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Loss of Mbd2 protects mice against high fat diet-induced obesity and insulin resistance

by regulating the of energy storage and expenditure

Jia Cheng,1,2,# Jia Song,1,# Xiaoyu He,1 Meng Zhang,1 Shuang Hu,1 Shu Zhang,1 Qilin Yu,1

Ping Yang,1 Fei Xiong,1 Dao Wen Wang,2 Jianfeng Zhou,3 Qin Ning,4 Zhishui Chen, 1 Decio L

Eizirik,5 Zhiguang Zhou,6 Chunxia Zhao, 2,* and CongYi Wang1,*

1The Center for Biomedical Research, Key Laboratory of Organ Transplantation, Ministry of

Education, Key Laboratory of Organ Transplantation, Ministry of Health, 2The Institute of

Hypertension and Department of Internal Medicine, 3Department of Hematology,

4Department of Infectious Disease, Tongji Hospital, Tongji Medical College, Huazhong

University of Science and Technology, 1095 Jiefang Ave., Wuhan, 430030, China;

5Laboratory of Experimental Medicine, Universite Libre de Bruxelles, Route de Lennik 808,

CP 618, B1070, Brussels, Belgium;

6Diabetes Center, the Second Xiangya Hospital, Institute of Metabolism and Endocrinology，

Central South University, Changsha, 410011, China.

# These authors contributed equally to this work.

*All correspondence should be addressed to Drs. CongYi Wang ([email protected]) or Chunxia Zhao ([email protected]).

Running title: MBD2 regulates Highfat dietinduced obesity and insulin resistance

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Abstract

Previous studies including ours demonstrated that MBD2 acts as reader to decipher DNA

methylomeencoded information. We thus in the present report employed Mbd2/ mice as a

model to dissect the impact of highfat diet (HFD) on DNA methylome relevant to the

pathoetiology of obesity. It was interestingly noted that mice deficient in Mbd2 were

protected from HFDinduced obesity and insulin resistance. Mechanistic study revealed that

HFD rendered epididymal adipose tissues to undergo a DNA methylation turnover as

evidenced by the changes of methylation levels and patterns. Specifically, HFD was noted

with higher potency to induce DNA hypomethylation in relevant to energy storage than

that in genes associated with energy expenditure. As a result, arrays of genes were subjected

to expression changes, which led to an altered homeostasis for energy storage and expenditure

in favor of obesity development. Loss of Mbd2 resulted in impaired implementation of above

DNA methylation changes associated with altered energy homeostasis, which then protected

mice from HFDinduced obesity and insulin resistance. Those data would provide novel

insight into the understanding of the pathoetiology underlying obesity with potential for

developing effective therapies against obesity in clinical settings.

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The ongoing obesity epidemic and its associated complications of chronic diseases such as type 2 diabetes, dyslipidemia, nonalcoholic fatty liver disease (NAFLD) and hypertension, exert formidable challenges and burden to human health (1). Obesity is caused by a complex interplay between genetic and environmental factors. It is believed that environmental factors interact with susceptible genes to modulate the risk for obesity, which may also happen through direct chemical modifications of the genome by so called DNA methylation.

Although highfat diet (HFD), as a highly influential environmental factor, has long been employed to induce obesity and insulin resistance, its impact on epigenetic modifications of the genome, especially in the adipose genome, is yet to be fully elucidated. Evidence shows that shortterm of highfat overfeeding impacts genomewide DNA methylation patterns in human skeletal muscle (2). A global study of DNA methylation in human adipose tissue also characterized changes for the epigenetic patterns in response to longterm exercise, potentially affecting adipocyte metabolism (3). Given that DNA methylation acts as a

“footprint” to record environment interactions or accumulated environmental exposures during the course of daily life processes (4; 5), we thus hypothesize that HFD induces adipose tissues to undergo a DNA methylation turnover, which would be in favor of developing obesity and insulin resistance.

Previous studies including ours demonstrated that information encoded by the DNA methylome is read by a family of methylCpG–binding domain (MBD) , including

MBD1, MBD2, MBD3, MBD4 and the founding member, MeCP2 (68). It has been recognized that MBD1, MBD2, and MeCP2 selectively bind to methylated CpGs, by which

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they prevent factors binding to gene promoters and/or recruit histone

deacetyltransferases (HDACs) and (911). In contrast, binding affinity for

MBD3 is not dependent on DNA methylation, and MBD4 has been primarily regarded as a

thymine DNA glycosylase with little role in transcriptional repression (12; 13). Mice lacking

MeCP2 is associated with specific neurological defects that mimic the human neurological

disorder Rett Syndrome (14). Lack of Mbd1 develops deficits in adult neurogenesis and

hippocampal function (15), while loss of Mbd4 suppresses CpG mutability and tumorigenesis

(13; 16). In sharp contrast, mice deficient in Mbd2 are generally normal except for a minor

in maternal behavior (17), which endowed MBD2 to be an ideal target for the

study of DNA methylation on disease pathoetiology. In the current study, we employed

Mbd2/ mice as a model to investigate the effect of DNA methylation on HFDinduced

obesity. HFD induced genomic DNA of adipose tissue to undergo a DNA methylation

turnover, which altered the homeostasis of energy expenditure and storage in favor of obesity

development, and as a result, loss of Mbd2 provided protection for mice against HFDinduced

obesity and insulin resistance.

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RESEARCH DESIGN AND METHODS

Mice

Mbd2 knockout (Mbd2/) mice in C57BL/6 background were kindly provided by Dr. Adrian

Bird (Edinburgh University, UK) (12). Both male Mbd2/ mice and their WT littermates

(8weekold) were housed individually and either maintained on normal diet (ND) (MD12031,

10 kcal % fat, Medicience Ltd, Jiang Su, China) or switch to HFD (MD12033, 60 kcal % fat,

Medicience Ltd, Jiang Su, China) for 16 consecutive weeks. Mean daily food consumption was determined in each mouse by calculating the amount of accumulatively consumed food for one month (812 weeks old), and then normalized with body weight. All protocols for animal studies were approved by the Tongji Hospital Animal Care and Use Committee in accordance with the National Institutes of Health (NIH) guidelines.

Assays for glucose and insulin tolerance test and HOMA-IR

After 16 weeks of feeding, glucose and insulin tolerance tests were conducted by the intraperitoneal injection of glucose (SigmaAldrich Co., St. Louis, MO, USA) and insulin

(Novolin R, Novo Nordisk Co., Bagsvaerd, Denmark) as described previously (18).

HOMAIR was calculated according to the formula: fasting insulin (microU/L) x fasting glucose (nmol/L)/22.5 (19).

Histological and morphological analysis

HE and Oil Red O staining of epididymal adipose tissue and liver were performed as reported

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(20; 21). The adipocyte area was estimated by measuring the area of more than 120 cells per

100×magnification tissue sections using an image quantitative digital analysis system

(ImagePro plus 6.0, Media Cybernetics, Inc., MD, USA) (22; 23).

Western blotting and real-time PCR analysis

Western blotting and realtime PCR analysis were performed as reported (6).

against Mbd2 (sc10752), Raptor (Sc27744), ATGL (Sc50223), Cpt1 (sc20514) and pIRS

(sc17200) were purchased from Santa Cruz Biotechnology (Santa Cruz, CA, USA), while

antibodies against AKT (4685s), pAKT (Thr308) (5056s) and pHSL (4126s) were ordered

from Cell Signaling (Danvers, MA, USA).

Metabolic studies

For analysis of metabolic index, the mice were placed in metabolic cages individually

connected with a comprehensive laboratory animal monitoring systems (Columbus

Instruments, Columbus, OH, USA). The mice were acclimatized to respiratory chambers for

48 h, followed by recording in real time for the data of consumption (VO2), carbon

dioxide production (VCO2) and respiratory exchange ratio (RER).

Human samples

Paired samples of visceral tissues were obtained from 47 females with Chinese Han origin

during abdominal surgery. Among which, 24 subjects were scheduled for bariatric surgery due

to morbid obesity, while the other 23 patients were subjected to exploratory surgeries to

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exclude or inflammatory diseases. The subjects were assigned to two cohorts (lean,

BMI < 25; obese, BMI ≥ 30). All subjects had a stable weight with fluctuations smaller than

2% of the body weight for at least 3 months before surgery. This study was approved by the

Institutional Review Board of Tongji Hospital, and informed consent was obtained from each subject. Biopsy samples from omental adipose tissue were collected during surgery, and were frozen immediately in liquid nitrogen, and stored at 80℃ before use.

Global DNA methylation assay and bisulfite DNA sequencing

Global DNA methylation was determined using a MethylFlashTM Methylated DNA

Quantification Kit (Epigentek, Farmingdale, NY, USA) as instructed. Bisulfite DNA sequencing was conducted as previously described (24).

Chromatin immunoprecipitation (ChIP) assay

Fresh epididymal adipose tissues from HFDinduced obese mice were ground into small pieces (12mm3) in liquid nitrogen, and then crosslinked for 15min by 1% formaldehyde in

PBS. ChIP assays were performed using a ChIP Assay Kit (Beyotime Biotechnology, Jiang Su,

China) as detailed in the previous studies (25). Polyclonal antibodies against C/EBPα (sc61X) and ATF6 (sc22799X) were employed for the assays, and a normal rabbit IgG (sc2027X,

Santa Cruz Biotechnology, Santa Cruz, CA, USA) was used for negative controls. Primers used for ChIP assays are listed in Supplementary Table 3.

MBD2 ChIP-seq

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MBD2 ChIPseq was performed following a previously reported protocol (26). Briefly,

genomic DNA was isolated from epididymal adipose tissues of WT mice following 16wk of

HFD or ND induction. Genomic DNA originated from six mouse of each group was pooled,

and then fragmented into 100350bp in length using a Covaris M220TM

FocusedultrasonicatorTM (Covaris, MA, USA). The fragmented DNA from each pool was

then subject to enrichment of methylated CpG DNA using a MethylMiner methylated DNA

enrichment kit (Invitrogen, Carlsbad, CA) as instructed. The captured DNA was next

subjected to high throughput DNA sequencing using a Highseq 2500 platform in

BGIShenzhen (Shenzhen, China).

Plasmid constructs and luciferase reporter assay

The peak regions for Raptor (4128 to 3802) and Ucp1 (3467 to 3220) (start codon as +1)

were amplified from mouse genomic DNA. The mutated peak region for Raptor and Ucp1

were directly synthesized by the Tsingke Biological Technology (Beijing, China), in which

cytosines located in all CpG sites were mutated into adenosine. The core regions for

Raptor (3801 to +82) and Ucp1 (3221 to 1) were PCR amplified, and then PCR ligated to

the peak region prepared above as previously reported (27). The resulting products were

subcloned into a pGL3 vector (pGL3Raptor wt, pGL3Raptor mut, pGL3Ucp1 wt,

pGL3Ucp1 mut), and then confirmed by DNA sequencing, respectively. In vitro methylation

was carried out by incubating all constructs with SssI CpG Methyltransferase (Thermo Fisher,

Beverly, MA,USA) at 37℃ for 15 min, which was then confirmed by bisulfite DNA

sequencing as above. For Ucp1 promoter reporter assays, C3H10T 1/2 cells were transduced

with Mbd2 adenovirus (043798A, Abcam Inc.), followed by transfecting with a mixture of 8

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plasmids for pGL3 luciferase reporter and pRLTK luciferase (20:1). The cells were treated with 10µM forskolin for 4h following 24h of transfection, and then harvested for analysis of luciferase activities using the dualluciferase reporter assay system (Promega, Madison, WI,

USA). For analysis of Raptor promoter reporter activity, the plasmids were transfected into

3T3L1 cells as above, and the cells were harvested 30h after transfection without forskolin stimulation.

Statistical analysis

All data were expressed as mean ± SEM. The Graphpad Prism 5.0 software (La Jolla, CA,

USA) was employed for statistical analysis of all data using the student’s ttest or oneway or twoway ANOVA where appropriate. In all cases, P < 0.05 was considered with statistical significance. Detailed approaches for bioinformatic analysis of ChIPseq data were described in the supplementary methods.

