Optimal control of hepatic lipid metabolism is critical for organismal metabolic fitness. In liver, adipose triglyceride lipase (ATGL) serves as a major triacylglycerol (TAG) lipase and controls the bulk of intracellular lipid turnover. However, regulation of ATGL expression and its functional implications in hepatic lipid metabolism, particularly in the context of fatty liver disease, is unclear. We show that E3 ubiquitin ligase COP1 (also known as RFWD2) binds to the consensus VP motif of ATGL and targets it for proteasomal degradation by K-48 linked polyubiquitination, predominantly at the lysine 100 residue. COP1 thus serves as a critical regulator of hepatocyte TAG content, fatty acid mobilization, and oxidation. Moreover, COP1-mediated regulation of hepatic lipid metabolism requires optimum ATGL expression for its metabolic outcome. In vivo, adenovirus-mediated depletion of COP1 ameliorates high-fat diet–induced steatosis in mouse liver and improves liver function. Our study thus provides new insights into the regulation of hepatic lipid metabolism by the ubiquitin-proteasome system and suggests COP1 as a potential therapeutic target for nonalcoholic fatty liver disease.

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease and is strongly associated with obesity and type 2 diabetes (1). NAFLD describes a spectrum of conditions characterized mainly by the histological finding of macrovesicular hepatic steatosis (2) and now considered to be the hepatic component of the metabolic syndrome (3). The hallmark feature of NAFLD pathogenesis, both histologically and metabolically, is the accumulation of triacylglycerol (TAG) in the liver (4), which is caused by defects in lipid accumulation and mobilization (5,6).

Adipose triglyceride lipase (ATGL) is the first and rate-limiting enzyme for the breakdown of cellular TAG (710). Mutation in the ATGL gene causes neutral lipid storage disease and myopathy in humans (11). ATGL expression in adipose tissue is transcriptionally regulated by insulin through FoxO1 and EGR1, directly by peroxisome proliferator–activated receptor-γ (1214), and posttranscriptionally by G0S2 and CGI-58 (15). The importance of ATGL was evidenced by ectopic lipid accumulation in many tissues of ATGL-null mice, including cardiac muscle, skeletal muscle, and the liver (7,10). ATGL serves as the major TAG lipase in the liver (16), and liver-specific ATGL knockdown or deletion in mice reveals progressive hepatic steatosis and inflammation (17) as well as changes in the lipid droplet (LD) lipidome (18) with uncoupling of glucose tolerance from liver TAG accumulation (19). Lowered ATGL expression has also been found in patients with NAFLD (6). Molecular regulation of hepatic ATGL remained elusive, however.

Regulated cellular protein turnover via the ubiquitin-proteasome system underlies a wide variety of signaling pathways, from cell-cycle control and metabolic homeostasis to development (20). Stepwise ubiquitination of a target protein is achieved through three enzyme classes: E1-ubiquitin–activating enzymes, E2-ubiquitin–conjugating enzymes, and E3 ubiquitin ligases (21,22). COP1 is an evolutionarily conserved E3 ubiquitin ligase (23) essential for mouse development, because COP1-knockout mice were embryonically lethal (24). COP1 regulates the stabilities of p53 (25), c-Jun (26), and acetyl-CoA carboxylase 1 (27), each through different mechanisms. Recent discoveries have documented important roles of COP1 in the regulation of intermediary metabolism, including glucose (23,28) and lipid metabolism (27). The importance of COP1 in mediating insulin secretion from pancreatic β-cells appreciates the role of COP1 as a master regulator of whole-body glucose homeostasis (29).

In this study we have identified hepatic ATGL as a novel target of COP1, and their interaction controls hepatic TAG turnover. Moreover, depletion of COP1 in the liver abrogated hepatic steatosis, thereby suggesting that COP1 could be a novel target for ameliorating lipid accumulation in NAFLD.

Antibodies

Antibodies to ATGL, HA-tag, myc-tag, and GAPDH were from Cell Signaling Technology (Boston, MA); the COP1 antibody was from Bethyl Laboratories Inc.; anti-Ub antibody was from Santa Cruz Biotechnology; and anti-FLAG M2 and β-actin antibody were from Sigma-Aldrich.

Plasmids and Vectors

Human ubiquitin-HA and COP1-myc-FLAG clones were from Addgene and OriGene, respectively. ATGL was cloned in pcDNA 3.1(-) b myc-his vector using the forward primer 5′ TCACCTCGAGATGTTCCCGAGGGAGACCAAGTGG 3′ and reverse primer 5′ TAGAAGCTTGGGCAAGGCGGGAGGCCAGGTGGATC 3′ containing Xho1 and HindIII restriction sites, respectively. Mutagenesis of the ATGL clone was done using the QuickChange II Site-Directed Mutagenesis Kit (Agilent). Details of primers for mutagenesis are in Supplementary Table 1.

Animal Experiments

C57BL/6 male mice 8–10 weeks of age were divided in two groups for normal chow and high-fat diet (HFD) containing 45% fat and 5.81 kcal/g diet energy content (# 960192; MP Biomedicals). Animals were fed the HFD for 4 weeks, and 8 × 109 plaque-forming units short hairpin (sh)COP1 adenovirus was injected retro-orbitally. Animals were sacrificed after 1 week. All data are representative of two independent experiments with four to seven animals per group. The experimental protocols were approved by the Institutional Animal Ethics Committee (approved by CPCSEA, Ministry of Environment & Forest, Government of India).

Technetium-99m–Mebrofenin Liver Activity Imaging

Technetium-99m (99mTc)O4 was obtained by 2-butanone extraction of a 5N NaOH solution of 99MoO4, procured from Bhabha Atomic Research Centre (Mumbai, India). 99mTc-labeled mebrofenin (15–18 MBq/animal) was administered to each anesthetized animal through a tail vein. Scintigraphic imaging of animals was done in a GE Infinia gamma camera equipped with a Xeleris Work Station. Dynamic single-photon emission computed tomography acquisition was done over 30 min using 180 time frames of 10 s each.

Cell Culture and Transfection

Human hepatoma cell line HepG2, HUH7, and human embryonic kidney cell line HEK293A were cultured in high-glucose DMEM supplemented with 10% FBS containing 1% penicillin/streptomycin. Transient transfections with plasmids and small interfering (si)RNA were done using Lipofectamine 2000 reagent (Life Technologies) according to the manufacturer’s instruction. For stable expression and knockdown of ATGL, cells were transfected with pcDNA3.1-b myc-his vector and infected with lentivirus generated from pooled shATGL plasmids (Santa Cruz Biotechnology), respectively. siRNA for human RFWD2 against the GCUGUGGUCUACCAAUCUA sequence was from Eurogentec, Liège, Belgium.

Adenovirus Production

Recombinant adenoviruses containing shCOP1 construct were generated by the BLOCK-iT Adenoviral Expression System (Invitrogen) using the sequence CACCGAGTCCAATGTGCTGATTGC (28). Recombinant adenoviruses were purified and concentrated using the FAST-TRAP adenovirus purification and concentration kit (Millipore).

