Transcriptional regulation of adipocyte lipolysis by IRF2BP2

Transcriptional regulation of adipocyte lipolysis by IRF2BP2 | 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 Transcriptional regulation of adipocyte lipolysis by IRF2BP2 Yang Chen , Lin Liu , Ryan Calhoun , Lan Cheng , David Merrick , David J. Steger , Patrick Seale doi: https://doi.org/10.1101/2024.07.31.605689 Yang Chen 1 Institute for Diabetes , Obesity and Metabolism 2 Dept. of Cell and Developmental Biology, Perelman School of Medicine University of Pennsylvania Find this author on Google Scholar Find this author on PubMed Search for this author on this site Lin Liu 1 Institute for Diabetes , Obesity and Metabolism 2 Dept. of Cell and Developmental Biology, Perelman School of Medicine University of Pennsylvania Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ryan Calhoun 1 Institute for Diabetes , Obesity and Metabolism 2 Dept. of Cell and Developmental Biology, Perelman School of Medicine University of Pennsylvania Find this author on Google Scholar Find this author on PubMed Search for this author on this site Lan Cheng 1 Institute for Diabetes , Obesity and Metabolism 2 Dept. of Cell and Developmental Biology, Perelman School of Medicine University of Pennsylvania Find this author on Google Scholar Find this author on PubMed Search for this author on this site David Merrick 1 Institute for Diabetes , Obesity and Metabolism Find this author on Google Scholar Find this author on PubMed Search for this author on this site David J. Steger 1 Institute for Diabetes , Obesity and Metabolism Find this author on Google Scholar Find this author on PubMed Search for this author on this site Patrick Seale 1 Institute for Diabetes , Obesity and Metabolism 2 Dept. of Cell and Developmental Biology, Perelman School of Medicine University of Pennsylvania Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: sealep{at}pennmedicine.upenn.edu Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract Adipocyte lipolysis controls systemic energy levels and metabolic homeostasis. Lipolysis is regulated by post-translational modifications of key lipolytic enzymes. However, less is known about the transcriptional mechanisms that regulate lipolysis. Here, we identify the transcriptional factor interferon regulatory factor-2 binding protein 2 (IRF2BP2) as a repressor of adipocyte lipolysis. Deletion of IRF2BP2 in primary human adipocytes increases lipolysis without affecting glucose uptake, whereas IRF2BP2 overexpression decreases lipolysis. RNA-seq and ChIP-seq analyses reveal that IRF2BP2 directly represses several lipolysis-related genes, including LIPE ( HSL , hormone sensitive lipase), which encodes the rate-limiting enzyme in lipolysis. Adipocyte-selective deletion of Irf2bp2 in mice increases Lipe expression and free fatty acid levels, resulting in elevated adipose tissue inflammation and glucose intolerance. Altogether, these findings demonstrate that IRF2BP2 restrains adipocyte lipolysis and opens new avenues to target lipolysis for the treatment of metabolic disease. Introduction Adipocytes play a central role in regulating systemic energy levels and metabolic health. Adipocytes store energy as triglyceride in lipid droplets, and release energy in the form of free fatty acids (FFAs) through lipolysis 1 . Adipocytes display remarkable plasticity and undergo dynamic changes in their metabolic program in response to many physiologic and pathologic stimuli. Lipolysis is activated under conditions of energy demand, such as during fasting or exercise. Triglycerides are cleaved into diacylglycerol and fatty acids by the enzyme PNPLA2 (also called ATGL), followed by the hydrolysis of diacylglycerol into monoacylglycerol and fatty acids through the action of hormone-sensitive lipase E (LIPE, also known as HSL). Free fatty acids (FFA) are released into bloodstream to provide fuel for other organs. Excessive or dysregulated adipocyte lipolysis leads to ectopic fat deposition in liver, muscle, pancreas, and other organs, promoting insulin resistance and glucose intolerance 2 , 3 , 4 . Aberrant lipolysis can also lead to hyperlipidemia and cardiometabolic abnormalities 5 , 6 . Mutations in key lipolysis genes (e.g. PNPLA2 , LIPE ) are associated with human metabolic and cardiac dysfunction, such as lipodystrophy, insulin resistance and cardiac myopathy 7 , 8 . Adipocyte lipolysis is activated by the sympathetic nervous system and pro-lipolytic hormones such as cortisol, glucagon and natriuretic peptides 4 , 9 , 10 , 11 . These stimuli induce the phosphorylation and activation of lipolytic proteins PNPLA2 and LIPE 12 , 13 , 14 . Conversely, insulin acts on adipocytes to restrain lipolysis 11 , 15 , 16 . Adipocyte PNPLA2 and LIPE activities are also regulated via other various pathways e.g. cyclic adenosine monophosphate activators, FGF-1, serotonin, and inflammatory factors 17 , 18 , 19 , 20 , 21 , 22 , 23 . However, there is limited research on the transcriptional regulation of lipolytic enzymes and lipolysis. Transcriptional mechanisms may be especially important for determining the rates of basal lipolysis. Peroxisome proliferator activated receptor gamma (PPARγ), liver X receptor alpha (LXRα), and steroidogenic factor-1 (SF1) have been shown to regulate LIPE expression 24 , 25 , 26 . Identifying additional transcription factors and mechanisms that regulate lipolysis may provide new therapeutic avenues to ameliorate and/or prevent insulin resistance and related cardiometabolic disorders. Interferon regulatory factor-2 binding protein-2 (IRF2BP2) is a transcriptional cofactor, governing diverse biological processes including macrophage inflammatory responses, lymphocyte differentiation, cardiomyocyte hypertrophy, and hepatic steatosis 27 , 28 , 29 , 30 . IRF2BP2 was first described as an IRF2-dependent transcriptional co-repressor but has also been reported to activate target genes in certain contexts 31 , 32 . Notably, IRF2BP2 variants identified from genome wide association studies (GWAS) are associated with circulating lipid levels and coronary artery disease risk 33 . However, the role of IRF2BP2 in regulating adipocyte function was unknown. In this study, we found that IRF2BP2 represses lipolysis in adipocytes, and this action is required to maintain systemic metabolic homeostasis. In human adipocytes, deletion of IRF2BP2 elevates lipolysis, whereas overexpression of IRF2BP2 suppresses lipolysis. Integrated RNA-seq and ChIP-seq analysis demonstrate that IRF2BP2 binds and represses lipolysis-related genes, including the rate-limiting enzyme LIPE . Adipocyte-selective deletion of Irf2bp2 in mice increases Lipe expression and leads to elevated levels of circulating FFA. Consequently, Irf2bp2 deficient mice exhibit