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RESULTS

Mice deficient in Mbd2 are protected from HFD-induced obesity

We first sought to address the impact of DNA methylation and Mbd2 deficiency on the

development of obesity and type 2 diabetes. For this purpose, 8week old Mbd2/ and control

littermates were fed with HFD for 16 weeks. It was interestingly noted that Mbd2/ mice were

significantly protected from HFDinduced obesity (Fig. 1A & B), and importantly, the lower

body weight in Mbd2/ mice was predominantly featured by the reduction of white adipose

tissue (WAT) mass such as the epididymal adipose tissues (Fig. 1C & D). Of note, no

significant difference in terms of tibia length, a marker for mouse development, was

characterized between Mbd2/ mice and control littermates (Fig. 1E), indicating that the lower

body weight identified in Mbd2/ mice was not caused by the delay of body development

(growth retardation). Furthermore, measurement of food intake revealed that Mbd2/ mice

actually consumed more food than their counterparts (Fig. 1F). Together, these data suggest

that loss of Mbd2 provides protection for mice against HFDinduced obesity.

Mbd2 deficiency improves glucose tolerance and insulin sensitivity

To elucidate the impact of Mbd2 deficiency on type 2 diabetes, we examined the development

of insulin resistance and glucose intolerance in Mbd2/ and WT littermates after 16 weeks of

HFD feeding. Consistent with the above observations, Mbd2/ mice showed significantly

lower levels of blood glucose both in the fasted and fed state than that of control littermates

(Fig. 2A). Similarly, Mbd2/ mice displayed significantly decreased serum insulin levels in

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the fasted state (Fig. 2B) along with a significant reduction for the homeostasis model assessment of insulin resistance (HOMAIR) index (Fig. 2C). Unlike their WT littermates,

Mbd2/ mice were characterized by the significantly improved glucose tolerance (Fig. 2D) and insulin sensitivity (Fig. 2E, Fig. S1). Indeed, Western blot analysis of AKT and IRS1, the two critical insulin signaling molecules, revealed that epididymal adipose tissue originated from Mbd2/ mice was featured by the significantly increased phosphorylated AKT (pAKT

Thr308 ) and IRS1 (pIRS1 Tyr989 ) as compared with their control counterparts following

16week of HFD induction, while no perceptible difference was noted between Mbd2/ mice and littermate controls in terms of their expressions (Fig. 2F). Collectively, our results support that loss of Mbd2 improves glucose tolerance and insulin sensitivity following HFD induction.

Loss of Mbd2 attenuates HFD-induced hyperlipemia and hepatosteatosis

Next, we examined the effect of Mbd2 deficiency on HFDinduced hyperlipemia and hepatic steatosis. Remarkably, mice deficient in Mbd2 were manifested by the significantly lower levels of plasma triglycerides (TG) and total cholesterol (TC) than their littermate controls after 16week of HFD induction, and particularly, significantly lower TC levels were even noted in Mbd2/ mice under normal diet (Fig. 3A). In line with this observation, hepatic steatosis was detected in HFDinduced WT controls as featured by the significant change of liver color (Fig. 3B, left panel) and weight (Fig. 3B, right panel) as compared with that of

Mbd2/ mice. Indeed, a marked intrahepatic lipid accumulation was noted in HFDinduced littermate controls, while it was significantly attenuated in Mbd2/ mice as determined by

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H&E and OilredO staining (Fig. 3C). Moreover, the control littermates displayed a 3.6fold

higher level of hepatic triglycerides than that of Mbd2/ mice (Fig. 3D). Taken together, these

data provided evidence suggesting that loss of Mbd2 also protects mice against HFDinduced

dyslipidemia and hepatic steatosis.

Mbd2 deficiency prevents altered energy homeostasis and inflammation.

To further assess the impact of Mbd2 deficiency on the development of obesity, we measured

metabolic index by assessing respiratory exchange ratio (RER) of mice housed in metabolic

cages. Remarkably, HFDinduced Mbd2/ mice showed significantly higher RER than that of

control mice (Fig. 4A), while they manifested comparable RER as control mice once they

were under ND condition (Fig. 4B, Fig. S2), indicating that that WT mice displayed abnormal

fat metabolism upon HFD induction as indicated by the decreased RER, while loss of Mbd2

attenuated HFDinduced RER decrease. Consistently, the size of epididymal adipocytes was

significantly larger in littermate controls (Fig. 4C) as manifested by the 1.4fold higher mean

adipocyte area than that of Mbd2/ mice (Fig. 4C, 9087±240µm2 vs. 3810±355µm2) following

HFD induction, which was consistent with the aforementioned reduced epididymal adipose

mass in Mbd2/ mice (Fig. 1D). We then checked plasma , an adipocytederived

hormone. HFDinduced littermate controls displayed a 4.5fold increase for plasma leptin,

while no perceptible change in terms of plasma leptin in Mbd2/ mice was noted following

HFD induction (Fig. 4D).

Next, we examined the expression of genes associated with energy expenditure by realtime

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PCR. Similarly, no discernible difference for the expression of Ucp1, Pgc1a and Ppara was noted between Mbd2/ and control littermates under normal diet, while significantly higher levels of Ucp1, Pgc1a and Ppara mRNA were detected in Mbd2/ mice following HFD induction, and particularly, Mbd2/ mice showed significant upregulation of Ucp1 mRNA once fed with HFD (Fig. 4E). Indeed, Western blot analysis of epididymal adipose tissues revealed that Mbd2/ mice were featured by the enhanced lipolysis and βoxidation as evidenced by the higher levels of phosphorylated hormonesensitive lipase ( pHSL), adipose triglyceride lipase (ATGL) and carnitine palmitoyltransferase (CPT1) than that of littermate controls (Fig. 4F). Comparable results were obtained for analysis of tissue lysates derived from skeletal muscle and liver (Fig. S3 & 4).

Given that obesity is generally associated with inflammation in the visceral adipose tissues, we thus next selectively examined several inflammatory markers. It was interestingly noted that mRNA levels for F4/80, Mcp1 and Tnfα were significantly lower in eWAT originated from Mbd2/ mice as compared with that of control littermates (Fig. 4G). Together, our data support that loss of Mbd2 protects mice against HFDinduced alteration for energy homeostasis and inflammatory response in adipose tissues.

Mbd2 deficiency provides protection for ob/ob mice against obesity

To confirm the above observations, we bred the Mbd2 null allele into ob/ob mice to generate

Mbd2 and leptin double knockout (Mbd2ob/ob) mice. Remarkably, Mbd2ob/ob mice gained substantially less weight than that of ob/ob mice (Fig. 5A). Consistent with this observation,

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Mbd2ob/ob mice displayed significantly smaller size for adipocytes in epididymal adipose

tissues than that of ob/ob mice (Fig. 5B, 9722 ±309.2m2 vs. 11720 ±504.4m2). Similarly, lipid

deposition in the liver was significantly attenuated in Mbd2ob/ob mice (Fig. 5C) along with a

marked reduction for the levels of hepatic triglycerides (Fig. 5D). Consistently, Mbd2ob/ob

mice were characterized by the significantly improved glucose tolerance (Fig. 5E) and insulin

sensitivity (Fig. 5F) as compared with that of ob/ob mice. Collectively, these results suggest

that loss of Mbd2 also provides protection for ob/ob mice against obesity and insulin

resistance.

HFD induces epididymal adipocytes to undergo a DNA methylation turnover

To dissect the mechanisms by which Mbd2 deficiency prevents obesity and insulin resistance,

we first compared global DNA methylation levels in epididymal adipose tissues between

normal and HFDinduced mice. Interestingly, HFD induced a global DNA hypomethylation

as manifested by the reduction of total 5mC levels as compared with that of mice with

normal diet (Fig. 6A). Importantly, a similar trend was noted by the analysis of genomic DNA

originated from omental adipose tissues of obese patients and normal subjects (Fig. 6B),

indicating that the development of obesity is associated with changes of DNA methylation

levels and/or patterns (methylation turnover). To exclude that the above global methylation

changes were not a result from shift of infiltrated inflammatory cells such as macrophages, we

isolated mature adipocytes from epididymal adipose tissue of obese mice and normal mice,

followed by analysis of global DNA methylation as above, and comparable results were

obtained (Fig. S5). In line with these observations, HFD attenuated the expression of MBD2,

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a reader for DNA methylomeencoded information (12; 28), in the eWAT, liver and skeletal muscle (Fig. 6C). Of note, we also compared global DNA methylation levels between WT and Mbd2/ mice fed with normal or HFD, and failed to detect a perceptible difference (data not shown). Given that MBD2 itself does not affect the methylation of DNA (7; 12), our results indicate that MBD2 modulates HFDinduced obesity and insulin resistance by deciphering the information resulted from DNA methylation changes.

To demonstrate the detailed information of above HFDinduced DNA methylation turnover, eWAT MBD2MethylCpG DNA complexes were first precipitated from mice fed with HFD and normal diet, followed by high throughput DNA sequencing (ChIPseq). Interestingly,

11,218 peakrelated genes were actually shared by both normal and HFDinduced mice, while

7,439 peakrelated genes were noted to be HFD specific, and 1,069 genes were associated with normal diet (Fig. 6D). Methylation associated representative genes relevant to energy metabolism are listed in supplementary Tables 5 and 6. Indeed, the color of heat map and curve associated with DNA methylation levels and/or patterns generated by bioinformatics analysis indicated a typical DNA methylation turnover following HFD induction (Fig. 6E).

HFD potently induces DNA demethylation of genes for energy storage

Mbd2 ChIPPCR for selective analysis of promoter regions of above identified genes demonstrated positive results, confirming that these methylated peaks are the endogenous binding sites for Mbd2 (data not shown). To further dissect the mechanisms by which

HFDinduced DNA methylation turnover predisposes to the development of obesity, we

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defined gene panels for energy storage and expenditure as described, which allowed us to

characterize 159 genes associated with energy expenditure (supplementary Table 7), and 216

genes relevant to energy storage (supplementary Table 8 ). Analysis of total signals of

ChIPseq data in the promoter region (5K up TSS) of two panels failed to detect a significant

difference in terms of methylation state for most of the genes between HFD and NDinduced

mice. However, once we analyzed the data again with a 1.5fold cutoff, a significant

reduction for methylation levels of genes associated with energy storage was noted after HFD

induction as evidenced by the boxplot analysis of energy storage and expenditure genes (Fig.

7A). Although HFD induced a trend for decreased methylation levels of energy expenditure

genes, but without a statistical significance (Fig. 7A). Collectively, these data support that

HFD induces DNA demethylation of genes both for energy storage and expenditure, but its

potency to induce DNA demethylation of genes associated with energy storage is much higher.

To confirm this notion, we compared the enrichment of peaks between HFD and NDinduced

mice, and found that HFDinduced mice manifested 2836 decreased peaks and 2103 increased

peaks as compared with NDinduced mice. analysis for differential peaks of

related genes demonstrated MAPK signaling pathway was significant enriched in the

decreased peaks (Fig. 7B). Given the role of MAPK signaling pathway played in obesity and

insulin resistance (2931), the ChIPseq data after gene ontology analysis also support that

HFD induced DNA hypomethylation of genes associated with energy storage.

We then sought to confirm the methylation state of above identified genes by selectively

analyzing the promoters of representative genes. Raptor, a typical gene involved in energy

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storage, and Ucp1, the most critical gene associated with energy expenditure, were selected for this analysis. Indeed, HFD induced a DNA hypomethylation for Raptor and Ucp1 promoters as evidenced by the lower total methylation levels in mice following HFD induction (Fig. 7C, Fig. S6). Bioinformatic analysis revealed that CpG site at position 3881 of Raptor promoter (start codon as +1) contains a potential Cebpα (Fig. S7), while CpG site at position –3288 of Ucp1 promoter (Start codon as +1) contains a potential

ATF6 binding site (Fig. S8). ChIP assays confirmed that Cebpα selectively bound to Raptor promoter at CpG site of 3881 (Fig. 7D, upper panel), and ATF6 selectively bound to Ucp1 promoter at CpG site of 3288 (Fig. 7D, lower panel).