Histology

For histological analysis, tissues were fixed in 10% formaldehyde in PBS, embedded in paraffin, sectioned at 10 μm, and stained with hematoxylin and eosin (H&E) following standard staining protocol.

Immunoprecipitation and Ubiquitination Assay

Cells were harvested in radioimmunoprecipitation assay buffer (10 mmol/L Tris-HCl [pH 8.0], 1 mmol/L EDTA, 0.5 mmol/L EGTA, 1% Triton X-100, 0.1% SDS, 140 mmol/L NaCl with protease, and phosphatase-inhibitor cocktail; Roche). Then, 200 µg of protein was incubated overnight with 2 µg primary antibody and 30 µL of Protein A magnetic beads at 4°C. Immune complexes were separated by Magnetic GrIP RAC (Millipore) and washed thrice. For affinity purification of COOH-terminal hexahistidine containing ATGL, cells were harvested in radioimmunoprecipitation assay buffer and incubated overnight with 30 µL of Ni Sepharose beads (Roche). Beads were then warmed at 60°C for 10 min in 2× sample buffer and centrifuged. β-Marcaptoethanol was added to the supernatant to make the final concentration 5%. For immunoprecipitation, cells were harvested in cell lysis buffer containing 20 mmol/L Tris-HCl (pH 7.4), 100 mmol/L NaCl, 2.5 mmol/L MgCl2, and 0.05% Nonidet P-40 for 5 h on ice. Immunoprecipitation was performed as described previously and analyzed by Western blotting.

Western Blot Analysis

Proteins were separated by SDS-PAGE and transferred onto polyvinylidene fluoride membrane (Millipore). Membranes were incubated in 5% nonfat dry milk, followed by incubation with primary and secondary antibody. Membranes were developed using Clarity Western ECL Blotting substrate (Bio-Rad), and images were captured in the Bio-Rad Gel Documentation system using ImageLab Software.

Quantitative PCR

Total RNA from cell homogenates was isolated using Trizol (Invitrogen), and cDNA was synthesized using iScript Reverse Transcription Supermix (Bio-Rad). The gene expression was measured by SYBR green chemistry (Fast Start Universal SYBR Green Master; Roche) in LightCycler 96 real-time PCR (Roche) and normalized by 18S RNA expression by the ΔΔCt method. The primer sequences are in Supplementary Table 2.

Fatty Acid Oxidation, TAG, and Cholesterol Assay

Fatty acid (FA) oxidation (FAO) was measured as described earlier (30). 14C-labeled released CO2 was estimated using a β-counter (PerkinElmer) and normalized to protein concentrations. Lipids were extracted from cells or from the liver using hexane/isopropyl alcohol (3:2, vol/vol). TAG was assayed using the Serum Triglyceride Determination Kit (TR0100; Sigma-Aldrich). Cholesterol levels were assayed in extracted lipid or in animal serum using ferric chloride/sulfuric acid reagent (31). TAG and cholesterol content were normalized with cellular protein or liver weight, and data were expressed as means ± SD for duplicate samples repeated thrice.

Oil Red O Staining

Oil Red O staining was performed as described before (30). Photographs were taken with a Canon SX10 PowerShot camera under optimal illumination.

FA Mobilization Assay, Confocal Microscopy, and Image Analysis

At 30 h after transfection, cells were incubated with 1 μmol/L boron-dipyrromethene (BODIPY) 558/568 C12 (Red C12; Thermo Fisher Scientific) for 6 h. Cells were washed and kept in complete media. Subsequently, 100 μmol/L oleic acid-BSA (both Sigma-Aldrich) conjugate was treated for 16 h. BODIPY 493/503 (Life Technologies) was used to label LDs at a concentration of 200 ng/mL, 20 min before imaging. Hoechst 33342 (5 µg/mL; Thermo Fisher Scientific) was added for 5 min to stain the nucleus. Cells were washed twice with 1× PBS and viewed under a Leica TCS (True Confocal System) SP8 microscope with HC PLAN APO objective (original magnification: 63*6×/1.40, 63*1.83×/1.40). Images were analyzed using LAS X (Leica) and ImageJ (National Institutes of Health) software. Brightness and contrast were adjusted in Adobe Photoshop Elements 10. LD number was calculated manually for at least 30 cells from a different field (original magnification: 63*1.83×/1.40) for each experimental condition. For the FA mobilization assay, the area ratio of the red channel (C12 BODIPY 558/568) and green channel (BODIPY 493/503) was calculated from the thresholded image using the Analyze Particles tool of ImageJ software. This ratio was called the FA mobilization index.

Molecular Modeling and Docking

Homologs of ATGL and COP1 were searched in the structural databases Protein Data Bank (PDB) (32) and Structural Classification of Proteins (SCOP) (33). The highest identity and coverage was selected, and sequences were subjected to secondary structures prediction using the online servers Psi-Blast Based Secondary Structure Prediction (PSIPRED) (34) and Phyre2 (35). Homology modeling by Modeler V9 (36) and ab initio modeling by the online server Iterative Threading Assembly Refinement (I-TASSER) (37) were both used to build full-length structures. Loop modeling and ligand modeling was performed, and minimal energy full-length models were selected and optimized by the Normal Mode Analysis, Deformation and Refinement (NOMAD-REF) server (38) using GROMACS force fields. Models were subjected to validation tools, such as Verify3D (39), which determines the compatibility of an atomic model (three dimensional) with its own amino acid sequence (one dimensional) and Rampage (40), which checks the stereo chemical quality of protein structure by analyzing a Ramachandran plot. Solvation free energy of folding for each model was calculated by the Protein Data Bank in Europe Proteins, Interfaces, Structures and Assemblies (PDBePISA) web server (41) and compared with the corresponding templates. Stand-alone version of PatchDock 1.1 package (42) was used for protein-protein docking in a generalized protocol. Directed docking was done to generate 100 solutions, followed by refinement and rescoring by the FireDock refinement package (43) and clustered based on their overall orientation using ensemble clustering of Chimera1.8.1 (44). The top three largest clusters were inspected manually and statistically analyzed. Top 10 solutions identified by geometrical shape complementarity score (by PatchDock), solvation free energy of binding (by PDBePISA), and size of interface area (by PDBePISA). Finally, the best solution was identified by manual inspection, which satisfied favorable interaction between two proteins.

For further validation of the selected docking interface, eight protein complexes were identified from PDB having similar interface area (± 100 Å2) by the PDBePISA web server (41) and refined by distance calculation. Residues of two different proteins, located at the distance ≤10 Å, were considered at interface, and residues located ≤5 Å apart were considered to be interacting. Hydrogen bonds and salt bridges were identified by the PDBePISA web server. Non-Polar contacts were identified by an in-house perl script. Approximate ∆G of binding (solvation free energy gained upon complex formation) was calculated. The protein complexes used for comparison of binding properties with respect to the ATGL-COP1 complex are reported in Supplementary Table 3.

Statistical Analysis

The Student unpaired two-tailed t test was used to evaluate the statistical significance between two groups. Statistical significance was predefined as P ≤ 0.05.