increased adipose tissue and systemic inflammation and glucose intolerance. Altogether, our results demonstrate that adipocyte IRF2BP2 contributes importantly to whole body metabolic homeostasis through transcriptional repression of LIPE expression and lipolysis. Results Loss of IRF2BP2 increases lipolysis in human adipocytes We first evaluated the mRNA expression levels of IRF2BP2 during human adipocyte differentiation. Primary human adipose tissue-derived precursor cells (hAPC) were induced to differentiate into lipid-droplet containing adipocytes that expressed high levels of adipocyte- selective genes ( ADIPOQ , FABP4 , PPARG , LIPE ) by day 14 ( Extended Data Fig. 1a-c) . IRF2BP2 mRNA levels decreased by ∼50% at day 7 and remained lower in mature adipocytes compared to hAPC ( Fig. 1a ). Analysis of a single nucleus RNA-seq dataset from human adipose tissue also showed lower IRF2BP2 mRNA levels in adipocytes relative to hAPC ( Extended Data Fig. 1d,e) 34 . Download figure Open in new tab Fig. 1: IRF2BP2 regulates adipocyte lipolysis a , Relative IRF2BP2 mRNA levels during human adipocyte differentiation (n=3 in each time point). b-e , hAPC were transduced with IRF2BP2-targeting (knockout, KO) CRISPR lentivirus or non-targeting control lentivirus (Ctrl), and differentiated into adipocytes for 14 d. b , Relative mRNA levels of IRF2BP2 and adipocyte marker genes ( ADIPOQ , FABP4 , PPARG ). c , Western blot analysis of IRF2BP2 and GAPDH (loading control) protein levels. d , Glucose uptake in Ctrl and KO adipocytes treated with either PBS or 10 - 8 M insulin. e , Non-esterified fatty acid (NEFA) levels in culture medium from Ctrl and KO adipocytes under basal conditions or following stimulation with 10 -6 M isoproterenol (ISP). f-i , hAPC were transduced with IRF2BP2-expressing (overexpression, OE) or GFP-expressing lentivirus (Ctrl) and differentiated into adipocytes for 14 d. f , Relative mRNA levels of IRF2BP2 , ADIPOQ , FABP4 , and PPARG . g , Western blot analysis of IRF2BP2 and GAPDH (loading control) protein levels. h , Glucose uptake in Ctrl and OE adipocytes treated with either PBS or 10 -8 M insulin. i , NEFA levels in culture medium from Ctrl and OE adipocytes under basal conditions or following stimulation with 10 -6 M ISP. Unpaired two-tailed Student’s t tests were used in b , e , f , and i . One-way ANOVA followed by Dunnett multiple comparisons test was applied in a . To evaluate the function of IRF2BP2 in human adipocytes, we deleted IRF2BP2 in hAPC using a lentiviral CRISPR system and induced adipocyte differentiation for 14 days. IRF2BP2 mRNA levels were markedly reduced, and protein levels were near absent in IRF2BP2 -knockout (KO) cells compared to control (transduced with non-targeting sgRNA) cells ( Fig. 1b,c ). Deletion of IRF2BP2 had a minimal effect on the adipocyte differentiation process, with slight increases in the expression levels of adipocyte marker genes ADIPOQ and PPARG ( Fig. 1b ). IRF2BP2 KO and control adipocytes (at day 14) also exhibited equivalent levels of basal and insulin-stimulated glucose uptake ( Fig. 1d ) . Interestingly, IRF2BP2 KO adipocytes released significantly higher levels of non-esterified fatty acids (NEFA) into the culture medium under basal conditions, as compared to control cells ( Fig. 1e ). Isoproterenol treatment greatly increased NEFA release (lipolysis) in control and IRF2BP2 KO adipocytes, with the KO adipocytes attaining higher levels (∼2-fold) of NEFA release compared to control cells. IRF2BP2 overexpression in human adipocytes decreases lipolysis To determine if IRF2BP2 overexpression (OE) could reduce lipolysis, we transduced hAPC with control (GFP) or IRF2BP2-expressing lentivirus, and induced adipocyte differentiation for 14 days. IRF2BP2 OE cells expressed high levels of IRF2BP2 mRNA and protein and slightly increased the levels of adipocyte genes ADIPOQ and FABP4 ( Fig. 1f,g ). Control and IRF2BP2-OE adipocytes displayed similar rates of glucose uptake under basal conditions and following insulin stimulation ( Fig. 1h ). Strikingly, IRF2BP2 expression decreased NEFA release by ∼70% under basal conditions, and significantly decreased NEFA levels following isoproterenol treatment ( Fig. 1i ). Taken together, these results demonstrate that IRF2BP2 represses NEFA release from human adipocytes without influencing the differentiation process or glucose uptake. IRF2BP2 represses lipolysis-related genes in adipocytes To identify IRF2BP2-regulated genes and pathways in adipocytes, we performed bulk RNA- sequencing analysis of IRF2BP2-KO and IRF2BP2-OE adipocytes, along with their respective control adipocytes ( Fig. 2a,b , Extended Data Fig. 2a-f ). These studies identified high confidence sets of IRF2BP2-repressed genes (163 genes upregulated in KO and downregulated in OE cells) and IRF2BP2-activated genes (175 genes downregulated in KO and upregulated in OE cells). Pathway analysis of IRF2BP2-repressed genes identified “fatty acid oxidation” and “lipid catabolic process” as top-ranking terms ( Fig. 2c , Extended Data Fig. 2g ). Notably, the IRF2BP2-repressed gene set included several classical lipolysis-related genes e.g. LIPE , HSD11B1 , PNPLA2 ( Fig. 2e ). IRF2BP2-activated genes were enriched for pathways related to “cell migration”, “ossification”, and “extracellular matrix organization” ( Fig. 2d , Extended Data Fig. 2h ). Download figure Open in new tab Fig. 2: Identification of IRF2BP2 target genes including LIPE a-b , Volcano plots showing results from RNA-seq analyses of control (Ctrl) vs. IRF2BP2-knockout (KO) ( a ) and Ctrl vs. IRF2BP2-overexpressing (OE) adipocytes ( b ). X axis: fold changes in mRNA levels (log2 transformed) over Ctrl group. Y axis: -log10 (p-value) for significance. c-d , Gene enrichment pathway analysis using Biological Processes (BP) database. c , The top 10 pathways that are: (1) upregulated in KO and (2) downregulated in OE adipocytes. d , The top 10 pathways that are: (1) downregulated in KO and (2) upregulated in OE adipocytes. e , Heatmap showing the expression profile of lipolytic genes in KO and OE adipocytes, relative to control cells. f , Motif analysis of IRF2BP2 binding regions in hAPC subjected to differentiation cocktail for 1 day. g , Venn diagram illustrates the overlap of genes identified from RNA-seq and ChIP-seq analyses. h-i , Expression heatmap of the top 50 IRF2BP2-repressed ( h ) and IRF2BP2-activated genes ( i ) that exhibit nearby IRF2BP2 binding peaks. j , ChIP-seq tracks for IRF2BP2 and H3K27Ac in LIPE , MGLL , HSD11B1 , and NPR3 . k-l , Relative LIPE mRNA levels in: ( k ) Ctrl and KO adipocytes and ( l ) Ctrl and OE adipocytes. m-n , Western blot analysis of LIPE, phospho-LIPE, and GAPDH (loading control) levels in: ( m ) Ctrl and KO adipocytes and ( n ) Ctrl and OE adipocytes. o , Transcription assay showing activity of -5.9 k region of LIPE in immortalized hAPC transfected with control vector (Ctrl) or IRF2BP2-expressing vector. For k , l , o , unpaired two-tailed Student’s t tests were used. To identify genes that may be directly regulated by IRF2BP2, we performed chromatin immunoprecipitation sequencing (ChIP-seq) analysis for IRF2BP2 in hAPC following stimulation with adipogenesis cocktail. Motif analysis of IRF2BP2 binding regions identified a strong enrichment of motifs for several transcription factors, especially AP-1 and C/EBP ( Fig. 2f ). Integrated analysis of RNA-seq and ChIP-seq datasets was used to predict IRF2BP2 direct target genes by identifying genes that contain proximal binding sites and exhibit IRFBP2-regulated expression (repressed and activated, Fig. 2g-i ). Several lipolysis-related genes (i.e. LIPE , MGLL , HSD11B1 and NPR3 ) were identified as potential direct IRF2BP2-repressed genes ( Fig. 2h,j ). Many of these binding regions also displayed peaks of H3K27-acetylation, suggesting that they correspond to regulatory regions ( Fig. 2j ). IRF2BP2 directly represses LIPE transcription We next focused on the IRF2BP2-regulation of LIPE , which encodes the rate-limiting enzyme in adipocyte lipolysis. qRT-PCR analysis showed that LIPE mRNA levels were increased (∼1.8 fold) by IRF2BP2 deletion and reduced (∼60%) by IRF2BP2 OE in human adipocytes ( Fig. 2k,l ) . LIPE protein levels were similarly regulated, with IRF2BP2-KO cells displaying increased LIPE protein levels and IRF2BP2-OE cells displaying lower LIPE levels compared to control cells ( Fig. 2m,n ) . Levels of phosphorylated (activated) LIPE followed a similar expression pattern ( Fig. 2m,n ). To determine if the IRF2BP2-binding region located 5.9 kb upstream of the LIPE transcriptional start site is regulated by IRF2BP2, we performed luciferase-based transcription assays in an immortalized hAPC cell line. IRF2BP2 expression decreased the transcriptional activity of this putative regulatory region by about 70%, relative to the vector control ( Fig. 2o ). These results suggest that IRF2BP2 represses LIPE transcription via binding to the -5.9 kb region. Adipocyte IRF2BP2 deficiency increases lipolysis and inflammation in mice We next sought to determine the in vivo role of IRF2BP2 in adipocytes. To do this, we generated adipocyte-selective Irf2bp2 knockout (AKO) mice by interbreeding Irf2bp2 flox and Adiponectin ( Adipoq )- Cre mice. Irf2bp2 mRNA levels were significantly reduced in inguinal white adipose tissue (iWAT) and epididymal WAT (eWAT) of 12-week-old AKO compared to control mice ( Fig. 3a ). IRF2BP2 protein levels were also substantially reduced in WAT from AKO mice ( Fig. 3b ). Notably, Irf2bp2 mRNA and protein levels were significantly higher in iWAT compared to eWAT ( Fig. 3a,b ). AKO and control mice had similar body weights at 12-weeks of age ( Fig. 3c ). iWAT weight was reduced by ∼25% in AKO mice compared to control mice, with no significant differences in either eWAT or brown adipose tissue (BAT) weights ( Fig. 3d,e ). H&E staining of iWAT sections showed that adipocyte size was reduced in iWAT of AKO compared to control mice, which likely accounts for the reduction in depot weight ( Fig. 3f,g ) . Circulating FFA was substantially elevated (∼75% higher) in AKO mice compared to control mice ( Fig. 3h ) . Consistent with the results in human adipocytes, Lipe expression was significantly elevated in iWAT (2-fold increased) and eWAT (1.5-fold increase) of AKO compared to control mice ( Fig. 3i ) . iWAT from AKO mice also expressed slightly higher levels of Mgll ( Fig. 3j ) . Irf2bp2 deficiency did not affect the expression of Adipoq , or the lipogenic genes Fasn , Scd , and Acly ( Fig. 3k ) . Fasting for 16 hours reduced WAT weights and increased circulating NEFA levels to similar levels in control and AKO mice ( Extended data Fig. 3a,b ). Download figure Open in new tab Fig. 3: Adipocyte-specific deletion of Irf2bp2 increases LIPE expression, lipolysis, and inflammation in adipose tissue Control and adipocyte-specific Irf2bp2 knockout mice (AKO) were assessed as follows. a , Relative Irf2bp2 mRNA levels in inguinal WAT (iWAT) and epididymal WAT (eWAT). b , Western blot analysis of IRF2BP2 and GAPDH (loading control) protein levels in iWAT and eWAT. Protein quantification was performed with imageJ. c , Body weights (n=9). d-e , Weights of: ( d ) brown adipose tissue (BAT), and ( e ) iWAT and eWAT (n=9). f , H&E staining of iWAT (scale bar, 50 um). g , Quantification of adipocyte cell size in iWAT (n=7). h , Circulating NEFA levels under ad libitum fed conditions (n=8). i , Relative Lipe mRNA levels in iWAT and eWAT (n=7). j , Relative mRNA levels of Pnpla2 and Mgll in iWAT and eWAT (n=7). k , Relative mRNA levels of adipocyte genes Adipoq , Fasn , Scd , and Acly in iWAT (n=7). l , Relative mRNA levels of inflammatory genes Adgre1 (F4/80), Il1b , Il6 , and Ccl2 ( Mcp1 ) in iWAT (n=7). m-n , Flow cytometry analysis of F4/80+; CD11c+ (CD45+) cells in stromal vascular cells from iWAT ( m ) and eWAT ( n ) (n=3). In a , b , e , h , i , j , l , m , and n , unpaired two-tailed Student’s t tests were applied. Two-way ANOVA followed by Sidak’s test was applied for g . Elevations in adipose tissue lipolysis and FFA are linked with macrophage recruitment, inflammation and metabolic dysfunction 35 , 36 . Consistent with this, we found that the expression of pro-inflammatory genes, including the macrophage marker Adgre1 (i.e. F4/80 ), inflammatory cytokines Il1b , Il6 and chemokine Ccl2 were increased in iWAT of AKO versus control mice ( Fig. 3l ). Furthermore, flow cytometry analysis revealed a ∼2.5-fold increase in the proportion of pro- inflammatory F4/80 + ;CD11c + cells in the stromal-vascular fraction of iWAT from AKO compared to control mice ( Fig. 3m ). The proportion of F4/80 + /CD11c + cells was also increased, but to a lesser extent, in the eWAT of AKO mice ( Fig. 3n ). Additionally, the circulating levels of inflammatory cytokines, IL6, IL1β, and MCP-1 trended to be higher in Irf2bp2 AKO compared to control mice ( Extended Data Fig. 3c-e ). Hepatic triglyceride levels were increased in AKO mice, suggesting that adipose tissue-derived fatty acids accumulated in liver ( Extended Data Fig. 3f ). Together, these data indicate that IRF2BP2 represses adipocyte Lipe expression and suppresses lipolysis under basal conditions in mice. Adipocyte IRF2BP2 deficiency causes glucose intolerance in mice We further tested if the action of IRF2BP2 in adipocytes regulates systemic glucose metabolism and insulin sensitivity. We found that fasting glucose levels were significantly elevated in AKO mice compared to control mice at 12 weeks of age ( Fig. 