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, 1 (8), 765-774

M 6 A mRNA Methylation Regulates Human β-Cell Biology in Physiological States and in Type 2 Diabetes

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M 6 A mRNA Methylation Regulates Human β-Cell Biology in Physiological States and in Type 2 Diabetes

Dario F De Jesus et al. Nat Metab.

Abstract

The regulation of islet cell biology is critical for glucose homeostasis1.N6 -methyladenosine (m6A) is the most abundant internal messenger RNA (mRNA) modification in mammals2. Here we report that the m6A landscape segregates human type 2 diabetes (T2D) islets from controls significantly better than the transcriptome and that m6A is vital for β-cell biology. m6A-sequencing in human T2D islets reveals several hypomethylated transcripts involved in cell-cycle progression, insulin secretion, and the Insulin/IGF1-AKT-PDX1 pathway. Depletion of m6A levels in EndoC-βH1 induces cell-cycle arrest and impairs insulin secretion by decreasing AKT phosphorylation and PDX1 protein levels. β-cell specific Mettl14 knock-out mice, which display reduced m6A levels, mimic the islet phenotype in human T2D with early diabetes onset and mortality due to decreased β-cell proliferation and insulin degranulation. Our data underscore the significance of RNA methylation in regulating human β-cell biology, and provide a rationale for potential therapeutic targeting of m6A modulators to preserve β-cell survival and function in diabetes.

Conflict of interest statement

COMPETING FINANCIAL INTERESTS C.H. is a scientific founder and a member of the scientific advisory board of Accent Therapeutics Inc. The remaining authors have no conflicts of interest.