ATGL Is Ubiquitinated and Proteasomally Degraded in Hepatocytes

To assess whether ATGL is ubiquitinated in hepatocytes, myc-ATGL and hemagglutinin (HA)-ubiquitin constructs were cotransfected in HepG2 and HUH7 cells, and ATGL was immunoprecipitated using myc-tag antibody. Immune complexes were analyzed by immunoblotting using HA-tag antibody. In both cell lines, cotransfection of ATGL and ubiquitin resulted in the development of protein smears that indicate an accumulation of polyubiquitinated ATGL protein (Fig. 1A and Supplementary Fig. 1A). Furthermore, treatment with proteasomal inhibitor MG-132 and not with lysosomal inhibitor chloroquine significantly increased the intensity of protein smear, suggesting polyubiquitinated ATGL proteins are degraded predominantly in the proteasome (Fig. 1A and B and Supplementary Fig. 1A and B). To confirm that endogenous ubiquitin binds with ATGL protein, we performed reciprocal immunoprecipitation by ATGL and ubiquitin in HepG2 cell lysate and found that endogenous ATGL and endogenous ubiquitin were reciprocally coprecipitated (Fig. 1C).

Figure 1

ATGL is polyubiquitinated at lysine 100 in patatin-like domain by the lysine K48 linked chain of ubiquitin and degraded in proteasome. A: HepG2 cells were transfected with myc-tagged ATGL and HA-tagged ubiquitin constructs. After 48 h of transfection, cells were treated with 50 μmol/L MG-132 for 4 h. Cell lysates were then immunoprecipitated (IP) with myc-tag antibody and analyzed by immunoblot (IB) using anti-HA antibody (top). The bottom panels show the respective protein levels of ATGL and actin. B: Cells were transfected with indicated plasmids and after 48 h treated with respective concentrations of chloroquine (Chlor) for 4 h. Ubiquitination assay was performed as described in A. C: Immunoprecipitation experiments were performed in HepG2 cells. Endogenous ATGL and ubiquitin (Ub) were immunoprecipitated and probed with Ub (upper panel) and ATGL (lower panel) antibody, respectively. D: Different fragments of ATGL containing different combination of domains (top); myc-tagged clones containing patatin-like and cPLA domain were transfected in HepG2 cells together with HA-ubiquitin, and polyubiquitination of ATGL was assayed by immunoblotting. EV, empty vector. E: Mutant clones with arginine in place of lysine at four positions of ATGL were transfected and checked for their ability to be polyubiquitinylated. F: Ubiquitination of ATGL with indicated lysine mutant variants of ubiquitin. The immunoblots are representative of one of at least three independent experiments.

Figure 1

ATGL is polyubiquitinated at lysine 100 in patatin-like domain by the lysine K48 linked chain of ubiquitin and degraded in proteasome. A: HepG2 cells were transfected with myc-tagged ATGL and HA-tagged ubiquitin constructs. After 48 h of transfection, cells were treated with 50 μmol/L MG-132 for 4 h. Cell lysates were then immunoprecipitated (IP) with myc-tag antibody and analyzed by immunoblot (IB) using anti-HA antibody (top). The bottom panels show the respective protein levels of ATGL and actin. B: Cells were transfected with indicated plasmids and after 48 h treated with respective concentrations of chloroquine (Chlor) for 4 h. Ubiquitination assay was performed as described in A. C: Immunoprecipitation experiments were performed in HepG2 cells. Endogenous ATGL and ubiquitin (Ub) were immunoprecipitated and probed with Ub (upper panel) and ATGL (lower panel) antibody, respectively. D: Different fragments of ATGL containing different combination of domains (top); myc-tagged clones containing patatin-like and cPLA domain were transfected in HepG2 cells together with HA-ubiquitin, and polyubiquitination of ATGL was assayed by immunoblotting. EV, empty vector. E: Mutant clones with arginine in place of lysine at four positions of ATGL were transfected and checked for their ability to be polyubiquitinylated. F: Ubiquitination of ATGL with indicated lysine mutant variants of ubiquitin. The immunoblots are representative of one of at least three independent experiments.

Close modal

ATGL Ubiquitination Occurs Predominantly on Lysine100 Residue in the Patatin-Like Domain Via Lysine 48 Residue of Ubiquitin

We next sought to identify the lysine residue(s) of ATGL that are ubiquitinated. To this end, we first examined the polyubiquitination of different ATGL domains. The polyubiquitin signal of ATGL was obtained in full-length (486 amino acids) or patatin-like (11–178 amino acids) or cytosolic phospholipase A (cPLA) domain (299–388 amino acids) containing vectors (Fig. 1D) indicating that ATGL ubiquitination occurs between 1 and 178 amino acid. Sequence analysis of the patatin-like domain revealed that lysine residues of murine amino acid positions 74, 78, 92, and 100 are conserved in mammals. As shown in Fig. 1E, lys→arg mutation only at 100th position significantly reduced ATGL polyubiquitination. We next sought to determine the role of lysine 48 and 63 residues on ubiquitin, the two most well-characterized residues implicated in polyubiquitination. ATGL is polyubiquitinated in K63R, but ubiquitinated ATGL was undetectable in the K48R-transfected cells (Fig. 1F).

COP1 Is the E3 Ligase for ATGL in Hepatocytes

To identify the putative E3 ligase responsible for ATGL ubiquitination, we searched for the consensus E3 ligase–binding amino acid sequences on the ATGL protein. We found one putative COP1 binding motif E-W-L-P-D-VP-E-D (consensus binding motif being D/E-x-x-x-VP-D/E), the so called VP motif in the cPLA domain of the murine ATGL protein (Fig. 2A). To examine whether COP1 interacts with ATGL, we cotransfected myc-ATGL and FLAG-COP1 in HEK293A cells and immunoprecipitated with anti-FLAG antibody. ATGL was detected in the immune complex (Fig. 2B). Similarly, in the HepG2 cell line, stably expressing myc-tagged ATGL (Supplementary Fig. 2A), COP1, and myc-ATGL were, respectively, coimmunoprecipitated (Fig. 2C). Moreover, endogenous ATGL and COP1 in rat liver lysates were also coimmunoprecipitated with each other (Supplementary Fig. 2B). To further determine whether COP1 binds to ATGL via its VP motif, we find that mutation in the VP motif (V361A/P362A) led to loss of COP1 binding (Fig. 2D) and significant attenuation in ATGL ubiquitination (Fig. 2E).

