1266 Research Article

IntroductionThe large variety of metabolic disorders related to bio-energetical stress underlines the essential role of mitochondrialactivity in cellular physiology. More particularly, several linesof evidence now show that defects in �-cells insulin secretionas well as systemic insulin resistance in type 2 diabetes couldbe attributable to mitochondrial dysfunction (Lowell andShulman, 2005). In human muscle cells, the major effectorsinvolved in insulin resistance include adipokines (Lazar, 2005)and fatty acids, which cause a direct inhibition of insulin-stimulated glucose transport activity through a decrease inphosphoinositide 3-kinase (PI 3-kinase) signaling (Dresner etal., 1999). Furthermore, impairment of mitochondrial activityassociated with ageing, which could result from alterations inmitochondrial DNA (mtDNA), also leads to triglyceride (TG)

accumulation in muscles and liver of healthy and lean elderlypeople (Petersen et al., 2003). Reduced mitochondrial activityand intramyocytic accumulation of TG were also found in theyoung and insulin-resistant offspring of parents with type 2diabetes. Insulin-resistant patients usually have a lower ratio oftype 1 muscle fibers to the more glycolytic type 2 musclefibers, an observation that could be explained by the reducedexpression of members of the peroxisome proliferator-activated receptor � (PPAR�)-coactivator-1 (PGC-1) familyand the downregulation of their target genes involved inmitochondrial biogenesis (Wu et al., 1999; Mootha et al.,2003). Hypoxic conditions that inhibit mitochondrialrespiration also lead to TG accumulation in cardiomyocytes(Huss et al., 2001). In addition, we recently showed that, theimpairment of mitochondrial activity by inhibitors of

Several mitochondrial pathologies are characterized bylipid redistribution and microvesicular cell phenotypesresulting from triglyceride accumulation in lipid-metabolizing tissues. However, the molecular mechanismsunderlying abnormal fat distribution induced bymitochondrial dysfunction remain poorly understood. Inthis study, we show that inhibition of respiratory complexIII by antimycin A as well as inhibition of mitochondrialprotein synthesis trigger the accumulation of triglyceridevesicles in 3T3-L1 fibroblasts. We also show that treatmentwith antimycin A triggers CREB activation in these cells.To better delineate how mitochondrial dysfunction inducestriglyceride accumulation in preadipocytes, we developed alow-density DNA microarray containing 89 probes, whichallows gene expression analysis for major effectors and/ormarkers of adipogenesis. We thus determined geneexpression profiles in 3T3-L1 cells incubated withantimycin A and compared the patterns obtained withdifferentially expressed genes during the course of in vitroadipogenesis induced by a standard pro-adipogeniccocktail. After an 8-day treatment, a set of 39 genes wasfound to be differentially expressed in cells treated withantimycin A, among them CCAAT/enhancer-binding

protein �� (C/EBP��), C/EBP homologous protein-10(CHOP-10), mitochondrial glycerol-3-phosphatedehydrogenase (GPDmit), and stearoyl-CoA desaturase 1(SCD1). We also demonstrate that overexpression of twodominant negative mutants of the cAMP-response element-binding protein CREB (K-CREB and M1-CREB) andsiRNA transfection, which disrupt the factor activity andexpression, respectively, inhibit antimycin-A-inducedtriglyceride accumulation. Furthermore, CREB knock-down with siRNA also downregulates the expression ofseveral genes that contain cAMP-response element (CRE)sites in their promoter, among them one that is potentiallyinvolved in synthesis of triglycerides such as SCD1. Theseresults highlight a new role for CREB in the control oftriglyceride metabolism during the adaptative response ofpreadipocytes to mitochondrial dysfunction.

Supplementary material available online athttp://jcs.biologists.org/cgi/content/full/119/7/1266/DC1

Key words: CREB, Lipid metabolism, Mitochondrial dysfunction,Gene expression, SiRNA, Adipocytes

Summary

CREB activation induced by mitochondrialdysfunction triggers triglyceride accumulation in3T3-L1 preadipocytesSébastien Vankoningsloo1, Aurélia De Pauw1, Andrée Houbion1, Silvia Tejerina1, Catherine Demazy1,Françoise de Longueville2, Vincent Bertholet2, Patricia Renard1, José Remacle1,2, Paul Holvoet3, MartineRaes1 and Thierry Arnould1,*1Laboratory of Biochemistry and Cellular Biology, University of Namur (F.U.N.D.P.), Rue de Bruxelles, 61, 5000 Namur, Belgium2Eppendorf Array Technologies, Rue du Séminaire, 12, 5000 Namur, Belgium 3Cardiovascular Research Unit of the Center for Experimental Surgery and Anesthesiology, Katholieke Universiteit Leuven (KUL), Belgium*Author for correspondence (e-mail: thierry.arnould@fundp.ac.be)

Accepted 12 December 2005Journal of Cell Science 119, 1266-1282 Published by The Company of Biologists 2006doi:10.1242/jcs.02848

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respiratory complexes also triggers TG accumulation in murine3T3-L1 preadipocytes, resulting from a decrease in fatty acid�-oxidation and an increase in glucose uptake enhancingglycerol 3-phosphate synthesis (Vankoningsloo et al., 2005).

Changes in cellular metabolism due to a loss ofmitochondrial oxidative capacity lead to the activation of cellsignaling pathways and modifications in the expression ofmany nuclear genes. This process, known as mitochondria-nucleus retrograde communication, has mainly been studied inyeast (Liao et al., 1991; Butow and Avadhani, 2004) and morerecently in mammalian cells depleted in mitochondrial DNA(mtDNA) (Amuthan et al., 2002; Biswas et al., 1999; Biswaset al., 2005; Arnould et al., 2002). For example, we haverecently shown that depletion of mtDNA or inhibition ofmitochondrial respiration activates the cAMP-response-element binding protein (CREB) by phosphorylation of Ser133mediated through a Ca2+/calmodulin-dependent kinase IV(CaMK IV) pathway (Arnould et al., 2002).

CREB is a transcription factor with pleiotropic effects thathas already been reported to play a role in the control ofmemory (Scott et al., 2002), cell proliferation (Della Fazia etal., 1997), and in glucose and lipid metabolism (Zhou et al.,2004; Reusch et al., 2000; Herzig et al., 2003). Previousstudies showed that this transcription factor is also an earlyregulator of adipocyte differentiation because it is activated byphosphorylation of Ser133 in the presence of adipogenicinducers, such as glucocorticoids, cyclic AMP analogues andinsulin-like growth factor-1 (IGF-1), or high concentrations ofinsulin (MacDougald and Lane, 1995). Furthermore, ectopicexpression of the chimeric and constitutively active VP16-CREB is sufficient to trigger adipogenesis, whereasoverexpression of a dominant negative form of CREB (K-CREB) inhibits the adipogenic program (Reusch et al., 2000)and leads to apoptosis of mature adipocytes (Reusch andKlemm, 2002). These data suggest that CREB acts as pro-adipogenic and survival factor. It has also been reported thatthe positive effect of activated CREB on adipogenesis ismediated by the overexpression of the CCAAT/enhancer-binding protein � (C/EBP�) gene, a key transcription factorin the differentiation program that contains dual cAMP-response element (CRE)-like cis regulatory-elements in itspromoter (Zhang et al., 2004). Whereas defects in adipocytemetabolism induced by mitochondrial dysfunction mightinfluence muscle and liver metabolism because it has beenassociated with lipodystrophy and impairment of fatty acid �-oxidation in these tissues (Petersen et al., 2002), preadipocyteresponse to mitochondrial dysfunction is still poorlyunderstood.

Here, we show that CREB is activated in 3T3-L1preadipocytes when the cells are incubated with antimycin A(AA), an inhibitor of the complex III in the mitochondrialelectron transporter chain that triggers the accumulation ofcytosolic TG in these cells (Vankoningsloo et al., 2005). Thefact that CREB can be activated by the inhibition ofmitochondrial activity in several cell lines and acts as a survivaland differentiating factor in adipocytes and preadipocytes,respectively, led us to hypothesize that CREB also plays a rolein the accumulation of triglycerides in preadipocytes withimpaired mitochondrial activity.

We thus developped and used a low-density DNAmicroarray to study gene expression profiles of major

adipogenic markers that are potentially responsible for TGaccumulation in AA-treated preadipocytes. These results werecompared with differentially expressed genes obtained fordifferentiating 3T3-L1 cells in the presence of a standardhormone cocktail. The DNA microarray used in this studyallows gene expression profiling for 89 genes related toadipogenesis and lipid metabolism. These markers have beencarefully selected, based on the literature reporting ondifferentiation-specific gene expression during 3T3-L1adipogenesis (Burton et al., 2004; Guo and Liao, 2000;Kratchmarova et al., 2002). We also evidenced that, inhibitionof CREB expression with small interfering RNA (siRNA) andreduction of its activity by overexpression of two dominantnegative mutants (K-CREB and M1-CREB) diminishes the TGaccumulation induced by AA in 3T3-L1 preadipocytes. Finally,combining RNA interference (RNAi) and microarraytechnology, we identified several CREB-target genes that aredifferentially regulated when 3T3-L1 cells are incubated withAA. Taken together, these results not only extend the role ofCREB in adipocyte biology and lipid metabolism but alsohighlight the 3T3-L1 preadipocyte response to mitochondrialdysfunction leading to TG accumulation, which might not onlyimpair adipocyte metabolism but also the physiology ofinsulin-dependent tissues.

ResultsMitochondrial dysfunction induces TG accumulation in3T3-L1 preadipocytesDifferentiation of 3T3-L1 preadipocytes into adipocytes iseasily triggered by a standard adipogenic cocktail comprisinginsulin, a cAMP-elevating agent and dexamethasone(MacDougald and Lane, 1995). The main morphologicalcharacteristic of adipogenesis is the progressive storage oflarge amounts of cytosolic TG, whereas TG that accumulate in3T3-L1 cells incubated with 10 nM AA form small butnumerous vesicles, as revealed after the staining of neutrallipids with Oil Red O (Fig. 1A) (Vankoningsloo et al., 2005).Quantitative analysis showed that TG accumulation in 3T3-L1cells treated for 8 days with AA depends on the concentrationof this metabolic inhibitor (Fig. 1B). A similar phenotype wasobserved for 3T3-L1 cells incubated 16 days withchloramphenicol (a well-known inhibitor of mitochondrialprotein synthesis), although it took longer for TG toaccumulate (Fig. 1C).

Characterization of CREB activation in AA-treated 3T3-L1 cellsWe previously reported a constitutively enhanced CREBactivity in mtDNA-depleted L929 and rho0 143B cells, as wellas phosphorylation of the CREB Ser133 in several cell linesthat had been incubated with oxidative phosphorylationinhibitors (Arnould et al., 2002). Here, we extended these databy showing that preadipocytes also respond to the impairmentof mitochondrial activity by the activation of this transcriptionfactor. Indeed, using several approaches, we showed thatCREB is phosphorylated on Ser133 and localizes in thenucleus of 3T3-L1 cells incubated with AA (Fig. 2A-B).Western blot analysis revealed that CREB phosphorylation isincreased after 6 hours of treatment with 10 nM AA andremains sustained for at least 72 hours, whereas theadipogenic cocktail increases levels of Ser133-phosphorylated

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CREB (pCREB) for 24 to 72 hours. Increases in levels ofpCREB are not observed after 8 days of treatment. Theabundance of total CREB is similar in all tested conditions(Fig. 2A). These results clearly indicate that thephosphorylation of CREB on Ser133 is enhanced in 3T3-L1cells treated with AA. These results were also confirmed byimmunofluorescence experiments and confocal microscopy,which show that pCREB mainly accumulates in the nucleusof cells incubated for 24 hours with the mitochondrialinhibitor or the adipogenic cocktail (Fig. 2B). An enhancedphosphorylation of Ser133 strongly suggests that CREB isbound to DNA and transcriptionally active under theseconditions. Therefore, we next used a colorimetric assayallowing the quantification of CREB and also pCREB boundto a synthetic oligonucleotide containing a CRE-site. Weobserved that, whereas the total amount of CREB binding toDNA remained unchanged, the relative amount of boundpCREB was increased (1.5- to three-fold increase after 24hours) by both AA and the adipogenic cocktail (Fig. 2C). Theresulting effect of pCREB on its ability to transactivate geneexpression in these conditions was demonstrated in transienttransfection experiments with a CREB-sensitive luciferase-reporter construct driven by the authentic �-inhibin promoter,which contains four CRE sites (Pei et al., 1991; Fig. 2D). Asexpected, the transcriptional activity of CREB wassignificantly increased in cells incubated for 24 hours with 10nM AA or the adipogenic cocktail (threefold or fourfoldincrease, respectively).

CREB is involved in AA-induced TG accumulationCREB is suspected to play a role in TG metabolism because itbinds to the promoter of adipogenic marker genes, such asC/EBP�, during 3T3-L1 cell differentiation (Zhang et al.,2004). To delineate a potential role for CREB in the AA-induced TG accumulation, cells were transiently transfectedwith plasmids encoding either dominant negative CREBmutants (K-CREB and M1-CREB) or enhanced greenfluorescent protein (EGFP) as a negative control, and thenincubated for 8 days with 10 nM AA followed by staining forTG and spectrophotometric quantification. We found that AA-induced TG accumulation is significantly reduced in cells thatoverexpress either K-CREB or M1-CREB dominant negativemutants (43.1 % or 44.8 %, respectively; data not shown). Tocircumvent the rather low transfection efficiency of these cellswith the Superfect reagent (ranging from 20 to 45 % asdetermined by a �-galactosidase reporter construct), whichmight minimize the inhibitory effect of the dominant negativeforms, we next used a specific siRNA to silence CREB geneexpression.

