Single-Cell RNAseq Reveals That Pancreatic β-Cells From Very Old Male Mice Have a Young Gene Signature

Exploring the heterogeneous targets of metabolic aging at single-cell resolution

Our limited understanding of metabolic aging poses major challenges to comprehending the diverse cellular alterations that contribute to age-related decline, and to devising targeted interventions. This review provides insights into the heterogeneous nature of cellular metabolism during aging and its response to interventions, with a specific focus on cellular heterogeneity and its implications. By synthesizing recent findings using single-cell approaches, we explored the vulnerabilities of distinct cell types and key metabolic pathways. Delving into the cell type-specific alterations underlying the efficacy of systemic interventions, we also discuss the complexity of integrating single-cell data and advocate for leveraging computational tools and artificial intelligence to harness the full potential of these data, develop effective strategies against metabolic aging, and promote healthy aging.

Development, regeneration, and physiological expansion of functional β-cells: Cellular sources and regulators

Pancreatic regeneration is a complex process observed in both normal and pathological conditions. The aim of this review is to provide a comprehensive understanding of the emergence of a functionally active population of insulin-secreting β-cells in the adult pancreas. The renewal of β-cells is governed by a multifaceted interaction between cellular sources of genetic and epigenetic factors. Understanding the development and heterogeneity of β-cell populations is crucial for functional β-cell regeneration. The functional mass of pancreatic β-cells increases in situations such as pregnancy and obesity. However, the specific markers of mature β-cell populations and postnatal pancreatic progenitors capable of increasing self-reproduction in these conditions remain to be elucidated. The capacity to regenerate the β-cell population through various pathways, including the proliferation of pre-existing β-cells, β-cell neogenesis, differentiation of β-cells from a population of progenitor cells, and transdifferentiation of non-β-cells into β-cells, reveals crucial molecular mechanisms for identifying cellular sources and inducers of functional cell renewal. This provides an opportunity to identify specific cellular sources and mechanisms of regeneration, which could have clinical applications in treating various pathologies, including in vitro cell-based technologies, and deepen our understanding of regeneration in different physiological conditions.

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.

MulCNN: An efficient and accurate deep learning method based on gene embedding for cell type identification in single-cell RNA-seq data

Advancements in single-cell sequencing research have revolutionized our understanding of cellular heterogeneity and functional diversity through the analysis of single-cell transcriptomes and genomes. A crucial step in single-cell RNA sequencing (scRNA-seq) analysis is identifying cell types. However, scRNA-seq data are often high dimensional and sparse, and manual cell type identification can be time-consuming, subjective, and lack reproducibility. Consequently, analyzing scRNA-seq data remains a computational challenge. With the increasing availability of well-annotated scRNA-seq datasets, advanced methods are emerging to aid in cell type identification by leveraging this information. Deep learning neural networks have great potential for analyzing single-cell data. This paper proposes MulCNN, a multi-level convolutional neural network that uses a unique cell type-specific gene expression feature extraction method. This method extracts critical features through multi-scale convolution while filtering noise. Extensive testing using datasets from various species and comparisons with popular classification methods show that MulCNN has outstanding performance and offers a new and scalable direction for scRNA-seq analysis.

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.

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.

The pancreatic β-cell in ageing: Implications in age-related diabetes

The prevalence of type 2 diabetes (T2D) and impaired glucose tolerance (IGT) increases with ageing. T2D generally results from progressive impairment of the pancreatic islets to adapt β-cell mass and function in the setting of insulin resistance and increased insulin demand. Several studies have shown an age-related decline in peripheral insulin sensitivity. However, a precise understanding of the pancreatic β-cell response in ageing is still lacking. In this review, we summarize the age-related alterations, adaptations and/or failures of β-cells at the molecular, morphological and functional levels in mouse and human. Age-associated alterations include processes such as β-cell proliferation, apoptosis and cell identity that can influence β-cell mass. Age-related changes also affect β-cell function at distinct steps including electrical activity, Ca²⁺ signaling and insulin secretion, among others. We will consider the potential impact of these alterations and those mediated by senescence pathways on β-cells and their implications in age-related T2D. Finally, given the great diversity of results in the field of β-cell ageing, we will discuss the sources of this heterogeneity. A better understanding of β-cell biology during ageing, particularly at older ages, will improve our insight into the contribution of β-cells to age-associated T2D and may boost new therapeutic strategies.

