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

Molecular correlates of glycine receptor activity in human β cells

OBJECTIVES

Glycine acts in an autocrine positive feedback loop in human β cells through its ionotropic receptors (GlyRs). In type 2 diabetes (T2D), islet GlyR activity is impaired by unknown mechanisms. We sought to investigate if the GlyR dysfunction in T2D is replicated by hyperglycemia per se, and to further characterize its action in β cells and islets.

METHODS

GlyR-mediated currents were measured using whole-cell patch-clamp in human β cells from donors with or without T2D, or after high glucose (15 mM) culture. We also correlated glycine-induced current amplitude with transcript expression levels through patch-seq. The expression of the GlyR α1, α3, and β subunit mRNA splice variants was compared between islets from donors with and without T2D, and after high glucose culture. Insulin secretion from human islets was measured in the presence or absence of the GlyR antagonist strychnine.

RESULTS

Although gene expression of GlyRs was decreased in T2D islets, and β cell GlyR-mediated currents were smaller, we found no evidence for a shift in GlyR subunit splicing. Glycine-induced currents are also reduced after 48 h culture of islets from donors without diabetes in high glucose, where we also find the reduction of the α1 subunit expression, but an increase in the α3 subunit. We discovered that glycine-evoked currents are highly heterogeneous amongst β cells, inversely correlate with donor HbA1c, and are significantly correlated to the expression of 92 different transcripts and gene regulatory networks (GRNs) that include CREB3(+), RREB1(+) and ZNF697(+). Finally, glucose-stimulated insulin secretion is decreased in the presence of the GlyR antagonist strychnine.

CONCLUSIONS

We demonstrate that glucose can modulate GlyR expression, and that the current decrease in T2D is likely due to the receptor gene expression downregulation, and not a change in transcript splicing. Moreover, we define a previously unknown set of genes and regulons that are correlated to GlyR-mediated currents and could be involved in GlyR downregulation in T2D. Among those we validate the negative impact of EIF4EBP1 expression on GlyR activity.

Single-Cell RNA Sequencing Outperforms Single-Nucleus RNA Sequencing in Analyzing Pancreatic Cell Diversity and Gene Expression in Goats

The objective of this study was to determine whether single-cell RNA sequencing (scRNA-seq) or single-nucleus RNA sequencing (snRNA-seq) was more effective for studying the goat pancreas. Pancreas tissues from three healthy 10-day-old female Xiangdong black goats were processed into single-cell and single-nucleus suspensions. These suspensions were then used to compare cellular composition and gene expression levels following library construction and sequencing. Both scRNA-seq and snRNA-seq were eligible for primary analysis but produced different cell identification profiles in pancreatic tissue. Both methods successfully annotated pancreatic acinar cells, ductal cells, alpha cells, beta cells, and endothelial cells. However, pancreatic stellate cells, immune cells, and delta cells were uniquely annotated by scRNA-seq, while pancreatic stem cells were uniquely identified by snRNA-seq. Furthermore, the genes related to digestive enzymes showed a higher expression in scRNA-seq than in snRNA-seq. In the present study, scRNA-seq detected a great diversity of pancreatic cell types and was more effective in profiling key genes than snRNA-seq, demonstrating that scRNA-seq was better suited for studying the goat pancreas. However, the choice between scRNA-seq and snRNA-seq should consider the sample compatibility, technical differences, and experimental objectives.

A systematic review of single-cell RNA sequencing applications and innovations

Bulk RNA sequencing is one type of RNA sequencing technique, as well as targeted RNA sequencing and whole transcriptome sequencing. It provides valuable insights into gene expression in specific cell populations or regions. However, these methods often miss the diversity of cells within complex tissues. This restriction is overcome by single-cell RNA sequencing, which records gene expression at the single-cell level. It offers a detailed picture of the diversity of cells. It is essential to study glucose homeostasis. It offers thorough explanations of cellular variation. Networks and Governance Dynamics The use of scRNA-seq in islet cells is reviewed in this study, along with sample preparation, sequencing, and computational analysis. It highlights advances in understanding cell types. Gene activity and cell interactions. Along with the challenges and limitations of scRNA-seq, this review highlights the importance of scRNA-seq in understanding complex biological processes and diseases. It is an essential resource for future research and method development in this field, which will help to build personalized treatment.

Transcriptomic heterogeneity of non-beta islet cells is associated with type 2 diabetes development in mouse models

AIMS/HYPOTHESIS

The aim of this work was to understand the role of non-beta cells in pancreatic islets at early stages of type 2 diabetes pathogenesis.

METHODS

Specific clustering was employed to single-cell transcriptome data from islet cells of obese mouse strains differing in their diabetes susceptibility (diabetes-resistant B6.V.Lepob/ob [OB] and diabetes-susceptible New Zealand Obese [NZO] mice) on a diabetogenic diet.

RESULTS

Refined clustering analysis revealed several heterogeneous subpopulations for alpha cells, delta cells and macrophages, of which 133 mapped to human diabetes genes identified by genome-wide association studies. Importantly, a similar non-beta cell heterogeneity was found in a dataset of human islets from donors at different stages of type 2 diabetes. The predominant alpha cell cluster in NZO mice displayed signs of cellular stress and lower mitochondrial capacity (97 differentially expressed genes [DEGs]), whereas delta cells from these mice exhibited higher expression levels of maturation marker genes (Hhex and Sst) but lower somatostatin secretion than OB mice (184 DEGs). Furthermore, a cluster of macrophages was almost twice as abundant in islets of OB mice, and displayed extensive cell-cell communication with beta cells of OB mice. Treatment of beta cells with IL-15, predicted to be released by macrophages, activated signal transducer and activator of transcription (STAT3), which may mediate anti-apoptotic effects. Similar to mice, humans without diabetes possess a greater number of macrophages than those with prediabetes (39 mmol/mol [5.7%] < HbA1c < 46 mmol/mol [6.4%]) and diabetes.

CONCLUSIONS/INTERPRETATION

Our study indicates that the transcriptional heterogeneity of non-beta cells has an impact on intra-islet crosstalk and participates in beta cell (dys)function.

DATA AVAILABILITY

scRNA-seq data from the previous study are available in gene expression omnibus under gene accession number GSE159211 ( https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE159211 ).

Regulation of endocrine cell alternative splicing revealed by single-cell RNA sequencing in type 2 diabetes pathogenesis

The prevalent RNA alternative splicing (AS) contributes to molecular diversity, which has been demonstrated in cellular function regulation and disease pathogenesis. However, the contribution of AS in pancreatic islets during diabetes progression remains unclear. Here, we reanalyze the full-length single-cell RNA sequencing data from the deposited database to investigate AS regulation across human pancreatic endocrine cell types in non-diabetic (ND) and type 2 diabetic (T2D) individuals. Our analysis demonstrates the significant association between transcriptomic AS profiles and cell-type-specificity, which could be applied to distinguish the clustering of major endocrine cell types. Moreover, AS profiles are enabled to clearly define the mature subset of β-cells in healthy controls, which is completely lost in T2D. Further analysis reveals that RNA-binding proteins (RBPs), heterogeneous nuclear ribonucleoproteins (hnRNPs) and FXR1 family proteins are predicted to induce the functional impairment of β-cells through regulating AS profiles. Finally, trajectory analysis of endocrine cells suggests the β-cell identity shift through dedifferentiation and transdifferentiation of β-cells during the progression of T2D. Together, our study provides a mechanism for regulating β-cell functions and suggests the significant contribution of AS program during diabetes pathogenesis.

