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. Author manuscript; available in PMC: 2019 Oct 15.
Published in final edited form as: J Mol Endocrinol. 2018 Oct 15;61(4):195–205. doi: 10.1530/JME-18-0154

Loss of DBC1 (CCAR2) affects TNFα-induced lipolysis and Glut4 gene expression in murine adipocytes.

Ashley A Able 1,2, Allison J Richard 1, Jacqueline M Stephens 1,2,*
PMCID: PMC6193813  NIHMSID: NIHMS1506390  PMID: 30139876

Abstract

STAT5A (signal transducer and activator of transcription 5A) is a transcription factor that plays a role in adipocyte development and function. In this study, we report DBC1 (deleted in breast cancer 1; also known as CCAR2) as a novel STAT5A-interacting protein. DBC1 has been primarily studied in tumor cells, but there is evidence that loss of this protein may promote metabolic health in mice. Currently, the functions of DBC1 in mature adipocytes are largely unknown. Using immunoprecipitation and immunoblotting techniques, we confirmed that there is an association between endogenous STAT5A and DBC1 proteins under physiological conditions in the adipocyte nucleus that is not dependent upon STAT5A tyrosine phosphorylation. We used siRNA to knockdown DBC1 in 3T3-L1 adipocytes to determine the impact on STAT5A activity, adipocyte gene expression, and TNFα (tumor necrosis factor α)-regulated lipolysis. The loss of DBC1 did not affect the expression of several STAT5A target genes including Socs3, Cish, Bcl6, Socs2, and Igf1. However, we did observe decreased levels of TNFα-induced glycerol and free fatty acids released from adipocytes with reduced DBC1 expression. In addition, DBC1-knockdown adipocytes had increased Glut4 expression. In summary, DBC1 can associate with STAT5A in adipocyte nucleus, but it does not appear to impact regulation of STAT5A target genes. Loss of adipocyte DBC1 modestly increases Glut4 gene expression and reduces TNFα-induced lipolysis. These observations are consistent with in vivo observations that show loss of DBC1 promotes metabolic health in mice.

Keywords: DBC1, adipocytes, gene expression, lipolysis

Introduction

Signal transducer and activators of transcription 5A (STAT5A) is a transcription factor that utilizes the Janus Kinase/Signal Transducer and Activator of Transcription (JAK/STAT) pathway to mediate the biological actions of a variety of hormones and cytokines. In vivo and in vitro approaches have demonstrated that STAT5A has a prominent role in adipogenesis (Teglund et al. 1998, Floyd & Stephens 2003, Stewart et al. 2011a, Wakao et al. 2011, Tse et al. 2013). Growth hormone (GH) is a primary activator of STAT5A in adipocytes. Upon GH activation, STAT5A can activate or repress several genes including suppressor of cytokine signaling 3 (Socs3), cytokine-inducible SH2-containing protein (Cish), B-cell lymphoma 6 (Bcl6), fatty acid synthase (Fasn), Adiponectin, and pyruvate dehydrogenase kinase 4 (Pdk4) in adipocytes (Hogan & Stephens 2005, Story & Stephens 2006, White et al. 2007, 2016, Lin et al. 2014). Despite the identification of these direct STAT5 target genes, very little is known about the molecular mechanisms that contribute to the ability of STAT5A to regulate gene expression in adipocytes. To further investigate the functions of STAT5A in adipocytes, we sought to identify novel proteins that interact with STAT5A by performing a non-biased co-immunoprecipitation and mass spectrometry approach (Richard et al. 2017). This approach identified DBC1 (deleted in breast cancer 1) as a potential STAT5A-interacting protein.

DBC1, also referred to as CCAR2 (cell cycle and apoptosis regulator 2), is a pleiotropic protein that is primarily localized in the nucleus. DBC1 has been shown to physically interact and negatively regulate several epigenetic modifiers including sirtuin 1 (SIRT1), histone deacetylase 3 (HDAC3), and suppressor of variegation 3–9 homolog 1 (SUV39H1) (Zhao et al. 2008, Li et al. 2009, Chini et al. 2010). SIRT1 is a nicotinamide adenine dinucleotide (NAD)-dependent deacetylase involved in a variety of cellular processes including regulation of obesity-associated metabolic diseases, cancer, aging, and cellular senescence (Rahman & Islam 2011). A loss of DBC1 expression is associated with increased SIRT1 activity in A459 human alveolar basal epithelial cells (Zhao et al. 2008). DBC1 also interacts and negatively regulates estrogen receptor β (ERβ) and breast cancer 1 susceptibility protein 1 (BRCA1) (Hiraike et al. 2010, Koyama et al. 2010). In addition, DBC1 can be present in a complex with and positively regulate estrogen receptor α (ERα), androgen receptor (AR), and nuclear receptor subfamily 1, group D, member 2 (Rev-erbα) (Fu et al. 2009, Yu et al. 2011, Chini et al. 2013). DBC1 has also been shown to physically interact with and positively regulate IKK-α and IKK-β; two kinases that are part of the inhibitor of kappa B Kinase (IKK) complex that affects nuclear factor kappa B (NF-κB) signaling and transcriptional activity (Kong et al. 2015).

