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Li J, Wang Y, Yang P, Han H, Zhang G, Xu H, Quan K. Overexpression of ATGL impairs lipid droplet accumulation by accelerating lipolysis in goat mammary epithelial cells. Anim Biotechnol 2023; 34:3126-3134. [PMID: 36306180 DOI: 10.1080/10495398.2022.2136678] [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] [Indexed: 11/01/2022]
Abstract
Adipose triglyceride lipase (ATGL) is the key enzyme for the degradation of triacylglycerols (TAGs). It functions in concert with other enzymes to mobilize TAG and supply fatty acids (FAs) for energy production. Dysregulated lipolysis leads to excess concentrations of circulating FAs, which may lead to destructive and lipotoxic effects to the organism. To understand the role of ATGL in mammary lipid metabolism, ATGL was overexpressed in goat mammary epithelial cells (GMECs) by using a recombinant adenovirus system. ATGL overexpression decreased lipid droplet (LD) accumulation and cellular TG content (p < 0.05) along with a decrease in the expression of the key enzyme that catalyzes the final step of TG synthesis (DGAT). Significant increases were observed in the expression of genes related to lipolysis (hormone-sensitive lipase [HSL]) and FA desaturation (SCD) by ATGL overexpression. Genes responsible for FA oxidation (PPARα), LD formation and secretion (ADRP and BTN1A1), and long-chain FA uptake (CD36) were all decreased by ATGL overexpression (p < 0.05). The primary products of TAG lipolysis, free FAs (FFAs), were notably increased in the ATGL-overexpressing cells. Taken together, our results demonstrated that ATGL activation impairs lipid formation partially through accelerating lipolysis in GMECs.
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Affiliation(s)
- Jun Li
- College of Animal Science and Technology, Henan University of Animal Husbandry and Economy, Zhengzhou, PR China
| | - Yaling Wang
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, PR China
| | - Pengkun Yang
- College of Animal Science and Technology, Henan University of Animal Husbandry and Economy, Zhengzhou, PR China
| | - Haoyuan Han
- College of Animal Science and Technology, Henan University of Animal Husbandry and Economy, Zhengzhou, PR China
| | - Guizhi Zhang
- College of Animal Science and Technology, Henan University of Animal Husbandry and Economy, Zhengzhou, PR China
| | - Huifen Xu
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, PR China
| | - Kai Quan
- College of Animal Science and Technology, Henan University of Animal Husbandry and Economy, Zhengzhou, PR China
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Simillion C, Semmo N, Idle JR, Beyoğlu D. Robust Regression Analysis of GCMS Data Reveals Differential Rewiring of Metabolic Networks in Hepatitis B and C Patients. Metabolites 2017; 7:metabo7040051. [PMID: 28991180 PMCID: PMC5746731 DOI: 10.3390/metabo7040051] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2017] [Revised: 09/30/2017] [Accepted: 10/05/2017] [Indexed: 12/17/2022] Open
Abstract
About one in 15 of the world’s population is chronically infected with either hepatitis virus B (HBV) or C (HCV), with enormous public health consequences. The metabolic alterations caused by these infections have never been directly compared and contrasted. We investigated groups of HBV-positive, HCV-positive, and uninfected healthy controls using gas chromatography-mass spectrometry analyses of their plasma and urine. A robust regression analysis of the metabolite data was conducted to reveal correlations between metabolite pairs. Ten metabolite correlations appeared for HBV plasma and urine, with 18 for HCV plasma and urine, none of which were present in the controls. Metabolic perturbation networks were constructed, which permitted a differential view of the HBV- and HCV-infected liver. HBV hepatitis was consistent with enhanced glucose uptake, glycolysis, and pentose phosphate pathway metabolism, the latter using xylitol and producing threonic acid, which may also be imported by glucose transporters. HCV hepatitis was consistent with impaired glucose uptake, glycolysis, and pentose phosphate pathway metabolism, with the tricarboxylic acid pathway fueled by branched-chain amino acids feeding gluconeogenesis and the hepatocellular loss of glucose, which most probably contributed to hyperglycemia. It is concluded that robust regression analyses can uncover metabolic rewiring in disease states.
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Affiliation(s)
- Cedric Simillion
- Interfaculty Bioinformatics Unit and SIB Swiss Institute of Bioinformatics, University of Bern, Baltzerstrasse 6, 3012 Bern, Switzerland.
- Department of BioMedical Research, University of Bern, Murtenstrasse 35, 3008 Bern, Switzerland.
| | - Nasser Semmo
- Department of BioMedical Research, University of Bern, Murtenstrasse 35, 3008 Bern, Switzerland.
- Department of Visceral Surgery and Medicine, Department of Hepatology, Inselspital, University Hospital of Bern, 3010 Bern, Switzerland.
| | - Jeffrey R Idle
- Department of BioMedical Research, University of Bern, Murtenstrasse 35, 3008 Bern, Switzerland.
- Department of Visceral Surgery and Medicine, Department of Hepatology, Inselspital, University Hospital of Bern, 3010 Bern, Switzerland.
