Blockade of glucagon receptor induces α-cell hypersecretion by hyperaminoacidemia in mice

Abstract

Blockade of the glucagon receptor (GCGR) has been shown to improve glycemic control. However, this therapeutic approach also brings side effects, such as α-cell hyperplasia and hyperglucagonemia, and the mechanisms underlying these side effects remain elusive. Here, we conduct single-cell transcriptomic sequencing of islets from male GCGR knockout (GCGR-KO) mice. Our analysis confirms the elevated expression of Gcg in GCGR-KO mice, along with enhanced glucagon secretion at single-cell level. Notably, Vgf (nerve growth factor inducible) is specifically upregulated in α cells of GCGR-KO mice. Inhibition of VGF impairs the formation of glucagon immature secretory granules and compromises glucagon maturation, lead to reduced α-cell hypersecretion of glucagon. We further demonstrate that activation of both mTOR-STAT3 and ERK-CREB pathways, induced by elevated circulation amino acids, is responsible for upregulation of Vgf and Gcg expression following glucagon receptor blockade. Thus, our findings elucidate parts of the molecular mechanism underlying hyperglucagonemia in GCGR blockade.

Fig. 1. Characteristics of α cells from wild-type (WT) and glucagon receptor knockout (GCGR-KO) mouse islets.

a Schematic representation of the experimental workflow for single-cell RNA-sequencing (scRNA-seq) of WT and GCGR-KO mouse islet. b t-SNE visualization of scRNA-seq data from a total of 4399 α cells. 8 clusters are labeled with different colors as indicated on the right. c Analysis of cell number and distribution across different clusters. d Heatmap illustrating the number of interactions between various cell types. The colored scale bar indicates an increase (red) or decrease (blue) of interaction number in GCGR-KO islets compared to WT islets. e Bubble plot depicting the significantly altered ligand-receptor pairs contributing to signaling pathways from α, β, δ, pp cells to α cells. Red or blue in the color scale bar indicates an increase or decrease signal intensity in GCGR-KO islets relative to WT islets. f, g Effects of somatostatin-14 (SST-14) and insulin on glucose-stimulated glucagon secretion from WT (circles) and GCGR-KO (squares) islets. Islets were incubated in the presence of 1 mM glucose and varying concentrations of SST-14 or insulin for 1 h. Data are collected from 3 independent experiments and expressed as a percentage of maximal secretion, with secretion in the presence of 1 mM glucose alone defined as 100%. Data presented in (f, g) are mean ± SEM and analyzed by two-way ANOVA, followed by Bonferroni post-hoc test. p-values < 0.05 are displayed. Source data are provided as a Source Data file.

Fig. 2. Disruption of GCGR increases glucagon mRNA and protein levels in α cells.

a Violin and t-SNE plots illustrating the expression levels and distribution of Gcg mRNA in α cells. b Violin plot depicting Gcg expression across different α-cell subclusters. In a and b, the whiskers indicated the maximum and minimum values, the center indicated the median and the bound of the box indicated upper and lower quartiles. c Representative confocal microscopy images of pancreatic sections stained with anti-glucagon antibody. Scale bar, 50 μm. d Quantification of the average single α-cell area (WT, n = 4 mice; GCGR-KO, n = 4 mice). e Quantification of glucagon fluorescence intensity per α cell (WT, n = 4 mice; GCGR-KO, n = 4 mice). f, g Representative TEM images of α-cells from WT and GCGR-KO islets. Yellow dotted lines indicate cell boundaries, and gray or black dots indicate the glucagon granules. Scale bar, 5 μm. h Quantification of the number of glucagon granules per α cell, normalized to cell area. (WT, n = 3 mice; GCGR-KO, n = 3 mice). i Quantification of individual glucagon granule area (WT, n = 3 mice; GCGR-KO, n = 3 mice). j Density curve of individual glucagon granule areas (WT, n = 2313 granules; GCGR-KO, n = 3289 granules). Data presented in (d, e, h, i) are mean ± SEM, analyzed by an unpaired two-tailed t-test. p-values < 0.05 are displayed. Source data are provided as a Source Data file.

