MetaboAnalyst 6.0: towards a unified platform for metabolomics data processing, analysis and interpretation.

We introduce MetaboAnalyst version 6.0 as a unified platform for processing, analyzing, and interpreting data from targeted as well as untargeted metabolomics studies using liquid chromatography - mass spectrometry (LC-MS). The two main objectives in developing version 6.0 are to support tandem MS (MS2) data processing and annotation, as well as to support the analysis of data from exposomics studies and related experiments. Key features of MetaboAnalyst 6.0 include: (i) a significantly enhanced Spectra Processing module with support for MS2 data and the asari algorithm; (ii) a MS2 Peak Annotation module based on comprehensive MS2 reference databases with fragment-level annotation; (iii) a new Statistical Analysis module dedicated for handling complex study design with multiple factors or phenotypic descriptors; (iv) a Causal Analysis module for estimating metabolite - phenotype causal relations based on two-sample Mendelian randomization, and (v) a Dose-Response Analysis module for benchmark dose calculations. In addition, we have also improved MetaboAnalyst's visualization functions, updated its compound database and metabolite sets, and significantly expanded its pathway analysis support to around 130 species. MetaboAnalyst 6.0 is freely available at https://www.metaboanalyst.ca.

CK2 activity is crucial for proper glucagon expression.

AIMS/HYPOTHESIS: Protein kinase CK2 acts as a negative regulator of insulin expression in pancreatic beta cells. This action is mainly mediated by phosphorylation of the transcription factor pancreatic and duodenal homeobox protein 1 (PDX1). In pancreatic alpha cells, PDX1 acts in a reciprocal fashion on glucagon (GCG) expression. Therefore, we hypothesised that CK2 might positively regulate GCG expression in pancreatic alpha cells. METHODS: We suppressed CK2 kinase activity in αTC1 cells by two pharmacological inhibitors and by the CRISPR/Cas9 technique. Subsequently, we analysed GCG expression and secretion by real-time quantitative RT-PCR, western blot, luciferase assay, ELISA and DNA pull-down assays. We additionally studied paracrine effects on GCG secretion in pseudoislets, isolated murine islets and human islets. In vivo, we examined the effect of CK2 inhibition on blood glucose levels by systemic and alpha cell-specific CK2 inhibition. RESULTS: We found that CK2 downregulation reduces GCG secretion in the murine alpha cell line αTC1 (e.g. from 1094±124 ng/l to 459±110 ng/l) by the use of the CK2-inhibitor SGC-CK2-1. This was due to a marked decrease in Gcg gene expression through alteration of the binding of paired box protein 6 (PAX6) and transcription factor MafB to the Gcg promoter. The analysis of the underlying mechanisms revealed that both transcription factors are displaced by PDX1. Ex vivo experiments in isolated murine islets and pseudoislets further demonstrated that CK2-mediated reduction in GCG secretion was only slightly affected by the higher insulin secretion after CK2 inhibition. The kidney capsule transplantation model showed the significance of CK2 for GCG expression and secretion in vivo. Finally, CK2 downregulation also reduced the GCG secretion in islets isolated from humans. CONCLUSIONS/INTERPRETATION: These novel findings not only indicate an important function of protein kinase CK2 for proper GCG expression but also demonstrate that CK2 may be a promising target for the development of novel glucose-lowering drugs.

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

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

Web-based multi-omics integration using the Analyst software suite.

The growing number of multi-omics studies demands clear conceptual workflows coupled with easy-to-use software tools to facilitate data analysis and interpretation. This protocol covers three key components involved in multi-omics analysis, including single-omics data analysis, knowledge-driven integration using biological networks and data-driven integration through joint dimensionality reduction. Using the dataset from a recent multi-omics study of human pancreatic islet tissue and plasma samples, the first section introduces how to perform transcriptomics/proteomics data analysis using ExpressAnalyst and lipidomics data analysis using MetaboAnalyst. On the basis of significant features detected in these workflows, the second section demonstrates how to perform knowledge-driven integration using OmicsNet. The last section illustrates how to perform data-driven integration from the normalized omics data and metadata using OmicsAnalyst. The complete protocol can be executed in ~2 h. Compared with other available options for multi-omics integration, the Analyst software suite described in this protocol enables researchers to perform a wide range of omics data analysis tasks via a user-friendly web interface.

A role and mechanism for redox sensing by SENP1 in ß-cell responses to high fat feeding.