4a ). During a glucose tolerance test (GTT), Irf2bp2 AKO mice exhibited higher blood glucose levels at each time point, with significant differences at 15 and 30 minutes ( Fig. 4b ). The area under the curve (AUC) for GTT was higher in Irf2bp2 knockout mice ( Fig. 4c ). AKO mice also displayed reduced glucose-lowering effects of insulin during an insulin tolerance test (ITT), with elevated blood glucose levels at 0, 15, 60, 90, and 120 minutes ( Fig. 4d,e ). The data suggests that IRF2BP2-mediated suppression of basal lipolysis is required to maintain systemic glucose homeostasis. Download figure Open in new tab Fig. 4: Adipocyte IRF2BP2 deficiency causes glucose intolerance a-d , Analysis of metabolic parameters in 12-14 week-old control (Ctrl) and adipocyte-specific Irf2bp2 knockout (AKO) mice (n=8-10). a , Fasting glucose levels. b , Intraperitoneal glucose tolerance test (GTT). c , GTT area under the curve (AUC) values from ( b ). d , Intraperitoneal insulin tolerance test (ITT). e , ITT AUC values from ( d ). f, Correlation between Irf2bp2 mRNA levels in subcutaneous adipose tissue and serum free fatty acid (FFA) levels in 42 mouse strains (data extracted from GeneNetwork database, EPFL LISP3 Cohort) 37 . g , Correlation between IRF2BP2 and LIPE mRNA levels in subcutaneous adipose tissue from healthy, non-diabetic female subjects (n=39). h , IRF2BP2 mRNA levels in subcutaneous adipose tissue from diabetic (n=31) and non-diabetic individuals (n=39). i , Working model: (left) IRF2BP2 transcriptionally represses LIPE expression in adipocytes to decrease the rate of lipolysis. (right) Loss of IRF2BP2 (or its downregulation in diabetes) increases lipolysis, leading to inflammation and impaired metabolic homeostasis. In a , c , e , h , unpaired two-sided t-tests were utilized. Two-way ANOVA followed by Sidak’s test was used in b , d . Person correlational analysis was performed in f and g . IRF2BP2 levels correlate with lipolysis markers in mice and humans We next assessed if IRF2BP2 expression levels correlate with markers of lipolysis in mouse and human cohorts. In the GeneNetwork cohort consisting of 42 different normal mouse strains 37 , Irf2bp2 mRNA was significantly negatively correlated (r coefficient equals to -0.47) with circulating FFA levels ( Fig. 4f ). These data further support the role of IRF2BP2 as a negative regulator of adipocyte lipolysis in mice. To explore associations between IRF2BP2 and lipolysis in humans, we collected subcutaneous adipose tissue samples from non-diabetic (n=39) and diabetic subjects (n=31) for expression analysis by qRT-PCR. In the non-diabetic human cohort (n=39), IRF2BP2 mRNA levels were negatively correlated (r=-0.47) with LIPE mRNA levels in subcutaneous adipose tissue ( Fig. 4g ). Interestingly, IRF2BP2 mRNA levels were slightly (∼20%), but significantly decreased in adipose tissue from diabetic patients, compared to non-diabetic individuals ( Fig. 4h ). Taken together, these studies strongly support a conserved role of IRF2BP2 in restraining LIPE expression and lipolysis in mice and humans. Discussion Dysregulated adipocyte lipolysis promotes the development of insulin resistance and cardiometabolic disease. In this study, we identified a novel role for the transcriptional cofactor IRF2BP2 as a repressor of adipocyte lipolysis. In human adipocytes, increased expression of IRF2BP2 decreased NEFA release, while loss of IRF2BP2 increased NEFA levels. In mice, deletion of IRF2BP2 in adipocytes elevated NEFA levels, and led to increased adipose tissue inflammation and systemic insulin resistance. Our results suggest that IRF2BP2 restrains basal adipocyte lipolysis, but does not regulate the lipolytic response to catecholamines. In this regard, isoproterenol induced similar fold increases in lipolysis (i.e. NEFA levels) in IRF2BP2-expressing or IRF2BP2-deficient adipocytes relative to control adipocytes. Moreover, control and adipocyte-selective Irf2bp2 knockout mice exhibited comparably high levels of circulating NEFA levels following a 16-hour fasting. Interestingly, the rate of basal (or resting) adipocyte lipolysis increases in obesity and correlates with cardiometabolic complications 38 , 39 . Additional studies indicate that lipolysis is increased in the early phase of impaired glucose tolerance in humans 40 , 41 . Mechanistically, fatty acids released by excessive lipolysis trigger pro-inflammatory cytokine production (i.e. IL-6, IL-1β, TNF-α) and provoke tissue inflammation 42 , 43 . Consistent with this, adipocyte-selective deletion of Irf2bp2 led to adipose tissue inflammation and systemic insulin resistance in the absence of high fat diet or weight gain. These results suggest that chronic high levels of basal lipolysis are sufficient to trigger inflammation and insulin resistance. Our results suggest that IRF2BP2 controls the rate of lipolysis via regulating the transcription of LIPE , which encodes the key lipolytic enzyme HSL. Previous studies revealed that upstream stimulatory factor (USF) and PPARγ bind to the LIPE promoter and modulate its transcription 24 , 25 . Our ChIP-seq analysis identified IRF2BP2 binds to a putative upstream enhancer region in the human LIPE gene. Previous studies suggest that IRF2BP2 functions as a transcriptional co-factor. Motif analysis of IRF2BP2 binding regions in adipocytes suggest that IRF2BP2 may interact with one or more member(s) of the AP-1 family of transcription factors e.g. ATF2, JUN FOS proteins to regulate LIPE enhancer activity. In this regard, IRF2BP2 was recently shown to interact and repress the function of the AP-1 heterodimer ATF7/JDP2 in leukemia cells 44 . Studies employing JNK upstream kinase of JUN) and p38 (downstream effector of ATF2) inhibitors 45 , 46 suggest that adipocyte lipolysis may be regulated by ATF2 and JUN, although the involved mechanisms remain unclear. Further studies are required to determine if IRF2BP2 interacts with AP-1 transcription factors to control LIPE expression and lipolysis in adipocytes. Moreover, our results show that IRF2BP2 regulates many other genes involved in lipolysis and adipocyte function, suggesting additional effects of IRF2BP2 beyond its regulation of LIPE levels. Deletion of Irf2bp2 had a more pronounced effect in the subcutaneous iWAT as compared to the visceral eWAT depot. It is well-established that iWAT and eWAT exhibit distinct responses to metabolic and inflammatory signals 47 . eWAT undergoes higher rates of lipolysis 47 and harbors more pro-inflammatory macrophages 48 . This may be related to the significantly higher expression levels of IRF2BP2 in iWAT. Thus, while IRF2BP2 disruption led to increased inflammation in both iWAT and eWAT, the effect was more consequential in iWAT due to its lower baseline levels. Future