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Comparative microarray analyses of mono(2-ethylhexyl)phthalate impacts on fat cell bioenergetics and adipokine network Subtitle: MEHP enhances energy metabolism-related gene expression in adipocytes Huai-chih Chiang,a Chih-Hong Wang,b Szu-Ching Yeh,a Yi-Hua Lin,a Ya-Ting Kuo,a Chih-Wei Liao,a Feng-Yuan Tsai,a Wei-Yu Lin,b Wen-Han Chuang,b and Tsui-Chun Tsou,a,* a National Institute of Environmental Health Sciences, National Health Research Institutes, Zhunan, Miaoli 350, Taiwan b Department of Biological Science and Technology, National Chiao Tung University, Hsinchu 300, Taiwan * Corresponding author: Tsui-Chun Tsou National Institute of Environmental Health Sciences, National Health Research Institutes, 35 Keyan Road, Zhunan, Miaoli 350, Taiwan; Tel.: +886-37-246-166 ext. 36511; fax: +886-37-587-406; E-mail: tctsou@nhri.org.tw 1 Abstract Cellular accumulation of mono(2-ethylhexyl)phthalate (MEHP) has been recently demonstrated to disturb fat cell energy metabolism; however, the underlying mechanism remained unclear. The study aimed to determine how MEHP influenced fat cell transcriptome and how the changes might contribute to bioenergetics. Because of the pivotal role of PPARγ in energy metabolism of fat cells, comparative microarray analysis of gene expression in 3T3-L1 adipocytes treated with both MEHP and rosiglitazone was performed. Pathway enrichment analysis and gene ontology (GO) enrichment analysis revealed that both treatments caused up-regulation of genes involved in PPAR signaling/energy metabolism-related pathways and down-regulation of genes related to adipokine/inflammation signals. MEHP/rosiglitazone-treated adipocytes exhibited increased levels of lipolysis, glucose uptake, and glycolysis; the gene expression profiles provided molecular basis for the functional changes. Moreover, MEHP was shown to induce nuclear translocation and activation of PPARγ. The similarity in gene expression and functional changes in response to MEHP and rosiglitazone suggested that MEHP influenced bioenergetics and adipokine network mainly via PPARγ. Importantly, adipokine levels in C57BL/6J mice with di(2-ethylhexyl)phthalate (DEHP) treatments provided in vivo evidence for microarray results. On the basis of correlation between gene expression and functional 2 assays, possible involvements of genes in bioenergetics of MEHP-treated adipocytes were proposed. Keywords: phthalates; endocrine disruptor; energy metabolism; PPARγ; adipocytes Abbreviations: βAR, β-adrenergic receptor; DAVID, Database for Annotation, Visualization and Integrated Discovery; DEHP, di(2-ethylhexyl)phthalate; FABPs, fatty acid-binding proteins; GO, gene ontology; HFD, high-fat diet; KEGG, Kyoto Encyclopedia of Genes and Genomes; MEHP, mono(2-ethylhexyl)phthalate; Mlycd, malonyl-CoA decarboxylase; NCD, normal chow diet; NEFA, non-esterified fatty acids; OCR, oxygen consumption rate; PANTHER, Protein Analysis through Evolutionary Relationships; PCA, principal component analysis; PDC, pyruvate dehydrogenase complex; PDH, pyruvate dehydrogenase; PPRE, PPAR response element; REVIGO, Reduce + Visual Gene Ontology; T2DM, type 2 diabetes mellitus; WAT, white adipose tissue 3 Introduction Phthalates, commonly used as softeners in plastics, are the most ubiquitous environmental pollutants. Phthalates are easily released from plastics due to a lack of covalent bonds between plastics and phthalates. Accumulating epidemiological studies have revealed the association between phthalate exposure and prevalence of metabolic diseases including obesity and its complications, i.e., type 2 diabetes mellitus (T2DM) and insulin resistance (James-Todd et al. 2012; Kim et al. 2013; Wang et al. 2013); the association is evident especially for di(2-ethylhexyl)phthalate (DEHP). In animal studies, DEHP accelerates atherosclerosis in apolipoprotein E-deficient mice (Zhao et al. 2014) and maternal exposure to DEHP deregulates blood pressure, adiposity, cholesterol metabolism, and social interaction in mouse offspring (Lee et al. 2015). These experimental and epidemiological studies strongly suggests that phthalate exposure is a critical health issue. Adipose tissue is a metabolically dynamic organ, acting as a regulator in maintenance of fatty acid homeostasis and adipokine network. Upon ingestion of phthalates in human body, the majority of phthalates (≈90%) is excreted in the first 24 h and monoesters are the major metabolites (Koch et al. 2012). However, adipose tissue is found to be major storage sites for lipophilic pollutants, including phthalates. Phthalate accumulation in adipose tissue has been demonstrated in both the general 4 human population (Zhang et al. 2003) and the phthalate-treated rats (Zeng et al. 2013). Mono(2-ethylhexyl)phthalate (MEHP), the primary metabolite of DEHP, promotes differentiation of preadipocytes and to induce obesity in mice, possibly via PPARγ activation (Feige et al. 2007; Campioli et al. 2011; Hao et al. 2012). Disturbed lipid metabolism has been observed in both human primary adipocytes with MEHP treatments (Ellero-Simatos et al. 2011) and neonatal rat cardiomyocytes with DEHP treatments (Posnack et al. 2012). Our recent study found that cellular MEHP accumulation disturbed energy metabolism, including lipolysis, glucose uptake, and glycolysis, in 3T3-L1 adipocyte (Chiang et al. 2016). These studies provide clear evidence reveling that MEHP not only enhances adipogenic differentiation of preadipocytes via PPARγ but also markedly interferes with energy metabolism in mature adipocytes. Fat cells proliferate in childhood, but not in adulthood; fat cell numbers are set and generally stay constant through adult life (Spalding et al. 2008). Therefore, for both fat cell biology and obesity development, the influences of phthalates on preadipocytes and mature adipocytes could be fundamentally different. Using a special phthalate exposure procedure during adipogenesis, we demonstrated effects of MEHP on energy metabolism in mature adipocytes (Chiang et al. 2016). However, the possible involvement of PPARγ in the process remains unclear, mainly due to the 5 difficulty in conducting DNA/RNA transfection of mature adipocytes with the standard lipid-based techniques. Also, inhibition of PPARγ with specific inhibitors usually results in poor adipogenesis, which makes the following functional assays of mature adipocytes impossible. Through observations of differential expression for thousands of genes across multiple conditions, microarray analysis can be a promising technique to address the roles of PPARγ in the MEHP-induced energy disturbance in mature adipocytes. The study combines both in vitro cell models (microarray analysis and functional assays) and in vivo animal models to determine phthalate effects on adipocytes, mainly focusing on metabolism of glucose and fatty acids for energy production and adipokine network. To the best of our knowledge, this is the first study demonstrating comprehensive expression profiles of genes involved in energy metabolism pathways, which clearly highlights several scientific interests for future phthalate studies. 