To date, most DBC1 studies have been performed in tumor cells and little is known about the function of DBC1 in adipocytes. However, studies have shown that knockdown of DBC1 in 3T3-L1 preadipocytes promotes adipocyte development in vitro (Moreno-Navarrete et al. 2015a). Also, DBC1 knockout mice have increased fat accumulation in adipose tissue, but remain metabolically healthy (Escande et al. 2015). DBC1 knockout mice maintained insulin sensitivity, had lower circulating free fatty acids, and were protected against atherosclerosis and liver steatosis following diet induced obesity (Escande et al. 2015). Other studies have shown that loss of DBC1 in 3T3-L1 adipocytes results in decreased expression of inflammatory markers such as interleukin 6 (IL-6), monocyte chemoattractant protein 1 (MCP1), and tumor necrosis factor alpha (TNFα), indicating that DBC1 may influence adipocyte inflammation (Moreno-Navarrete et al. 2015). DBC1 has also been implicated in senescence of preadipocytes as loss of DBC1 protects again cellular senescence and senescence-driven inflammation in obesity (Escande et al. 2014).

Our studies are the first to show that DBC1 is present in a complex with STAT5A under physiological conditions in the nucleus of adipocytes. However, knockdown approaches revealed that DBC1 does not have a profound effect on the ability of growth hormone to regulate STAT5 target genes. In studies to observe an impact of DBC1 loss in adipocytes, we found that DBC1 can impact TNFα-mediated lipolysis in mature 3T3-L1 adipocytes. Although, DBC1 did not have a profound effect on TNFα-mediated changes in Mcp-1 or Adiponectin expression, the loss of DBC1 resulted in increased Glut4 expression.

Materials and Methods

Cell culture

Murine 3T3-L1 preadipocytes (obtained from Dr. Howard Green at Harvard University) were grown in Dulbecco’s Modified Eagle’s Media (DMEM) (Sigma-Aldrich, St. Louis, MO) with 10% bovine calf serum. Two days after confluence, the preadipocytes were induced to differentiate using a standard protocol and 3-isobutyl-methylxanthine, dexamethasone, insulin (MDI) induction cocktail plus 10% fetal bovine serum (FBS) in DMEM (Richard et al. 2017). HyClone calf and fetal bovine serum were purchased from Thermo Scientific (Waltham, MA) or GE Healthcare Life Sciences (Marlborough, MA). The medium was changed every 48–72 hours during growth and differentiation. Cells were serum deprived by changing the medium to DMEM containing 1% calf serum for 16 – 24 h before treatment with murine growth hormone (mGH) or murine TNFα. Recombinant murine GH was obtained from Dr. A.F. Parlow at the National Hormone and Peptide Program (NHPP; Torrance, CA). Recombinant murine TNFα was purchased from Thermo Fisher (Waltham, MA; Cat #: PMC3013).

Small interfering RNA (siRNA)-mediated knockdown

3T3-L1 adipocytes (5–7 days post-MDI) were trypsinized and re-plated in 6-well, 12-well, or 24-well plates at a density of 5.8 × 105 cells/cm2 in antibiotic-free medium (10% FBS/DMEM). Using the protocol from Dharmacon, adipocytes were transfected with 50 nM siRNA (Dharmacon, Lafayette, CO; Non-targeting siRNA Cat #: D-001810–10-50, siRNA targeting DBC1 Cat #: L-047837–00-0005) and the DharmaFECT Duo reagent (Dharmacon, Lafayette, CO, Cat #: T-2010–03) in OptiMEM reduced serum medium (Thermo Fisher, Waltham, MA; Cat #: 31985088). Non-targeting siRNA was used as negative control. After 24hrs, siRNA-containing media was removed, replaced with antibiotic-free 10% FBS/DMEM, and cells were transfected again with 50 nM siRNA. After 24 hours, the media was removed and replaced with antibiotic-free 10% FBS/DMEM. Cell monolayers were collected 72 hours following the initial transfection and harvested for protein in immunoprecipitation (IP) buffer, and for RNA in buffer provided in the RNeasy mini kit (Qiagen, Hilden, Germany) to assess knockdown efficiency. Knockdown of Cyclophilin B was used as a positive control to assess siRNA transfection efficiency in 3T3-L1 adipocytes because it is a well-characterized housekeeping gene that isn’t affected by experimental treatments in adipocytes and has been validated in our lab. (Dharmacon, Lafayette, CO; Cat #: D-001820–02-05).