The above results prompted us to examine with focus for the methylation levels of those two

CpG sites following HFD induction. It was interestingly noted that CpG site at position 3881 of Raptor promoter was highly demethylated in HFDinduced mice (methylation levels: 55% vs. 90%) (Fig. 7E, left panel). In sharp contrast, analysis of CpG site at position –3288 of

Ucp1 promoter failed to detect such a great difference in terms of DNA demethylation

(methylation levels: 80% vs. 95%) (Fig. 7E, right panel), which in fact was similar to the methylation levels from analysis of Ucp1 promoter (Fig. 7C, right panel). Similar as above, analysis of Mbd2/ mice revealed similar methylation rates for the above indicated CpG sites following HFD induction (data not shown). In line with this observation, Western blot analysis of eWAT lysates detected significantly higher levels of Raptor in HFDinduced mice

(Fig. 7F), and PCR analysis of Raptor mRNA obtained similar results (Fig. S9). In contrast,

Western blotting still failed to detect Ucp1 in eWAT of HFDinduced mice (data not shown).

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Together, those data support the notion that HFD is more potent to induce DNA

hypomethylation of genes associated with energy storage.

Finally, we have cloned Raptor promoter into a pGL3 vector (pGLRaptor wt) as described

to confirm that MBD2 modulation of obesity is associated with HFDinduced DNA

methylation turnover. A mutated Raptor promoter reporter vector was also constructed, in

which cytosines in all CpG sites at the ChIPseq peak region between 4089 to 3874 were

mutated into adenosine (pGLRaptor mut). CpG sites within the reporter vectors were

methylated by SssI as described. 3T3L1 cells were first transduced with Mbd2 adenoviruses

and then transfected with above reporters, respectively. As expected, pGLRaptor mut showed

lower reporter activities than pGLRaptor wt under unmethylated condition. However,

treatment of reporters with SssI resulted in a significant reduction for the reporter activities,

but SssI treated pGLRaptor mut displayed similar reporter activities as that of its pGLRaptor

wt counterpart (Fig. 7G), indicating that methylation of CpG sites attenuated reporter

activities. We next conducted reporter assays for Ucp1 promoter, and consistent results were

obtained (Fig. 7H). Taken together, our results suggest that HFD induces a DNA methylation

turnover, and MBD2 modulates HFDinduced obesity by reading the information encoded by

this methylation turnover.

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Discussion

Previous studies including ours demonstrated evidence indicating that environmental insultinduced alterations of DNA methylome are implicated in the pathoetiology of complex diseases (3; 7; 32). Particularly, we found that ischemic insult induced endothelial cells to undergo a DNA methylation turnover as manifested by the changes of methylation levels and patterns, and MBD2 regulates angiogenesis by deciphering the information resulted from this

DNA methylation turnover (7). Obesity is a multifactorial chronic disease, which involves altered homeostasis of energy storage and expenditure via physiological processes (33).

Specifically, alterations in energy homeostasis could be caused by the changes of epigenetic factors such as DNA methylation, which can be induced by inadequate dietary habits, diminished physical exercise and genetic background (34). Despite past extensive studies, the exact impact of dietary style on DNA methylome relevant to the pathogenesis of obesity, however, is yet to be fully addressed. Given that consumption of unhealthy foods such as high carbohydrates and high fat with low fiber is considered to be the leading cause for developing metabolic disorders, we thus employed Mbd2/ mice to dissect the impact of DNA methylation on the pathoetiology of HFDinduced obesity and insulin resistance.

It was interestingly noted that mice deficient in Mbd2 were protected from HFDinduced obesity, which was not caused by the reduction of less food intake, and in fact, food consumption was found to be slightly higher in Mbd2/ mice than that of control mice. We also excluded the possibility that the phenotype was caused by retarded growth as there was

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no perceptible difference in terms of the length for tibias between Mbd2/ mice and control

littermates. In fact, previous studies have already suggested that loss of Mbd2 does not affect

murine development (12). Since obesity is generally associated with an array of metabolic

abnormalities termed “metabolic syndrome” such as insulin resistance and hyperlipidemia, we

also noted that Mbd2/ mice were protected from HFDinduced insulin resistance,

hyperlipidemia and hepatosteatosis. Particularly, the reduced adipocyte size characterized in

Mbd2/ mice could be the main cause of attenuated adipose tissue accumulation following

HFD induction. Indeed, it has been widely accepted that adipocyte size is associated with

triglyceride accumulation (35). To confirm the above phenotype, we then bred Mbd2 null

allele into ob/ob (Mbd2ob/ob) mice. Consistently, Mbd2ob/ob mice displayed significantly

less amount of weight gain along with improved glucose homeostasis and lipid deposition in

the liver. Collectively, we demonstrated convincing evidence that MBD2 regulates glucose

homeostasis and lipid metabolism implicated in the pathogenesis of HFDinduced obesity and

insulin resistance.

To dissect the mechanisms by which loss of Mbd2 represses HFDinduced obesity, we first

compared total DNA methylation state in epididymal adipose tissues between control and

HFDinduced mice. Interestingly, HFD induced a global DNA hypomethylation in epididymal

adipose tissues, and a similar trend was also noted in omental adipose tissues originated from

obese patients. These results are actually consistent with previous studies, in which oxidative

stress leads to a global DNA hypomethylation by interfering with the ability of DNA to

function as a substrate for DNMTs (36; 37). Surprisingly, attenuated MBD2 expression was

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characterized in the epididymal adipose tissues, skeletal muscle and liver following HFD induction. The cause by which HFD attenuates MBD2 expression is currently unknown.

Given that loss of Mbd2 prevents HFDinduced obesity, the attenuated MBD2 expression could be a compensated response due to HFDinduced imbalance of energy homeostasis.

Nevertheless, additional studies would be necessary to address the exact mechanism underlying this phenomenon.

MBD2 based ChIPseq assays were next conducted to characterize target genes with manifestation of DNA methylation changes following HFD induction. Indeed, the assays characterized a large number of genes relevant to energy storage and expenditure. Importantly, those genes exhibited unique changes either in DNA methylation levels or patterns, indicating that HFD rendered epididymal adipose tissues to undergo a DNA methylation turnover.

Bioinformatic analysis of ChIPseq data characterized 216 genes associated with energy storage and 159 genes relevant to energy expenditure, in which a significant decrease of DNA methylation levels for those genes associated with energy storage was noted. Importantly, selective analysis of Raptor, a specific and essential component of mTORC1 that positively regulates adipogenesis, lipogenesis, and glucose uptake (38), and Ucp1, an essential gene for energy expenditure (39), by bisulfite DNA sequencing confirmed our ChIPseq data. It was interestingly noted although HFD induced DNA hypomethylation for both genes involved in energy storage and expenditure, the extent of its impact on the induction of DNA hypomethylation in genes relevant to energy storage was much more potent. Indeed, GO pathway analysis revealed that MAPK signaling pathway was significantly hypomethylated.

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Given the role of MAPK signaling pathway played in adipogenesis, obesity and insulin

resistance, those data further support that HFD is more potent to induce DNA

hypomethylation of energy storage genes in favor of obesity development.

It is worthy of note that the discrepancy in terms of HFDinduced DNA hypomethylation

between genes responsible for energy storage and expenditure is likely associated with the

binding sites for transcription factors. For example, the extent of DNA hypomethylation for

CpG site at position 3881 of Raptor promoter was significantly higher than that of CpG site

at position –3288 of Ucp1 promoter as compared with their corresponding counterpart.

Bioinformatic analysis and ChIP assays revealed that CpG site at position 3881 of Raptor

promoter contains a binding site for Cebpα, while CpG site at position –3288 of Ucp1

promoter contains a binding site for ATF6. Importantly, it seems that this methylation

discrepancy contributed to the enhanced Raptor expression following HFD induction, as

determined by the methylation dependent promoter reporter assays and Western blot analysis

of epididymal adipose tissues. In line with our assumption, the DNA methylome settings have

also been noted to be the ultimate integration sites of both environmental and differentiative

inputs, which preferentially determine the transcription of NFκBdependent genes such as

IL1β and TNFα (4043). Taken together, our studies indicate that HFD induced a global

DNA hypomethylation, but its impact on the induction of DNA hypomethylation in genes

responsible for energy storage is much more potent than that in genes associated with energy

expenditure. MBD2 implicates in the pathogenesis of HFDinduced obesity and insulin

resistance by reading the information resulted from those DNA methylation changes.

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Therefore, once MBD2 is depleted, the effect of this methylation turnover cannot be implemented, which then promotes energy expenditure to prevent HFDinduced obesity. It is noteworthy that the changes of DNA methylation profiles identified in eWAT are unlikely caused by the shift of infiltrated immune cells such as macrophages, since the isolated mature adipocytes from eWAT of HFD induced obese mice and normal mice displayed comparable results as the ChIPseq data.

In summary, we demonstrated evidence that HFD renders epididymal adipose tissues to undergo a DNA methylation turnover as manifested by the changes of methylation levels and/or patterns. MBD2 interprets the information encoded by this DNA methylation turnover for regulation of an array of genes to alter the homeostasis of energy storage and expenditure in favor of obesity development. Therefore, loss of Mbd2 provides protection for mice against

HFDinduced obesity and insulin resistance. Given that MBD2 itself does not affect DNA methylation and is dispensable for daily life processes, our results suggest that MBD2 could be a viable epigenetic target for developing more efficacious and costeffective therapies for prevention and treatment of obesity in clinical settings.

Acknowledgments

We are grateful to Dr. Adrian Bird ( Wellcome Trust Centre for Cell Biology, University of

Edinburgh，Edinburgh, UK) for providing the Mbd2 knockout mice, and Dr. QiQun Tang

(Department of Biochemistry and Molecular Biology, Fudan University Shanghai Medical

College, Shanghai, China) for providing the C3H10T 1/2 cell line. We would also like to

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thank Dr. Wenye Mo (the Center for Biomedical Research, Tongji Hospital, Tongji Medical

College, Huazhong University of Science and Technology, China）for animal studies.

Duality of Interest

No potential conflicts of interest relevant to this article were reported.

Sources of Funding

This study was supported by the National Natural Science Foundation of China (81130014,

81428001 and 81530024), the European Foundation for the Study of Diabetes

(EFSD)/Chinese Diabetes Society (CDS)/Lilly Program for Collaborative Diabetes Research

between China and Europe, the Program for Changjiang Scholars and Innovative Research

Team in University (IRT_14R20), and the Innovative Funding for Translational Research

from Tongji Hospital.

Author Contributions

J.C., J.S., X.H., M.Z., S.H, S.Z., P.Y., and C.Z. were responsible for conducting all

experiments and data analysis. J.C. and J.S. wrote the manuscript. Q.Y., F.X. and D.W.W

were involved in review of the manuscript. S.Z., C.Z., J.Z., Q.N., D.L.E. Z.Z. and Z.C

contributed to discussion and review of the manuscript. D.L.E., C. Z. and C.Y.W. contributed

to the study design and manuscript preparation. C.Y.W. is the guarantor of this work and takes

full responsibility for the content of the manuscript.

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Disclosures

None.

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Figure Legends

Fig. 1: Loss of Mbd2 provides protection for mice against HFDinduced obesity. A:

Representative pictures for WT and Mbd2/ (KO) mice after feeding with HFD or normal chow for 16 weeks. B: Comparison of body weight changes between WT and KO mice during the course of HFD induction (n = 15 for each group). C: Representative pictures for epididymal adipose tissues collected from WT and KO mice after 16wk of HFD or normal chow feeding. D: Analysis of the weight for epididymal adipose tissues collected from WT and KO mice after 16wk of HFD or normal chow feeding (n = 15 for each group). E:

Comparison of tibia length between WT and KO mice (N = 15 for each group). F:

Comparison of mean weekly food consumption between WT and KO mice (n = 15 for each group). HF WT: WT mice fed with HFD; HF KO: Mbd2/ mice fed with HFD; ND WT: WT mice fed with normal diet; ND KO: Mbd2/ mice fed with normal diet. *, p < 0.05; **, p <

0.01.