6 Materials and methods Chemicals and cells The information on chemicals and cells was described in detail in Supplemental Material. Induction of adipogenesis and MEHP/rosiglitazone treatments Adipogenesis of mouse 3T3-L1 cells was induced following the standard procedure as described (Hsu et al. 2010). Figure 1a shows the procedures of adipogenesis and MEHP/rosiglitazone treatments and the details were described in Supplemental Material. Microarray analysis Following the standard DIM induction from D0 to D5, 3T3-L1 adipocytes were treated with DMSO (0.1%) (the vehicle control), MEHP (100 μM), or rosiglitazone (2 µM) from D5 to D11 (Figure 1a). RNA samples were collected at D5 (Control_D5), D8 (DMSO_D8, MEHP_D8, and Rosig._D8), and D10 (DMSO_D10, MEHP_D10, and Rosig._D10) from three independent experiments. RNA samples were prepared with RNAspin Mini Kit (25-0500-87) (GE Healthcare Life Sciences). RNA samples (3 µg) were sent to the Microarray Core Laboratory at NHRI for cDNA synthesis/labeling and then were hybridized onto the GeneChip® Mouse Gene 2.0 ST Array (Affymetrix, Inc.); the array contains a total of 35,240 RefSeq transcripts and 7 26,515 RefSeq (Entrez) genes. Data analyses were conducted by software of Partek Genomics Suite (http://www.partek.com/); principal component analysis (PCA) was used to simplify the analysis and visualization of multidimensional microarray data sets and relevance network was used to determine the linkage between two treatments. Venn diagrams were performed by GeneVenn (http://genevenn.sourceforge.net/), a web application for comparison and visualization of microarray data. Pathway enrichment analysis was performed by using the Database for Annotation, Visualization and Integrated Discovery (DAVID) online analysis tool (http://david.abcc.ncifcrf.gov/) with BioCarta, Kyoto Encyclopedia of Genes and Genomes (KEGG), and Protein Analysis through Evolutionary Relationships (PANTHER) pathway databases. The pathways with fold enrichment ≥1.5 (vs. DMSO_D10) were selected. Gene ontology (GO) enrichment analysis was performed by using the DAVID online analysis tool based on the category of biological processes. The pathways with fold enrichment ≥1.5 (vs. DMSO_D10) were selected as the candidate GO: biological process terms. Following removal of redundant GO terms by using Reduce + Visual Gene Ontology (REVIGO) (http://revigo.irb.hr/), the top ten GO: biological process terms were shown. Heatmaps were visualized by MultiExperiment Viewer downloaded from the TM4 microarray software suite (http://www.tm4.org/). The color-coded scale for the normalized expression value, 8 log2 (fold change), is shown at the bottom of each figure (the red indicates up-regulated genes and the green indicates the down-regulated genes). qPCR was used to validate microarray data as described in detail in Supplemental Material. Determination of glycerol, triglycerides, non-esterified fatty acids (NEFA), and lactate Cellular glycerol, triglycerides, and NEFA were extracted as previously described (Samuel et al. 2013). Briefly, to completely dissolve the intracellular lipids, cells were collected in 5% NP-40 for lysis at 90°C for 5 min and then cool to RT for at least three times. Following centrifugation at 15,000 rpm for 5 min to remove cell debris, supernatants were collected for analysis by using glycerol assay (GY105) (Randox), triglycerides assay (TR213) (Randox), NEFA-C assay (279-75401) (Wako Pure Chemical). Lipolytic activity in adipocytes was determined by glycerol release assay. For analysis of the basal lipolytic activity, cells were replenished with fresh DMEM-HG with 10% FBS and cultured for another 24 h, the basal lipolytic activity was determined by levels of glycerol released in culture medium. For analysis of the β-adrenergic receptor (βAR)-induced lipolytic activity, following starvation in DMEM-LG with 0.1% BSA for 2 h, cell were treated with the βAR agonist isoproterenol (1 µM) for 4 h and culture medium was collected for analysis by using 9 glycerol assay kit (GY105) (Randox). Moreover, culture medium was collected at D11 for determination of lactate production. Following centrifugation at 15,000 rpm for 5 min to remove cell debris, supernatants were collected for analysis by using lactate assay (LC2389) (Randox). Cellular uptake of exogenous glucose and palmitate To determine cellular uptake of exogenous glucose and NEFA, adipocytes were subjected to glucose/pyruvate-free DMEM supplemented with glucose (5 mM) or palmitate (BSA-conjugated) (200 μM), a model NEFA. Preparation of BSA-conjugated palmitate was described in Supplemental Material. At the indicated time points, 100 μl of culture medium samples were collected. Following centrifugation at 10,000 rpm for 5 min to remove cell debris, supernatants were kept on ice for the following determination of glucose and palmitate by using glucose assay (GL2623) (Randox) and NEFA-C assay (279-75401) (Wako Pure Chemical), respectively. Animal treatments Male C57BL/6J mice, aged 4 weeks purchased from the National Laboratory Animal Center (Taipei, Taiwan), were housed in the Laboratory Animal Center in National Health Research Institutes. The mice were kept in individually ventilated cages, at controlled temperatures of 25 ± 1 °C, with a 12 : 12 light-dark cycle (lights 10 on at 6:00 AM), and