Figure 2

COP1 directly interacts with ATGL through VP binding motif in the cPLA domain of ATGL. A: Conserved lysine residues in the patatin-like domain in different mammalian taxa. ATGL and COP1 interaction in coimmunoprecipitation (IP) assays in HEK293A cells (B) and in HepG2 cells stably expressing ATGL (C). D: Coimmunoprecipitation experiment of COP1 with WT and VP mutant (V361A/V362A) of ATGL showing the importance of the VP motif in COP1 and ATGL interaction. E: Ubiquitination status of WT and VP mutant of ATGL. The immunoblots (IB) are representative of one of at least three independent experiments. F, left panel: Three-dimensional structure of ATGL protein predicted by ab initio and comparative modeling. The residues, which interact with COP1, are highlighted in orange and presented in sphere orientation. The active site (red color) and ubiquitination site (blue color) are also presented in sphere orientation. Right panel: Three-dimensional structure of COP1 protein predicted by ab initio and comparative modeling. The residues, which interact with ATGL, are highlighted in green and presented in sphere orientation. G, left panel: Docked complex of ATGL (blue) and COP1 (pink). Interface residues are shown as spheres in orange (ATGL) and green (COP1) colors. ATGL and COP1 interact through two interfaces marked as IF1 and IF2. Right panel: IF1 and IF2 are enlarged and the residues are represented in stick orientation. H: Interface area (top panel) and gain of solvation free energy (bottom panel) of the docked complex are compared with the same obtained from eight different protein complexes having interface area of similar sizes.

Figure 2

COP1 directly interacts with ATGL through VP binding motif in the cPLA domain of ATGL. A: Conserved lysine residues in the patatin-like domain in different mammalian taxa. ATGL and COP1 interaction in coimmunoprecipitation (IP) assays in HEK293A cells (B) and in HepG2 cells stably expressing ATGL (C). D: Coimmunoprecipitation experiment of COP1 with WT and VP mutant (V361A/V362A) of ATGL showing the importance of the VP motif in COP1 and ATGL interaction. E: Ubiquitination status of WT and VP mutant of ATGL. The immunoblots (IB) are representative of one of at least three independent experiments. F, left panel: Three-dimensional structure of ATGL protein predicted by ab initio and comparative modeling. The residues, which interact with COP1, are highlighted in orange and presented in sphere orientation. The active site (red color) and ubiquitination site (blue color) are also presented in sphere orientation. Right panel: Three-dimensional structure of COP1 protein predicted by ab initio and comparative modeling. The residues, which interact with ATGL, are highlighted in green and presented in sphere orientation. G, left panel: Docked complex of ATGL (blue) and COP1 (pink). Interface residues are shown as spheres in orange (ATGL) and green (COP1) colors. ATGL and COP1 interact through two interfaces marked as IF1 and IF2. Right panel: IF1 and IF2 are enlarged and the residues are represented in stick orientation. H: Interface area (top panel) and gain of solvation free energy (bottom panel) of the docked complex are compared with the same obtained from eight different protein complexes having interface area of similar sizes.

Close modal

To obtain the structural insight into the ATGL-COP1 binding, we generated in silico molecular models for ATGL and COP1. The full-length ATGL model generated by joining the N-terminal homology model and the COOH-terminal ab initio model (Fig. 2F and Supplementary Fig. 3A) was subjected to the GROMACS energy minimization function using the NOMAD-REF web server (38) and validated by a Ramachandran plot (Supplementary Fig. 3C). Templates for COP1 were available for ring finger (region: 114–203) and WD40 repeat region (region: 323–731). Full-length COP1 model structure was also constructed by combining template-based homology and ab initio modeling. Optimized COP1 structure was selected based on energy and overall structural stability (Fig. 2F and Supplementary Fig. 3B) and was validated by a Ramachandran plot (Supplementary Fig. 3D). We then performed directed docking for COP1 and ATGL using the stand-alone version of PatchDock 1.1 package (42) (Fig. 2G, left panel). The complex was stabilized by interprotein interactions at interface (IF) 1 and IF2. In IF1, the WD40 propeller region interacts with the VP motif (E354–D361: EWLPDVPED) exposed at the surface of ATGL COOH-terminal, whereas IF2 is formed by the ring finger of COP1 and N-terminal domain of ATGL (Fig. 2G, right panel). The total interface area was 708 Å2, and the ∆G of interaction (solvation free energy) was −7.49 kcal/mol (Fig. 2H). To validate the ATGL-COP1 docking, the solvation free energy of interaction of the docked complex was compared with other complexes with an interface area of a similar size (Fig. 2H). Collectively, using in silico modeling and docking, we provide support for direct binding of COP1 with ATGL.

To test whether COP1 functions as an E3 ligase for ATGL, we overexpressed and knocked down COP1 in HepG2 cells (Fig. 3A). Overexpression of COP1 significantly decreased, but siRNA-mediated depletion of COP1 increased the ATGL protein level without any change in the ATGL mRNA expression (data not shown). Moreover, an increase in the ATGL protein after COP1 knockdown resulted in a significant reduction in the level of ATGL ubiquitination (Fig. 3B). Further, we find that COP1-dependent ATGL ubiquitination was considerably reduced in the K100R ATGL mutant (Fig. 3C), suggesting that COP1 ubiquitinates ATGL predominantly at the 100th lysine residue. Albeit with appreciably decreased intensity, the presence of background smear could be a result of low abundant ubiquitination on other lysine residues or of nonspecific ubiquination by overexpressed COP1. To further test this possibility, we asked whether K100R mutation increases the ATGL protein’s half life. Thus HepG2 cells were transfected with wild-type (WT) or K100R mutant ATGL and treated with protein translation inhibitor cycloheximide for different time periods, as shown in Fig. 3D. K100R mutant had significantly longer half life (≥24 h) than WT ATGL (∼16 h), suggesting COP1 predominantly ubiquitinates at lysine the 100th lysine residue (Fig. 3D, bottom panel). Taken together, we uncover a hitherto unknown posttranscriptional regulation of ATGL in hepatocytes where COP1 directly binds to ATGL via the VP motif and serves as the bona fide E3 ubiquitin ligase for ATGL.

Figure 3

COP1 regulates ATGL stability and ubiquitination in hepatocytes. A: ATGL protein levels in COP1-overexpressed and -depleted conditions in hepatocytes. Densitometric quantification of ATGL band intensity (right) normalized with actin (n = 3). B: Ubiquitination status of ATGL in COP1-depleted hepatocytes. IB, immunoblot; IP, immunoprecipitation. C: Effect of COP1 in ubiquitination of WT and K100R mutant of ATGL assayed by Ni pull-down. The immunoblots are representative of one of at least three independent experiments. D: Cycloheximide (Chx) chase experiment in HepG2 cells transfected with WT or K100R mutant ATGL for indicated time durations (top). Densitometric analysis of ATGL levels normalized to actin for three independent experiments (bottom). EV, empty vector; sc, scrambled. Data are expressed as mean ± SD. *P < 0.05; **P < 0.01.

Figure 3

COP1 regulates ATGL stability and ubiquitination in hepatocytes. A: ATGL protein levels in COP1-overexpressed and -depleted conditions in hepatocytes. Densitometric quantification of ATGL band intensity (right) normalized with actin (n = 3). B: Ubiquitination status of ATGL in COP1-depleted hepatocytes. IB, immunoblot; IP, immunoprecipitation. C: Effect of COP1 in ubiquitination of WT and K100R mutant of ATGL assayed by Ni pull-down. The immunoblots are representative of one of at least three independent experiments. D: Cycloheximide (Chx) chase experiment in HepG2 cells transfected with WT or K100R mutant ATGL for indicated time durations (top). Densitometric analysis of ATGL levels normalized to actin for three independent experiments (bottom). EV, empty vector; sc, scrambled. Data are expressed as mean ± SD. *P < 0.05; **P < 0.01.