studies are warranted to explore the differential regulation and roles of IRF2BP2 in different fat depots. Reducing fatty acid levels can ameliorate insulin action and improve cardiometabolic health, underscoring the therapeutic potential of targeting this pathway 3 , 5 , 49 , 50 , 51 . For example, treatment of mice with the ATGL inhibitor, atglistatin, lowers circulating fatty acids, decreases adipose inflammation, reduces liver fat, and ameliorates glucose homeostasis 50 . Similar findings are observed in Mgll mutant mice, Lipe haploinsufficient mice, and in mice treated with a LIPE inhibitor 3 , 51 . Increasing the function of IRF2BP2 in adipocytes may provide a selective strategy to blunt basal lipolysis and limit chronic inflammation for therapeutic benefit. Materials and Methods Mice The mice used in our study were housed and cared for by the University of Pennsylvania University Laboratory Animal Resources (ULAR) in accordance with the guidelines set forth by the University of Pennsylvania Institutional Animal Care and Use Committee (IACUC). All animal procedures were performed following the guidance of the IACUC. Mice were maintained at room temperature on a normal chow diet and subjected to a 12-hour light/dark cycle unless specified otherwise. Adipoq-Cre mice were obtained from Jackson Laboratory (strain name: B6;FVB-Tg(Adipoq-cre)1dEvdr/J, RRID:IMSR_JAX:010803) 52 . The Irf2bp2 loxP/loxP strain was kindly provided by Dr. Alex Stewart 27 . Mice were euthanized by CO 2 asphyxiation, followed by cervical dislocation. Blood (fed condition) was collected by cardiac puncture and subjected to centrifuge for plasma non-esterified fatty acids (NEFA) determination (HR series NEFA, WAKO). Fat tissues were immersed in 4% freshly prepared formaldehyde for histology analysis or immediately cryopreserved for protein and mRNA analysis. Mouse metabolic phenotyping Glucose tolerance test (GTT) and insulin tolerance test (ITT) were conducted in male mice aged 12-14 weeks. For GTTs, a 6 h fasting period preceded the intraperitoneal (i.p.) administration of 1.5 g of glucose per kilogram, delivered as a 20% D-glucose solution dissolved in sterile water. For ITTs, mice were fasted for 4 h, followed by a bolus i.p. injection of 0.65 U/kg insulin (Humulin, Novo Nordisk). Blood glucose levels were monitored from the tail-tip using an automatic glucometer (Contour Next, Bayer) at baseline and at 15, 30, 60, 90, and 120 minutes post-injection. Adipose tissue flow cytometry analysis Stromal vascular cells were isolated from adipose tissue depots for analysis. Dissected and minced adipose tissue was washed in PBS followed by digestion in DMEM/F12 medium (Gibco Invitrogen) containing 2.4 U/ml of dispase, 1.5 U/mL of type I collagenase (Gibco Invitrogen), and 1% bovine serum albumin (BSA) at 37°C incubator with constant shaking for 30 minutes. The digestion was quenched with DMEM/F12 medium supplemented with 10% fetal bovine serum (FBS). The digested cell suspension was filtered through a 100 μm mesh filter (BD Biosciences) and centrifuged at 400 × g for 4 minutes at 4 °C. Red blood cells were lysed by incubating cell suspensions in a hemolysis buffer for 4 minutes. Cells were suspended in FBS-containing medium and further filtered using a 70 μm and a 40 μm mesh, followed by centrifugation (400 x g, 4 minutes). Cell pellets were re-suspended in FACS buffer (0.5% BSA, 2 mM EDTA in PBS) and incubated with fluorophore-conjugated antibodies for 45 minutes at 4°C in the dark. The following antibodies were used: CD45-APC/Cy7 (103116, BioLegend), F4/80-APC (123116, BioLegend), and CD11c-PE (12-0114-82, eBioscience). DAPI was used for viability staining. After three washes with FACS buffer, stained cells were suspended in 200 µL of FACS buffer for analysis. The CytoFlex Flow Cytometer (Beckman) was used to acquire 40,000 events for each sample. Unstained and single stain controls were used for setting compensation and gates. Debris, cell aggregation and dead cells (DAPI + ) were excluded. Macrophages were identified as CD45 + ;F4/80 + , and M1 macrophages were identified as CD45 + ;F4/80 + ;CD11c + . Data was analyzed using FlowJo v10 (Flowjo). Cytokine multiplex array assay Mouse plasma samples were diluted 2-fold with PBS and subjected to cytokine multiplexing analysis using the Luminex 200 system (Luminex, Austin, TX, USA) by Eve Technologies Corp. We utilized the mouse Focused 10-Plex Discovery Assay (Millipore Sigma) according to the manufacturer’s protocol. Hepatic triglyceride measurement Liver samples from male mice (age 12-14 weeks) weighing 50-100 mg were homogenized using a tissue lyser (25 Hz, 5 min) in a lysis buffer composed of 140 mM NaCl, 2.5% Triton-X, 0.2% sodium deoxycholate, and 50 mM Tris pH 7.4. Triglyceride levels were quantified employing the Stanbio Triglyceride LiquiColor kit. Following the manufacturer’s instructions, 2 µl of the sample or standard was added to 200 µl of the TG enzymatic mix, incubated for 10 minutes, and the reactions were subsequently assayed in a plate reader at 500 nm. Human adipose tissue-derived precursor cells (hAPC) and adipogenic differentiation hAPC were obtained from subcutaneous adipose tissue samples collected through lipoaspiration. hAPC were differentiated into mature adipocytes using DMEM/F12 medium supplemented with 10% FBS and treated with a standard cocktail consisting of 2.5X10 -8 M insulin, 10 -5 M dexamethasone, 5X10 -4 M IBMX, and 10 -6 M rosiglitazone for 14 days. For ChIP and luciferase assays, hAPC were treated with the above differentiation cocktail without rosiglitazone. Lentivirus transduction hAPC were seeded in 60 mm or 100 mm culture dishes and transduced with lentivirus using the lentivirus viraductin kit from Cell Biolabs. Lentivirus used in the experiments were produced by HEK239T cells (ATCC) in 150mm dishes. Lentivirus for IRF2BP2 knockout was produced using lentiCRISPR v2 (Addgene plasmid # 52961) carrying guide RNAs (gRNAs) targeting IRF2BP2 . The gRNAs were designed using CRISPOR 53 and IDT CRISPR web design tools and synthesized by IDT. IRF2BP2 OE lentivirus was produced using plenti backbone plasmid (Addgene plasmid # 17448) containing the full-length coding sequence cloned from hAPC. Plasmid sequences were confirmed by Sanger sequencing (Genewiz). qRT-PCR and RNA-seq analysis Tissue RNA was harvested using Trizol (Invitrogen) according to the manufacturer’s protocol. Reverse transcription reactions were performed with High Capacity cDNA Reverse Transcription Kit (Thermo Fisher). Quantitative real time PCR (qRT-PCR) was performed using PowerUp SYBR Green Master Mix (Thermo Fisher Scientific) on a QuantStudio 5 instrument (Thermo Fisher Scientific). Primers used for qRT-PCR reactions were summarized in Extended