on ad libitum food and water intake. Following acclimation for 2 weeks, the mice were fed with normal chow diet (NCD) (10 kcal% fat) (D12450B) or high-fat diet (HFD) (60 kcal% fat) (D12492) (Research Diets Inc., New Brunswick, NJ, USA) for 10 weeks. Then, the mice with both diets were treated with DEHP (1 mg/kg body weight) or corn oil (the vehicle controls) daily by gavage for 25 weeks. After the treatments, mice were euthanized with continuous CO2 inhalation to cardiac arrest following the policy of the American Veterinary Medical Association (AVMA). Blood samples were collected by cardiac puncture for enzyme-linked immunosorbent assay (ELISA) (see Supplemental Material in detail). The animal protocol was approved by the Institutional Animal Care and Use Committee (IACUC) at NHRI (NHRI-IACUC-099092). All animal studies were performed following the National Institutes of Health Guide for the Care and Use of Laboratory Animals. Statistical analyses All qualitative data were from at least three independent experiments. Relative quantitative data were expressed as fold changes and presented as mean ± SD. Statistical significance was determined by using student’s t-test and a value of p < 0.05 was considered statistically significant. Trend test for evaluating the dose-dependent effect of chemicals was conducted by the nonparametric Jonckheere–Terpstra test in SPSS Version 18. 11 Results Comparative microarray analyses Comparative microarray analysis of gene expression in 3T3-L1 adipocytes with both MEHP and rosiglitazone treatments was performed as described in Figure 1a. First, PCA analysis was used to simplify analysis and visualization of multidimensional microarray data. PCA analysis of seven samples revealed the clear separation of DMSO- and MEHP/rosiglitazone-treated data sets (Figure 1b, left panel), indicating that the gene expression patterns in MEHP/rosiglitazone-treated cells were different from that in the vehicle control. Moreover, the distinct separation of MEHP_D8 and MEHP_D10 data sets suggested a marked gene expression change in MEHP-treated cells during adipogenesis from D8 to D10. Next, relevance networks were used to compute comprehensive pair-wise measures of similarity for all genes in microarray data sets to find genetic regulatory networks (Figure 1b, right panel), where relevant links of transcriptomic patterns of MEHP_D10 were relatively lower than the others, suggesting the unique influence of MEHP on gene expression at D10. A total of 711 genes with up- or down-regulation at D10 (by ≥ 2-fold change vs. DMSO_D10) were summarized in the Venn diagrams (Figure 1c), including 346 up-regulated genes (202 genes in MEHP_D10, 185 genes in Rosig._D10, and 41 overlapped genes) and 365 down-regulated genes (175 genes in MEHP_D10, 256 12 genes in Rosig._D10, and 66 overlapped genes). Functional ontology analyses To assign biological significance of the 711 genes in response to MEHP/rosiglitazone, both pathway enrichment analysis and GO enrichment analysis were performed. Results of pathway enrichment analysis were summarized in Figure 2a. In the up-regulated genes (Figure 2a, top panel), the pathways involved in PPAR signaling, unsaturated fatty acid biosynthesis, fatty acid metabolism, and glycolysis/gluconeogenesis were markedly enriched in both MEHP_D10 and Rosig._D10. All these biosynthesis/metabolism pathways have been previously demonstrated as PPARγ-mediated biological functions in adipocytes (Sharma and Staels 2007). In the down-regulated genes (Figure 2a, bottom panel), the pathways involved in sulfur metabolism, complement signaling, β3 adrenergic receptor signaling, starch and sucrose metabolism, systemic lupus erythematosus, glutathione metabolism, and heterotrimeric G-protein signaling/Giα and Gsα mediated signaling were enriched in both adipocytes. Results of GO enrichment analysis were summarized in Figure 2b. In the up-regulated genes (Figure 2b, top panel), both adipocytes exhibited higher scores in metabolism-related biological processes, i.e., glycerol, pyruvate, and lipid metabolism. In the down-regulated genes (Figure 2b, bottom panel), the pathways involved in 13 dietary excess response, immune/inflammation-related responses (i.e., cytokine stimulus response, acute inflammatory response, and complement activation), and fat cell differentiation were significantly enriched in both adipocytes. It was noted that expression patterns of those genes particularly involved in biosynthesis/metabolism-related processes were highly similar between MEHP_D10 and Rosig._D10 (Figure 2). The finding might provide a mechanistic explanation for our previous studies that MEHP disturbed energy metabolism in fat cells (Chiang et al. 2016). Up-regulation of PPAR signaling-related genes The genes involved in PPAR signaling pathway were significantly up-regulated in both MEHP_D10 and Rosig._D10 (Figure 2a). Analysis of microarray data revealed that a total of 16 PPAR signaling-related genes were up-regulated in MEHP/rosiglitazone-treated adipocytes (vs. DMSO) (Figure 3a). The genes were functionally categorized into six groups, i.e., nuclear receptor, transcriptional coactivator, fatty acid transport, fatty acid β-oxidation, adipocyte differentiation, and gluconeogenesis/glyceroneogenesis. The details of microarray data were summarized in Table S1 in Supplemental Material. Moreover, qPCR analysis of 10 genes (Ppara, Ppargc1a, Fabp3, Fabp5, Olr1, Acaa2, Acox1, Plin2, Gyk, and Pck1) was used to validate the microarray data, confirming the higher PPAR signaling-related gene 14 expression in MEHP/rosiglitazone-treated adipocytes (Figure 3b). Up-regulation of energy metabolism-related genes Microarray analysis also revealed that, in MEHP/rosiglitazone treated adipocytes, the genes involved in both lipid/glucose metabolism (Figure 2) and PPAR pathways (Figures 2 and 3) were markedly up-regulated. Whether the gene expression caused the disturbed energy metabolism in MEHP-treated adipocytes (Chiang et al. 2016) was the major concern here. Therefore, energy metabolism-related genes were categorized based on GO annotation (GO: biological process); a total of 37 energy metabolism-related genes shown in the heatmap were functionally categorized into six