Generation of human islet cell type-specific identity genesets

Islet Like Cells Induced from Umbilical Cord Mesenchymal Stem Cells with Neonatal Bovine Pancreatic Mesenchymal Exosomes for Treatment of Diabetes Mellitus

To investigate the safety and efficacy of the islet-like cell (cell) induced from human umbilical cord mesenchymal stem cell (UCMSC) with different methods for the treatment of diabetic animal model. UCMSCs were induced to βcells with cytokines (CY) and neonatal bovine pancreatic mesenchymal cell exosomes (Ex) combined with CY (EX+CY). The insulin secretion of UCMSC and βcell was measured with ELISA when the cells were growing in different concentrations of glucose media for different times. UCMSCs (4×105) and the same number of cells prepared with two methods were transplanted to type I diabetic rat models. UCMSCs could be induced into islet βcells by CY or EX+CY in vitro. The insulin secretion of the prepared β cells growing in 25.0 mM glucose medium was over 5-fold of that in 6.0 mM glucose. The transplantation of the βcells to type I diabetic rat models could reduce the blood glucose and prolong the survival time. The β cells induced by EX+CY had much more significant effects on decreasing blood glucose and increasing survival time (p<0.01). The cells did not affect blood sugar level and had no serious side-effects in human health. UCMSC could be induced to islet βcells with either CY or EX+CY. The transplantation of the induced islet βcells could reduce blood glucose and prolong the survival time of diabetic animal models. Although the cells induced with EX+CY had more significant effects on diabetic rats, they did not affect blood glucose level and had no serious side-effects in human health.

LDHB contributes to the regulation of lactate levels and basal insulin secretion in human pancreatic β cells

Using 13C6 glucose labeling coupled to gas chromatography-mass spectrometry and 2D 1H-13C heteronuclear single quantum coherence NMR spectroscopy, we have obtained a comparative high-resolution map of glucose fate underpinning β cell function. In both mouse and human islets, the contribution of glucose to the tricarboxylic acid (TCA) cycle is similar. Pyruvate fueling of the TCA cycle is primarily mediated by the activity of pyruvate dehydrogenase, with lower flux through pyruvate carboxylase. While the conversion of pyruvate to lactate by lactate dehydrogenase (LDH) can be detected in islets of both species, lactate accumulation is 6-fold higher in human islets. Human islets express LDH, with low-moderate LDHA expression and β cell-specific LDHB expression. LDHB inhibition amplifies LDHA-dependent lactate generation in mouse and human β cells and increases basal insulin release. Lastly, cis-instrument Mendelian randomization shows that low LDHB expression levels correlate with elevated fasting insulin in humans. Thus, LDHB limits lactate generation in β cells to maintain appropriate insulin release.

Single cell regulatory architecture of human pancreatic islets suggests sex differences in β cell function and the pathogenesis of type 2 diabetes

Biological sex affects the pathogenesis of type 2 and type 1 diabetes (T2D, T1D) including the development of β cell failure observed more often in males. The mechanisms that drive sex differences in β cell failure is unknown. Studying sex differences in islet regulation and function represent a unique avenue to understand the sex-specific heterogeneity in β cell failure in diabetes. Here, we examined sex and race differences in human pancreatic islets from up to 52 donors with and without T2D (including 37 donors from the Human Pancreas Analysis Program [HPAP] dataset) using an orthogonal series of experiments including single cell RNA-seq (scRNA-seq), single nucleus assay for transposase-accessible chromatin sequencing (snATAC-seq), dynamic hormone secretion, and bioenergetics. In cultured islets from nondiabetic (ND) donors, in the absence of the in vivo hormonal environment, sex differences in islet cell type gene accessibility and expression predominantly involved sex chromosomes. Of particular interest were sex differences in the X-linked KDM6A and Y-linked KDM5D chromatin remodelers in female and male islet cells respectively. Islets from T2D donors exhibited similar sex differences in differentially expressed genes (DEGs) from sex chromosomes. However, in contrast to islets from ND donors, islets from T2D donors exhibited major sex differences in DEGs from autosomes. Comparing β cells from T2D and ND donors revealed that females had more DEGs from autosomes compared to male β cells. Gene set enrichment analysis of female β cell DEGs showed a suppression of oxidative phosphorylation and electron transport chain pathways, while male β cell had suppressed insulin secretion pathways. Thus, although sex-specific differences in gene accessibility and expression of cultured ND human islets predominantly affect sex chromosome genes, major differences in autosomal gene expression between sexes appear during the transition to T2D and which highlight mitochondrial failure in female β cells.