Pancreatic ß-cells respond to metabolic stress by upregulating insulin secretion, however the underlying mechanisms remain unclear. Here we show, in ß-cells from overweight humans without diabetes and mice fed a high-fat diet for 2 days, insulin exocytosis and secretion are enhanced without increased Ca2+ influx. RNA-seq of sorted ß-cells suggests altered metabolic pathways early following high fat diet, where we find increased basal oxygen consumption and proton leak, but a more reduced cytosolic redox state. Increased ß-cell exocytosis after 2-day high fat diet is dependent on this reduced intracellular redox state and requires the sentrin-specific SUMO-protease-1. Mice with either pancreas- or ß-cell-specific deletion of this fail to up-regulate exocytosis and become rapidly glucose intolerant after 2-day high fat diet. Mechanistically, redox-sensing by the SUMO-protease requires a thiol group at C535 which together with Zn+-binding suppresses basal protease activity and unrestrained ß-cell exocytosis, and increases enzyme sensitivity to regulation by redox signals.

RFX6 Maintains Gene Expression and Function of Adult Human Islet α-Cells.

Mutations in the gene encoding the transcription factor regulatory factor X-box binding 6 (RFX6) are associated with human diabetes. Within pancreatic islets, RFX6 expression is most abundant in islet α-cells, and α-cell RFX6 expression is altered in diabetes. However, the roles of RFX6 in regulating gene expression, glucagon output, and other crucial human adult α-cell functions are not yet understood. We developed a method for selective genetic targeting of human α-cells and assessed RFX6-dependent α-cell function. RFX6 suppression with RNA interference led to impaired α-cell exocytosis and dysregulated glucagon secretion in vitro and in vivo. By contrast, these phenotypes were not observed with RFX6 suppression across all islet cells. Transcriptomics in α-cells revealed RFX6-dependent expression of genes governing nutrient sensing, hormone processing, and secretion, with some of these exclusively expressed in human α-cells. Mapping of RFX6 DNA-binding sites in primary human islet cells identified a subset of direct RFX6 target genes. Together, these data unveil RFX6-dependent genetic targets and mechanisms crucial for regulating adult human α-cell function.

HNF1α maintains pancreatic α and ß cell functions in primary human islets.

HNF1A haploinsufficiency underlies the most common form of human monogenic diabetes (HNF1A-maturity onset diabetes of the young [HNF1A-MODY]), and hypomorphic HNF1A variants confer type 2 diabetes risk. But a lack of experimental systems for interrogating mature human islets has limited our understanding of how the transcription factor HNF1α regulates adult islet function. Here, we combined conditional genetic targeting in human islet cells, RNA-Seq, chromatin mapping with cleavage under targets and release using nuclease (CUT&RUN), and transplantation-based assays to determine HNF1α-regulated mechanisms in adult human pancreatic α and ß cells. Short hairpin RNA-mediated (shRNA-mediated) suppression of HNF1A in primary human pseudoislets led to blunted insulin output and dysregulated glucagon secretion after transplantation in mice, recapitulating phenotypes observed in patients with diabetes. These deficits corresponded with altered expression of genes encoding factors critical for hormone secretion, including calcium channel subunits, ATPase transporters, and extracellular matrix constituents. Additionally, HNF1A loss led to upregulation of transcriptional repressors, providing evidence for a mechanism of transcriptional derepression through HNF1α. CUT&RUN mapping of HNF1α DNA binding sites in primary human islets imputed a subset of HNF1α-regulated genes as direct targets. These data elucidate mechanistic links between HNF1A loss and diabetic phenotypes in mature human α and ß cells.

Modulation of insulin secretion by RBFOX2-mediated alternative splicing.

Insulin secretion is a tightly regulated process that is vital for maintaining blood glucose homeostasis. Although the molecular components of insulin granule trafficking and secretion are well established, how they are regulated to rapidly fine-tune secretion in response to changing environmental conditions is not well characterized. Recent studies have determined that dysregulation of RNA-binding proteins (RBPs) and aberrant mRNA splicing occurs at the onset of diabetes. We demonstrate that the RBP, RBFOX2, is a critical regulator of insulin secretion through the alternative splicing of genes required for insulin granule docking and exocytosis. Conditional mutation of Rbfox2 in the mouse pancreas results in decreased insulin secretion and impaired blood glucose homeostasis. Consistent with defects in secretion, we observe reduced insulin granule docking and corresponding splicing defects in the SNARE complex components. These findings identify an additional mechanism for modulating insulin secretion in both healthy and dysfunctional pancreatic ß cells.

Caloric restriction promotes beta cell longevity and delays aging and senescence by enhancing cell identity and homeostasis mechanisms.

