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Mozaffaritabar S, Koltai E, Zhou L, Bori Z, Kolonics A, Kujach S, Gu Y, Koike A, Boros A, Radák Z. PGC-1α activation boosts exercise-dependent cellular response in the skeletal muscle. J Physiol Biochem 2024; 80:329-335. [PMID: 38261146 PMCID: PMC11074013 DOI: 10.1007/s13105-024-01006-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 01/10/2024] [Indexed: 01/24/2024]
Abstract
The role of Peroxisome proliferator-activated receptor-gamma coactivator alpha (PGC-1α) in fat metabolism is not well known. In this study, we compared the mechanisms of muscle-specific PGC-1α overexpression and exercise-related adaptation-dependent fat metabolism. PGC-1α trained (PGC-1α Ex) and wild-trained (wt-ex) mice were trained for 10 weeks, five times a week at 30 min per day with 60 percent of their maximal running capacity. The PGC-1α overexpressed animals exhibited higher levels of Fibronectin type III domain-containing protein 5 (FNDC5), 5' adenosine monophosphate-activated protein kinase alpha (AMPK-α), the mammalian target of rapamycin (mTOR), Sirtuin 1 (SIRT1), Lon protease homolog 1 (LONP1), citrate synthase (CS), succinate dehydrogenase complex flavoprotein subunit A (SDHA), Mitofusin-1 (Mfn1), endothelial nitric oxide synthase (eNOS), Hormone-sensitive lipase (HSL), adipose triglyceride lipase (ATGL), G protein-coupled receptor 41 (GPR41), and Phosphatidylcholine Cytidylyltransferase 2 (PCYT2), and lower levels of Sirtuin 3 (SIRT3) compared to wild-type animals. Exercise training increased the protein content levels of SIRT1, HSL, and ATGL in both the wt-ex and PGC-1α trained groups. PGC-1α has a complex role in cellular signaling, including the upregulation of lipid metabolism-associated proteins. Our data reveals that although exercise training mimics the effects of PGC-1α overexpression, it incorporates some PGC-1α-independent adaptive mechanisms in fat uptake and cell signaling.
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Affiliation(s)
- Soroosh Mozaffaritabar
- Research Institute of Molecular Exercise Science, Hungarian University of Sports Science, 1123, Budapest, Hungary
| | - Erika Koltai
- Research Institute of Molecular Exercise Science, Hungarian University of Sports Science, 1123, Budapest, Hungary
| | - Lei Zhou
- Research Institute of Molecular Exercise Science, Hungarian University of Sports Science, 1123, Budapest, Hungary
| | - Zoltan Bori
- Research Institute of Molecular Exercise Science, Hungarian University of Sports Science, 1123, Budapest, Hungary
| | - Attila Kolonics
- Research Institute of Molecular Exercise Science, Hungarian University of Sports Science, 1123, Budapest, Hungary
| | - Sylwester Kujach
- Research Institute of Molecular Exercise Science, Hungarian University of Sports Science, 1123, Budapest, Hungary
- Department of Neurophysiology, Neuropsychology and Neuroinformatics, Faculty of Health Sciences, Medical University of Gdansk, 80-210, Gdansk, Poland
| | - Yaodong Gu
- Faculty of Sports Science, Ningbo University, Ningbo, 315211, China
| | - Atsuko Koike
- Research Institute of Molecular Exercise Science, Hungarian University of Sports Science, 1123, Budapest, Hungary
| | - Anita Boros
- Research Institute of Molecular Exercise Science, Hungarian University of Sports Science, 1123, Budapest, Hungary
| | - Zsolt Radák
- Research Institute of Molecular Exercise Science, Hungarian University of Sports Science, 1123, Budapest, Hungary.
- Waseda Institute for Sport Sciences, Waseda University, Saitama, 359-1192, Japan.
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Qi R, Kang SS, Pei Y, Liu M, Zhou Y, Guan B, Zhang X, Li Z, Cao F. LC-MS-based untargeted metabolomics reveals the mechanism underlying prostate damage in a type 2 diabetes mouse model. Reprod Biol 2023; 23:100811. [PMID: 37660522 DOI: 10.1016/j.repbio.2023.100811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 08/18/2023] [Accepted: 08/24/2023] [Indexed: 09/05/2023]
Abstract
Type 2 diabetes mellitus (T2DM) can cause prostate damage and affect male reproductive function, but the underlying mechanisms are not completely understood. In this study, we used liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics to identify endogenous metabolites in the prostate of a T2DM mouse model. The selected endogenous metabolites were then subjected to bioinformatics analysis and metabolic pathway studies to understand their role in the development of T2DM-induced prostate damage. We used male homozygous BTBR ob/ob mice (n = 12) and BTBR WT mice (n = 11) in this study. We monitored changes in blood glucose, body weight, prostate weight, and prostate index, as well as performed hematoxylin and eosin (H&E) staining and observed that the prostate of the BTBR ob/ob was damaged. We then used ultra-high-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) for metabolomics analysis. The stability of the model was validated using principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA). Using variable importance in projection (VIP) > 1, false discovery rate (FDR) < 0.05, and coefficient of variation (CV) < 30 as criteria, a total of 149 differential metabolites (62 upregulated and 87 downregulated) were identified between the prostates of the two groups of mice. Topological pathway analysis showed that these differential metabolites were mainly involved in sphingolipid (SP) and glycerophospholipid (GP) metabolism. In conclusion, our study not only emphasizes the damage caused by T2DM to the prostate but also provides new insights into the potential mechanisms of T2DM-induced male reproductive dysfunction.
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Affiliation(s)
- Rong Qi
- Clinical Medical College, North China University of Science and Technology, Tangshan 063210, China
| | - Shao-San Kang
- Clinical Medical College, North China University of Science and Technology, Tangshan 063210, China
| | - Yongchao Pei
- Clinical Medical College, North China University of Science and Technology, Tangshan 063210, China
| | - Mingming Liu
- School of Public Health, North China University of Science and Technology, Tangshan 063210, China
| | - Yufan Zhou
- School of Public Health, North China University of Science and Technology, Tangshan 063210, China
| | - Bo Guan
- School of Public Health, North China University of Science and Technology, Tangshan 063210, China
| | - Xinduo Zhang
- School of Public Health, North China University of Science and Technology, Tangshan 063210, China
| | - Zhiguo Li
- School of Public Health, North China University of Science and Technology, Tangshan 063210, China.
| | - Fenghong Cao
- Clinical Medical College, North China University of Science and Technology, Tangshan 063210, China.
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