Before testing the effect that CREB silencing has onaccumulation of TG in 3T3-L1 cells incubated for 8 days with10 nM AA (Fig. 3), we verified by confocal microscopy thatFITC-labeled siRNA had been efficiently introduced into 3T3-L1 preadipocytes, and estimated that transfection efficiencywas at least 90% (Fig. 3A). Out of the three different siRNAstested, only one inhibited CREB expression efficiently by morethan 80% (data not shown). Using western blot analysis, we

Fig. 1. Antimycin A and chloramphenicol induce triglyceride accumulation in 3T3-L1 preadipocytes. (A) Photomicrographs of 3T3-L1 cells (a)not treated or treated (b) for 8 days with 10 nM AA, (c) for 16 days with 100 �g/ml chloramphenicol and (d) for 8 days with an adipogeniccocktail. Cells were stained for the presence of neutral lipids with Oil Red O. (B-C) Quantitative determination of triglyceride accumulation in3T3-L1 cells (B) incubated without a drug (controls, CTL) or incubated with the indicated concentrations for 8 days with antimycin A and (C)for 16 days with chloramphenicol. The absorbance of cell monolayers was spectrophotometrically determined at 490 nm after Oil Red Ostaining. Results are expressed in optical density (O.D.) as the mean ± s.d. for n=3 experiments. **P<0.01 and ***P<0.001, significantlydifferent from control cells. Magnification, 150�.

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then checked that this CREB-specific siRNA reduces theabundance of CREB protein in a concentration-dependentmanner (Fig. 3B). The maximal inhibitory effect was observed24 to 48 hours post-transfection, whereas CREB knock-downwas relieved 96 hours after transfection (data not shown), aresult in agreement with the transient effect of siRNA inmammalian cells. The expression of TATA-box-bindingprotein (TBP) was monitored by western blot analysis and wasfound unchanged in these conditions, suggesting that siRNAtargeting CREB did not repress global protein synthesis by an‘off-target’ effect. To test the potential role of CREB on TGthat accumulate in AA-treated 3T3-L1 cells, 100 nM siRNAwere transfected and cells were then incubated for 8 days with10 nM AA. In these conditions, we observed that delivery ofsiRNA into 3T3-L1 cells reduces the AA-induced TGaccumulation by 75% (Fig. 3C-D). These results show thatCREB activation induced by AA is required for accumulationof TG – as observed in response to mitochondrial inhibition –and suggest that CREB-mediated transcription at the earlystage of the mitochondria-impairing treatment is an importantmechanism, leading to the observed phenotype.

Comparison of alterations in gene expression inducedby the adipogenic cocktail or AAThe accumulation of TG in preadipocytes leading to theadipocyte phenotype is controlled by numerous genes ofseveral classes. Products of these genes either drivedifferentiation (mainly C/EBP� and PPAR�) or maintain adifferentiated state (C/EBP�). We thus hypothesized that TGaccumulation in 3T3-L1 preadipocytes with impairedmitochondrial activity is also caused by alterations in geneexpression. We then compared differences and similarities ingene expression induced by the adipogenic cocktail or AA. Toinvestigate the expression of genes that are differentiallyregulated by AA, a low-density DNA microarray wasdeveloped. This microarray allows gene expression analysis fora set of key genes related to adipogenesis and lipid metabolism(supplementary material Table S1 and Fig. S1). 3T3-L1 cellswere incubated for 2, 4, 6 or 8 days with the adipogeniccocktail or with 10 nM AA. Cells were harvested and totalRNA was extracted and reverse transcribed by includingbiotinylated nucleotides. The resulting cDNAs were hybridizedon the microarray and stained with a cyanin-3-conjugated anti-

Fig. 2. Antimycin A and the adipogenic cocktailtrigger CREB activation by phosphorylation onSer133. (A) Western blot analysis for CREB andCREB phosphorylated on Ser133 (pCREB) performedwith 20 �g of nuclear proteins extracted from 3T3-L1cells incubated for 6, 24 and 48 hours, and 3 and 8days without a drug (controls, CTL), with 10 nM AAor with the adipogenic cocktail (DIFF); TBP served asa loading control. (B) Immunostaining and confocalmicroscopic analysis of abundance and localization ofpCREB in 3T3-L1 cells incubated for 24 hours (a)without, (b) with 10 nM AA or (c) with adipogeniccocktail. Arrows indicate nuclear localization ofpCREB. (C) Quantitative detection of pCREB and totalCREB that binds to a DNA consensus sequence in acolorimetric assay (TransAM kit). Assays wereperformed on 10 �g of nuclear protein extract from3T3-L1 cells incubated for 24 hours without (CTL),with 10 nM AA or with adipogenic cocktail (DIFF).Phosphorylated and total forms of CREB binding ofpCREB and total CREB to DNA was detected withanti-Ser133-pCREB or anti-CREB antibodies,respectively, followed by a colorimetric reaction in thepresence of a HRP-conjugated secondary antibody.Absorbance values were measured at 450 nm for DNA-binding of pCREB and CREB, and signals obtained forpCREB were normalized against total CREB bound tothe capture probe (n=3). (D) Effect of AA and theadipogenic cocktail on CREB transcriptional activity in3T3-L1. Cells were transiently co-transfected with aplasmid encoding �-galactosidase and a CREB-sensitive luciferase-reporter construct. The next day,cells were incubated for 24 hours without (CTL) orwith 10 nM AA, or with the adipogenic cocktail(DIFF) and then processed for luciferase assay. Resultswere normalized against �-galactosidase activity andexpressed as fold-increase of controls as the mean ±s.d. for n=3 experiments. *P<0.05, **P<0.01,***P<0.001 are significantly different from controlcells.

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biotin antibody. Three independent experiments wereperformed for each incubation time and each sample washybridized to three submicroarrays, represented by the probesspotted in triplicate. The array data were subjected to a simplealgorithm (Materials and Methods) to set a lower threshold andto normalize the data to internal-standard controls and housekeeping genes. Then, average ratios and their standarddeviations (s.d.) were calculated. We ended up with a categoryof gene transcripts that were not detected owing to their lowabundance, detected with no modification, or quantitatively orqualitatively up- or down-regulated. Genes were assigned tothe latter category when their fluorescent signal was eithersaturated or less than 2.5 times that of the local background inone of the experimental conditions.

Adipogenic cocktail-induced gene expression profilesGene expression data for differentiating 3T3-L1 cells arepresented in Table 1. The first list identified 36 genes foundto be significantly upregulated during the time course of invitro adipogenesis. Many of these include genes involved inlipid metabolism (CPT-2, DHAPAT, FABP4/aP2, FAS,GPAT, HSL, LPL1, MCAD, SCD1, SCD2), in thetranscriptional control of adipogenesis (C/EBP�, PPAR�,SREBP-1) and in cell-cycle arrest (p18), as well as genesencoding adipokines (Acrp30, AGT, resistin). Among theupregulated genes during preadipocyte differentiation,several sets of genes (clusters) display various kineticprofiles: genes are either significantly induced after 2 days(AAAT, AGT, Cav-1, Coll VI�2, CPT-2, FAS, GPDcyt, Gsn,Hp, MMP-2, PPAR�, resistin, RXR�, SCD1, SREBP-1,

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UCP-2), begin to be upregulated after 4 days (Acrp30,adipsin, Cav-2, C/EBP�, Clic4, cyclin D3, DHAPAT,FABP4/aP2, GPAT, HSD, HSL, HSP 60, LPL-1, MCAD, p18,PPAR�, SCD2) or are only found to be differentiallyregulated after 6 days of treatment (CL, Plin, VEGF-A). Theexpression of the genes upregulated most is sustained duringthe whole adipogenic program, but some genes also displaytransient overexpression profiles as found for Gsn, MMP-2and RXR�. As already reported, 3T3-L1 cell differentiationis also characterized by the downregulation of adipogenesisrepressors such as Pref-1 and the transcription factorsGATA2 and GATA3 (Lee et al., 2003; Tong et al., 2005).Other downregulated genes in differentiating adipocytesinclude PEDF, SDF1, SDF2, Smad3, TF and VEGF-C. Nochanges were observed for C/EBP�, a well-known earlymarker of adipogenesis (Darlington et al., 1998). However,due to inaccurate probe selectivity, C/EBP�-derived cDNAcan cross-hybridize with the probe for C/EBP� (data notshown). Therefore, we analyzed the expression profile forthese two transcription factors in differentiating 3T3-L1 cellsby real time PCR (RT-PCR) and found that C/EBP� andC/EBP� are transiently upregulated during the first 2 to 4days of adipogenesis (Fig. 4). Several gene transcripts werenot detected on the microarray (ATR II, CaMK IV, CPT-1 M,Gyk, IL-6, iNOS, leptin, renin, RXR�) probably because lowabundance makes their detection impossible below thesensitivity threshold of the microarray technique. Indeed,when analyzed by RT-PCR assays, leptin was found to beupregulated in differentiated 3T3-L1 adipocytes, whereas IL-6 was shown to be downregulated (Fig. 4).

Fig. 3. Silencing of CREB by using specific siRNAprevents triglyceride accumulation in antimycin-A-treated 3T3-L1 cells. (A) Visualization of siRNAtransfection efficiency in 3T3-L1 preadipocytes.Cells were transfected for 4 hours with fluorescein-labeled siRNA (20 nM) and processed for confocalmicroscopy after (a) 24 hours or (b) 48 hours. (B)Effect of a CREB-specific siRNA on CREB proteinexpression. 3T3-L1 preadipocytes were transfectedfor 4 hours with different concentrations of siRNA orincubated for 4 hours with the transfection reagent(JetSI). CREB abundance was determined by westernblotting of 40 �g of clear cell lysate proteinsprepared 48 hours after transfection. TBP served as aloading control. (C) Effect of a CREB-specificsiRNA on AA-induced triglyceride accumulation.Cells were transfected for 4 hours with 100 nMsiRNA and then incubated for 8 days without(controls, CTL) or with 10 nM AA. The absorbanceof cell monolayers was spectrophotometricallydetermined at 490 nm after Oil Red O staining.Results are expressed in optical density (O.D.) as themean ± s.d. for n=3 or the mean of n=2 experiments.*P<0.05, significantly different from control cells.(D) Photomicrographs of 3T3-L1 cells transfected ornot for 4 hours with 100 nM siRNA and incubated ornot (CTL) for 8 days with 10 nM AA before Oil RedO staining. Magnification, 75�.

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3T3-L1 fibroblasts, differentiated with a standard pro-adipogenic cocktail, are a commonly used model to studydifferentiation for which a lot of experimental data on geneexpression can be found in the literature (Rosen and

Spiegelman, 2000; Guo and Liao, 2000; Burton et al., 2002;Burton et al., 2004; Ross et al., 2002). The fact that our dataare in good agreement with previous studies that reportchanges in gene expression during adipogenesis in vitro,

Table 1. Gene expression profiles of differentiating 3T3-L1 adipocytes

Genes M.R. S.D. M.R. S.D. M.R. S.D. M.R. S.D. Genes M.R. S.D. M.R. S.D. M.R. S.D. M.R. S.D.AAAT 2.87 0.35 4.60 0.57 4.35 0.55 3.85 0.41 HSP 60 1.53 0.10 3.14 0.84 4.36 0.72 3.63 0.82

Acrp30 0.63 0.17 24.16 16.68 ++++ ++++ HSP 84 1.32 0.29 1.49 0.34 1.11 0.10 1.05 0.29

Actin 0.91 0.05 0.79 0.07 0.79 0.05 0.77 0.11 HSP 86 1.06 0.60 1.50 0.72 1.58 0.41 1.08 0.42

ADD1 0.84 0.13 0.78 0.05 0.69 0.04 0.80 0.11 IL-6 ND ND ND ND

Adipsin 0.50 0.13 5.84 4.02 34.80 14.91 49.33 13.38 iNOS ND ND ND ND

AGT 1.80 18.12 6.99 20.22 4.83 12.67 1.90 Leptin ND ND ND ND

ASP 0.65 0.23 1.03 0.06 1.29 0.06 1.25 0.12 L-PK 1.59 0.94 1.58 0.58 1.45 0.48 1.89 0.50

ATR I 1.82 0.20 1.31 0.50 1.02 0.21 0.87 0.13 LPL1 0.46 0.32 1.72 0.50 2.92 0.75 3.42 1.51

ATR II ND ND ND ND MCAD 1.18 0.44 3.13 0.03 4.31 0.44 3.97 0.86

β3AR ND ND ND + MMP-2 2.00 0.40 1.80 0.90 1.49 0.12 0.91 0.09

CaMK IIγ 0.59 0.03 0.81 0.17 0.71 0.07 0.62 0.24 NFATc2 ND ND ND 1.33

CaMK IV ND ND ND ND NFATc4 0.82 0.08 0.89 0.13 1.02 0.13 1.16 0.20

Cav-1 2.11 0.69 4.25 0.47 4.61 0.71 3.92 1.01 p110α 0.62 0.24 1.35 1.04 0.15 0.96

Cav-2 1.03 ++ 4.67 0.92 ++++ p18 1.01 0.18 2.89 1.73 3.40 0.40 3.62 0.57

C/EBPα 1.45 0.21 6.57 3.17 9.90 1.85 +++ PAI-1 1.68 + ND +

C/EBPβ 1.10 0.12 1.05 0.08 1.17 0.30 1.00 0.18 PEDF 0.67 0.08 0.40 0.13 0.44 0.07 0.46 0.03

C/EBPδ 2.16 0.88 1.95 0.57 1.29 0.18 1.00 0.03 PEPCK1 ND ND ND +

CHOP-10 0.49 0.07 0.74 0.20 0.76 0.15 1.12 0.40 Plin 0.85 0.19 1.23 0.14 2.57 1.29 2.02 0.79

CL 1.14 0.09 1.36 0.19 1.66 0.23 1.79 0.24 PPARδ 1.08 0.05 1.82 0.55 1.87 0.37 2.10 0.23

Clic4 1.54 0.30 2.22 0.67 2.56 0.21 2.27 0.40 PPARγ 1.98 0.37 6.80 1.35 15.68 3.76 20.73 7.64

Coll VIα2 2.15 0.37 2.19 0.42 2.39 0.24 1.91 0.01 Pref-1 0.58 0.07 0.33 0.10 0.31 0.09 0.27 0.05

CPT-1 L 0.64 0.05 0.76 0.29 0.87 0.11 0.63 0.14 RAB3D 1.09 0.16 1.41 0.22 1.61 0.83 +

CPT-1 M ND ND ND ND Renin ND ND ND ND

CPT-2 2.28 0.33 4.35 0.96 5.71 0.99 5.47 0.69 Resistin 1.93 ++++ ++++ ++++

CREB1 0.63 0.23 1.13 1.12 0.47 0.93 rRNA18s 1.12 0.24 0.76 0.15 0.70 0.29 0.71 0.11