Conditional c-MYC activation in catecholaminergic cells drives distinct neuroendocrine tumors: neuroblastoma vs somatostatinoma

The MYC proto-oncogenes (c-MYC, MYCN , MYCL ) are among the most deregulated oncogenic drivers in human malignancies including high-risk neuroblastoma, 50% of which are MYCN -amplified. Genetically engineered mouse models (GEMMs) based on the MYCN transgene have greatly expanded the understanding of neuroblastoma biology and are powerful tools for testing new therapies. However, a lack of c-MYC-driven GEMMs has hampered the ability to better understand mechanisms of neuroblastoma oncogenesis and therapy development given that c-MYC is also an important driver of many high-risk neuroblastomas. In this study, we report two transgenic murine neuroendocrine models driven by conditional c-MYC induction in tyrosine hydroxylase (Th) and dopamine β-hydroxylase (Dbh)-expressing cells. c-MYC induction in Th-expressing cells leads to a preponderance of Pdx1 + somatostatinomas, a type of pancreatic neuroendocrine tumor (PNET), resembling human somatostatinoma with highly expressed gene signatures of δ cells and potassium channels. In contrast, c-MYC induction in Dbh-expressing cells leads to onset of neuroblastomas, showing a better transforming capacity than MYCN in a comparable C57BL/6 genetic background. The c-MYC murine neuroblastoma tumors recapitulate the pathologic and genetic features of human neuroblastoma, express GD2, and respond to anti-GD2 immunotherapy. This model also responds to DFMO, an FDA-approved inhibitor targeting ODC1, which is a known MYC transcriptional target. Thus, establishing c-MYC-overexpressing GEMMs resulted in different but related tumor types depending on the targeted cell and provide useful tools for testing immunotherapies and targeted therapies for these diseases.

Proteomic predictors of individualized nutrient-specific insulin secretion in health and disease

Population level variation and molecular mechanisms behind insulin secretion in response to carbohydrate, protein, and fat remain uncharacterized despite ramifications for personalized nutrition. Here, we define prototypical insulin secretion dynamics in response to the three macronutrients in islets from 140 cadaveric donors, including those diagnosed with type 2 diabetes. While islets from the majority of donors exhibited the expected relative response magnitudes, with glucose being highest, amino acid moderate, and fatty acid small, 9% of islets stimulated with amino acid and 8% of islets stimulated with fatty acids had larger responses compared with high glucose. We leveraged this insulin response heterogeneity and used transcriptomics and proteomics to identify molecular correlates of specific nutrient responsiveness, as well as those proteins and mRNAs altered in type 2 diabetes. We also examine nutrient-responsiveness in stem cell-derived islet clusters and observe that they have dysregulated fuel sensitivity, which is a hallmark of functionally immature cells. Our study now represents the first comparison of dynamic responses to nutrients and multi-omics analysis in human insulin secreting cells. Responses of different people's islets to carbohydrate, protein, and fat lay the groundwork for personalized nutrition.

ONE-SENTENCE SUMMARY

Deep phenotyping and multi-omics reveal individualized nutrient-specific insulin secretion propensity.

Glucagon-producing α-cell transcriptional identity and reprogramming towards insulin production

β-Cell replacement by in situ reprogramming of non-β-cells is a promising diabetes therapy. Following the observation that near-total β-cell ablation in adult mice triggers the reprogramming of pancreatic α-, δ-, and γ-cells into insulin (INS)-producing cells, recent studies are delving deep into the mechanisms controlling adult α-cell identity. Systematic analyses of the α-cell transcriptome and epigenome have started to pinpoint features that could be crucial for maintaining α-cell identity. Using different transgenic and chemical approaches, significant advances have been made in reprogramming α-cells in vivo into INS-secreting cells in mice. The recent reprogramming of human α-cells in vitro is an important step forward that must now be complemented with a comprehensive molecular dissection of the mechanisms controlling α-cell identity.

Comparative and integrative single cell analysis reveals new insights into the transcriptional immaturity of stem cell-derived β cells

Diabetes cell replacement therapy has the potential to be transformed by human pluripotent stem cell-derived β cells (SC-β cells). However, the precise identity of SC-β cells in relationship to primary fetal and adult β-cells remains unclear. Here, we used single-cell sequencing datasets to characterize the transcriptional identity of islets from in vitro differentiation, fetal islets, and adult islets. Our analysis revealed that SC-β cells share a core β-cell transcriptional identity with human adult and fetal β-cells, however SC-β cells possess a unique transcriptional profile characterized by the persistent expression and activation of progenitor and neural-biased gene networks. These networks are present in SC-β cells, irrespective of the derivation protocol used. Notably, fetal β-cells also exhibit this neural signature at the transcriptional level. Our findings offer insights into the transcriptional identity of SC-β cells and underscore the need for further investigation of the role of neural transcriptional networks in their development.

