HumanIslets.com: Improving accessibility, integration, and usability of human research islet data.

HumanIslets.com supports diabetes research by offering easy access to islet phenotyping data, analysis tools, and data download. It includes molecular omics, islet and cellular function assays, tissue processing metadata, and phenotypes from 547 donors. As it expands, the resource aims to improve human islet data quality, usability, and accessibility.

Transcriptional coactivator MED15 is required for beta cell maturation.

Mediator, a co-regulator complex required for RNA Polymerase II activity, interacts with tissue-specific transcription factors to regulate development and maintain homeostasis. We observe reduced Mediator subunit MED15 expression in endocrine hormone-producing pancreatic islets isolated from people living with type 2 diabetes and sought to understand how MED15 and Mediator control gene expression programs important for the function of insulin-producing ß-cells. Here we show that Med15 is expressed during mouse ß-cell development and maturation. Knockout of Med15 in mouse ß-cells causes defects in ß-cell maturation without affecting ß-cell mass or insulin expression. ChIP-seq and co-immunoprecipitation analyses found that Med15 binds ß-cell transcription factors Nkx6-1 and NeuroD1 to regulate key ß-cell maturation genes. In support of a conserved role during human development, human embryonic stem cell-derived ß-like cells, genetically engineered to express high levels of MED15, express increased levels of maturation markers. We provide evidence of a conserved role for Mediator in ß-cell maturation and demonstrate an additional layer of control that tunes ß-cell transcription factor function.

HumanIslets: An integrated platform for human islet data access and analysis.

Comprehensive molecular and cellular phenotyping of human islets can enable deep mechanistic insights for diabetes research. We established the Human Islet Data Analysis and Sharing (HI-DAS) consortium to advance goals in accessibility, usability, and integration of data from human islets isolated from donors with and without diabetes at the Alberta Diabetes Institute (ADI) IsletCore. Here we introduce HumanIslets.com, an open resource for the research community. This platform, which presently includes data on 547 human islet donors, allows users to access linked datasets describing molecular profiles, islet function and donor phenotypes, and to perform various statistical and functional analyses at the donor, islet and single-cell levels. As an example of the analytic capacity of this resource we show a dissociation between cell culture effects on transcript and protein expression, and an approach to correct for exocrine contamination found in hand-picked islets. Finally, we provide an example workflow and visualization that highlights links between type 2 diabetes status, SERCA3b Ca2+-ATPase levels at the transcript and protein level, insulin secretion and islet cell phenotypes. HumanIslets.com provides a growing and adaptable set of resources and tools to support the metabolism and diabetes research community.

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

Population-level variation and mechanisms behind insulin secretion in response to carbohydrate, protein, and fat remain uncharacterized. We defined prototypical insulin secretion responses to three macronutrients in islets from 140 cadaveric donors, including those with type 2 diabetes. The majority of donors' islets exhibited the highest insulin response to glucose, moderate response to amino acid, and minimal response to fatty acid. However, 9% of donors' islets had amino acid responses, and 8% had fatty acid responses that were larger than their glucose-stimulated insulin responses. We leveraged this heterogeneity and used multi-omics to identify molecular correlates of nutrient responsiveness, as well as proteins and mRNAs altered in type 2 diabetes. We also examined nutrient-stimulated insulin release from stem cell-derived islets and observed responsiveness to fat but not carbohydrate or protein-potentially a hallmark of immaturity. Understanding the diversity of insulin responses to carbohydrate, protein, and fat lays the groundwork for personalized nutrition.

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.

Effect of sodium-glucose cotransporter 2 inhibitors on serum low-density lipoprotein cholesterol in Japanese patients with type 2 diabetes mellitus.