groups, i.e., fatty acid β-oxidation, glucose metabolism, energy production, fatty acid synthesis, triglyceride synthesis, and lipid droplet-associated proteins (Figure 4a). MEHP/rosiglitazone-treated adipocytes exhibited higher expression levels of the most energy metabolism-related genes in both time-dependent (Figure 4a, left panel) and treatment-dependent manners (Figure 4a, right panel) (see the details of microarray data in Table S2 in Supplemental Material). It was critical to determine whether the gene expression caused any energy metabolism-related functional change in adipocytes. First, following supplementation of culture medium with glucose or a model NEFA, palmitate, the cellular consumption rates of exogenous fuel substrates were 15 determined. Results in Figure 4b revealed that, after the supplementation for ≥ 6 h and ≥ 0.5 h, levels of glucose and palmitate left in culture medium of MEHP-treated adipocytes were significantly lower than that of the vehicle controls (DMSO), respectively. In lipolysis, triglycerides are hydrolyzed into glycerol and NEFA for energy. Second, lipolytic activity in adipocytes was evaluated with cellular changes of the three lipid molecules. As shown in Figure 4c, glycerol levels in adipocyte with MEHP and rosiglitazone treatments were significantly increased by 1.87 folds and 2.42 folds (vs. DMSO), respectively, meanwhile triglycerides and NEFA levels did not change significantly. Lipolytic activity was also determined with glycerol release assay. Levels of glycerol released from adipocytes with MEHP and rosiglitazone treatments were significantly increased by 2.56 folds and 2.21 folds (vs. DMSO), respectively (Figure 4d, left panel). In the presence of the βAR agonist isoproterenol, the glycerol changes were not significant (Figure 4d, right panel). Finally, glucose metabolism in adipocytes was evaluated with glucose uptake and glycolysis. In MEHP/rosiglitazone-treated adipocytes, both basal and insulin-induced glucose uptake levels were significantly enhanced by 2–3 folds (vs. DMSO/basal) (Figure 4e, left panel). Glycolytic activity, as determined by cellular release of lactate, in adipocytes with MEHP and rosiglitazone treatments were significantly increased by 3.02 folds and 3.58 folds (vs. DMSO), respectively (Figure 4e, right panel). 16 Taken together, MEHP-treated adipocytes consume more exogenous glucose/fatty acids and exhibit higher activities in both lipolysis (in a βAR-independent manner) and glucose metabolism, suggesting a higher energy metabolism activity in the adipocytes. Evidently, both MEHP and rosiglitazone cause similar changes in energy metabolism-related gene expression/biological functions in adipocytes. Down-regulation of adipokine-related genes White adipose tissue (WAT) is emerging as an active regulator in control of various physiologic processes, where adipokines provide an elaborate network for systemic communication. The genes involved in cytokine/inflammation/complement activation-related responses (Figure 2b, bottom panel) were here collectively classified as adipokine-related genes. The heatmap of 55 adipokine-related genes was summarized in Figure 5a (see the details in Table S3 in Supplemental Material). Clearly, the majority of adipokine-related genes, e.g., Lep, Adipsin, Vegfc, Ccl2, Ccl6, Fgf7, and Csf1, in MEHP/rosiglitazone-treated adipocytes were down-regulated (vs. DMSO). It was noted that several important adipokine genes, such as Adipor2, Fgf21, Angptl4, and Ghrh, were up-regulated in MEHP/rosiglitazone-treated adipocytes (vs. DMSO). Microarray results were further validated with qPCR analysis of 5 genes (Adipsin, Lep, Adipor2, Fgf21, and Angptl4) (Figure 5b). Expression patterns of the 17 adipokine-related genes in response to both MEHP and rosiglitazone are highly similar, supporting the hypothesis that MEHP disturbs adipokine network via PPARγ. Following ingestion, DEHP is quickly metabolized into MEHP in vivo. Mouse models with both normal chow diet (NCD) and high-fat diet (HFD) were subjected to DEHP treatments (1 mg/kg body weight/day) (Figure 5c) to address MEHP effects on adipokine network in vivo. After the treatments, body weight of HFD-mice was significantly increased by 36% than that of NCD-mice; the DEHP treatment caused on significant change on body weight of both mouse models (data not shown). ELISA analysis revealed that plasma levels of Fgf21 in HFD-mice were lower than that in NCD-mice and DEHP treatments significantly enhanced Fgf21 levels in both mouse models (Figure 5d, left panel). Plasma Angptl4 levels in HFD-mice were significantly higher than that in NCD-mice; in the presence of DEHP, Angptl4 levels in HFD-mice were further increased (Figure 5d, right panel). It is clear that DEHP treatments result in the higher Fgf21 and Angptl4 levels in NCD-mice and/or HFD-mice, which is consistent with the higher mRNA levels of both genes in MEHP-treated adipocytes (Figures 5a and 5b). The results provide in vivo evidence for MEHP impacts on systemic regulation via adipokine network. Activation of PPARγ by MEHP PPARγ is highly expressed in fat tissue and its activation orchestrates both 18 triglyceride/fatty acid metabolism and adipocyte differentiation (Sharma and Staels 2007). The present microarray results suggested the potential involvement of PPARγ in energy metabolism in MEHP-treated adipocytes. It was necessary to determine whether MEHP directly induced PPARγ expression and its activation. qPCR analysis revealed that PPARγ mRNA levels in vehicle controls (DMSO) and MEHP-treated adipocytes at D11 were increased by 3.39 folds and 2.89 folds (vs. Control_D5), respectively (Figure 6a); no significant differences were detected between the two adipocytes. Immunoblot analysis with total protein samples indicated that MEHP up to 100 µM caused no significant change in both PPARγ1 and PPARγ2 isoforms (Figure 6b, top panel), whereas analysis with nuclear fraction samples revealed that MEHP significantly enhanced nuclear translocation of PPARγ2 in a dose-dependent manner (Figure 6b, bottom panel). Genetic analysis has demonstrated that PPARγ2 is more potent than PPARγ1 in transcriptional activation of the genes involved in adipogenesis (Mueller et al. 2002). By using a recombinant PPAR response element (PPRE)-driven luciferase cell line, Huh7-PPRE-Luc (Tsai et al. 2014), PPAR transcriptional activity in response to MEHP (100 µM) and rosiglitazone (2 µM) was induced by 1.92 folds and 2.64 folds, respectively (Figure 6c). Clearly, MEHP can act as a PPARγ agonist for PPARγ nuclear translocation/activation. 