Loss of GIPR in LEPR cells impairs glucose control by GIP and GIP:GLP-1 co-agonism without affecting body weight and food intake in mice.

OBJECTIVE: The glucose-dependent insulinotropic polypeptide (GIP) decreases body weight via central GIP receptor (GIPR) signaling, but the underlying mechanisms remain largely unknown. Here, we assessed whether GIP regulates body weight and glucose control via GIPR signaling in cells that express the leptin receptor (Lepr). METHODS: Hypothalamic, hindbrain, and pancreatic co-expression of Gipr and Lepr was assessed using single cell RNAseq analysis. Mice with deletion of Gipr in Lepr cells were generated and metabolically characterized for alterations in diet-induced obesity (DIO), glucose control and leptin sensitivity. Long-acting single- and dual-agonists at GIPR and GLP-1R were further used to assess drug effects on energy and glucose metabolism in DIO wildtype (WT) and Lepr-Gipr knock-out (KO) mice. RESULTS: Gipr and Lepr show strong co-expression in the pancreas, but not in the hypothalamus and hindbrain. DIO Lepr-Gipr KO mice are indistinguishable from WT controls related to body weight, food intake and diet-induced leptin resistance. Acyl-GIP and the GIPR:GLP-1R co-agonist MAR709 remain fully efficacious to decrease body weight and food intake in DIO Lepr-Gipr KO mice. Consistent with the demonstration that Gipr and Lepr highly co-localize in the endocrine pancreas, including the ß-cells, we find the superior glycemic effect of GIPR:GLP-1R co-agonism over single GLP-1R agonism to vanish in Lepr-Gipr KO mice. CONCLUSIONS: GIPR signaling in cells/neurons that express the leptin receptor is not implicated in the control of body weight or food intake, but is of crucial importance for the superior glycemic effects of GIPR:GLP-1R co-agonism relative to single GLP-1R agonism.

Insulin regulates human pancreatic endocrine cell differentiation in vitro.

OBJECTIVE: The consequences of mutations in genes associated with monogenic forms of diabetes on human pancreas development cannot be studied in a time-resolved fashion in vivo. More specifically, if recessive mutations in the insulin gene influence human pancreatic endocrine lineage formation is still an unresolved question. METHODS: To model the extremely reduced insulin levels in patients with recessive insulin gene mutations, we generated a novel knock-in H2B-Cherry reporter human induced pluripotent stem cell (iPSC) line expressing no insulin upon differentiation to stem cell-derived (SC-) ß cells in vitro. Differentiation of iPSCs into the pancreatic and endocrine lineage, combined with immunostaining, Western blotting and proteomics analysis phenotypically characterized the insulin gene deficiency in SC-islets. Furthermore, we leveraged FACS analysis and confocal microscopy to explore the impact of insulin shortage on human endocrine cell induction, composition, differentiation and proliferation. RESULTS: Interestingly, insulin-deficient SC-islets exhibited low insulin receptor (IR) signaling when stimulated with glucose but displayed increased IR sensitivity upon treatment with exogenous insulin. Furthermore, insulin shortage did not alter neurogenin-3 (NGN3)-mediated endocrine lineage induction. Nevertheless, lack of insulin skewed the SC-islet cell composition with an increased number in SC-ß cell formation at the expense of SC-α cells. Finally, insulin deficiency reduced the rate of SC-ß cell proliferation but had no impact on the expansion of SC-α cells. CONCLUSIONS: Using iPSC disease modelling, we provide first evidence of insulin function in human pancreatic endocrine lineage formation. These findings help to better understand the phenotypic impact of recessive insulin gene mutations during pancreas development and shed light on insulin gene function beside its physiological role in blood glucose regulation.

NEUROD2 function is dispensable for human pancreatic ß cell specification.

Introduction: The molecular programs regulating human pancreatic endocrine cell induction and fate allocation are not well deciphered. Here, we investigated the spatiotemporal expression pattern and the function of the neurogenic differentiation factor 2 (NEUROD2) during human endocrinogenesis. Methods: Using Crispr-Cas9 gene editing, we generated a reporter knock-in transcription factor (TF) knock-out human inducible pluripotent stem cell (iPSC) line in which the open reading frame of both NEUROD2 alleles are replaced by a nuclear histone 2B-Venus reporter (NEUROD2nVenus/nVenus). Results: We identified a transient expression of NEUROD2 mRNA and its nuclear Venus reporter activity at the stage of human endocrine progenitor formation in an iPSC differentiation model. This expression profile is similar to what was previously reported in mice, uncovering an evolutionarily conserved gene expression pattern of NEUROD2 during endocrinogenesis. In vitro differentiation of the generated homozygous NEUROD2nVenus/nVenus iPSC line towards human endocrine lineages uncovered no significant impact upon the loss of NEUROD2 on endocrine cell induction. Moreover, analysis of endocrine cell specification revealed no striking changes in the generation of insulin-producing b cells and glucagon-secreting a cells upon lack of NEUROD2. Discussion: Overall, our results suggest that NEUROD2 is expendable for human b cell formation in vitro.

Glucose-dependent insulinotropic polypeptide regulates body weight and food intake via GABAergic neurons in mice.