A Single-Cell Atlas of the Murine Pancreatic Ductal Tree Identifies Novel Cell Populations With Potential Implications in Pancreas Regeneration and Exocrine Pathogenesis

BACKGROUND & AIMS

Pancreatic ducts form an intricate network of tubules that secrete bicarbonate and drive acinar secretions into the duodenum. This network is formed by centroacinar cells, terminal, intercalated, intracalated ducts, and the main pancreatic duct. Ductal heterogeneity at the single-cell level has been poorly characterized; therefore, our understanding of the role of ductal cells in pancreas regeneration and exocrine pathogenesis has been hampered by the limited knowledge and unexplained diversity within the ductal network.

METHODS

We used single cell RNA sequencing to comprehensively characterize mouse ductal heterogeneity at single-cell resolution of the entire ductal epithelium from centroacinar cells to the main duct. Moreover, we used organoid cultures, injury models, and pancreatic tumor samples to interrogate the role of novel ductal populations in pancreas regeneration and exocrine pathogenesis.

RESULTS

We have identified the coexistence of 15 ductal populations within the healthy pancreas and characterized their organoid formation capacity and endocrine differentiation potential. Cluster isolation and subsequent culturing let us identify ductal cell populations with high organoid formation capacity and endocrine and exocrine differentiation potential in vitro, including a Wnt-responsive population, a ciliated population, and Flrt3+ cells. Moreover, we have characterized the location of these novel ductal populations in healthy pancreas, chronic pancreatitis, and tumor samples. The expression of Wnt-responsive, interferon-responsive, and epithelial-to-mesenchymal transition population markers increases in chronic pancreatitis and tumor samples.

CONCLUSIONS

In light of our discovery of previously unidentified ductal populations, we unmask potential roles of specific ductal populations in pancreas regeneration and exocrine pathogenesis. Thus, novel lineage-tracing models are needed to investigate ductal-specific populations in vivo.

NKX2-2 based nuclei sorting on frozen human archival pancreas enables the enrichment of islet endocrine populations for single-nucleus RNA sequencing

BACKGROUND

Current approaches to profile the single-cell transcriptomics of human pancreatic endocrine cells almost exclusively rely on freshly isolated islets. However, human islets are limited in availability. Furthermore, the extensive processing steps during islet isolation and subsequent single cell dissolution might alter gene expressions. In this work, we report the development of a single-nucleus RNA sequencing (snRNA-seq) approach with targeted islet cell enrichment for endocrine-population focused transcriptomic profiling using frozen archival pancreatic tissues without islet isolation.

RESULTS

We cross-compared five nuclei isolation protocols and selected the citric acid method as the best strategy to isolate nuclei with high RNA integrity and low cytoplasmic contamination from frozen archival human pancreata. We innovated fluorescence-activated nuclei sorting based on the positive signal of NKX2-2 antibody to enrich nuclei of the endocrine population from the entire nuclei pool of the pancreas. Our sample preparation procedure generated high-quality single-nucleus gene-expression libraries while preserving the endocrine population diversity. In comparison with single-cell RNA sequencing (scRNA-seq) library generated with live cells from freshly isolated human islets, the snRNA-seq library displayed comparable endocrine cellular composition and cell type signature gene expression. However, between these two types of libraries, differential enrichments of transcripts belonging to different functional classes could be observed.

CONCLUSIONS

Our work fills a technological gap and helps to unleash frozen archival pancreatic tissues for molecular profiling targeting the endocrine population. This study opens doors to retrospective mappings of endocrine cell dynamics in pancreatic tissues of complex histopathology. We expect that our protocol is applicable to enrich nuclei for transcriptomics studies from various populations in different types of frozen archival tissues.

Single-cell sequencing: A promising approach for uncovering the characteristic of pancreatic islet cells in type 2 diabetes

Single-cell sequencing is a novel and rapidly advancing high-throughput technique that can be used to investigating genomics, transcriptomics, and epigenetics at a single-cell level. Currently, single-cell sequencing can not only be used to draw the pancreatic islet cells map and uncover the characteristics of cellular heterogeneity in type 2 diabetes, but can also be used to label and purify functional beta cells in pancreatic stem cells, improving stem cells and islet organoids therapies. In addition, this technology helps to analyze islet cell dedifferentiation and can be applied to the treatment of type 2 diabetes. In this review, we summarize the development and process of single-cell sequencing, describe the potential applications of single-cell sequencing in the field of type 2 diabetes, and discuss the prospects and limitations of single-cell sequencing to provide a new direction for exploring the pathogenesis of type 2 diabetes and finding therapeutic targets.

A single-cell atlas of the murine pancreatic ductal tree identifies novel cell populations with potential implications in pancreas regeneration and exocrine pathogenesis

Background and aims

Pancreatic ducts form an intricate network of tubules that secrete bicarbonate and drive acinar secretions into the duodenum. This network is formed by centroacinar cells, terminal, intercalated, intracalated ducts, and the main pancreatic duct. Ductal heterogeneity at the single-cell level has been poorly characterized; therefore, our understanding of the role of ductal cells in pancreas regeneration and exocrine pathogenesis has been hampered by the limited knowledge and unexplained diversity within the ductal network.

Methods

We used scRNA-seq to comprehensively characterize mouse ductal heterogeneity at single-cell resolution of the entire ductal epithelium from centroacinar cells to the main duct. Moreover, we used organoid cultures, injury models and pancreatic tumor samples to interrogate the role of novel ductal populations in pancreas regeneration and exocrine pathogenesis.

Results

We have identified the coexistence of 15 ductal populations within the healthy pancreas and characterized their organoid formation capacity and endocrine differentiation potential. Cluster isolation and subsequent culturing let us identify ductal cell populations with high organoid formation capacity and endocrine and exocrine differentiation potential in vitro , including Wnt-responsive-population, ciliated-population and FLRT3 + cells. Moreover, we have characterized the location of these novel ductal populations in healthy pancreas, chronic pancreatitis, and tumor samples, highlighting a putative role of WNT-responsive, IFN-responsive and EMT-populations in pancreatic exocrine pathogenesis as their expression increases in chronic pancreatitis and PanIN lesions.

Conclusions

In light of our discovery of previously unidentified ductal populations, we unmask the potential roles of specific ductal populations in pancreas regeneration and exocrine pathogenesis.

Mapping Cell Atlases at the Single-Cell Level

Recent advancements in single-cell technologies have led to rapid developments in the construction of cell atlases. These atlases have the potential to provide detailed information about every cell type in different organisms, enabling the characterization of cellular diversity at the single-cell level. Global efforts in developing comprehensive cell atlases have profound implications for both basic research and clinical applications. This review provides a broad overview of the cellular diversity and dynamics across various biological systems. In addition, the incorporation of machine learning techniques into cell atlas analyses opens up exciting prospects for the field of integrative biology.