19 The microarray analysis revealed the highly similar expression patterns of genes involved in PPAR signaling, energy metabolism, and adipokine network between MEHP- and rosiglitazone-treated adipocytes. Significant correlation between gene expression profiles and energy-metabolism-related functional changes suggests the pivotal roles of PPARγ in regulation of energy metabolism in MEHP-treated adipocytes. Importantly, expression of adipokine-related genes, i.e., Fgf21 and Angptl4, in MEHP-treated adipocytes was confirmed with plasma samples from DEHP-treated mice, providing in vivo evidence for an adipokine-mediated systemic regulation in response to DEHP/MEHP exposure. 20 Discussion By using microarray analysis of gene expression in MEHP/rosiglitazone-treated adipocytes, it was noted that expression patterns of significant amounts of genes were highly similar between the two cells (Figure 1). Following pathway enrichment analysis, we found that PPAR signaling pathway stood on the top of up-regulated genes in MEHP/rosiglitazone-treated adipocytes (Figure 2a). PPARγ, a key player in adipogenesis, acts as a metabolic regulator primarily involved in lipid and carbohydrate metabolism (Savage 2005). Both MEHP and rosiglitazone treatments resulted in similar expression patterns of the genes involved in PPAR signaling (Figure 3), energy metabolism (Figure 4), and adipokine network (Figure 5). The results clearly suggested the central role of PPARγ in regulation of energy metabolism in MEHP-treated adipocytes. The present gene expression profiles provide molecular clues on how MEHP influences energy metabolism in adipocytes. Following uptake, MEHP activates PPARγ and its downstream genes, primarily transcription factor Ppara (PPARα) and transcriptional coactivators Ppargc1a (PGC-1α) and Ppargc1b (PGC-1β) (Figure 3). PPARγ activates different panels of gene expression via coordination with PPARα (Park et al. 2012), PGC-1α (Powell et al. 2007), and PGC-1β (Deng et al. 2011). Particularly, the PGC-1 coactivator family plays a central role in control of 21 mitochondrial biogenesis and fatty acid β-oxidation (Vega et al. 2000; Kleiner et al. 2012; Enguix et al. 2013). Results in Figure 3 suggest the involvement of PPARγ in fatty acid transport, fatty acid β-oxidation, adipocyte differentiation, and gluconeogenesis/glyceroneogenesis in MEHP-treated adipocytes. MEHP-treated adipocytes consumed more fatty acids (Figure 4b, right panel). Up-regulation of the genes involved in fatty acid transport and fatty acid β-oxidation in MEHP/rosiglitazone-treated adipocytes (Figures 3 and 4a) provides a possible scenario for the higher cellular fatty acid uptake. The fatty acid transport-related genes include Olr1, Fabp3, Fabp5, and the solute carrier family 25 (Slc25a20, Slc25a22, Slc25a34, and Slc25a54). Olr1 encodes a cell-surface receptor for endocytosis of oxidized low density lipoprotein (Mehta and Li 1998). Fatty acid-binding proteins (FABPs), e.g., Fabp3 and Fabp5, facilitate fatty acid transport to mitochondria for β-oxidation (Furuhashi and Hotamisligil 2008). The solute carrier family 25, e.g., Slc25a20, has been reported as a mitochondrial fatty acid transporter (Palmieri 2004). Fatty acids are transported into mitochondria for energy production via fatty acid β-oxidation; the genes involved in β-oxidation include Acox1, Acaa1b, Acaa2, Hadha, Hsdl2, Echdc1, and Eci1 (Figure 4a). Clearly, in MEHP-treated adipocytes, the higher fatty acid consumption combined with the higher fatty acid transport/β-oxidation may lead to the higher mitochondrial respiration for energy. Moreover, the higher fatty acid 22 demand in MEHP-treated adipocytes is supported by the up-regulation of genes involved in fatty acid synthesis, including Acacb, Elovl3, Ephx2, Mlycd, and Cyp4f17 (Figure 4a). MEHP-treated adipocytes also consumed more glucose (Figure 4b, left panel) and exhibited a higher glycolytic activity (Figure 4e). The genes involved in glucose metabolism, including glucose transport (Slc2a1), glycolysis (Fbp2, Gapdh, and Pgam1), and gluconeogenesis/glyceroneogenesis (Pdk2, Pdk4, Pck1, and Gyk), were up-regulated in MEHP-treated adipocytes (Figure 4a), suggesting that the gene expression may contribute to the higher glucose uptake/glycolysis in the cells. Moreover, it was noted that, in MEHP-treated adipocytes, the higher glucose uptake was accompanied with a proportional lactate production (Figure 4e), indicating that the majority of glucose uptake is metabolized into lactate, with limited energy production via mitochondrial respiration. Therefore, fatty acids could be the major fuel for the higher oxygen consumption rate (OCR) in MEHP-treated adipocytes that we previously reported (Chiang et al. 2016). It is suggested that two enzyme activities, Pdk2/Pdk4 and Mlycd, (Figure 4a) are responsible for the preferential fatty acid utilization for mitochondrial energy production. First, Pdk4 has been reported to inhibit pyruvate dehydrogenase (PDH), the first component enzyme of pyruvate dehydrogenase complex (PDC) (Zhang et al. 23 2014). PDH/PDC bridges the glycolysis metabolic pathway to the TCA cycle; inactivation of PDH/PDC prevents conversion of pyruvate to acetyl CoA and thus switches glucose catabolism to fatty acid oxidation (Zhang et al. 2014). Second, Mlycd encodes an enzyme of malonyl-CoA decarboxylase (Mlycd). Mlycd catalyzes the conversion of malonyl-CoA to acetyl-CoA and prevents accumulation of malonyl-CoA, a potent inhibitor of mitochondrial fatty acid uptake (Foster 2012). Therefore, up-regulation of Mlycd in MEHP-treated adipocytes suggests facilitation of mitochondrial fatty acid uptake and β-oxidation. Our findings support the hypothesis that MEHP-treated adipocytes prefer to utilize fatty acids rather than glucose in mitochondrial respiration for energy. Lipolysis involves hydrolysis of triglycerides into glycerol and NEFA and plays critical roles