Close modal

COP1 Controls Lipid Content and Mobilization in Hepatocytes

If COP1 targets ATGL for proteasomal degradation, depletion of COP1 should increase the rate of lipolysis and, hence, decrease cellular lipid accumulation and increase in lipid mobilization. To examine this possibility, cells were treated with oleate-BSA conjugate for 16 h and stained with Oil Red O, which stains neutral lipids, or BODIPY 493/503, a hydrophobic fluorescent dye that stains LDs. As shown in Fig. 4A and C knockdown or overexpression of COP1, respectively, attenuated and enhanced oleate-dependent TAG accumulation. Likewise, the number of cellular LDs was also significantly decreased when COP1 was knocked down (Fig. 4B) and increased when COP1 was overexpressed (Fig. 4D). Accumulation of LDs also corroborates with the cellular TAG content. We thus found a significant drop in oleate-induced TAG accumulation when COP1 was depleted (Fig. 4E) and a significant increase in TAG when COP1 was overexpressed (Fig. 4F).

Figure 4

COP1 regulates hepatocyte lipid metabolism. A and C: Differential intracellular LD staining using Oil Red O or BODIPY (493/503) for indicated experimental conditions. EV, empty vector; OA, oleic acid; sc, scrambled. Scale bars, 10 µm. B and D: Intracellular LD number for mentioned experimental conditions. Data are presented as mean LD number per cell ± SD. E and F: Cellular TAG concentrations for different conditions normalized to protein concentrations. G: Schematic presentation of fluorescent FA pulse-chase assay. Cells were labeled with Red C12, a saturated FA analog, followed by treatment with hydrophobic BODIPY 493/503 (green) for LD staining and visualizing fluorescence with confocal microscopy. H: Confocal microscopy showing LDs and Red C12 following the assay as described in G for indicated experimental conditions. BF, bright field. Scale bars, 10 µm. I: FA mobilization index for different experimental conditions. J: FAO rate for the indicated experimental conditions. Data are expressed as mean ± SD. NS, not significant. *P < 0.05; **P < 0.01.

Figure 4

COP1 regulates hepatocyte lipid metabolism. A and C: Differential intracellular LD staining using Oil Red O or BODIPY (493/503) for indicated experimental conditions. EV, empty vector; OA, oleic acid; sc, scrambled. Scale bars, 10 µm. B and D: Intracellular LD number for mentioned experimental conditions. Data are presented as mean LD number per cell ± SD. E and F: Cellular TAG concentrations for different conditions normalized to protein concentrations. G: Schematic presentation of fluorescent FA pulse-chase assay. Cells were labeled with Red C12, a saturated FA analog, followed by treatment with hydrophobic BODIPY 493/503 (green) for LD staining and visualizing fluorescence with confocal microscopy. H: Confocal microscopy showing LDs and Red C12 following the assay as described in G for indicated experimental conditions. BF, bright field. Scale bars, 10 µm. I: FA mobilization index for different experimental conditions. J: FAO rate for the indicated experimental conditions. Data are expressed as mean ± SD. NS, not significant. *P < 0.05; **P < 0.01.

Close modal

ATGL serves as a major hepatic TAG hydrolase (16), and modulation of its expression concomitantly alters cellular FA mobilization. As COP1 degrades ATGL, its differential expression would also correspondingly modulate FA mobilization. To test how COP1 controls FA mobilization in hepatocytes, we performed a pulse-chase assay, as described by Rambold et al. (45) (Fig. 4G). The ratio of red and green channel area that represents the distribution of FAs outside the LDs was calculated as the FA mobilization index. Thus, stable knockdown (shATGL) or overexpression of ATGL in HepG2 cells respectively decreased or increased FA mobilization (Supplementary Fig. 4A and B). Both in control and in COP1-overexpressing cells, RedC12 fluorescence remains mostly localized to LDs, as revealed by the yellow color in the merge panel. In contrast, siRNA-mediated depletion of COP1 showed diffused Red C12 resulting a significant drop in the yellow signal (Fig. 4H). Similar to ATGL overexpressing cells, we also found a significant increase in the FA mobilization index in the siCOP1 transfected cells (Fig. 4I). COP1-dependent FA mobilization would also correspondingly modulate the FAO rate; thus, FAO rates were, respectively, increased or diminished upon COP1 knockdown or overexpression (Fig. 4J). Collectively, our findings clearly indicate an important role of COP1 in hepatocyte lipid metabolism.

ATGL Is Required for COP1-Dependent Hepatic Lipid Metabolism

The metabolic output of COP1 could be mediated via one or more of its targets. We thereby asked whether ATGL is necessary for COP1-dependent hepatocyte lipid metabolism. Knockdown of COP1 in ATGL-depleted cells would not significantly alter COP1-dependent lipid metabolism. In line with this argument, we transiently depleted COP1 (siCOP1) in shATGL cells. Although shATGL cells accumulate higher LDs and TAG, siRNA-mediated knockdown of COP1 (siCOP1+shATGL) did not show any difference even after oleate induction (Fig. 5A–C). Consistently, in the FA mobilization assay, siCOP1 in shATGL cells did not show any difference over shATGL cells in merged yellow signal (Fig. 5D) or in FA mobilization index (Fig. 5E), implying no further change in FA mobilization from cellular lipid stores. The FAO rate also remains similar after siRNA-mediated COP1 knockdown in shATGL cells (Fig. 5F).

Figure 5

COP1-mediated hepatic fat metabolism is ATGL dependent. A and G: BODIPY (493/503) staining of intracellular LDs in indicated experimental conditions. EV, empty vector; OA, oleic acid. Scale bars, 10 µm. B and H: Intracellular LD number for each condition. Data are expressed as mean LD number per cell ± SD. C and I: Measurement of intracellular TAG for indicated conditions. sc, scrambled. D and J: Confocal microscopy showing LDs and Red C12 following the assay as described in Fig. 4G for different conditions. BF, bright field. Scale bars, 10 µm. E and K: FA mobilization index for mentioned experimental conditions. F and L: FAO rate for indicated conditions. Protein normalized data are presented. Data are expressed as mean ± SD. NS, not significant. *P < 0.05; **P < 0.01.

Figure 5

COP1-mediated hepatic fat metabolism is ATGL dependent. A and G: BODIPY (493/503) staining of intracellular LDs in indicated experimental conditions. EV, empty vector; OA, oleic acid. Scale bars, 10 µm. B and H: Intracellular LD number for each condition. Data are expressed as mean LD number per cell ± SD. C and I: Measurement of intracellular TAG for indicated conditions. sc, scrambled. D and J: Confocal microscopy showing LDs and Red C12 following the assay as described in Fig. 4G for different conditions. BF, bright field. Scale bars, 10 µm. E and K: FA mobilization index for mentioned experimental conditions. F and L: FAO rate for indicated conditions. Protein normalized data are presented. Data are expressed as mean ± SD. NS, not significant. *P < 0.05; **P < 0.01.