Integrating single-cell transcriptomics with cellular phenotypes: cell morphology, Ca2+ imaging and electrophysiology

I review recent technological advancements in coupling single-cell transcriptomics with cellular phenotypes including morphology, calcium signaling, and electrophysiology. Single-cell RNA sequencing (scRNAseq) has revolutionized cell type classifications by capturing the transcriptional diversity of cells. A new wave of methods to integrate scRNAseq and biophysical measurements is facilitating the linkage of transcriptomic data to cellular function, which provides physiological insight into cellular states. I briefly discuss critical factors of these phenotypical characterizations such as timescales, information content, and analytical tools. Dedicated sections focus on the integration with cell morphology, calcium imaging, and electrophysiology (patch-seq), emphasizing their complementary roles. I discuss their application in elucidating cellular states, refining cell type classifications, and uncovering functional differences in cell subtypes. To illustrate the practical applications and benefits of these methods, I highlight their use in tissues with excitable cell-types such as the brain, pancreatic islets, and the retina. The potential of combining functional phenotyping with spatial transcriptomics for a detailed mapping of cell phenotypes in situ is explored. Finally, I discuss open questions and future perspectives, emphasizing the need for a shift towards broader accessibility through increased throughput.

Phogrin Regulates High-Fat Diet-Induced Compensatory Pancreatic β-Cell Growth by Switching Binding Partners

The receptor protein tyrosine phosphatase phogrin primarily localizes to hormone secretory granules in neuroendocrine cells. Concurrent with glucose-stimulated insulin secretion, phogrin translocates to pancreatic β-cell plasma membranes, where it interacts with insulin receptors (IRs) to stabilize insulin receptor substrate 2 (IRS2) that, in turn, contributes to glucose-responsive β-cell growth. Pancreatic β-cell development was not altered in β-cell-specific, phogrin-deficient mice, but the thymidine incorporation rate decreased in phogrin-deficient islets with a moderate reduction in IRS2 protein expression. In this study, we analyzed the β-cell response to high-fat diet stress and found that the compensatory expansion in β-cell mass was significantly suppressed in phogrin-deficient mice. Phogrin-IR interactions occurred only in high-fat diet murine islets and proliferating β-cell lines, whereas they were inhibited by the intercellular binding of surface phogrin under confluent cell culture conditions. Thus, phogrin could regulate glucose-stimulated compensatory β-cell growth by changing its binding partner from another β-cell phogrin to IR in the same β-cells.

Repression of latent NF-κB enhancers by PDX1 regulates β cell functional heterogeneity

Interactions between lineage-determining and activity-dependent transcription factors determine single-cell identity and function within multicellular tissues through incompletely known mechanisms. By assembling a single-cell atlas of chromatin state within human islets, we identified β cell subtypes governed by either high or low activity of the lineage-determining factor pancreatic duodenal homeobox-1 (PDX1). β cells with reduced PDX1 activity displayed increased chromatin accessibility at latent nuclear factor κB (NF-κB) enhancers. Pdx1 hypomorphic mice exhibited de-repression of NF-κB and impaired glucose tolerance at night. Three-dimensional analyses in tandem with chromatin immunoprecipitation (ChIP) sequencing revealed that PDX1 silences NF-κB at circadian and inflammatory enhancers through long-range chromatin contacts involving SIN3A. Conversely, Bmal1 ablation in β cells disrupted genome-wide PDX1 and NF-κB DNA binding. Finally, antagonizing the interleukin (IL)-1β receptor, an NF-κB target, improved insulin secretion in Pdx1 hypomorphic islets. Our studies reveal functional subtypes of single β cells defined by a gradient in PDX1 activity and identify NF-κB as a target for insulinotropic therapy.

Dynamic scRNA-seq of live human pancreatic slices reveals functional endocrine cell neogenesis through an intermediate ducto-acinar stage

Human pancreatic plasticity is implied from multiple single-cell RNA sequencing (scRNA-seq) studies. However, these have been invariably based on static datasets from which fate trajectories can only be inferred using pseudotemporal estimations. Furthermore, the analysis of isolated islets has resulted in a drastic underrepresentation of other cell types, hindering our ability to interrogate exocrine-endocrine interactions. The long-term culture of human pancreatic slices (HPSs) has presented the field with an opportunity to dynamically track tissue plasticity at the single-cell level. Combining datasets from same-donor HPSs at different time points, with or without a known regenerative stimulus (BMP signaling), led to integrated single-cell datasets storing true temporal or treatment-dependent information. This integration revealed population shifts consistent with ductal progenitor activation, blurring of ductal/acinar boundaries, formation of ducto-acinar-endocrine differentiation axes, and detection of transitional insulin-producing cells. This study provides the first longitudinal scRNA-seq analysis of whole human pancreatic tissue, confirming its plasticity in a dynamic fashion.

An Integrated Map of Cell Type-Specific Gene Expression in Pancreatic Islets

Pancreatic islets consist of multiple cell types that produce hormones required for glucose homeostasis, and islet dysfunction is a major factor in type 1 and type 2 diabetes. Numerous studies have assessed transcription across individual cell types using single-cell assays; however, there is no canonical reference of gene expression in islet cell types that is also easily accessible for researchers to query and use in bioinformatics pipelines. Here we present an integrated map of islet cell type-specific gene expression from 192,203 cells from single-cell RNA sequencing of 65 donors without diabetes, donors who were type 1 diabetes autoantibody positive, donors with type 1 diabetes, and donors with type 2 diabetes from the Human Pancreas Analysis Program. We identified 10 distinct cell types, annotated subpopulations of several cell types, and defined cell type-specific marker genes. We tested differential expression within each cell type across disease states and identified 1,701 genes with significant changes in expression, with most changes observed in β-cells from donors with type 1 diabetes. To facilitate user interaction, we provide several single-cell visualization and reference mapping tools, as well as the open-access analytical pipelines used to create this reference. The results will serve as a valuable resource to investigators studying islet biology.

ARTICLE HIGHLIGHTS

Single-cell analysis reveals the immune heterogeneity and interactions in lungs undergoing hepatic ischemia-reperfusion

Hepatic ischemia-reperfusion IR (HIR) is an unavoidable pathophysiological process during liver transplantation, resulting in systematic sterile inflammation and remote organ injury. Acute lung injury (ALI) is a serious complication after liver transplantation with high postoperative morbidity and mortality. However, the underlying mechanism is still unclear. To assess the phenotype and plasticity of various cell types in the lung tissue microenvironment after HIR at the single-cell level, single-cell RNA sequencing (scRNA-seq) was performed using the lungs from HIR-induced mice. In our results, we identified 23 cell types in the lungs after HIR and found that this highly complex ecosystem was formed by subpopulations of bone marrow-derived cells that signaled each other and mediated inflammatory responses in different states and different intervals. We described the unique transcriptional profiles of lung cell clusters and discovered two novel cell subtypes (Tspo+Endothelial cells and Vcan+ monocytes), as well as the endothelial cell-immune cell and immune cell-T cell clusters interactome. In addition, we found that S100 calcium binding protein (S100a8/a9), specifically and highly expressed in immune cell clusters of lung tissues and exhibited detrimental effects. Finally, the cellular landscape of the lung tissues after HIR was established, highlighting the heterogeneity and cellular interactions between major immune cells in HIR-induced lungs. Our findings provided new insights into the mechanisms of HIR-induced ALI and offered potential therapeutic target to prevent ALI after liver transplantation.