Fig. 2: Mice deficient in Mbd2 manifest improved glucose homeostasis after 16wk of HFD induction. A: Comparison of blood glucose levels between WT and KO mice under fasting

(left) and fed condition (right). B: Analysis of fasting plasma insulin levels. All mice were fasted for 12h before the analysis. C: Results for HOMAIR index. D: Results for intraperitoneal glucose tolerance tests (up), and Areas Under Curves (AUC) for the blood glucose levels (low). E: Results for intraperitoneal insulin tolerance tests (up) and Areas

Under Curves (AUC) for the blood glucose levels (low). F: Western blot analysis for pIRS

(Y989), total IRS1, pAkt (Thr308), and total Akt in the epididymal adipose tissues. Upper

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panel: representative Western blot results; lower panel: bar graphs showing the results of all

animals examined. Fifteen mice were included in each study group. *, p < 0.05; **, p < 0.01.

Fig. 3: Loss of Mbd2 prevents HFDinduced hyperlipemia and hepatosteatosis. A: Results for

fasting plasma triglyceride (left) and total cholesterol (right) levels (n = 13~16 for each

group). B: Comparison of liver weight. Left: Representative pictures for livers collected from

WT and KO mice. Right: Results for liver weight (n = 13~16 for each group). C:

Representative results for H&E staining (left panel) and oil red O staining (right panel) of

liver sections. The images were taken under ×200 amplifications. D: Results for analysis of

triglyceride levels in the liver (n = 13~16 for each group). **, p < 0.01.

Fig. 4: Mbd2 deficiency protects against HFDinduced alteration of energy homeostasis and

adipose inflammation. A: Results for metabolic analysis of respiratory exchange ratio (RER)

of mice under HFD induction. Left: results for real time monitoring of RER; Right: mean

value of RER. B: Results for metabolic analysis of respiratory exchange ratio (RER) of mice

under normal diet. Similarly, left panel is the results for real time monitoring of RER, while

right panel presents mean value of RER. C: Results for analysis of the adipocyte size. Left:

representative results for H&E staining of epididymal tissue sections. The images were taken

under ×200 amplifications. Right: results for analysis of mean adipocyte area in the

epididymal adipose tissues. D: Analysis of plasma leptin levels. E: Realtime PCR results for

analysis of thermogenic genes Ucp1, Pparα and Ppargc1a. F: Western blot results for

analysis of pHSL and ATGL (lipolysis) and CPT1 (βoxidation) in the epididymal adipose

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tissues. G: Realtime PCR analysis of inflammatory markers, Mcp1, Tnfα and F4/80, in the visceral adipose tissues. Six mice were studied in each group. *, p < 0.05; **, p < 0.01.

Fig. 5: Loss of Mbd2 attenuates obesity and insulin resistance in ob/ob mice. A: Comparison of body weight between ob/ob and Mbd2ob/ob mice (n = 8 for each group). B Mbd2ob/ob mice manifested reduced adipocyte size as compared with that of ob/ob mice. Left:

Representative results for H&E stained epididymal adipose sections. Right: Results for analysis of mean adipocyte area. C: Loss of Mbd2 repressed hepatic lipid deposition in ob/ob mice. Left: representative results for oilred O staining of liver sections. Right: results for triglyceride levels in the liver. D: Results for intraperitoneal glucose tolerance tests (Left) and

AUC for GTTs (Right). E: Results for intraperitoneal insulin tolerance tests (Left) and AUC for ITTs (Right). Six mice were examined in each study group, and images were taken under

×200 amplifications. *, p < 0.05.

Fig. 6: HFD induces a DNA methylation turnover in the epididymal adipose tissues. A:

Comparison of total 5mC levels in eWAT DNA between WT mice fed with HFD or normal chow for 16 weeks (n = 8 for each group). B: Analysis of total 5mC levels in genomic DNA of omentum adipose tissues originated from obese patients (n = 24) and control subjects (n =

23). C: Western blot analysis of MBD2 expression in the eWAT, liver and skeletal muscle after 16wk of HFD or normal induction. Left: Representative Western blotting results. Right:

Quantitative results for all mice examined (n = 6 for each group). D: Result for differential analysis according to the peakrelated genes shown in Venn diagram. Pink part represents

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unique ChIPseq enriched genes following HFD induction, blue part represents unique genes

enriched from normal chow fed mice, and violet part represents the number of enrich genes

shared by HFD and normal chow induced mice. E: Results for analysis of common peaks’

fold enrichment. Heat maps were generated using the heatmap.2 function in the gplots

package. The color of heat map and curve represent the relationship of each sample’s fold

enrichment. Values represent means ± SEM. *, p < 0.05.

Fig. 7: HFD is more potent to induce DNA demethylation of genes relevant to energy storage.

A: Boxplot results of genes identified from bioinformatic analysis of ChIPseq data. Left:

CHIPseq enrichment level of promoters in genes associated with energy storage; Right:

CHIPseq enrichment level of promoters in genes relevant to energy expenditure. B: Results

for gene ontology analysis of hypomethylated peaks. C: Bisulfite analysis of DNA

methylation within the Raptor and Ucp1 promoter region. D: Chromatin immunoprecipitation

(ChIP) PCR results for analysis of Cebpα and ATF6 binding activity in the Raptor and Ucp1

promoter. E: Results for bisulfite analysis of 3881 CpG within the Raptor promoter and

–3288 CpG within the Ucp1 promoter. F: Results for Western blot analysis of Raptor in the

eWAT of HFD or normal diet fed mice. Left: representative Western blotting results. Right:

result for 6 mice analyzed in each group. G: Results for methylation dependent Raptor

promoter luciferase reporter assays. The plasmids were methylated by SssI as described and

then transfected into 3T3L1 cells. H: Methylation dependent luciferase reporter assays for

the Ucp1 promoter. The assays were conducted as above in C3H10T 1/2 cells. *, p < 0.05.

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Fig. 1: Loss of Mbd2 provides protection for mice against HFD-induced obesity. A: Representative pictures for WT and Mbd2-/- (KO) mice after feeding with HFD or normal chow for 16 weeks. B: Comparison of body weight changes between WT and KO mice during the course of HFD induction (n = 15 for each group). C: Representative pictures for epididymal adipose tissues collected from WT and KO mice after 16wk of HFD or normal chow feeding. D: Analysis of the weight for epididymal adipose tissues collected from WT and KO mice after 16wk of HFD or normal chow feeding (n = 15 for each group). E: Comparison of tibia length between WT and KO mice (N = 15 for each group). F: Comparison of mean weekly food consumption between WT and KO mice (n = 15 for each group). HF WT: WT mice fed with HFD; HF KO: Mbd2-/- mice fed with HFD; ND WT: WT mice fed with normal diet; ND KO: Mbd2-/- mice fed with normal diet. *, p < 0.05; **, p < 0.01.

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Fig. 2: Mice deficient in Mbd2 manifest improved glucose homeostasis after 16wk of HFD induction. A: Comparison of blood glucose levels between WT and KO mice under fasting (left) and fed condition (right). B: Analysis of fasting plasma insulin levels. All mice were fasted for 12h before the analysis. C: Results for HOMA-IR index. D: Results for intraperitoneal glucose tolerance tests (up), and Areas Under Curves (AUC) for the blood glucose levels (low). E: Results for intraperitoneal insulin tolerance tests (up) and Areas Under Curves (AUC) for the blood glucose levels (low). F: Western blot analysis for p-IRS (Y989), total IRS1, p-Akt (Thr308), and total Akt in the epididymal adipose tissues. Upper panel: representative Western blot results; lower panel: bar graphs showing the results of all animals examined. Fifteen mice were included in each study group. *, p < 0.05; **, p < 0.01.

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Fig. 3: Loss of Mbd2 prevents HFD-induced hyperlipemia and hepatosteatosis. A: Results for fasting plasma triglyceride (left) and total cholesterol (right) levels (n = 13~16 for each group). B: Comparison of liver weight. Left: Representative pictures for livers collected from WT and KO mice. Right: Results for liver weight (n = 13~16 for each group). C: Representative results for H&E staining (left panel) and oil red O staining (right panel) of liver sections. The images were taken under ×200 amplifications. D: Results for analysis of triglyceride levels in the liver (n = 13~16 for each group). **, p < 0.01.

190x142mm (300 x 300 DPI)

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Fig. 4: Mbd2 deficiency protects against HFDinduced alteration of energy homeostasis and adipose inflammation. A: Results for metabolic analysis of respiratory exchange ratio (RER) of mice under HFD induction. Left: results for real time monitoring of RER; Right: mean value of RER. B: Results for metabolic analysis of respiratory exchange ratio (RER) of mice under normal diet. Similarly, left panel is the results for real time monitoring of RER, while right panel presents mean value of RER. C: Results for analysis of the adipocyte size. Left: representative results for H&E staining of epididymal tissue sections. The images were taken under ×200 amplifications. Right: results for analysis of mean adipocyte area in the epididymal adipose tissues. D: Analysis of plasma leptin levels. E: Realtime PCR results for analysis of thermogenic genes Ucp1, Pparα and Ppargc1a. F: Western blot results for analysis of pHSL and ATGL (lipolysis) and CPT1 (βoxidation) in the epididymal adipose tissues. G: Realtime PCR analysis of inflammatory markers, Mcp1, Tnfα and F4/80, in the visceral adipose tissues. Six mice were studied in each group. *, p < 0.05; **, p < 0.01.

190x142mm (300 x 300 DPI)

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Fig. 5: Loss of Mbd2 attenuates obesity and insulin resistance in ob/ob mice. A: Comparison of body weight between ob/ob and Mbd2-ob/ob mice (n = 8 for each group). B Mbd2-ob/ob mice manifested reduced adipocyte size as compared with that of ob/ob mice. Left: Representative results for H&E stained epididymal adipose sections. Right: Results for analysis of mean adipocyte area. C: Loss of Mbd2 repressed hepatic lipid deposition in ob/ob mice. Left: representative results for oil-red O staining of liver sections. Right: results for triglyceride levels in the liver. D: Results for intraperitoneal glucose tolerance tests (Left) and AUC for GTTs (Right). E: Results for intraperitoneal insulin tolerance tests (Left) and AUC for ITTs (Right). Six mice were examined in each study group, and images were taken under ×200 amplifications. *, p < 0.05.

190x142mm (300 x 300 DPI)

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Fig. 6: HFD induces a DNA methylation turnover in the epididymal adipose tissues. A: Comparison of total 5- mC levels in eWAT DNA between WT mice fed with HFD or normal chow for 16 weeks (n = 8 for each group). B: Analysis of total 5-mC levels in genomic DNA of omentum adipose tissues originated from obese patients (n = 24) and control subjects (n = 23). C: Western blot analysis of MBD2 expression in the eWAT, liver and skeletal muscle after 16wk of HFD or normal induction. Left: Representative Western blotting results. Right: Quantitative results for all mice examined (n = 6 for each group). D: Result for differential analysis according to the peak-related genes shown in Venn diagram. Pink part represents unique ChIP-seq enriched genes following HFD induction, blue part represents unique genes enriched from normal chow fed mice, and violet part represents the number of enrich genes shared by HFD and normal chow induced mice. E: Results for analysis of common peaks’ fold enrichment. Heat maps were generated using the heatmap.2 function in the gplots package. The color of heat map and curve represent the relationship of each sample’s fold enrichment. Values represent means ± SEM. *, p < 0.05.

