Cell-state dependent regulation of PPARγsignaling by ZBTB9 in adipocytes

Cell-state dependent regulation of PPARγ signaling by ZBTB9 in adipocytes | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Cell-state dependent regulation of PPAR γ signaling by ZBTB9 in adipocytes Xuan Xu , Alyssa Charrier , Sunny Congrove , View ORCID Profile David A. Buchner doi: https://doi.org/10.1101/2024.03.04.583402 Xuan Xu 1 Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine , Cleveland, OH, 44106, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Alyssa Charrier 1 Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine , Cleveland, OH, 44106, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Sunny Congrove 2 Department of Biochemistry, Case Western Reserve University School of Medicine , Cleveland, OH, 44106, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site David A. Buchner 1 Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine , Cleveland, OH, 44106, USA 2 Department of Biochemistry, Case Western Reserve University School of Medicine , Cleveland, OH, 44106, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for David A. Buchner For correspondence: dab22{at}case.edu Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract Adipocytes play a critical role in metabolic homeostasis. Peroxisome proliferator-activated receptor- γ (PPAR γ ) is a nuclear hormone receptor that is a master regulator of adipocyte differentiation and function. ZBTB9 was predicted to interact with PPAR γ based on large-scale protein interaction experiments. In addition, GWAS studies in the type 2 diabetes (T2D) Knowledge Portal revealed associations between Z btb9 and both BMI and T2D risk. Here we show that ZBTB9 positively regulates PPAR γ activity in mature adipocytes. Surprisingly Z btb9 knockdown (KD) also increased adipogenesis in 3T3-L1 cells and human preadipocytes. E2F activity was increased and E2F downstream target genes were upregulated in Zbtb9 -KD preadipocytes. Accordingly, RB phosphorylation, which regulates E2F activity, was enhanced in Zbtb9 -KD preadipocytes. Critically, an E2F1 inhibitor blocked the effects of Zbtb9 deficiency on adipogenic gene expression and lipid accumulation. Collectively, these results demonstrate that Zbtb9 inhibits adipogenesis as a negative regulator of Pparg expression via altered RB-E2F1 signaling. Our findings reveal complex cell-state dependent roles of ZBTB9 in adipocytes, identifying a new molecule that regulates adipogenesis and adipocyte biology as both a positive and negative regulator of PPAR γ signaling depending on the cellular context, and thus may be important in the pathogenesis and treatment of obesity and T2D. Introduction Obesity is a one of the greatest health challenges facing our world today. Comorbidities include type 2 diabetes (T2D), cardiovascular disease, and certain types of cancer which collectively increase the risk of premature mortality ( 1 ). Treatments for these metabolic diseases include surgery, lifestyle modifications, and therapeutics such as the recently developed incretin mimetics ( 2 ). However, despite tremendous recent successes in the treatment of obesity and T2D, there remain many individuals for which safely maintaining a healthy body weight and long-term glucose homeostasis remains challenging such that new therapeutic approaches are a major unmet clinical need ( 3 , 4 ). Adipose tissue is the body’s primary site of fat storage and has a vital role for integrating and communicating metabolic signals. Adipose tissue expands when energy intake exceeds energy expenditure, storing the excess nutrients in lipid droplets as inert triacylglycerol (TAG) and thereby maintaining metabolic homeostasis ( 5 ). Adipocytes within adipose tissues store excess energy via hyperplasia, an increase in the number of adipocytes, and hypertrophy, an increase in the size of adipocytes ( 6 ). Discovering the mechanisms regulating adipocyte function and adipocyte differentiation is central for understanding the pathophysiology of obesity and its related metabolic diseases and identifying new therapeutic opportunities ( 7 – 9 ). Peroxisome proliferator-activated receptor γ (PPAR γ ) is a member of the nuclear hormone receptor family of ligand-inducible transcription factors ( 10 ). PPAR γ is a master transcriptional regulator of adipogenesis and also a key regulator of gene expression in mature adipocytes ( 11 , 12 ). Thiazolidinedione (TZDs), synthetic ligands of PPAR γ , are activators of PPAR γ with robust insulin-sensitizing activities ( 13 ). Although treatment with these compounds causes weight gain and an array of additional safety issues (e.g., cardiovascular risk and fluid retention), TZDs were once widely used to treat T2D ( 14 ). A more complete understanding of PPAR γ activation and signaling will potentially lead to new and improved therapies for T2D. Control of PPAR γ transcriptional activity depends on multi-protein complexes containing dimerization