Close modal

On the basis of these results, we argue that ectopic expression of COP1 in ATGL-overexpressing cells cellular lipid turnover would be unaffected. To this end, we expressed COP1 with increasing levels in HepG2 cells stably expressing ATGL and found that COP1 dose-dependently reduced ATGL proteins even in these cells (Supplementary Fig. 4C). To address our hypothesis, we thus chose an optimum level of COP1 expression where ATGL proteins are present at a physiologically relevant level. In contrast to shATGL cells, ATGL-overexpressing cells had a lower LD number and TAG content (Fig. 5G–I). Coexpression of COP1 partially reversed the effects of ATGL expression; however, they remained significantly lower compared with the cells transfected with empty vector (Fig. 5G–I). In agreement with that, COP1 could not reduce FA mobilization (Fig. 5J and K) and the rate of FAO (Fig. 5L) in the ATGL-overexpressing cells. Taken together, these rescue experiments indicate that ATGL is required for COP1-mediated regulation of hepatic lipid storage and its mobilization.

COP1 Knockdown Ameliorates Hepatic Steatosis in HFD-Fed Mice

Given the important role of COP1 in TAG accumulation in cultured hepatocytes, we next sought to examine the effect of COP1 inhibition in an HFD-induced fatty liver mouse model. Because of hepatic tropism of adenovirus, we used an adenovirus-based gene-targeting approach to specifically knockdown COP1 (shAd) in livers of male C57Bl/6 mice fed the HFD for 4 weeks. We found a significant reduction of COP1 expressions with a concomitant increase in ATGL protein levels in the mouse liver (Fig. 6A–C). Compared with livers from chow-fed mice, TAG levels were expectedly higher in HFD-fed animals, whereas shAd lowered its levels (Fig. 6D). Knockdown of hepatic COP1 also consistently decreased serum TAG levels but did not reach statistical significance (Fig. 6E). H&E staining of shAd liver sections revealed a reduction in hepatic lipid accumulation (Fig. 6F). Conversely, no corresponding alterations in serum and liver cholesterol levels were observed (Fig. 6G and H). Collectively, our results demonstrate that knockdown of COP1 in mouse liver increases ATGL levels and prevents TAG accumulation in diet-induced hepatic steatosis.

Figure 6

Knockdown of hepatic COP1 reduces hepatic lipid accumulation and improves liver function in HFD-fed mice. HFD-fed mice were injected with adenovirus carrying shRNA against murine COP1 (shAd, green) or with vehicle (mock, red). Relative mRNA expression (A) and protein levels (B) of COP1 and ATGL in livers of indicated mice. C: Relative quantification of the band intensity normalized with actin (n = 6). Data are expressed as mean ± SD relative to mock. Liver (D) and serum TAG (E) levels of chow-fed control (black), HFD (red), and shAd (green) mice. F: The H&E staining of liver sections from indicated mice. Scale bars, 100 μm. Cholesterol levels were assayed from serum (G) and liver tissue (H). Liver activity measured by analyzing 99mTc-mebrofenin signal 30 min after injection (n = 4) (I) and quantification of 99mTc-mebrofenin distribution in liver and gall bladder by calculating the area under the curve (AUC) at different time points for 30 min through 180 time frames, with data expressed as mean ± SD relative to chow (J). *P < 0.05, **P < 0.01 compared with chow or mock.

Figure 6

Knockdown of hepatic COP1 reduces hepatic lipid accumulation and improves liver function in HFD-fed mice. HFD-fed mice were injected with adenovirus carrying shRNA against murine COP1 (shAd, green) or with vehicle (mock, red). Relative mRNA expression (A) and protein levels (B) of COP1 and ATGL in livers of indicated mice. C: Relative quantification of the band intensity normalized with actin (n = 6). Data are expressed as mean ± SD relative to mock. Liver (D) and serum TAG (E) levels of chow-fed control (black), HFD (red), and shAd (green) mice. F: The H&E staining of liver sections from indicated mice. Scale bars, 100 μm. Cholesterol levels were assayed from serum (G) and liver tissue (H). Liver activity measured by analyzing 99mTc-mebrofenin signal 30 min after injection (n = 4) (I) and quantification of 99mTc-mebrofenin distribution in liver and gall bladder by calculating the area under the curve (AUC) at different time points for 30 min through 180 time frames, with data expressed as mean ± SD relative to chow (J). *P < 0.05, **P < 0.01 compared with chow or mock.

Close modal

We next examined the effects of hepatic COP1 depletion on the functional restoration of HFD-induced liver damage. To assay liver function in vivo, we injected 99mTc-mebrofenin through a tail vein and monitored its clearance from the liver into the gall bladder over 30 min using a gamma camera, as described earlier (46). No difference was detected in hepatic 99mTc-mebrofenin uptake in animals fed chow or the HFD. However, HFD-fed mice showed dampened 99mTc-mebrofenin clearance from the liver into the gall bladder (Fig. 6I and J and Supplementary Fig. 5). Conversely, shAd animals fed the HFD revealed significant recovery of 99mTc-mebrofenin clearance comparable to chow-fed mice (Fig. 6I and J and Supplementary Fig. 5). We thus find that COP1 plays an important role in liver function and hepatobiliary transport in diet-induced steatosis.

Control of ATGL expression has extensively been studied in adipocytes (12,13,30); however, its regulation in other metabolically active tissues, including the liver, is essentially unknown. Although ubiquitination of ATGL has been reported in adipose tissue (47), where ATGL expression is predominantly controlled transcriptionally, the molecular details of such ubiquitination are lacking. Using various biochemical and in silico tools, we describe the ubiquitin-proteasome system as a critical regulator of hepatic ATGL content, which in turn is linked to hepatic TAG turnover, particularly in the context of HFD-induced NAFLD. Molecular pathogenesis of NAFLD and its downstream sequelae involve a multitude of metabolic pathways, including hepatic insulin resistance, augmented de novo lipogenesis and TAG synthesis, impaired FAO, altered TAG secretion, and lipid sequestration by lipolysis, (48) of which the latter has been the focus of the current study.

In summary, we identify COP1 as a novel player in controlling hepatic TAG metabolism that is mediated by its direct interaction through VP-motif and K48-linked polyubiquitination of ATGL predominantly at lysine 100. However, we cannot exclude the existence of other E3 ubiquitin ligases that can also target ATGL. In adipose, COP1 degrades acetyl CoA carboxylase, the rate-limiting enzyme for lipogenesis, and stimulates lipolysis (27), whereas in the liver it ubiquitinates FA synthase (49). Interestingly, COP1 was also shown to control hepatic gluconeogenesis through FoxO1 (23) or TORC2 (29), both of which are transcriptional regulators of gluconeogenesis. Together with previous studies, our results thus support the notion that COP1 integrates multiple metabolic outputs to maintain hepatic metabolic homeostasis. Thus identification of COP1-mediated ATGL degradation in the current study not only provides novel insight into how hepatic TAG turnover is maintained but also offers new therapeutic strategies by targeting COP1 in hepatic steatosis.

M.G., S.N., and M.B. contributed equally to this work.