Identification and validation of core genes for type 2 diabetes mellitus by integrated analysis of single-cell and bulk RNA-sequencing

BACKGROUND

The exact mechanisms of type 2 diabetes mellitus (T2DM) remain largely unknown. We intended to authenticate critical genes linked to T2DM progression by tandem single-cell sequencing and general transcriptome sequencing data.

METHODS

T2DM single-cell RNA-sequencing data were submitted by the Gene Expression Omnibus (GEO) database and ArrayExpress (EBI), from which gene expression matrices were retrieved. The common cell clusters and representative marker genes were ascertained by principal component analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE), CellMarker, and FindMarkers in two datasets (GSE86469 and GSE81608). T2DM-related differentially expressed marker genes were defined by intersection analysis of marker genes and GSE86468-differentially expressed genes. Receiver operating characteristic (ROC) curves were utilized to assign representative marker genes with diagnostic values by GSE86468, GSE29226 and external validation GSE29221, and their prospective target compounds were forecasted by PubChem. Besides, the R package clusterProfiler-based functional annotation was designed to unveil the intrinsic mechanisms of the target genes. At last, western blot was used to validate the alternation of CDKN1C and DLK1 expression in primary pancreatic islet cells cultured with or without 30mM glucose.

RESULTS

Three common cell clusters were authenticated in two independent T2DM single-cell sequencing data, covering neurons, epithelial cells, and smooth muscle cells. Functional ensemble analysis disclosed an intimate association of these cell clusters with peptide/insulin secretion and pancreatic development. Pseudo-temporal trajectory analysis indicated that almost all epithelial and smooth muscle cells were of neuron origin. We characterized CDKN1C and DLK1, which were notably upregulated in T2DM samples, with satisfactory availability in recognizing three representative marker genes in non-diabetic and T2DM samples, and they were also robustly interlinked with the clinical characteristics of patients. Western blot also demonstrated that, compared with control group, the expression of CDKN1C and DLK1 were increased in primary pancreatic islet cells cultured with 30 mM glucose for 48 h. Additionally, PubChem projected 11 and 21 potential compounds for CDKN1C and DLK1, respectively.

CONCLUSION

It is desirable that the emergence of the 2 critical genes indicated (CDKN1C and DLK1) could be catalysts for the investigation of the mechanisms of T2DM progression and the exploitation of innovative therapies.

Reversing pancreatic β-cell dedifferentiation in the treatment of type 2 diabetes

The maintenance of glucose homeostasis is fundamental for survival and health. Diabetes develops when glucose homeostasis fails. Type 2 diabetes (T2D) is characterized by insulin resistance and pancreatic β-cell failure. The failure of β-cells to compensate for insulin resistance results in hyperglycemia, which in turn drives altered lipid metabolism and β-cell failure. Thus, insulin secretion by pancreatic β-cells is a primary component of glucose homeostasis. Impaired β-cell function and reduced β-cell mass are found in diabetes. Both features stem from a failure to maintain β-cell identity, which causes β-cells to dedifferentiate into nonfunctional endocrine progenitor-like cells or to trans-differentiate into other endocrine cell types. In this regard, one of the key issues in achieving disease modification is how to reestablish β-cell identity. In this review, we focus on the causes and implications of β-cell failure, as well as its potential reversibility as a T2D treatment.

New Insights and Potential Therapeutic Interventions in Metabolic Diseases

Endocrine homeostasis and metabolic diseases have been the subject of extensive research in recent years. The development of new techniques and insights has led to a deeper understanding of the mechanisms underlying these conditions and opened up new avenues for diagnosis and treatment. In this review, we discussed the rise of metabolic diseases, especially in Western countries, the genetical, psychological, and behavioral basis of metabolic diseases, the role of nutrition and physical activity in the development of metabolic diseases, the role of single-cell transcriptomics, gut microbiota, epigenetics, advanced imaging techniques, and cell-based therapies in metabolic diseases. Finally, practical applications derived from this information are made.

Integrating genetics with single-cell multiomic measurements across disease states identifies mechanisms of beta cell dysfunction in type 2 diabetes

Dysfunctional pancreatic islet beta cells are a hallmark of type 2 diabetes (T2D), but a comprehensive understanding of the underlying mechanisms, including gene dysregulation, is lacking. Here we integrate information from measurements of chromatin accessibility, gene expression and function in single beta cells with genetic association data to nominate disease-causal gene regulatory changes in T2D. Using machine learning on chromatin accessibility data from 34 nondiabetic, pre-T2D and T2D donors, we identify two transcriptionally and functionally distinct beta cell subtypes that undergo an abundance shift during T2D progression. Subtype-defining accessible chromatin is enriched for T2D risk variants, suggesting a causal contribution of subtype identity to T2D. Both beta cell subtypes exhibit activation of a stress-response transcriptional program and functional impairment in T2D, which is probably induced by the T2D-associated metabolic environment. Our findings demonstrate the power of multimodal single-cell measurements combined with machine learning for characterizing mechanisms of complex diseases.

Understanding cell fate acquisition in stem-cell-derived pancreatic islets using single-cell multiome-inferred regulomes

Pancreatic islet cells derived from human pluripotent stem cells hold great promise for modeling and treating diabetes. Differences between stem-cell-derived and primary islets remain, but molecular insights to inform improvements are limited. Here, we acquire single-cell transcriptomes and accessible chromatin profiles during in vitro islet differentiation and pancreas from childhood and adult donors for comparison. We delineate major cell types, define their regulomes, and describe spatiotemporal gene regulatory relationships between transcription factors. CDX2 emerged as a regulator of enterochromaffin-like cells, which we show resemble a transient, previously unrecognized, serotonin-producing pre-β cell population in fetal pancreas, arguing against a proposed non-pancreatic origin. Furthermore, we observe insufficient activation of signal-dependent transcriptional programs during in vitro β cell maturation and identify sex hormones as drivers of β cell proliferation in childhood. Altogether, our analysis provides a comprehensive understanding of cell fate acquisition in stem-cell-derived islets and a framework for manipulating cell identities and maturity.

Epigenetic dosage identifies two major and functionally distinct β cell subtypes

The mechanisms that specify and stabilize cell subtypes remain poorly understood. Here, we identify two major subtypes of pancreatic β cells based on histone mark heterogeneity (βHI and βLO). βHI cells exhibit ∼4-fold higher levels of H3K27me3, distinct chromatin organization and compaction, and a specific transcriptional pattern. βHI and βLO cells also differ in size, morphology, cytosolic and nuclear ultrastructure, epigenomes, cell surface marker expression, and function, and can be FACS separated into CD24+ and CD24- fractions. Functionally, βHI cells have increased mitochondrial mass, activity, and insulin secretion in vivo and ex vivo. Partial loss of function indicates that H3K27me3 dosage regulates βHI/βLO ratio in vivo, suggesting that control of β cell subtype identity and ratio is at least partially uncoupled. Both subtypes are conserved in humans, with βHI cells enriched in humans with type 2 diabetes. Thus, epigenetic dosage is a novel regulator of cell subtype specification and identifies two functionally distinct β cell subtypes.

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.

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.

