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Additional file 3: Figure S1. Ambient contribution and islet cell gene marker UMAP and violin plots in scRNA-seq and snRNA-seq in cultured human islets. (A,B) Box plots representing the levels of ambient RNA contamination in droplets of (A) scRNA-seq and (B) snRNA-seq datasets. (C) Violin plot representing the duplication rate in scRNA-seq (orange plot) and snRNA-seq (blue plot) methodologies. The rate was calculated by normalizing the average number of UMI per cell/nucleus on the average number of reads per cell/nucleus. (D, F, H, J) UMAP plots displaying expression levels of (D) GCG, (F) INS, (H) PPY, and (J) SST within the global distribution in scRNA-seq (left panels) and snRNA-seq (right panels). Expression levels are indicated as natural log of counts and range from 0 (gray) to 5 (purple). (E, G, I, K) Violin plots representing expression levels (natural log of counts, Y-axis) of (E) GCG, (G) INS, (I) PPY, and (K) SST within each cluster (X-axis) identified in scRNA-seq (orange plots) or snRNA-seq (blue plots) datasets. Figure S2. Correlation plots and fractional overlap estimation of islet cell types from scRNA-seq dataset with those from the reference dataset. (A) Scatter plots representing correlation of gene expression levels between scRNA-seq-derived (Y-axis) α-cells (first row from top), β-cells (second row from top), PP-cells (third row from top), and δ-cells (fourth row from top) and reference-derived (X-axis) α-cells (first column from left), β-cells (second column from left), PP-cells (third column from left) or δ-cells (fourth column from left). X-axis and Y-axis represent the expression levels in natural log of counts in the indicated datasets. The blue line in each plot represents the regression line, whose fit is indicated by the R2 value (the square of the Pearson correlation coefficient). The red circles indicate the islet cell specific marker genes driving the correlation between the same cell type from the two datasets. The red dotted squares highlight the correlation plots used in the main Fig. 3D. (B-E) Fractional overlap expressed in percentages (%, Y-axis) of the (B) top 100, (C) 200, (D) 500, or (E) 1000 genes between the indicated islet cell types from the reference dataset (X-axis) and the α-cells (yellow bars), β-cells (green bars), PP-cells (blue bars), or δ-cells (red bars) from the scRNA-seq dataset. Figure S3. Quality check parameters in the transplanted human islet snRNA-seq dataset. (A-D) Violin plots of (A) number of genes, (B) number of reads, (C) proportion of mitochondrial genes, and (D) proportion of mouse genes per nucleus across the 4 transplanted human islet samples in the snRNA-seq dataset. (E) Box plot of the levels of ambient RNA contamination in droplets of the in vivo snRNA-seq dataset within each human islet graft. (F) UMAP plot of nuclear cluster distribution and cell type prediction of in vivo snRNA-seq dataset following harmonization to the reference dataset. Figure S4. Islet cell type validation in human islet graft sections by immunofluorescence. Representative images of human islet cells identified as α-cells, β-cells or δ-cells according to the glucagon (GCG, green), insulin (INS, red) and somatostatin (SST, white) labeling. Nuclei are stained in blue. Scale bar is: 50 μm.

Additional file 1: Table S1. Characteristics of human islet donors and human islet preparations used for single-cell or single-nucleus transcriptomic analysis.

Additional file 2: Table S2. Number of different types of droplets, reads and genes generated by scRNA-seq and snRNA-seq in cultured or transplanted human islets.

Strategies to increase functional pancreatic beta cell mass is of great interest in diabetes-related research. TNF-related apoptosis-inducing ligand (TRAIL) is well known to promote proliferation and survival in various cell types, including vascular smooth muscle and endothelial cells. Correlation between the protective nature of TRAIL on these cells and its proliferative effect is noteworthy. TRAIL's seemingly protective/therapeutic effect in diabetes prompted us to question whether it may act as an inducer of proliferation in pancreatic beta cells. We used rat primary islet cells and MIN6 mouse beta cell line to investigate TRAIL-induced proliferation. Cell viability and/or death was analyzed by MTT, WST-1, and Annexin-V/PI assays, while proliferation rates and pathways were assessed via immunocytochemical and Western blot analyses. Receptor neutralization antibodies identified the mediator receptors. Recombinant soluble TRAIL (sTRAIL) treatment led to 1.6-fold increased proliferation in insulin-positive cells in dispersed rat islets compared to the untreated group, while adenovirus-mediated overexpression of TRAIL increased the number of proliferating beta cells up to more than six-fold. sTRAIL or adenoviral vector-mediated TRAIL overexpression induced proliferation in MIN6 cells also. TRAIL's proliferative effect was mediated via AKT activation, which was suppressed upon specific inhibition. Neutralization of each TRAIL receptor reversed the proliferative effect to some degree, with the highest level of inhibition in death receptor 5 (DR5) blockage in MIN6 cells and in decoy receptor 1 (DcR1) blockage in primary rat beta cells. Thus, TRAIL induces proliferation in rodent pancreatic beta cells through activation of the AKT pathway.