AIMS/INTRODUCTION: We aimed to evaluate factors that influence changes in blood low-density lipoprotein cholesterol (LDL-C) levels after treatment with sodium-glucose cotransporter 2 (SGLT2) inhibitors in Japanese patients with type 2 diabetes. MATERIALS AND METHODS: We retrospectively analyzed clinical data of outpatients newly initiated on SGLT2 inhibitors (n = 176) and other oral antidiabetic drugs (n = 227). The patients were classified into four subgroups according to statin administration and baseline LDL-C levels (<120 or ≥120 mg/dL). Clinical characteristics were compared among the subgroups. Multivariate analysis was carried out to identify factors contributing to changes in LDL-C. RESULTS: The median follow-up period was 13.0 weeks (range 11.9-14.1 weeks, min 8 weeks, maximum 16 weeks) in the SGLT2i group, and 12.0 weeks (range 10.0-14.0 weeks, min 8 weeks, maximum 16 weeks) in the control group. Both groups showed a significant decrease in LDL-C (SGLT2i group -3.8 ± 24.7 mg/dL, control group -3.4 ± 15.0 mg/dL). Multivariate regression analyses showed that in both groups, the change in LDL-C depended on statin use and baseline LDL-C levels. Stratified analyses showed that LDL-C level was significantly decreased in statin users with baseline LDL-C ≥120 mg/dL (from 148.9 ± 33.5 to 109.3 ± 17.9 mg/dL, P = 0.002), and significantly increased in statin non-users with baseline LDL-C <120 mg/dL (from 96.3 ± 27.3 to 104.7 ± 24.8 mg/dL, P = 0.002). These changes were more characteristic for SGLT2 inhibitors than for other oral antidiabetic drugs (P for interaction = 0.010 and <0.001, respectively). CONCLUSIONS: LDL-C levels and statin medication at baseline influence changes in LDL-C after SGLT2 inhibitors treatment in Japanese patients with type 2 diabetes.

Novel time-resolved reporter mouse reveals spatial and transcriptional heterogeneity during alpha cell differentiation.

AIMS/HYPOTHESIS: Glucagon-expressing pancreatic alpha cells have attracted much attention for their plasticity to transdifferentiate into insulin-producing beta cells; however, it remains unclear precisely when, and from where, alpha cells emerge and what regulates alpha cell fate. We therefore explored the spatial and transcriptional heterogeneity of alpha cell differentiation using a novel time-resolved reporter system. METHODS: We established the mouse model, 'Gcg-Timer', in which newly generated alpha cells can be distinguished from more-differentiated cells by their fluorescence. Fluorescence imaging and transcriptome analysis were performed with Gcg-Timer mice during the embryonic and postnatal stages. RESULTS: Fluorescence imaging and flow cytometry demonstrated that green fluorescence-dominant cells were present in Gcg-Timer mice at the embryonic and neonatal stages but not after 1 week of age, suggesting that alpha cell neogenesis occurs during embryogenesis and early neonatal stages under physiological conditions. Transcriptome analysis of Gcg-Timer embryos revealed that the mRNAs related to angiogenesis were enriched in newly generated alpha cells. Histological analysis revealed that some alpha cells arise close to the pancreatic ducts, whereas the others arise away from the ducts and adjacent to the blood vessels. Notably, when the glucagon signal was suppressed by genetic ablation or by chemicals, such as neutralising glucagon antibody, green-dominant cells emerged again in adult mice. CONCLUSIONS/INTERPRETATION: Novel time-resolved analysis with Gcg-Timer reporter mice uncovered spatiotemporal features of alpha cell neogenesis that will enhance our understanding of cellular identity and plasticity within the islets. DATA AVAILABILITY: Raw and processed RNA sequencing data for this study has been deposited in the Gene Expression Omnibus under accession number GSE229090.

Human A2-CAR T Cells Reject HLA-A2 + Human Islets Transplanted Into Mice Without Inducing Graft-versus-host Disease.