A beta cell subset with enhanced insulin secretion and glucose metabolism is reduced in type 2 diabetes

The pancreatic islets are composed of discrete hormone-producing cells that orchestrate systemic glucose homeostasis. Here we identify subsets of beta cells using a single-cell transcriptomic approach. One subset of beta cells marked by high CD63 expression is enriched for the expression of mitochondrial metabolism genes and exhibits higher mitochondrial respiration compared with CD63lo beta cells. Human and murine pseudo-islets derived from CD63hi beta cells demonstrate enhanced glucose-stimulated insulin secretion compared with pseudo-islets from CD63lo beta cells. We show that CD63hi beta cells are diminished in mouse models of and in humans with type 2 diabetes. Finally, transplantation of pseudo-islets generated from CD63hi but not CD63lo beta cells into diabetic mice restores glucose homeostasis. These findings suggest that loss of a specific subset of beta cells may lead to diabetes. Strategies to reconstitute or maintain CD63hi beta cells may represent a potential anti-diabetic therapy.

Single-cell infrared phenomics identifies cell heterogeneity of individual pancreatic islets in mouse model

Identifying the islet heterogeneity (cell types and the proportion of each subpopulation) and their relevance to function and disease will lead to fundamental information for the prevention and therapies of diabetes. Here, we introduce a single-cell phenotypic essay on the heterogeneity within individual pancreatic islets by using the combination of synchrotron infrared microspectroscopy and quantitative calculation. In a mouse model, the cellular heterogeneities at both the whole pancreas and single intact islet level were identified. The variation of biochemical phenotypes successfully subdivided islet cells into five main groups and quantitatively determined their proportion. These findings not only demonstrate single-cell infrared phenomics as a value complementary technique and strategy for the description of cellular heterogeneity within the pancreatic islets but also provide a quick, label-free optical platform for investigating phenotypic heterogeneity at the small-organelle level with single cell resolution.

Integrated transcriptomics contrasts fatty acid metabolism with hypoxia response in β-cell subpopulations associated with glycemic control

BACKGROUND

Understanding how heterogeneous β-cell function impacts diabetes is imperative for therapy development. Standard single-cell RNA sequencing analysis illuminates some factors driving heterogeneity, but new strategies are required to enhance information capture.

RESULTS

We integrate pancreatic islet single-cell and bulk RNA sequencing data to identify β-cell subpopulations based on gene expression and characterize genetic networks associated with β-cell function in obese SM/J mice. We identify β-cell subpopulations associated with basal insulin secretion, hypoxia response, cell polarity, and stress response. Network analysis associates fatty acid metabolism and basal insulin secretion with hyperglycemic-obesity, while expression of Pdyn and hypoxia response is associated with normoglycemic-obesity.

CONCLUSIONS

By integrating single-cell and bulk islet transcriptomes, our study explores β-cell heterogeneity and identifies novel subpopulations and genetic pathways associated with β-cell function in obesity.

Reassessing the Abundance of miRNAs in the Human Pancreas and Rodent Cell Lines and Its Implication

miRNAs are critical for pancreas development and function. However, we found that there are discrepancies regarding pancreatic miRNA abundance in published datasets. To obtain a more relevant profile that is closer to the true profile, we profiled small RNAs from human islets cells, acini, and four rodent pancreatic cell lines routinely used in diabetes and pancreatic research using a bias reduction protocol for small RNA sequencing. In contrast to the previous notion that miR-375-3p is the most abundant pancreatic miRNA, we found that miR-148a-3p and miR-7-5p were also abundant in islets. In silico studies using predicted and validated targets of these three miRNAs revealed that they may work cooperatively in endocrine and exocrine cells. Our results also suggest, compared to the most-studied miR-375, that both miR-148a-3p and miR-7-5p may play more critical roles in the human pancreas. Moreover, according to in silico-predicted targets, we found that miR-375-3p had a much broader target spectrum by targeting the coding sequence and the 5' untranslated region, rather than the conventional 3' untranslated region, suggesting additional unexplored roles of miR-375-3p beyond the pancreas. Our study provides a valuable new resource for studying miRNAs in pancreata.

Functional characteristics of hub and wave-initiator cells in β cell networks

Islets of Langerhans operate as multicellular networks in which several hundred β cells work in synchrony to produce secretory pulses of insulin, a hormone crucial for controlling metabolic homeostasis. Their collective rhythmic activity is facilitated by gap junctional coupling and affected by their functional heterogeneity, but the details of this robust and coordinated behavior are still not fully understood. Recent advances in multicellular imaging and optogenetic and photopharmacological strategies, as well as in network science, have led to the discovery of specialized β cell subpopulations that were suggested to critically determine the collective dynamics in the islets. In particular hubs, i.e., β cells with many functional connections, are believed to significantly enhance communication capacities of the intercellular network and facilitate an efficient spreading of intercellular Ca2+ waves, whereas wave-initiator cells trigger intercellular signals in their cohorts. Here, we determined Ca2+ signaling characteristics of these two β cell subpopulations and the relationship between them by means of functional multicellular Ca2+ imaging in mouse pancreatic tissue slices in combination with methods of complex network theory. We constructed network layers based on individual Ca2+ waves to identify wave initiators, and functional correlation-based networks to detect hubs. We found that both cell types exhibit a higher-than-average active time under both physiological and supraphysiological glucose concentrations, but also that they differ significantly in many other functional characteristics. Specifically, Ca2+ oscillations in hubs are more regular, and their role appears to be much more stable over time than for initiator cells. Moreover, in contrast to wave initiators, hubs transmit intercellular signals faster than other cells, which implies a stronger intercellular coupling. Our research indicates that hubs and wave-initiator cell subpopulations are both natural features of healthy pancreatic islets, but their functional roles in principle do not overlap and should thus not be considered equal.

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.

Type 2 diabetes candidate genes, including PAX5, cause impaired insulin secretion in human pancreatic islets

Type 2 diabetes (T2D) is caused by insufficient insulin secretion from pancreatic β cells. To identify candidate genes contributing to T2D pathophysiology, we studied human pancreatic islets from approximately 300 individuals. We found 395 differentially expressed genes (DEGs) in islets from individuals with T2D, including, to our knowledge, novel (OPRD1, PAX5, TET1) and previously identified (CHL1, GLRA1, IAPP) candidates. A third of the identified expression changes in islets may predispose to diabetes, as expression of these genes associated with HbA1c in individuals not previously diagnosed with T2D. Most DEGs were expressed in human β cells, based on single-cell RNA-Seq data. Additionally, DEGs displayed alterations in open chromatin and associated with T2D SNPs. Mouse KO strains demonstrated that the identified T2D-associated candidate genes regulate glucose homeostasis and body composition in vivo. Functional validation showed that mimicking T2D-associated changes for OPRD1, PAX5, and SLC2A2 impaired insulin secretion. Impairments in Pax5-overexpressing β cells were due to severe mitochondrial dysfunction. Finally, we discovered PAX5 as a potential transcriptional regulator of many T2D-associated DEGs in human islets. Overall, we have identified molecular alterations in human pancreatic islets that contribute to β cell dysfunction in T2D pathophysiology.