Caloric restriction (CR) extends organismal lifespan and health span by improving glucose homeostasis mechanisms. How CR affects organellar structure and function of pancreatic beta cells over the lifetime of the animal remains unknown. Here, we used single nucleus transcriptomics to show that CR increases the expression of genes for beta cell identity, protein processing, and organelle homeostasis. Gene regulatory network analysis link this transcriptional phenotype to transcription factors involved in beta cell identity (Mafa) and homeostasis (Atf6). Imaging metabolomics further demonstrates that CR beta cells are more energetically competent. In fact, high-resolution light and electron microscopy indicates that CR reduces beta cell mitophagy and increases mitochondria mass, increasing mitochondrial ATP generation. Finally, we show that long-term CR delays the onset of beta cell aging and senescence to promote longevity by reducing beta cell turnover. Therefore, CR could be a feasible approach to preserve compromised beta cells during aging and diabetes.

Caloric restriction promotes beta cell longevity and delays aging and senescence by enhancing cell identity and homeostasis mechanisms.

Caloric restriction (CR) extends organismal lifespan and health span by improving glucose homeostasis mechanisms. How CR affects organellar structure and function of pancreatic beta cells over the lifetime of the animal remains unknown. Here, we used single nucleus transcriptomics to show that CR increases the expression of genes for beta cell identity, protein processing, and organelle homeostasis. Gene regulatory network analysis link this transcriptional phenotype to transcription factors involved in beta cell identity (Mafa) and homeostasis (Atf6). Imaging metabolomics further demonstrates that CR beta cells are more energetically competent. In fact, high-resolution light and electron microscopy indicates that CR reduces beta cell mitophagy and increases mitochondria mass, increasing mitochondrial ATP generation. Finally, we show that long-term CR delays the onset of beta cell aging and senescence to promote longevity by reducing beta cell turnover. Therefore, CR could be a feasible approach to preserve compromised beta cells during aging and diabetes.

Deletion of Carboxypeptidase E in ß-Cells Disrupts Proinsulin Processing but Does Not Lead to Spontaneous Development of Diabetes in Mice.

Carboxypeptidase E (CPE) facilitates the conversion of prohormones into mature hormones and is highly expressed in multiple neuroendocrine tissues. Carriers of CPE mutations have elevated plasma proinsulin and develop severe obesity and hyperglycemia. We aimed to determine whether loss of Cpe in pancreatic ß-cells disrupts proinsulin processing and accelerates development of diabetes and obesity in mice. Pancreatic ß-cell-specific Cpe knockout mice (ßCpeKO; Cpefl/fl x Ins1Cre/+) lack mature insulin granules and have elevated proinsulin in plasma; however, glucose-and KCl-stimulated insulin secretion in ßCpeKO islets remained intact. High-fat diet-fed ßCpeKO mice showed weight gain and glucose tolerance comparable with those of Wt littermates. Notably, ß-cell area was increased in chow-fed ßCpeKO mice and ß-cell replication was elevated in ßCpeKO islets. Transcriptomic analysis of ßCpeKO ß-cells revealed elevated glycolysis and Hif1α-target gene expression. On high glucose challenge, ß-cells from ßCpeKO mice showed reduced mitochondrial membrane potential, increased reactive oxygen species, reduced MafA, and elevated Aldh1a3 transcript levels. Following multiple low-dose streptozotocin injections, ßCpeKO mice had accelerated development of hyperglycemia with reduced ß-cell insulin and Glut2 expression. These findings suggest that Cpe and proper proinsulin processing are critical in maintaining ß-cell function during the development of hyperglycemia. ARTICLE HIGHLIGHTS: Carboxypeptidase E (Cpe) is an enzyme that removes the carboxy-terminal arginine and lysine residues from peptide precursors. Mutations in CPE lead to obesity and type 2 diabetes in humans, and whole-body Cpe knockout or mutant mice are obese and hyperglycemic and fail to convert proinsulin to insulin. We show that ß-cell-specific Cpe deletion in mice (ßCpeKO) does not lead to the development of obesity or hyperglycemia, even after prolonged high-fat diet treatment. However, ß-cell proliferation rate and ß-cell area are increased, and the development of hyperglycemia induced by multiple low-dose streptozotocin injections is accelerated in ßCpeKO mice.

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.

Loss of RREB1 in pancreatic beta cells reduces cellular insulin content and affects endocrine cell gene expression.