BACKGROUND: Type 1 diabetes is an autoimmune disease characterized by T-cell-mediated destruction of pancreatic beta-cells. Islet transplantation is an effective therapy, but its success is limited by islet quality and availability along with the need for immunosuppression. New approaches include the use of stem cell-derived insulin-producing cells and immunomodulatory therapies, but a limitation is the paucity of reproducible animal models in which interactions between human immune cells and insulin-producing cells can be studied without the complication of xenogeneic graft-versus-host disease (xGVHD). METHODS: We expressed an HLA-A2-specific chimeric antigen receptor (A2-CAR) in human CD4 + and CD8 + T cells and tested their ability to reject HLA-A2 + islets transplanted under the kidney capsule or anterior chamber of the eye of immunodeficient mice. T-cell engraftment, islet function, and xGVHD were assessed longitudinally. RESULTS: The speed and consistency of A2-CAR T-cell-mediated islet rejection varied depending on the number of A2-CAR T cells and the absence/presence of coinjected peripheral blood mononuclear cells (PBMCs). When <3 million A2-CAR T cells were injected, coinjection of PBMCs accelerated islet rejection but also induced xGVHD. In the absence of PBMCs, injection of 3 million A2-CAR T cells caused synchronous rejection of A2 + human islets within 1 wk and without xGVHD for 12 wk. CONCLUSIONS: Injection of A2-CAR T cells can be used to study rejection of human insulin-producing cells without the complication of xGVHD. The rapidity and synchrony of rejection will facilitate in vivo screening of new therapies designed to improve the success of islet-replacement therapies.

Type 2 diabetes susceptibility gene GRK5 regulates physiological pancreatic ß-cell proliferation via phosphorylation of HDAC5.

Restoring functional ß cell mass is a potential therapy for those with diabetes. However, the pathways regulating ß cell mass are not fully understood. Previously, we demonstrated that Sox4 is required for ß cell proliferation during prediabetes. Here, we report that Sox4 regulates ß cell mass through modulating expression of the type 2 diabetes (T2D) susceptibility gene GRK5. ß cell-specific Grk5 knockout mice showed impaired glucose tolerance with reduced ß cell mass, which was accompanied by upregulation of cell cycle inhibitor gene Cdkn1a. Furthermore, we found that Grk5 may drive ß cell proliferation through a pathway that includes phosphorylation of HDAC5 and subsequent transcription of immediate-early genes (IEGs) such as Nr4a1, Fosb, Junb, Arc, Egr1, and Srf. Together, these studies suggest GRK5 is linked to T2D through regulation of ß cell growth and that it may be a target to preserve ß cells during the development of T2D.

ATP6AP2 is robustly expressed in pancreatic ß cells and neuroendocrine tumors, and plays a role in maintaining cellular viability.

ATP6AP2, also known as (pro)renin receptor, has been shown to be expressed in several tissues including pancreatic ß cells. Whereas ATP6AP2 plays an important role in regulating insulin secretion in mouse pancreatic ß cells, the expression profiles and roles of ATP6AP2 in human pancreatic endocrine cells and neuroendocrine tumor cells remain unclear. Here in this study, we investigated the expression profiles of ATP6AP2 in pancreatic endocrine cells, and found that ATP6AP2 is robustly expressed in pancreatic insulinoma cells as well as in normal ß cells. Although ATP6AP2 was also expressed in low-grade neuroendocrine tumors, it was not or faintly detected in intermediate- and high-grade neuroendocrine tumors. Knockdown experiments of the Atp6ap2 gene in rat insulinoma-derived INS-1 cells demonstrated decreased cell viability accompanied by a significant increase in apoptotic cells. Taken together, these findings suggest that ATP6AP2 plays a role in maintaining cellular homeostasis in insulinoma cells, which could lead to possible therapeutic approaches for endocrine tumors.

Effect of a mobile app chatbot and an interactive small-group webinar on COVID-19 vaccine intention and confidence in Japan: a randomised controlled trial.