Acknowledgments. The authors thank Mita Chatterjee Debnath, Council of Scientific and Industrial Research–Indian Institute of Chemical Biology, Kolkata, and Samarendu Sinha, Regional Radiation and Medicine Centre, Variable Energy Cyclotron Centre, Kolkata, for their assistance with the 99mTc-mebrofenin experiments, and Sounak Bhattacharya, Council of Scientific and Industrial Research–Indian Institute of Chemical Biology, Kolkata, for help with confocal microscopy.

Funding. M.G., M.B., and D.K.N. received research fellowships from the Council of Scientific and Industrial Research, India. S.N. and M.A. received research fellowships from the Department of Science and Technology–Innovation in Science Pursuit for Inspired Research and University Grants Commission, India, respectively. This work was supported by Council of Scientific and Industrial Research, India, grants BSC 0121 to S.C. and BSC 0206 to P.C. and Department of Science and Technology, Ministry of Science and Technology, India, grant SB/S0/BB/007/2013 to P.C.

Duality of Interest. No potential conflicts of interest relevant to this article were reported.

Author Contributions. M.G. performed experiments for Figs. 13 and 6. M.G., S.N., S.C., and P.C. analyzed data. S.N. conducted experiments for Figs. 46. M.B. performed the in silico studies. M.A. generated cell lines and screened. D.K.N. conducted the 99mTc-mebrofenin experiments. S.C. and P.C. designed the research. P.C. wrote the paper. P.C. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