The effects of aging on male mouse pancreatic β-cell function involve multiple events in the regulation of secretion: influence of insulin sensitivity

Aging is associated with a decline in peripheral insulin sensitivity and an increased risk of impaired glucose tolerance and type 2 diabetes. During conditions of reduced insulin sensitivity, pancreatic β-cells undergo adaptive responses to increase insulin secretion and maintain euglycemia. However, the existence and nature of β-cell adaptations and/or alterations during aging are still a matter of debate. In this study, we investigated the effects of aging on β-cell function from control (3-month-old) and aged (20-month-old) mice. Aged animals were further categorized in two groups: high insulin sensitive (aged-HIS) and low insulin sensitive (aged-LIS). Aged-LIS mice were hyperinsulinemic, glucose intolerant and displayed impaired glucose-stimulated insulin and C-peptide secretion, whereas aged-HIS animals showed characteristics in glucose homeostasis similar to controls. In isolated β-cells, we observed that glucose-induced inhibition of KATP channel activity was reduced with aging, particularly in the aged-LIS group. Glucose-induced islet NAD(P)H production was decreased in aged mice, suggesting impaired mitochondrial function. In contrast, voltage-gated Ca 2+ currents were higher in aged-LIS β-cells, and pancreatic islets of both aged groups displayed increased glucose-induced Ca 2+ signaling and augmented insulin secretion compared with controls. Morphological analysis of pancreas sections also revealed augmented β-cell mass with aging, especially in the aged-LIS group, as well as ultrastructural β-cell changes. Altogether, these findings indicate that aged mouse β-cells compensate for the aging-induced alterations in the stimulus-secretion coupling, particularly by adjusting their Ca 2+ influx to ensure insulin secretion. These results also suggest that decreased peripheral insulin sensitivity exacerbates the effects of aging on β-cells.

Pancreatic β-cell heterogeneity in health and diabetes: classes, sources, and subtypes

Pancreatic β-cells perform glucose-stimulated insulin secretion, a process at the center of type 2 diabetes etiology. Efforts to understand how β-cells behave in healthy and stressful conditions have revealed a wide degree of morphological, functional, and transcriptional heterogeneity. Sources of heterogeneity include β-cell topography, developmental origin, maturation state, and stress response. Advances in sequencing and imaging technologies have led to the identification of β-cell subtypes, which play distinct roles in the islet niche. This review examines β-cell heterogeneity from morphological, functional, and transcriptional perspectives, and considers the relevance of topography, maturation, development, and stress response. It also discusses how these factors have been used to identify β-cell subtypes, and how heterogeneity is impacted by diabetes. We examine open questions in the field and discuss recent technological innovations that could advance understanding of β-cell heterogeneity in health and disease.

Insights from single cell studies of human pancreatic islets and stem cell-derived islet cells to guide functional beta cell maturation in vitro

There is now a sizeable number of single cell transcriptomics studies performed on human and rodent pancreatic islets that have shed light on the unique gene signatures and level of heterogeneity within each individual islet cell type. Following closely from these studies, there is also rapidly-growing activity on characterizing islet-like cells derived from in vitro differentiation of human pluripotent stem cells (hPSCs) at the single cell level. The overall consensus across the studies so far suggests that the first few stages of differentiation are largely uniform, whereas during pancreatic endocrine commitment, cell trajectories start to diverge, resulting in multiple end-stage pancreatic cells that include progenitor-like, endocrine and non-endocrine cells. Comprehensive transcriptional profiling is important for understanding how and why islet cells, especially the insulin-secreting beta cells, exist in subpopulations that differ in maturity, proliferation rate, sensitivity to stress, and insulin secretion function. For hPSC-derived beta cells to be used confidently for cell therapy, optimal differentiation and thorough characterization is required. The key questions to address are-What is the trajectory of differentiation? Is heterogeneity a natural occurrence or is it a consequence of imperfect differentiation protocols? Can lessons be drawn from the extensive single cell transcriptomic data to help guide maturation of beta cells in vitro? This book chapter seeks to address some of these questions, and facilitate ongoing efforts in improving the beta cell differentiation pipeline or enriching for desired beta cell populations following differentiation, to make way for better mechanistic studies and future clinical translation.

Single-cell RNA sequencing for engineering and studying human islets

The islets of Langerhans are complex tissues composed of several cell types that secrete hormones. Loss or dysfunction of the insulin-producing β cells leads to dysregulation of blood glucose levels, resulting in diabetes. A major goal in cellular engineering has been to generate β cells from stem cells for use in cell-based therapies. However, the presence of other cell types within these islets can mask important details about β cells when using population-level assays. Single-cell RNA sequencing have enabled transcriptional assessment of individual cells within mixed populations. These technologies allow for accurate assessment of specific cell types and subtypes of β cells. Studies investigating different stages of β cell maturity have led to several insights into understanding islet development and diabetes pathology. Here, we highlight the key findings from the use of single-cell RNA sequencing on stem cell-derived and primary human islet cells found in different maturation and diabetic states.