AIMS/HYPOTHESIS: Genome-wide studies have uncovered multiple independent signals at the RREB1 locus associated with altered type 2 diabetes risk and related glycaemic traits. However, little is known about the function of the zinc finger transcription factor Ras-responsive element binding protein 1 (RREB1) in glucose homeostasis or how changes in its expression and/or function influence diabetes risk. METHODS: A zebrafish model lacking rreb1a and rreb1b was used to study the effect of RREB1 loss in vivo. Using transcriptomic and cellular phenotyping of a human beta cell model (EndoC-ßH1) and human induced pluripotent stem cell (hiPSC)-derived beta-like cells, we investigated how loss of RREB1 expression and activity affects pancreatic endocrine cell development and function. Ex vivo measurements of human islet function were performed in donor islets from carriers of RREB1 type 2 diabetes risk alleles. RESULTS: CRISPR/Cas9-mediated loss of rreb1a and rreb1b function in zebrafish supports an in vivo role for the transcription factor in beta cell mass, beta cell insulin expression and glucose levels. Loss of RREB1 also reduced insulin gene expression and cellular insulin content in EndoC-ßH1 cells and impaired insulin secretion under prolonged stimulation. Transcriptomic analysis of RREB1 knockdown and knockout EndoC-ßH1 cells supports RREB1 as a novel regulator of genes involved in insulin secretion. In vitro differentiation of RREB1KO/KO hiPSCs revealed dysregulation of pro-endocrine cell genes, including RFX family members, suggesting that RREB1 also regulates genes involved in endocrine cell development. Human donor islets from carriers of type 2 diabetes risk alleles in RREB1 have altered glucose-stimulated insulin secretion ex vivo, consistent with a role for RREB1 in regulating islet cell function. CONCLUSIONS/INTERPRETATION: Together, our results indicate that RREB1 regulates beta cell function by transcriptionally regulating the expression of genes involved in beta cell development and function.

Metabolic Messengers: glucagon.

Plasma glucose is tightly regulated via the secretion of the two glucose-regulating hormones insulin and glucagon. Situated next to the insulin-secreting ß-cells, the α-cells produce and secrete glucagon-one of the body's few blood glucose-increasing hormones. Diabetes is a bihormonal disorder, resulting from both inadequate insulin secretion and dysregulation of glucagon. The year 2023 marks the 100th anniversary of the discovery of glucagon, making it particularly timely to highlight the roles of this systemic metabolic messenger in health and disease.

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.

A genome-wide CRISPR screen identifies CALCOCO2 as a regulator of beta cell function influencing type 2 diabetes risk.

Identification of the genes and processes mediating genetic association signals for complex diseases represents a major challenge. As many of the genetic signals for type 2 diabetes (T2D) exert their effects through pancreatic islet-cell dysfunction, we performed a genome-wide pooled CRISPR loss-of-function screen in a human pancreatic beta cell line. We assessed the regulation of insulin content as a disease-relevant readout of beta cell function and identified 580 genes influencing this phenotype. Integration with genetic and genomic data provided experimental support for 20 candidate T2D effector transcripts including the autophagy receptor CALCOCO2. Loss of CALCOCO2 was associated with distorted mitochondria, less proinsulin-containing immature granules and accumulation of autophagosomes upon inhibition of late-stage autophagy. Carriers of T2D-associated variants at the CALCOCO2 locus further displayed altered insulin secretion. Our study highlights how cellular screens can augment existing multi-omic efforts to support mechanistic understanding and provide evidence for causal effects at genome-wide association studies loci.

Loss of tetraspanin-7 expression reduces pancreatic ß-cell exocytosis Ca2+ sensitivity but has limited effect on systemic metabolism.

BACKGROUND: Tetraspanin-7 (Tspan7) is an islet autoantigen involved in autoimmune type 1 diabetes and known to regulate ß-cell L-type Ca2+ channel activity. However, the role of Tspan7 in pancreatic ß-cell function is not yet fully understood. METHODS: Histological analyses were conducted using immunostaining. Whole-body metabolism was tested using glucose tolerance test. Islet hormone secretion was quantified using static batch incubation or dynamic perifusion. ß-cell transmembrane currents, electrical activity and exocytosis were measured using whole-cell patch-clamping and capacitance measurements. Gene expression was studied using mRNA-sequencing and quantitative PCR. RESULTS: Tspan7 is expressed in insulin-containing granules of pancreatic ß-cells and glucagon-producing α-cells. Tspan7 knockout mice (Tspan7y/- mouse) exhibit reduced body weight and ad libitum plasma glucose but normal glucose tolerance. Tspan7y/- islets have normal insulin content and glucose- or tolbutamide-stimulated insulin secretion. Depolarisation-triggered Ca2+ current was enhanced in Tspan7y/- ß-cells, but ß-cell electrical activity and depolarisation-evoked exocytosis were unchanged suggesting that exocytosis was less sensitive to Ca2+ . TSPAN7 knockdown (KD) in human pseudo-islets led to a significant reduction in insulin secretion stimulated by 20 mM K+ . Transcriptomic analyses show that TSPAN7 KD in human pseudo-islets correlated with changes in genes involved in hormone secretion, apoptosis and ER stress. Consistent with rodent ß-cells, exocytotic Ca2+ sensitivity was reduced in a human ß-cell line (EndoC-ßH1) following Tspan7 KD. CONCLUSION: Tspan7 is involved in the regulation of Ca2+ -dependent exocytosis in ß-cells. Its function is more significant in human ß-cells than their rodent counterparts.