PancrESS - a meta-analysis resource for understanding cell-type specific expression in the human pancreas

BACKGROUND

The human pancreas is composed of specialized cell types producing hormones and enzymes critical to human health. These specialized functions are the result of cell type-specific transcriptional programs which manifest in cell-specific gene expression. Understanding these programs is essential to developing therapies for pancreatic disorders. Transcription in the human pancreas has been widely studied by single-cell RNA technologies, however the diversity of protocols and analysis methods hinders their interpretability in the aggregate.

RESULTS

In this work, we perform a meta-analysis of pancreatic single-cell RNA sequencing data. We present a database for reference transcriptome abundances and cell-type specificity metrics. This database facilitates the identification and definition of marker genes within the pancreas. Additionally, we introduce a versatile tool which is freely available as an R package, and should permit integration into existing workflows. Our tool accepts count data files generated by widely-used single-cell gene expression platforms in their original format, eliminating an additional pre-formatting step. Although we designed it to calculate expression specificity of pancreas cell types, our tool is agnostic to the biological source of count data, extending its applicability to other biological systems.

CONCLUSIONS

Our findings enhance the current understanding of expression specificity within the pancreas, surpassing previous work in terms of scope and detail. Furthermore, our database and tool enable researchers to perform similar calculations in diverse biological systems, expanding the applicability of marker gene identification and facilitating comparative analyses.

Ghrelin deletion and conditional ghrelin cell ablation increase pancreatic islet size in mice

Ghrelin exerts key effects on islet hormone secretion to regulate blood glucose levels. Here, we sought to determine whether ghrelin's effects on islets extend to the alteration of islet size and β cell mass. We demonstrate that reducing ghrelin - by ghrelin gene knockout (GKO), conditional ghrelin cell ablation, or high-fat diet (HFD) feeding - was associated with increased mean islet size (up to 62%), percentage of large islets (up to 854%), and β cell cross-sectional area (up to 51%). In GKO mice, these effects were more apparent in 10- to 12-week-old mice than in 4-week-old mice. Higher β cell numbers from decreased β cell apoptosis drove the increase in β cell cross-sectional area. Conditional ghrelin cell ablation in adult mice increased the β cell number per islet by 40% within 4 weeks. A negative correlation between islet size and plasma ghrelin in HFD-fed plus chow-fed WT mice, together with even larger islet sizes in HFD-fed GKO mice than in HFD-fed WT mice, suggests that reduced ghrelin was not solely responsible for diet-induced obesity-associated islet enlargement. Single-cell transcriptomics revealed changes in gene expression in several GKO islet cell types, including upregulation of Manf, Dnajc3, and Gnas expression in β cells, which supports decreased β cell apoptosis and/or increased β cell proliferation. These effects of ghrelin reduction on islet morphology might prove useful when designing new therapies for diabetes.

Generation of β-like cell subtypes from differentiated human induced pluripotent stem cells in 3D spheroids

Since the identification of four different pancreatic β-cell subtypes and bi-hormomal cells playing a role in the diabetes pathogenesis, the search for in vitro models that mimics such cells heterogeneity became a key priority in experimental and clinical diabetology. We investigated the potential of human induced pluripotent stem cells to lead to the development of the different β-cells subtypes in honeycomb microwell-based 3D spheroids. The glucose-stimulated insulin secretion confirmed the spheroids functionality. Then, we performed a single cell RNA sequencing of the spheroids. Using a knowledge-based analysis with a stringency on the pancreatic markers, we extracted the β-cells INS+/UCN3+ subtype (11%; β1-like cells), the INS+/ST8SIA1+/CD9- subtype (3%, β3-like cells) and INS+/CD9+/ST8SIA1-subtype (1%; β2-like cells) consistently with literature findings. We did not detect the INS+/ST8SIA1+/CD9+ cells (β4-like cells). Then, we also identified four bi-hormonal cells subpopulations including δ-like cells (INS+/SST+, 6%), γ-like cells (INS+/PPY+, 3%), α-like-cells (INS+/GCG+, 6%) and ε-like-cells (INS+/GHRL+, 2%). Using data-driven clustering, we extracted four progenitors' subpopulations (with the lower level of INS gene) that included one population highly expressing inhibin genes (INHBA+/INHBB+), one population highly expressing KCNJ3+/TPH1+, one population expressing hepatocyte-like lineage markers (HNF1A+/AFP+), and one population expressing stem-like cell pancreatic progenitor markers (SOX2+/NEUROG3+). Furthermore, among the cycling population we found a large number of REST+ cells and CD9+ cells (CD9+/SPARC+/REST+). Our data confirm that our differentiation leads to large β-cell heterogeneity, which can be used for investigating β-cells plasticity under physiological and pathophysiological conditions.