Cst C 0.75 0.18 0.88 0.26 0.82 0.10 0.61 0.04 RXRα 1.74 0.14 1.80 0.31 2.28 0.57 1.27 0.18

Cyclin D3 1.39 0.16 1.53 0.30 1.71 0.31 1.81 0.12 RXRγ ND ND ND ND

DHAPAT 1.10 0.14 3.62 1.97 5.31 0.66 6.09 1.35 SCD1 1.83 0.18 17.39 5.16 ++++ ++++

eNOS 0,.86 1.24 0.15 1.39 0.37 1.30 SCD2 1.30 0.26 2.70 1.61 3.41 0.46 6.42 0.50

ERA 0.79 0.09 1.17 0.05 1.50 0.36 1.60 0.12 SDF1 0.50 0.19 0.66 0.13 0.86 0.12 0.66 0.25

FABP4/aP2 1.49 0.31 25.37 16.57 56.28 17.57 31.31 13.77 SDF2 0.29 0.10 0.31 0.04 0.46 0.09 0.37 0.18

FAS 1.96 0.16 3.93 1.27 6.44 1.34 6.03 0.34 Smad3 0.52 0.00 0.59 0.06 0.89 0.51 -

GAPDH 1.75 0.48 1.25 0.19 1.39 0.21 1.60 0.20 SPARC 0.92 0.08 0.93 0.15 0.81 0.22 0.78 0.18

GATA-2 - - - - SREBP-1 1.77 0.38 1.68 0.19 2.30 0.25 1.82 0.24

GATA-3 - ND ND ND Stat6 1.09 0.13 1.30 0.25 1.17 0.25 1.22 0.16

GLUT-4 ND 1,05 + + TBP 0.97 0.17 1.25 1.43 1.80

GPAT 1.11 0.24 2.15 0.28 3.03 0.12 3.32 0.58 TF 0.28 0.08 0.46 0.08 0.54 0.10 0.50 0.18

GPDcyt 1.91 +++ ++++ ++++ TGF-β1 1.11 0.42 1.47 0.13 1.40 0.11 1.52

GPDmit 0.87 0.16 1.47 0.07 1.51 0.05 1.24 0.22 TNFα ND ND ND ND

Gsn 2.11 0.13 2.13 0.17 1.57 0.15 1.01 0.19 UCP-2 1.89 0.20 1.89 0.05 2.27 0.44 3.30 0.26

Gyk ND ND ND ND VEGF-A 0.89 0.34 1.24 0.12 1.83 0.49 3.50 0.99

HCNP 1.18 0.23 1.04 0.13 1.02 0.11 0.83 0.12 VEGF-B 0.72 0.12 1.05 0.04 1.14 0.20 0.94 0.07

Hp 6.81 3.18 7.45 2.56 6.59 2.92 6.33 5.04 VEGF-C 0.48 0.22 0.59 0.13 0.35 0.04 0.24 0.12

HSD ND +++ ++++ ++++ Wnt10b ND ND ND ND

HSL 1.08 0.05 2.13 0.51 6.38 0.36 4.62 2.96

Day 2 Day 4 Day 6 Day 8Day 2 Day 4 Day 6 Day 8

Gene expression profiling in differentiating 3T3-L1 adipocytes analyzed with the DNA microarray. Cells were incubated for 2, 4, 6 and 8 days with the adipogenic cocktail before total RNA extraction, reverse-transcription and cDNA hybridization, as described in Materials and Methods. Each value is the average of three ratio values calculated from three – or two, when no standard deviation (S.D.) is indicated – independent RNA extractions for both reference and test conditions. Mean ratios (M.R.) indicate a fold-increase or decrease in gene expression. Significant mean ratios, obtained from ratios falling out of the 95% confidence interval, determined on the basis of house-keeping gene variations, are shown on a grey background. ND, transcript not detected in both conditions (test and reference). Qualitative ratios are represented as (+) < 5; 5.1< (++) <10; 10.1< (+++) <25; (++++) >25.1; (-) >–5. For gene abbreviations, please refer to supplementary material Table S1.

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already validates the DNA microarray developed in this study.To further validate our data, we also performed SYBR Greenquantitative RT-PCR assays for selected genes. Values obtainedfor a set of three genes upregulated in response to theadipogenic cocktail were confirmed for different incubationtimes (Fig. 5A). For these genes we found a very goodcorrelation of the relative transcript-abundance-data obtainedby DNA microarray and by RT-PCR.

AA-induced gene expression profilesWe next analyzed the effect of AA-induced mitochondrialdysfunction on gene expression in 3T3-L1 cells (Table 2). Fewgenes were found to be continuously upregulated in cellsresponding to the inhibition of mitochondrial activity. Thesegenes included those encoding cytokines (PAI-1, TGF-�1),stress proteins (HSP 60), transcription factors (CHOP-10,GATA-3) and proteins involved in energy and lipid metabolism(GPDmit, FABP4/aP2, SCD1). Some genes were transientlyupregulated in these conditions (adipsin, ATR I, Cav-1, cyclinD3, GLUT-4, Gyk). We also found that AA reduces theexpression of many genes, such as ADD1, AGT, ASP, C/EBP�,Coll VI�2, CPT-1 L, FAS, GPDcyt, LPL1, MCAD, NFATc2,NFATc4, p110�, p18, Pref-1, resistin, SDF1, Smad3, Stat6 andVEGF-C. Relative transcript abundance for FAS and Clic4,determined by RT-PCR at day 4 of AA treatment, is similar tothe values obtained with the microarray analysis on the samesamples (Fig. 5A). We also observed that AA increases theabundance of mitochondrial glycerol-3-phosphatedehydrogenase (GPDmit) protein in 3T3-L1 cells (Fig. 5B), inaccordance to upregulation of the GPDmit transcript (asdetermined with the microarray).

The expression status of genes that were up- or down-regulated by both AA and the adipogenic cocktail wascompared after 2, 4, 6 and 8 days of treatment (Fig. 6).Although it is known that many stresses, including energeticstresses, trigger a shut-down of global transcription and proteinsynthesis (Buttgereit and Brand, 1995; Wieser andKrumschnabel, 2001), most of these genes were not known to

Journal of Cell Science 119 (7)

be differentially regulated in response to a mitochondrialdysfunction. Several patterns of gene expression wereidentified and some of them are illustrated in Fig. 7. In the firstpattern, expression of the gene was elevated at day 2 and thendeclined (Fig. 7A). This group included adipsin, ATR I, Cav-1, CPT-2, cyclin D3, GLUT-4 and Gyk. In the second pattern,gene expression was increased at day 2 and sustained duringthe whole programme, as for GPDmit (Fig. 7B). In the thirdgroup, gene expression was elevated at day 4 and maintainedat high levels, as observed for CHOP-10, GATA-3, HSP60,SCD-1 and TGF-�1 (Fig. 7C). The last profile included genesfound to be downregulated from day 4 (AGT, C/EBP�, CPT-1L, MCAD, p18, Stat6, VEGF-C) or day 6 (ADD1, CL, NFATc2,NFATc4, p110�, Pref-1, resistin, SCD2, SDF1, SDF2, Smad3)of AA treatment (Fig. 7D).

CREB-dependence of AA-regulated genesThe role of CREB in the modifications of gene expressioninduced by AA was further investigated using the powerfulcombination of RNAi (to silence CREB) and microarraytechnology. This analysis was performed because CREB is animportant transcription factor activated by mitochondrialdysfunction (Arnould et al., 2002), a primary regulator ofadipogenesis leading to TG accumulation (Reusch et al.,2000) and contributes to TG accumulation in AA-treated cells(Figs 3 and 4). 3T3-L1 cells were evenly divided into twogroups. One group was transfected with double-strandedRNA olignucleotides directed against CREB transcripts,whereas the other group was treated as a control with thesiRNA delivery reagent JetSITM alone. Previous studies,targeted at the NF-�B, HTLV-I tax and HIV-1 reversetranscriptase genes showed that unrelated siRNAs do not

Up/Down-

Gene Time regulation

(fold change)

C/EBP � day 2 2.38

C/EBP � day 4 1.27

C/EBP � day 6 0.45

C/EBP � day 2 3.36

C/EBP � day 4 2.46

C/EBP � day 6 0.57

Leptin day 8 6.30

IL-6 day 8 0.11

Fig. 4. Effect of the adipogenic cocktail on the transcription levels ofleptin, IL-6, C/EBP� and C/EBP� genes analyzed by RT-PCR. Cellswere incubated for the indicated times with the adipogenic cocktailbefore RNA extraction, reverse-transcription and amplification in thepresence of SYBR Green and specific primers. TBP was used as ahouse-keeping gene for data normalization.

Fig. 5. (A) Comparison of the results obtained with RT-PCR andDNA microarray analyses for FAS, Clic4 and CPT-2 genes. Cellswere incubated for the indicated times with the adipogenic cocktail(DIFF) or 10 nM antimycin A (AA) before RNA extraction, reverse-transcription and amplification in the presence of SYBR Green andspecific primers. TBP was used as a house keeping gene for datanormalization. (B) Western blot analysis for GPDmit performed on20 �g of clear cell lysate proteins prepared from 3T3-L1 cellsincubated or not (controls, CTL) for 2, 4, 6 or 8 days with 10 nMAA. Equal protein loading was controlled by the immunodetection ofPARP.

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impair gene expression that is specifically altered by TNF�,and give equivalent results to the transfection reagent alone(Zhou et al., 2003). Thus, cells transfected or not with siRNAsilencing CREB were incubated for 4 days with 10 nM AAand processed for hybridization (Table 3). We first observed

that the JetSI reagent does not significantly modify theexpression of most genes analyzed by the microarray, whencompared with the profiles obtained for two independentRNA extractions prepared from 3T3-L1 cells that had beentreated for 4 days with 10 nM AA (Table 3, AA1 and AA2

Table 2. Gene expression profiles of 3T3-L1 preadipocytes treated with antimycin A

Gene-expression profiling in 3T3-L1 preadipocytes treated with AA analyzed with the DNA microarray. Cells were incubated for 2, 4, 6 and 8 days with 10nM AA before total RNA extraction, reverse-transcription and cDNA hybridization, as described in Materials and Methods. Each value is the average of threeratio values calculated from three – or two, when no standard deviation (S.D.) is indicated – independent RNA extractions for both reference and test conditions.Mean ratios (M.R.) indicate a fold-increase or decrease in gene expression. Significant mean ratios, obtained from ratios falling out of the 95% confidenceinterval, determined on the basis of house keeping gene variations are shown on a grey background. ND, transcript not detected in both conditions (test andreference). Qualitative ratios are represented as(+) <5; 5.1< (++) <10; 10.1< (+++) <25; (-) > –5; –10.1> (---) > –25; (----) <–25.1. For gene abbreviations, pleaserefer to supplementary material Table S1.

Genes M.R. S.D. M.R. S.D. M.R. S.D. M.R. S.D. Genes M.R. S.D. M.R. S.D. M.R. S.D. M.R. S.D.AAAT 0.80 0.24 1.09 0.14 0.74 0.24 0.90 0.23 HSP 60 1.72 1.07 1.86 0.37 1.71 0.,18 2.02 0.67

Acrp30 1.06 0.44 - - - HSP 84 1.09 1.35 0.31 1.08 0.15 1.07 0.16

Actin 1.25 0.29 0.83 0.16 0.81 0.27 0.84 0.21 HSP 86 ND 1.29 0.38 1.36 0.34 1.56 0.92

ADD1 1.39 0.17 0.68 0.09 0.48 0.09 0.52 0.05 IL-6 ND ++ + ++

Adipsin 3.07 1.32 0.47 0.28 0.09 0.20 0.13 iNOS 1.08 ND 1,02 ND

AGT 1.27 0.39 0.63 0.25 0.35 0.07 0.49 0.04 Leptin ND 0.91 0.72 0.68

ASP 1.57 0.47 0.37 0.16 0.21 0.08 0.12 0.08 L-PK 0.77 1.19 0.09 1.08 0.09 1.17 0.39

ATR I 2.08 0.43 1.23 0.25 0.95 0.06 1.10 0.09 LPL1 1.17 0.01 1.07 0.29 0.69 0.04 0.53 0.23

ATR II 2.19 0.84 ND ---- --- MCAD 1.10 0.31 0.46 0.14 0.26 0.06 0.32 0.08

β3AR - 0.99 0.86 0.85 MMP-2 1.05 1.26 0.34 1.03 0.17 0.65 0.34

CaMK IIγ - 0.91 0.16 0.51 0.09 0.75 0.18 NFATc2 1.22 0.13 0.91 0.05 0.68 0.11 0.61

CaMK IV 1.19 0.58 ND ND ND NFATc4 1.00 0.05 0.64 0.05 0.48 0.03 0.59 0.06

Cav-1 2.45 0.61 1.41 0.32 1.15 0.18 1.89 0.90 p110α 0.92 0.19 0.73 0.40 0.38 0.09 0.51

Cav-2 ++ 1.72 0.58 1.58 1.85 p18 0.89 0.17 0.52 0.06 0.39 0.07 0.41 0.08

C/EBPα 1.09 0.79 0.45 0.14 0.36 0.05 0.38 0.16 PAI-1 1.02 0.24 +++ 12.44 7.66 14.51

C/EBPβ 0.83 0.19 1.08 0.06 1.02 0.21 0.95 0.07 PEDF ND 0.77 0.17 0.67 0.07 0.52 0.08

C/EBPδ 1.32 0.24 0.74 0.29 0.42 0.13 0.59 0.28 PEPCK1 0.97 0.19 ND 0.91 ND

CHOP-10 1.35 0.27 4.88 1.90 4.64 1.18 4.02 0.84 Plin ND 0.90 0.10 0.86 0.04 0.83 0.06

CL 1.22 0.45 0.67 0.03 0.51 0.10 0.72 0.29 PPARδ 0.95 0.02 1.28 0.12 1.05 0.08 1.07 0.10

Clic4 1.60 0.40 1.71 0.21 1.23 0.16 1.35 0.14 PPARγ 0.95 0.07 1.23 0.23 0.93 0.16 1.15 0.40

Coll VIα2 0.73 0.50 0.60 0.10 0.41 0.02 0.44 0.04 Pref-1 1.07 0.26 0.60 0.12 0.46 0.03 0.32 0.04