partners and other co-regulators, which each have their own physiological effects on insulin resistance and metabolic dysfunction ( 15 – 17 ). PPAR-gamma coactivator-1 α (PGC-1 α ) is a PPAR γ coactivator which serves as a scaffolding protein to recruit a variety of other coactivators. PGC-1 α regulates the activity of PPAR γ on adaptive thermogenesis and fatty acid oxidation by interacting with the PPAR γ /RXR α heterodimer. This interaction stimulates the expression of UCP-1, resulting in enhanced metabolic rate and insulin sensitivity, and resistance to obesity ( 18 – 21 ). NCoR and SMRT are other examples of well characterized PPAR γ co-regulators that function to recruit histone deacetylase (HDAC) complexes, which covalently modify nucleosomes to compact DNA and repress transcription ( 22 ). In the absence of ligand, PPAR γ recruits the transcription corepressors NCoR and SMRT to downregulate PPAR γ -mediated transcriptional activity. Gene silencing of Ncor or Smrt in 3T3-L1 preadipocytes increases adipocyte differentiation ( 22 – 24 ). These cofactors, and many others, have specific physiological functions and differential effects on regulating the transcriptional action of PPAR γ , and therefore unique non-redundant roles in lipid and energy metabolism. Zinc finger protein 407 (ZFP407) was first identified as a positive regulator of insulin-stimulated glucose uptake via regulation of the PPAR γ signaling pathway both in vitro and in vivo ( 25 , 26 ). ZFP407 was subsequently shown to directly interact with the PPAR γ /RXRα protein complex ( 27 ). To better understand the mechanism by which PPAR γ activity is regulated, we focused on discovering novel proteins that interact with the PPAR γ and ZFP407 transcriptional regulatory protein complex. Towards this end, a previously performed high-throughput mammalian two-hybrid analysis of transcription factor protein-protein interactions ( 28 ) identified, among many other novel interactions, that ZBTB9 directly interacted with multiple proteins critical for PPAR γ signaling, including PPAR γ itself, but also including ZFP407 and PGC-1β ( 26 , 29 – 32 ). Furthermore, Zbtb9 is the closest gene to a series of SNPs that are significantly associated with Body Mass Index (BMI). The lead SNP among them, rs11757081 , was significantly associated with BMI (p < 10 -15 ) in a GWAS meta-analysis of over 3 million individuals ( 33 ). Zbtb9 is also the closest gene to SNP rs210192 , which was significantly associated with T2D risk (p = 4.52e -8 ) in a similar meta-analysis ( 33 ). These data suggest that ZBTB9 may play a critical role in determining an individual’s risk of developing metabolic disease and T2D. To assess the potential role of ZBTB9 in PPAR γ signaling and adipocyte biology, we generated Zbtb9 -deficienct mouse and human adipocytes and preadipocytes, and demonstrated for the first time the critical role ZBTB9 has on adipogenesis and insulin sensitivity via modulation of PPAR γ signaling. We further show that ZBTB9 is a negative regulator of early steps in adipogenesis via E2F-dependent regulation of Pparg expression. Interestingly, in mature adipocytes, ZBTB9 is required for PPAR γ signaling and insulin response via a different mechanism that regulates PPAR γ activity, but not expression. Together, our results provide the first functional characterization of ZBTB9 in adipocytes, revealing unique cell-state-dependent regulation of PPAR γ signaling in both early adipogenesis and mature adipocyte function. Results ZBTB9 positively regulates PPAR γ activity in mature adipocytes A high throughput mammalian two-hybrid analysis of transcription factor protein-protein interactions suggested that ZBTB9 interacts with PPAR γ and other PPAR γ -interacting proteins including ZFP407 (28). To further test whether ZBTB9 interacts with these proteins, a co-IP was performed in differentiated 3T3-L1 adipocytes. The co-IP confirmed that ZBTB9 does indeed interact with the PPAR γ /RXRα/ZFP407 complex ( Fig. 1A ). To investigate the role of ZBTB9 in PPAR γ signaling, ZBTB9 and PPAR γ were co-expressed with a PPAR γ response element (PPRE) luciferase reporter plasmid that contains 3 copies of the canonical PPAR γ DNA binding sequence DR1. Together, ZBTB9 and PPAR γ increased expression from the PPAR γ reporter construct ( Fig. 1B-C ), suggesting that ZBTB9 positively regulates PPAR γ activity through the canonical PPAR γ response element. Download figure Open in new tab Figure 1. ZBTB9 is a positive regulator of PPAR γ signaling in mature adipocytes. (A) Co-IP using anti-RXRα antibody of exogenously expressed proteins as indicated in differentiated 3T3-L1 cells. (B) PPRE luciferase reporter activity from 293T cells or from (C) differentiated 3T3-L1 adipocytes transfected with an empty vector, Zbtb9 cDNA, Pparg cDNA as indicated. (D) Zbtb9 was knocked down in differentiated 3T3-L1 adipocytes with 2 independent shRNAs (shRNA #1, shRNA #2) and compared to the control shRNA (shCtrl). Gene