180x137mm (300 x 300 DPI)

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Fig. 7: HFD is more potent to induce DNA demethylation of genes relevant to energy storage. A: Boxplot results of genes identified from bioinformatic analysis of ChIPseq data. Left: CHIPseq enrichment level of promoters in genes associated with energy storage; Right: CHIPseq enrichment level of promoters in genes relevant to energy expenditure. B: Results for gene ontology analysis of hypomethylated peaks. C: Bisulfite analysis of DNA methylation within the Raptor and Ucp1 promoter region. D: Chromatin immunoprecipitation (ChIP) PCR results for analysis of Cebpα and ATF6 binding activity in the Raptor and Ucp1 promoter. E: Results for bisulfite analysis of 3881 CpG within the Raptor promoter and –3288 CpG within the Ucp1 promoter. F: Results for Western blot analysis of Raptor in the eWAT of HFD or normal diet fed mice. Left: representative Western blotting results. Right: result for 6 mice analyzed in each group. G: Results for methylation dependent Raptor promoter luciferase reporter assays. The plasmids were methylated by SssI as described and then transfected into 3T3L1 cells. H: Methylation dependent luciferase reporter assays for the Ucp1 promoter. The assays were conducted as above in C3H10T 1/2 cells. *, p < 0.05.

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SUPPLEMENTARY DATA

Bioinformatic analysis of ChIP-seq data

Define the panel of genes associated with energy storage and expenditure

We searched the genes list from NCBI Gene, Gene Ontology and UniProt database

with the terms “obesity”, “energy homeostasis”, "energy metabolism", “energy

storage”, and “energy expenditure” by two independent investigators, and through which

we identified 742 genes from all these databases (supplementary Table 8). We then

selected the genes associated either with energy storage or expenditure by searching

the literatures from PubMed and Google Scholar with the term “gene name" and

"obesity" or "energy metabolism" or "energy homeostasis" and "adipose tissue" or

"adipocyte”. For a particular gene, if its deficiency protected mice from obesity or

overexpression exacerbated obesity, we then categorized it into the panel of energy storage.

On the contrary, if its deficiency or overexpression generated opposite phenotype, we

classified it into the panel of energy expenditure. We next searched them in the BioGPS

database to check their expression in the adipose tissue or adipocyte. If the transcriptional

activity index is lower than 50, the gene was considered without expression in adipose tissue.

Those genes were also excluded in which they are only expressed in the central nervous

system to involve in energy metabolism. The above screenings allowed us to characterize

216 genes associated with energy storage (supplementary Table 9) and 159 genes associated

with energy expenditure (supplementary Table 10).

Characterization of differential methylated genes. Diabetes Page 44 of 117

We first compared the signal of chipseq data in the promoter region to check the DNA methylation state of two panels. Promoter region of those differential methylated genes was defined as 5kb upstream TSS sites. We failed to detect a significant difference for most of the genes between HF and ND fed mice. To enhance the discrimination, a cutoff value

(defined >1.5fold) was then set up for data analysis. We calculated MBD2 ChIPseq enrichment levels over energy storage and energy expenditure gene loci with normalization to the Fragments Per Kilobase Of Exon Per Million Fragments Mapped (FPKM) value. For a particular differential methylated gene, at least a twofold difference between ND and HF samples was characterized. We divided TSS region of those genes into 100 bins and normalized MBD2 ChIPseq signal with the FPKM value.

Isolation of mature adipocytes

Isolation of adipocytes was performed as described previously (13). Briefly, male mice were sacrificed by CO2 inhalation, and the epididymal adipose tissue depots were washed in cold Dulbecco’s PBS supplemented with 0.5% BSA, followed by digestion with 1 mg/mL type II collagenase in the presence of 5 mmol/L CaCl2.

Tissue homogenates were incubated at 37°C for 30 min with shaking. After centrifugation, the floating oil were removed ,buoyant adipocytes were collected, filtered and collected as the adipocyte fraction. Page 45 of 117 Diabetes

References: 1. Aune UL, Ruiz L, Kajimura S: Isolation and differentiation of stromal vascular cells to beige/brite cells. J Vis Exp, 2013 2. Orr JS, Puglisi MJ, Ellacott KL, Lumeng CN, Wasserman DH, Hasty AH: Tolllike 4 deficiency promotes the alternative activation of adipose tissue macrophages. Diabetes 61:27182727, 2012 3. H X, GT B, Q Y, G T, D Y, CJ C, J S, A N, JS R, LA T, H C: Chronic inflammation in fat plays a crucial role in the development of obesityrelated insulin resistance. Journal of Clinical Investigation, 2003 4. Zhong J, Yu Q, Yang P, Rao X, He L, Fang J, Tu Y, Zhang Z, Lai Q, Zhang S, Kuczma M, Kraj P, Xu JF, Gong F, Zhou J, Wen L, Eizirik DL, Du J, Wang W, Wang CY: MBD2 regulates TH17 differentiation and experimental autoimmune encephalomyelitis by controlling the homeostasis of Tbet/Hlx axis. J Autoimmun 53:95104, 2014

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Figure Legends for Supplementary Figures:

Supplementary Figure S1: Results for the Area Above Curve (AAC) of Insulin tolerance tests.

Supplementary Figure S2: Metabolic index measured in CLAMS metabolic cages.

A: Metabolic data for mean oxygen consumption (VO2) and carbon dioxide production

(VCO2) of HFDinduced mice at each time point（Left, Middle）; The average VO2 and VCO2 of mice under HFD (Right). B: Metabolic data for mean oxygen consumption (VO2) and carbon dioxide production (VCO2) of mice under normal diet at each time point （Left, Middle）; The average VO2 and VCO2 of mice under normal diet (Right).

Supplementary Figure S3: Real Time PCR results for genes associated with energy metabolism in the liver and skeletal muscle after 16wk of HFD or ND induction (n=8 per group).

Supplementary Figure S4: HFD induced Mbd2/ mice show higher expression of genes relevant to lipolysis and βoxidative. Western blot results for analysis of pHSL,

ATGL (lipolysis) and CPT1 (βoxidation) in the liver (A) and skeletal muscle (B). The expression of pHSL and CPT1 was higher in HFDinduced Mbd2/ mice as compared with WT controls.

Page 47 of 117 Diabetes

Supplementary Figure S5: The total 5mC levels of genomic DNA isolated from

mature adipocyte of HFD and NDinduced mice. Mature adipocytes were isolated

from epididymal adipose tissues after 16wk of HFD or ND induction as described, and the

5mC levels were measured using a MethylFlash Methylated DNA Quantification kit.

Supplementary Figure S6: Bisulfite DNA sequencing analysis of the selected Raptor

and Ucp1 promoter region. A: Results for a selected peak region located within the

Raptor promoter from MBD2 ChIPseq analysis. B: Results for a selected peak region

located within the Ucp1 promoter from MBD2 ChIPseq analysis. Genomic DNA was

isolated from epididymal adipose tissues, and was then subjected to bisulfite DNA

sequencing as described. C: Results for the same Raptor promoter region using

mature adipocytes genomic DNA isolated from epididymal adipose tissues. D: Results

for the same Ucp1 promoter region using mature adipocyte genomic DNA isolated

from epididymal adipose tissues. Unfilled cycles represent unmethylated cytosines,

while filled cycles represent methylated cytosines. A total of 20 clones were analyzed

for each sample.

Supplementary Figure S7: Results for bioinformatic analysis of the potential

binding sites within the Raptor promoter enriched from the

ChIPseq data. The Raptor promoter region enriched from ChIPseq data was

subjected to Transfac and PROMO analysis to predict potential transcription factor

binding sites. A potential Cebpα binding site was identified, which contains the 3881 Diabetes Page 48 of 117

CpG site.

Supplementary Figure S8: Results for bioinformatic analysis of the potential transcription factor binding sites within the Ucp1 promoter enriched from the

ChIPseq data. Similar as above, the Ucp1 promoter region enriched from ChIPseq data was subjected to Transfac and PROMO analysis to predict potential transcription factor binding sites. A potential ATF6 binding site was identified, which contains the

3302 CpG site.

Supplementary Figure S9: HFD is more potent to induce the expression of genes relevant to energy storage. A: Relative fold enrichment of peak regions in the promoter of genes relevant to energy storage and energy expenditure. Dok1 (tyrosine kinases1), Fasn (Fatty acid synthase), Trem2 (Triggering receptor expressed on myeloid cells 2), Thbs1 (Thrombospondin 1), Agpat4 (1acylglycerol3phosphate

Oacyltransferase 4) and Mir1032 are relevant to energy storage, while Leptin,

Gpr12 (coupled receptor 12), Ppargc1a (peroxisome proliferatoractivated receptorgamma 1 alpha), Parp1 (Poly(ADPribose)polymerase1),

FATP1 (fatty acid transport protein1) and Vegfa ( vascular endothelial growth factor

A) are associated with energy expenditure. B: Real Time PCR results in the epididymal adipose tissues for analysis of the above selected genes. The results confirmed the ChIPseq data as evidenced by the higher expression of energy storage genes after HFD induction (n=8 per group). Page 49 of 117 Diabetes

Supplementary Table 1: Primer sequences for real-time PCR.

Gene Sequence(5’3’)

UCP1 CACGGGGACCTACAATGCTT

GATTAGGGGTCGTCCCTTTCC

PGC1α CGGAAATCATATCCAACCAG

TGAGAACCGCTAGCAAGTTTG

PPARα GCGTACGGCAATGGCTTTAT

GAACGGCTTCCTCAGGTTCTT

Leptin TTCACACACGCAGTCGGTATC

GGCTGGTGAGGACCTGTTG

MCP1 CTCAGCCAGATGCAGTTAACGCCC

GGTGCTGAAGACCTTAGGGCAGAT

TNFα CGTCGTAGCAAACCACCAAG

GAGATAGCAAATCGGCTGACG

F4/80 CTCTTCTGGGGCTTCAGTGG

GCAGACTGAGTTAGGACCACA

Dok1 AAGACCGAGGCTTCTGAACG

ATAGCGACGCAACAGAGTGT

Trem2 CTGGAACCGTCACCATCACTC

CGAAACTCGATGACTCCTCGG

Fasn AAGCGGTCTGGAAAGCTGAA

CCTCTGAACCACTCACACCC

Thbs1 GCTGCCAATCATAACCAGCG

TTCGTTAAAGGCCGAGTGCT Diabetes Page 50 of 117

Agpat4 AATGCAAAGAACTGCCCGGA

TTGATGGGCCAGATGACCAG

Scd1 AATATCCTGGTTTCCCTGGGTG

AGGAACTCAGAAGCCCAAAGCTC

Srebf1 AACTTTTCCTTAACGTGGGCCT

TGTCCAGTTCGCACATCTCG

Ucp2 CCTCCCCTGTTGATGTGGTC GGAAGGCATGAACCCCTTGT Ucp3 CTGCACCGCCAGATGAGTTT

ATCATGGCTTGAAATCGGACC mmumir1032 MI0000588 from Guangzhou Ribobio, China

Page 51 of 117 Diabetes

Supplementary Table 2: Primer sequences for bisulfate DNA PCR (NCBI mm9)

and

Gene Peaks Region Primer Sequence Size

chr8:85,811,11685, ATTTAGTGAAAGATATATTGGGAGT Ucp1 222 811,337 CACCTCTCTTCACCAATCTTAC chr11:119,183,582 TTTTGAGTTAGAATTTTATGAAG Raptor 333 119,183,914 CATACCCAACACACACACTA

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Supplementary Table 3: Primer sequences for ChIP PCR.