INTRODUCTION: We investigated the effect of social media-based interventions on COVID-19 vaccine intention (VI) and confidence in Japan. METHODS: We conducted a three-arm randomised controlled trial between 5 November 2021 and 9 January 2022 during a low incidence (<1000/day) of COVID-19 in Japan in the midst of the second and the third waves. Japanese citizens aged ≥20 who had not received any COVID-19 vaccine and did not intend to be vaccinated were randomly assigned to one of the following three groups: (1) a control group, (2) a group using a mobile app chatbot providing information on COVID-19 vaccines and (3) a group using interactive webinars with health professionals. VI and predefined Vaccine Confidence Index (VCI) measuring confidence in the importance, safety and effectiveness were compared before and after the interventions under intention-to-treat principle. Logistic regression models were used to investigate the effect of each intervention on postintervention VI and changes of VCI compared with control. RESULTS: Among 386 participants in each group, 359 (93.0%), 231 (59.8%) and 207 (53.6%) completed the postsurvey for the control, chatbot and webinar groups, respectively. The average duration between the intervention and the postsurvey was 32 days in chatbot group and 27 days in webinar group. VI increased from 0% to 18.5% (95% CI 14.5%, 22.5%) in control group, 15.4% (95% CI 10.8%, 20.1%) in chatbot group and 19.7% (95% CI 14.5%, 24.9%) in webinar group without significant difference (OR for improvement=0.8 (95% CI 0.5, 1.3), p=0.33 between chatbot and control, OR=1.1 (95% CI 0.7, 1.6), p=0.73 between webinar and control). VCI change tended to be larger in chatbot group compared with control group without significant difference (3.3% vs -2.5% in importance, OR for improvement=1.3 (95% CI 0.9, 2.0), p=0.18; 2.5% vs 1.9% in safety, OR=1.1 (95% CI 0.7, 1.9), p=0.62; -2.4% vs -7.6% in effectiveness, OR=1.4 (95% CI 0.9, 2.1), p=0.09). Improvement in VCI was larger in webinar group compared with control group for importance (7.8% vs -2.5%, OR=1.8 (95% CI 1.2, 2.8), p<0.01), effectiveness (6.4% vs -7.6%, OR=2.2 (95% CI 1.4, 3.4), p<0.01) and safety (6.0% vs 1.9%, OR=1.6 (95% CI 1.0, 2.6), p=0.08). CONCLUSION: This study demonstrated that neither the chatbot nor the webinar changed VI importantly compared with control. Interactive webinars could be an effective tool to change vaccine confidence. Further study is needed to identify risk factors associated with decreased vaccine confidence and investigate what intervention can increase VI and vaccine confidence for COVID-19 vaccines. TRIAL REGISTRATION NUMBER: UMIN000045747.

Newly discovered knowledge pertaining to glucagon and its clinical applications.

Glucagon has been defined as an 'insulin counteracting hormone', which raises blood glucose levels. Recent progress in basic research has shown that glucagon is closely involved in glucose and amino acid metabolism. Additionally, its secretion is intricately, but precisely, regulated by various mechanisms involving molecules in addition to glucose, thus showing its critical role in systemic nutrient metabolism. An innovative dual-antibody-linked immunosorbent assay for glucagon that improves measurement accuracy has been developed, and substantial clinical findings have been obtained using this new system. This discovery expanded the pathophysiological significance of glucagon and accelerated the development of its clinical applications in diabetes.

In silico discovery of small molecules for efficient stem cell differentiation into definitive endoderm.

Improving methods for human embryonic stem cell differentiation represents a challenge in modern regenerative medicine research. Using drug repurposing approaches, we discover small molecules that regulate the formation of definitive endoderm. Among them are inhibitors of known processes involved in endoderm differentiation (mTOR, PI3K, and JNK pathways) and a new compound, with an unknown mechanism of action, capable of inducing endoderm formation in the absence of growth factors in the media. Optimization of the classical protocol by inclusion of this compound achieves the same differentiation efficiency with a 90% cost reduction. The presented in silico procedure for candidate molecule selection has broad potential for improving stem cell differentiation protocols.

Heterogeneity of Islet Cells during Embryogenesis and Differentiation.

Diabetes is caused by insufficient insulin secretion due to ß-cell dysfunction and/or ß-cell loss. Therefore, the restoration of functional ß-cells by the induction of ß-cell differentiation from embryonic stem (ES) and induced-pluripotent stem (iPS) cells, or from somatic non-ß-cells, may be a promising curative therapy. To establish an efficient and feasible method for generating functional insulin-producing cells, comprehensive knowledge of pancreas development and ß-cell differentiation, including the mechanisms driving cell fate decisions and endocrine cell maturation is crucial. Recent advances in single-cell RNA sequencing (scRNA-seq) technologies have opened a new era in pancreas development and diabetes research, leading to clarification of the detailed transcriptomes of individual insulin-producing cells. Such extensive high-resolution data enables the inference of developmental trajectories during cell transitions and gene regulatory networks. Additionally, advancements in stem cell research have not only enabled their immediate clinical application, but also has made it possible to observe the genetic dynamics of human cell development and maturation in a dish. In this review, we provide an overview of the heterogeneity of islet cells during embryogenesis and differentiation as demonstrated by scRNA-seq studies on the developing and adult pancreata, with implications for the future application of regenerative medicine for diabetes.