expression was measured by qRT-PCR. ** p < 0.01, *** p < 0.001, *** p < 0.0001. n=3-5/group. To explore the role of ZBTB9 on PPAR γ target gene expression under more physiological conditions, we reduced Zbtb9 expression by lentivirus-mediated shRNA in differentiated 3T3-L1 adipocytes, and observed consistently decreased expression of a number of well-characterized PPAR γ target genes in Zbtb9 knockdown (KD) cells compared to the control ( Fig. 1D ). Altogether, this data suggests that ZBTB9 acts as a positive regulator of PPAR γ signaling in adipocytes. Zbtb9 is a negative regulator of adipogenesis Given the interaction between PPAR γ and ZBTB9 ( Fig. 1A ), the role of ZBTB9 in regulating PPAR γ -dependent gene expression in mature adipocytes ( Fig. 1B-D ), and the central role of PPAR γ in adipogenesis ( 31 ), we next examined whether ZBTB9 played a role in adipocyte differentiation. Two independent shRNAs were used to inhibit Zbtb9 expression in 3T3-L1 preadipocytes. The cells were then induced to undergo adipocyte differentiation in the context of reduced Zbtb9 expression. Surprisingly, lipid accumulation, as assessed by Oil Red O staining, was significantly increased in the Zbtb9 KD cells relative to control cells ( Fig. 2A-B ). Consistent with the lipid accumulation, expression of the adipogenic genes Pparg , Adipoq , Fabp4 and Glut4 were all significantly higher in Zbtb9 -KD cells relative to control cells ( Fig. 2C ). The increased levels of Pparg and Fabp4 expression in Zbtb9 -KD cells were observed at different time points during differentiation, starting within three days of inducing adipogenesis, with bigger effects at day 3 and day 7, suggested that ZBTB9 plays an early role in regulating key genes that are critical to the molecular induction of adipogenesis ( Fig. 2D ). Download figure Open in new tab Figure 2. Zbtb9 deficiency increases adipogenesis. (A) Oil Red O staining and (B) quantification to assess lipid accumulation in Zbtb9 -KD 3T3-L1 cells or control cells. (C) Zbtb9 and adipogenic gene expression at the end of differentiation (day 11) in Zbtb9 -KD 3T3-L1 cells or control cells as determined by qRT-PCR. (D) Time course of Pparg and Fabp4 gene expression during differentiation at D0, D3, D7 and D11 in Zbtb9 -KD 3T3-L1 cells or control cells as determined by qRT-PCR. (E) Lipid accumulation in differentiated human adipocytes treated with hZBTB9 shRNA (shRNA #3) or control shRNA (shCtrl) shown with brightfield images and (F) oil red O staining and (G) oil red O quantification. (H) ZBTB9 was knocked down with 2 independent shRNAs (shRNA #3, shRNA #4) in human preadipocytes. Gene expression was measured by qRT-PCR at the end of differentiation (day 14). * p < 0.05, ** p < 0.01, **** p < 0.0001, ns: not significant. n=3-5/group. ZBTB9 protein is highly conserved between mice and humans (77% identical at the amino acid level, Fig. S1). The level of conservation is even higher specifically within the BTB domain and the two C2H2 zinc finger domains (96% identical, Fig. S1). Thus, to extend the findings observed in mouse 3T3-L1 cells, and test whether ZBTB9 has a similar function during adipogenesis in humans, analogous studies were performed in a human-derived cell model of adipogenesis. ZBTB9 levels were reduced by lentiviral-mediated shRNA treatment in human preadipocytes, and upon adipogenesis, there was again a significant increase in both lipid accumulation, as assessed by oil red O staining ( Fig. 2E-G ) and adipogenic marker gene expression ( Fig. 2H ). Together, these data suggest that while ZBTB9 positively regulates PPAR γ activity in mature adipocytes, it regulates the early stages of adipogenesis by an alternative mechanism in a manner that is evolutionarily conserved in both humans and mice. Transcriptome-wide profiling reveals that Zbtb9 broadly regulates the expression of genes within the adipogenesis pathway To identify the genes and biological processes regulated by Zbtb9 during differentiation, Zbtb9 -KD 3T3-L1 cells were analyzed by RNA-Seq throughout adipocyte differentiation, beginning at day 0 (before adipogenic induction), as well as days 3, day 7, and finally day 11 when the cells are terminally differentiated into adipocytes. Principle component analysis (PCA) was performed to test whether samples clustered with each other at each time point during adipogenesis. Figure 3A shows the results of the PCA, demonstrating that samples at day 0 and day 3 were distinct from those at day 7 and day 11. On day 0 or day 3, there was a clear distinction between KD and control samples, whereas samples at day 7 and day 11 tended to cluster together, regardless of whether the cells were treated with a control or Zbtb9 -targeting shRNA. This suggests that the cells have different gene profiles at later time points compared to early ones during adipocyte differentiation, consistent with the transition from preadipocytes to adipocytes. Additionally, bigger differences were observed between KD