (cellular identity and transcriptomes) and identified previously unrecognized paracrine signals and mechanisms (somatostatin and ghrelin paracrine actions), while shifting prior views of intraislet communication. This review will summarize the paracrine signals regulating islet endocrine function and survival, the disruption and dysfunction that occur in diabetes, and potential therapeutic targets to preserve beta cell mass and function.

De novo discovery of metabolic heterogeneity with immunophenotype-guided imaging mass spectrometry

Imaging mass spectrometry enables in situ label-free detection of thousands of metabolites from intact tissue samples. However, automated steps for multi-omics analyses and interpretation of histological images have not yet been implemented in mass spectrometry data analysis workflows. The characterization of molecular properties within cellular and histological features is done via time-consuming, non-objective, and irreproducible definitions of regions of interest, which are often accompanied by a loss of spatial resolution due to mass spectra averaging.

Methods: We developed a new imaging pipeline called Spatial Correlation Image Analysis (SPACiAL), which is a computational multimodal workflow designed to combine molecular imaging data with multiplex immunohistochemistry (IHC). SPACiAL allows comprehensive and spatially resolved in situ correlation analyses on a cellular resolution. To demonstrate the method, matrix-assisted laser desorption-ionization (MALDI) Fourier-transform ion cyclotron resonance (FTICR) imaging mass spectrometry of metabolites and multiplex IHC staining were performed on the very same tissue section of mouse pancreatic islets and on human gastric cancer tissue specimens. The SPACiAL pipeline was used to perform an automatic, semantic-based, functional tissue annotation of histological and cellular features to identify metabolic profiles. Spatial correlation networks were generated to analyze metabolic heterogeneity associated with cellular features.

Results: To demonstrate the new method, the SPACiAL pipeline was used to identify metabolic signatures of alpha and beta cells within islets of Langerhans, which are cell types that are not distinguishable via morphology alone. The semantic-based, functional tissue annotation allows an unprecedented analysis of metabolic heterogeneity via the generation of spatial correlation networks. Additionally, we demonstrated intra- and intertumoral metabolic heterogeneity within HER2/neu-positive and -negative gastric tumor cells.

Conclusions: We developed the SPACiAL workflow to provide IHC-guided in situ metabolomics on intact tissue sections. Diminishing the workload by automated recognition of histological and functional features, the pipeline allows comprehensive analyses of metabolic heterogeneity. The multimodality of immunohistochemical staining and extensive molecular information from imaging mass spectrometry has the advantage of increasing both the efficiency and precision for spatially resolved analyses of specific cell types. The SPACiAL method is a stepping stone for the objective analysis of high-throughput, multi-omics data from clinical research and practice that is required for diagnostics, biomarker discovery, or therapy response prediction.

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Novel method enables phenotype-guided in situ metabolomics on intact tissue sections.

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Metabolic heterogeneity can be objectified under (patho-)physiological conditions.

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Innovative approach for tissue-based, preclinical, and clinical research.

Recovery of viable endocrine-specific cells and transcriptomes from human pancreatic islet-engrafted mice

Human pancreatic islets engrafted into immunodeficient mice serve as an important model for in vivo human diabetes studies. Following engraftment, islet function can be monitored in vivo by measuring circulating glucose and human insulin; however, it will be important to recover viable cells for more complex graft analyses. Moreover, RNA analyses of dissected grafts have not distinguished which hormone-specific cell types contribute to gene expression. We developed a method for recovering live cells suitable for fluorescence-activated cell sorting from human islets engrafted in mice. Although yields of recovered islet cells were relatively low, the ratios of bulk-sorted β, α, and δ cells and their respective hormone-specific RNA-Seq transcriptomes are comparable pretransplant and posttransplant, suggesting that the cellular characteristics of islet grafts posttransplant closely mirror the original donor islets. Single-cell RNA-Seq transcriptome analysis confirms the presence of appropriate β, α, and δ cell subsets. In addition, ex vivo perifusion of recovered human islet grafts demonstrated glucose-stimulated insulin secretion. Viable cells suitable for patch-clamp analysis were recovered from transplanted human embryonic stem cell-derived β cells. Together, our functional and hormone-specific transcriptome analyses document the broad applicability of this system for longitudinal examination of human islet cells undergoing developmental/metabolic/pharmacogenetic manipulation in vivo and may facilitate the discovery of treatments for diabetes.

Informing β-cell regeneration strategies using studies of heterogeneity

BACKGROUND

Current therapeutic strategies for type 1 (T1DM) and type 2 diabetes mellitus (T2DM) rely on increasing or substituting endogenous insulin secretion in combination with lifestyle changes. β-cell regeneration, a process whereby new β-cells arise from progenitors, self-renewal or transdifferentiation, has the potential to become a viable route to insulin self-sufficiency. Current regeneration strategies capture many of the transcriptomic and protein features of native β-cells, generating cells capable of glucose-dependent insulin secretion in vitro and alleviation of hyperglycemia in vivo. However, whether novel β-cells display appreciable heterogeneity remains poorly understood, with potential consequences for long-term functional robustness.