Figures

Figure 1:
Figure 1:. RNA N6-methyladenosine sequencing reveals a homogeneous m6A decoration in human type 2 diabetic islets.
a, PCA plot of RNA-sequencing after regressing out batch, gender and age in Controls (red dots, n=7 independent biological samples) and type 2 diabetic islets (T2D, blue squares, n=8 independent biological samples). b, Heat-map visualization of differential expressed genes in Controls versus T2D islets. c, PCA plot of m6A-sequencing after regressing out the batch and gender effects in Controls (red dots, n=7 independent biological samples) and T2D islets (T2D, blue squares, n=8 independent biological samples). d, Heat-map visualization of differential methylated loci in Controls versus T2D islets. e, The gene expression variability of β-cells represented by the coefficient of variation from single-cell RNA sequencing data (GSE81608) in human dispersed islets comparing Controls (n=12 independent biological samples) and T2D patients (n=6 independent biological samples). The stratification of m6A-modified vs. non-m6A-modified gene is based on our patient m6A-sequencing data. Box plot shows the median, box edges show first and third quartiles and whiskers show the minimum and maximum. P-values were calculated using Mann-Whitney-Wilcoxon test. f, Histogram of log-fold change showing the distribution of differential m6A loci fold changes from Controls versus T2D. g, Gene-ontology (GO) analyses of differently m6A-methylated genes in T2D (=8 independent biological samples) versus Control (n=7 independent biological samples) islets. P-values were calculated according to the hypergeometric test based on the number of physical entities present in both the predefined set and user-specified list of physical entities. h, Representation of Insulin/IGF1 pathway and induction of PDX1 expression based on KEEG and Wikipathway annotations depicting several m6A hypomethylated genes (red shade) and unchanged genes (grey shade) in T2D as compared to Controls (genes filtered for FDR<0.05). I, Coverage plots of m6A peaks in PDX1 gene comparing T2D (=8 independent biological samples) versus Controls (n=7 independent biological samples). Plotted coverages are the median of the n replicates presented.
Figure 2:
Figure 2:. m6A controls PDX1 expression and modulates Insulin/IGF1-mediated AKT phosphorylation.
a, Venn diagram representation of the intersection between differently methylated genes in T2D human islets and differentially expressed genes in METTL3 KD and METTL14 KD in EndoC-βH1 (Human islets: Controls, n=7 independent biological samples; T2D, n=8 independent biological samples. EndoC-βH1 cells: n=3 independent experiments/group). Statistical analyses was performed using Benjamini-Hochberg procedure and genes were filtered for FDR<0.10. b, Enriched-GO and pathway analyses of intersected genes (Human islets: Controls, n=7 independent biological samples; T2D, n=8 independent biological samples. EndoC-βH1 cells: n=3 independent experiments/group). P-values were calculated according to the hypergeometric test based on the number of physical entities present in both the predefined set and user-specified list of physical entities. c, Western-blot analyses of indicated proteins after IGF1 stimulation in METTL3 KD in EndoC-βH1 cells (n=3 independent experiments/group/condition). d, Protein quantification of indicated protein after IGF1 stimulation in METTL3 KD. e, Western-blot analyses of indicated proteins after IGF1 stimulation in METTL14 KD EndoC-βH1 cells (n=3 independent experiments/group/condition). f, Protein quantification of indicated proteins after IGF1 stimulation in METTL14 KD. g, Western-blot analyses of indicated proteins after insulin stimulation in METTL3 KD (n=3 independent experiments/group/condition). h, Protein quantification of indicated protein after insulin stimulation in METTL3 KD. i, Western-blot analyses of indicated proteins after insulin stimulation in METTL14 KD (n=3 independent experiments/group/condition). j, Protein quantification of indicated proteins after insulin stimulation in METTL14 KD. k, Coverage plot of m6A peaks in PDX1 gene depicting hypomethylation after METTL3 or METTL14 KD in EndoC-βH1 (n=3 independent experiments/group, FDR<0.05). l, Western-blot analyses of PDX1 protein levels in stable METTL3 KD, METTL14 KD or (METTL3 + METTL14) KD (n=3 independent experiments/group). m, PDX1 protein quantification. n, Western-blot analyses of indicated proteins after DMSO or SC79 stimulation in METTL3 KD for 48h (n=3 independent experiments/group/condition). o, PDX1 protein quantifications. Data are represented as mean ± SEM. Statistical analyses by Two-way ANOVA with Fisher’s LSD test (in d,f,h,j,m and o).
Figure 3:
Figure 3:. β-cell specific Mettl14 knock-out (KO) results in early diabetes and mortality secondary to decreased Pdx-1 expression and decreased phosphorylation of AKT.