Table 1 . Relative gene expression levels were calculated by the ddCt method using the house-keeping gene GADPH (human) or Gapdh (mouse) as control. For RNA-seq, extracted cellular total RNA samples were sequenced by NovaSeq 6000 PE150 (Novogene). The raw paired-end Fastq files were trimmed using the tool TrimGalore (version 0.6.5) with default parameters and paired option enabled. The trimmed files were then aligned to the GRCh38 (version 104) genome using kallisto (version 0.46.1) with the default parameters of the kallisto quant command for paired-end data 54 . Kallisto output files were read into R (version 4.3.0) and differentially expressed genes were generated by EdgeR (version 4.0.2) 55 . Volcano plots were generated using the package ggplot2 (version 3.4.4) where genes with a p-value less than 0.05 were colored based on expression. The enrichment analysis was performed with gprofiler2 (version 0.2.2) using genes with a false discovery rate less than 0.1, positive or negative logFC cutoff, and being ordered by significance. A gSCS correction method was applied to the enriched terms, organism was set to hsapiens, ordered query to TRUE, a cutoff of 0.001 for significance, and using the "Biological Processes" as the source. The top enriched pathways were plotted into bar graphs using the ggplot2 package where the terms were ordered based on p-value for merged datasets. Heatmaps were generated using packages ComplexHeatmap (version 2.16.0) and pheatmap (version 1.0.12). Rows were scaled to their relative scores (Z-score) for both heatmaps. In Extended Figure 2 , heatmaps rows were clustered in ComplexHeatmap by their Euclidean distances with a ward.D2 clustering method, and a k-means clustering of 4. The Venndiagram was generated using genes with a positive or negative foldchange and a false discovery rate cutoff of 0.1 in which genes were compared between the different datasets to evaluate overlapping differentially expressed genes across conditions for the RNA-seq. Lipolysis and glucose uptake in adipocytes Fully differentiated adipocytes were serum starved overnight in DMEM/F12 medium. The cells were then treated with 2% BSA, serum-free medium containing either PBS (control) or 10 -6 M isoproterenol for 4 h, and culture medium was collected for NEFA assessment (HR series NEFA, WAKO) following the manufacturer’s instructions. Briefly, 20 μl of the sample was added with 180 μl of solution A, followed by 60 ul of solution B. The absorbance was measured in a colorimetric plate reader at a wavelength of 550 nm. NEFA values were normalized to protein content, which was determined using Pierce BCA Protein assay. Glucose uptake was determined using a Promega Assay Kit (J1342). Briefly, overnight serum-starved adipocytes were washed with PBS, followed by treatment with 10 - 8 M insulin for 1 h in glucose-free medium. Cells were then subjected to 2-DG uptake, acid termination, neutralization, and luminescence measurement. Western blotting Cells were lysed with RIPA lysis buffer (NaCl 150 mM, NP-40 1%, sodium deoxycholate 0.5%, SDS 0.1%, 50 mM Tris pH 7.4) containing protease inhibitors (Roche), phosphatase inhibitors (Thermo Fisher Scientific), and 100 uM PMSF (Sigma). Adipose tissue depots were homogenized in RIPA buffer using the Qiagen TissueLyser (28 hz, 4 min). Tissue homogenates were kept on ice for 30 min with intermittent vortex, followed by 2-3 rounds of centrifugation (15 min, 12000 g) to remove cell debris and lipids. Protein concentration was determined by BCA assay. 30 ug lysates were separated on precast 4-12% bis-tris NuPage gels (Thermo Fisher Scientific) and transferred to PVDF membranes. Proteins were detected using primary antibodies against IRF2BP2 (A303-190A, Bethyl Laboratories), phospho-LIPE (4126S, Cell Signaling, Danvers, MA), LIPE (4107S, Cell Signaling), and GAPDH (MA5-15738, Thermo Fisher Scientific). Horseradish-peroxidase-conjugated secondary antibodies i.e. anti-mouse (7076S, Cell Signaling) and anti-rabbit (7074S, Cell Signaling) were used, followed by SuperSignal West Pico PLUS ECL detection (Thermo Fisher Scientific). Blotting images were scanned using Amersham ImageQuant 800 (Cytiva). Bands were quantified using ImageJ. Dual-luciferase reporter assay Luciferase reporter assay was performed as previously described 56 . Immortalized hAPC were seeded in 48-well plates. Cells were treated with the differentiation cocktail of insulin, dexamethasone, and IBMX for 24 h, followed by transfection using lipofectamine 3000 method (Thermo Fisher Scientific). For 1 well, 0.75 ul lipo3000 and P3000 diluted with Opti-MEM medium (Thermo Fisher Scientific) were used. 200 ng of firefly luciferase enhancer reporter vector was co-transfected with 200 ng of IRF2BP2 or empty pcDNA3.1 vector, with 5 ng of PGK promoter- driven renilla luciferase as a normalization control for transfection efficiency. Cells were harvested 48 h post-transfection and lysates were subjected to luminescence measurement. Luciferase assay was performed using dual-luciferase reporter assay (E1910, Promega) according to the manufacturer’s instructions. ChIP and CUT & RUN sequencing ChIP was performed as described previously 57 . Cells were treated with the differentiation cocktail of insulin, dexamethasone, and IBMX for 24 h prior to chromatin collection. Sonicated input sample (10% of total chromatin) was saved and subjected to crosslink reversing and column purification. Sonicated chromatin samples were incubated overnight at 4°C with IRF2BP2 antibody in 1 ml ChIP buffer (50 mM HEPES pH 7.8, 140 mM NaCl, 1% Triton X-100, 0.1% Na- Deoxycholate and Complete protease inhibitor). IP was washed and then eluted by incubation at 65°C overnight in 50 μl ChIP elution buffer (50 mM Tris pH 7.5, 10 mM EDTA, 1% SDS) with 10 mM DTT. Beads were pelleted and the supernatant was transferred to a new tube. DNA was subsequently isolated by columns (NucleoSpin, Takara). H3K27ac CUT & RUN experiment was similarly performed in hAPC following manufacturer’s protocol (86652, Cell Signaling). DNA bound by H3K27Ac (Active Motif) or IgG (Millipore) was collected. ChIP and CUT& RUN libraries were prepared and sent for next-generation sequencing (Novogene). Sequencing data was analyzed as previously reported 58 . Briefly, reads were aligned using Bowtie2 (version 2.5.0), followed by MACS2 (version 2.2.8) peak calling and Homer (version 4.11) annotation and motif enrichment. Histology Tissues were fixed in 4% PFA overnight, washed in PBS, dehydrated in ethanol, paraffin- embedded and sectioned. Sections were stained with hematoxylin and eosin. Images were captured on a Keyence inverted microscope. Adipocyte size was quantified with ImageJ software. IRF2BP2 correlational studies in mice and humans Irf2bp2 mRNA