1.
Ahmed
A
,
Wong
RJ
,
Harrison
SA
.
Nonalcoholic fatty liver disease review: Diagnosis, treatment, and outcomes
.
Clin Gastroenterol Hepatol
2015
;
13
:
2062
2070
[PubMed]
2.
Ludwig
J
,
Viggiano
TR
,
McGill
DB
,
Oh
BJ
.
Nonalcoholic steatohepatitis: Mayo Clinic experiences with a hitherto unnamed disease
.
Mayo Clin Proc
1980
;
55
:
434
438
[PubMed]
3.
Marchesini
G
,
Brizi
M
,
Morselli-Labate
AM
, et al
.
Association of nonalcoholic fatty liver disease with insulin resistance
.
Am J Med
1999
;
107
:
450
455
[PubMed]
4.
Parks
EJ
,
Krauss
RM
,
Christiansen
MP
,
Neese
RA
,
Hellerstein
MK
.
Effects of a low-fat, high-carbohydrate diet on VLDL-triglyceride assembly, production, and clearance
.
J Clin Invest
1999
;
104
:
1087
1096
[PubMed]
5.
Cohen
JC
,
Horton
JD
,
Hobbs
HH
.
Human fatty liver disease: old questions and new insights
.
Science
2011
;
332
:
1519
1523
[PubMed]
6.
Kato
M
,
Higuchi
N
,
Enjoji
M
.
Reduced hepatic expression of adipose tissue triglyceride lipase and CGI-58 may contribute to the development of non-alcoholic fatty liver disease in patients with insulin resistance
.
Scand J Gastroenterol
2008
;
43
:
1018
1019
[PubMed]
7.
Zimmermann
R
,
Strauss
JG
,
Haemmerle
G
, et al
.
Fat mobilization in adipose tissue is promoted by adipose triglyceride lipase
.
Science
2004
;
306
:
1383
1386
[PubMed]
8.
Villena
JA
,
Roy
S
,
Sarkadi-Nagy
E
,
Kim
KH
,
Sul
HS
.
Desnutrin, an adipocyte gene encoding a novel patatin domain-containing protein, is induced by fasting and glucocorticoids: ectopic expression of desnutrin increases triglyceride hydrolysis
.
J Biol Chem
2004
;
279
:
47066
47075
[PubMed]
9.
Jenkins
CM
,
Mancuso
DJ
,
Yan
W
,
Sims
HF
,
Gibson
B
,
Gross
RW
.
Identification, cloning, expression, and purification of three novel human calcium-independent phospholipase A2 family members possessing triacylglycerol lipase and acylglycerol transacylase activities
.
J Biol Chem
2004
;
279
:
48968
48975
[PubMed]
10.
Haemmerle
G
,
Lass
A
,
Zimmermann
R
, et al
.
Defective lipolysis and altered energy metabolism in mice lacking adipose triglyceride lipase
.
Science
2006
;
312
:
734
737
[PubMed]
11.
Fischer
J
,
Lefèvre
C
,
Morava
E
, et al
.
The gene encoding adipose triglyceride lipase (PNPLA2) is mutated in neutral lipid storage disease with myopathy
.
Nat Genet
2007
;
39
:
28
30
[PubMed]
12.
Chakrabarti
P
,
Kandror
KV
.
FoxO1 controls insulin-dependent adipose triglyceride lipase (ATGL) expression and lipolysis in adipocytes
.
J Biol Chem
2009
;
284
:
13296
13300
[PubMed]
13.
Chakrabarti
P
,
Kim
JY
,
Singh
M
, et al
.
Insulin inhibits lipolysis in adipocytes via the evolutionarily conserved mTORC1-Egr1-ATGL-mediated pathway
.
Mol Cell Biol
2013
;
33
:
3659
3666
[PubMed]
14.
Nielsen
R
,
Pedersen
TA
,
Hagenbeek
D
, et al
.
Genome-wide profiling of PPARgamma:RXR and RNA polymerase II occupancy reveals temporal activation of distinct metabolic pathways and changes in RXR dimer composition during adipogenesis
.
Genes Dev
2008
;
22
:
2953
2967
[PubMed]
15.
Subramanian
V
,
Rothenberg
A
,
Gomez
C
, et al
.
Perilipin A mediates the reversible binding of CGI-58 to lipid droplets in 3T3-L1 adipocytes
.
J Biol Chem
2004
;
279
:
42062
42071
[PubMed]
16.
Ong
KT
,
Mashek
MT
,
Bu
S
,
Greenberg
AS
,
Mashek
DG
.
Adipose triglyceride lipase is a major hepatic lipase that regulates triacylglycerol turnover and fatty acid signaling and partitioning
.
Hepatology
2011
;
53
:
116
126
[PubMed]
17.
Wu
JW
,
Wang
SP
,
Alvarez
F
, et al
.
Deficiency of liver adipose triglyceride lipase in mice causes progressive hepatic steatosis
.
Hepatology
2011
;
54
:
122
132
[PubMed]
18.
Chitraju
C
,
Trötzmüller
M
,
Hartler
J
, et al
.
The impact of genetic stress by ATGL deficiency on the lipidome of lipid droplets from murine hepatocytes
.
J Lipid Res
2013
;
54
:
2185
2194
[PubMed]
19.
Ong
KT
,
Mashek
MT
,
Bu
SY
,
Mashek
DG
.
Hepatic ATGL knockdown uncouples glucose intolerance from liver TAG accumulation
.
FASEB J
2013
;
27
:
313
321
[PubMed]
20.
Nalepa
G
,
Rolfe
M
,
Harper
JW
.
Drug discovery in the ubiquitin-proteasome system
.
Nat Rev Drug Discov
2006
;
5
:
596
613
[PubMed]
21.
Hershko
A
,
Heller
H
,
Elias
S
,
Ciechanover
A
.
Components of ubiquitin-protein ligase system. Resolution, affinity purification, and role in protein breakdown
.
J Biol Chem
1983
;
258
:
8206
8214
[PubMed]
22.
Nakatsukasa
K
,
Okumura
F
,
Kamura
T
.
Proteolytic regulation of metabolic enzymes by E3 ubiquitin ligase complexes: lessons from yeast
.
Crit Rev Biochem Mol Biol
2015
;
50
:
489
502
[PubMed]
23.
Kato
S
,
Ding
J
,
Pisck
E
,
Jhala
US
,
Du
K
.
COP1 functions as a FoxO1 ubiquitin E3 ligase to regulate FoxO1-mediated gene expression
.
J Biol Chem
2008
;
283
:
35464
35473
[PubMed]
24.
Migliorini
D
,
Bogaerts
S
,
Defever
D
, et al
.
Cop1 constitutively regulates c-Jun protein stability and functions as a tumor suppressor in mice
.
J Clin Invest
2011
;
121
:
1329
1343
[PubMed]
25.
Dornan
D
,
Wertz
I
,
Shimizu
H
, et al
.
The ubiquitin ligase COP1 is a critical negative regulator of p53
.
Nature
2004
;
429
:
86
92
[PubMed]
26.
Wertz
IE
,
O’Rourke
KM
,
Zhang
Z
, et al
.
Human De-etiolated-1 regulates c-Jun by assembling a CUL4A ubiquitin ligase
.
Science
2004
;
303
:
1371
1374
[PubMed]
27.
Qi
L
,
Heredia
JE
,
Altarejos
JY
, et al
.
TRB3 links the E3 ubiquitin ligase COP1 to lipid metabolism
.
Science
2006
;
312
:
1763
1766
[PubMed]
28.
Dentin
R
,
Liu
Y
,
Koo
SH
, et al
.
Insulin modulates gluconeogenesis by inhibition of the coactivator TORC2
.
Nature
2007
;
449
:
366
369
[PubMed]
29.
Suriben
R
,
Kaihara
KA
,
Paolino
M
, et al
.
β-Cell Insulin Secretion Requires the Ubiquitin Ligase COP1
.
Cell
2015
;
163
:
1457
1467
[PubMed]
30.
Chakrabarti
P
,
English
T
,
Shi
J
,
Smas
CM
,
Kandror
KV
.
Mammalian target of rapamycin complex 1 suppresses lipolysis, stimulates lipogenesis, and promotes fat storage
.
Diabetes
2010
;
59
:
775
781
[PubMed]
31.
Zlatkis
A
,
Zak
B
,
Boyle
AJ
.
A new method for the direct determination of serum cholesterol
.
J Lab Clin Med
1953
;
41
:
486
492
[PubMed]
32.
Berman
HM
,
Westbrook
J
,
Feng
Z
, et al
.
The Protein Data Bank
.
Nucleic Acids Res
2000
;
28
:
235
242
[PubMed]
33.
Lo Conte
L
,
Ailey
B
,
Hubbard
TJ
,
Brenner
SE
,
Murzin
AG
,
Chothia
C
.
SCOP: a structural classification of proteins database
.
Nucleic Acids Res
2000
;
28
:
257
259
[PubMed]
34.
Jones
DT
.
Protein secondary structure prediction based on position-specific scoring matrices
.
J Mol Biol
1999
;
292
:
195
202
[PubMed]
35.
Kelley
LA
,
Mezulis
S
,
Yates
CM
,
Wass
MN
,
Sternberg
MJ
.
The Phyre2 web portal for protein modeling, prediction and analysis
.
Nat Protoc
2015
;
10
:
845
858
[PubMed]
36.
Eswar
N
,
Eramian
D
,
Webb
B
,
Shen
MY
,
Sali
A
.
Protein structure modeling with MODELLER
.
Methods Mol Biol
2008
;
426
:
145
159
[PubMed]
37.
Roy
A
,
Kucukural
A
,
Zhang
Y
.
I-TASSER: a unified platform for automated protein structure and function prediction
.
Nat Protoc
2010
;
5
:
725
738
[PubMed]
38.
Lindahl E, Azuara C, Koehl P, Delarue M. NOMAD-Ref: visualization, deformation and refinement of macromolecular structures based on all-atom normal mode analysis. Nucleic Acids Res 2006;34(Web Server issue):W52–W56.
39.
Eisenberg
D
,
Lüthy
R
,
Bowie
JU
.
VERIFY3D: assessment of protein models with three-dimensional profiles
.
Methods Enzymol
1997
;
277
:
396
404
[PubMed]
40.
Davis IW, Leaver-Fay A, Chen VB, Block JN, et al. MolProbity: all-atom contacts and structure validation for proteins and nucleic acids. Nucleic Acids Res 2007;35(Web Server issue):W375–W383
41.
Krissinel
E
,
Henrick
K
.
Inference of macromolecular assemblies from crystalline state
.
J Mol Biol
2007
;
372
:
774
797
[PubMed]
42.
Schneidman-Duhovny D, Inbar Y, Nussinov R, Wolfson HJ. PatchDock and SymmDock: servers for rigid and symmetric docking. Nucleic Acids Res 2005;33(Web Server issue):W363–W367.
43.
Mashiach E, Schneidman-Duhovny D, Andrusier N. FireDock: a web server for fast interaction refinement in molecular docking. Nucleic Acids Res 2008;36(Web Server issue):W229–W232.
44.
Pettersen
EF
,
Goddard
TD
,
Huang
CC
, et al
.
UCSF Chimera--a visualization system for exploratory research and analysis
.
J Comput Chem
2004
;
25
:
1605
1612
[PubMed]
45.
Rambold
AS
,
Cohen
S
,
Lippincott-Schwartz
J
.
Fatty acid trafficking in starved cells: regulation by lipid droplet lipolysis, autophagy, and mitochondrial fusion dynamics
.
Dev Cell
2015
;
32
:
678
692
[PubMed]
46.
Neyt
S
,
Huisman
MT
,
Vanhove
C
, et al
.
In vivo visualization and quantification of (Disturbed) Oatp-mediated hepatic uptake and Mrp2-mediated biliary excretion of 99mTc-mebrofenin in mice
.
J Nucl Med
2013
;
54
:
624
630
[PubMed]
47.
Dai
Z
,
Qi
W
,
Li
C
, et al
.
Dual regulation of adipose triglyceride lipase by pigment epithelium-derived factor: a novel mechanistic insight into progressive obesity
.
Mol Cell Endocrinol
2013
;
377
:
123
134
[PubMed]
48.
Sun
Z
,
Lazar
MA
.
Dissociating fatty liver and diabetes
.
Trends Endocrinol Metab
2013
;
24
:
4
12
[PubMed]
49.
Yu
J
,
Deng
R
,
Zhu
HH
, et al
.
Modulation of fatty acid synthase degradation by concerted action of p38 MAP kinase, E3 ligase COP1, and SH2-tyrosine phosphatase Shp2
.
J Biol Chem
2013
;
288
:
3823
3830
[PubMed]
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