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Publication

Mild Impairment of Mitochondrial OXPHOS Promotes Fatty Acid Utilization in POMC Neurons and Improves Glucose Homeostasis in Obesity.

Cell reports | 2018

Mitochondrial oxidative phosphorylation (OXPHOS) and substrate utilization critically regulate the function of hypothalamic proopiomelanocortin (POMC)-expressing neurons. Here, we demonstrate that inactivation of apoptosis-inducing factor (AIF) in POMC neurons mildly impairs mitochondrial respiration and decreases firing of POMC neurons in lean mice. In contrast, under diet-induced obese conditions, POMC-Cre-specific inactivation of AIF prevents obesity-induced silencing of POMC neurons, translating into improved glucose metabolism, improved leptin, and insulin sensitivity, as well as increased energy expenditure in AIFΔPOMC mice. On a cellular level, AIF deficiency improves mitochondrial morphology, facilitates the utilization of fatty acids for mitochondrial respiration, and increases reactive oxygen species (ROS) formation in POMC neurons from obese mice, ultimately leading to restored POMC firing upon HFD feeding. Collectively, partial impairment of mitochondrial function shifts substrate utilization of POMC neurons from glucose to fatty acid metabolism and restores their firing properties, resulting in improved systemic glucose and energy metabolism in obesity.

Pubmed ID: 30304679 RIS Download

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Associated grants

Agency: NIDDK NIH HHS, United States
Id: R01 DK104998
Agency: NIDDK NIH HHS, United States
Id: R01 DK111178

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Fiji (tool)

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Software package as distribution of ImageJ and ImageJ2 together with Java, Java3D and plugins organized into coherent menu structure. Used to assist research in life sciences.

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PRISM (tool)

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THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role.

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