Application of Single-Cell RNA Sequencing in Pancreatic Cancer and the Endocrine Pancreas

The pancreas is a complex organ composed of an endocrine (pancreatic islets) and an exocrine portion. This mixed cell population has resulted in an implacable barrier to exploring the detailed mechanism and function of each cell type in previous investigative approaches. In recent years, single-cell RNA sequencing (scRNA-seq) technologies have provided in-depth analysis of cell heterogeneity in the pancreas and in pancreatic cancer. It is especially effective in cell-type-specific molecule identification and detection of interactions between cancer cells and the stromal microenvironment. To date, numerous reports have described the application of scRNA-seq in studies of pancreatic islets and pancreatic cancer. The aim of this paper is to review recent advances of pancreatic transcriptomics and pancreatic cancer using scRNA-seq strategies.

Single-cell RNA-seq with spike-in cells enables accurate quantification of cell-specific drug effects in pancreatic islets

BACKGROUND

Single-cell RNA-seq (scRNA-seq) is emerging as a powerful tool to dissect cell-specific effects of drug treatment in complex tissues. This application requires high levels of precision, robustness, and quantitative accuracy-beyond those achievable with existing methods for mainly qualitative single-cell analysis. Here, we establish the use of standardized reference cells as spike-in controls for accurate and robust dissection of single-cell drug responses.

RESULTS

We find that contamination by cell-free RNA can constitute up to 20% of reads in human primary tissue samples, and we show that the ensuing biases can be removed effectively using a novel bioinformatics algorithm. Applying our method to both human and mouse pancreatic islets treated ex vivo, we obtain an accurate and quantitative assessment of cell-specific drug effects on the transcriptome. We observe that FOXO inhibition induces dedifferentiation of both alpha and beta cells, while artemether treatment upregulates insulin and other beta cell marker genes in a subset of alpha cells. In beta cells, dedifferentiation and insulin repression upon artemether treatment occurs predominantly in mouse but not in human samples.

CONCLUSIONS

This new method for quantitative, error-correcting, scRNA-seq data normalization using spike-in reference cells helps clarify complex cell-specific effects of pharmacological perturbations with single-cell resolution and high quantitative accuracy.

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

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

Klf6 protects β-cells against insulin resistance-induced dedifferentiation

OBJECTIVES

In the pathogenesis of type 2 diabetes, development of insulin resistance triggers an increase in pancreatic β-cell insulin secretion capacity and β-cell number. Failure of this compensatory mechanism is caused by a dedifferentiation of β-cells, which leads to insufficient insulin secretion and diabetic hyperglycemia. The β-cell factors that normally protect against dedifferentiation remain poorly defined. Here, through a systems biology approach, we identify the transcription factor Klf6 as a regulator of β-cell adaptation to metabolic stress.

METHODS

We used a β-cell specific Klf6 knockout mouse model to investigate whether Klf6 may be a potential regulator of β-cell adaptation to a metabolic stress.

RESULTS

We show that inactivation of Klf6 in β-cells blunts their proliferation induced by the insulin resistance of pregnancy, high-fat high-sucrose feeding, and insulin receptor antagonism. Transcriptomic analysis showed that Klf6 controls the expression of β-cell proliferation genes and, in the presence of insulin resistance, it prevents the down-expression of genes controlling mature β-cell identity and the induction of disallowed genes that impair insulin secretion. Its expression also limits the transdifferentiation of β-cells into α-cells.

CONCLUSION

Our study identifies a new transcription factor that protects β-cells against dedifferentiation, and which may be targeted to prevent diabetes development.

Targeted Elimination of Senescent Beta Cells Prevents Type 1 Diabetes

Type 1 diabetes (T1D) is an organ-specific autoimmune disease characterized by hyperglycemia due to progressive loss of pancreatic beta cells. Immune-mediated beta cell destruction drives the disease, but whether beta cells actively participate in the pathogenesis remains unclear. Here, we show that during the natural history of T1D in humans and the non-obese diabetic (NOD) mouse model, a subset of beta cells acquires a senescence-associated secretory phenotype (SASP). Senescent beta cells upregulated pro-survival mediator Bcl-2, and treatment of NOD mice with Bcl-2 inhibitors selectively eliminated these cells without altering the abundance of the immune cell types involved in the disease. Significantly, elimination of senescent beta cells halted immune-mediated beta cell destruction and was sufficient to prevent diabetes. Our findings demonstrate that beta cell senescence is a significant component of the pathogenesis of T1D and indicate that clearance of senescent beta cells could be a new therapeutic approach for T1D.

