In Vitro Disease Models of the Endocrine Pancreas

Transcriptomic profiling analysis of the effect of palmitic acid on 3D spheroids of β-like cells derived from induced pluripotent stem cells

Type 2 diabetes (T2D) is posing a serious public health concern with a considerable impact on human life and health expenditures worldwide. The disease develops when insulin plasma level is insufficient for coping insulin resistance, caused by the decline of pancreatic β-cell function and mass. In β-cells, the lipotoxicity exerted by saturated free fatty acids in particular palmitate (PA), which is chronically elevated in T2D, plays a major role in β-cell dysfunction and mass. However, there is a lack of human relevant in vitro model to identify the underlying mechanism through which palmitate induces β-cell failure. In this frame, we have previously developed a cutting-edge 3D spheroid model of β-like cells derived from human induced pluripotent stem cells. In the present work, we investigated the signaling pathways modified by palmitate in β-like cells derived spheroids. When compared to the 2D monolayer cultures, the transcriptome analysis (FDR set at  0.1) revealed that the 3D spheroids upregulated the pancreatic markers (such as GCG, IAPP genes), lipids metabolism and transporters (CD36, HMGSC2 genes), glucose transporter (SLC2A6). Then, the 3D spheroids are exposed to PA 0.5 mM for 72 h. The differential analysis demonstrated that 32 transcription factors and 135 target genes were mainly modulated (FDR set at  0.1) including the upregulation of lipid and carbohydrates metabolism (HMGSC2, LDHA, GLUT3), fibrin metabolism (FGG, FGB), apoptosis (CASP7). The pathway analysis using the 135 selected targets extracted the fibrin related biological process and wound healing in 3D PA treated conditions. An overall pathway gene set enrichment analysis, performed on the overall gene set (with pathway significance cutoff at 0.2), highlighted that PA perturbs the citrate cycle, FOXO signaling and Hippo signaling as observed in human islets studies. Additional RT-PCR confirmed induction of inflammatory (IGFBP1, IGFBP3) and cell growth (CCND1, Ki67) pathways by PA. All these changes were associated with unaffected glucose-stimulated insulin secretion (GSIS), suggesting that they precede the defect of insulin secretion and death induced by PA. Overall, we believe that our data demonstrate the potential of our spheroid 3D islet-like cells to investigate the pancreatic-like response to diabetogenic environment.

LncRNA ARGI Contributes to Virus-Induced Pancreatic β Cell Inflammation Through Transcriptional Activation of IFN-Stimulated Genes

Type 1 diabetes (T1D) is a complex autoimmune disease that develops in genetically susceptible individuals. Most T1D-associated single nucleotide polymorphisms (SNPs) are located in non-coding regions of the human genome. Interestingly, SNPs in long non-coding RNAs (lncRNAs) may result in the disruption of their secondary structure, affecting their function, and in turn, the expression of potentially pathogenic pathways. In the present work, the function of a virus-induced T1D-associated lncRNA named ARGI (Antiviral Response Gene Inducer) is characterized. Upon a viral insult, ARGI is upregulated in the nuclei of pancreatic β cells and binds to CTCF to interact with the promoter and enhancer regions of IFNβ and interferon-stimulated genes, promoting their transcriptional activation in an allele-specific manner. The presence of the T1D risk allele in ARGI induces a change in its secondary structure. Interestingly, the T1D risk genotype induces hyperactivation of type I IFN response in pancreatic β cells, an expression signature that is present in the pancreas of T1D patients. These data shed light on the molecular mechanisms by which T1D-related SNPs in lncRNAs influence pathogenesis at the pancreatic β cell level and opens the door for the development of therapeutic strategies based on lncRNA modulation to delay or avoid pancreatic β cell inflammation in T1D.

Overview of Transcriptomic Research on Type 2 Diabetes: Challenges and Perspectives

Type 2 diabetes (T2D) is a common chronic disease whose etiology is known to have a strong genetic component. Standard genetic approaches, although allowing for the detection of a number of gene variants associated with the disease as well as differentially expressed genes, cannot fully explain the hereditary factor in T2D. The explosive growth in the genomic sequencing technologies over the last decades provided an exceptional impetus for transcriptomic studies and new approaches to gene expression measurement, such as RNA-sequencing (RNA-seq) and single-cell technologies. The transcriptomic analysis has the potential to find new biomarkers to identify risk groups for developing T2D and its microvascular and macrovascular complications, which will significantly affect the strategies for early diagnosis, treatment, and preventing the development of complications. In this article, we focused on transcriptomic studies conducted using expression arrays, RNA-seq, and single-cell sequencing to highlight recent findings related to T2D and challenges associated with transcriptome experiments.