in systemic supply of fatty acids for energy. Up-regulation of the lipid metabolism-related genes (Figures 3 and 4a) supported the higher lipolytic activity detected in MEHP/rosiglitazone-treated adipocytes (Figures 4c and 4d). It was noted that the lipolytic activity was regulated in a βAR-independent manner (Figure 4d). Among the genes involved in triglyceride synthesis in adipocytes (Figure 4a), Ces1d encodes the major non-hormone-sensitive/βAR-independent lipase, carboxylesterase 1D (Soni et al. 2004). Expression levels of Ces1d in MEHP_D10 and Rosig._D10 were increased by 1.31 folds and 1.69 folds (vs. DMSO_D10), respectively; the 24 higher Ces1d expression may lead to the higher βAR-independent lipolytic activity. Moreover, Aqp7 deficiency leads to triglyceride accumulation in adipocytes, indicating the role of Aqp7 in glycerol release (Hibuse et al. 2005). Thus, the higher Aqp7 expression in MEHP/rosiglitazone-treated adipocytes (Figure 3) may also contribute to the higher glycerol release (Figure 4d). Obesity is a major etiological factor for metabolic complication, such as T2DM. Adipose tissue functions as a key endocrine organ mainly via adipokine network; adipokines play important roles in both inflammatory responses and systemic regulation of metabolism (Ouchi et al. 2011). The majority of adipokine-related genes in MEHP/rosiglitazone-treated adipocytes were down-regulated (Figure 5a), which is generally consistent with a previous rosiglitazone study (Wang et al. 2007). Expression levels of Lep in adipocytes treated with MEHP (30 µM and 100 µM) and rosiglitazone (2 µM) were markedly decreased by 80%, 92%, and 96%, respectively (Figure 5b). Leptin, predominantly synthesized in WAT, plays critical roles in control of appetite and energy balance. Lep-deficient (ob/ob) mouse, an animal model of T2DM, exhibits uncontrolled food intake and thus rapidly develops obesity (Muzzin et al. 1996). Therefore, down-regulation of Lep in MEHP/rosiglitazone-treated adipocytes provides a potential linkage between MEHP exposure/TZD therapy and obesity. Importantly, up-regulation of two specific adipokine-related genes (Fgf21 and 25 Angptl4) was presented here with both in vitro (microarray and qPCR) and in vivo (animal) studies (Figure 5). FGF21 plays pivotal roles in control of glucose homeostasis and body weight (Kharitonenkov et al. 2005; Dutchak et al. 2012). Angtl4 acts as a regulator of glucose and lipid metabolism (Xu et al. 2005). Microarray data listed in Figure 5a provide comprehensive information about how phthalate exposures may influence systemic regulation via adipokine network. 26 Conclusion Taken together, on the basis of causal correlation between the microarray-based gene expression profiles and the energy metabolism-related functional assays, a proposed model of MEHP effects on bioenergetics and adipokine network in adipocytes is schematically summarized in Figure 7. Upon uptake in adipocytes, MEHP functions as a PPARγ agonist for PPARγ activation. The activated PPARγ is translocated into nucleus and promotes the PPARγ-mediated gene expression. PPARγ also cooperate with different coactivators, such as PPARα, PGC1α, and PGC1β, to regulate expression of different panels of the genes involved in control of energy metabolism (i.e., glycolysis, gluconeogenesis/glyceroneogenesis, lipolysis, fatty acid β-oxidation, and TCA cycle) and adipokine network. The MEHP-treated adipocytes exhibit significant increases in fatty acid consumption, glucose uptake, and lipolytic activity. The higher fatty acid consumption combined with the higher fatty acid transport/β-oxidation may lead to the higher mitochondrial respiration for energy. The higher glucose uptake accompanied with a proportional lactate production indicates that the majority of glucose uptake is metabolized into lactate, with limited energy production via mitochondrial respiration. It is noted that the higher expression of Pdk2/Pdk4 and Mlycd genes in MEHP-treated adipocytes may result in preferential utilization of fatty acids rather than glucose 27 in mitochondrial respiration. Moreover, changes in adipokine profile and lactate/glycerol levels in circulation can also disturb systemic metabolic homeostasis. 28 Acknowledgements This work was supported by grants from the Ministry of Science and Technology (101-2314-B-400-003-MY3, 102-2811-B-400-015, and 103-2811-B-400-022) and the National Health Research Institutes (EO-103-PP-03 and EO-104-PP-03) in Taiwan. 29 References Campioli E, Batarseh A, Li J, Papadopoulos V. The endocrine disruptor mono-(2-ethylhexyl) phthalate affects the differentiation of human liposarcoma cells (SW 872). PloS one. 2011;6:e28750. Chiang HC, Kuo YT, Shen CC, Lin YH, Wang SL, Tsou TC. Mono(2-ethylhexyl)phthalate accumulation disturbs energy metabolism of fat cells. Archives of toxicology. 2016;90:589-601. Deng T, Sieglaff DH, Zhang A, Lyon CJ, Ayers SD, Cvoro A, et al. A peroxisome proliferator-activated receptor gamma (PPARgamma)/PPARgamma coactivator 1beta autoregulatory loop in adipocyte mitochondrial function. The Journal of biological chemistry. 2011;286:30723-31. Dutchak PA, Katafuchi T, Bookout AL, Choi JH, Yu RT, Mangelsdorf DJ, et al. Fibroblast growth factor-21 regulates PPARgamma activity and the antidiabetic actions of thiazolidinediones. Cell. 2012;148:556-67. Ellero-Simatos S, Claus SP, Benelli C, Forest C, Letourneur F, Cagnard N, et al. Combined transcriptomic-(1)H NMR metabonomic study reveals that monoethylhexyl phthalate stimulates adipogenesis and glyceroneogenesis in human adipocytes. Journal of proteome research. 2011;10:5493-502. Enguix N, Pardo R, Gonzalez A, Lopez VM, Simo R, Kralli A, et al. Mice lacking 30 PGC-1beta in adipose tissues reveal a dissociation between mitochondrial dysfunction and insulin resistance. Molecular metabolism. 2013;2:215-26. Feige JN, Gelman L, Rossi D, Zoete V, Metivier R, Tudor C, et al. The endocrine disruptor monoethyl-hexyl-phthalate is a selective peroxisome proliferator-activated receptor gamma modulator that promotes adipogenesis. The Journal of biological chemistry. 2007;282:19152-66. Foster DW. Malonyl-CoA: the regulator of fatty acid synthesis and oxidation. The Journal of clinical investigation. 