- Division of Systems Pharmacology and Pharmacogenomics, Samuel J. and Joan B. Williamson Institute, Arnold & Marie Schwartz College of Pharmacy and Health Sciences, Long Island University, Brooklyn, 11201 New York, NY, USA.
| | - Diren Beyoğlu
- Department of BioMedical Research, University of Bern, Murtenstrasse 35, 3008 Bern, Switzerland.
- Division of Systems Pharmacology and Pharmacogenomics, Samuel J. and Joan B. Williamson Institute, Arnold & Marie Schwartz College of Pharmacy and Health Sciences, Long Island University, Brooklyn, 11201 New York, NY, USA.
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Rito J, Viegas I, Pardal MA, Jones JG. Evidence of extensive plasma glucose recycling following a glucose load in seabass. Comp Biochem Physiol A Mol Integr Physiol 2017; 211:41-48. [DOI: 10.1016/j.cbpa.2017.05.009] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2017] [Revised: 05/11/2017] [Accepted: 05/19/2017] [Indexed: 11/26/2022]
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Coelho M, Mendes VM, Lima IS, Martins FO, Fernandes AB, Macedo MP, Jones JG, Manadas B. Direct analysis of [6,6-(2)H2]glucose and [U-(13)C6]glucose dry blood spot enrichments by LC-MS/MS. J Chromatogr B Analyt Technol Biomed Life Sci 2016; 1022:242-248. [PMID: 27107853 DOI: 10.1016/j.jchromb.2016.04.027] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2016] [Revised: 04/08/2016] [Accepted: 04/11/2016] [Indexed: 11/29/2022]
Abstract
A liquid chromatography tandem mass spectrometry (LC-MS/MS) using multiple reaction monitoring (MRM) in a triple-quadrupole scan mode was developed and comprehensively validated for the determination of [6,6-(2)H2]glucose and [U-(13)C6]glucose enrichments from dried blood spots (DBS) without prior derivatization. The method is demonstrated with dried blood spots obtained from rats administered with a primed-constant infusion of [U-(13)C6]glucose and an oral glucose load enriched with [6,6-(2)H2]glucose. The sensitivity is sufficient for analysis of the equivalent to <5μL of blood and the overall method was accurate and precise for the determination of DBS isotopic enrichments.
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Affiliation(s)
- Margarida Coelho
- CNC - Center for Neuroscience and Cell Biology, University of Coimbra, UC Biotech, Parque Tecnológico de Cantanhede, Núcleo 04, Lote 8, 3060-197 Cantanhede, Portugal
| | - Vera M Mendes
- CNC - Center for Neuroscience and Cell Biology, University of Coimbra, UC Biotech, Parque Tecnológico de Cantanhede, Núcleo 04, Lote 8, 3060-197 Cantanhede, Portugal
| | - Inês S Lima
- Chronic Diseases Research Center (CEDOC), NOVA Medical School/Faculdade de Ciências Médicas, Universidade Nova de Lisboa, Rua Câmara Pestana n° 6, 6-A Edifício CEDOC II, 1150-082 Lisboa, Portugal
| | - Fátima O Martins
- CNC - Center for Neuroscience and Cell Biology, University of Coimbra, UC Biotech, Parque Tecnológico de Cantanhede, Núcleo 04, Lote 8, 3060-197 Cantanhede, Portugal; Chronic Diseases Research Center (CEDOC), NOVA Medical School/Faculdade de Ciências Médicas, Universidade Nova de Lisboa, Rua Câmara Pestana n° 6, 6-A Edifício CEDOC II, 1150-082 Lisboa, Portugal; Institute for Interdisciplinary Research (IIIUC), University of Coimbra, Casa Costa Alemão, Pólo II, Rua Dom Francisco de Lemos, 3030-789 Coimbra, Portugal
| | - Ana B Fernandes
- Chronic Diseases Research Center (CEDOC), NOVA Medical School/Faculdade de Ciências Médicas, Universidade Nova de Lisboa, Rua Câmara Pestana n° 6, 6-A Edifício CEDOC II, 1150-082 Lisboa, Portugal
| | - M Paula Macedo
- Chronic Diseases Research Center (CEDOC), NOVA Medical School/Faculdade de Ciências Médicas, Universidade Nova de Lisboa, Rua Câmara Pestana n° 6, 6-A Edifício CEDOC II, 1150-082 Lisboa, Portugal; APDP-Portuguese Diabetes Association, Rua Rodrigo da Fonseca, n° 1, 1250-189 Lisboa, Portugal
| | - John G Jones
- CNC - Center for Neuroscience and Cell Biology, University of Coimbra, UC Biotech, Parque Tecnológico de Cantanhede, Núcleo 04, Lote 8, 3060-197 Cantanhede, Portugal; APDP-Portuguese Diabetes Association, Rua Rodrigo da Fonseca, n° 1, 1250-189 Lisboa, Portugal
| | - Bruno Manadas
- CNC - Center for Neuroscience and Cell Biology, University of Coimbra, UC Biotech, Parque Tecnológico de Cantanhede, Núcleo 04, Lote 8, 3060-197 Cantanhede, Portugal.
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