An integrated map of cell type-specific gene expression in pancreatic islets

Pancreatic islets are comprised of multiple endocrine cell types that produce hormones required for glucose homeostasis, and islet dysfunction is a major factor in the development of type 1 and type 2 diabetes (T1D, T2D). Numerous studies have generated gene expression profiles in individual islet cell types using single cell assays. However, there is no canonical reference of gene expression in islet cell types in both health and disease that is also easily accessible for researchers to access, query, and use in bioinformatics pipelines. Here we present an integrated reference map of islet cell type-specific gene expression from 192,203 cells derived from single cell RNA-seq assays of 65 non-diabetic, T1D autoantibody positive (Aab+), T1D, and T2D donors from the Human Pancreas Analysis Program. We identified 10 endocrine and non-endocrine cell types as well as sub-populations of several cell types, and defined sets of marker genes for each cell type and sub-population. We tested for differential expression within each cell type in T1D Aab+, T1D, and T2D states, and identified 1,701 genes with significant changes in expression in any cell type. Most changes were observed in beta cells in T1D, and, by comparison, there were almost no genes with changes in T1D Aab+. To facilitate user interaction with this reference, we provide the data using several single cell visualization and reference mapping tools as well as open-access analytical pipelines used to create this reference. The results will serve as a valuable resource to investigators studying islet biology and diabetes.

Deficiency of transcription factor Nkx6.1 does not prevent insulin secretion in INS-1E cells

Pancreatic-β-cell-specifying transcription factor Nkx6.1, indispensable for embryonic development of the pancreatic epithelium and commitment to β-cell lineage, directly controls the expression of a glucose transporter (Glut2), pyruvate carboxylase (Pcx), and genes for insulin processing (endoplasmic reticulum oxidoreductase-1β, Ero1lb; zinc transporter-8, Slc30a8). The Nkx6.1 decline in aging diabetic Goto-Kakizaki rats contributes to β-cell trans-differentiation into δ-cells. Elucidating further Nkx6.1 roles, we studied Nkx6.1 ablation in rat INS-1E cells, prepared by CRISPR/Cas9 gene editing from single colonies. INS-1E^Nkx6.1-/- cells exhibited unchanged glucose-stimulated insulin secretion (GSIS), moderately decreased phosphorylating/non-phosphorylating respiration ratios at high glucose; unchanged but delayed ATP-elevation responses to glucose; delayed uptake of fluorescent glucose analog, but slightly improved cytosolic Ca²⁺-oscillations, induced by glucose; despite approximately halved Glut2, Pcx, Ero1lb, and Slc30a8 expression, and reduced nuclear receptors Nr4a1 and Nr4a3. Thus, ATP synthesis was time-compensated, despite the delayed GLUT2-mediated glucose uptake and crippled pyruvate-malate redox shuttle (owing to the PCX-deficiency) in INS-1E^Nkx6.1-/- cells. Nkx6.1 thus controls the expression of genes that are not essential for acute insulin secretion, the function of which can be compensated for. Considerations that Nkx6.1 deficiency is an ultimate determinant of β-cell pathology beyond cell trans-(de-)differentiation or β-cell identity are not supported by our results.

Integration of single-cell multiomic measurements across disease states with genetics identifies mechanisms of beta cell dysfunction in type 2 diabetes

Altered function and gene regulation of pancreatic islet beta cells is a hallmark of type 2 diabetes (T2D), but a comprehensive understanding of mechanisms driving T2D is still missing. Here we integrate information from measurements of chromatin activity, gene expression and function in single beta cells with genetic association data to identify disease-causal gene regulatory changes in T2D. Using machine learning on chromatin accessibility data from 34 non-diabetic, pre-T2D and T2D donors, we robustly identify two transcriptionally and functionally distinct beta cell subtypes that undergo an abundance shift in T2D. Subtype-defining active chromatin is enriched for T2D risk variants, suggesting a causal contribution of subtype identity to T2D. Both subtypes exhibit activation of a stress-response transcriptional program and functional impairment in T2D, which is likely induced by the T2D-associated metabolic environment. Our findings demonstrate the power of multimodal single-cell measurements combined with machine learning for identifying mechanisms of complex diseases.

Pancreatic Islet Cells Response to IFNγ Relies on Their Spatial Location within an Islet

Type 1 diabetes (T1D) is an auto-immune disease characterized by the progressive destruction of insulin-producing pancreatic beta cells. While beta cells are the target of the immune attack, the other islet endocrine cells, namely the alpha and delta cells, can also be affected by the inflammatory milieu. Here, using a flow cytometry-based strategy, we compared the impact of IFNγ, one of the main cytokines involved in T1D, on the three endocrine cell subsets isolated from C57BL/6 mouse islets. RNA-seq analyses revealed that alpha and delta cells exposed in vitro to IFNγ display a transcriptomic profile very similar to that of beta cells, with an increased expression of inflammation key genes such as MHC class I molecules, the CXCL10 chemokine and the programmed death-ligand 1 (PD-L1), three hallmarks of IFNγ signaling. Interestingly, at low IFNγ concentration, we observed two beta cell populations (responders and non-responders) based on PD-L1 protein expression. Our data indicate that this differential sensitivity relies on the location of the cells within the islet rather than on the existence of two different beta cells subsets. The same findings were corroborated by the in vivo analysis of pancreatic islets from the non-obese diabetic mouse model of T1D, showing more intense PD-L1 staining on endocrine cells close to immune infiltrate. Collectively, our work demonstrates that alpha and delta cells are as sensitive as beta cells to IFNγ, and suggests a gradual diffusion of the cytokine into an islet. These observations provide novel insights into the in situ inflammatory processes occurring in T1D progression.

Single-cell RNA-seq transcriptomic landscape of human and mouse islets and pathological alterations of diabetes

Single-cell RNA sequencing has paved the way for delineating the pancreatic islet cell atlas and identifying hallmarks of diabetes. However, pathological alterations of type 2 diabetes (T2D) remain unclear. We isolated pancreatic islets from control and T2D mice for single-cell RNA sequencing (scRNA-seq) and retrieved multiple datasets from the open databases. The complete islet cell landscape and robust marker genes and transcription factors of each endocrine cell type were identified. GLRA1 was restricted to beta cells, and beta cells exhibited obvious heterogeneity. The beta subcluster in the T2D mice remarkably decreased the expression of Slc2a2, G6pc2, Mafa, Nkx6-1, Pdx1, and Ucn3 and had higher unfolded protein response (UPR) scores than in the control mice. Moreover, we developed a Web-based interactive tool, creating new opportunities for the data mining of pancreatic islet scRNA-seq datasets. In conclusion, our work provides a valuable resource for a deeper understanding of the pathological mechanism underlying diabetes.

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Cross-species scRNA-seq reveals the complete cell landscape of the islets of Langerhans

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We identify the robust marker genes and TFs of each endocrine and exocrine cell type

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Pathological alterations of beta cells in type 2 diabetes are explored

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A Web-based interactive tool is established for pancreatic islet scRNA-seq datasets

Sex Differences in the Molecular Programs of Pancreatic Cells Contribute to the Differential Risks of Type 2 Diabetes

Epidemiology studies demonstrate that women are at a significantly lower risk of developing type 2 diabetes (T2D) compared to men. However, the molecular basis of this risk difference is not well understood. In this study, we examined the sex differences in the genetic programs of pancreatic endocrine cells. We combined pancreas perifusion data and single-cell genomic data from our laboratory and from publicly available data sets to investigate multiple axes of the sex differences in the human pancreas at the single-cell type and single-cell level. We systematically compared female and male islet secretion function, gene expression program, and regulatory principles of pancreatic endocrine cells. The perifusion data indicate that female endocrine cells have a higher secretion capacity than male endocrine cells. Single-cell RNA-sequencing analysis suggests that endocrine cells in male controls have molecular signatures that resemble T2D. In addition, we identified genomic elements associated with genome-wide association study T2D loci to have differential accessibility between female and male delta cells. These genomic elements may play a sex-specific causal role in the pathogenesis of T2D. We provide molecular mechanisms that explain the differential risk of T2D between women and men. Knowledge gained from our study will accelerate the development of diagnostics and therapeutics in sex-aware precision medicine for diabetes.