transcript expression and free fatty acid (FFA) levels in 42 mouse strains were determined using data extracted from GeneNetwork database (i.e. EPFL LISP3 Cohort) 37 . We assessed the mRNA levels of IRF2BP2 , LIPE , and GAPDH (normalization control) in subcutaneous adipose tissue samples from non-diabetic (n=39) and diabetic (n=31) female subjects that underwent bariatric surgery with an approved IRB protocol at Hospital of the University of Pennsylvania. Statistical analysis Data analysis was performed with GraphPad Prism 10 software. No power calculations were performed prior to initiation of the study. All individual data points were plotted to assay normality. Data normality was assessed with Shapiro-Wilk test. For normally distributed data, two-sided t tests were performed where comparisons between two groups were being assayed. Nonparametric Mann-Whitney test was applied for data that were not normally distributed. Two- way and one-way ANOVA with pairwise comparisons were performed where comparisons between more than two groups were being assayed in cell or mice studies. Correlational analysis was performed using Graphpad. Funding This work was supported by NIH grants R01 DK121801, R01 DK120982, and UM1 DK126194 to P.S.; and American Heart Association grant 826869 to Y.C. Author Contributions L.L., R.C., L.C., and D.M. were involved in study design, conceived the idea, conducted the experiments, analyzed the data and drafted the paper; Y.C., D.S., and L.L. designed the study and performed the experiments; P.S. designed and supervised the study, obtained the funding and cowrote the paper. Competing Interests All authors declare no competing interests. Acknowledgments We are grateful for the Irf2bp2 loxP/loxP mouse strain kindly provided by Dr. Alex Stewart from the University of Ottawa Heart Institute. We thank Dr. Jeff Ishibashi for his excellent technical support for CRISPR design. References 1. ↵ Sakers A , De Siqueira MK , Seale P , Villanueva CJ . Adipose-tissue plasticity in health and disease . Cell 185 , 419 – 446 ( 2022 ). OpenUrl CrossRef 2. ↵ Kashyap S , et al. A sustained increase in plasma free fatty acids impairs insulin secretion in nondiabetic subjects genetically predisposed to develop type 2 diabetes . Diabetes 52 , 2461 – 2474 ( 2003 ). OpenUrl Abstract / FREE Full Text 3. ↵ Taschler U , et al. Monoglyceride Lipase Deficiency in Mice Impairs Lipolysis and Attenuates Diet-induced Insulin Resistance* . Journal of Biological Chemistry 286 , 17467 – 17477 ( 2011 ). OpenUrl Abstract / FREE Full Text 4. ↵ Morigny P , Houssier M , Mouisel E , Langin D. Adipocyte lipolysis and insulin resistance . Biochimie 125 , 259 – 266 ( 2016 ). OpenUrl CrossRef PubMed 5. ↵ Takahara S , et al. Inhibition of ATGL in adipose tissue ameliorates isoproterenol-induced cardiac remodeling by reducing adipose tissue inflammation . Am J Physiol Heart Circ Physiol 320 , H432 – h446 ( 2021 ). OpenUrl 6. ↵ Kintscher U , Foryst-Ludwig A , Haemmerle G , Zechner R . The Role of Adipose Triglyceride Lipase and Cytosolic Lipolysis in Cardiac Function and Heart Failure . Cell Rep Med 1 , 100001 ( 2020 ). 7. ↵ Schweiger M , Lass A , Zimmermann R , Eichmann TO , Zechner R . Neutral lipid storage disease: genetic disorders caused by mutations in adipose triglyceride lipase/PNPLA2 or CGI-58/ABHD5 . American journal of physiology Endocrinology and metabolism 297 , E289 – 296 ( 2009 ). OpenUrl CrossRef PubMed Web of Science 8. ↵ Zolotov S , Xing C , Mahamid R , Shalata A , Sheikh-Ahmad M , Garg A . Homozygous LIPE mutation in siblings with multiple symmetric lipomatosis, partial lipodystrophy, and myopathy . Am J Med Genet A 173 , 190 – 194 ( 2017 ). OpenUrl 9. ↵ Grabner GF , Xie H , Schweiger M , Zechner R . Lipolysis: cellular mechanisms for lipid mobilization from fat stores . Nat Metab 3 , 1445 – 1465 ( 2021 ). OpenUrl 10. ↵ Pereira MJ , et al. Direct effects of glucagon on glucose uptake and lipolysis in human adipocytes . Mol Cell Endocrinol 503 , 110696 ( 2020 ). 11. ↵ Yang A , Mottillo EP . Adipocyte lipolysis: from molecular mechanisms of regulation to disease and therapeutics . Biochem J 477 , 985 – 1008 ( 2020 ). OpenUrl CrossRef PubMed 12. ↵ Sengenes C , et al. Involvement of a cGMP-dependent pathway in the natriuretic peptide- mediated hormone-sensitive lipase phosphorylation in human adipocytes . J Biol Chem 278 , 48617 – 48626 ( 2003 ). OpenUrl Abstract / FREE Full Text 13. ↵ Carper D , et al. Atrial Natriuretic Peptide Orchestrates a Coordinated Physiological Response to Fuel Non-shivering Thermogenesis . Cell reports 32 , 108075 ( 2020 ). 14. ↵ Pagnon J , et al. Identification and functional characterization of protein kinase A phosphorylation sites in the major lipolytic protein, adipose triglyceride lipase . Endocrinology 153 , 4278 – 4289 ( 2012 ). OpenUrl CrossRef PubMed Web of Science 15. ↵ Choi SM , et al. Insulin regulates adipocyte lipolysis via an Akt-independent signaling pathway . Mol Cell Biol 30 , 5009 – 5020 ( 2010 ). OpenUrl Abstract / FREE Full Text 16. ↵ Chakrabarti P , et al. Insulin inhibits lipolysis in adipocytes via the evolutionarily conserved mTORC1-Egr1-ATGL-mediated pathway . Mol Cell Biol 33 , 3659 – 3666 ( 2013 ). OpenUrl Abstract / FREE Full Text 17. ↵ Snyder PB , Esselstyn JM , Loughney K , Wolda SL , Florio VA . The role of cyclic nucleotide phosphodiesterases in the regulation of adipocyte lipolysis . J Lipid Res 46 , 494 – 503 ( 2005 ). OpenUrl Abstract / FREE Full Text 18. ↵ Sancar G , et al. FGF1 and insulin control lipolysis by convergent pathways . Cell Metab 34 , 171 – 183 .e176 ( 2022 ). OpenUrl 19. ↵ Choi WG , et al. Inhibiting serotonin signaling through HTR2B in visceral adipose tissue improves obesity-related insulin resistance . J Clin Invest 131 , ( 2021 ). 20. ↵ Li J , et al. Adipose HuR protects against diet-induced obesity and insulin resistance . Nat Commun 10 , 2375 ( 2019 ). 21. ↵ Wang Y , et al. ApoL6 associates with lipid droplets and disrupts Perilipin1-HSL interaction to inhibit lipolysis . Nature Communications 15 , 186 ( 2024 ). 22. ↵ Kimura T , et al. Adipocyte Gq signaling is a regulator of glucose and lipid homeostasis in mice . Nature Communications 13 , 1652 ( 2022 ). 