CPT-1 L 1.00 0.44 0.67 0.06 0.52 0.03 0.61 0.06 RAB3D 1.14 0.27 0.96 0.08 0.86 0.03 0.81 0.08

CPT-1 M 1.63 0.13 0.69 0.66 ND Renin 0.99 0.06 1.22 0.08 0.97 0.08 1.01

CPT-2 1.68 0.84 0.19 0.52 0.15 0.82 0.21 Resistin 0.97 0.85 0.57 0.57

CREB1 1.52 1.04 0.23 0.95 0.07 0.89 0.06 rRNA18s 1.01 0.19 0.67 0.44 0.80 0.08 0.74 0.25

Cst C 1.48 0.31 1.25 0.17 1.03 0.11 0.94 0.22 RXRα ND 1.16 0.20 1.01 0.03 0.92 0.02

Cyclin D3 1.70 0.27 1.28 0.21 0.76 0.11 0.81 0.11 RXRγ 1.16 0.11 1.05 1.03 0.09 0.84

DHAPAT 1.61 0.43 1.10 0.24 0.78 0.11 0.97 0.19 SCD1 1.27 0.09 1.88 0.54 3.24 2.41 1.13

eNOS 2.05 1.09 0.05 0.81 0.09 0.93 0.11 SCD2 1.05 0.11 0.82 0.02 0.61 0.17 0.68 0.26

ERA ND 0.65 0.19 0.39 0.05 0.70 0.20 SDF1 0.79 0.10 0.87 0.07 0.54 0.10 0.37 0.19

FABP4/aP2 ND 3.26 0.82 2.23 0.41 2.44 0.17 SDF2 0.74 0.11 1.11 0.31 0.60 0.10 0.57 0.24

FAS ND 0.75 0.02 0.63 0.13 0.62 0.03 Smad3 0.91 0.09 0.78 0.22 0.53 0.02 0.55 0.14

GAPDH ND 1.11 0.14 1.08 0.06 1.05 0.13 SPARC 1.02 0.23 0.93 0.21 0.72 0.02 0.65 0.18

GATA-2 ND 0.70 0.20 0.55 0.27 0.67 SREBP-1 1.01 0.16 0.89 0.04 0.67 0.11 0.69 0.10

GATA-3 1.41 0.15 2.10 0.27 2.03 0.47 2.66 1.13 Stat6 0.91 0.10 0.54 0.16 0.34 0.02 0.45 0.07

GLUT-4 2.15 1.49 1.21 0.19 1.41 0.21 1.44 0.35 TBP 0.99 0.95 0.67 0.82

GPAT 2.42 2.11 0.77 0.19 0.50 0.06 0.55 TF 1.04 0.06 1.29 0.13 1.11 0.17 1.13 0.35

GPDcyt 1.33 0.60 0.74 0.50 0.18 0.55 TGF-β1 0.98 0.37 2.71 0.46 3.24 0.87 3.07 0.41

GPDmit 1.97 0.73 2.27 0.35 1.95 0.37 1.97 0.14 TNFα 0.88 0.18 ND ND ND

Gsn 1.99 0.54 0.74 0.16 0.56 0.05 0.62 0.18 UCP-2 1.08 0.11 0.81 0.05 0.59 0.03 0.83 0.23

Gyk 2.25 1.17 1.50 1.49 1.53 VEGF-A 1.41 0.09 1.30 0.29 0.98 0.12 1.14 0.11

HCNP 0.83 0.25 1.13 0.12 0.97 0.04 1.11 0.11 VEGF-B 1.43 0.21 1.26 0.05 1.14 0.04 1.05 0.09

Hp 1.27 2.13 0.81 0.96 0.70 1.82 2.67 VEGF-C 1.18 0.12 0.58 0.11 0.34 0.05 0.37 0.01

HSD 1.08 0.35 ++ + ++ Wnt10b 0.80 0.17 ND ND ND

HSL 1.56 1.15 0.95 0.12 1.04 0.22 0.80 0.17

Day 2 Day 4 Day 6 Day 8Day 2 Day 4 Day 6 Day 8

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columns). We also found that, out of the 89 genes analyzed,the transcript abundance for eight genes (CHOP-10, Clic4,GPDmit, HSP 60, PAI-1, TF, VEGF-A and SCD1) wassignificantly decreased by CREB-specific siRNA, suggestinga role for CREB in the control of the transcription of thesegenes in response to AA. On the opposite, the differentialexpression of some genes, such as upregulation of FABP4 anddownregulation of p18, is not affected by the inhibition ofCREB expression in AA-treated cells.

Journal of Cell Science 119 (7)

DiscussionNumerous experimental data and observations reported fromphysiopathological situations and experimental models nowclearly support a direct link between mitochondrialdysfunction and metabolic disorders, therefore addressing theessential role of mitochondrial-activity impairment inalterations in lipid metabolism (Lowell and Shulman, 2005;Petersen et al., 2003; Petersen et al., 2004). The myoclonicepilepsy with ragged red fibers (MERRF) syndrome that is

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Fig. 6. Comparison of geneexpression profiles as quantifiedwith the DNA microarray indifferentiating 3T3-L1adipocytes (white) and in 3T3-L1preadipocytes incubated with 10nM antimycin A (grey). Cellswere differentiated or treatedwith 10 nM AA for (A) 2, (B) 4,(C) 6 and (D) 8 days; data arepresented for some selectedgenes to illustrate majorsimilarities and differencesbetween both treatments. For theother genes, see Tables 1 and 3.Mean ratios indicate a fold-increase or decrease in geneexpression. *, significant meanratios, obtained from ratiosfalling out of the 95% confidenceinterval.

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often caused by numerous point mutations (G611A,A3243G, A8344G, G8361A, G12147A) inmtDNA, which affect genes encoding differentmitochondrial tRNAs (Mancuso et al., 2004;Mongini et al., 2002; Shoffner et al., 1990;Rossmanith et al., 2003; Melone et al., 2004), isalso to some extent associated with lipid-storagedisorders and TG accumulation in muscles (Munoz-Malaga et al., 2000; Naumann et al., 1997). It hasalso been shown that most of multiple symmetricallipomatosis (MSL) patients also displaymitochondrial dysfunction (Naumann et al., 1997;Berkovic et al., 1991), lipomas that contain atypicalmultivacuolar white adipocytes (Zancanaro et al.,1990) as well as ragged red fibers and TGaccumulation in muscles (Klopstock et al., 1997;Munoz-Malaga et al., 2000). The role ofmitochondria in TG metabolism is alsostrengthened by their implication in thelipodystrophy syndrome resulting from anti-retroviral therapies that combine drugs known toinhibit mitochondrial DNA polymerase � andmitochondrial processing protease (Kakuda, 2000;Brinkman et al., 1999). Cytosolic TG accumulationis also observed in cardiomyocytes incubated underhypoxia (Huss et al., 2001) and in preadipocytesincubated with mitochondrial respiration inhibitors(Vankoningsloo et al., 2005). Both conditions leadto the downregulation of CPT-1 M (carnitinepalmitoyltransferase-1, muscle isoform) and asubsequent decrease in mitochondrial fatty acid �-oxidation. These data emphasize the link betweenmitochondrial dysfunction and abnormalities in TGstorage. However, even if TG accumulation inresponse to mitochondrial alterations is of interest,because it can modify cell sensitivity to agonistssuch as insulin (Lowell and Shulman, 2005), themechanisms leading to cellular TG accumulation inthese conditions remain largely unknown.

Cells with mitochondrial dysfunction provide anadaptative response mainly characterized byactivation of glycolysis and a decrease in cellproliferation. In addition, depending on cell typeand model, several signaling pathways participateto the so-called ‘retrograde communication’between mitochondria and the nucleus, allowing thecells to change the activity status of severaltranscription factors such as nuclear factor ofactivated T cells (NFAT), nuclear factor-�B (NF-�B) and CREB leading to modifications in gene expression(Liu and Butow, 1999; Biswas et al., 1999; Butow andAvadhani, 2004; Arnould et al., 2002). For example, we havepreviously shown that CREB is activated by phosphorylationon Ser133 in the cell lines L929 and 143B, with impairedmitochondrial activity induced either by mtDNA depletion orinhibitors of the oxidative phosphorylation such as AA,oligomycin or FCCP (Arnould et al., 2002). A constitutiveactivation of CREB was also found in cybrid cells, with theA8344G mutation in the mitochondrial genome described tobe responsible for the MERRF syndrome (Arnould et al.,2002). Interestingly, CREB has also been reported to be

phosphorylated on Ser133 in PC12 cells incubated underhypoxia, another condition known to inhibit mitochondrialrespiration (Beitner-Johnson and Millhorn, 1998; Beitner-Johnson et al., 2000).

CREB is an ubiquitous transcription factor that regulatesnumerous cellular functions such as cell survival, proliferationand differentiation, as well as glucose and lipid metabolism(Reusch and Klemm, 2002; Reusch et al., 2000; Della Fazia etal., 1997; Zhou et al., 2004; Herzig et al., 2003). Here weclearly show that CREB is phosphorylated on Ser133 andtranscriptionally more active in 3T3-L1 preadipocytes whenmitochondrial activity is inhibited by AA, a complex-IIIinhibitor. The kinase that phosphorylates CREB in AA-treated

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AGT ADD1C/EBPa CLCPT-1 L NFATc2MCAD NFATc4

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Fig. 7. Representative time-course profiles of gene expression in 3T3-L1preadipocytes incubated with 10 nM antimcyin A, determined by the DNAmicroarray is illustrated for (A) ATR I, (B) GPDmit, (C) CHOP-10 and (D)C/EBP�. Similar profiles were obtained for the genes listed on the right in A-D.Mean ratios indicate a fold-increase or decrease in gene expression. *,significant mean ratios, obtained from ratios falling out of the 95% confidenceinterval.

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Table 3. Determination of CREB-regulated genes among genes differentially expressed in 3T3-L1 preadipocytes treatedwith antimycin A

Genes AA 1 AA 2 AA+JetSI AA+siRNA Genes AA 1 AA 2 AA+JetSI AA+siRNAAAAT 1.11 1.26 1.38 -1.19 HSP 60 2.02 1.80 1.46 -1.92

Acrp30 - - - - - - - ND ND HSP 84 1.11 -1.10 -1.04 -2.08

Actin 1.11 1.14 1.16 1.08 HSP 86 1.86 1.08 1.07 1.00

ADD1 -1.54 -2.08 -1.82 -1.45 IL-6 ND ND ND ND

Adipsin - - - - - ND ND iNOS ND ND ND ND

AGT - -2.86 - ND Leptin ND ND ND ND

ASP -3.12 -10.00 -7.14 -1.85 L-PK 1.18 1.43 -1.07 -1.64

ATR I 1.13 -1.19 -1.11 -1.09 LPL1 -1.08 -2.22 -1.51 -3.12

ATR II ND ND ND ND MCAD - -2.63 -2.44 -

β3AR ND ND ND ND MMP-2 -1.35 -1.59 -1.96 1.03

CaMK IIγ -1.16 -1.51 -1.35 -2.00 NFATc2 ND 1.22 - -

CaMK IV ND ND ND ND NFATc4 -1.85 -1.79 -1.82 -1.33

Cav-1 2.40 1.35 1.09 -1.51 p110a -1.35 -1.79 - -

Cav-2 ND ND ND ND p18 -1.02 -2.78 -1.96 -1.69

C/EBPα - - - ND PAI-1 ++++ ++++ +++ -1.75

C/EBPβ -1.04 -1.18 -1.18 1.03 PEDF -1.39 -1.23 -1.28 1.09

C/EBPδ -1.51 -1.32 -1.43 -1.18 PEPCK1 ND ND ND ND

CHOP-10 6.61 5.81 3.68 -1.59 Plin -1.37 -1.12 -1.10 1.80

CL -1.26 -1.39 -1.28 -1.85 PPARd 1.01 1.02 -1.14 -1.30

Clic4 1.60 1.50 1.36 -1.82 PPARg -1.30 1.23 1.10 -1.75

Coll VIα2 -1.79 -2.32 -2.00 1.09 Pref-1 -1.85 -2.13 -1.96 1.25

CPT-1 L -1.27 -1.96 -1.72 -1.54 RAB3D 1.45 1.06 -1.06 -

CPT-1 M ND ND ND ND Renin ND 1.05 ND ND

CPT-2 -1.05 -1.27 -1.23 -1.09 Resistin - - ND ND ND

CREB1 -1.14 -1.12 -1.14 - rRNA18s -1.04 -1.23 -1.14 1.01

Cst C -1.07 -1.05 -1.14 -1.23 RXRa -1.14 -1.03 1.18 -1.09

Cyclin D3 -1.10 -1.07 -1.11 -1.09 RXRg ND ND ND ND

DHAPAT ND 1.00 -1.12 1.61 SCD1 -2.00 1.30 1.07 -1.72

eNOS -1.33 1.18 -1.06 -1.33 SCD2 -1.75 -1.51 -1.59 -1.67

ERA -1.54 -2.04 -1.30 -1.19 SDF1 -1.20 -2.94 -2.32 -1.28

FABP4/aP2 -2.00 1.74 2.11 3.03 SDF2 -1.16 -2.00 -2.04 -1.72

FAS -2.08 -1.27 -1.89 -1.16 Smad3 -1.59 -1.67 1.01 -1.09

GAPDH 1.04 1.06 1.04 -1.04 SPARC -1.45 -1.22 -1.11 -1.11

GATA-2 - -1.59 -1.07 1.13 SREBP-1 -1.82 -1.51 -1.30 -1.23

GATA-3 ND + + -1,30 Stat6 - -1.56 -1.61 -

GLUT-4 -1.05 1.20 ND - TBP ND ND ND -

GPAT - -1.67 - - TF 1.03 -1.11 1.26 -2.56

GPDcyt - - - - ND ND TGF-b1 2.48 1.99 1.94 -1.01

GPDmit 1.64 1.65 1.66 -2.56 TNFa ND ND ND ND

Gsn -1.79 -1.45 -1.43 -1.22 UCP-2 -1.56 -1.11 -1.19 -1.19

Gyk ND ND ND ND VEGF-A -1.11 1.14 1.50 -2.27

HCNP -1.27 -1.11 -1.02 -1.25 VEGF-B 1.05 1.00 1.12 -1.12

Hp -1.89 -5.88 -3.22 -1.51 VEGF-C -1.18 -1.85 -1.23 -2.00

HSD ND ND ND ND Wnt10b ND ND ND ND

HSL -1.72 -1.20 -1.14 1.11

Effect of CREB knock-down induced by specific siRNA on gene expression in AA-treated 3T3-L1 cells analyzed with the DNA microarray. Cells were transfected for 4 hours with 100 nM siRNA (AA + siRNA) or incubated for 4 hours with JetSI (AA + JetSI) and then incubated for 4 days with 10 nM AA before RNA extraction, retro-transcription and hybridization. Results are compared with those of two independent experiments performed on 3T3-L1 cells incubated for 4 days with 10 nM antimycin A before RNA extraction, retro-transcription and hybridization (AA1 and AA2). Significant ratios falling out of the 95% confidence interval are shown in grey. Data are expressed as detailed in tables 1 and 3. Qualitative ratios are represented as (+) <5; 10.1< (+++) <25; (++++) >25.1; (-) >–5; -5.1> (--) >–10; –10.1> (---) >–25; (----) <–25.1. For gene abbreviations, please refer supplementary material Table S1.