Lessons from single-cell RNA sequencing of human islets

Islet dysfunction is central in type 2 diabetes and full-blown type 2 diabetes develops first when the beta cells lose their ability to secrete adequate amounts of insulin in response to raised plasma glucose. Several mechanisms behind beta cell dysfunction have been put forward but many important questions still remain. Furthermore, our understanding of the contribution of each islet cell type in type 2 diabetes pathophysiology has been limited by technical boundaries. Closing this knowledge gap will lead to a leap forward in our understanding of the islet as an organ and potentially lead to improved treatments. The development of single-cell RNA sequencing (scRNAseq) has led to a breakthrough for characterising the transcriptome of each islet cell type and several important observations on the regulation of cell-type-specific gene expression have been made. When it comes to identifying type 2 diabetes disease mechanisms, the outcome is still limited. Several studies have identified differentially expressed genes, although there is very limited consensus between the studies. As with all new techniques, scRNAseq has limitations; in addition to being extremely expensive, genes expressed at low levels may not be detected, noise may not be appropriately filtered and selection biases for certain cell types are at hand. Furthermore, recent advances suggest that commonly used computational tools may be suboptimal for analysis of scRNAseq data in small-scale studies. Fortunately, development of new computational tools holds promise for harnessing the full potential of scRNAseq data. Here we summarise how scRNAseq has contributed to increasing the understanding of various aspects of islet biology as well as type 2 diabetes disease mechanisms. We also focus on challenges that remain and propose steps to promote the utilisation of the full potential of scRNAseq in this area.

Exfoliated Kidney Cells from Urine for Early Diagnosis and Prognostication of CKD: The Way of the Future?

Chronic kidney disease (CKD) is a global health issue, affecting more than 10% of the worldwide population. The current approach for formal diagnosis and prognostication of CKD typically relies on non-invasive serum and urine biomarkers such as serum creatinine and albuminuria. However, histological evidence of tubulointerstitial fibrosis is the 'gold standard' marker of the likelihood of disease progression. The development of novel biomedical technologies to evaluate exfoliated kidney cells from urine for non-invasive diagnosis and prognostication of CKD presents opportunities to avoid kidney biopsy for the purpose of prognostication. Efforts to apply these technologies more widely in clinical practice are encouraged, given their potential as a cost-effective approach, and no risk of post-biopsy complications such as bleeding, pain and hospitalization. The identification of biomarkers in exfoliated kidney cells from urine via western blotting, enzyme-linked immunosorbent assay (ELISA), immunofluorescence techniques, measurement of cell and protein-specific messenger ribonucleic acid (mRNA)/micro-RNA and other techniques have been reported. Recent innovations such as multispectral autofluorescence imaging and single-cell RNA sequencing (scRNA-seq) have brought additional dimensions to the clinical application of exfoliated kidney cells from urine. In this review, we discuss the current evidence regarding the utility of exfoliated proximal tubule cells (PTC), podocytes, mesangial cells, extracellular vesicles and stem/progenitor cells as surrogate markers for the early diagnosis and prognostication of CKD. Future directions for development within this research area are also identified.

Overview of Transcriptomic Research on Type 2 Diabetes: Challenges and Perspectives

Type 2 diabetes (T2D) is a common chronic disease whose etiology is known to have a strong genetic component. Standard genetic approaches, although allowing for the detection of a number of gene variants associated with the disease as well as differentially expressed genes, cannot fully explain the hereditary factor in T2D. The explosive growth in the genomic sequencing technologies over the last decades provided an exceptional impetus for transcriptomic studies and new approaches to gene expression measurement, such as RNA-sequencing (RNA-seq) and single-cell technologies. The transcriptomic analysis has the potential to find new biomarkers to identify risk groups for developing T2D and its microvascular and macrovascular complications, which will significantly affect the strategies for early diagnosis, treatment, and preventing the development of complications. In this article, we focused on transcriptomic studies conducted using expression arrays, RNA-seq, and single-cell sequencing to highlight recent findings related to T2D and challenges associated with transcriptome experiments.

Generation of human islet cell type-specific identity genesets

Generation of surrogate cells with stable functional identities is crucial for developing cell-based therapies. Efforts to produce insulin-secreting replacement cells to treat diabetes require reliable tools to assess islet cellular identity. Here, we conduct a thorough single-cell transcriptomics meta-analysis to identify robustly expressed markers used to build genesets describing the identity of human α-, β-, γ- and δ-cells. These genesets define islet cellular identities better than previously published genesets. We show their efficacy to outline cell identity changes and unravel some of their underlying genetic mechanisms, whether during embryonic pancreas development or in experimental setups aiming at developing glucose-responsive insulin-secreting cells, such as pluripotent stem-cell differentiation or in adult islet cell reprogramming protocols. These islet cell type-specific genesets represent valuable tools that accurately benchmark gain and loss in islet cell identity traits.

Intermittent protein restriction protects islet β cells and improves glucose homeostasis in diabetic mice

Diabetes is caused by the interplay between genetics and environmental factors, tightly linked to lifestyle and dietary patterns. In this study, we explored the effectiveness of intermittent protein restriction (IPR) in diabetes control. IPR drastically reduced hyperglycemia in both streptozotocin-treated and leptin receptor-deficient db/db mouse models. IPR improved the number, proliferation, and function of β cells in pancreatic islets. IPR reduced glucose production in the liver and elevated insulin signaling in the skeletal muscle. IPR elevated serum level of FGF21, and deletion of the Fgf21 gene in the liver abrogated the hypoglycemic effect of IPR without affecting β cells. IPR caused less lipid accumulation and damage in the liver than that caused by continuous protein restriction in streptozotocin-treated mice. Single-cell RNA sequencing using mouse islets revealed that IPR reversed diabetes-associated β cell reduction and immune cell accumulation. As IPR is not based on calorie restriction and is highly effective in glycemic control and β cell protection, it has promising translational potential in the future.

It's What and When You Eat: An Overview of Transcriptional and Epigenetic Responses to Dietary Perturbations in Pancreatic Islets

Our ever-changing modern environment is a significant contributor to the increased prevalence of many chronic diseases, and particularly, type 2 diabetes mellitus (T2DM). Although the modern era has ushered in numerous changes to our daily living conditions, changes in "what" and "when" we eat appear to disproportionately fuel the rise of T2DM. The pancreatic islet is a key biological controller of an organism's glucose homeostasis and thus plays an outsized role to coordinate the response to environmental factors to preserve euglycemia through a delicate balance of endocrine outputs. Both successful and failed adaptation to dynamic environmental stimuli has been postulated to occur due to changes in the transcriptional and epigenetic regulation of pathways associated with islet secretory function and survival. Therefore, in this review we examined and evaluated the current evidence elucidating the key epigenetic mechanisms and transcriptional programs underlying the islet's coordinated response to the interaction between the timing and the composition of dietary nutrients common to modern lifestyles. With the explosion of next generation sequencing, along with the development of novel informatic and -omic approaches, future work will continue to unravel the environmental-epigenetic relationship in islet biology with the goal of identifying transcriptional and epigenetic targets associated with islet perturbations in T2DM.