and control samples at day 7 and day 11, respectively, as compared with early time points, suggesting bigger effects of Zbtb9 on the gene profiles later during differentiation. Differentially expressed genes (DEGs) were identified at each time point during differentiation (FDR ≤ 0.05). In general, more DEGs were observed upon adipogenic differentiation, consistent with the PCA results. A total of 826, 1103, 4088 and 3195 genes were found to be differentially regulated, with 352, 594, 2198 and 1639 gene transcripts upregulated, and 474, 509, 1890 and 1556 genes downregulated at day 0, day 3, day 7 or day 11 respectively ( Fig. 3B-D ). Gene set enrichment analysis showed that upregulated genes were enriched for lipid metabolism-related pathways, and included adipogenesis, oxidative phosphorylation, fatty acid metabolism, and MTORC1 signaling ( Fig. 3E ). Increased expression of most of the pathways in Zbtb9 -KD cells relative to control cells was observed beginning at day 3. These expression differences are likely to be largely attributable to the upregulation of Pparg in KD cells compared with control cells that was also seen at this time point during differentiation ( Fig. 2D and Fig. 4 ). Significantly upregulated genes in KD vs. control cells of adipogenesis pathway at days 3, 7, and 11 included many well-known adipogenic and Pparg target genes including Adipoq , Fabp4 , Cd36 , and Lpl ( Fig. 4 ). Download figure Open in new tab Figure 3. Global transcriptional profiling reveals that Zbtb9 regulates multiple target genes during adipogenesis. (A) Principle component analysis (PCA) of Zbtb9 knockdown (KD) or control (CTL) transcriptomes in 3T3-L1 cells at different time points during adipogenesis. (B) Number of differentially expressed genes (DEGs) significantly (FDR < 0.05) up or down regulated upon Zbtb9 KD in 3T3-L1 cells at D0, D3, D7 and D11. (C) Venn diagrams showing the overlap between DEGs ( Zbtb9 -KD vs. control) upregulated or downregulated at different time points from paired comparisons. (D) Volcano plots showing the DEGs between Zbtb9 -KD and control 3T3-L1 cells. Highlighted are genes in E2F targets pathway (Day 0) and adipogenesis pathway (Days 3, 7, 11). (E) Gene set enrichment analysis for all DEGs using the Hallmark gene sets. All pathways shown were significantly different in Zbtb9 -KD vs. control (FDR < 0.05). NES, normalized enrichment score. Download figure Open in new tab Figure 4. ZBTB9 broadly regulates the expression of genes within the adipogenesis pathway. Heatmap of the adipogenesis pathway in Zbtb9 -KD vs. control (CTL) 3T3-L1 cells at D0, D3, D7 and D11 based on the RNA-Seq expression profiles. All genes shown in the heatmap were significantly upregulated in KD cells compared to CTL at D3, D7 and D11. sh1_1-2, sh2_1-2, and shCtrl_1-4 indicate individual biological replicates of shRNA#1, shRNA#2, and shCtrl, respectively. In addition to the downstream effects on adipogenesis likely resulting from increased Pparg expression, of interest were the earliest transcriptional differences that led to the upregulation of Pparg . For example, at day 0, prior to the induction of adipogenesis, there was no difference in expression levels of Pparg between control and Zbtb9 -KD cells ( Fig. 2D ) and no upregulation of genes in the adipogenesis pathway ( Fig. 3E ). Thus, an important question was how Zbtb9 was driving the increased expression of Pparg , one of the earliest and most critical steps in adipogenesis ( 31 ). Pathway analysis of the DEGs at day 0, which precedes the increase in adipogenesis gene expression, revealed a significant enrichment of cell cycle-related signaling pathways, including G2M check point, E2F targets, MYC targets and mitotic spindle ( Fig. 3E ). To identify the transcription factor binding sites in promoter regions of these DEGs in Zbtb9 -KD cells vs control cells, TransFind ( 34 ) was used to predict the transcriptional regulators of the upregulated genes in KD cells relative to control cells at day 0, and identified an enrichment of the canonical E2F binding site in KD cells ( Table 1 and Table S1 for detail). The identification of E2F target genes among the most upregulated pathways and enrichment of the E2F consensus binding sites upstream of DEGs was of particular interest given that E2F has previously been shown to directly regulate the expression of Pparg both in vitro and in vivo ( 35 , 36 ). View this table: View inline View popup Download powerpoint Table 1. Transcription factor motifs enriched in Zbtb9 deficient preadipocytes (Day 0). ZBTB9 modulates RB-E2F signaling to control the early induction of adipogenesis E2F is a family of transcription factors that play a critical role in early adipogenesis ( 37 , 38 ). Given that Zbtb9 deficiency causes upregulation of E2F target genes ( Fig. 3D , Day 0), we sought to test whether the effects of ZBTB9 on adipogenesis and adipogenic gene expression were mediated by E2F. We first examined the activity of E2F in 