RNA analysis

Adipocyte monolayers were harvested in lysis buffer from the RNeasy mini kit and total RNA was isolated from harvested cells using the RNeasy mini kit (Qiagen, Hilden, Germany). 10 μl of purified RNA was used for reverse transcription (RT) PCR to generate cDNA according to the Applied Biosystems protocol (Applied Biosystems, Foster City, CA; Cat #: 4368813). cDNA was quantitated using the real-time quantitative PCR (qPCR) method in a total volume of 10 μl (2 μl DNA and 8 μl reaction master mix) using an Applied Biosystems 7900HT Fast Real-Time PCR System and the qPCR amplification program specified in the kit (Clontech, Mountain View, CA; Cat #: RR420A). Cyclophilin B, Ubiquitin B, and Nono were used as endogenous controls. The following mouse genes were examined by RT-qPCR: Cyclophilin b, Ubb, Nono, Dbc1, Socs3, Cish, Bcl6, Igf1, Mcp1, Glut4, and Adiponectin using primers purchased from Integrated DNA Technologies (IDT, Coralville, IA). Primer sequences for each gene are shown in Table 1.

Table 1.

Primer sequences for each gene examined by real-time qPCR.

Gene Primer 1 Sequence Primer 2 Sequence
Cyclophilin B (PpiB) 5’-CCGTAGTGCTTCAGCTTGA-3’ 5’-AGCAAGTTCCATCGTGTCATC-3’
Ubiquitin B 5’-GCTTACCATGCAACAAAACCT-3’ 5’-CCAGTGGGCAGTGATGG-3’
Nono 5’-TCTTCAGGTCAATAGTCAAGCC-3’ 5’-CATCATCAGCATCACCACCA-3’
Dbc1 (Ccar2) 5’-TGCGTTTCTTCGAGTCATAGT-3’ 5’-CTTCCAGACATCCCACACAC-3’
Socs3 5’-TAGACTTCACGGCTGCAAC-3’ 5’-CGGGGAGCTAGTCCCGAA-3’
Cish 5’-CCGCCCAATTTGCTCCA-3’ 5’-GCTCCTTTCTCCTTCCATCC-3’
Bcl6 5’-AGTCACATTCGTTGCAGAAGA-3’ 5’-CAGAGATGTGCCTCCATACTG-3’
Igf1 5’-AGTACATCTCCAGTCTCCTCAG-3’ 5’-ATGCTCTTCAGTTCGTGTGT-3’
Mcp1 5’-GCAGAGAGCCAGACGGGAGGA-3’ 5’-TGGGGCGTTAACTGCATCTGG-3’
Glut4 5’-TCTTATTGCAGCGCCTGAG-3’ 5’-GAGAATACAGCTAGGACCAGTG-3’
Adiponectin 5’-GCAGGATTAAGAGGAACAGGAG-3’ 5’-TGTCTGTACGATTGTCAGTGG-3’
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Whole cell extract preparation

Adipocyte monolayers were rinsed once with phosphate buffered saline (PBS) and then harvested in non-denaturing IP buffer as previously described (Richard et al. 2017). The cell extract was subjected to a freeze/thaw cycle at −80°C and then passed through a 20-gauge needle three times. The whole cell extract was further purified by centrifugation at 13,000 x g for 10 min at 4°C.

Subcellular fractionation

Mature 3T3-L1 adipocytes were treated with vehicle or murine growth hormone prior to subcellular fractionation. Adipocyte monolayers from twenty 10-cm culture plates were scraped into nuclear homogenization buffer (NHB) (20 mM Tris pH 7.4, 10 mM NaCl, and 3 mL MgCl2) as previously described (Richard et al. 2017). After adding 0.15% IGEPAL CA-630 (from 10% stock) to the cell suspension, it was homogenized on ice using 16 strokes in a Dounce homogenizer. The extract was centrifuged at 2500 rpm in a Beckman GS-6KR centrifuge with a swinging bucket rotor. Subsequently, the supernatant containing cytosol and mitochondria was centrifuged as previously described (Richard et al. 2017). The nuclear pellet from the first centrifugation was washed once with half of the initial volume of NHB buffer and re-centrifuged at 4°C for 5 min at 500 rpm in the Beckman GS-6KR centrifuge. The supernatant was discarded, while the nuclear pellet was resuspended in IP buffer and incubated on ice for 1 hour. To break open the nuclei, the nuclear extract was passed through a 20G needle four times and further purified by centrifuging at 13,000 x g for 10 min at 4°C.