Physically interacting beta-delta pairs in the regenerating pancreas revealed by single-cell sequencing

Objectives

Until recently, communication between neighboring cells in islets of Langerhans was overlooked by genomic technologies, which require rigorous tissue dissociation into single cells.

Methods

We utilize sorting of physically interacting cells (PICs) with single-cell RNA-sequencing to systematically map cellular interactions in the endocrine pancreas after pancreatectomy.

Results

The pancreas cellular landscape features pancreatectomy associated heterogeneity of beta-cells, including an interaction-specific program between paired beta and delta-cells.

Conclusions

Our analysis suggests that the particular cluster of beta-cells that pairs with delta-cells benefits from stress protection, implying that the interaction between beta- and delta-cells might safeguard against pancreatectomy associated challenges. The work encourages testing the potential relevance of physically-interacting beta-delta-cells also in diabetes mellitus.

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Single-cell RNA-sequencing systematically maps physically interacting endocrine cells in the pancreas.

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The landscape of pancreatectomy associated beta-cell heterogeneity is mapped in a single cell resolution.

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Interaction-specific beta - delta cellular program safeguards beta cells against pancreatectomy-associated stress.

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Physically interacting beta delta pairs were discovered in an injury model and may also be relevant in diabetes.

Mitogen Synergy: An Emerging Route to Boosting Human Beta Cell Proliferation

Decreased number and function of beta cells are a key aspect of diabetes mellitus (diabetes), a disease that remains an onerous global health problem. Means of restoring beta cell mass are urgently being sought as a potential cure for diabetes. Several strategies, such as de novo beta cell derivation via pluripotent stem cell differentiation or mature somatic cell transdifferentiation, have yielded promising results. Beta cell expansion is another promising strategy, rendered challenging by the very low proliferative capacity of beta cells. Many effective mitogens have been identified in rodents, but the vast majority do not have similar mitogenic effects in human beta cells. Extensive research has led to the identification of several human beta cell mitogens, but their efficacy and specificity remain insufficient. An approach based on the simultaneous application of several mitogens has recently emerged and can yield human beta cell proliferation rates of up to 8%. Here, we discuss recent advances in restoration of the beta cell population, focusing on mitogen synergy, and the contribution of RNA-sequencing (RNA-seq) to accelerating the elucidation of signaling pathways in proliferating beta cells and the discovery of novel mitogens. Together, these approaches have taken beta cell research up a level, bringing us closer to a cure for diabetes.

Discoveries in Pancreatic Physiology and Disease Biology Using Single-Cell RNA Sequencing

Transcriptome analysis is used to study gene expression in human tissues. It can promote the discovery of new therapeutic targets for related diseases by characterizing the endocrine function of pancreatic physiology and pathology, as well as the gene expression of pancreatic tumors. Compared to whole-tissue RNA sequencing, single-cell RNA sequencing (scRNA-seq) can detect transcriptional activity within a single cell. The scRNA-seq had an invaluable contribution to discovering previously unknown cell subtypes in normal and diseased pancreases, studying the functional role of rare islet cells, and studying various types of cells in diabetes as well as cancer. Here, we review the recent in vitro and in vivo advances in understanding the pancreatic physiology and pathology associated with single-cell sequencing technology, which may provide new insights into treatment strategy optimization for diabetes and pancreatic cancer.

Intestinal Gpr17 deficiency improves glucose metabolism by promoting GLP-1 secretion

G protein-coupled receptors (GPCRs) in intestinal enteroendocrine cells (EECs) respond to nutritional, neural, and microbial cues and modulate the release of gut hormones. Here we show that Gpr17, an orphan GPCR, is co-expressed in glucagon-like peptide-1 (GLP-1)-expressing EECs in human and rodent intestinal epithelium. Acute genetic ablation of Gpr17 in intestinal epithelium improves glucose tolerance and glucose-stimulated insulin secretion (GSIS). Importantly, inducible knockout (iKO) mice and Gpr17 null intestinal organoids respond to glucose or lipid ingestion with increased secretion of GLP-1, but not the other incretin glucose-dependent insulinotropic polypeptide (GIP). In an in vitro EEC model, overexpression or agonism of Gpr17 reduces voltage-gated calcium currents and decreases cyclic AMP (cAMP) production, and these are two critical factors regulating GLP-1 secretion. Together, our work shows that intestinal Gpr17 signaling functions as an inhibitory pathway for GLP-1 secretion in EECs, suggesting intestinal GPR17 is a potential target for diabetes and obesity intervention.

Yan et al. locate GPR17 expression in the enteroendocrine cells of human and rodent intestinal epithelium. They find that GPR17 signaling inhibits intracellular rise of cAMP and calcium and that loss of intestinal Gpr17 in rodents leads to better glucose tolerance via increased hormone secretion in response to nutrient ingestion.

BACH2 inhibition reverses β cell failure in type 2 diabetes models

Type 2 diabetes (T2D) is associated with defective insulin secretion and reduced β cell mass. Available treatments provide a temporary reprieve, but secondary failure rates are high, making insulin supplementation necessary. Reversibility of β cell failure is a key translational question. Here, we reverse engineered and interrogated pancreatic islet-specific regulatory networks to discover T2D-specific subpopulations characterized by metabolic inflexibility and endocrine progenitor/stem cell features. Single-cell gain- and loss-of-function and glucose-induced Ca2+ flux analyses of top candidate master regulatory (MR) proteins in islet cells validated transcription factor BACH2 and associated epigenetic effectors as key drivers of T2D cell states. BACH2 knockout in T2D islets reversed cellular features of the disease, restoring a nondiabetic phenotype. BACH2-immunoreactive islet cells increased approximately 4-fold in diabetic patients, confirming the algorithmic prediction of clinically relevant subpopulations. Treatment with a BACH inhibitor lowered glycemia and increased plasma insulin levels in diabetic mice, and restored insulin secretion in diabetic mice and human islets. The findings suggest that T2D-specific populations of failing β cells can be reversed and indicate pathways for pharmacological intervention, including via BACH2 inhibition.

Deciphering regulatory protein activity in human pancreatic islets via reverse engineering of single-cell sequencing data

The loss of functional β cell mass contributes to development and progression of type 2 diabetes (T2D). However, the molecular mechanisms differentiating islet dysfunction in T2D from nondiabetic states remain elusive. In this issue of the JCI, Son et al. applied reverse engineering to obtain the activity of gene expression regulatory proteins from single-cell RNA sequencing data of nondiabetic and T2D human islets. The authors identify unique patterns of regulatory protein activities associated with T2D. Furthermore, BACH2 emerged as a potential transcription factor that drives activation of T2D-associated regulatory proteins in human islets.