Multi-level remodeling of transcriptional landscapes in aging and longevity

In multi-cellular organisms, the control of gene expression is key not only for development, but also for adult cellular homeostasis, and gene expression has been observed to be deregulated with aging. In this review, we discuss the current knowledge on the transcriptional alterations that have been described to occur with age in metazoans. First, we discuss age-related transcriptional changes in protein-coding genes, the expected functional impact of such changes, and how known pro-longevity interventions impact these changes. Second, we discuss the changes and impact of emerging aspects of transcription in aging, including age-related changes in splicing, lncRNAs and circRNAs. Third, we discuss the changes and potential impact of transcription of transposable elements with aging. Fourth, we highlight small ncRNAs and their potential impact on the regulation of aging phenotypes. Understanding the aging transcriptome will be key to identify important regulatory targets, and ultimately slow-down or reverse aging and extend healthy lifespan in humans.

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

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

Multi-level remodeling of transcriptional landscapes in aging and longevity

In multi-cellular organisms, the control of gene expression is key not only for development, but also for adult cellular homeostasis, and gene expression has been observed to be deregulated with aging. In this review, we discuss the current knowledge on the transcriptional alterations that have been described to occur with age in metazoans. First, we discuss age-related transcriptional changes in protein-coding genes, the expected functional impact of such changes, and how known pro-longevity interventions impact these changes. Second, we discuss the changes and impact of emerging aspects of transcription in aging, including age-related changes in splicing, lncRNAs and circRNAs. Third, we discuss the changes and potential impact of transcription of transposable elements with aging. Fourth, we highlight small ncRNAs and their potential impact on the regulation of aging phenotypes. Understanding the aging transcriptome will be key to identify important regulatory targets, and ultimately slow-down or reverse aging and extend healthy lifespan in humans. [BMB Reports 2019; 52(1): 86-108].

Transcriptional Signatures of Aging

Genome-wide studies of aging have identified subsets of genes that show age-related changes in expression. Although the types of genes that are age regulated vary among different tissues and organisms, some patterns emerge from these large data sets. First, aging is associated with a broad induction of stress response pathways, although the specific genes and pathways involved differ depending on cell type and species. In contrast, a wide variety of functional classes of genes are downregulated with age, often including tissue-specific genes. Although the upregulation of age-regulated genes is likely to be governed by stress-responsive transcription factors, questions remain as to why particular genes are susceptible to age-related transcriptional decline. Here, we discuss recent findings showing that splicing is misregulated with age. While defects in splicing could lead to changes in protein isoform levels, they could also impact gene expression through nonsense-mediated decay of intron-retained transcripts. The discovery that splicing is misregulated with age suggests that other aspects of gene expression, such as transcription elongation, termination, and polyadenylation, must also be considered as potential mechanisms for age-related changes in transcript levels. Moreover, the considerable variation between genome-wide aging expression studies indicates that there is a critical need to analyze the transcriptional signatures of aging in single-cell types rather than whole tissues. Since age-associated decreases in gene expression could contribute to a progressive decline in cellular function, understanding the mechanisms that determine the aging transcriptome provides a potential target to extend healthy cellular lifespan.

Interrogating islets in health and disease with single-cell technologies

BACKGROUND

Blood glucose levels are tightly controlled by the coordinated actions of hormone-producing endocrine cells that reside in pancreatic islets. Islet cell malfunction underlies diabetes development and progression. Due to the cellular heterogeneity within islets, it has been challenging to uncover how specific islet cells contribute to glucose homeostasis and diabetes pathogenesis. Recent advances in single-cell technologies and computational methods have opened up new avenues to resolve islet heterogeneity and study islet cell states in health and disease.

SCOPE OF REVIEW

In the past year, a multitude of studies have been published that used single-cell approaches to interrogate the transcriptome and proteome of the different islet cell types. Here, we summarize the conclusions of these studies, as well as discuss the technologies used and the challenges faced with computational analysis of single-cell data from islet studies.

MAJOR CONCLUSIONS

By analyzing single islet cells from rodents and humans at different ages and disease states, the studies reviewed here have provided new insight into endocrine cell function and facilitated a high resolution molecular characterization of poorly understood processes, including regeneration, maturation, and diabetes pathogenesis. Gene expression programs and pathways identified in these studies pave the way for the discovery of new targets and approaches to prevent, monitor, and treat diabetes.