3T3-L1 preadipocytes utilizing an E2F response element luciferase reporter, and demonstrated a significant increase in E2F activity due to Zbtb9 deficiency (2.2 and 1.8-fold increase with shRNA#1 and #2 respectively), confirming that ZBTB9 does negatively regulate E2F activity ( Fig. 5A ). Next, we tested whether the increase in adipogenic gene expression and adipogenesis due to Zbtb9 deficiency was dependent on E2F activity. Towards this end, Zbtb9 was knocked down in 3T3-L1 preadipocytes and the cells were induced to undergo adipocyte differentiation, either in the presence or absence of the E2F inhibitor HLM006474 (E2Fi). Consistent with previous results ( Fig. 2A-C ), Zbtb9 deficiency again increased adipogenic gene expression and adipogenesis as measured by Oil Red O lipid staining ( Fig. 5B-D ). However, in the presence of E2Fi, Zbtb9 deficiency failed to increase levels of Pparg , Adiponectin , Glut4 , and Fabp4 , relative to in the absence of E2Fi when each of these genes was significantly increased ( Fig. 5B ). Lipid accumulation was also significantly reduced in E2Fi-treated cells compared to DMSO control, as quantified by Oil Red O staining ( Fig. 5C-D ). These results demonstrate that the effect of ZBTB9 on adipogenesis is dependent on E2F activity. Download figure Open in new tab Figure 5. ZBTB9 regulates early induction of adipogenesis through Rb-E2F signaling. (A) An E2F consensus reporter plasmid was transfected into Zbtb9 -KD or control 3T3-L1 preadipocytes. Luciferase activity was measured. (B) Zbtb9 -KD or control 3T3-L1 preadipocytes were treated with the E2F inhibitor HLM006474 (E2Fi) or DMSO as a control, and differentiated. Adipogenic gene expression was analyzed by qRT-PCR at the end of differentiation (day 11). (C) Oil Red O staining and (D) quantification of these cells treated with E2Fi or DMSO as a control. (E) Western blots of Zbtb9 -KD and control 3T3-L1 preadipocytes before the initiation of differentiation (D0) or in differentiation medium for one day (D1). Cell lysates were subjected to SDS-PAGE and western blotting for phosphorylated RB (p-RB) and total RB. GAPDH represents a loading control. (F) p-RB protein levels from panel E were quantified by image J. (G) Western blot analysis of p-RB, total RB and GAPDH (loading control) in ZBTB9 -KD and control human preadipocytes before differentiation. (H) p-RB protein levels from panel G were measured by image J. * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001. n=3-5/group. E2F has been shown to directly regulate the expression of lineage-specifying transcription factors, including PPAR γ , both in vitro and in vivo ( 35 , 36 ), which is independent of its function as a cell cycle regulator. This function of E2F is regulated by the phosphorylation of pocket protein RB (pRB), with pRB dissociating from E2F, enabling the activation and increased transcriptional activity of E2F ( 39 ). To test whether ZBTB9 regulates the phosphorylation status of RB, Western blots were performed in control and Zbtb9 KD cells in both human and mouse preadipocytes. As a control for increased pRB levels, we tested adipogenic induction medium, which is known to induce pRB phosphorylation ( 38 ), and which indeed increased phosphorylation of RB as expected ( Fig. 5E-F , Day 1). In addition, a clear and reproducible increase in pRB levels was detected in Zbtb9 -KD mouse preadipocytes compared to control cells, without changing total RB levels ( Fig. 5E-F , Day 0, prior to induction of differentiation). In human preadipocytes, Zbtb9 -KD also increased pRB levels at Day 0 ( Fig. 5G-H ). The results demonstrated that ZBTB9 regulates adipogenesis via an E2F-dependent mechanism that is associated with increased pRB levels and elevated E2F activity. Discussion Little is known about the cellular function of ZBTB9, although multiple GWAS suggested a role in metabolic disease susceptibility. We now report for the first time that ZBTB9 regulates adipogenesis and adipocyte function, suggesting a possible molecular mechanism underlying the altered risk of obesity and T2D associated with allelic variation near ZBTB9. We demonstrated that ZBTB9 interacts with the PPAR γ /RXRα/ZFP407 protein complex in adipocytes and increased PPAR γ activity via the consensus PPAR γ /RXRα DNA binding motif. Interestingly, ZBTB9 itself increased the PPAR γ reporter gene expression in HEK293T cells ( Fig. 1B ), which do not express endogenous PPAR γ . Thus, it is possible that ZBTB9 activates PPAR γ target genes by directly binding to the response element with or without interacting with PPAR γ . Unlike ZFP407, which regulates PPAR γ activity in the absence of a direct effect on PPAR γ expression, ZBTB9 deficiency reduced PPAR γ gene expression as well as PPAR γ target genes in 3T3-L1 adipocytes ( Fig. 1D ). PPAR γ is important for mature adipocyte function ( 40 , 41 ), and crucial for controlling gene networks involved in glucose homeostasis and insulin sensitization ( 31 ). PPAR γ transactivation is induced by ligand-dependent and independent mechanisms. Ligand-dependent transactivation is induced by ligand binding to the C-terminal activation function (AF-2) domain ( 42 ). PPARs form heterodimers with the RXR and bind to PPAR response elements (PPREs) in enhancers of downstream target genes ( 43 ). Binding of a ligand to a PPAR results in the dissociation of a corepressor protein complex and then recruitment of several transcriptional coactivators, some of which are responsible for the modification of histone and chromatin structure to open up DNA for transcription, while others provide linkage to core basal transcriptional machinery ( 44 , 45 ). Many coactivators and corepressors of PPAR γ have been reported over the past two decades, such as TIF2 , PGC-1α , TRAP220/DRIP205/PBP , RIP140 , NCoR , SMRT , Sirt1 , and TAZ ( 17 , 45 ). PPAR γ and the coregulators function as multiprotein complexes to activate target gene transcription. Each of the coregulators has its own unique inherent physiological function in lipid and energy metabolism. PPAR γ -mediated hormonal or non-hormonal signal transduction regulates cell growth, differentiation, development, metabolism and other important physiological functions. An understanding of the functional significance of individual components of the complicated coregulator complexes in PPAR γ signal transduction pathway will provide multiple drug targets that may fine-tune PPAR γ signaling or better integrate other signaling pathways. Our study shows that ZBTB9 functions as a positive regulator of PPAR γ signaling in mature adipocytes, which adds an important piece to the PPAR γ transcriptional puzzle by discovering a novel protein with its own non-redundant properties in regulating adipogenesis and adipocyte gene expression. Adipogenesis has been studied extensively in vivo and in vitro but many questions remain about the exact molecules and mechanisms that govern this process ( 8 , 46 , 47 ). The growth and expansion of adipocytes and adipose tissue in vivo depends on the self-renewal and differentiation of adipose precursor cells (APCs), differentiation into preadipocytes, and finally the differentiation of preadipocytes into mature adipocytes ( 48 ). Adipose expansion through adipogenesis can offset the negative metabolic effects of obesity, and the mechanisms and regulators of this adaptive process are now emerging. Adipocyte differentiation involves a temporally regulated set of gene-expression events, and understanding the underlying transcriptional networks is of fundamental importance. PPAR γ is the master regulator of adipogenesis ( 11 , 12 ). Identifying new molecules interacting with PPAR γ will shed light on the function of PPAR γ in adipogenesis. One of the most consequential downstream effects of PPAR γ is the activation of the transcription factor C/EBPα ( 49 ). C/EBPα and PPAR γ functionally synergize to fully activate the mature adipocyte program ( 50 , 51 ). Over the past two decades, many factors have been found to regulate adipogenesis. For example, transcription factor ZFP467 suppresses osteogenesis and promotes adipogenesis of the fibroblast-like progenitors by enhancing the expression of C/EBPα ( 52 ). Furthermore, KLF5 binds to and activates the Pparg promoter, functioning in concert with C/EBPα ( 53 ). By contrast, GATA2 and GATA3 inhibit adipogenesis through inhibition of PPARG transcription ( 54 ). We further explored the role of ZBTB9 in adipocyte differentiation. Surprisingly, shRNA-mediated Zbtb9 deficiency in preadipocytes led to an increase in adipogenesis as indicated by both lipid accumulation and adipogenic gene expression. In support of this, pathway analysis of RNA-Seq data revealed significant enrichment of genes in the adipogenesis pathway, with gene expression elevated by Zbtb9 deficiency shortly after the induction of differentiation ( Fig. 4 , Day 3). These results were unexpected given the role of ZBTB9 as a positive regulator of PPAR γ in mature adipocytes, as for example is illustrated in Figure 1 . In contrast, PPAR γ and its target genes, which are key drivers of adipogenesis, were negatively regulated by ZBTB9 at the early stages of differentiation by an alternative mechanism. Like ZFP467 and KLF5 mentioned above, the identification of ZBTB9 also helps to better define the precise mechanisms in adipogenesis, by recognizing the role of ZBTB9 and demonstrating that it works via the E2F pathway. Adipogenesis involves two major events: preadipocyte proliferation and adipocyte differentiation ( 55 ). In vitro studies using 3T3-L1 preadipocyte model have been instrumental in studying this process. Re-entry into cell cycle of growth arrested preadipocytes following differentiation induction is a required initial event occurring during adipogenesis. After several rounds of clonal expansion, cells arrest proliferation again and undergo terminal adipocyte differentiation ( 56 ). E2F transcription factors can promote