SCOPE OF REVIEW

The review brings together crucial discoveries in the β-cell regeneration field with state-of-the-art knowledge regarding β-cell heterogeneity. Aspects that might aid production of longer-lasting and more plastic regenerated β-cells are highlighted and discussed.

MAJOR CONCLUSIONS

Different β-cell regeneration approaches result in a similar outcome: glucose-sensitive, insulin-positive cells that mimic the native β-cell phenotype but which lack normal plasticity. The β-cell subpopulations identified to date expand our understanding of β-cell survival, proliferation and function, signposting the direction for future regeneration strategies. Therefore, regenerated β-cells should exhibit stimulus-dependent differences in gene and protein expression, as well as establish a functional network with different β-cells, all while coexisting with other cell types on a three-dimensional platform.

Heterogeneity and Delayed Activation as Hallmarks of Self-Organization and Criticality in Excitable Tissue

Self-organized critical dynamics is assumed to be an attractive mode of functioning for several real-life systems and entails an emergent activity in which the extent of observables follows a power-law distribution. The hallmarks of criticality have recently been observed in a plethora of biological systems, including beta cell populations within pancreatic islets of Langerhans. In the present study, we systematically explored the mechanisms that drive the critical and supercritical behavior in networks of coupled beta cells under different circumstances by means of experimental and computational approaches. Experimentally, we employed high-speed functional multicellular calcium imaging of fluorescently labeled acute mouse pancreas tissue slices to record calcium signals in a large number of beta cells simultaneously, and with a high spatiotemporal resolution. Our experimental results revealed that the cellular responses to stimulation with glucose are biphasic and glucose-dependent. Under physiological as well as under supraphysiological levels of stimulation, an initial activation phase was followed by a supercritical plateau phase with a high number of global intercellular calcium waves. However, the activation phase displayed fingerprints of critical behavior under lower stimulation levels, with a progressive recruitment of cells and a power-law distribution of calcium wave sizes. On the other hand, the activation phase provoked by pathophysiologically high glucose concentrations, differed considerably and was more rapid, less continuous, and supercritical. To gain a deeper insight into the experimentally observed complex dynamical patterns, we built up a phenomenological model of coupled excitable cells and explored empirically the model’s necessities that ensured a good overlap between computational and experimental results. It turned out that such a good agreement between experimental and computational findings was attained when both heterogeneous and stimulus-dependent time lags, variability in excitability levels, as well as a heterogeneous cell-cell coupling were included into the model. Most importantly, since our phenomenological approach involved only a few parameters, it naturally lends itself not only for determining key mechanisms of self-organized criticality at the tissue level, but also points out various features for comprehensive and realistic modeling of different excitable systems in nature.

NIH Initiative to Improve Understanding of the Pancreas, Islet, and Autoimmunity in Type 1 Diabetes: The Human Pancreas Analysis Program (HPAP)

Type 1 diabetes risk can reliably be predicted by markers of autoimmunity, but approaches to prevent or modify the underlying disease process are needed. We posit this void fundamentally results from a limited understanding of immune-islet cell interactions within the pancreas and relevant immune organs, contributions of β-cells to their own demise, and epigenetic predispositions affecting both immune and islet cells. Because biopsy of the human pancreas and pancreatic lymph nodes carries risk and the pancreas begins to autodigest soon after death, detailed cellular and molecular phenotyping of the human type 1 diabetes pancreas is lacking, limiting our understanding of the mechanisms of β-cell loss. To address these challenges, the National Institutes of Health/National Institute of Diabetes and Digestive and Kidney Diseases established the Human Pancreas Analysis Program (HPAP) to procure human type 1 diabetes pancreata for an extensive array of tissue-based, cellular, and epigenetic assays aimed at critical knowledge gaps in our understanding of the local immune attack and loss of β-cells. In this Methodology Review, we describe how HPAP is performing detailed islet and immune cell phenotyping and creating publicly available data sets with the goals of an improved understanding of type 1 diabetes and the development of more effective treatments to prevent or reverse the disease.

High-fat diet impacts more changes in beta-cell compared to alpha-cell transcriptome

Characterization of endocrine-cell functions and associated molecular signatures in diabetes is crucial to better understand why and by which mechanisms alpha and beta cells cause and perpetuate metabolic abnormalities. The now recognized role of glucagon in diabetes control is a major incentive to have a better understanding of dysfunctional alpha cells. To characterize molecular alterations of alpha cells in diabetes, we analyzed alpha-cell transcriptome from control and diabetic mice using diet-induced obesity model. To this aim, we quantified the expression levels of total mRNAs from sorted alpha and beta cells of low-fat and high-fat diet-treated mice through RNAseq experiments, using a transgenic mouse strain allowing collections of pancreatic alpha- and beta-cells after 16 weeks of diet. We now report that pancreatic alpha cells from obese hyperglycemic mice displayed minor variations of their transcriptome compared to controls. Depending on analyses, we identified 11 to 39 differentially expressed genes including non-alpha cell markers mainly due to minor cell contamination during purification process. From these analyses, we identified three new target genes altered in diabetic alpha cells and potently involved in cellular stress and exocytosis (Upk3a, Adcy1 and Dpp6). By contrast, analysis of the beta-cell transcriptome from control and diabetic mice revealed major alterations of specific genes coding for proteins involved in proliferation and secretion. We conclude that alpha cell transcriptome is less reactive to HFD diet compared to beta cells and display adaptations to cellular stress and exocytosis.

Single-Cell RNA-Seq of the Pancreatic Islets--a Promise Not yet Fulfilled?

In the past 3 years, we have seen a flurry of publications on single-cell RNA sequencing (RNA-seq) analyses of pancreatic islets from mouse and human. This technology holds the promise to refine cell-type signatures and discover cellular heterogeneity among the canonical endocrine cell types such as the glucagon-producing α and insulin-producing β cells, going as far as suggesting new subtypes. In addition, single-cell RNA-seq has the ability to characterize rare endocrine cell types that are not captured by prior bulk analysis. With transcriptomics data from individual endocrine cells, cellular states can be profiled both along developmental processes and during the emergence of metabolic diseases. However, the promises of this new technology have not yet been met in full. While the methodology for the first time enabled the transcriptional definition of rare endocrine cell types such as ghrelin-producing ɛ cells, some of the conclusions regarding cell-type-specific gene expression changes in type 2 diabetes might need to be revisited once larger sample sizes become available. Data generation and analysis are continuously improving single-cell RNA-seq approaches and are helping us to understand the (mal)adaptations of the islet cells during development, metabolic challenge, and disease.

Concise Review: Human Pluripotent Stem Cells for the Modeling of Pancreatic β-Cell Pathology

Pancreatic β‐cells are the only source of insulin. Disturbances in β‐cell development or function may thus result in insulin deficiency or excess, presenting as hyper‐ or hypoglycemia. It is increasingly evident that common forms of diabetes (types 1 and 2) are pathogenically heterogeneous. Development of efficient therapies is dependent on reliable disease models. Although animal models are remarkably useful research tools, they present limitations because of species differences. As an alternative, human pluripotent stem cell technologies offer multiple possibilities for the study of human diseases in vitro. In the last decade, advances in the derivation of induced pluripotent stem cells from diabetic patients, combined with β‐cell differentiation protocols, have resulted in the generation of useful disease models for diabetes. First disease models have been focusing on monogenic diabetes. The development of genome editing technologies, more advanced differentiation protocols and humanized mouse models based on transplanted cells have opened new horizons for the modeling of more complex forms of β‐cell dysfunction. We present here the incremental progress made in the modeling of diabetes using pluripotent stem cells. We discuss the current challenges and opportunities of these approaches to dissect β‐cell pathology and devise new pharmacological and cell replacement therapies. stem cells2019;37:33–41

Insulin mutations impair beta-cell development in a patient-derived iPSC model of neonatal diabetes

Insulin gene mutations are a leading cause of neonatal diabetes. They can lead to proinsulin misfolding and its retention in endoplasmic reticulum (ER). This results in increased ER-stress suggested to trigger beta-cell apoptosis. In humans, the mechanisms underlying beta-cell failure remain unclear. Here we show that misfolded proinsulin impairs developing beta-cell proliferation without increasing apoptosis. We generated induced pluripotent stem cells (iPSCs) from people carrying insulin (INS) mutations, engineered isogenic CRISPR-Cas9 mutation-corrected lines and differentiated them to beta-like cells. Single-cell RNA-sequencing analysis showed increased ER-stress and reduced proliferation in INS-mutant beta-like cells compared with corrected controls. Upon transplantation into mice, INS-mutant grafts presented reduced insulin secretion and aggravated ER-stress. Cell size, mTORC1 signaling, and respiratory chain subunits expression were all reduced in INS-mutant beta-like cells, yet apoptosis was not increased at any stage. Our results demonstrate that neonatal diabetes-associated INS-mutations lead to defective beta-cell mass expansion, contributing to diabetes development.

The role of beta cell heterogeneity in islet function and insulin release

It is becoming increasingly apparent that not all insulin-secreting beta cells are equal. Subtle differences exist at the transcriptomic and protein expression levels, with repercussions for beta cell survival/proliferation, calcium signalling and insulin release. Notably, beta cell heterogeneity displays plasticity during development, metabolic stress and type 2 diabetes mellitus (T2DM). Thus, heterogeneity or lack thereof may be an important contributor to beta cell failure during T2DM in both rodents and humans. The present review will discuss the molecular and cellular features of beta cell heterogeneity at both the single-cell and islet level, explore how this influences islet function and insulin release and look into the alterations that may occur during obesity and T2DM.