Corowa-kun: A messenger app chatbot delivers COVID-19 vaccine information, Japan 2021.

BACKGROUND: There is a long history in Japan of public concerns about vaccine adverse events. Few studies have assessed how mobile messenger apps affect COVID-19 vaccine hesitancy. METHODS: Corowa-kun, a free chatbot, was created on February 6, 2021 in LINE, the most popular messenger app in Japan. Corowa-kun provides instant, automated answers to 70 frequently asked COVID-19 vaccine questions. A cross-sectional survey with 21 questions was performed within Corowa-kun during April 5-12, 2021. RESULTS: A total of 59,676 persons used Corowa-kun during February-April 2021. Of them, 10,192 users (17%) participated in the survey. Median age was 55 years (range 16-97), and most were female (74%). COVID-19 vaccine hesitancy reported by survey respondents decreased from 41% to 20% after using Corowa-kun. Of the 20% who remained hesitant, 16% (1,675) were unsure, and 4% (364) did not intend to be vaccinated. Factors associated with vaccine hesitancy were: age 16-34 (odds ratio [OR] = 3.7; 95% confidential interval [CI]: 3.0-4.6, compared to age ≥ 65), female sex (OR = 2.4; Cl: 2.1-2.8), and history of a previous vaccine side-effect (OR = 2.5; Cl: 2.2-2.9). Being a physician (OR = 0.2; Cl: 0.1-0.4) and having received a flu vaccine the prior season (OR = 0.4; Cl: 0.3-0.4) were protective. CONCLUSIONS: A substantial number of people used the chabot in a short period. Mobile messenger apps could be leveraged to provide accurate vaccine information and to investigate vaccine intention and risk factors for vaccine hesitancy.

Calcium-dependent transcriptional changes in human pancreatic islet cells reveal functional diversity in islet cell subtypes.

AIMS/HYPOTHESIS: Pancreatic islets depend on cytosolic calcium (Ca2+) to trigger the secretion of glucoregulatory hormones and trigger transcriptional regulation of genes important for islet response to stimuli. To date, there has not been an attempt to profile Ca2+-regulated gene expression in all islet cell types. Our aim was to construct a large single-cell transcriptomic dataset from human islets exposed to conditions that would acutely induce or inhibit intracellular Ca2+ signalling, while preserving biological heterogeneity. METHODS: We exposed intact human islets from three donors to the following conditions: (1) 2.8 mmol/l glucose; (2) 16 mmol/l glucose and 40 mmol/l KCl to maximally stimulate Ca2+ signalling; and (3) 16 mmol/l glucose, 40 mmol/l KCl and 5 mmol/l EGTA (Ca2+ chelator) to inhibit Ca2+ signalling, for 1 h. We sequenced 68,650 cells from all islet cell types, and further subsetted the cells to form an endocrine cell-specific dataset of 59,373 cells expressing INS, GCG, SST or PPY. We compared transcriptomes across conditions to determine the differentially expressed Ca2+-regulated genes in each endocrine cell type, and in each endocrine cell subcluster of alpha and beta cells. RESULTS: Based on the number of Ca2+-regulated genes, we found that each alpha and beta cell cluster had a different magnitude of Ca2+ response. We also showed that polyhormonal clusters expressing both INS and GCG, or both INS and SST, are defined by Ca2+-regulated genes specific to each cluster. Finally, we identified the gene PCDH7 from the beta cell clusters that had the highest number of Ca2+-regulated genes, and showed that cells expressing cell surface PCDH7 protein have enhanced glucose-stimulated insulin secretory function. CONCLUSIONS/INTERPRETATION: Here we use our large-scale, multi-condition, single-cell dataset to show that human islets have cell-type-specific Ca2+-regulated gene expression profiles, some of them specific to subpopulations. In our dataset, we identify PCDH7 as a novel marker of beta cells having an increased number of Ca2+-regulated genes and enhanced insulin secretory function. DATA AVAILABILITY: A searchable and user-friendly format of the data in this study, specifically designed for rapid mining of single-cell RNA sequencing data, is available at https://lynnlab.shinyapps.io/Human_Islet_Atlas/ . The raw data files are available at NCBI Gene Expression Omnibus (GSE196715).