23. ↵ Yu HC , et al. p21-activated kinase 4 counteracts PKA-dependent lipolysis by phosphorylating FABP4 and HSL . Nature Metabolism 6 , 94 – 112 ( 2024 ). OpenUrl 24. ↵ Smih F , et al. Transcriptional Regulation of Adipocyte Hormone-Sensitive Lipase by Glucose . Diabetes 51 , 293 – 300 ( 2002 ). OpenUrl Abstract / FREE Full Text 25. ↵ Deng T , et al. Peroxisome Proliferator-Activated Receptor-γ Transcriptionally Up- Regulates Hormone-Sensitive Lipase via the Involvement of Specificity Protein-1 . Endocrinology 147 , 875 – 884 ( 2006 ). OpenUrl CrossRef PubMed Web of Science 26. ↵ Stenson BM , et al. Liver X receptor (LXR) regulates human adipocyte lipolysis . J Biol Chem 286 , 370 – 379 ( 2011 ). OpenUrl Abstract / FREE Full Text 27. ↵ Chen HH , et al. IRF2BP2 Reduces Macrophage Inflammation and Susceptibility to Atherosclerosis . Circ Res 117 , 671 – 683 ( 2015 ). OpenUrl Abstract / FREE Full Text 28. ↵ Sécca C , et al. IRF2BP2 transcriptional repressor restrains naive CD4 T cell activation and clonal expansion induced by TCR triggering . J Leukoc Biol 100 , 1081 – 1091 ( 2016 ). OpenUrl CrossRef PubMed 29. ↵ Fang J , et al. Control of Pathological Cardiac Hypertrophy by Transcriptional Corepressor IRF2BP2 (Interferon Regulatory Factor-2 Binding Protein 2) . Hypertension 70 , 515 – 523 ( 2017 ). OpenUrl CrossRef PubMed 30. ↵ Fang J , et al. Hepatic IRF2BP2 Mitigates Nonalcoholic Fatty Liver Disease by Directly Repressing the Transcription of ATF3 . Hepatology 71 , 1592 – 1608 ( 2020 ). OpenUrl CrossRef 31. ↵ Childs KS , Goodbourn S . Identification of novel co-repressor molecules for Interferon Regulatory Factor-2 . Nucleic Acids Res 31 , 3016 – 3026 ( 2003 ). OpenUrl CrossRef PubMed Web of Science 32. ↵ Ramalho-Oliveira R , Oliveira-Vieira B , Viola JPB . IRF2BP2: A new player in the regulation of cell homeostasis . J Leukoc Biol 106 , 717 – 723 ( 2019 ). OpenUrl CrossRef PubMed 33. ↵ Hoffmann TJ , et al. A large electronic-health-record-based genome-wide study of serum lipids . Nat Genet 50 , 401 – 413 ( 2018 ). OpenUrl CrossRef 34. ↵ Emont MP , et al. A single-cell atlas of human and mouse white adipose tissue . Nature 603 , 926 – 933 ( 2022 ). OpenUrl CrossRef PubMed 35. ↵ Tripathy D , et al. Elevation of Free Fatty Acids Induces Inflammation and Impairs Vascular Reactivity in Healthy Subjects . Diabetes 52 , 2882 – 2887 ( 2003 ). OpenUrl Abstract / FREE Full Text 36. ↵ Kennedy A , Martinez K , Chuang CC , LaPoint K , McIntosh M . Saturated fatty acid- mediated inflammation and insulin resistance in adipose tissue: mechanisms of action and implications . J Nutr 139 , 1 – 4 ( 2009 ). OpenUrl Abstract / FREE Full Text 37. ↵ Williams EG , et al. Systems proteomics of liver mitochondria function . Science 352 , aad0189 ( 2016 ). 38. ↵ Coppack SW , Jensen MD , Miles JM . In vivo regulation of lipolysis in humans . J Lipid Res 35 , 177 – 193 ( 1994 ). OpenUrl Abstract 39. ↵ Rydén M , Arner P . Subcutaneous Adipocyte Lipolysis Contributes to Circulating Lipid Levels. Arteriosclerosis , Thrombosis, and Vascular Biology 37 , 1782 – 1787 ( 2017 ). OpenUrl 40. ↵ Kim JY , Nasr A , Tfayli H , Bacha F , Michaliszyn SF , Arslanian S. Increased Lipolysis, Diminished Adipose Tissue Insulin Sensitivity, and Impaired β-Cell Function Relative to Adipose Tissue Insulin Sensitivity in Obese Youth With Impaired Glucose Tolerance . Diabetes 66 , 3085 – 3090 ( 2017 ). OpenUrl Abstract / FREE Full Text 41. ↵ Fryk E , et al. Hyperinsulinemia and insulin resistance in the obese may develop as part of a homeostatic response to elevated free fatty acids: A mechanistic case-control and a population-based cohort study . EBioMedicine 65 , 103264 ( 2021 ). 42. ↵ Kosteli A , et al. Weight loss and lipolysis promote a dynamic immune response in murine adipose tissue . J Clin Invest 120 , 3466 – 3479 ( 2010 ). OpenUrl CrossRef PubMed Web of Science 43. ↵ Wang L , Gill R , Pedersen TL , Higgins LJ , Newman JW , Rutledge JC . Triglyceride-rich lipoprotein lipolysis releases neutral and oxidized FFAs that induce endothelial cell inflammation . J Lipid Res 50 , 204 – 213 ( 2009 ). OpenUrl Abstract / FREE Full Text 44. ↵ Fischer S , et al. IRF2BP2 counteracts the ATF7/JDP2 AP-1 heterodimer to prevent inflammatory overactivation in acute myeloid leukemia (AML) cells . Nucleic Acids Res , ( 2024 ). 45. ↵ Du X , et al. Tumor necrosis factor-α promotes lipolysis and reduces insulin sensitivity by activating nuclear factor kappa B and c-Jun N-terminal kinase in primary bovine adipocytes . J Dairy Sci 105 , 8426 – 8438 ( 2022 ). OpenUrl 46. ↵ Maekawa T , Jin W , Ishii S . The role of ATF-2 family transcription factors in adipocyte differentiation: antiobesity effects of p38 inhibitors . Mol Cell Biol 30 , 613 – 625 ( 2010 ). OpenUrl Abstract / FREE Full Text 47. ↵ Oquendo MB , et al. Effects of adrenergic-stimulated lipolysis and cytokine production on in vitro mouse adipose tissue–islet interactions . Scientific Reports 12 , 15831 ( 2022 ). 48. ↵ Zhou Z , et al. CX3CR1(hi) macrophages sustain metabolic adaptation by relieving adipose-derived stem cell senescence in visceral adipose tissue . Cell reports 42 , 112424 ( 2023 ). 49. ↵ Schoiswohl G , et al. Impact of Reduced ATGL-Mediated Adipocyte Lipolysis on Obesity- Associated Insulin Resistance and Inflammation in Male Mice . Endocrinology 156 , 3610 – 3624 ( 2015 ). OpenUrl CrossRef PubMed 50. ↵ Schweiger M , et al. Pharmacological inhibition of adipose triglyceride lipase corrects high-fat diet-induced insulin resistance and hepatosteatosis in mice . Nat Commun 8 , 14859 ( 2017 ). 51. ↵ Girousse A , et al. Partial inhibition of adipose tissue lipolysis improves glucose metabolism and insulin sensitivity without alteration of fat mass . PLoS Biol 11 , e1001485 ( 2013 ). OpenUrl CrossRef PubMed 52. ↵ Eguchi J , et al. Transcriptional control of adipose lipid handling by IRF4 . Cell Metab 13 , 249 – 259 ( 2011 ). OpenUrl CrossRef PubMed Web of Science 53. ↵ Concordet JP , Haeussler M . CRISPOR: intuitive guide selection for CRISPR/Cas9 genome editing experiments and screens . Nucleic Acids Res 46 , W242 – w245 ( 2018 ). OpenUrl CrossRef PubMed 54. ↵ Bray NL , Pimentel H , Melsted P , Pachter L . Near-optimal probabilistic RNA-seq quantification . Nat Biotechnol 34 , 525 – 527 ( 2016 ). OpenUrl CrossRef PubMed 55. ↵ Robinson MD , McCarthy DJ , Smyth GK . edgeR: a Bioconductor package for differential expression analysis of digital gene expression data . Bioinformatics 26 , 139 – 140 ( 2010 ). OpenUrl CrossRef PubMed Web of Science 56. ↵ Liu L , et al. Histone methyltransferase MLL4 controls myofiber identity and muscle performance through MEF2 interaction . J Clin Invest 130 , 4710 – 4725 ( 2020 ). OpenUrl CrossRef 57. ↵ Cohen DM , Won K-J , Nguyen N , Lazar MA , Chen CS , Steger DJ . ATF4 licenses C/EBPβ activity in human mesenchymal stem cells primed for adipogenesis . eLife 4 , e06821 ( 2015 ). OpenUrl CrossRef PubMed 58. ↵ Bishnupuri KS , et al. IDO1 and Kynurenine Pathway Metabolites Activate PI3K-Akt Signaling in the Neoplastic Colon Epithelium to Promote Cancer Cell Proliferation and Inhibit Apoptosis . Cancer Res 79 , 1138 – 1150 ( 2019 ). OpenUrl Abstract / FREE Full Text View the discussion thread. Back to top Previous Next Posted July 31, 2024. 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