transcriptional activation of genes that encode cell-cycle regulators required for S-phase entry and progression of the cell cycle ( 57 ). These events are critical for mitotic clonal expansion, an obligate step in the adipocyte differentiation program ( 58 ). E2F also has important metabolic functions beyond the control of the cell cycle ( 59 – 61 ). For example, E2F1 was demonstrated to be a positive regulator of adipogenesis, by promoting Pparg expression or activity, independent of its role as cell cycle regulator ( 38 ). Regulation of Pparg expression by E2F1 is through direct binding to an E2F-responsive element in the Pparg promoter early during adipogenesis ( 38 ). Thus, E2Fs represent a link between proliferative signaling pathways, triggering clonal expansion and terminal adipocyte differentiation through regulation of Pparg expression. The pocket protein RB is a major regulator of E2F1 activity. Phosphorylation of RB results in dissociating from E2F, enabling the activation and increased transcriptional activity of E2F ( 39 ). RB has an inhibitory role at early stage of adipocyte differentiation, through the formation of a complex including HDAC3 that inhibits PPAR γ -dependent gene expression and adipocyte differentiation ( 62 ). However, the lack of RB inhibits adipogenesis in 3T3-L1 and MEF cells ( 63 ). In addition, mice with a conditional deletion of Rb in adipose tissue have increased mitochondrial activity resulting in an increased energy expenditure, which protects them from diet-induced obesity ( 64 ). These apparently opposite roles of RB in adipogenesis can be reconciled as during early stage of adipocyte differentiation, cells need to exit cell cycle. In this withdrawal stage RB plays a major role, and positively regulates adipogenesis in a PPAR γ -independent manner. Later during differentiation, RB represses PPAR γ activity but the net result is still decreased fat mass in the absence of RB. Thus, the pRB-E2F1 pathway, in which we show that Zbtb9 is a key regulatory molecule, plays an important role in metabolism at different stages of adipogenesis. The gene expression data in our study shows no difference in expression levels of Pparg between Zbtb9 -KD and control cells at Day 0, which precedes the increase in adipogenic gene expression, but a significant enrichment of E2F target pathway in Zbtb9 -KD cells compared with control cells at this time point. During this clonal expansion phase of adipocyte differentiation which represents the early stage of adipogenesis, E2F1 regulates the expression of genes implicated in the entry of the cells into cell cycle. E2F1 also promotes Pparg expression at this stage, as shown by gene expression results at Day 3 ( Fig. 2D , Fig. 4 ). The luciferase assay indicates increased E2F transcriptional activity in Zbtb9 -KD cells, as compared to control cells, before differentiation. In line with this, RB phosphorylation was also enhanced in Zbtb9 -KD cells at Day 0, which activated E2F1 . Our data suggest ZBTB9 regulates adipogenesis via an E2F-dependent mechanism that is associated with increased RB phosphorylation levels and elevated E2F activity. Based on our data, ZBTB9 plays dual roles in the regulation of PPAR γ signaling in a cell state-dependent manner. Our study provides mechanistic insights into how ZBTB9 regulates early adipogenesis and adipocyte function, identifying a new molecule that may be important in the pathogenesis and treatment of obesity and T2D. Although much remains to be discovered about the underlying molecular mechanism as well as the physiological role of ZBTB9 in adiposity. Experimental procedures Cell culture 3T3-L1 cells were passaged and differentiated as previously described ( 25 ). Briefly, 3T3-L1 cells were induced to differentiation at day 0 (2 days post confluence) by adding the induction medium, which is the complete culture medium supplemented with the DMI cocktail (1 μ M dexamethasone, 0.5 mM 3-isobutyl-1-methylxanthine, and 167 nM insulin, all from Sigma, Saint Louis, MO). At day 3, the induction medium was removed and the maintenance medium (complete culture medium supplemented with 167 nM insulin) was added. At day 7, the maintenance medium was removed, and complete culture medium was added. The cells were harvested for staining or RNA extraction at day 11. Human preadipocytes were obtained from Sigma (#802S-05A) and plated and cultured with Human Preadipocyte Growth Medium (Sigma #811-500). Once confluent, the cells were subjected to differentiation with Human Preadipocyte Differentiation Medium (Sigma #811D-250) for 12 days. The differentiation medium was refreshed every other day. Cells were harvested for staining or RNA extraction at the end of differentiation. Lentiviral production and infection Lentiviral particles expressing either a control shRNA (shCtrl: pLKO.1, Sigma-Aldrich, St. Louis, MO, USA) or shRNAs targeting Zbtb9 (mouse Zbtb9 shRNA #1: TRCN0000125706; mouse Zbtb9 shRNA #2: TRCN0000125707; human