Spatial and transcriptional heterogeneity of pancreatic beta cell neogenesis revealed by a time-resolved reporter system.

AIMS/HYPOTHESIS: While pancreatic beta cells have been shown to originate from endocrine progenitors in ductal regions, it remains unclear precisely where beta cells emerge from and which transcripts define newborn beta cells. We therefore investigated characteristics of newborn beta cells extracted by a time-resolved reporter system. METHODS: We established a mouse model, 'Ins1-GFP; Timer', which provides spatial information during beta cell neogenesis with high temporal resolution. Single-cell RNA-sequencing (scRNA-seq) was performed on mouse beta cells sorted by fluorescent reporter to uncover transcriptomic profiles of newborn beta cells. scRNA-seq of human embryonic stem cell (hESC)-derived beta-like cells was also performed to compare newborn beta cell features between mouse and human. RESULTS: Fluorescence imaging of Ins1-GFP; Timer mouse pancreas successfully dissected newly generated beta cells as green fluorescence-dominant cells. This reporter system revealed that, as expected, some newborn beta cells arise close to the ducts (ßduct); unexpectedly, the others arise away from the ducts and adjacent to blood vessels (ßvessel). Single-cell transcriptomic analyses demonstrated five distinct populations among newborn beta cells, confirming spatial heterogeneity of beta cell neogenesis such as high probability of glucagon-positive ßduct, musculoaponeurotic fibrosarcoma oncogene family B (MafB)-positive ßduct and musculoaponeurotic fibrosarcoma oncogene family A (MafA)-positive ßvessel cells. Comparative analysis with scRNA-seq data of mouse newborn beta cells and hESC-derived beta-like cells uncovered transcriptional similarity between mouse and human beta cell neogenesis including microsomal glutathione S-transferase 1 (MGST1)- and synaptotagmin 13 (SYT13)-highly-expressing state. CONCLUSIONS/INTERPRETATION: The combination of time-resolved histological imaging with single-cell transcriptional mapping demonstrated novel features of spatial and transcriptional heterogeneity in beta cell neogenesis, which will lead to a better understanding of beta cell differentiation for future cell therapy. DATA AVAILABILITY: Raw and processed single-cell RNA-sequencing data for this study has been deposited in the Gene Expression Omnibus under accession number GSE155742.

Author Correction: Super-resolution microscopy compatible fluorescent probes reveal endogenous glucagon-like peptide-1 receptor distribution and dynamics.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Super-resolution microscopy compatible fluorescent probes reveal endogenous glucagon-like peptide-1 receptor distribution and dynamics.

The glucagon-like peptide-1 receptor (GLP1R) is a class B G protein-coupled receptor (GPCR) involved in metabolism. Presently, its visualization is limited to genetic manipulation, antibody detection or the use of probes that stimulate receptor activation. Herein, we present LUXendin645, a far-red fluorescent GLP1R antagonistic peptide label. LUXendin645 produces intense and specific membrane labeling throughout live and fixed tissue. GLP1R signaling can additionally be evoked when the receptor is allosterically modulated in the presence of LUXendin645. Using LUXendin645 and LUXendin651, we describe islet, brain and hESC-derived ß-like cell GLP1R expression patterns, reveal higher-order GLP1R organization including membrane nanodomains, and track single receptor subpopulations. We furthermore show that the LUXendin backbone can be optimized for intravital two-photon imaging by installing a red fluorophore. Thus, our super-resolution compatible labeling probes allow visualization of endogenous GLP1R, and provide insight into class B GPCR distribution and dynamics both in vitro and in vivo.