Fig. 3. Disruption of GCGR increases glucagon secretion in α cells.

a Measurement of glucagon secretion from isolated WT and CGGR-KO mouse islets. Data are derived from 3 biological replicates. b Fold change in glucagon secretion for each group. Data from (a) were normalized to the baseline (7 mM glucose) for each respective group. c Representative confocal microscopy images of WT and GCGR-KO α-cells before and after stimulation with 1 mM glucose + 10 μM adrenaline (adr). Glucagon granules are visualized by NPY-mCherry expression. Scale bar, 5 μm. d Average exocytosis as a function of time for WT and GCGR-KO α-cells as in (c). For WT, n = 8 cells/4 mice; for GCGR-KO, n = 9 cells/3 mice. Cells were stimulated with 1 mM glucose + 10 μM adrenaline from 1 to 5 min. e Variance in Fluo4 intensity when WT or GCGR-KO islets were perfused with different stimulation (as indicated). The arrow indicates α cells that started spiking after application of 1 mM glucose. Scale bar, 50 μm. f Pancreatic α-cell Ca²⁺ oscillation in response to a series of stimulations. In the heatmap, each column represents a time point, and each row represents one cell. The color scale ranges from red (high intensity) to blue (low intensity) (upper panel). The average Ca²⁺ oscillation of α-cells in response to a series of stimulations is shown in the time course (lower panel). Calcium influx responses for each α cell were normalized to the initial fluorescence intensity (20 mM glucose). For WT, n = 53 cells/3 mice; for GCGR-KO, n = 71 cells/3 mice. g Comparison of Ca²⁺ oscillation intensity in WT and GCGR-KO α-cell in response to indicated stimulations. The whiskers indicated the maximum and minimum values, the center indicated the median and the bound of the box indicated the upper and lower quartiles. Data presented in panels (a, b, d, g) are mean ± SEM. Data in (a, d, g) were analyzed using two-tailed unpaired t-tests. Data in (b) were analyzed by two-way ANOVA with Bonferroni’s post hoc test. p-values < 0.05 are displayed. Source data are provided as a Source Data file.

Fig. 4. Disruption of GCGR dramatically upregulates the glucagon granule component, VGF, in α cells.

a Violin plot showing the expression levels of Vgf in WT and GCGR-KO α cells. The whiskers indicated the maximum and minimum values, the center indicated the median and the bound of the box indicated the upper and lower quartiles. b Violin plot illustrating Vgf expression across all cell types. c Representative confocal microscopy images of VGF expression in pancreas from WT and GCGR-KO mice. Scale, 50 μm. d Quantification of VGF fluorescence intensity in α-cells from WT (n = 4 mice) and GCGR-KO (n = 4 mice) mouse pancreas sections. e Immunofluorescence staining of VGF and glucagon in αTC1-6 cells. Scale bar, 10 μm. f, g Representative confocal microscopy images of αTC1-6 cells transfected with sh-Control or sh-VGF adenovirus. In (f), cells were stained with anti-glucagon (green) and anti-VGF (red) antibodies. In (g), cells were stained with anti-glucagon (green) and anti-GM130 (red) antibodies. Scale bar, 10 μm. h Western blot analysis of the glucagon protein levels in αTC1-6 cells after VGF knockdown. Cells were stimulated with 1 mM glucose +10 μM adrenaline for 2 h. i Measurement of glucagon secretion from αTC1-6 cells at 1 mM glucose after VGF knockdown. Data are derived from 3 independent experiments. j Immunofluorescence staining of SCG2, CHGA and SCG3 in αTC1-6 cells. Scale bar, 10 μm. k Western blot analysis the SCG2, CHGA and SCG3 protein levels in αTC1-6 cells after VGF knockdown. l Quantification of SCG2, CHGA and SCG3 protein levels in (k). Values were normalized to GAPDH, and data are derived from 3 independent experiments. Data presented in (d, i, l) are mean ± SEM and were analyzed using two-tailed unpaired t-tests. p-values < 0.05 are displayed. Source data are provided as a Source Data file.