Intertumoral lineage diversity and immunosuppressive transcriptional programs in well-differentiated gastroenteropancreatic neuroendocrine tumors

Neuroendocrine tumors (NETs) are rare cancers that most often arise in the gastrointestinal tract and pancreas. The fundamental mechanisms driving gastroenteropancreatic (GEP)-NET growth remain incompletely elucidated; however, the heterogeneous clinical behavior of GEP-NETs suggests that both cellular lineage dynamics and tumor microenvironment influence tumor pathophysiology. Here, we investigated the single-cell transcriptomes of tumor and immune cells from patients with gastroenteropancreatic NETs. Malignant GEP-NET cells expressed genes and regulons associated with normal, gastrointestinal endocrine cell differentiation, and fate determination stages. Tumor and lymphoid compartments sparsely expressed immunosuppressive targets commonly investigated in clinical trials, such as the programmed cell death protein-1/programmed death ligand-1 axis. However, infiltrating myeloid cell types within both primary and metastatic GEP-NETs were enriched for genes encoding other immune checkpoints, including VSIR (VISTA), HAVCR2 (TIM3), LGALS9 (Gal-9), and SIGLEC10. Our findings highlight the transcriptomic heterogeneity that distinguishes the cellular landscapes of GEP-NET anatomic subtypes and reveal potential avenues for future precision medicine therapeutics.

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.

Deficiency of the metabolic enzyme SCHAD in pancreatic β-cells promotes amino acid-sensitive hypoglycemia

Congenital hyperinsulinism of infancy (CHI) can be caused by a deficiency of the ubiquitously expressed enzyme short-chain 3-hydroxyacyl-CoA dehydrogenase (SCHAD). To test the hypothesis that SCHAD-CHI arises from a specific defect in pancreatic β-cells, we created genetically engineered β-cell-specific (β-SKO) or hepatocyte-specific (L-SKO) SCHAD knockout mice. While L-SKO mice were normoglycemic, plasma glucose in β-SKO animals was significantly reduced in the random-fed state, after overnight fasting, and following refeeding. The hypoglycemic phenotype was exacerbated when the mice were fed a diet enriched in leucine, glutamine, and alanine. Intraperitoneal injection of these three amino acids led to a rapid elevation in insulin levels in β-SKO mice compared to controls. Consistently, treating isolated β-SKO islets with the amino acid mixture potently enhanced insulin secretion compared to controls in a low-glucose environment. RNA sequencing of β-SKO islets revealed reduced transcription of β-cell identity genes and upregulation of genes involved in oxidative phosphorylation, protein metabolism, and Ca2+ handling. The β-SKO mouse offers a useful model to interrogate the intra-islet heterogeneity of amino acid sensing given the very variable expression levels of SCHAD within different hormonal cells, with high levels in β- and δ-cells and virtually absent α-cell expression. We conclude that the lack of SCHAD protein in β-cells results in a hypoglycemic phenotype characterized by increased sensitivity to amino acid-stimulated insulin secretion and loss of β-cell identity.

Pharmacological HDAC inhibition impairs pancreatic β-cell function through an epigenome-wide reprogramming

Histone deacetylases enzymes (HDACs) are chromatin modifiers that regulate gene expression through deacetylation of lysine residues within specific histone and non-histone proteins. A cell-specific gene expression pattern defines the identity of insulin-producing pancreatic β cells, yet molecular networks driving this transcriptional specificity are not fully understood. Here, we investigated the HDAC-dependent molecular mechanisms controlling pancreatic β-cell identity and function using the pan-HDAC inhibitor trichostatin A through chromatin immunoprecipitation assays and RNA sequencing experiments. We observed that TSA alters insulin secretion associated with β-cell specific transcriptome programming in both mouse and human β-cell lines, as well as on human pancreatic islets. We also demonstrated that this alternative β-cell transcriptional program in response to HDAC inhibition is related to an epigenome-wide remodeling at both promoters and enhancers. Our data indicate that HDAC activity could be required to protect against loss of β-cell identity with unsuitable expression of genes associated with alternative cell fates.

