| 1. |
- Andersson, Lotta, et al.
(författare)
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Characterization of Stimulus-Secretion Coupling in the Human Pancreatic EndoC-βH1 Beta Cell Line.
- 2015
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 10:3
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Tidskriftsartikel (refereegranskat)abstract
- Studies on beta cell metabolism are often conducted in rodent beta cell lines due to the lack of stable human beta cell lines. Recently, a human cell line, EndoC-βH1, was generated. Here we investigate stimulus-secretion coupling in this cell line, and compare it with that in the rat beta cell line, INS-1 832/13, and human islets.
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| 2. |
- Nicholas, Lisa M., et al.
(författare)
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Mitochondrial transcription factor B2 is essential for mitochondrial and cellular function in pancreatic β-cells
- 2017
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Ingår i: Molecular Metabolism. - : Elsevier BV. - 2212-8778. ; 6:7, s. 651-663
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Tidskriftsartikel (refereegranskat)abstract
- Objective: Insulin release from pancreatic β-cells is controlled by plasma glucose levels via mitochondrial fuel metabolism. Therefore, insulin secretion is critically dependent on mitochondrial DNA (mtDNA) and the genes it encodes. Mitochondrial transcription factor B2 (TFB2M) controls transcription of mitochondrial-encoded genes. However, its precise role in mitochondrial metabolism in pancreatic β-cells and, consequently, in insulin secretion remains unknown. Methods: To elucidate the role of TFB2M in mitochondrial function and insulin secretion in vitro and in vivo, mice with a β-cell specific homozygous or heterozygous knockout of Tfb2m and rat clonal insulin-producing cells in which the gene was silenced were examined with an array of metabolic and functional assays. Results: There was an effect of gene dosage on Tfb2m expression and function. Loss of Tfb2m led to diabetes due to disrupted transcription of mitochondrial DNA (mtDNA) and reduced mtDNA content. The ensuing mitochondrial dysfunction activated compensatory mechanisms aiming to limit cellular dysfunction and damage of β-cells. These processes included the mitochondrial unfolded protein response, mitophagy, and autophagy. Ultimately, however, these cell-protective systems were overridden, leading to mitochondrial dysfunction and activation of mitochondrial-dependent apoptotic pathways. In this way, β-cell function and mass were reduced. Together, these perturbations resulted in impaired insulin secretion, progressive hyperglycemia, and, ultimately, development of diabetes. Conclusions: Loss of Tfb2m in pancreatic β-cells results in progressive mitochondrial dysfunction. Consequently, insulin secretion in response to metabolic stimuli is impaired and β-cell mass reduced. Our findings indicate that TFB2M plays an important functional role in pancreatic β-cells. Perturbations of its actions may lead to loss of functional β-cell mass, a hallmark of T2D.
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| 3. |
- Sun, Jiangming, et al.
(författare)
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Discriminative prediction of A-To-I RNA editing events from DNA sequence
- 2016
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 11:10
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Tidskriftsartikel (refereegranskat)abstract
- RNA editing is a post-transcriptional alteration of RNA sequences that, via insertions, deletions or base substitutions, can affect protein structure as well as RNA and protein expression. Recently, it has been suggested that RNA editing may be more frequent than previously thought. A great impediment, however, to a deeper understanding of this process is the paramount sequencing effort that needs to be undertaken to identify RNA editing events. Here, we describe an in silico approach, based on machine learning, that ameliorates this problem. Using 41 nucleotide long DNA sequences, we show that novel A-to-I RNA editing events can be predicted from known A-to-I RNA editing events intra- and interspecies. The validity of the proposed method was verified in an independent experimental dataset. Using our approach, 203 202 putative A-to-I RNA editing events were predicted in the whole human genome. Out of these, 9% were previously reported. The remaining sites require further validation, e.g., by targeted deep sequencing. In conclusion, the approach described here is a useful tool to identify potential A-to-I RNA editing events without the requirement of extensive RNA sequencing.
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