Measurement of protein concentration

Protein content of cell extracts was quantified using the Bicinchoninic acid (BCA) assay kit (Sigma-Aldrich, St. Louis, MO; Cat #: BCA1).

Gel electrophoresis and immunoblotting

Samples were separated on 7.5%, 10%, or 15% sodium dodecyl sulfate (SDS) polyacrylamide (PA) gels (acrylamide; National Diagnostics, Atlanta, GA; Cat #: EC-890) and transferred to nitrocellulose membranes (BioRad, Hercules, CA; Cat #: 162–0115) in 25 mM Tris, 192 mM glycine, and 20% methanol. After the transfer, the membrane was blocked in 4% milk for 1 hour at room temperature and then immunoblotted. Results were visualized with horseradish peroxidase-conjugated secondary antibodies (Jackson ImmunoResearch, West Grove, PA) and enhanced chemiluminescence (Pierce/Thermo Scientific, Waltham, MA).

Immunoprecipitation (IP)

Cell extracts (300–400 μg total protein) were incubated with 4–5 μg of immunoprecipitating antibody, diluted in IP buffer, overnight on a mini-tube rotator at 4°C. Protein A-conjugated agarose beads (IPA300 Protein A Resin; Repligen, Waltham, MA; Cat #: 10–2003-02) were added to the antibody-epitope mixture, and the conjugation reaction proceeded for an additional 3–4 h at 4°C with rotation. Following conjugation to the bead resin, the beads were pelleted by centrifugation at 13,000 rpm for 3 min at 4°C. The supernatant was removed by aspiration and the beads were washed 3 times with ice cold 1X IP buffer. Between each wash, the beads were pelleted by centrifugation at 10,000 rpm for 3 min at 4°C and the supernatant removed by aspiration. After the final wash, the IP antibody and immunoprecipitated proteins were eluted from the bead resin into 2X SDS loading buffer (LB) by boiling the samples for 10 min at 100°C. Samples were flicked every 2 minutes during heat step to ensure efficient elution. The samples were briefly centrifuged and the supernatants analyzed by SDS-PAGE and immunoblotting. A mock sample containing only IP antibody and IP buffer (no cell extract) was used as a negative control for each IP experiment.

SIRT1 activity measurement

The deacetylase activity of SIRT1 was measured using a fluorometric assay kit (Enzo Life Sciences, Farmingdale, NY; Cat #: BML-AK500–0001). Cell extracts (75 μg total protein) were incubated with 5 μg of anti-SIRT1 antibody using the immunoprecipitation method described above. After the final wash, the samples were resuspended in 100 μl of assay buffer provided by the assay kit. The manufacturer’s instructions were followed and optimized for our samples. Briefly, the deacetylase reaction was initiated by adding 50 μM of Fluor de lys® substrate and 1 mM nicotinamide adenine dinucleotide (NAD+; SIRT1 substrate) to samples. After incubating the samples for 20 minutes at room temperature, the reactions were stopped by addition of 1X Fluor de lys® developer that contained either 1 μM trichostatin A (TricA; HDAC inhibitor) or 2 mM of nicotinamide (NAM ; SIRT1 inhibitor). Samples were read in a fluorometer (SpectraMax M5) at an excitation wavelength of 360 nm and emission wavelength of 460 nm.

Measurement of glycerol and free fatty acid release

3T3-L1 adipocytes were transfected with either non-targeting or DBC1 siRNA as described above. 54 hours later, media was changed to 1% calf/DMEM and cells were treated with equivalent volume of vehicle (0.1% BSA/PBS) or 0.75 nM TNFα overnight. After 16 hours, 1% calf/DMEM was removed and replaced with incubation media that consisted of 2% fatty acid free bovine serum albumin (BSA; Sigma-Aldrich, St. Louis, MO; Cat #: A6003) and 0.1% glucose in glucose-free phenol red-free DMEM, and the cells were treated again with vehicle (0.1% BSA/PBS) or 0.75 nM TNFα. After 2 hours, 500 μL of conditioned media was collected and stored at −20°C. Glycerol release was measured using 50 μL of each sample according to the kit protocol (Millipore, Burlington, MA; Cat #: OB100). Free fatty acid release was measured using 50 μL of each sample according to the kit protocol (BioVision, Milpitas, CA; Cat #: K612).

Antibodies

Anti-STAT5A (L-20; sc1081; rabbit polyclonal) and anti-ERK1/2 (C-16; sc-93; rabbit polyclonal) antibodies were purchased from Santa Cruz Biotechnology (Dallas, TX). We used both mouse monoclonal (clone 8–5-2; 05–495) and rabbit polyclonal (07–586) anti-phospho-STAT5 A/B (Tyr 694/699) antibodies from Millipore (Burlington, MA) to detect tyrosine phosphorylated STAT5 (STAT5pY). Anti-Adiponectin (PA1–054; rabbit polyclonal) antibody was purchased from Thermo Scientific (Waltham, MA). Anti-DBC1 (5693; rabbit polyclonal) and anti-SIRT1 (1F3; 8469; mouse monoclonal) antibodies were purchased from Cell Signaling Technology (Danvers, MA).