Pseudotemporal Ordering of Single Cells Reveals Metabolic Control of Postnatal β Cell Proliferation

Pancreatic β cell mass for appropriate blood glucose control is established during early postnatal life. β cell proliferative capacity declines postnatally, but the extrinsic cues and intracellular signals that cause this decline remain unknown. To obtain a high-resolution map of β cell transcriptome dynamics after birth, we generated single-cell RNA-seq data of β cells from multiple postnatal time points and ordered cells based on transcriptional similarity using a new analytical tool. This analysis captured signatures of immature, proliferative β cells and established high expression of amino acid metabolic, mitochondrial, and Srf/Jun/Fos transcription factor genes as their hallmark feature. Experimental validation revealed high metabolic activity in immature β cells and a role for reactive oxygen species and Srf/Jun/Fos transcription factors in driving postnatal β cell proliferation and mass expansion. Our work provides the first high-resolution molecular characterization of state changes in postnatal β cells and paves the way for the identification of novel therapeutic targets to stimulate β cell regeneration.

Is a β cell a β cell?

PURPOSE OF REVIEW

This report examines recent publications identifying phenotypic and functional heterogeneity among pancreatic β cells and investigating their potential roles in normal and abnormal islet function. The development of new methods and tools for the study of individual islet cells has produced a surge of interest in this topic.

RECENT FINDINGS

Studies of β cell maturation and pregnancy-induced proliferation have identified changes in serotonin and transcription factors SIX2/3 expression as markers of temporal heterogeneity. Structural and functional heterogeneity in the form of functionally distinct 'hub' and 'follower' β cells was found in mouse islets. Heterogeneous expression of Fltp (in mouse β cells) and ST8SIA1 and CD9 (in human β cells) were associated with distinct functional potential. Several impressive reports describing the transcriptomes of individual β cells were also published in recent months. Some of these reveal previously unknown β cell subpopulations.

SUMMARY

A wealth of information on functional and phenotypic heterogeneity has been collected recently, including the transcriptomes of individual β cells and the identities of functionally distinct β cell subpopulations. Several studies suggest the existence of two broad categories: a more proliferative but less functional and a less proliferative but more functional β cell type. The identification of functionally distinct subpopulations and their association with type 2 diabetes underlines the potential clinical importance of these investigations.

Heterogeneity of the Pancreatic Beta Cell

The pancreatic beta cell functions as a key regulator of blood glucose levels by integrating a variety of signals in response to changing metabolic demands. Variations in beta cell identity that translate into functionally different subpopulations represent an interesting mechanism to allow beta cells to efficiently respond to diverse physiological and pathophysiological conditions. Recently, there is emerging evidence that morphological and functional differences between beta cells exist. Furthermore, the ability of novel single cell technologies to characterize the molecular identity of individual beta cells has created a new era in the beta cell field. These studies are providing important novel information about the origin of beta cell heterogeneity, the type and proportions of the different beta cell subpopulations, as well as their intrinsic properties. Furthermore, characterization of different beta cell subpopulations that could variably offer protection from or drive progression of diabetes has important clinical implications in diabetes prevention, beta cell regeneration and stem cell treatments. In this review, we will assess the evidence that supports the existence of heterogeneous populations of beta cells and the factors that could influence their formation. We will also address novel studies using islet single cell analysis that have provided important information toward understanding beta cell heterogeneity and discuss the caveats that may be associated with these new technologies.

Searching for the β-Cell Fountain of Youth

Aging affects every species and tissue but not in equal ways. Human pancreatic β-cells lose their ability to replicate, regenerate, and secrete insulin as one gets older. This natural process increases risk of developing diabetes as you age and is a concern for donor islets and stem cells obtained from older subjects destined for transplantation or emerging regenerative therapies. Using fluidic sorting and RNA sequencing on single cells, Xin et al describe a transcriptional signature of mouse β-cell aging between adulthood and a very old age. Amazingly, expression levels of more than 99% of genes do not change over time, despite the long lifespan of this specialized tissue. They identify a novel set of transcription factors that can explain decreases in cell survival and proliferation genes and potentially drive age-associated decline in regenerative capacity. Yet somehow, mouse β-cells maintain pathways regulating glucose metabolism and β-cell function despite experiencing challenges commonly associated with old age, including increased weight and fat mass. The authors conclude that β-cells of old mice are overall strikingly similar to young β-cells, implying that mechanisms may exist to resist aging and maintain their 'youth'. These new discoveries have interesting implications for efforts to preserve or improve function of human β-cells, providing potential clues toward prolonging the life and health of donor tissues or islets of people with diabetes.