Fig 2: Generation of a disease model of neonatal diabetes caused by insulin mutations.(A) 24 hr glucose sensor curves of a newborn carrying the INS C96R mutation showing deterioration of glycemic control during the first 3 months of life. (B) Proinsulin model depicting the mutated disulphide bridge-forming cysteines. (C) Mutation correction strategy mediated by CRISPR/Cas9 stimulated homology directed repair, resulting in four INS C96R mutation corrected iPSC clones. (D) Flow cytometry for definitive endoderm marker CXCR4 on day 3 of differentiation of INS mutant and corrected cells lines (n = 1–7 independent differentiation experiments per cell line). (E) Flow cytometry for PDX1, NKX6.1 and INS on Stage 7 of differentiation (n = 3–16 independent differentiation experiments). (F) Whole-mount immunostaining for the pancreatic transcription factors PDX1 and NKX6.1 and islet hormones glucagon (GCG) and INS of Stage 7 differentiated islet-like clusters. Scale bars = 100 µm. Data represent mean ± SEM. **p < 0.01, Student’s t test.

Fig 3: Altered endocrine cell proportions and reduced PDX1 expression in INS mutant grafts.(A) Immunohistochemistry for endocrine hormones glucagon (GCG), insulin (INS), chromogranin A (CHGA), C-peptide (CPEP), pancreatic polypeptide (PP), ghrelin (GHRL), somatostatin (SST), transcription factors PDX1 and NKX6.1, and proliferation marker MK67 (KI67) on 3 months old grafts. Scale bars = 100 µm. (B) Quantification of immunohistochemistry presented in (A) for proportions of monohormonal cells in 3 months old grafts. (n = 4–5, Student’s t test for all except for GHRL where Mann-Whitney test was used) (C) Proportions of polyhormonal cells in 3 months old grafts. (D) Quantification of immunohistochemistry presented in (A). Percentage of c-peptide/insulin positive cells expressing PDX1, NKX6.1 or KI67 in 3 months old grafts (n = 5–6 independent transplanted animals per genotype, Student’s t test with Welch’s correction). (E) Dynamic changes in the percentage of insulin positive cells expressing KI67 between Stage 7 and 6 months old grafts (n = 4–6; Student’s t test). (F) Dynamic changes in the percentage of insulin positive cells expressing PCNA between Stage 7 and 6 months old grafts (n = 4–6; Student’s t test). Data represents individual values and mean ± SEM. See also Figure 5—figure supplement 1.

Fig 4: Proinsulin and C-peptide in the hypothalamus are localized in the PVN neuronal somata and ME neurosecretory nerve terminals, respectively.(A–D) In situ hybridization images. PVN sections were incubated with the Ins2 antisense probe (A, low magnification; B and C, high magnification) or with the Ins2 sense probe (D). (E and F) An immunofluorescence image showing the presence of proinsulin immunoreactivity in the PVN of WT mice (E). The specificity of the proinsulin antibody (R&D Systems, Bio-Techne, MAB13361) was validated in the PVN sections from Ins2-KO mice (F). (G) A confocal image of double immunostaining for proinsulin and the neuronal marker NeuN in the PVN. Solid arrowheads show colocalization. (H–J) Immunofluorescence images showing the presence of C-peptide immunoreactivity in the ME of WT mice (H, low magnification; I, high magnification). The specificity of the C-peptide antibody (Cell Signaling Technology, 4593) was validated in the ME sections from Ins2-KO mice (J). (K) A confocal image of double immunostaining for C-peptide and the presynaptic marker synapsin in the ME. (L and M) Confocal images of double immunostaining of proinsulin with CRH (L) or SST (M) in the PVN. Open arrowheads indicate single proinsulin labeling. Solid arrowheads show colocalization. (N and O) Confocal images of double immunostaining of C-peptide with CRH (N) or SST (O) in the ME. Solid arrowheads indicate colocalization. (P) The percentage of proinsulin-positive cells coexpressing CRH or SST in the PVN. (Q and R) Fluorescence intensity of C-peptide and CRH (Q) or SST (R) along white arrows in the enlarged images in (N) and (O), respectively. Data are shown as mean ± SEM, n = 3 or 4 mice/group. Scale bars: 200 µm (A), 100 µm (H and J), 50 µm (E–G and L–O), 20 µm (B–D, I, and K; high-magnification inset images in L–O), 10 µm (high-magnification inset images in G), 5 µm (high-magnification inset images in K). 3V, third ventricle; PVN, paraventricular nucleus; Arc, arcuate nucleus; ME, median eminence.

Fig 5: Single cell RNA sequencing revealed increased ER-stress and reduced proliferation in INS mutant beta-like cells.(A) Single cell RNAseq clustering analysis of Stage 7 islet-like aggregates cells derived from both INS C96R and INS corrected iPSC. A total of 1991 post-QC cells mapped to the Baron et al. (2016) dataset were used for clustering. Four distinct clusters were identified: beta-like cells (308 cells), endocrine progenitor cells (236 cells), alpha-like cells (1252 cells) and proliferating alpha-like cells (45 cells). (B) Violin plots showing log-normalized expression of selected marker genes for each cluster. See also Supplementary file 1 – Table 2. (C) Expression of INS in the different cell populations clusters. (D) Volcano plots illustrate the differentially expressed genes between INS C96R and INS corrected cells in beta-like and progenitor clusters. Violin plots show the relative expression of INS, unfolded protein response (UPR) gene HSPA5 (BIP), proliferation and oxidative phosphorylation related genes that are differentially expressed (fold change = 1.3, adjusted p value < 0.05) between INS C96R and INS corrected cells in the beta-like and progenitor clusters. See also Supplementary file 1 – Table 3. (E) Differentiation trajectory inferred from pseudotime analysis of the beta-like and progenitor clusters. (F) Heatmaps show the normalized, smoothed expression of INS, proliferation (red) and ER-stress (yellow) genes that are differentially regulated across pseudotime between INS C96R and INS corrected cells.10.7554/eLife.38519.012Figure 2—source data 1.Single-cell RNA-seq gene count matrices and alignment statistics.10.7554/eLife.38519.014Figure 2—source data 2.HALLMARK_APOPTOSIS and curated C2 gene sets from Broad Institute’s Molecular Signatures Database (MSigDB).