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Biology subjects

Igoillo-Esteve, M.

Publications and source records attributed to Igoillo-Esteve, M..

3 recordsLinked to original sources

TRMT10A deficiency and tRNA fragmentation disrupt human pancreatic β-cell identity and insulin maturation

Mutations in the tRNA-modifying enzyme TRMT10A cause a rare monogenic syndrome characterized by early-onset diabetes and neurodevelopmental defects, yet the molecular mechanisms underlying TRMT10A diabetes remain unclear. Using human TRMT10A-deficient (knockout and mutant) induced pluripotent stem cells (iPSCs) differentiated into islet-like aggregates and TRMT10A-silenced EndoC-{beta}H1 human {beta}-cells, we show that TRMT10A deficiency impairs {beta}-cell differentiation, insulin content and glucose-stimulated insulin secretion while inducing widespread transcriptional alterations. These defects are accompanied by oxidative stress, diminished antioxidant capacity, and defective proinsulin processing driven by reduced PCSK1 expression. Mechanistically, the loss of TRMT10A promotes tRNA fragmentation and the generation of fragments derived from the 5 end of tRNAGln-CTG (tDRGln-CTG) that interact with hnRNPM. Our data support the existence of a previously unrecognized hnRNPM-PTBP1 interaction in human {beta}-cells and suggest that this complex may contribute to the regulation of PCSK1 mRNA stability and/or translation. Furthermore, through its interaction with hnRNPM, tDRGln-CTG may alter the function of the complex thereby contributing to reduced PCSK1 expression, defective proinsulin processing, and impaired insulin content. Our findings link tRNA fragmentation, RNA-binding protein networks and insulin maturation, positioning TRMT10A as a critical regulator of {beta}-cell identity and function and uncovering a novel mechanism of {beta}-cell failure in the pathogenesis of diabetes.

molecular biology↗

The type 1 diabetes-associated lncRNA ARGI participates in virus-induced pancreatic beta cell inflammation.

Type 1 diabetes-associated single nucleotide polymorphisms are mainly located in non-coding regions of the human genome. Single nucleotide polymorphisms located in long non-coding RNAs may result in the disruption of their secondary structure, affecting their function. Here, we functionally characterized the virus-induced type 1 diabetes-associated lncRNA ARGI (Antiviral Response Gene Inducer). ARGI upregulation in pancreatic {beta} cells leads to the transcriptional activation of antiviral and pro-inflammatory genes. Upon a viral insult, ARGI is upregulated in the nuclei of pancreatic {beta} cells and binds to CTCF to interact with the regulatory regions of IFN{beta} and interferon-stimulated genes, promoting their transcriptional activation in an allele-specific manner. The presence of the risk allele for type 1 diabetes in ARGI induces an hyperactivation of type I IFN response in {beta} cells, an expression signature that is present in the pancreas of diabetic patients. These data shed light on the molecular mechanisms by which type 1 diabetes-related single nucleotide polymorphisms in long non-coding RNAs influence pathogenesis at the pancreatic {beta} cell level.

genetics↗

A functional genomic approach to identify reference genes for human pancreatic beta cell real-time quantitative RT-PCR analysis

Exposure of human pancreatic beta cells to pro-inflammatory cytokines or metabolic stressors is used to model events related to type 1 and type 2 diabetes, respectively. Quantitative real-time PCR is commonly used to quantify changes in gene expression. The selection of the most adequate reference gene(s) for gene expression normalization is an important pre-requisite to obtain accurate and reliable results. There are no universally applicable reference genes, and the human beta cell expression of commonly used reference genes can be altered by different stressors. Here we aimed to identify the most stably expressed genes in human beta cells to normalize quantitative real-time PCR gene expression. We used comprehensive RNA-sequencing data from the human pancreatic beta cell line EndoC-{beta}H1, human islets exposed to cytokines or the free fatty acid palmitate in order to identify the most stably expressed genes. Genes were filtered based on their level of significance (adjusted P-value >0.05), fold-change (|fold-change| <1.5) and a coefficient of variation <10%. Candidate reference genes were validated by quantitative real-time PCR in independent samples. We identified a total of 264 genes stably expressed in EndoC-{beta}H1 cells and human islets following cytokine- or palmitate-induced stress, displaying a low coefficient of variation. Validation by quantitative real-time PCR of the top five genes ARF1, CWC15, RAB7A, SIAH1 and VAPA corroborated their expression stability under most of the tested conditions. Further validation in independent samples indicated that the geometric mean of ACTB and VAPA expression can be used as a reliable normalizing factor in human beta cells.

systems biology↗