Aging compromises human islet beta cell function and identity by decreasing transcription factor activity and inducing ER stress.

Pancreatic islet beta cells are essential for maintaining glucose homeostasis. To understand the impact of aging on beta cells, we performed meta-analysis of single-cell RNA sequencing datasets, transcription factor (TF) regulon analysis, high-resolution confocal microscopy, and measured insulin secretion from nondiabetic donors spanning most of the human life span. This revealed the range of molecular and functional changes that occur during beta cell aging, including the transcriptional deregulation that associates with cellular immaturity and reorganization of beta cell TF networks, increased gene transcription rates, and reduced glucose-stimulated insulin release. These alterations associate with activation of endoplasmic reticulum (ER) stress and autophagy pathways. We propose that a chronic state of ER stress undermines old beta cell structure function to increase the risk of beta cell failure and type 2 diabetes onset as humans age.

Zmiz1 is required for mature ß-cell function and mass expansion upon high fat feeding.

OBJECTIVE: Identifying the transcripts which mediate genetic association signals for type 2 diabetes (T2D) is critical to understand disease mechanisms. Studies in pancreatic islets support the transcription factor ZMIZ1 as a transcript underlying a T2D GWAS signal, but how it influences T2D risk is unknown. METHODS: ß-Cell-specific Zmiz1 knockout (Zmiz1ßKO) mice were generated and phenotypically characterised. Glucose homeostasis was assessed in Zmiz1ßKO mice and their control littermates on chow diet (CD) and high fat diet (HFD). Islet morphology and function were examined by immunohistochemistry and in vitro islet function was assessed by dynamic insulin secretion assay. Transcript and protein expression were assessed by RNA sequencing and Western blotting. In islets isolated from genotyped human donors, we assessed glucose-dependent insulin secretion and islet insulin content by static incubation assay. RESULTS: Male and female Zmiz1ßKO mice were glucose intolerant with impaired insulin secretion, compared with control littermates. Transcriptomic profiling of Zmiz1ßKO islets identified over 500 differentially expressed genes including those involved in ß-cell function and maturity, which we confirmed at the protein level. Upon HFD, Zmiz1ßKO mice fail to expand ß-cell mass and become severely diabetic. Human islets from carriers of the ZMIZ1-linked T2D-risk alleles have reduced islet insulin content and glucose-stimulated insulin secretion. CONCLUSIONS: ß-Cell Zmiz1 is required for normal glucose homeostasis. Genetic variation at the ZMIZ1 locus may influence T2D-risk by reducing islet mass expansion upon metabolic stress and the ability to maintain a mature ß-cell state.

Ca2+ Oscillations, Waves, and Networks in Islets From Human Donors With and Without Type 2 Diabetes.

Pancreatic islets are highly interconnected structures that produce pulses of insulin and other hormones, maintaining normal homeostasis of glucose and other nutrients. Normal stimulus-secretion and intercellular coupling are essential to regulated secretory responses, and these hallmarks are known to be altered in diabetes. In the current study, we used calcium imaging of isolated human islets to assess their collective behavior. The activity occurred in the form of calcium oscillations, was synchronized across different regions of islets through calcium waves, and was glucose dependent: higher glucose enhanced the activity, elicited a greater proportion of global calcium waves, and led to denser and less fragmented functional networks. Hub regions were identified in stimulatory conditions, and they were characterized by long active times. Moreover, calcium waves were found to be initiated in different subregions and the roles of initiators and hubs did not overlap. In type 2 diabetes, glucose dependence was retained, but reduced activity, locally restricted waves, and more segregated networks were detected compared with control islets. Interestingly, hub regions seemed to suffer the most by losing a disproportionately large fraction of connections. These changes affected islets from donors with diabetes in a heterogeneous manner.