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3T3-L1 cells remains to be identified but CaMK IV is a goodcandidate because it is the effector in mtDNA-depleted cells(Arnould et al., 2002). However, several other kinases such asPKA (protein kinase A), PKB/Akt, CaMK I/II or ribosomal S6kinase 1/2 (RSK1/2) could also play a role because theyphosphorylate CREB in response to various stimuli(Johannessen et al., 2004; Shaywitz and Greenberg, 1999). Adecrease in PP1 or PP2A (protein phosphatase 1 or 2A,respectively) activity can also be considered because theseenzymes dephosphorylate CREB (Hagiwara et al., 1992;Wadzinski et al., 1993).

CREB activation that is induced by impaired mitochondrialactivity in different cell types, suggests an important role forthis transcription factor in the adaptative cell response toenergetical stress. Although the molecular mechanisms are stillunidentified, we clearly show that CREB is involved in thecytosolic accumulation of TG induced by a prolonged (severaldays) exposure of 3T3-L1 preadipocytes to AA. Indeed, theamount of TG accumulated in cells treated for 8 days with AAis reduced by overexpression of the dominant negative formsof either K-CREB or M1-CREB (by about 40%) and thesilencing of CREB expression in transiently transfected cellswith a specific siRNA (by 75%). The weaker inhibitory effectof dominant negative mutants might be caused by a lowertransfection efficiency of plasmids (ranging from 20 to 40% asdetermined in subconfluent cells transfected with a plasmidencoding a pCMV-�-galactosidase as a reporter gene)compared with that of siRNA. However, a lesser inhibition ofTG accumulation, observed in cells that overexpress dominantnegative CREB mutants, might also be owing to a briefinhibition of CREB activity, caused by dominant negativemutants, whereas a longer-lasting effect is obtained in thepresence of siRNA.

CREB silencing was shown to take place during the first 48hours post-transfection with siRNA but was transient becauseCREB expression is recovered after 96 hours (data not shown).Since TG accumulated significantly after 7 to 8 days oftreatment (Vankoningsloo et al., 2005), our data suggest thatthe rapid CREB activation induced by AA triggers a cascadeof events, leading to TG accumulation later on. CREBactivation in 3T3-L1 cells responding to a pro-adipogeniccocktail was also detected very early in differentiation, beforeany TG started to accumulate (Reusch et al., 2000). We thusidentified CREB as a key-effector in cytosolic accumulation ofTG, induced by AA in 3T3-L1 cells.

To better understand the metabolic origin of TGaccumulation in 3T3-L1 preadipocytes with impairedmitochondrial activity, we developed and used a low-densityDNA microarray that allowed simultaneous gene-expressionanalysis for numerous adipogenic markers. We validated thedata obtained in the array experiments by several means. First,using the 3T3-L1 preadipocyte cell line was advantageousbecause it has been used extensively to investigatedifferentiation-dependent gene expression in adipocytes(Rosen and Spiegelman, 2000; Guo and Liao, 2000; Burton etal., 2002; Burton et al., 2004; Ross et al., 2002). Since theseprevious studies have led to the identification of several genesthat are differentially expressed during differentiation, any newapproach should also successfully pick up these genes and, indoing so, serve as a compelling control method. Indeed, wefound that many adipogenic markers were upregulated during

adipogenesis, e.g. several transcription factors (C/EBP�,PPAR�, RXR�, SREBP-1), enzymes involved in fatty acid andTG metabolism (DHAPAT, FABP4/aP2, FAS, GPAT, SCD1,SCD2), and adipokines (AGT, resistin) (MacDougald andLane, 1995; Gregoire et al., 1998; Burton et al., 2004; Hajra etal., 2000; Song et al., 2002). We also observed thedownregulation of anti-adipogenic markers, such as Pref-1, anautocrine and/or paracrine inhibitor of adipogenesis, and thetranscription factors GATA-2 and GATA-3. These genes havebeen reported to be only highly expressed in preadipocytes(Lee et al., 2003; Tong et al., 2005). Second, we used RT-PCRto confirm the data obtained in the microarrays for FAS, Clic4and CPT-2. We observed in this study that, several proteinsknown to be overexpressed by differentiating 3T3-L1 cells(Welsh et al., 2004) are also upregulated at the transcript level,e.g. Acrp30 and GPDcyt. Third, by using a proteomicapproach, Kratchmarova et al found that several proteins aresecreted by differentiating 3T3-L1 cells (Kratchmarova et al.,2002); we found that mRNA levels of some of these proteins,such as Acrp30, adipsin, Gsn, Hp, resistin and MMP-2, werealso upregulated. By contrast, we observed that PEDF, knownto be secreted mainly by undifferentiated preadipocytes(Kratchmarova et al., 2002), is downregulated during 3T3-L1adipogenesis.

To highlight similarities and differences of gene expressionprofiles in differentiating cells and also in preadipocytes withimpaired mitochondrial activity (cellular circumstances thatin both cases lead to the accumulation of TG) we nextanalyzed changes in gene expression in preadipocytesincubated with AA for different times and compared thesegene expression profiles with those observed during thedifferentiation of 3T3-L1 cells. For example, we found hatboth AA and the adipogenic cocktail downregulate Pref-1 andupregulate some adipogenic genes involved in fatty-acid andsterol metabolism, such as FABP4/aP2, SCD1 and HSD. Wefound that many genes that are upregulated during in vitroadipogenesis (such as those encoding the transcription factorsC/EBP�, PPAR�, PPAR�, RXR� and SREBP-1, the lipid-metabolizing enzymes DHAPAT, FAS, HSL and LPL1, or theadipokines AGT and resistin) are either unaffected ordownregulated by AA. Furthermore, AA also induces thetranscription of anti-adipogenic transcription factors, such asGATA-3 and CHOP-10 (an endogenous dominant negativeprotein that heterodimerizes with C/EBP family members andrepresses C/EBP-dependent transcription) (Ron and Habener,1992). CHOP-10 overexpression in AA-treated 3T3-F442Acells has been previously reported and shown to preventadipogenesis (Carriere et al., 2004). All together, these datasuggest that AA does not induce the expression of classicadipogenic markers. It is therefore likely that the mechanismsleading to TG accumulation in response to a mitochondrialdysfunction are not the same as those described for celldifferentiation into adipocytes, a conclusion that alsoemerged from our previous report (Vankoningsloo et al.,2005).

Transcripts for Gyk (glycerol kinase) were not detectedduring adipogenesis, probably because of their very lowabundance. However, Gyk mRNA levels raise to detectablelevels in cells incubated with AA, and Gyk is transientlyoverexpressed under this condition. Since glycerol kinaseconverts glycerol into glycerol-3-phosphate, a direct precursor

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of TG (Lin, 1977), it might also contribute to the accumulationof TG in 3T3-L1 cells treated with AA. Moreover, thedownregulation of genes, such as CPT-1, that encode enzymesof the mitochondrial fatty acid �-oxidation, controlling themitochondrial entry of free fatty acids, and MCAD, a fatty acyldehydrogenase, is in agreement with our previous findings,showing that AA-induced TG accumulation could result, atleast partly, from a decrease in fatty acid �-oxidation(Vankoningsloo et al., 2005). Interestingly, MCADtranscription is controlled by PPAR transcription factors(Gulick et al., 1994), and we have recently shown that theactivity of PPAR� is decreased in cells treated with AA(Vankoningsloo et al., 2005). Cav-1 has recently been shownto associate with intracellular lipid droplets and to modulate,in combination with perilipin, both lipolysis and vesicleformation (Cohen et al., 2004). In this study, we showed thatthe Cav-1 gene is upregulated during 3T3-L1 cell adipogenesisand also (although to a lesser extent) during AA treatment.Therefore, these differencies in Cav-1 expression might alsocontribute to the fact that TG vesicles accumulating in 3T3-L1cells incubated with AA are smaller compared with those indifferentiating 3T3-L1 cells.

By using siRNA to disrupt CREB expression, we found thatthe transcription of several genes (CHOP-10, Clic4, GPDmit,HSP 60, PAI-1, TF, SCD1 and VEGF-A) might depend on AA-induced CREB activation. Furthermore, it is interesting thatsome of these genes contain between one and six putativeCRE sites in their promoters [determined by in silicopromoter analysis with the Data Base for TranscriptionalStart Sites (http://dbtss.hgc.jp) and TF Search(http://molsun1.cbrc.aist.go.jp/research/db/TFSEARCH.html)].However, in silico identification of potential consensussequences for transcriptional regulators does not reveal anyinformation concerning their biological relevance. To test thefunctionality of the CRE motifs, gene expression analysisusing the DNA array was performed in 3T3-L1 cells that hadbeen incubated for 48 hours with 1 mM dibutyryl cyclic AMP(db-cAMP) , a component of the adipogenic cocktail and awell-known activator of the PKA-CREB pathway (Boissel etal., 2004; Chio et al., 2004). We first tested whether db-cAMPcan activate the CREB-responsive luciferase reporter gene. A2.8-fold increase was found after 48 hours of treatment (datanot shown). Under these conditions, a significant upregulationof candidate genes was only found for VEGF-A and SCD1 (1.8-fold increase). Although the discrepancy of these two sets ofdata is unknown we suggest that, either not all CRE sites arefunctional or they require the contribution of other regulatorsas partners in the promoter to be fully active. These regulatorsets might be different in db-cAMP- and AA-treated cells. Ithas been reported that, in liver, the cAMP-sensivity of severalgenes, such as tyrosine aminotransferase (TAT) or PEPCKdepends on the cooperative action of CREB and HNF4� orCREB and C/EBPs, respectively (Nitsch et al., 1993; Roesler,2000). A similar cooperation between CREB and HNF4� hasalso been shown for the transcriptional control of CPT-1 L(Louet et al., 2002). These data suggest that the molecularmechanisms involved in the cAMP-mediated induction oftarget genes is more complex than the simple presence of aCRE motif requiring a cooperation between several factors. Inaddition, as for the expression of VEGF-A (a gene for whichin silico analysis failed to reveal any potential CRE sites in the

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promoter, despite the fact that it seems to depend on CREBexpression because it is downregulated when CREB is silencedby specific siRNA), one can not exclude that the CREB-dependence of gene expression is an indirect effect.

Overexpression of GPDmit protein in AA-treated 3T3-L1cells has been verified and GPDmit was considered a potentialcandidate linking CREB activation to TG accumulation inresponse to mitochondrial dysfunction. Indeed, GPDmitknockout mice display reduced adiposity and body weight,suggesting that this enzyme is involved in the control of TGsynthesis and/or storage (Brown et al., 2002). However, cellstransfected – either before or after a 5-day treatment with AA– with an efficient GPDmit-specific siRNA that inhibitsGPDmit expression at the protein and transcript level stillaccumulate the same amount of TG (as determined by Oil RedO staining) in response to an 8-day treatment with AA, whencompared with control cells (data not shown). These resultssuggest that GPDmit is not involved in the lipid deposition incells with impaired mitochondrial activity.

CREB has also been described to control hepatic lipidmetabolism by indirectly repressing PPAR� and by inducingPGC-1� (Herzig et al., 2003). PGC-1� is a co-activator ofnumerous transcriptional regulators and is involved in severalcell functions such as mitochondrial biogenesis (Scarpulla,2002), gluconeogenesis (Herzig et al., 2001), and lipidcatabolism because it controls the expression of genesencoding mitochondrial fatty-acid-oxidation enzymes (Vega etal., 2000). Although PGC-1� expression could not be analyzedusing the microrray, we monitored its expression in RT-PCRand western blots, and found that PGC-1� mRNA and proteinlevels remain stable – and even slightly decreased in cellsincubated for 24 or 48 hours with 10 nM AA or the adipogeniccocktail (data not shown), two conditions that activate CREBin 3T3-L1 cells. The absence of CREB-dependent PGC-1�regulation might seem surprising. However, varioustranscription factors have been identified to control PGC-1expression in tissues other than liver and among them, ATF-2in brown adipocytes (Cao et al., 2004), MEF-2 in muscle tissue(Czubryt et al., 2003), and orphan nuclear receptor ERR� inbrown adipocytes (Wang et al., 2005). Furthermore, in cellstransfected with a smart-pool of four siRNAs specific for PGC-1� [which reduce the expression of the gene by more than 50%(data not shown)] either before or during the treatment withAA, no modification was found in the accumulation of TG in3T3-L1 preadipocytes treated with the metabolic inhibitor(data not shown).

Finally, the SCD1 gene might also be an interestingcandidate to explain TG accumulation in preadipocytes withimpaired mitochondrial activity. Indeed, this gene encodes theenzyme that catalyzes the 9-cis desaturation of fatty acids(e.g. palmitoyl-CoA and stearoyl-CoA to palmitoleoyl-CoAand oleoyl-CoA, respectively), altogether representing up to60% of the fatty acids esterified into TGs in differentiated cells(Kasturi and Joshi, 1982). SCD1 is upregulated in AA-treated3T3-L1 cells, is downregulated following the inhibition ofCREB expression and contains a cAMP-dependent regulatoryelement in its promoter sequence (position –285 to –278relative to the start of transcription) (Ntambi et al., 1988).Recently, Miyazaki et al. showed that a lipogenic diet failed toinduce hepatic triglyceride synthesis in SCD1(–/–) mice, despitethe induction of FAS and GPAT (Miyazaki et al., 2001). The

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authors suggested that SCD1 activity would thus help toproduce substrates within the vicinity of GPAT to aid in theefficient esterification of glycerol 3-phosphate for TGsynthesis. Although the role of this enzyme in TGaccumulation has been clearly established (Ntambi et al.,2002), its regulation and potential implication as an effector inthe accumulation of TG in response to mitochondrialdysfunction is awaiting future studies in cells with modifiedSCD1 gene expression.