Statistical analysis

All data were analyzed by two-tailed unpaired Student’s t-test (using GraphPad Prism 7). Results from studies of cultured adipocytes are shown as mean ± standard error of the mean (SEM). Results were considered statistically significant when p < 0.05.

Results

We previously utilized a semi-nonbiased screening approach to identify novel STAT5 interaction partners using co-immunoprecipitation and mass spectrometry. Pyruvate dehydrogenase complex-E2 (PDC-E2) was the first interacting protein that we reported from this screen (Richard et al. 2017). In our present study, we report that DBC1 was also identified as a potential novel STAT5A-interacting protein in 3T3-L1 adipocytes. To validate our mass spectrometry results, we performed co-immunoprecipitation with a STAT5A antibody followed by Western blotting using an anti-DBC1 antibody and we examined both cytosolic and nuclear extracts from mature 3T3-L1 adipocytes in the absence or presence of an acute growth hormone (GH) treatment, a condition that activates STAT5A (Figure 1A). These studies revealed that DBC1 interacts with STAT5A in the nucleus and that the nuclear localization of DBC1, unlike STAT5A, was not dependent on GH-induced STAT5 tyrosine phosphorylation (Figure 1A). To further validate that these two proteins were present in the same protein complex in adipocytes, we demonstrated that STAT5A could also be pulled down by a reverse co-immunoprecipitation using a DBC1 antibody (Figure 1B). Together, these experiments corroborate that DBC1 is present in a complex with STAT5A under physiological conditions in the nucleus of adipocytes and that this interaction is not dependent upon GH stimulation or STAT5 tyrosine phosphorylation.

Figure 1. DBC1 is present in the nucleus of adipocytes and can be co-immunoprecipitated with STAT5A.

Figure 1.

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(A) Fully differentiated 3T3-L1 adipocytes were treated with 5 nM murine growth hormone (GH) or an equivalent volume of vehicle (10 mM NaHCO3) for 20 minutes. Monolayers were collected and subjected to subcellular fractionation. As shown in the left-hand portion of the figure, cytosolic and nuclear protein extracts (300 μg total protein/sample) were immunoprecipitated (IP) with an anti-STAT5A antibody. The mock sample contained anti-STAT5A antibody without cell extract. The right-hand portion of the figure are direct western blot (WB) controls containing 75 μg total protein that were directly subjected to Western blotting without IP. STAT5pY represents phosphorylated STAT5 at tyrosine 694/699. This is a representative figure of an experiment independently performed three times. (B) The monolayers of fully differentiated 3T3-L1 adipocytes were harvested and whole cell protein extracts were prepared. The left-hand portion of the figure shows IP of whole cell extract containing 400 μg of total protein, anti-DBC1 antibody, and IP buffer. Mock sample contained anti-DBC1 antibody without cell extract. The right-hand portion of the figure contains Western blot controls. This is a representative figure of an experiment independently performed three times on different groups of adipocytes.

To assess the function of the DBC1/STAT5A interaction, we performed siRNA experiments to knockdown DBC1 in mature adipocytes. The goal was to determine if DBC1 expression had any effect on STAT5 phosphoactivation or transcriptional activity. In these studies, we examined the ability of GH to induce STAT5A activation by measuring STAT5A tyrosine phosphorylation. Western blot analysis showed that loss of DBC1 levels did not have an effect on levels of STAT5A or STAT5pY (Figure 2).

Figure 2. Knockdown of DBC1 does not affect STAT5A protein expression or STAT5 tyrosine phosphorylation in 3T3-L1 adipocytes.

Figure 2.

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Fully differentiated 3T3-L1 adipocytes were transfected once per day for two days with non-targeting siRNA or DBC1 siRNA. After 48 hours, adipocytes were serum deprived for 4 hours and treated with 5 nM murine growth hormone (GH) or equivalent volume of vehicle (10 mM NaHCO3) for 20 minutes. Monolayers were collected and 75 μg of total protein was separated using SDS-PAGE. Protein expression was visualized using Western blotting with the antibodies indicated to the left of panel. ERK was used as a loading control. Three biological replicates were used for each treatment group in each individual experiment. This is a representative figure of an experiment independently performed three times on different groups of adipocytes.