Gene Sequence(5’3’) Size

UCP1 CATTGGACATAACTTAGTGAAA 127bp

TGAGATGATTTGGCAGTGTG

Raptor TGTGTGTGGTGTGTGTTTATG 145bp

CCAAAGTCTCCTCCAATAGC

Page 53 of 117 Diabetes

Supplementary Table 4: Primer for constructing plasmid of luciferase reporter assay. UCP1_Me_F1 CTGGCCCCACTTACTAAAGAGTT UCP1_Me_R1 GCCAGGCAAGCTGAAACTCC UCP1_Me_R2 GTGACGGCACTATAAATTGGCAT UCP1_Me_F2 CATGCCAATTTATAGTGCCGTC UCP1_KpnI_F GGGGTACCCTGGCCCCACTTACTAAAGAG UCP1_NcoI_R CATGCCATGGTGGCTTGGAGGGCAGAG

Raptor_F1 AAGGATGGCTCTAAACTTCTGAACC Raptor_R2 TCTCTCCAAAGTCTCCTCCAATAGC Raptor_F2 AGCTCAGCTATTGGAGGAGACTTT Raptor_R1 CCCCGAGTCCCATAAGAGGC Raptor_ Sma I _F TCCCCCGGGAAGGATGGCTCTAAACTTCTGAACC Raptor_HindIII_R CCAAGCTTGGGGAGGAGGGGGAGGG Diabetes Page 54 of 117

Page 55 of 117 Diabetes

Supplementary Table 5: Genes associated with energy storage characterized by

MBD2 ChIP-seq analysis.

Gene symbol Gene ID

Abca1 11303 Abcb11 27413 Abcg1 11307 Abhd6 66082 Acot11 329910 Acp5 11433 Acvr1c 269275 Acvr2b 11481 Adam12 11489 Adam17 11491 Adam23 23792 Aebp1 11568 Ager 11596 Agpat4 68262 Agt 11606 Agtr1a 11607 Akt1 11651 Alox5ap 11690 Angptl2 26360 Angptl3 30924 Arntl 11865 Atf3 11910 Atg7 74244 Bcat1 12035 Ccnd3 12445 Ccr2 12772 Diabetes Page 56 of 117

Ccrn4l 12457 Cd36 12491 Cd38 12494 Cd47 16423 Ceacam2 26367 Cebpa 12606 Cebpb 12608 Cerk 223753 Clic5 224796 Cmklr1 14747 Cnot3 232791 Cnr1 12801 Creb1 12912 Crtc3 70461 Cry1 12952 Cry2 12953 Ctsk 13038 Cx3cr1 13051 Cxcl14 57266 Cxcl5 20311 Cyp2e1 13106 Ddit3 13198 Dgat1 13350 Dgat2 67800 Dok1 13448 13555 Egln1 112405 Egr1 13653 Enpp2 18606 Page 57 of 117 Diabetes

Ephx2 13850 F2rl1 14063 Fabp4 11770 Fabp5 16592 Fads2 56473 Fas 14102 Flcn 216805 Fto 26383 Fyn 14360 G0s2 14373 Ghr 14600 Gprc5b 64297 Grn 14824 Hif1a 15251 Hmox1 15368 Hnf4a 15378 Htr2a 15558 Ifng 15978 Igf2bp2 319765 Ikbkb 16150 Ikbke 56489 Il17a 16171 Il1a 16175 Il1b 16176 Il1rn 16181 Irf5 27056 Irf7 54123 Itgax 16411 Jun 16476 Diabetes Page 58 of 117

Kcna3 16491 Keap1 50868 Khk 16548 Kl 16591 Lcat 16816 Lgals3 16854 Lgr4 107515 Lipc 15450 Lox 16948 Lpin1 14245 Lrrc8c 100604 Ltb4r1 16995 Ly86 17084 Maf1 68877 Map3k14 53859 Mapk8 26419 Mapk9 26420 Mark3 17169 Mark4 232944 Mchr1 207911 Mfge8 17304 Mgat1 17308 Mir1032 723825 Mir335 723930 Mir34a 723848 Mlxipl 58805 Mogat2 233549 Mstn 17700 Mtor 56717 Page 59 of 117 Diabetes

Nampt 59027 Nck1 17973 Nfkb1 18033 Nlrp3 216799 Nnmt 18113 Nod1 107607 Npy2r 18167 Nr1d2 353187 Nr1h4 20186 Nr1i2 18171 Nr2c2 22026 Nr3c2 110784 Nupr1 56312 Ogg1 18294 Oip5 70645 Pank1 75735 Paqr3 231474 Pask 269224 Pdcd4 18569 Pemt 18618 Pgf 18654 Pid1 98496 Pik3cg 30955 Pik3r1 18708 Pla2g1b 18778 Pla2g4c 232889 Plcd1 18799 Plin1 103968 Plin2 11520 Diabetes Page 60 of 117

Pnpla2 66853 Pnrc2 52830 Prcp 72461 Prkab1 19079 Prkar2a 19087 Prkcb 18751 Prkcd 18753 Pten 19211 Ptgs2 19225 Ptpn1 19246 Ptpn11 19247 Ralbp1 19765 Rasd1 19416 Rb1 19645 Rbp4 19662 Ren1 19701 Retn 57264 Rorc 19885 Rptor 74370 Scd1 20249 Sel1l 20338 Serpine1 18787 Sertad2 58172 Skp2 27401 Smad3 17127 Sort1 20661 Sp1 20683 Srebf1 20787 Ssfa2 70599 Page 61 of 117 Diabetes

Stat3 20848 Stat4 20849 Stk39 53416 Tas1r3 83771 Tbk1 56480 Tbx21 57765 Tgfb1 21803 Thbs1 21825 Thrsp 21835 Timp3 21859 Tlr2 24088 Tnc 21923 Tnf 21926 Tnfrsf14 230979 Tnfrsf1a 21937 Tnfrsf9 21942 Tnfsf12 21944 Tnfsf13b 24099 Tph1 21990 Traf3 22031 Traf6 22034 Trem2 83433 Trim72 434246 Trp53 22059 Trpm5 56843 Trpv4 63873 Txnip 56338 Vegfb 22340 Wisp1 22402 Diabetes Page 62 of 117

Xbp1 22433 Zfp423 94187

Page 63 of 117 Diabetes

Supplementary Table 6: Genes associated with energy expenditure characterized by MBD2 ChIP-seq analysis.

Gene symbol Gene ID

Abhd5 67469 Acacb 100705 Acadl 11363 Adipoq 11450 Adipor1 72674 Adipor2 68465 Adrb1 11554 Adrb2 11555 Adrb3 11556 Akr1b7 11997 Alkbh7 66400 Ankrd26 232339 Anxa1 16952 Apoa1 11806 Apoc1 11812 Apoe 11816 Aqp7 11832 Arf6 11845 Arrdc3 105171 Bdnf 12064 Bmp7 12162 Brd2 14312 Ccdc80 67896 Cd40 21939 Ceacam1 26365 Cidea 12683 Diabetes Page 64 of 117

Cideb 12684 Clock 12753 Cxcl1 14825 Cxcr4 12767 Dio2 13371 Dlk1 13386 Epo 13856 Esr1 13982 Ffar2 233079 Fgf21 56636 Foxc2 14234 Foxo1 56458 Fstl3 83554 Gcg 14526 Gcgr 14527 Gh 14599 Gip 14607 Gpr12 14738 Gpr39 71111 Igfbp2 16008 Il10 16153 Il18 16173 Il22 50929 Il6 16193 Irf4 16364 Irs2 384783 Jak2 16452 Jazf1 231986 Kdm3a 104263 Page 65 of 117 Diabetes

Lcn2 16819 Ldlr 16835 Lep 16846 Lepr 16847 Lipe 16890 Lrp6 16974 Med1 19014 Metrnl 210029 Mir27a 387220 Mir33 723897 Mkl1 223701 Mrap2 244958 Nfe2l2 18024 Nmu 56183 Nos3 18127 Npr3 18162 Nr0b2 23957 Osmr 18414 Otop1 21906 Parp1 11545 Pde3b 18576 Ppara 19013 Ppard 19015 Pparg 19016 Ppargc1a 19017 Prrx1 18933 Rgs5 19737 Rock1 19877 Serpina12 68054 Diabetes Page 66 of 117

Sfrp5 54612 Sh2b1 20399 Sirt1 93759 Slc2a4 20528 Stat5a 20850 Stat5b 20851 Tbc1d1 57915 Thrb 21834 Tmbim6 110213 Tnfaip3 21929 Tnfsf10 22035 Tpcn1 252972 Tpcn2 233979 Trib3 228775 Trpm8 171382 Trpv1 193034 Tsc1 64930 Tsc2 22084 Ube2l6 56791 Ucn3 83428 Ucp1 22227 Ucp2 22228 Ucp3 22229 Vav3 57257 Vegfa 22339 Wdtc1 230796 Xdh 22436 Hipk2 15258 Nrip1 268903 Page 67 of 117 Diabetes

Bmp4 12159 Prdm16 70673 Cnr2 12802 Crhr2 12922 Fam132a 67389 Gdf15 23886 Gstk1 76263 Gtf2h1 14884 Hdac4 208727 Lpl 16956 Mmp19 58223 Ncoa1 17977 Neil1 72774 Nos2 18126 Nr1h3 22259 Ntrk2 18212 Oma1 67013 Park7 57320 Pias1 56469 Pon3 269823 Prkaa1 105787 Prkaca 18747 Ptafr 19204 Rapgef3 223864 Sesn3 75747 Sfrp1 20377 Sirt2 64383 Sirt3 64384 Sirt6 50721 Diabetes Page 68 of 117

stk11 20869 Ppargc1b 170826 Adcy3 104111 Cidec 14311 Mfn2 170731 Opa1 74143 Nenf 66208 Atxn2 20239 Pik3ca 18706 Plscr3 70310 Page 69 of 117 Diabetes

Supplementary Table 7 Clinical characteristics for subjects included in the present study.

Lean (BMI<25) Obese (BMI≥30) P Value n 23 24 Age, y 40.08±2.32 42.63±2.82 0.486 BMI, Kg/m2 21.63±0.49 34.74±1.68 <0.001 Waist circumference, cm 70±2.21 95±2.47 <0.001 Hip circumference, cm 83.21±2.52 102±3.85 <0.001 Systolic BP, mm Hg 123±5.84 130±8.76 <0.05 TG, mmol/L 1.10±0.44 1.43±0.43 <0.05 TC, mmol/L 4.26±0.41 4.51±0.62 0.268 LDLc, mmol/L 2.54±0.52 2.85±0.71 0.088 HDLc, mmol/L 1.14±0.29 0.97±0.33 0.348 Fasting Glucose, mmol/L 5.33±0.42 6.12±0.39 0.068

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Supplementary Table 8 List for genes involved in energy metabolism.