Fig. 5. Knockdown of VGF significantly abolishes glucagon secretion in vitro and in vivo.

a Representative confocal microscopy images of GCGR-KO islets transfected with sh-Control or sh-VGF adenovirus. Scale bar, 50 μm. b, c Quantification of α-cell VGF and glucagon fluorescence intensity in (a). For sh-Control, n = 9 islets; for sh-VGF, n = 8 islets. d Dynamic glucagon secretion profiles from perfused GCGR-KO mouse islets transfected with sh-Control or sh-VGF adenovirus. Islets were perfused with KRBH solution containing either 7 mM glucose or 1 mM glucose. Data are presented as mean values ± SEM. e Corresponding area under the curve (AUC) of glucagon secretion from ex vivo perfused islets of GCGR-KO mice. f Schematic diagram of VGF knockdown in vivo. GCGR-KO mice were intraperitoneally injected with AAV-sh-Control or AAV-sh-VGF. Samples were harvested and assessed 14 days post-injection. g Representative confocal microscopy images of VGF expression in pancreas from mice injected with AAV-sh-Control or AAV-sh-VGF. Scale bar, 50 μm. h Quantification of VGF fluorescent intensity in α-cells from (g). For sh-Control, n = 3 mice; for sh-VGF, n = 3 mice. i Average serum glucagon levels in WT (n = 3), GCGR-KO (n = 3), GCGR-KO injected with AAV-sh-Control (n = 4), and GCGR-KO injected with AAV-sh-Control (n = 4) mice. j Dynamic glucagon secretion profiles from perfused islets isolated from GCGR-KO mice injected with AAV-sh-Control or AAV-sh-VGF. Data are presented as mean values ± SEM. k Corresponding area under the curve (AUC) of glucagon secretion from ex vivo perfused islets in (j). Data presented in (b, c, e, h, i, k) are mean ± SEM. Data in (b, e, h, k) were analyzed using two-tailed unpaired t-tests. Data in (c) were analyzed by Mann Whitney test. Data in (i) were analyzed by one-way ANOVA with Bonferroni’s post hoc test. p-values < 0.05 are displayed. Source data are provided as a Source Data file.

Fig. 6. Amino acid induce VGF expression in α cells.

a Western blot analysis of VGF and pro-glucagon protein levels in αTC1-6 cells after incubation with WT or GCGR-KO serum for 72 h. b Quantification of VGF and pro-glucagon protein levels from (a). Values were normalized to GAPDH, and data were generated from 3 independent experiments. c Representative confocal microscopy images of pancreatic islets after 72 h incubation with WT or GCGR-KO serum. Scale bar, 50 μm. d Quantification of VGF fluorescence intensity in α cells of islets following serum treatment (WT serum, n = 11 islets; GCGR-KO serum, n = 13 islets). e Glucagon secretion levels from islets treated with WT or GCGR-KO serum. Serum-incubated islets were stimulated at different glucose concentrations for 1 h. Data were generated from 3 independent experiments. f Schematic diagram of serum amino acid measurement. Serum was collected from 6 WT or GCGR-KO mice. g Quantification of serum amino acid levels in WT and GCGR-KO mice. h Western blot analysis of VGF and pro-glucagon protein levels in αTC1-6 cells after incubation with 4 mM glutamine and alanine for 72 h. i Quantification of VGF and pro-glucagon protein levels in (h). Values were normalized to GAPDH, and data were generated from 4 independent experiments. j Representative confocal microscopy images of pancreatic islets after 72 h incubation with 4 mM glutamine and alanine. Scale bar, 50 μm. k Quantification of VGF fluorescence intensity in α cells of islets following amino acid treatment (Control, n = 8 islets; Gln+Ala, n = 8 islets). l Glucagon secretion levels from islets following 72 h treatments with indicated conditions and subsequent stimulated with different glucose concentrations for 1 h. Data were generated from 3 independent experiments. Data presented in (b, d, e, g, i, k, l) are mean ± SEM. Data in (b, d, e, g, i, k) were analyzed using two-tailed unpaired t-tests. Data in (l) were analyzed by two-way ANOVA with Bonferroni’s post hoc test. p-values < 0.05 are displayed. Source data are provided as a Source Data file.