In conclusion, although the molecular mechanism(s) andtarget gene(s) by which activated CREB, a factor involved inmany cellular processes and in the regulation of severalhundred genes, leads to TG deposition in preadipocytes withimpaired mitochondrial activity still await discovery, our studyclearly extends the role of the ubiquitous CREB transcriptionfactor. We bring some evidence for its contribution to lipidmetabolism alterations in preadipocytes with mitochondrialdysfunction. We also show that the mechanisms leading to TGaccumulation in response to mitochondrial dysfunction aredifferent than those described for lipid accumulation observedduring cell differentiation, which is triggered by a standardhormon cocktail; we identified new potential targets involvedin the acquisition of the phenotype. All together, these datacontribute to a better molecular understanding of themechanisms leading to TG accumulation in response tomitochondrial dysfunction in various pathologies such as MSLor lipodystrophy syndromes.

Materials and MethodsCell culture and experimental models3T3-L1 fibroblasts, purchased from the American Type Culture Collection (ATCC),were grown to confluence in Dulbecco’s modified Eagle’s high glucose (DHG)medium containing 4.5 g/l glucose (Invitrogen) and 10% fetal calf serum (FCS,GibcoBRL). Differentiation of 3T3-L1 cells was initiated at confluence (day 0) byaddition of medium containing an adipogenic cocktail, DHG-L1 medium (DHGcontaining 1.5 g/l NaHCO3), supplemented with 10% FCS, 5 �g/ml insulin (Sigma),300 �M dibutyryl cyclic AMP (db-cAMP, Sigma) and 1 �M dexamethasone(Sigma). After 2 days, cells were transferred to adipocyte growth medium (DHG-L1 containing 10% FCS and 5 �g/ml insulin) and re-fed every two days. To inducea prolonged mitochondrial inhibition, confluent cells (day 0) were incubated inDHG-L1 supplemented with 10% FCS and AA) or chloramphenicol (Sigma). Whenneeded, medium was replaced every other day with DHG-L1 containing the abovesupplements at the same concentration. TG accumulation in cells was monitored byOil Red O staining as described previously (Vankoningsloo et al., 2005). Briefly,cell monolayers were washed with PBS and then fixed for 2 minutes with 0.5 ml3.7% paraformaldehyde (Sigma) in PBS. Oil red O (Sigma) was added for 30minutes at room temperature and cells were washed twice with PBS. TGs werevisualized by light phase contrast microscopy and quantitative determination wasobtained by measuring the absorbance of cell monolayers at 490 nm in aspectrophotometer (Ultramark, Biorad).

Clear cell lysate preparation and nuclear proteins extraction3T3-L1 cells cultured in 75 cm2 flasks or in 12-well plates (both Corning) wererinsed with PBS and lysed in respectively 1 ml or 150 �l of cold lysis buffer (20mM Tris pH 7.4, 150 mM NaCl, 1 mM EDTA, 1% Triton-X100) containing proteaseinhibitors (Roche) and phosphatase inhibitors (1 mM Na3VO4, 5 mM NaF, 10 mMp-nitrophenylphosphate, 10 mM �-glycerophosphate). Clear cell lysates wereprepared and protein contents was determined by the BCA method (Pierce).

Nuclear protein extractions in high-salt buffer were prepared as previouslydescribed (Chen et al., 1996). Briefly, cells seeded in 75 cm2 flasks were incubatedwith 10 nM AA or the pro-adipogenic cocktail for 24 hours. At the end of theincubations, 3T3-L1 cells were incubated on ice for 3 minutes with 10 ml coldhypotonic buffer (HB; 20 mM HEPES, 5 mM NaF, 1 mM Na2MoO4, 0.1 mMEDTA) and harvested in 500 �l HB containing 0.2% NP-40 (Sigma), a proteaseinhibitor cocktail and phosphatase inhibitors. Cell lysates were centrifuged 30seconds at 13,000 rpm in a tabletop centrifuge and sedimented nuclei wereresuspended in 50 �l HB containing 20% glycerol, and protease and phosphataseinhibitors. Extraction was performed for 30 minutes at 4°C by addition of 100 �lHB containing 20% glycerol, 0.8 M NaCl, and protease and phosphatase inhibitors.

Aliquots were frozen at –70°C and protein concentrations were determinedaccording to Bradford (Bradford, 1976).

Western blot analysisSamples corresponding to 20 �g or 40 �g of protein were prepared in LaemmliSDS loading buffer, resolved on 10% SDS-PAGE and transferred to PVDFmembranes (Millipore). For detection of phosphorylated CREB (pCREB),membranes were blocked for 3 hours in TBS-T (20 mM Tris pH 7.4, 150 mM NaCl,0.1% Tween-20) containing 5% bovine serum albumin (BSA, Sigma) and incubatedfor 16 hours (4°C) with a rabbit antibody that recognizes Ser133 pCREB (Upstate)at a 1:1000 dilution. For detection of CREB, GPDmit, PGC-1�, TBP and PARP,membranes were blocked for 3 hours in TBS-T containing 5% dry milk (Gloria)and incubated for 1 hour with either an anti-CREB (Rockland) rabbit antibody at a1:1000 dilution, an anti-GPDmit rabbit antibody at a 1:4000 dilution, an anti-PGC-1� rabbit antibody at a 1:1000 dilution, an anti-TBP (Santa Cruz) rabbit antibodyat a 1:1000 dilution or an anti-PARP (Pharmingen) mouse antibody at a 1:2000dilution. The blots were washed and proteins were visualized with a horseradishperoxidase (HRP)-conjugated anti-rabbit or anti-mouse IgG antibody (Dako) andenhanced chemiluminescence (ECL) system (Pierce). Equal protein loading waschecked by the immunodetection of TBP or PARP.

CREB-DNA-binding assayTo detect the DNA-binding activity of a transcription factor we used the TransAMELISA kit (Active Motif) according to the manufacturer’s recommendations. TheELISA DNA-binding assays are based on multi-well plates coated with anoligonucleotide containing the consensus binding site of the transcription factor ofinterest. The presence of the DNA-bound transcription factor is then detected byspecific antibodies and revealed by colorimetry. The specificity, selectivity and highreproducibility of these assays have been previously demonstrated for nuclearfactor-�B (NF-�B) (Renard et al., 2001), hypoxia-inducible factor-1 (HIF-1)(Mottet et al., 2002) and peroxisome proliferator-activated receptor � (PPAR�)(Vankoningsloo et al., 2005).

Briefly, 10 �g of nuclear proteins were incubated for 2 hours in a 96-well platecoated with a double-stranded oligonucleotide containing the consensus CRE site(TGACGTCA). Total CREB bound to DNA was detected with a rabbit antibodyraised against CREB (Rockland) and presence of the phosphorylated form wasdetermined with an anti-Ser133-pCREB rabbit antibody (Upstate). Colorimetricreaction was then performed with a HRP-conjugated anti-rabbit IgG antibody andabsorbance was measured at 450 nm in a spectrophotometer (Biorad).

Immunofluorescence staining and confocal microscopy3T3-L1 cells were seeded at 40,000 cells/well on coverslips (Assistent) in 24-wellplates; 3 days later cells were incubated or not for 24 hours with the adipogeniccocktail or with 10 nM AA. Cells were washed once with PBS, fixed andpermeabilized with methanol-acetone (1:4, v/v) at –20°C for 10 minutes. Cells werethen washed twice with PBS containing 1% BSA (Sigma) and incubated for 90minutes at room temperature with a specific rabbit antibody raised againstSer133pCREB (Upstate) used at a 1:100 dilution in 1% BSA-PBS. Cells werewashed twice in PBS with 1% BSA, incubated for 60 minutes with an Alexa-Fluor-568-conjugated anti-rabbit IgG antibody (Molecular Probes) at a 1:500 dilution in1% BSA-PBS and processed for fluorescence confocal microscopy (TCS confocalmicroscope Leica).

Transient transfection and luciferase assay3T3-L1 cells, seeded at 80,000 cells/well in 12-well plates 24 hours beforetransfection, were transiently co-transfected for 6 hours with 0.75 �g of a luciferasereporter construct driven by the �-inhibin promoter and 0.25 �g of an expressionvector encoding �-galactosidase (Invitrogen) using SuperFect (5 �l/�g DNA)(Qiagen). The next day, cells were incubated for 24 hours with the adipogeniccocktail or 10 nM AA, or for 48 hours with 1 mM db-cAMP diluted in DHG-L1medium. Cells were then harvested, luciferase activity was measured in clearedlysates using the commercial Reporter Assay System (Promega) and results werenormalized against �-galactosidase activity.

To determine the putative role of CREB in the accumulation of TG, cells wereseeded in 24-well plates and transiently transfected for 6 hours with 1 �g/well ofplasmids encoding M1-CREB and K-CREB, or EGFP (Clontech) as a negativecontrol, using SuperFect (5 �l/�g DNA). The next day, cells were induced todifferentiate with the adipogenic cocktail or incubated with 10 nM of AA for 8 daysbefore neutral lipid content was determined by Oil Red O staining.

Low-density DNA microarrayArray designWe developed an ‘ADIPOCHIP’, a low-density DNA array allowing geneexpression analysis of 89 murine genes related to adipocyte differentiation incollaboration with Eppendorf (Germany) (see supplementary material Table S1 forthe list of genes, and Fig. S1 for the array design). Results using reliable andvalidated arrays developed by Eppendorf were reported elsewhere (de Longuevilleet al., 2002; de Longueville et al., 2003; de Magalhaes et al., 2004; Debacq-

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Chainiaux et al., 2005). The method is based on a system with two arrays (a controland a test) on a glass slide and three identical sub-arrays (triplicate spots) per array.Except for C/EBP� and C/EBP�, no cross-hybridization was detected. Thereliability of hybridizations and experimental data was evaluated using severalpositive and negative hybridization controls as well as detection controls spotted onthe microarray.

RNA reverse transcription and cDNA hybridization3T3-L1 cells cultured in 75 cm2 flasks were incubated for 2, 4, 6 or 8 days with 10nM AA, and the adipogenic cocktail, or for 2 days with 1 mM db-cAMP. In someexperiments, cells were transfected with 100 nM CREB-specific siRNA beforebeing incubated for 4 days with 10 nM AA. At the end of the incubations, totalRNA was extracted with the Total RNAgents extraction kit (Promega), quality waschecked with a bioanalyzer (Agilent Technologies) and 20 �g were used for reversetranscription in the presence of biotin-11-dCTP (Perkin-Elmer) and Superscript IIreverse transcriptase (Invitrogen), as described previously (de Longueville et al.,2002). Three synthetic poly(A)-tailed RNA standards (Eppendorf) were added at 10ng, 1 ng or 0.1 ng per reaction) into the purified RNA to quantify the experimentalvariation introduced during labeling and analysis. For the kinetic profiles of geneexpression, three independent experiments were performed in triplicate, providinghybridization on nine arrays that were carried out as described by the manufacturerand reported previously (de Longueville et al., 2002). Detection was performed witha cyanin 3-conjugated IgG anti-biotin (Jackson ImmunoResearch Laboratories).Fluorescence of hybridized arrays was scanned with the Packard ScanArray (Perkin-Elmer) at a resolution of 10 �m. To maximize the dynamic range of detection, thesame arrays were scanned with different photomultiplier gains to quantify both thehigh-copy and low-copy expression of genes. The scanned 16-bit images wereimported into ImaGene 4.1 software (BioDiscovery) to quantify signal intensities.The fluorescence intensity of each DNA spot (average intensity of each pixel presentwithin the spot) was calculated by subtracting local mean background. A signal wasonly accepted when the average intensity after background subtraction was at least2.5� higher than the local background around the spot. Intensity values of triplicatefluorescent signals were averaged and used to calculate the intensity ratio ofreference and test.

Data normalizationThe data were normalized in two steps. First, a correction was applied using a factorcalculated from the intensity ratios of internal standards in the reference and testsamples. The presence of the internal standard probes at different locations of thearray allowed quantification of the local background and evaluation of the arrayhomogeneity that is taken into account in the normalization. Furthermore, toconsider the purity and quality of the mRNA, a second normalization step wasperformed based on the average of fluorescence intensities measured for a set of 9-16 housekeeping genes. The variance of the normalized set of housekeeping geneswas used to generate an estimate of expected variance, leading to a predictedconfidence interval for testing the significance of the ratios obtained. Ratios outsidethe 95% confidence interval were considered to be statistically significant, asdetermined by ANOVA (de Longueville et al., 2002; de Magalhaes et al., 2004).

RT-PCRAfter various treatments, total RNA was extracted using the Total RNAgentextraction kit (Promega). mRNA contained in 5 �g total RNA was reversetranscribed using SuperScript II reverse transcriptase (Invitrogen) according to themanufacturer’s instructions. Forward and reverse primers, for C/EBP� (FP:GGTTTCGGGACTTGATGCAA, RP: GCAGGAACATCTTTAAGGTGAT-TACTC); C/EBP� (FP: CCGCCCGAATCGCTAGT, RP: GCAGTCCAGTGCC-CAAGCT); Clic4 (FP: AGAGCCCACAGCAAGCATTCT, RP: ATCAGCCG-CATGGAGACATC); CPT-2 (FP: CCTGATGGCTTTGGCATTG, RP:GGGCATTGCGTCCTGAGTA); FAS (FP: GTGAAGAAGTGTCTGGACTGTGT-CAT, RP: TCGCTCACGTGCAGTTTAATTG); GPDmit (FP: GCAGCTGAT-GAGCGCAGTT, RP: TCCAAGTTCTCCTCGGCAGTT); IL-6 (FP: CCTAGT-GCGTTATGCCTAAGCA, RP: TCGTAGAGAACAACATAAGTCAGATACCT);leptin (FP: GATCCCACGTGCCACAGTCT, RP: GGAACAAGCCATAGTG-CAAGGT); PGC-1� (FP: CGGATTGCCCTCATTTGATG, RP: GAGGAAG-GACTGGCCTCGTT) and TBP (FP: CAGTTACAGGTGGCAGCATGA, RP:TAGTGCTGCAGGGTGATTTCAG) were designed using the Primer Express 1.5software (Applied Biosystem). Amplification reaction assays contained 1� SYBRGreen PCR Mastermix (Applied Biosystem) and primers (Eurogentech) at theoptimal concentrations. A hot start at 95° C for 5 minutes was followed by 40 cyclesat 95°C for 15 seconds each, terminated at 65°C for 1 minute, using an ABI PRISM7000 SDS thermal cycler (Applied Biosystem). TBP was used as the reference genefor normalization and relative mRNA steady-state level quantification. Meltingcurves were generated after amplification and data were analyzed using the thermal-cycler software. Each sample was tested in duplicate.