2012;122:1958-9. Furuhashi M, Hotamisligil GS. Fatty acid-binding proteins: role in metabolic diseases and potential as drug targets. Nature reviews Drug discovery. 2008;7:489-503. Hao C, Cheng X, Xia H, Ma X. The endocrine disruptor mono-(2-ethylhexyl) phthalate promotes adipocyte differentiation and induces obesity in mice. Bioscience reports. 2012;32:619-29. Hibuse T, Maeda N, Funahashi T, Yamamoto K, Nagasawa A, Mizunoya W, et al. Aquaporin 7 deficiency is associated with development of obesity through activation of adipose glycerol kinase. Proceedings of the National Academy of Sciences of the United States of America. 2005;102:10993-8. Hsu HF, Tsou TC, Chao HR, Kuo YT, Tsai FY, Yeh SC. Effects of 2,3,7,8-tetrachlorodibenzo-p-dioxin 31 on adipogenic differentiation and insulin-induced glucose uptake in 3T3-L1 cells. Journal of hazardous materials. 2010;182:649-55. James-Todd T, Stahlhut R, Meeker JD, Powell SG, Hauser R, Huang T, et al. Urinary phthalate metabolite concentrations and diabetes among women in the National Health and Nutrition Examination Survey (NHANES) 2001-2008. Environmental health perspectives. 2012;120:1307-13. Kharitonenkov A, Shiyanova TL, Koester A, Ford AM, Micanovic R, Galbreath EJ, et al. FGF-21 as a novel metabolic regulator. The Journal of clinical investigation. 2005;115:1627-35. Kim JH, Park HY, Bae S, Lim YH, Hong YC. Diethylhexyl phthalates is associated with insulin resistance via oxidative stress in the elderly: a panel study. PloS one. 2013;8:e71392. Kleiner S, Mepani RJ, Laznik D, Ye L, Jurczak MJ, Jornayvaz FR, et al. Development of insulin resistance in mice lacking PGC-1alpha in adipose tissues. Proceedings of the National Academy of Sciences of the United States of America. 2012;109:9635-40. Koch HM, Christensen KL, Harth V, Lorber M, Bruning T. Di-n-butyl phthalate (DnBP) and diisobutyl phthalate (DiBP) metabolism in a human volunteer after single oral doses. Archives of toxicology. 2012;86:1829-39. 32 Lee KI, Chiang CW, Lin HC, Zhao JF, Li CT, Shyue SK, et al. Maternal exposure to di-(2-ethylhexyl) phthalate exposure deregulates blood pressure, adiposity, cholesterol metabolism and social interaction in mouse offspring. Archives of toxicology. 2015. Mehta JL, Li DY. Identification and autoregulation of receptor for OX-LDL in cultured human coronary artery endothelial cells. Biochemical and biophysical research communications. 1998;248:511-4. Mueller E, Drori S, Aiyer A, Yie J, Sarraf P, Chen H, et al. Genetic analysis of adipogenesis through peroxisome proliferator-activated receptor gamma isoforms. The Journal of biological chemistry. 2002;277:41925-30. Muzzin P, Eisensmith RC, Copeland KC, Woo SL. Correction of obesity and diabetes in genetically obese mice by leptin gene therapy. Proceedings of the National Academy of Sciences of the United States of America. 1996;93:14804-8. Ouchi N, Parker JL, Lugus JJ, Walsh K. Adipokines in inflammation and metabolic disease. Nature reviews Immunology. 2011;11:85-97. Palmieri F. The mitochondrial transporter family (SLC25): physiological and pathological implications. Pflugers Archiv : European journal of physiology. 2004;447:689-709. Park BO, Ahrends R, Teruel MN. Consecutive positive feedback loops create a 33 bistable switch that controls preadipocyte-to-adipocyte conversion. Cell reports. 2012;2:976-90. Posnack NG, Swift LM, Kay MW, Lee NH, Sarvazyan N. Phthalate exposure changes the metabolic profile of cardiac muscle cells. Environmental health perspectives. 2012;120:1243-51. Powell E, Kuhn P, Xu W. Nuclear Receptor Cofactors in PPARgamma-Mediated Adipogenesis and Adipocyte Energy Metabolism. PPAR research. 2007;2007:53843. Samuel P, Khan MA, Nag S, Inagami T, Hussain T. Angiotensin AT(2) receptor contributes towards gender bias in weight gain. PloS one. 2013;8:e48425. Savage DB. PPAR gamma as a metabolic regulator: insights from genomics and pharmacology. Expert reviews in molecular medicine. 2005;7:1-16. Sharma AM, Staels B. Review: Peroxisome proliferator-activated receptor gamma and adipose tissue--understanding obesity-related changes in regulation of lipid and glucose metabolism. The Journal of clinical endocrinology and metabolism. 2007;92:386-95. Soni KG, Lehner R, Metalnikov P, O'Donnell P, Semache M, Gao W, et al. Carboxylesterase 3 (EC 3.1.1.1) is a major adipocyte lipase. The Journal of biological chemistry. 2004;279:40683-9. 34 Spalding KL, Arner E, Westermark PO, Bernard S, Buchholz BA, Bergmann O, et al. Dynamics of fat cell turnover in humans. Nature. 2008;453:783-7. Tsai FY, Cheng YT, Tsou TC. A recombinant PPRE-driven luciferase bioassay for identification of potential PPAR agonists. Vitamins and hormones. 2014;94:427-35. Vega RB, Huss JM, Kelly DP. The coactivator PGC-1 cooperates with peroxisome proliferator-activated receptor alpha in transcriptional control of nuclear genes encoding mitochondrial fatty acid oxidation enzymes. Molecular and cellular biology. 2000;20:1868-76. Wang H, Zhou Y, Tang C, He Y, Wu J, Chen Y, et al. Urinary phthalate metabolites are associated with body mass index and waist circumference in Chinese school children. PloS one. 2013;8:e56800. Wang P, Renes J, Bouwman F, Bunschoten A, Mariman E, Keijer J. Absence of an adipogenic effect of rosiglitazone on mature 3T3-L1 adipocytes: increase of lipid catabolism and reduction of adipokine expression. Diabetologia. 2007;50:654-65. Xu A, Lam MC, Chan KW, Wang Y, Zhang J, Hoo RL, et al. Angiopoietin-like protein 4 decreases blood glucose and improves glucose tolerance but induces hyperlipidemia and hepatic steatosis in mice. Proceedings of the National 35 Academy of Sciences of the United States of America. 2005;102:6086-91. Zeng Q, Wei C, Wu Y, Li K, Ding S, Yuan J, et al. Approach to distribution and accumulation of dibutyl phthalate in rats by immunoassay. Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association. 2013;56:18-27. Zhang S, Hulver MW, McMillan RP, Cline MA, Gilbert ER. The pivotal role of pyruvate dehydrogenase kinases in metabolic flexibility. Nutrition & metabolism. 2014;11:10. Zhang YH, Chen BH, Zheng LX, Wu XY. [Study on the level of phthalates in human biological samples]. Zhonghua yu fang yi xue za zhi [Chinese journal of preventive medicine]. 