Gene symbol Gene ID Abca1 11303 Abcb11 27413 Abcg1 11307 Abhd5 67469 Abhd6 66082 Acacb 100705 Acadl 11363 Ace2 70008 Acot11 329910 Acp5 11433 Acsm3 20216 Acvr1c 269275 Acvr2b 11481 Ad 104253 Adam12 11489 Adam17 11491 Adam23 23792 Adamts13 279028 Adcy3 104111 Adcy5 224129 Adipoq 11450 Adipor1 72674 Adipor2 68465 Adora2a 11540 Adrb1 11554 Adrb2 11555 Adrb3 11556 Page 71 of 117 Diabetes

Aebp1 11568 Agap2 216439 Ager 11596 Agrp 11604 Agt 11606 Agtr1a 11607 Agtr1b 11608 Agtr2 11609 Akr1b7 11997 Akt1 11651 Alkbh7 66400 Alms1 236266 Alox12 11684 Alox5ap 11690 AMPD2 109674 AMPD3 11717 Amy1 11722 Angptl2 26360 Angptl3 30924 Angptl4 57875 Angptl6 70726 Ankrd26 232339 Anxa1 16952 Aoc3 11754 Apba1 319924 Apln 30878 Apoa1 11806 Apobr 171504 Apoc1 11812 Diabetes Page 72 of 117

Apoe 11816 Aqp7 11832 Ar 11835 Arf6 11845 Arid5b 71371 Arntl 11865 Arrdc3 105171 Ascl1 17172 Atf3 11910 Atg7 74244 Atp10a 11982 Atp5g3 228033 Atrn 11990 Atxn2 20239 Avpr1a 54140 Azgp1 12007 Bbs12 241950 Bbs2 67378 Bbs4 102774 Bcat1 12035 Bdkrb1 12061 Bdnf 12064 Becn2 226720 Bhlhe40 20893 Bmp7 12162 Bmp8a 12163 Bmp8b 12164 Brd2 14312 Bsbob 493119 Page 73 of 117 Diabetes

Bsbob2 493120 Bsbob3 493121 Bsbob4 100035800 Bsbob5 100034953 C3 12266 C5ar2 319430 Ca3 12350 Calm1 12313 Capn10 23830 Cartpt 27220 Casp1 12362 Casp14 12365 Cav1 12389 Cbl 12402 Ccar2 219158 Ccdc80 67896 Cck 12424 Ccl2 20296 Ccl7 20306 Ccnd3 12445 Ccr2 12772 Cd14 12475 Cd180 17079 CD36 12491 Cd38 12494 Cd40 21939 Cd40lg 21947 Cd47 16423 Cd5l 11801 Diabetes Page 74 of 117

Cd69 12515 Cd80 12519 Cd86 12524 Cdh15 12555 Cdkn2a 12578 Ceacam1 26365 Ceacam2 26367 Cebpa 12606 Cebpb 12608 Cep19 66994 Cerk 223753 Ces3a 382053 Cfd 11537 Chga 12652 Chrm3 12671 Cidea 12683 Cideb 12684 Cidec 14311 Clec10a 17312 Clic5 224796 Clmp 71566 Clock 12753 Clps 109791 Cmklr1 14747 Cnot3 232791 Cnr1 12801 Cnr2 12802 Cntf 12803 Cntn2 21367 Page 75 of 117 Diabetes

Cntnap2 66797 Cort 12854 Cox4i1 12857 Cpe 12876 Creb1 12912 Crem 12916 Crhr1 12921 Crhr2 12922 CRTC3 70461 Cry1 12952 Cry2 12953 Ctf1 13019 Ctgf 14219 Ctla4 12477 Ctnnb1 12387 Ctsb 13030 Ctsd 13033 Ctse 13034 Ctsk 13038 Cux1 13047 Cx3cr1 13051 Cxcl1 14825 Cxcl12 20315 Cxcl14 57266 Cxcl5 20311 Cxcr3 12766 Cxcr4 12767 Cybb 13058 Cyp19a1 13075 Diabetes Page 76 of 117

Cyp2e1 13106 Dapk2 13143 Ddit3 13198 Dgat1 13350 Dgat2 67800 Dhrs7b 216820 Dio2 13371 Diobq 100035832 Dlk1 13386 Dll1 13388 Dnajc1 13418 Dnmt1 13433 Dnmt3a 13435 Dob1 109375 Dob2 112008 Dob3 112015 Dob4 112019 Dob7 112016 Dob9 112020 Dok1 13448 Dpp4 13482 Drd2 13489 Dusp2 13537 E2f1 13555 Edn1 13614 Efnb1 13641 Egln1 112405 Egr1 13653 Ei24 13663 Page 77 of 117 Diabetes

Eif2ak2 19106 Eif4ebp1 13685 Eif4ebp2 13688 Elovl3 12686 Enpp1 18605 Enpp2 18606 Epas1 13819 Ephx2 13850 Epm2aip1 77781 Epo 13856 Ern1 78943 Esr1 13982 Esr2 13983 Esrra 26379 F2rl1 14063 F3 14066 Fabp1 14080 Fabp3 14077 Fabp4 11770 Fabp5 16592 Fads2 56473 Fam132a 67389 Fas 14102 Fbp1 14121 Fcgr2b 14130 Fcor 100503924 Ffar1 233081 Ffar2 233079 Ffar4 107221 Diabetes Page 78 of 117

Fgf21 56636 Flcn 216805 Flt1 14254 Fob1 109394 Fob2 109399 Fob3 109398 Fob3a 100035759 Fob3b1 100034858 Fob4 109395 Foxc2 14234 Foxo1 56458 Foxo3 56484 Foxo6 329934 Fstl1 14314 Fstl3 83554 Fto 26383 Furin 18550 Fxn 14297 Fyn 14360 G0s2 14373 Gabbr1 54393 Gal 14419 Gata4 14463 Gcg 14526 Gcgr 14527 Gck 103988 Gdf15 23886 Gh 14599 Ghr 14600 Page 79 of 117 Diabetes

GHRL 58991 Ghsr 208188 Gip 14607 Gipr 381853 Gjd2 14617 Gk 14933 Glp1r 14652 Glp2r 93896 Gm2a 14667 Gnas 14683 Gnat3 242851 Gpam 14732 Gper1 76854 Gpr1 241070 Gpr119 236781 Gpr12 14738 Gpr21 338346 Gpr39 71111 Gprc5b 64297 Grk5 14773 Grm6 108072 Grn 14824 Gsk3b 56637 Gstk1 76263 Gtf2h1 14884 Gucy2c 14917 Gys1 14936 Gys2 232493 Hamp 84506 Diabetes Page 80 of 117

Hcar1 243270 Hcar2 80885 Hcrt 15171 Hcrtr2 387285 Hdac4 208727 Hgf 15234 Hif1a 15251 Hmox1 15368 Hnf4a 15378 Hoxa10 15395 Hsd11b1 15483 Hspa5 14828 Htr2a 15558 Iapp 15874 Ifitm1 68713 Ifng 15978 Igf1 16000 Igf1r 16001 Igf2 16002 Igf2bp2 319765 Igfbp2 16008 Ikbkb 16150 Ikbke 56489 Il10 16153 Il15 16168 Il15ra 16169 Il17a 16171 Il18 16173 Il1a 16175 Page 81 of 117 Diabetes

Il1b 16176 Il1r1 16177 Il1rn 16181 Il21 60505 Il22 50929 Il25 140806 Il33 77125 Il6 16193 Inppl1 16332 Ins1 16333 Ins2 16334 Insr 16337 Irf4 16364 Irf5 27056 Irf7 54123 Irs1 16367 Irs2 384783 Irx3 16373 Itgad 381924 Itgam 16409 Itgax 16411 Itpr2 16439 Jak2 16452 Jak3 16453 Jazf1 231986 Jun 16476 Kcna3 16491 Kdm3a 104263 Kdr 16542 Diabetes Page 82 of 117

Keap1 50868 Khk 16548 Kl 16591 Klrk1 27007 Kras 16653 Lcat 16816 Lcn2 16819 Ldlr 16835 Lep 16846 Lepr 16847 Leprot 230514 Letmd1 68614 Lgals3 16854 Lgi3 213469 Lipc 15450 Lipe 16890 Lnpep 240028 Lox 16948 Lpar1 14745 Lpin1 14245 Lpin2 64898 Lpl 16956 Lrp6 16974 Lrrc8c 100604 Lta 16992 Ltb4r1 16995 Ltf 17002 Ly86 17084 Lyrm1 73919 Page 83 of 117 Diabetes

Maf1 68877 Magel2 27385 Map3k11 26403 Map3k14 53859 Map3k8 26410 Map4k4 26921 Mapk1 26413 Mapk3 26417 Mapk8 26419 Mapk9 26420 Mark4 232944 Mc3r 17201 mc4r 17202 Mchr1 207911 Mdk 17242 Med1 19014 Met 17295 Metrnl 210029 Mex3c 240396 Mfge8 17304 Mfn2 170731 Mgat1 17308 Mgat2 217664 Mif 17319 Mir125a 387235 Mir27a 387220 Mir29c 387224 Mir33 723897 Mir335 723930 Diabetes Page 84 of 117

Mir34a 723848 Mir378a 723889 Mir504 100124476 Mir71 723902 Mkks 59030 Mkl1 223701 Mlxipl 58805 Mlycd 56690 Mme 17380 Mmp10 17384 Mmp14 17387 Mmp19 58223 Mmp9 17395 Mogat2 233549 Moo3 100034896 Moo4 100035774 Mors1 114752 Mors2 114751 Mors3 114753 Mors4 114754 Mrap2 244958 Mst1r 19882 Mstn 17700 Mt1 17748 Mt2 17750 Mtch2 56428 mtNd6 17722 Mtor 56717 17869 Page 85 of 117 Diabetes

Myd88 17874 Mzb1 69816 Nampt 59027 Ncf1 17969 Nck1 17973 Ncoa1 17977 Neil1 72774 Nenf 66208 NEWENTRY 192344 Nfe2l2 18024 Nfkb1 18033 Nhlh2 18072 Nkx11 672284 Nlrp3 216799 Nmu 56183 Nnat 18111 Nnmt 18113 Noct 12457 Nod1 107607 Nod2 257632 NOR1 18124 Nos1 18125 Nos2 18126 Nos3 18127 Nov 18133 Nox1 237038 Nox4 50490 Npc1 18145 Npr1 18160 Diabetes Page 86 of 117

Npr3 18162 Npy 109648 Npy1r 18166 Npy2r 18167 Npy4r 19065 Npy5r 18168 Nr0b2 23957 Nr1d2 353187 Nr1h3 22259 Nr1h4 20186 Nr1i2 18171 Nr2c2 22026 Nr3c2 110784 Nr4a3 18124 Nrip1 268903 Ntrk2 18212 Nuak2 74137 Nucb2 53322 Nupr1 56312 Ogg1 18294 Ogt 108155 Oip5 70645 Oma1 67013 Opa1 74143 Oprk1 18387 Osmr 18414 Otc 18416 Otop1 21906 Oxsr1 108737 Page 87 of 117 Diabetes

Oxtr 18430 P2rx2 231602 Pank1 75735 Paqr3 231474 Park7 57320 Parp1 11545 Pask 269224 Pcsk1 18548 Pcyt2 68671 Pdcd4 18569 Pde3b 18576 Pdx1 18609 Peg3 18616 Pemt 18618 Pfkfb2 18640 Pfkp 56421 Pgf 18654 Phb 18673 Phb2 12034 Pias1 56469 Pid1 98496 Pik3ca 18706 Pik3cb 74769 Pik3cg 30955 Pik3r1 18708 Pin1 23988 Pitrm1 69617 Pla2g1b 18778 Pla2g4c 232889 Diabetes Page 88 of 117

Plagl2 54711 Plcd1 18799 Plin1 103968 Plin2 11520 Plscr3 70310 Pmch 110312 Pnliprp1 18946 Pnoc 18155 Pnpla2 66853 Pnpla3 116939 Pnrc2 52830 Pomc 18976 Pon3 269823 Ppara 19013 Ppard 19015 Pparg 19016 Ppargc1a 19017 Ppargc1b 170826 Prcp 72461 Prkaa1 105787 Prkaa2 108079 Prkab1 19079 Prkaca 18747 Prkar2a 19087 Prkcb 18751 Prkcd 18753 Prkcq 18761 Prkcz 18762 Prkg1 19091 Page 89 of 117 Diabetes

Prl 19109 Prlhr 226278 Prox1 19130 Prrx1 18933 Ptafr 19204 Pten 19211 Ptgds 19215 Ptgs2 19225 Ptpn1 19246 Ptpn11 19247 Ptprt 19281 Ptx3 19288 Pycard 66824 Pyy 217212 Rai1 19377 Ralbp1 19765 Raly 19383 Rapgef3 223864 Rarres2 71660 Rasd1 19416 Rb1 19645 Rbp4 19662 Ren1 19701 Retn 57264 Retnlb 57263 Retnlg 245195 Rfx6 320995 Rgcc 66214 Rgs5 19737 Diabetes Page 90 of 117

Rock1 19877 Rock2 19878 Rora 19883 Rorc 19885 Rpgrip1l 244585 Rps6kb1 72508 Rsc1a1 69994 Saa 111345 Saa1 20208 Saa3 20210 Scarb1 20778 Scd1 20249 Scg3 20255 Scn3b 235281 Sdc 20249 Sdc3 20970 Sel1l 20338 Selplg 20345 Sema3e 20349 Sepp1 20363 Serpina12 68054 Serpine1 18787 Serpinf1 20317 Sertad2 58172 Sesn3 75747 Sfrp1 20377 Sfrp4 20379 Sfrp5 54612 Sftpd 20390 Page 91 of 117 Diabetes