Gene silencing experimentssiRNA transfection experiments were performed with double-stranded RNAdesigned and synthetized by Eurogentec. Out of three siRNA tested, a CREB-

specific siRNA sense-orientation strand with the following sequence (5-UACAGCUGGCUAACAAUGGdTdT-3) was selected. To investigate the potentialcontribution of GPDmit and PGC-1�, some experiments were performed with aGPDmit-specific siRNA (Eurogentec: 5-UCAGCUCCGUUGCCUAUCAdTdT-3)or with a smart-pool of four specific siRNA for PGC-1� (Dharmacon). Cells weretransfected with the siRNA delivery reagent JetSITM (Eurogentec) at 3 �l/�g ofsiRNA according to the manufacturer’s instructions. Transfection efficiency in cellsplated on coverslips was determined with fluorescein isothiocyanate (FITC)-labeledsiRNA and evaluated by cell counting using a confocal microscope (Leica) to be90-95% after 24 and 48 hours.

Efficiency of RNA interference on CREB, GPDmit and PGC-1� expression wasdetermined by either western blot analysis or by RT-PCR with specific primers. 3T3-L1 cells were seeded in 6-well plates at 200,000 cells/well 24 hours before beingtransfected for 4 hours by using JetSI with 10, 20, 50 or 100 nM CREB siRNA,100 nM GPDmit siRNA, or 100 nM siRNA PGC-1�. Medium was replaced andgene silencing was verified 48 hours post-transfection. The effect of the disruptingthe expression of CREB, GPDmit or PGC-1� by siRNA on AA-induced TGaccumulation was analyzed as followed: 3T3-L1 cells (70-80% confluent) seededin 24-well plates were treated or not for 5 days with 10 nM AA and then transientlytransfected with 100 nM siRNA or an equivalent amount of JetSI alone. Aftertransfection, cells were incubated for 3 and 8 days with or without 10 nM AA, andTGs were stained with Oil Red O. To identify genes potentially regulated by CREBthat might play a role in the cellular accumulation of TG in response to AA, CREBexpression was disrupted with siRNA. 3T3-L1 cells were plated in 75 cm2 flasks at50% confluence 3 days before transfection in the presence of 100 nM siRNA orwere incubated with JetSI. After 24 hours, cells were incubated for 4 days with 10nM AA before extraction of total RNA, reverse transcription of mRNA, biotin-labeling of cDNA and hybridization on microarrays.

T.A. is a research associate of the FNRS (Fonds National de laRecherche Scientifique, Belgium). S.V. is a recipient of a doctoralfellowship from Fonds pour la Recherche dans l’Industrie etl’Agriculture (FRIA). We are very grateful to Michael E. Greenberg(Harvard Medical School, Boston, MA, USA) for the constructsencoding dominant negative forms of CREB (K-CREB and M1-CREB). We also want to thank Joachim M. Weitzel(Universitätsklinikum, Hamburg-Eppendorf, Germany) for the anti-GPDmit antibody and Daniel P. Kelly (Center for CardiovascularResearch, Washington University School of Medicine, St Louis, MI,USA) for the PGC-1� antibody. This text presents results of theBelgian Programme on Interuniversity Poles of Attraction (PAI5/02)initiated by the Belgian State, Prime Minister’s Office Science PolicyProgramming. We also thank the French speaking communitygovernement for funding through an ARC (Action de RechercheConcertée). The scientific responsibility is assumed by the authors.

ReferencesAmuthan, G., Biswas, G., Ananadatheerthavarada, H. K., Vijayasarathy, C.,

Shephard, H. M. and Avadhani, N. G. (2002). Mitochondrial stress-induced calciumsignaling, phenotypic changes and invasive behavior in human lung carcinoma A549cells. Oncogene 21, 7839-7849.

Arnould, T., Vankoningsloo, S., Renard, P., Houbion, A., Ninane, N., Demazy, C.,Remacle, J. and Raes, M. (2002). CREB activation induced by mitochondrialdysfunction is a new signaling pathway that impairs cell proliferation. EMBO J. 21,53-63.

Beitner-Johnson, D. and Millhorn, D. E. (1998). Hypoxia induces phosphorylation ofthe cyclic AMP response element-binding protein by a novel signaling mechanism. J.Biol. Chem. 273, 19834-19839.

Beitner-Johnson, D., Rust, R. T., Hsieh, T. and Millhorn, D. E. (2000). Regulation ofCREB by moderate hypoxia in PC12 cells. Adv. Exp. Med. Biol. 475, 143-152.

Berkovic, S. F., Andermann, F., Shoubridge, E. A., Carpenter, S., Robitaille, Y.,Andermann, E., Melmed, C. and Karpati, G. (1991). Mitochondrial dysfunction inmultiple symmetrical lipomatosis. Ann. Neurol. 29, 566-569.

Biswas, G., Adebanjo, O. A., Freedman, B. D., Anandatheerthavarada, H. K.,Vijayasarathy, C., Zaidi, M., Kotlikoff, M. and Avadhani, N. G. (1999). RetrogradeCa2+ signaling in C2C12 skeletal myocytes in response to mitochondrial genetic andmetabolic stress: a novel mode of inter- organelle crosstalk. EMBO J. 18, 522-533.

Biswas, G., Anandatheerthavarada, H. K. and Avadhani, N. G. (2005). Mechanismof mitochondrial stress-induced resistance to apoptosis in mitochondrial DNA-depletedC2C12 myocytes. Cell Death Differ. 12, 266-278.

Boissel, J. P., Bros, M., Schrock, A., Godtel-Armbrust, U. and Forstermann, U.(2004). Cyclic AMP-mediated upregulation of the expression of neuronal NO synthasein human A673 neuroepithelioma cells results in a decrease in the level of bioactiveNO production: analysis of the signaling mechanisms that are involved. Biochemistry43, 7197-7206.

Bradford, M. M. (1976). A rapid and sensitive method for the quantitation of microgram

Jour

nal o

f Cel

l Sci

ence

1281Mitochondrial dysfunction triggers triglyceride accumulation

quantities of protein utilizing the principle of protein-dye binding. Anal. Biochem. 72,248-254.

Brinkman, K., Smeitink, J. A., Romijn, J. A. and Reiss, P. (1999). Mitochondrialtoxicity induced by nucleoside-analogue reverse-transcriptase inhibitors is a key factorin the pathogenesis of antiretroviral-therapy-related lipodystrophy. Lancet 354, 1112-1115.

Brown, L. J., Koza, R. A., Everett, C., Reitman, M. L., Marshall, L., Fahien, L. A.,Kozak, L. P. and MacDonald, M. J. (2002). Normal thyroid thermogenesis butreduced viability and adiposity in mice lacking the mitochondrial glycerol phosphatedehydrogenase. J. Biol. Chem. 277, 32892-32898.

Burton, G. R., Guan, Y., Nagarajan, R. and McGehee, R. E., Jr (2002). Microarrayanalysis of gene expression during early adipocyte differentiation. Gene 293, 21-31.

Burton, G. R., Nagarajan, R., Peterson, C. A. and McGehee, R. E., Jr (2004).Microarray analysis of differentiation-specific gene expression during 3T3-L1adipogenesis. Gene 329, 167-185.

Butow, R. A. and Avadhani, N. G. (2004). Mitochondrial signaling: the retrograderesponse. Mol. Cell 14, 1-15.

Buttgereit, F. and Brand, M. D. (1995). A hierarchy of ATP-consuming processes inmammalian cells. Biochem. J. 312, 163-167.

Cao, W., Daniel, K. W., Robidoux, J., Puigserver, P., Medvedev, A. V., Bai, X.,Floering, L. M., Spiegelman, B. M. and Collins, S. (2004). p38 mitogen-activatedprotein kinase is the central regulator of cyclic AMP-dependent transcription of thebrown fat uncoupling protein 1 gene. Mol. Cell. Biol. 24, 3057-3067.

Carriere, A., Carmona, M. C., Fernandez, Y., Rigoulet, M., Wenger, R. H., Penicaud,L. and Casteilla, L. (2004). Mitochondrial reactive oxygen species control thetranscription factor CHOP-10/GADD153 and adipocyte differentiation: A mechanismfor hypoxia-dependent effect. J. Biol. Chem. 279, 40462-40469.

Chen, Y., Takeshita, A., Ozaki, K., Kitano, S. and Hanazawa, S. (1996).Transcriptional regulation by transforming growth factor beta of the expression ofretinoic acid and retinoid X receptor genes in osteoblastic cells is mediated throughAP-1. J. Biol. Chem. 271, 31602-31606.

Chio, C. C., Chang, Y. H., Hsu, Y. W., Chi, K. H. and Lin, W. W. (2004). PKA-dependent activation of PKC, p38 MAPK and IKK in macrophage: implication in theinduction of inducible nitric oxide synthase and interleukin-6 by dibutyryl cAMP. CellSignal. 16, 565-575.

Cohen, A. W., Razani, B., Schubert, W., Williams, T. M., Wang, X. B., Iyengar, P.,Brasaemle, D. L., Scherer, P. E. and Lisanti, M. P. (2004). Role of caveolin-1 in themodulation of lipolysis and lipid droplet formation. Diabetes 53, 1261-1270.

Czubryt, M. P., McAnally, J., Fishman, G. I. and Olson, E. N. (2003). Regulation ofperoxisome proliferator-activated receptor gamma coactivator 1 alpha (PGC-1 alpha)and mitochondrial function by MEF2 and HDAC5. Proc. Natl. Acad. Sci. USA 100,1711-1716.

Darlington, G. J., Ross, S. E. and MacDougald, O. A. (1998). The role of C/EBP genesin adipocyte differentiation. J. Biol. Chem. 273, 30057-30060.

de Longueville, F., Surry, D., Meneses-Lorente, G., Bertholet, V., Talbot, V., Evrard,S., Chandelier, N., Pike, A., Worboys, P., Rasson, J. P. et al. (2002). Gene expressionprofiling of drug metabolism and toxicology markers using a low-density DNAmicroarray. Biochem. Pharmacol. 64, 137-149.

de Longueville, F., Atienzar, F. A., Marcq, L., Dufrane, S., Evrard, S., Wouters, L.,Leroux, F., Bertholet, V., Gerin, B., Whomsley, R. et al. (2003). Use of a low-densitymicroarray for studying gene expression patterns induced by hepatotoxicants onprimary cultures. of rat hepatocytes. Toxicol. Sci. 75, 378-392.

de Magalhaes, J. P., Chainiaux, F., de Longueville, F., Mainfroid, V., Migeot, V.,Marcq, L., Remacle, J., Salmon, M. and Toussaint, O. (2004). Gene expression andregulation in H2O2-induced premature senescence of human foreskin fibroblastsexpressing or not telomerase. Exp. Gerontol. 39, 1379-1389.

Debacq-Chainiaux, F., Borlon, C., Pascal, T., Royer, V., Eliaers, F., Ninane, N.,Carrard, G., Friguet, B., de Longueville, F., Boffe, S. et al. (2005). Repeatedexposure of human skin fibroblasts to UVB at subcytotoxic level triggers prematuresenescence through the TGF-beta1 signaling pathway. J. Cell Sci. 118, 743-758.

Della Fazia, M. A., Servillo, G. and Sassone-Corsi, P. (1997). Cyclic AMP signallingand cellular proliferation: regulation of CREB and CREM. FEBS Lett. 410, 22-24.

Dresner, A., Laurent, D., Marcucci, M., Griffin, M. E., Dufour, S., Cline, G. W.,Slezak, L. A., Andersen, D. K., Hundal, R. S., Rothman, D. L. et al. (1999). Effectsof free fatty acids on glucose transport and IRS-1-associated phosphatidylinositol 3-kinase activity. J. Clin. Invest. 103, 253-259.

Gregoire, F. M., Smas, C. M. and Sul, H. S. (1998). Understanding adipocytedifferentiation. Physiol. Rev. 78, 783-809.

Gulick, T., Cresci, S., Caira, T., Moore, D. D. and Kelly, D. P. (1994). The peroxisomeproliferator-activated receptor regulates mitochondrial fatty acid oxidative enzymegene expression. Proc. Natl. Acad. Sci. USA 91, 11012-11016.

Guo, X. and Liao, K. (2000). Analysis of gene expression profile during 3T3-L1preadipocyte differentiation. Gene 251, 45-53.

Hagiwara, M., Alberts, A., Brindle, P., Meinkoth, J., Feramisco, J., Deng, T., Karin,M., Shenolikar, S. and Montminy, M. (1992). Transcriptional attenuation followingcAMP induction requires PP-1-mediated dephosphorylation of CREB. Cell 70, 105-113.

Hajra, A. K., Larkins, L. K., Das, A. K., Hemati, N., Erickson, R. L. andMacDougald, O. A. (2000). Induction of the peroxisomal glycerolipid-synthesizingenzymes during differentiation of 3T3-L1 adipocytes. Role in triacylglycerol synthesis.J. Biol. Chem. 275, 9441-9446.

Herzig, S., Long, F., Jhala, U. S., Hedrick, S., Quinn, R., Bauer, A., Rudolph, D.,Schutz, G., Yoon, C., Puigserver, P. et al. (2001). CREB regulates hepaticgluconeogenesis through the coactivator PGC-1. Nature 413, 179-183.

Herzig, S., Hedrick, S., Morantte i Koo, S. H., Galimi, F. and Montminy, M. (2003).CREB controls hepatic lipid metabolism through nuclear hormone receptor PPAR-gamma. Nature 426, 190-193.