To confirm that the loss of DBC1 protein affected its activity in adipocytes, we performed additional experiments to measure SIRT1 activity. It is well established that SIRT1 activity is negatively regulated by DBC1 (Kim et al. 2008, Zhao et al. 2008). As expected, our experiments showed an increase in SIRT1 activity when DBC1 protein levels were reduced (*** p<0.001), suggesting that the knockdown of DBC1 also affected its activity in adipocytes as judged by SIRT1 activity (Figure 3A). Induction of SIRT1 deacetylase activity in HeLa extract with the addition of nicotinamide adenine dinucleotide (NAD+) or trichostatin A (TricA) was used as a control to confirm validity of the deacetylase assay (Figure 3B).

Figure 3. Knockdown of DBC1 increases the deacetylase activity of SIRT1 in 3T3-L1 adipocytes.

Figure 3.

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(A) SIRT1 deacetylase activity was measured in samples prepared by immunoprecipitating SIRT1 from 3T3-L1 adipocytes transfected with non-targeting (NT) or DBC1 siRNA. Each IP reaction contained 75 μg of total protein, anti-SIRT1 antibody, and IP buffer. (B) HeLa extract was used as a control to assess SIRT1 deacetylase activity. The graph shows the requirement of NAD+ for SIRT deacetylase activity and Trichostatin A (TricA) inhibiting the Fluor de Lys® substrate deacetylation in HeLa nuclear extract. Statistical significance was determined using a Student’s t-test and assigned as *** p<0.001.

Tyrosine phosphorylated STAT5A can activate or repress the expression of many genes. To determine if DBC1 expression had any effect on the transcriptional activity of STAT5, we examined the expression of several STAT5 target genes following GH treatment of mature adipocytes for 1 – 4 hours under control or DBC1-knockdown conditions. The expression of STAT5A target genes (Socs3, Cish, and Bcl6) was assessed by qPCR. It is known that Socs3 and Cish gene expression are highly induced one hour following STAT5 activation (Matsumoto et al. 1997, Karlsson et al. 1999, Barclay et al. 2007), whereas Bcl6 gene expression is reduced following four hours of growth hormone treatment (Lin et al. 2014). The data showed the expected regulation of Socs3, Cish, and Bcl6 gene expression following one hour of growth hormone treatment. However, there were no differences in mRNA levels of these genes in adipocytes with reduced DBC1 expression (Figure 4). Similar results were observed for other STAT5A target genes such as Adiponectin, Fasn, and Pdk4 (data not shown).

Figure 4. Knockdown of DBC1 in mature adipocytes does not affect the ability of GH to alter the expression of STAT5A target genes.

Figure 4.

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Fully differentiated 3T3-L1 adipocytes were transfected once per day for two days with non-targeting (NT) siRNA or DBC1 siRNA. After 48 hours, adipocytes were serum deprived for 4 hours and treated with 5 nM murine growth hormone (GH) or equivalent volume of vehicle (V; 10 mM NaHCO3) for 1, 2, or 4 hours. Total RNA was isolated and subjected to quantitative RT-PCR analysis. Each graph represents a different gene. The examined genes were normalized to Nono. This is a representative figure of an experiment independently performed three times on different groups of adipocytes.

Although DBC1 did not have a profound impact on STAT5A transcriptional activity, there is evidence in the literature that DBC1 may affect adipose tissue inflammation (Moreno-Navarrete et al. 2015). We explored this on the cellular level by investigating the ability of DBC1 to modulate TNFα action in adipocytes. TNFα is known to increase basal lipolysis, promote the expression and secretion of pro-inflammatory cytokines, such as IL-6, and reduce the secretion of anti-inflammatory hormones, such as adiponectin (Berghe et al. 2000, He et al. 2016). To investigate the effects of DBC1 on TNFα action, we used siRNA to knockdown DBC1 in mature 3T3-L1 adipocytes. Gene expression analysis showed that a loss of DBC1, independent of TNFα treatment, increased Glut4 gene expression (***p<0.01 for Vehicle treatment and **p<0.01 for TNFα treatment) but did not have a profound effect on TNFα-mediated changes in expression of Mcp1 or Adiponectin (Figure 5A). Western blot analysis was used to assess the level of DBC1 protein knockdown and the effectiveness of TNFα treatment, as judged by reduced adiponectin protein levels (Figure 5B), which was consistent with the changes observed in Adiponectin gene expression (Figure 5A). We also assessed whether DBC1 expression had an impact on TNFα-mediated lipolysis. Both free fatty acid and glycerol release were measured from mature adipocytes following TNFα treatment in control and DBC1-knockdown adipocytes. We observed a modest, but statistically significant, decrease in TNFα-induced glycerol (*** p<0.005) and free fatty acid (* p<0.05) release with reduced DBC1 expression (Figure 6).

Figure 5. Knockdown of DBC1 in mature adipocytes results in increased Glut4 gene expression but does not alter TNFα-mediated changes in gene expression.

Figure 5.