The development of single-molecule co-agonists for the glucagon-like peptide-1 (GLP-1) receptor (GLP-1R) and glucose-dependent insulinotropic polypeptide (GIP) receptor (GIPR) is considered a breakthrough in the treatment of obesity and type 2 diabetes. But although GIPR-GLP-1R co-agonism decreases body weight with superior efficacy relative to GLP-1R agonism alone in preclinical1-3 and clinical studies4,5, the role of GIP in regulating energy metabolism remains enigmatic. Increasing evidence suggests that long-acting GIPR agonists act in the brain to decrease body weight through the inhibition of food intake3,6-8; however, the mechanisms and neuronal populations through which GIP affects metabolism remain to be identified. Here, we report that long-acting GIPR agonists and GIPR-GLP-1R co-agonists decrease body weight and food intake via inhibitory GABAergic neurons. We show that acyl-GIP decreases body weight and food intake in male diet-induced obese wild-type mice, but not in mice with deletion of Gipr in Vgat(also known as Slc32a1)-expressing GABAergic neurons (Vgat-Gipr knockout). Whereas the GIPR-GLP-1R co-agonist MAR709 leads, in male diet-induced obese wild-type mice, to greater weight loss and further inhibition of food intake relative to a pharmacokinetically matched acyl-GLP-1 control, this superiority over GLP-1 vanishes in Vgat-Gipr knockout mice. Our data demonstrate that long-acting GIPR agonists crucially depend on GIPR signaling in inhibitory GABAergic neurons to decrease body weight and food intake.

Delineating mouse ß-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 ß-cell ablation model. The ß-cell landscape of MIA reveals new cell states during disease progression and cross-publication differences between previously suggested marker genes. We show that ß-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 ß-cells. We also report pathways that are shared between ß-cells in immature, aged and diabetes models. MIA enables a comprehensive analysis of ß-cell responses to different stressors, providing a roadmap for the understanding of ß-cell plasticity, compensation and demise.

Synaptotagmin-13 orchestrates pancreatic endocrine cell egression and islet morphogenesis.

During pancreas development endocrine cells leave the ductal epithelium to form the islets of Langerhans, but the morphogenetic mechanisms are incompletely understood. Here, we identify the Ca2+-independent atypical Synaptotagmin-13 (Syt13) as a key regulator of endocrine cell egression and islet formation. We detect specific upregulation of the Syt13 gene and encoded protein in endocrine precursors and the respective lineage during islet formation. The Syt13 protein is localized to the apical membrane of endocrine precursors and to the front domain of egressing endocrine cells, marking a previously unidentified apical-basal to front-rear repolarization during endocrine precursor cell egression. Knockout of Syt13 impairs endocrine cell egression and skews the α-to-ß-cell ratio. Mechanistically, Syt13 is a vesicle trafficking protein, transported via the microtubule cytoskeleton, and interacts with phosphatidylinositol phospholipids for polarized localization. By internalizing a subset of plasma membrane proteins at the front domain, including α6ß4 integrins, Syt13 modulates cell-matrix adhesion and allows efficient endocrine cell egression. Altogether, these findings uncover an unexpected role for Syt13 as a morphogenetic driver of endocrinogenesis and islet formation.

GLP-1-mediated delivery of tesaglitazar improves obesity and glucose metabolism in male mice.

Dual agonists activating the peroxisome proliferator-activated receptors alpha and gamma (PPARɑ/ɣ) have beneficial effects on glucose and lipid metabolism in patients with type 2 diabetes, but their development was discontinued due to potential adverse effects. Here we report the design and preclinical evaluation of a molecule that covalently links the PPARɑ/ɣ dual-agonist tesaglitazar to a GLP-1 receptor agonist (GLP-1RA) to allow for GLP-1R-dependent cellular delivery of tesaglitazar. GLP-1RA/tesaglitazar does not differ from the pharmacokinetically matched GLP-1RA in GLP-1R signalling, but shows GLP-1R-dependent PPARɣ-retinoic acid receptor heterodimerization and enhanced improvements of body weight, food intake and glucose metabolism relative to the GLP-1RA or tesaglitazar alone in obese male mice. The conjugate fails to affect body weight and glucose metabolism in GLP-1R knockout mice and shows preserved effects in obese mice at subthreshold doses for the GLP-1RA and tesaglitazar. Liquid chromatography-mass spectrometry-based proteomics identified PPAR regulated proteins in the hypothalamus that are acutely upregulated by GLP-1RA/tesaglitazar. Our data show that GLP-1RA/tesaglitazar improves glucose control with superior efficacy to the GLP-1RA or tesaglitazar alone and suggest that this conjugate might hold therapeutic value to acutely treat hyperglycaemia and insulin resistance.

CellRank for directed single-cell fate mapping.

Computational trajectory inference enables the reconstruction of cell state dynamics from single-cell RNA sequencing experiments. However, trajectory inference requires that the direction of a biological process is known, largely limiting its application to differentiating systems in normal development. Here, we present CellRank ( https://cellrank.org ) for single-cell fate mapping in diverse scenarios, including regeneration, reprogramming and disease, for which direction is unknown. Our approach combines the robustness of trajectory inference with directional information from RNA velocity, taking into account the gradual and stochastic nature of cellular fate decisions, as well as uncertainty in velocity vectors. On pancreas development data, CellRank automatically detects initial, intermediate and terminal populations, predicts fate potentials and visualizes continuous gene expression trends along individual lineages. Applied to lineage-traced cellular reprogramming data, predicted fate probabilities correctly recover reprogramming outcomes. CellRank also predicts a new dedifferentiation trajectory during postinjury lung regeneration, including previously unknown intermediate cell states, which we confirm experimentally.