Huss, J. M., Levy, F. H. and Kelly, D. P. (2001). Hypoxia inhibits the peroxisomeproliferator-activated receptor alpha/retinoid X receptor gene regulatory pathway incardiac myocytes: a mechanism for O2-dependent modulation of mitochondrial fattyacid oxidation. J. Biol. Chem. 276, 27605-27612.

Johannessen, M., Delghandi, M. P. and Moens, U. (2004). What turns CREB on? CellSignal. 16, 1211-1227.

Kakuda, T. N. (2000). Pharmacology of nucleoside and nucleotide reverse transcriptaseinhibitor-induced mitochondrial toxicity. Clin. Ther. 22, 685-708.

Kasturi, R. and Joshi, V. C. (1982). Hormonal regulation of stearoyl coenzyme Adesaturase activity and lipogenesis during adipose conversion of 3T3-L1 cells. J. Biol.Chem. 257, 12224-12230.

Klopstock, T., Naumann, M., Seibel, P., Shalke, B., Reiners, K. and Reichmann, H.(1997). Mitochondrial DNA mutations in multiple symmetric lipomatosis. Mol. CellBiochem. 174, 271-275.

Kratchmarova i Kalume, D. E., Blagoev, B., Scherer, P. E., Podtelejnikov, A. V.,Molina, H., Bickel, P. E., Andersen, J. S., Fernandez, M. M., Bunkenborg, J. et al.(2002). A proteomic approach for identification of secreted proteins during thedifferentiation of 3T3-L1 preadipocytes to adipocytes. Mol. Cell Proteomics 1, 213-222.

Lazar, M. A. (2005). How obesity causes diabetes: not a tall tale. Science 307, 373-375.Lee, K., Villena, J. A., Moon, Y. S., Kim, K. H., Lee, S., Kang, C. and Sul, H. S.

(2003). Inhibition of adipogenesis and development of glucose intolerance by solublepreadipocyte factor-1 (Pref-1). J. Clin. Invest. 111, 453-461.

Liao, X. S., Small, W. C., Srere, P. A. and Butow, R. A. (1991). Intramitochondrialfunctions regulate nonmitochondrial citrate synthase (CIT2) expression inSaccharomyces cerevisiae. Mol. Cell. Biol. 11, 38-46.

Lin, E. C. (1977). Glycerol utilization and its regulation in mammals. Annu. Rev.Biochem. 46, 765-795.

Liu, Z. and Butow, R. A. (1999). A transcriptional switch in the expression of yeasttricarboxylic acid cycle genes in response to a reduction or loss of respiratory function.Mol. Cell. Biol. 19, 6720-6728.

Louet, J. F., Hayhurst, G., Gonzalez, F. J., Girard, J. and Decaux, J. F. (2002). Thecoactivator PGC-1 is involved in the regulation of the liver carnitinepalmitoyltransferase I gene expression by cAMP in combination with HNF4 alpha andcAMP-response element-binding protein (CREB). J. Biol. Chem. 277, 37991-8000.

Lowell, B. B. and Shulman, G. I. (2005). Mitochondrial dysfunction and type 2 diabetes.Science 307, 384-387.

MacDougald, O. A. and Lane, M. D. (1995). Transcriptional regulation of geneexpression during adipocyte differentiation. Annu. Rev. Biochem. 64, 345-373.

Mancuso, M., Filosto, M., Mootha, V. K., Rocchi, A., Pistolesi, S., Murri, L.,DiMauro, S. and Siciliano, G. (2004). A novel mitochondrial tRNAPhe mutationcauses MERRF syndrome. Neurology 62, 2119-2121.

Melone, M. A., Tessa, A., Petrini, S., Lus, G., Sampaolo, S., di Fede, G., Santorelli,F. M. and Cotrufo, R. (2004). Revelation of a new mitochondrial DNA mutation(G12147A) in a MELAS/MERFF phenotype. Arch. Neurol. 61, 269-272.

Miyazaki, M., Kim, Y. C. and Ntambi, J. M. (2001). A lipogenic diet in mice with adisruption of the stearoyl-CoA desaturase 1 gene reveals a stringent requirement ofendogenous monounsaturated fatty acids for triglyceride synthesis. J. Lipid Res. 42,1018-1024.

Mongini, T., Doriguzzi, C., Chiado-Piat, L., Silvestri, G., Servidei, S. and Palmucci,L. (2002). MERRF/MELAS overlap syndrome in a family with A3243G mtDNAmutation. Clin. Neuropathol. 21, 72-76.

Mootha, V. K., Lindgren, C. M., Eriksson, K. F., Subramanian, A., Sihag, S., Lehar,J., Puigserver, P., Carlsson, E., Ridderstrale, M., Laurila, E. et al. (2003). PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinatelydownregulated in human diabetes. Nat. Genet. 34, 267-273.

Mottet, D., Michel, G., Renard, P., Ninane, N., Raes, M. and Michiels, C. (2002). ERKand calcium in activation of HIF-1. Ann. New York Acad. Sci. 973, 448-453.

Munoz-Malaga, A., Bautista, J., Salazar, J. A., Aguilera i Garcia, R., Chinchon iSegura, M. D., Campos, Y. and Arenas, J. (2000). Lipomatosis, proximal myopathy,and the mitochondrial 8344 mutation. A lipid storage myopathy? Muscle Nerve 23,538-542.

Naumann, M., Kiefer, R., Toyka, K. V., Sommer, C., Seibel, P. and Reichmann, H.(1997). Mitochondrial dysfunction with myoclonus epilepsy and ragged-red fiberspoint mutation in nerve, muscle, and adipose tissue of a patient with multiplesymmetric lipomatosis. Muscle Nerve 20, 833-839.

Nitsch, D., Boshart, M. and Schutz, G. (1993). Activation of the tyrosineaminotransferase gene is dependent on synergy between liver-specific and hormone-responsive elements. Proc. Natl. Acad. Sci. USA 90, 5479-5483.

Ntambi, J. M., Buhrow, S. A., Kaestner, K. H., Christy, R. J., Sibley, E., Kelly, T. J.,Jr and Lane, M. D. (1988). Differentiation-induced gene expression in 3T3-L1preadipocytes. Characterization of a differentially expressed gene encoding stearoyl-CoA desaturase. J. Biol. Chem. 263, 17291-17300.

Ntambi, J. M., Miyazaki, M., Stoehr, J. P., Lan, H., Kendziorski, C. M., Yandell, B.S., Song, Y., Cohen, P., Friedman, J. M. and Attie, A. D. (2002). Loss of stearoyl-CoA desaturase-1 function protects mice against adiposity. Proc. Natl. Acad. Sci. USA99, 11482-11486.

Pei, L., Dodson, R., Schoderbek, W. E., Maurer, R. A. and Mayo, K. E. (1991).Regulation of the alpha inhibin gene by cyclic adenosine 3,5-monophosphate aftertransfection into rat granulosa cells. Mol. Endocrinol. 5, 521-534.

Jour

nal o

f Cel

l Sci

ence

1282 Journal of Cell Science 119 (7)

Petersen, K. F., Oral, E. A., Dufour, S., Befroy, D., Ariyan, C., Yu, C., Cline, G. W.,DePaoli, A. M., Taylor, S. I., Gorden, P. et al. (2002). Leptin reverses insulinresistance and hepatic steatosis in patients with severe lipodystrophy. J. Clin. Invest.109, 1345-1350.

Petersen, K. F., Befroy, D., Dufour, S., Dziura, J., Ariyan, C., Rothman, D. L.,DiPietro, L., Cline, G. W. and Shulman, G. I. (2003). Mitochondrial dysfunction inthe elderly: possible role in insulin resistance. Science 300, 1140-1142.

Petersen, K. F., Dufour, S., Befroy, D., Garcia, R. and Shulman, G. I. (2004). Impairedmitochondrial activity in the insulin-resistant offspring of patients with type 2 diabetes.N. Engl. J. Med. 350, 664-671.

Renard, P., Ernest, I., Houbion, A., Art, M., Le Calvez, H., Raes, M. and Remacle,J. (2001). Development of a sensitive multi-well colorimetric assay for activeNFkappaB. Nucleic Acids Res. 29, E21.

Reusch, J. E. and Klemm, D. J. (2002). Inhibition of cAMP-response element-bindingprotein activity decreases protein kinase B/Akt expression in 3T3-L1 adipocytes andinduces apoptosis. J. Biol. Chem. 277, 1426-1432.

Reusch, J. E., Colton, L. A. and Klemm, D. J. (2000). CREB activation inducesadipogenesis in 3T3-L1 cells. Mol. Cell. Biol. 20, 1008-1020.

Roesler, W. J. (2000). What is a cAMP response unit? Mol. Cell Endocrinol. 162, 1-7.Ron, D. and Habener, J. F. (1992). CHOP, a novel developmentally regulated nuclear

protein that dimerizes with transcription factors C/EBP and LAP and functions as adominant-negative inhibitor of gene transcription. Genes Dev. 6, 439-453.

Rosen, E. D. and Spiegelman, B. M. (2000). Molecular regulation of adipogenesis. Annu.Rev. Cell Dev Biol. 16, 145-171.

Ross, S. E., Erickson, R. L., Gerin, I., DeRose, P. M., Bajnok, L., Longo, K. A., Misek,D. E., Kuick, R., Hanash, S. M., Atkins, K. B. et al. (2002). Microarray analyses duringadipogenesis: understanding the effects of Wnt signaling on adipogenesis and the rolesof liver X receptor alpha in adipocyte metabolism. Mol. Cell. Biol. 22, 5989-5999.

Rossmanith, W., Raffelsberger, T., Roka, J., Kornek, B., Feucht, M. and Bittner, R.E. (2003). The expanding mutational spectrum of MERRF substitution G8361A in themitochondrial tRNALys gene. Ann. Neurol. 54, 820-823.

Scarpulla, R. C. (2002). Nuclear activators and coactivators in mammalian mitochondrialbiogenesis. Biochim. Biophys. Acta 1576, 1-14.

Scott, R., Bourtchuladze, R., Gossweiler, S., Dubnau, J. and Tully, T. (2002). CREBand the discovery of cognitive enhancers. J. Mol. Neurosci. 19, 171-177.

Shaywitz, A. J. and Greenberg, M. E. (1999). CREB: a stimulus-induced transcriptionfactor activated by a diverse array of extracellular signals. Annu. Rev. Biochem. 68,821-861.

Shoffner, J. M., Lott, M. T., Lezza, A. M., Seibel, P., Ballinger, S. W. and Wallace,D. C. (1990). Myoclonic epilepsy and ragged-red fiber disease (MERRF) is associatedwith a mitochondrial DNA tRNA(Lys) mutation. Cell 61, 931-937.

Song, H., Shojima, N., Sakoda, H., Ogihara, T., Fujishiro, M., Katagiri, H., Anai, M.,

Onishi, Y., Ono, H., Inukai, K. et al. (2002). Resistin is regulated by C/EBPs, PPARs,and signal-transducing molecules. Biochem. Biophys. Res. Commun. 299, 291-298.

Tong, Q., Tsai, J., Tan, G., Dalgin, G. and Hotamisligil, G. S. (2005). Interactionbetween GATA and the C/EBP family of transcription factors is critical in GATA-mediated suppression of adipocyte differentiation. Mol. Cell. Biol. 25, 706-715.

Vankoningsloo, S., Piens, M., Lecocq, C., Gilson, A., De Pauw, A., Renard, P.,Demazy, C., Houbion, A., Raes, M. and Arnould, T. (2005). Mitochondrialdysfunction induces triglyceride accumulation in 3T3-L1 cells: role of fatty acid{beta}-oxidation and glucose. J. Lipid Res. 46, 1133-1149.

Vega, R. B., Huss, J. M. and Kelly, D. P. (2000). The coactivator PGC-1 cooperates withperoxisome proliferator-activated receptor alpha in transcriptional control of nucleargenes encoding mitochondrial fatty acid oxidation enzymes. Mol. Cell. Biol. 20, 1868-1876.

Wadzinski, B. E., Wheat, W. H., Jaspers, S., Peruski, L. F., Jr, Lickteig, R. L.,Johnson, G. L. and Klemm, D. J. (1993). Nuclear protein phosphatase 2Adephosphorylates protein kinase A-phosphorylated CREB and regulates CREBtranscriptional stimulation. Mol. Cell. Biol. 13, 2822-2834.

Wang, L., Liu, J., Saha, P., Huang, J., Chan, L., Spiegelman, B. and Moore, D. D.(2005). The orphan nuclear receptor SHP regulates PGC-1alpha expression and energyproduction in brown adipocytes. Cell Metab. 2, 227-238.

Welsh, G. I., Griffiths, M. R., Webster, K. J., Page, M. J. and Tavare, J. M. (2004).Proteome analysis of adipogenesis. Proteomics 4, 1042-1051.

Wieser, W. and Krumschnabel, G. (2001). Hierarchies of ATP-consuming processes:direct compared with indirect measurements, and comparative aspects. Biochem. J.355, 389-395.

Wu, Z., Puigserver, P., Andersson, U., Zhang, C., Adelmant, G., Mootha, V., Troy,A., Cinti, S., Lowell, B., Scarpulla, R. C. et al. (1999). Mechanisms controllingmitochondrial biogenesis and respiration through the thermogenic coactivator PGC-1.Cell 98, 115-124.

Zancanaro, C., Sbarbati, A., Morroni, M., Carraro, R., Cigolini, M., Enzi, G. andCinti, S. (1990). Multiple symmetric lipomatosis. Ultrastructural investigation of thetissue and preadipocytes in primary culture. Lab. Invest. 63, 253-258.

Zhang, J. W., Klemm, D. J., Vinson, C. and Lane, M. D. (2004). Role of CREB intranscriptional regulation of CCAAT/enhancer-binding protein beta gene duringadipogenesis. J. Biol. Chem. 279, 4471-4478.

Zhou, A., Scoggin, S., Gaynor, R. B. and Williams, N. S. (2003). Identification of NF-kappa B-regulated genes induced by TNFalpha utilizing expression profiling and RNAinterference. Oncogene 22, 2054-2064.

Zhou, X. Y., Shibusawa, N., Naik, K., Porras, D., Temple, K., Ou, H., Kaihara, K.,Roe, M. W., Brady, M. J. and Wondisford, F. E. (2004). Insulin regulation of hepaticgluconeogenesis through phosphorylation of CREB-binding protein. Nat. Med. 10,633-637.

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