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Fully differentiated 3T3-L1 adipocytes were transfected once per day for two days with non-targeting (NT) siRNA or DBC1 siRNA. After 54 hours, media was replaced with 1% calf and cells were treated with 0.75 nM TNFα overnight or equivalent volume of vehicle (0.1% BSA/PBS). After 16 hours, cells were re-treated again with vehicle or TNFα for 2 hours. Finally, monolayers were harvested for RNA and protein. (A) Total RNA was isolated and subjected to quantitative RT-PCR analysis. The examined genes (each represented by separate graph) were normalized to Nono. Statistical significance was determined using a Student’s t-test and assigned as ** p<0.01, *** p<0.001, and **** p<0.0001. (B) 75 μg of total protein was separated using SDS-PAGE. Protein expression was visualized using Western blotting and the antibodies indicated on the left of panel. Three biological replicates were used for each treatment group in each individual experiment. This is a representative figure of an experiment independently performed three times on different groups of adipocytes.

Figure 6. Knockdown of DBC1 in mature adipocytes modestly suppresses TNFα-induced lipolysis.

Figure 6.

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Fully differentiated 3T3-L1 adipocytes were transfected once per day for two days with non-targeting (NT) siRNA or DBC1 siRNA. After 54 hours, media was replaced with incubation media and cells were treated with 0.75 nM TNFα or equivalent volume of vehicle (0.1% BSA/PBS) overnight. After 12 hours, cells were treated again with vehicle or TNFα for 2 hours. 50 μL of conditioned medium was used for free fatty acid assay and glycerol assay. Statistical significance was determined using a Student’s t-test and assigned as * p<0.05 and *** p<0.005. This is a representative figure of an experiment independently performed two times on different groups of adipocytes.

Discussion

STAT5A is a transcription factor that can mediate the effects of growth hormone (Zvonic et al. 2003) and promote adipocyte development (Floyd & Stephens 2003, Stewart et al. 2011). In adipocytes, STAT5A regulates genes that contribute to insulin sensitivity and the endocrine properties of adipocytes (Hogan & Stephens 2005, White et al. 2007, 2016). To further understand the mechanisms involved in the contribution of STAT5A to fat cell function, we sought to identify novel STAT5A-interacting proteins in adipocytes using a co-immunoprecipitation/mass-spectrometry approach. We recently published data describing this approach and the identification of components of the pyruvate dehydrogenase complex as STAT5A-binding proteins (Richard et al. 2017). Another STAT5A-binding protein that we identified with this approach was the nuclear protein, DBC1. DBC1 has been shown to mediate cellular responses to stress and regulate the activity of a variety of enzymes and transcription factors in different cell types (Joshi et al. 2013). Our novel observations demonstrate that DBC1 can be present in the same protein complex as STAT5A in the nucleus of 3T3-L1 adipocytes (Figure 1). This interaction was observed with endogenous proteins and could be detected by immunoprecipitating either STAT5A or DBC1. In addition to this observation, our results reveal that this interaction is not dependent on STAT5A tyrosine phosphorylation (Figure 1A).

To assess the potential function of the STAT5A/DBC1 association, we examined STAT5A expression levels as well as STAT5A tyrosine phosphorylation in adipocytes that had substantially decreased levels of DBC1. These studies revealed that loss of DBC1 did not alter STAT5A total protein levels or its ability to be activated, as judged by tyrosine phosphorylation (Figure 2). We also examined the ability of STAT5A to regulate gene expression in adipocytes with reduced DBC1 expression. To our surprise, there were no profound changes in the expression of several STAT5A target genes in DBC1-deficient adipocytes, which strongly indicates that DBC1 levels do not affect the transcriptional activity of STAT5A (Figure 4). Although there were some modest differences in Socs3 and Cish gene expression following 4 hour GH treatment in DBC1 knockdown adipocytes, these results were not statistically significant. The effectiveness of siRNA-mediated DBC1 knockdown was assessed by examining gene and protein expression levels of DBC1 (Figures 2, 4, and 5) as well as SIRT1 deacetylase activity (Figure 3) since DBC1 is a well-known negative regulator of SIRT1 (Kim et al. 2008, Zhao et al. 2008, Liu et al. 2016). As expected, we observed an increase in SIRT1 activity, indicating that the activity of DBC1 was likely altered in the DBC1-knockdown adipocytes (Figure 3). Presumably, we only observed a modest increase in SIRT1 activity because DBC1 is only one of many regulators of SIRT1 activity in mature adipocytes. Other studies have shown that a variety of other factors including the cAMP/PKA pathway and AROS (active regulator of SIRT1) can positively regulate SIRT1 (Kim et al. 2007, Chao & Tontonoz 2012). Collectively, our observations suggest that DBC1 levels do not affect the transcriptional activity of STAT5A.