2003;37:429-34. Zhao JF, Hsiao SH, Hsu MH, Pao KC, Kou YR, Shyue SK, et al. Di-(2-ethylhexyl) phthalate accelerates atherosclerosis in apolipoprotein E-deficient mice. Archives of toxicology. 2014. 36 Figure legends Fig. 1. Comparative microarray analysis of gene expression in MEHP/rosiglitazone-treated adipocytes. (a) Procedures of cell treatments in this study. A total of seven samples were collected for microarray analysis. CF, confluence; Dex, dexamethasone; DIM, differentiation-inducing medium; IBMX, 3-isobutyl-1-methylxanthine; Ins, insulin; Rosig, rosiglitazone. (b) PCA analysis (left panel) was used to simplify analysis and visualization of multidimensional microarray data. Relevance network (right panel) was used to determine the linkage between two treatments. (c) Venn diagrams of the 711 genes with significant up- or down-regulation in MEHP_D10 or Rosig._D10 (vs. DMSO_D10). There were 346 up-regulated genes, i.e., 202 genes in MEHP_D10 and 185 genes in Rosig._D10, with 41 overlapped genes. There were 365 down-regulated genes, i.e., 175 genes in MEHP_D10 and 256 genes in Rosig._D10, with 66 overlapped genes. Fig. 2. Microarray data biological process classification. (a) Pathway enrichment analysis and (b) GO enrichment analysis were performed with a total of 711 genes with significant changes in either MEHP_D10 or Rosig._D10 (vs. DMSO_D10) as described in detail in Fig. 1c. Value in parenthesis indicates the number of genes in each MEHP_D10 or Rosig._D10 37 group. The common biological functions/pathways found in both treatments are underlined. p-values by Fisher extract test were indicated. Fig. 3. Up-regulation of PPAR signaling-related genes in MEHP/rosiglitazone-treated adipocytes. (a) Heatmap of mRNA levels of 16 PPAR signaling-related genes in response to DMSO (the vehicle control), MEHP, and rosiglitazone. (b) qPCR validation of microarray gene expression in adipocytes treated with DMSO, MEHP (30 and 100 μM), or rosiglitazone (2 μM). Data are expressed as relative mRNA levels (vs. Control_D5) and presented as mean ± SD (n ≥ 4). *p < 0.05, **p < 0.01, ***p < 0.001 vs. DMSO. P-values for trend were calculated by nonparametric Jonckheere-Terpstra test. Fig. 4. Higher energy metabolism activity in MEHP/rosiglitazone-treated adipocytes. (a) Heatmap of mRNA levels of 37 energy metabolism-related genes in response to DMSO (the vehicle control), MEHP, and rosiglitazone in time-dependent (vs. Control_D5) or treatment-dependent (vs. DMSO) manners. Energy metabolism activity in adipocytes treated with DMSO, MEHP (100 μM), or rosiglitazone (2 μM) was analyzed with (b) cellular uptake of exogenous glucose/palmitate, (c and d) lipolysis, and (e) glucose metabolism. Lipolytic activity was determined with (c) 38 cellular levels of triglyceride, NEFA, and glycerol as well as (d) glycerol release assay. Glucose metabolism activity was evaluated with glucose uptake (see Supplemental Material in detail) and lactate production. Data are presented as mean ± SD (n ≥ 4). *p < 0.05, **p < 0.01, ***p < 0.001 vs. DMSO of each time point (for b) or vs. DMSO (for c, d, and e). Fig. 5. Down-regulation of adipokine-related genes in MEHP/rosiglitazone-treated adipocytes. (a) Heatmap of mRNA levels of 55 adipokine-related genes in response to DMSO (the vehicle control), MEHP, and rosiglitazone. (b) Microarray gene expression was validated by qPCR as described in Figure 3b. Data are expressed as relative mRNA levels (vs. Control_D5) and presented as mean ± SD (n ≥ 4). *p < 0.05, **p < 0.01, ***p < 0.001 vs. DMSO. P-values for trend were calculated by nonparametric Jonckheere-Terpstra test. (c) Male C57BL/6J mice were fed with normal chow diet (NCD) or high-fat diet (HFD) for 10 weeks. Then, both mice were treated with DEHP (1 mg/kg body weight) or corn oil (the vehicle control) daily by gavage for 25 weeks. (d) After treatments, serum samples were collected for analysis of Fgf21 and Angptl4 by ELISA. Data are presented as mean ± SD (NCD, n = 2; NCD-DEHP, n = 5; HFD, n = 5; HFD-DEHP, n = 3). *p < 0.05 vs. NCD; †p < 0.05, HFD-DEHP vs. HFD. 39 Fig. 6. Activation of PPARγ by MEHP. (a) PPARγ mRNA levels in adipocytes treated with DMSO (the vehicle control) or MEHP (100 μM) were determined by qPCR. Data are expressed as relative mRNA levels (vs. Control_D5) and presented as mean ± SD (n = 4). (b) PPARγ levels in both total (top panel) and nuclear protein samples (bottom panel) from adipocytes treated with DMSO (the vehicle control) or MEHP (30 and 100 µM) were determined by immunoblot analysis with α-tubulin and lamin B as loading controls, respectively (see Supplemental Material in detail). Representative immunoblots are shown. Data are expressed as relative PPARγ protein levels (vs. loading controls) and presented as mean ± SD (n = 3). *p < 0.05 vs. DMSO. (c) Huh7-PPRE-Leu cells, carrying a PPRE-driven luciferase gene, were left untreated or treated with DMSO (the vehicle control), MEHP (100 µM), or rosiglitazone (2 µM) for 24 h; luciferase activity in the cells was determined (see Supplemental Material in detail). Data are expressed as relative luciferase activity (vs. untreated control) and presented as mean ± SD (n = 4). ***p < 0.001 vs. DMSO. Fig. 7. A proposed schematic diagram for MEHP impacts on fat cell bioenergetics and adipokine network. Functional correlation between the microarray-based gene expression and the energy metabolism-related functional assays suggested the pivotal 40 role of PPARγ in control of energy metabolism and adipokine network in MEHP-treated adipocytes. Transcription factors/coactivators, transporters, adipokines, and potential enzymes/proteins involved in energy metabolism pathways (i.e., glycolysis, lipolysis, gluconeogenesis/glyceroneogenesis, esterification, fatty acid β-oxidation, and TCA cycle) are depicted. Fuel molecules and their metabolites are underlined. Arrow (→) shows the flow direction of metabolites and pathways. Arrow to bar (→|) indicates inhibition of enzyme activity or protein function. Dashed lines represent a potential PPARγ-mediated regulation. Red color codes for up-regulated genes, increased metabolites, or activated pathways; green color codes for the opposite. Black color codes for no significant changes. Genes in frame indicate absent in the array. 41