Moleküler görüntüleme, canlı organizmalardaki biyolojik olayların anlaşılmasını kolaylaştıran bir teknolojidir. Günümüzde belirteç gen ifadesinin girişimsel olmayan yöntemlerle in vivo olarak görüntülenmesi, cooled charge-coupled (CCD) kameraların kullanılmasıyla mümkündür. In vivo olarak belirteç gen ifadesinin takibi, hastalık modellerinde tedavi edici genin hedef hücredeki ifadesinin takip edilebilmesi açısından önemli bir yaklaşımdır. Belirteç gen ifadesinin organizmadaki ifade yeri, yoğunluğu ve süresi, girişimsel yöntemlere ihtiyaç duyulmaksızın belirlenebilmektedir.Bu çalışmada, BALB/c farelerdeki transgen ifadesini in vivo olarak görüntüleyebilmek için yeni bir cihaz olan CCD kameranın kullanımı amaçlandı. Bu nedenle yeşil floresan protein geni taşıyan adenoviral vektörler (AdEGFP), BALB/c farelerin kuyruk veninden sistemik olarak farklı dozlarda enjekte edildi. Vektör enjeksiyonundan sonra, belirli zaman aralıklarında farelerdeki AdEGFP aracılı transgen ifadesi CCD kamera ile görüntülendi.Sonuçlarımız, adenoviral vektörlerle sistemik gen transferi sonrasında transgen ifadesinin karaciğerde olduğunu ve sentez miktarının 4. gün en üst seviye ulaşarak sonraki günlerde azaldığını ve en az 30 gün boyunca CCD kamera ile takip edilebileceğini göstermiştir. Bunun yanı sıra, derin dokulardaki transgen sentezine bağlı sinyallerin, cerrahi yöntemler ile %36 daha kolay tespit edildiği gösterilmiştir. Bu bulgular, girişimsel olmayan görüntüleme tekniğinin canlı organizmalarda transgen ifadesinin yeri, miktarı ve süresi ile ilgili bilgi verici olduğunu göstermektedir. Molecular imaging is a technology that enhances our understanding of biological process in living organisms. Lately, noninvasive imaging of reporter gene expression in vivo became feasible by cooled charge-coupled device (CCD) camera. Tracing and quantifying the reporter gene expression in vivo is an important approach to monitor the expression of therapeutic genes in targeted tissues in disease models. Detection of the location, intensity, and time variation of reporter gene expression without need of invasive techniques is now possible.For this reason, in this study we wanted to apply a new light detection CCD camera for in vivo imaging of EGFP transgene expression in BALB/c mice. Various titers of first generation adenoviral vectors encoding enhanced green fluorescent protein (AdEGFP) was injected into BALB/c mice via tail-vein. After vector administration, AdEGFP mediated transgene expression was imaged at different time points by using a CCD camera.Our results showed that adenovirus delivered transgene expression was observed only in the liver after systemic vector administration. It peaked at day 4 and then remained detectable for at least 30 days by CCD camera. However, based on our results fluorescent signal detection in deep tissue could be enhanced 36% by surgical methods. These findings demonstrate that, noninvasive imaging provides functional data indicating the approximate location, magnitude, and duration of transgene expression for living organisms. 62

N 6 -methyladenosine (m 6 A) is the most abundant chemical modification in mRNA, and plays important roles in human and mouse embryonic stem cell pluripotency, maintenance, and differentiation. We have recently reported, for the first time, the role of m 6 A in the postnatal control of β-cell function in physiological states and in Type 1 and 2 Diabetes. However, the precise mechanisms by which m 6 A acts to regulate the development of human and mouse β-cells are unexplored. Here, we show that the m 6 A landscape is dynamic during human pancreas development, and that METTL14, one of the m 6 A writer complex proteins, is essential for the early differentiation of both human and mouse β-cells.

Type 1 Diabetes (T1D) is characterized by autoimmune-mediated destruction of insulin-producing β-cells. Several observations have renewed interest in the innate immune system as an initiator of the disease process against β-cells. Here, we show that N 6 -Methyladenosine (m 6 A) is an adaptive β-cell safeguard mechanism that accelerates mRNA decay of the 2'-5'-oligoadenylate synthetase (OAS) genes to control the antiviral innate immune response at T1D onset. m 6 A writer methyltransferase 3 (METTL3) levels increase drastically in human and mouse β-cells at T1D onset but rapidly decline with disease progression. Treatment of human islets and EndoC-βH1 cells with pro-inflammatory cytokines interleukin-1 β and interferon α mimicked the METTL3 upregulation seen at T1D onset. Furthermore, m 6 A-sequencing revealed the m 6 A hypermethylation of several key innate immune mediators including OAS1, OAS2, and OAS3 in human islets and EndoC-βH1 cells challenged with cytokines. METTL3 silencing in human pseudoislets or EndoC-βH1 cells enhanced OAS levels by increasing its mRNA stability upon cytokine challenge. Consistently, in vivo gene therapy, to prolong Mettl3 overexpression specifically in β-cells, delayed diabetes progression in the non-obese diabetic (NOD) mouse model of T1D by limiting the upregulation of Oas pointing to potential therapeutic relevance. Mechanistically, the accumulation of reactive oxygen species blocked METTL3 upregulation in response to cytokines, while physiological levels of nitric oxide promoted its expression in human islets. Furthermore, for the first time to our knowledge, we show that the cysteines in position C276 and C326 in the zinc finger domain of the METTL3 protein are sensitive to S-nitrosylation (SNO) and are significant for the METTL3 mediated regulation of OAS mRNA stability in human β-cells in response to cytokines. Collectively, we report that m 6 A regulates human and mouse β-cells to control the innate immune response during the onset of T1D and propose targeting METTL3 to prevent β-cell death in T1D.