Since there was evidence suggesting that DBC1 may have a pro-inflammatory role in adipocytes by increasing the expression of NF-κB-regulated inflammatory cytokines (Moreno-Navarrete et al. 2015), we examined the actions of TNFα on adipocytes with reduced levels of DBC1. TNFα can induce insulin resistance, in part, through the transcriptional repression of the Glut4 gene in adipocytes (Stephens & Pekala 1991, Stephens et al. 1997, Ruan et al. 2002a) and by activating NF-κB (Ruan et al. 2002b). In addition, TNFα can repress adiponectin gene expression in mouse and human adipocytes (Fasshauer et al. 2002, Degawa-Yamauchi et al. 2005). Both increased GLUT4 protein expression in adipocytes (Carvalho et al. 2005, Atkinson et al. 2013) and increased adiponectin levels (Fu et al. 2005) are associated with improvements in insulin sensitivity. Knockdown of DBC1 did not alter TNFα-mediated induction of pro-inflammatory MCP-1 or repression of anti-inflammatory adiponectin (Figure 5A). However, we consistently observed that a loss of DBC1 protein resulted in increased Glut4 gene expression, which suggests a potential role for DBC1 in glucose regulation. Studies in HepG2 cells have shown a knockdown of DBC1 results in the upregulation of PEPCK (phosphoenolpyruvate carboxykinase) and consequently effects glucose production (Nin et al. 2014). Experiments performed with inguinal fat tissue from DBC1-null mice also showed increased PEPCK expression in DBC1-deficient tissue (Moreno-Navarrete et al. 2015). Although additional experiments will be required to determine if there are any direct effects of DBC1 on glucose metabolism or Glut4 gene expression, our results suggest that DBC1 is a likely a negative regulator of GLUT4 in adipocytes (Figure 5A).

Although the loss of DBC1 did not profoundly affect TNFα regulation of several genes in adipocytes (Figure 5), we did observe that alteration of DBC1 levels affected TNFα-induced lipolysis. Our studies revealed a modest but significant reduction in glycerol and free fatty acid release in DBC1-knockdown adipocytes under TNFα-stimulated conditions (Figure 6). This effect could be considered metabolically favorable, which is also evident by the increased Glut4 expression we observed with loss of DBC1. Overall, our observations are consistent with the phenotype of the DBC1-knockout mice fed a high fat diet that are more insulin sensitive and have decreased circulating FFA (Escande et al. 2015). Our data showing that loss of DBC1 increases Glut4 expression and reduces TNFα-induced lipolysis suggests that the loss of DBC1 in adipocytes may contribute to the metabolically protected phenotype of the DBC1 null mice. Although additional experiments in adipocyte specific DBC1 knockout mice will be needed, the current data are consistent with a role of DBC1 in promoting metabolic dysfunction. Decreased FFA levels are typically associated with a metabolically healthy phenotype. Whereas, an increase in glycerol and fatty acids is often harmful and associated with the clinical manifestations of metabolic syndrome, which also include obesity and insulin resistance (Boden 1999, Arner & Rydén 2015). Our results show a decrease in glycerol and free fatty acid release from TNFα-stimulated DBC1-deficient adipocytes that occurs in a cell autonomous manner and suggest that DBC1 plays a direct or indirect role in the ability of TNFα to induce lipolysis.

Although these novel observations revealed that DBC1 is present in a protein complex with STAT5A in adipocyte nuclei (Figure 1), most of our functional studies reproducibly generated negative observations. The loss of DBC1 did not affect STAT5A expression (Figure 2), STAT5A tyrosine phosphorylation (Figure 2), or the expression of STAT5A target genes (Figure 4). Although DBC1 is clearly in a complex with STAT5, and loss of DBC1 did result in expected increase in SIRT1 activity (Figure 3), we were unable to perturb STAT5A expression, activation or activity. We did, however, have two consistent effects that accompanied loss of DBC1 expression in adipocytes: 1) increased Glut4 expression and 2) a statistically significant decrease in TNFα-induced lipolysis. Nevertheless, it is unlikely that these functions of DBC1 are related to its interaction with STAT5A. Further studies are needed to identify additional proteins present in the DBC1/ STAT5A complex, to elucidate the function of the DBC1/STAT5A interaction, and to investigate the mechanism of DBC1’s ability to modulate TNFα-induced lipolysis.

Acknowledgements

This project used Genomics Core facilities that are supported in part by COBRE (NIH8 1P30GM118430–02) and NORC (NIH 2P30DK072476) center grants from the National Institutes of Health.

Funding:

This work was supported by National Institutes of Health Grant R01DK052968 to JMS.

Footnotes

Declaration of Interest

The authors declare no conflict of interest.

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