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Xia W, Veeragandham P, Cao Y, Xu Y, Rhyne TE, Qian J, Hung CW, Zhao P, Jones Y, Gao H, Liddle C, Yu RT, Downes M, Evans RM, Rydén M, Wabitsch M, Wang Z, Hakozaki H, Schöneberg J, Reilly SM, Huang J, Saltiel AR. Obesity causes mitochondrial fragmentation and dysfunction in white adipocytes due to RalA activation. Nat Metab 2024; 6:273-289. [PMID: 38286821 PMCID: PMC10896723 DOI: 10.1038/s42255-024-00978-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 01/04/2024] [Indexed: 01/31/2024]
Abstract
Mitochondrial dysfunction is a characteristic trait of human and rodent obesity, insulin resistance and fatty liver disease. Here we show that high-fat diet (HFD) feeding causes mitochondrial fragmentation in inguinal white adipocytes from male mice, leading to reduced oxidative capacity by a process dependent on the small GTPase RalA. RalA expression and activity are increased in white adipocytes after HFD. Targeted deletion of RalA in white adipocytes prevents fragmentation of mitochondria and diminishes HFD-induced weight gain by increasing fatty acid oxidation. Mechanistically, RalA increases fission in adipocytes by reversing the inhibitory Ser637 phosphorylation of the fission protein Drp1, leading to more mitochondrial fragmentation. Adipose tissue expression of the human homolog of Drp1, DNM1L, is positively correlated with obesity and insulin resistance. Thus, chronic activation of RalA plays a key role in repressing energy expenditure in obese adipose tissue by shifting the balance of mitochondrial dynamics toward excessive fission, contributing to weight gain and metabolic dysfunction.
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Affiliation(s)
- Wenmin Xia
- Division of Endocrinology and Metabolism, Department of Medicine, University of California San Diego, San Diego, CA, USA
| | - Preethi Veeragandham
- Division of Endocrinology and Metabolism, Department of Medicine, University of California San Diego, San Diego, CA, USA
| | - Yu Cao
- Division of Endocrinology and Metabolism, Department of Medicine, University of California San Diego, San Diego, CA, USA
| | - Yayun Xu
- Division of Endocrinology and Metabolism, Department of Medicine, University of California San Diego, San Diego, CA, USA
| | - Torrey E Rhyne
- Division of Endocrinology and Metabolism, Department of Medicine, University of California San Diego, San Diego, CA, USA
| | - Jiaxin Qian
- Division of Endocrinology and Metabolism, Department of Medicine, University of California San Diego, San Diego, CA, USA
| | - Chao-Wei Hung
- Division of Endocrinology and Metabolism, Department of Medicine, University of California San Diego, San Diego, CA, USA
| | - Peng Zhao
- Division of Endocrinology and Metabolism, Department of Medicine, University of California San Diego, San Diego, CA, USA
- Department of Biochemistry and Structural Biology, University of Texas Health Science Center, San Antonio, TX, USA
| | - Ying Jones
- Electron Microscopy Core, Cellular and Molecular Medicine, University of California San Diego, San Diego, CA, USA
| | - Hui Gao
- Department of Biosciences and Nutrition, Karolinska Institute, Stockholm, Sweden
| | - Christopher Liddle
- Storr Liver Centre, Westmead Institute for Medical Research and Westmead Hospital, University of Sydney School of Medicine, Sydney, New South Wales, Australia
| | - Ruth T Yu
- Gene Expression Laboratory, Salk Institute for Biological Studies, San Diego, CA, USA
| | - Michael Downes
- Gene Expression Laboratory, Salk Institute for Biological Studies, San Diego, CA, USA
| | - Ronald M Evans
- Gene Expression Laboratory, Salk Institute for Biological Studies, San Diego, CA, USA
| | - Mikael Rydén
- Department of Medicine (H7), Karolinska Institute (C2-94), Karolinska University Hospital, Stockholm, Sweden
| | - Martin Wabitsch
- Department of Pediatrics and Adolescent Medicine, Division of Pediatric Endocrinology and Diabetes, Ulm University Medical Center, Ulm, Germany
| | - Zichen Wang
- Department of Pharmacology, University of California San Diego, San Diego, CA, USA
- Department of Chemistry and Biochemistry, University of California San Diego, San Diego, CA, USA
| | - Hiroyuki Hakozaki
- Department of Pharmacology, University of California San Diego, San Diego, CA, USA
- Department of Chemistry and Biochemistry, University of California San Diego, San Diego, CA, USA
| | - Johannes Schöneberg
- Department of Pharmacology, University of California San Diego, San Diego, CA, USA
- Department of Chemistry and Biochemistry, University of California San Diego, San Diego, CA, USA
| | - Shannon M Reilly
- Division of Endocrinology and Metabolism, Department of Medicine, University of California San Diego, San Diego, CA, USA
- Weill Center for Metabolic Health, Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Jianfeng Huang
- Gene Expression Laboratory, Salk Institute for Biological Studies, San Diego, CA, USA
| | - Alan R Saltiel
- Division of Endocrinology and Metabolism, Department of Medicine, University of California San Diego, San Diego, CA, USA.
- Department of Pharmacology, University of California San Diego, San Diego, CA, USA.
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Vo Ngoc L, Rhyne TE, Kadonaga JT. Analysis of the Drosophila and human DPR elements reveals a distinct human variant whose specificity can be enhanced by machine learning. Genes Dev 2023; 37:377-382. [PMID: 37163335 PMCID: PMC10270198 DOI: 10.1101/gad.350572.123] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 04/06/2023] [Indexed: 05/11/2023]
Abstract
The RNA polymerase II core promoter is the site of convergence of the signals that lead to the initiation of transcription. Here, we performed a comparative analysis of the downstream core promoter region (DPR) in Drosophila and humans by using machine learning. These studies revealed a distinct human-specific version of the DPR and led to the use of machine learning models for the identification of synthetic extreme DPR motifs with specificity for human transcription factors relative to Drosophila factors and vice versa. More generally, machine learning models could similarly be used to design synthetic DNA elements with customized functional properties.
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Affiliation(s)
- Long Vo Ngoc
- Department of Molecular Biology, University of California, San Diego, La Jolla, California 92093, USA
| | - Torrey E Rhyne
- Department of Molecular Biology, University of California, San Diego, La Jolla, California 92093, USA
| | - James T Kadonaga
- Department of Molecular Biology, University of California, San Diego, La Jolla, California 92093, USA
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