The human α cell in health and disease

In commemoration of 100 years since the discovery of glucagon, we review current knowledge about the human α cell. Alpha cells make up 30-40% of human islet endocrine cells and play a major role in regulating whole-body glucose homeostasis, largely through the direct actions of their main secretory product - glucagon - on peripheral organs. Additionally, glucagon and other secretory products of α cells, namely acetylcholine, glutamate, and glucagon-like peptide-1, have been shown to play an indirect role in the modulation of glucose homeostasis through autocrine and paracrine interactions within the islet. Studies of glucagon's role as a counterregulatory hormone have revealed additional important functions of the α cell, including the regulation of multiple aspects of energy metabolism outside that of glucose. At the molecular level, human α cells are defined by the expression of conserved islet-enriched transcription factors and various enriched signature genes, many of which have currently unknown cellular functions. Despite these common threads, notable heterogeneity exists amongst human α cell gene expression and function. Even greater differences are noted at the inter-species level, underscoring the importance of further study of α cell physiology in the human context. Finally, studies on α cell morphology and function in type 1 and type 2 diabetes, as well as other forms of metabolic stress, reveal a key contribution of α cell dysfunction to dysregulated glucose homeostasis in disease pathogenesis, making targeting the α cell an important focus for improving treatment.

Single-nucleus multi-omics of human stem cell-derived islets identifies deficiencies in lineage specification

Insulin-producing β cells created from human pluripotent stem cells have potential as a therapy for insulin-dependent diabetes, but human pluripotent stem cell-derived islets (SC-islets) still differ from their in vivo counterparts. To better understand the state of cell types within SC-islets and identify lineage specification deficiencies, we used single-nucleus multi-omic sequencing to analyse chromatin accessibility and transcriptional profiles of SC-islets and primary human islets. Here we provide an analysis that enabled the derivation of gene lists and activity for identifying each SC-islet cell type compared with primary islets. Within SC-islets, we found that the difference between β cells and awry enterochromaffin-like cells is a gradient of cell states rather than a stark difference in identity. Furthermore, transplantation of SC-islets in vivo improved cellular identities overtime, while long-term in vitro culture did not. Collectively, our results highlight the importance of chromatin and transcriptional landscapes during islet cell specification and maturation.

Single-nucleus RNA sequencing of human pancreatic islets identifies novel gene sets and distinguishes β-cell subpopulations with dynamic transcriptome profiles

BACKGROUND

Single-cell RNA sequencing (scRNA-seq) provides valuable insights into human islet cell types and their corresponding stable gene expression profiles. However, this approach requires cell dissociation that complicates its utility in vivo. On the other hand, single-nucleus RNA sequencing (snRNA-seq) has compatibility with frozen samples, elimination of dissociation-induced transcriptional stress responses, and affords enhanced information from intronic sequences that can be leveraged to identify pre-mRNA transcripts.

METHODS

We obtained nuclear preparations from fresh human islet cells and generated snRNA-seq datasets. We compared these datasets to scRNA-seq output obtained from human islet cells from the same donor. We employed snRNA-seq to obtain the transcriptomic profile of human islets engrafted in immunodeficient mice. In both analyses, we included the intronic reads in the snRNA-seq data with the GRCh38-2020-A library.

RESULTS

First, snRNA-seq analysis shows that the top four differentially and selectively expressed genes in human islet endocrine cells in vitro and in vivo are not the canonical genes but a new set of non-canonical gene markers including ZNF385D, TRPM3, LRFN2, PLUT (β-cells); PTPRT, FAP, PDK4, LOXL4 (α-cells); LRFN5, ADARB2, ERBB4, KCNT2 (δ-cells); and CACNA2D3, THSD7A, CNTNAP5, RBFOX3 (γ-cells). Second, by integrating information from scRNA-seq and snRNA-seq of human islet cells, we distinguish three β-cell sub-clusters: an INS pre-mRNA cluster (β3), an intermediate INS mRNA cluster (β2), and an INS mRNA-rich cluster (β1). These display distinct gene expression patterns representing different biological dynamic states both in vitro and in vivo. Interestingly, the INS mRNA-rich cluster (β1) becomes the predominant sub-cluster in vivo.

CONCLUSIONS

In summary, snRNA-seq and pre-mRNA analysis of human islet cells can accurately identify human islet cell populations, subpopulations, and their dynamic transcriptome profile in vivo.