Fig. 7. Amino acid induce VGF expression through STAT3 activation in α cells.

a Venn diagrams showing transcription factors that can bind to the VGF promoter, as identified in the animalTFDB3.0, GTRD and TFBIND databases. b Amino acids increased VGF promoter luciferase activity in αTC1-6 cells incubated with 4 mM glutamine and alanine for 72 h (n = 6). c Screening for transcription factors involved in amino acid-induced VGF promoter activity. αTC1-6 cells were transfected with indicated siRNA and incubated with amino acids for 72 h. Data were generated from 3 independent experiments. d Western blot analysis of p-STAT3-S727, p-STAT3-Y705 and total STAT3 protein levels in αTC1-6 cells incubated amino acids for 72 h. e Quantification of relevant protein levels in (d). Data were generated from 3 independent experiments. f Representative confocal images of p-STAT3-S727 expression in the pancreatic sections from WT or GCGR-KO mice. Scale bar indicates 50 μm. g Western blot analysis of p-STAT3-S727, STAT3, VGF and pro-glucagon protein levels in αTC1-6 cells treated with S3I-201 (STAT3 inhibitor). h Quantification of relevant protein levels in (g). Data were generated from 3 independent experiments. i. Representative confocal microscopy images of VGF and glucagon expression in αTC1-6 cells treated with amino acids alone or plus S3I-201 for 72 h. Scale bar, 10 μm. j VGF promoter activity in αTC1-6 cells transfected with empty vector, wild-type STAT3 or constitutively active STAT3 mutant (STAT3-S727D) for 72 h. Data were generated from 3 independent experiments. k Diagram of STAT3 binding sites at VGF promoter. l Chip-qPCR analysis of STAT3 binding activity at VGF promoter. Data were generated from 3 independent experiments. m Western blot analysis of protein levels after treatment with amino acids or amino acids plus rapamycin in αTC1−6 cells for 72 h. n Quantification of relevant protein levels in (m). Data were generated from 3 independent experiments. Data presented in (b, c, e, h, j, l, n) are mean ± SEM. Data in (b, e, l) were analyzed using two-tailed unpaired t-tests. Data in (c, h, j, n) were analyzed by one-way ANOVA with Bonferroni’s post hoc test. p-values < 0.05 are displayed. Source data are provided as a Source Data file.

Fig. 8. Working model for glucagon receptor blockade resulting in hyperglucagonemia.

a Upon glucagon receptor blockade, the organism increases its demand for glucagon. Several factors (particularly elevated amino acids), arise from the GCGR-deficient liver and act on pancreatic islets, leading to α cell hyperplasia and enhanced α cell secretion. All these changes collectively contribute to hyperglucagonemia. b Increased circulating amino acids (especially glutamine and alanine) activate the mTOR-STAT3 and ERK-CREB signaling pathways. STAT3 enhances VGF transcription, while CREB promotes both VGF and GCG expression. Consequently, glucagon granule biogenesis and glucagon secretion are significantly increased. Conversely, blocking amino acid-induced VGF expression by inhibiting mTOR or STAT3 activation reduces levels of the glucagon granule component VGF, thereby decreasing glucagon granule biogenesis and glucagon secretion.