a, Body weight trajectories of Controls (black dots) and Mettl14 KO mice (M14KO) (red dots) (1 month: n=9 independent biological samples in Controls and M14KO; 2 months: n=8 independent biological samples in Controls and n=9 independent biological samples in M14KO; 3 months: n=10 independent biological samples in Controls and n=8 independent biological samples in M14KO). b, Random-fed blood glucose levels in Controls and M14KO (1 month: n=9 independent biological samples in Controls and M14KO; 2 months: n=8 independent biological samples in Controls and M14KO; 3 months: n=10 independent biological samples in Controls and n=8 independent biological samples in M14KO). c, Blood glucose levels after a glucose tolerance test in 2 month-old Controls (black line) and M14KO (red line) (n=6 animals/group). d, Serum insulin levels after an in vivo glucose-stimulated insulin secretion assay in 2 month old Controls (black line) and M14KO (red line) (n=4 animals/group). e, Serum C-peptide levels after an in vivo glucose-stimulated insulin secretion assay in 2 month-old Controls (black line) and M14KO (red line) (n=4 animals/group). f, Blood glucose levels after an insulin tolerance test in 2 month-old Controls (black line) and M14KO (red line) (n=6 animals/group). g, Representative pictures of immunofluorescence staining of insulin (red), somatostatin (green) and glucagon (blue) in pancreas sections from Controls and M14KO (n=3–5 animals/group). h, β-cell mass quantification in Controls and M14KO (1 month: n=4 independent biological samples in Controls and M14KO; 2 months: n=3 independent biological samples in Controls and M14KO; 3 months: n=5 independent biological samples in Controls and n=3 independent biological samples in M14KO). i, Representative pictures of immunofluorescence staining of Ki67 (green), insulin (red) and DAPI (blue) in pancreas sections from Controls and M14KO mice (n=3–5 animals/group). j, β-cell proliferation quantification in Controls and M14KO mice (1 month: n=4 independent biological samples in Controls and M14KO; 2 months: n=3 independent biological samples in Controls and M14KO; 3 months: n=5 independent biological samples in Controls and n=3 independent biological samples in M14KO). k, Representative pictures of immunofluorescence staining of Pdx1 (green), insulin (red) and DAPI (blue) in pancreas sections from Controls and M14KO (n=3–5 animals/group). l, Quantification of Pdx1+/Insulin+ cells in pancreas sections from Controls and M14KO (1 month: n=4 independent biological samples in Controls and M14KO; 2 months: n=3 independent biological samples in Controls and M14KO; 3 months: n=5 independent biological samples in Controls and n=3 independent biological samples in M14KO). m, Representative images of electron microscopic analyses of islet cell ultrastructure in 1 and 3 month-old Controls and M14KO (n=3 animals/group). Red arrows point to insulin granules that are degranulated in M14KO compared to Controls. Yellow arrow refers to the presence of nuclear membrane swelling in M14KO as compared to Controls (left two panels). Blue arrow points to enlarged mitochondria in M14KO as compared to Controls (right two panels). n, qRT-PCR analyses of the cell cycle, function and identity genes in whole islets isolated from 2 month old Controls (n=3 animals) and M14KO (n=6 animals). o, Western Blot analyses of indicated proteins in whole islets isolated from 2 months old Controls (n=3 pools, 2 animals/pool) and M14KO (n=3 pools, 4 animals/pool). p, Quantifications of indicated proteins. Data are represented as mean ± SEM. In all panels statistical analyses were performed by two-sided unpaired multiple t-tests and corrected for multiple comparisons using the Holm-Sidak method. Scale bar = 100 μm.
Figure 4:
Figure 4:. Functional protein-protein interaction network analyses reveal the central role of AKT in controlling the effects of Mettl14 ablation in β-cells.
a, Volcano-plot representation of differentially expressed genes by RNA-sequencing in FACS-sorted β-cells from M14KO compared to Controls (Controls, n=4 pools, 2 animals/pool; M14KO, n=4 pools, 4 animals/pool). Statistical analyses was performed using Benjamini-Hochberg procedure and genes were filtered for FDR<0.10. b, Enriched pathway analyses of significantly altered genes between M14KO and Controls (Controls, n=4 pools, 2 animals/pool; M14KO, n=4 pools, 4 animals/pool) (genes filtered for FDR<0.10) (p-values were calculated according to the hypergeometric test based on the number of physical entities present in both the predefined set and user-specified list of physical entities). c, Representation of altered genes in β-cells from M14KO compared to Controls (Controls, n=4 pools, 2 animals/pool; M14KO, n=4 pools, 4 animals/pool). Box plot shows the median, box edges show first and third quartiles and whiskers show the minimum and maximum. d, Volcano-plot representation of altered phosphosites by phospho-antibody microarrays in whole islets from M14KO compared to Controls (Controls, n=4 animals; M14KO, n=2 pools, 4 animals/pool). Statistical analyses were performed by using moderated t-tests with linear models for microarray data. e, Enriched pathway analyses of significantly altered phosphosites between M14KO and Controls (Controls, n=4 animals; M14KO, n=2 pools, 4 animals/pool) (genes filtered for p<0.05). f, Representation of altered phosphosites in M14KO islets compared to Controls (Controls, n=4 animals; M14KO, n=2 pools, 4 animals/pool). Box plot shows the median, box edges show first and third quartiles and whiskers show the minimum and maximum. g, Functional protein-protein interaction network of significantly altered phosphosites in M14KO compared to Controls. Different colors represent network nodes. h, Model depicting the effect of decreased expression of m6A modulators in type 2 diabetes: a) induces a generalized state of hypomethylation and downregulation of PDX1 and, b) increases expression of negative regulators of AKT, leading to decreased phosphorylation of AKT and consequent cell-cycle arrest and impaired insulin secretion.

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