SGIP1 73094 Sgms2 74442 Sh2b1 20399 Shc1 20416 Siae 22619 Sim1 20464 Sirt1 93759 Sirt2 64383 Sirt3 64384 Sirt4 75387 Sirt6 50721 Ski 20481 Skp2 27401 Slc12a1 20495 Slc15a1 56643 Slc16a1 20501 Slc22a12 20521 Slc27a6 225579 Slc2a4 20528 Slc30a8 239436 Slc35d3 76157 Slc36a1 215335 Slc38a2 67760 Slc6a20a 102680 Slc6a4 15567 Sln 66402 Smad3 17127 Snca 20617 Sncaip 67847 Diabetes Page 92 of 117

Sntb2 20650 Socs3 12702 Sorcs1 58178 Sort1 20661 Sost 74499 Sox6 20679 Sp1 20683 Spa17 20686 Spi1 20375 Spon2 100689 Spp1 20750 Spx 319552 Sqle 20775 Srebf1 20787 srl 106393 Srpr 67398 Ssfa2 70599 Sstr4 20608 Stat3 20848 Stat4 20849 Stat5a 20850 Stat5b 20851 Steap4 117167 stk11 20869 Stk39 53416 Sts 20905 Tabw2 100035794 Tas1r3 83771 Tbc1d1 57915 Page 93 of 117 Diabetes

Tbk1 56480 Tbx21 57765 Tcf7l2 21416 Tfap2b 21419 Tgfb1 21803 Thbs1 21825 Thrb 21834 Thrsp 21835 Timp1 21857 Timp3 21859 Tlr2 24088 Tlr4 21898 Tmbim6 110213 Tmem120a 215210 Tmem120b 330189 Tnc 21923 Tnf 21926 Tnfaip3 21929 Tnfrsf14 230979 Tnfrsf1a 21937 Tnfrsf9 21942 Tnfsf10 22035 Tnfsf12 21944 Tnfsf13b 24099 Tnfsf9 21950 Tp53inp2 68728 Tpcn1 252972 Tpcn2 233979 Tph1 21990 Diabetes Page 94 of 117

Traf3 22031 Traf6 22034 Trem2 83433 Trib3 228775 Trim30a 20128 Trim72 434246 Trp53 22059 Trp53inp2 68728 Trpm5 56843 Trpm8 171382 Trpv1 193034 Trpv4 63873 Trpv6 64177 Tsc1 64930 Tsc2 22084 Tsp1 108314 Ttr 22139 Tub 22141 Txnip 56338 Ubb 22187 UBC 22190 Ube2l6 56791 Ucn3 83428 Ucp1 22227 Ucp2 22228 Ucp3 22229 Vav3 57257 Vegfa 22339 Vegfb 22340 Page 95 of 117 Diabetes

Wdtc1 230796 Wisp1 22402 Xbp1 22433 Xdh 22436 Zfp36 22695 Zfp423 94187

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Supplementary Table 9 List for genes involved in energy storage (the gene panel of energy storage) in adipose tissue.

Symbol Gene ID

Abca1 11303 Abcb11 27413 Abcg1 11307 Abhd6 66082 Acot11 329910 Acp5 11433 Acvr1c 269275 Acvr2b 11481 Adam12 11489 Adam17 11491 Adam23 23792 Aebp1 11568 Ager 11596 Agpat4 68262 Agt 11606 Agtr1a 11607 Agtr2 11609 Akt1 11651 Alox5ap 11690 Angptl2 26360 Angptl3 30924 Arntl 11865 Atf3 11910 Atg7 74244 Bcat1 12035 Ccl2 20296 Page 97 of 117 Diabetes

Ccnd3 12445 Ccr2 12772 Ccrn4l 12457 Cd36 12491 Cd38 12494 Cd47 16423 Ceacam2 26367 Cebpa 12606 Cebpb 12608 Cerk 223753 Clic5 224796 Cmklr1 14747 Cnot3 232791 Cnr1 12801 Creb1 12912 Crtc3 70461 Cry1 12952 Cry2 12953 Ctsk 13038 Cx3cr1 13051 Cxcl12 20315 Cxcl14 57266 Cxcl5 20311 Cxcr3 12766 Cyp2e1 13106 Ddit3 13198 Dgat1 13350 Dgat2 67800 Dok1 13448 Diabetes Page 98 of 117

E2f1 13555 Egln1 112405 Egr1 13653 Elovl3 12686 Enpp2 18606 Ephx2 13850 F2rl1 14063 Fabp4 11770 Fabp5 16592 Fads2 56473 Fas 14102 Flcn 216805 Fto 26383 Fyn 14360 G0s2 14373 Ghr 14600 Gpr21 338346 Gprc5b 64297 Grn 14824 Hcar1 243270 Hif1a 15251 Hmox1 15368 Hnf4a 15378 Htr2a 15558 Ifng 15978 Igf2bp2 319765 Ikbkb 16150 Ikbke 56489 Il17a 16171 Page 99 of 117 Diabetes

Il1a 16175 Il1b 16176 Il1rn 16181 Inppl1 16332 Irf5 27056 Irf7 54123 Itgax 16411 Jun 16476 Kcna3 16491 Keap1 50868 Khk 16548 Kl 16591 Lcat 16816 Lgals3 16854 Lgr4 107515 Lipc 15450 Lox 16948 Lpin1 14245 Lrrc8c 100604 Ltb4r1 16995 Ly86 17084 Maf1 68877 Map3k14 53859 Mapk8 26419 Mapk9 26420 Mark3 17169 Mark4 232944 Mchr1 207911 Mfge8 17304 Diabetes Page 100 of 117

Mgat1 17308 Mir1032 723825 Mir335 723930 Mir34a 723848 Mlxipl 58805 Mogat2 233549 Mstn 17700 Mtor 56717 Myd88 17874 Nampt 59027 Nck1 17973 Nfkb1 18033 Nlrp3 216799 Nnmt 18113 Nod1 107607 Npy2r 18167 Nr1d2 353187 Nr1h4 20186 Nr1i2 18171 Nr2c2 22026 Nr3c2 110784 Nupr1 56312 Ogg1 18294 Oip5 70645 Pank1 75735 Paqr3 231474 Pask 269224 Pdcd4 18569 Pemt 18618 Page 101 of 117 Diabetes

Pgf 18654 Pid1 98496 Pik3cg 30955 Pik3r1 18708 Pla2g1b 18778 Pla2g4c 232889 Plcd1 18799 Plin1 103968 Plin2 11520 Pnpla2 66853 Pnrc2 52830 Prcp 72461 Prkab1 19079 Prkar2a 19087 Prkcb 18751 Prkcd 18753 Pten 19211 Ptgs2 19225 Ptpn1 19246 Ptpn11 19247 Ralbp1 19765 Rasd1 19416 Rb1 19645 Rbp4 19662 Ren1 19701 Retn 57264 Rgcc 66214 Rorc 19885 Rptor 74370 Diabetes Page 102 of 117

Scd1 20249 Sel1l 20338 Serpine1 18787 Sertad2 58172 Skp2 27401 Smad3 17127 Socs3 12702 Sort1 20661 Sp1 20683 Srebf1 20787 Ssfa2 70599 Stat3 20848 Stat4 20849 Stk39 53416 Tas1r3 83771 Tbk1 56480 Tbx21 57765 Tfap2b 21419 Tgfb1 21803 Thbs1 21825 Thrsp 21835 Timp1 21857 Timp3 21859 Tlr2 24088 Tlr4 21898 Tnc 21923 Tnf 21926 Tnfrsf14 230979 Tnfrsf1a 21937 Page 103 of 117 Diabetes

Tnfrsf9 21942 Tnfsf12 21944 Tnfsf13b 24099 Tnfsf9 21950 Tph1 21990 Traf3 22031 Traf6 22034 Trem2 83433 Trim72 434246 Trp53 22059 Trpm5 56843 Trpv4 63873 Txnip 56338 Vegfb 22340 Wisp1 22402 Xbp1 22433 Zfp423 94187

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Supplementary Table 10: List of genes involved in energy expenditure (the gene panel of energy expenditure) in adipose tissue.

Symbol GeneID

Abhd5 67469 Acacb 100705 Acadl 11363 Ace2 70008 Adipoq 11450 Adipor1 72674 Adipor2 68465 Adrb1 11554 Adrb2 11555 Adrb3 11556 Akr1b7 11997 Alkbh7 66400 Ankrd26 232339 Anxa1 16952 Apln 30878 Apoa1 11806 Apoc1 11812 Apoe 11816 Aqp7 11832 Ar 11835 Arf6 11845 Arrdc3 105171 Bdnf 12064 Bmp7 12162 Brd2 14312 Ccdc80 67896 Page 105 of 117 Diabetes

Cd40 21939 Ceacam1 26365 Cep19 66994 Cidea 12683 Cideb 12684 Clock 12753 Cntf 12803 Cxcl1 14825 Cxcr4 12767 Dio2 13371 Dlk1 13386 Epo 13856 Esr1 13982 Ffar2 233079 Fgf21 56636 Foxc2 14234 Foxo1 56458 Fstl3 83554 Gcg 14526 Gcgr 14527 Gh 14599 Gip 14607 Gpr12 14738 Gpr39 71111 Igfbp2 16008 Il10 16153 Il18 16173 Il22 50929 Il6 16193 Diabetes Page 106 of 117

Irf4 16364 Irs2 384783 Jak2 16452 Jazf1 231986 Kdm3a 104263 Lcn2 16819 Ldlr 16835 Lep 16846 Lepr 16847 Lipe 16890 Lrp6 16974 Med1 19014 Metrnl 210029 Mir27a 387220 Mir33 723897 Mkl1 223701 Mrap2 244958 Mt2 17750 Nfe2l2 18024 Nmu 56183 Nos3 18127 Npr3 18162 Nr0b2 23957 Osmr 18414 Otop1 21906 Parp1 11545 Pde3b 18576 Ppara 19013 Ppard 19015 Page 107 of 117 Diabetes

Pparg 19016 Ppargc1a 19017 Prrx1 18933 Rgs5 19737 Rock1 19877 Serpina12 68054 Sfrp5 54612 Sh2b1 20399 Sirt1 93759 Slc2a4 20528 Stat5a 20850 Stat5b 20851 Tbc1d1 57915 Thrb 21834 Tmbim6 110213 Tnfaip3 21929 Tnfsf10 22035 Tpcn1 252972 Tpcn2 233979 Trib3 228775 Trpm8 171382 Trpv1 193034 Tsc1 64930 Tsc2 22084 Ube2l6 56791 Ucn3 83428 Ucp1 22227 Ucp2 22228 Ucp3 22229 Diabetes Page 108 of 117

Vav3 57257 Vegfa 22339 Wdtc1 230796 Xdh 22436 Zfp36 22695 Hipk2 15258 Nrip1 268903 Bmp4 12159 Prdm16 70673 Cnr2 12802 Crhr2 12922 Fam132a 67389 Gdf15 23886 Gstk1 76263 Gtf2h1 14884 Hdac4 208727 Il15 16168 Lpl 16956 Mmp19 58223 Ncoa1 17977 Neil1 72774 Nos2 18126 Nox4 50490 Nr1h3 22259 Ntrk2 18212 Oma1 67013 Park7 57320 Pias1 56469 Pon3 269823 Page 109 of 117 Diabetes

Prkaa1 105787 Prkaca 18747 Ptafr 19204 Rapgef3 223864 Rock2 19878 Sesn3 75747 Sfrp1 20377 Sfrp4 20379 Sirt2 64383 Sirt3 64384 Sirt6 50721 stk11 20869 Ppargc1b 170826 Adcy3 104111 Cidec 14311 Mfn2 170731 Opa1 74143 Nenf 66208 Sts 20905 Atxn2 20239 Ffar4 107221 Pik3ca 18706 Plscr3 70310

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190x142mm (300 x 300 DPI)

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