ZBTB9 shRNA #3: TRCN0000017185; human ZBTB9 shRNA #4: TRCN0000017186) were prepared and propagated in HEK293T cells as described previously using the second generation of psPAX2 and pMD2.G packing vectors. After two rounds of lentiviral infection, cells were then cultured and differentiated as previously described ( 32 ). Oil Red O staining To make Oil Red O (ORO) working solution, 20 mL of 0.5% of the ORO stock solution (Sigma #O1391) (in isopropanol) was added to 30 mL of deionized water. Cells were washed with PBS and fixed with 10% formalin at room temperature for 30 min, then stained with the ORO working solution for 15 min. The cells were then rinsed with water three times, and then scanned with an image scanner (EPSON Perfection V600). For quantification, stain was extracted in isopropanol and measured at 492 nm using a BioTek Epoch Reader. RNA Analysis RNA was collected using QIAshredder and RNeasy mini kit (Qiagen). RNA for qRT-PCR was reversed transcribed using the high capacity cDNA reverse transcription kit without the RNase inhibitor (Applied Biosystems, Carlsbad, CA). Primer sequences are given in Table S2. qRT-PCR was performed in triplicate on a QuantStudio3 Real-time PCR system using the power SYBR Green PCR master mix (Applied Biosystems). The expression level for all genes was calculated using the ΔΔCt method relative to the Gapdh control gene. For RNA-Seq analysis, total RNA was isolated as described above with an additional on-column DNase treatment step. RNA quality was determined on the Agilent BioAnalyzer 2100 and all samples had an RNA integrity number score greater than 9.5. Illumina TruSeq sequencing libraries were prepared by Novogene Co., LTD using standard procedures. Samples were run on an Illumina NovaSeq generating an average of 68,511,857 reads per sample. Reads were aligned to the mouse genome (Ensembl m38.102) using TopHat version 2.1.0, SamTools version 1.3.1, and Bowtie2 version 2.2.6 ( 65 – 67 ). Gene expression count tables were generated using HTSeq version 0.6.1 ( 68 ) and analyzed for differential expression by DESeq2 version 1.30 ( 69 ). A false discovery rate-adjusted p value of < 0.05 was considered statistically significant for RNA-Seq analysis. The RNA-Seq expression profiling data are available in the Gene Expression Omnibus series GSE253544. Luciferase reporter assay To assess Pparg activity, HEK293T cells or 3T3-L1 mature adipocytes were transfected with DNA plasmid constructs encoding PPAR γ (Addgene no. 8862), ZBTB9 (MR207329; Origene Technologies, Rockville, MD), or an empty vector control plasmid (pRK5-Myc), together with the Pparg target gene luciferase reporter plasmid (PPRE-X3-Tk-luc, Addgene no. 1015), and control plasmid pRL-SV40 encoding Renilla for normalization. To assess E2F activity, Zbtb9 or control shRNA treated 3T3-L1 preadipocytes were transfected with the E2F target gene luciferase reporter plasmid (pGreenFire1_E2F1RE, Addgene no. 112248) and control plasmid pRL-SV40 encoding Renilla for normalization. Luciferase and Renilla were measured 48 hours post-transfection with the Dual-Glo Luciferase Assay System (Promega, Madison, WI). Western blotting Western blotting was performed and quantitated as described ( 25 ). A custom anti-ZFP407 antibody was generated in rabbit against the COOH-terminal 149 amino acids of the mouse ZFP407 protein (Proteintech Group) and has been described previously ( 25 ). The anti-ZBTB9 antibody was from Aviva Systems Biology (#ARP31669_P050). The anti-PPAR γ antibody was obtained from Bethyl Laboratories (#A304-461A, Montgomery, TX). The anti-RXRα (#3085), anti-phopho-RB (#8180), anti-RB (#9313) antibodies were from Cell Signaling Technologies (Danvers, MA). Anti-GAPDH was from Proteintech Group (#60004-1, Rosemont, IL). The goat anti-rabbit (31460) and goat anti-mouse (31430) secondary antibodies were from ThermoFisher Scientific (Waltham, MA). Statistical analyses All data are expressed as the mean ± SEM. Statistical significance was assessed with two-tailed Student’s t -Test using GraphPad Prism 8 software. P values < 0.05 were considered statistically significant for all statistical tests. Data availability All RNA-Seq data is available in the Gene Expression Omnibus at accession number GSE253544. Supporting information This article contains supporting information. Funding and additional information This study was supported by the NIDDK grant DK119305 (D.A.B.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Conflict of interest The authors declare that they have no conflicts of interest with the contents of this article. Figure S1. Evolutionary conservation of the mouse and human ZBTB9 protein sequence. Highlighted are the mouse and human ZBTB9 protein BTB domain and 2 zinc finger C2H2 domains. Acknowledgments This work made use of the High Performance Computing Resource in the Core Facility for Advanced Research Computing at Case Western Reserve University. 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