Page 1 of 46 Diabetes

Targeted disruption of the SUCNR1 metabolic receptor leads to dichotomous effects on obesity

Kenneth J. McCreath1, Sandra Espada1, Beatriz G. Gálvez1, Marina Benito2, Antonio de Molina3,

Pilar Sepúlveda4, & Ana M. Cervera1,4*

1Department of Cardiovascular Development and Repair, Fundación Centro Nacional de Investigaciones

Cardiovasculares Carlos III (CNIC). Madrid, Spain; 2Advanced Imaging Unit, Department of

Atherothrombosis, Imaging and Epidemiology, Fundación Centro Nacional de Investigaciones

Cardiovasculares Carlos III (CNIC). Madrid, Spain, and CIBER de Enfermedades Respiratorias

(CIBERES); 3Comparative Medicine Unit, Fundación Centro Nacional de Investigaciones

Cardiovasculares Carlos III (CNIC). Madrid, Spain; 4Instituto de Investigación Sanitaria La Fe,

Regenerative Medicine and Heart Transplantation Unit. Valencia, Spain.

Running title: SUCNR1 effects on obesity

Word count: 7657

Figures: 6 +4 supplemental figures

Table: 1 supplemental

*Corresponding author: Ana Maria Cervera

Instituto de Investigación Sanitaria La Fe, Regenerative Medicine and Heart Transplantation Unit.

Valencia, Spain

Phone: 0034961246600

FAX: 0034961246620

E-mail: [email protected]

1

Diabetes Publish Ahead of Print, published online October 28, 2014 Diabetes Page 2 of 46

Keywords: G- coupled receptor, SUCNR1, lipolysis, insulin, adipose tissue, obesity

Abstract

A number of metabolites have signaling properties by acting through G protein-coupled receptors.

Succinate, a Kreb´s cycle intermediate, increases after dysregulated energy metabolism and can bind to its cognate receptor succinate receptor 1 (Suncr1, or GPR91) to activate downstream signaling pathways. We show that Sucnr1 is highly expressed in the white adipose tissue (WAT) compartment of mice and regulates adipose mass and glucose homeostasis. Sucnr1-/- mice were generated and weight gain was monitored under basal and nutritional stress (high-fat diet, HFD) conditions. On chow diet, Sucnr1-/- mice had increased energy expenditure, were lean with a smaller WAT compartment, and had improved glucose buffering. Lipolysis measurements revealed that Sucnr1-/- mice were released from succinate-induced inhibition of lipolysis, demonstrating a function of Sucnr1 in adipose tissue. Sucnr1 deletion also protected mice from obesity on HFD, but only during the initial period; at later stages, body weight of HFD-fed

Sucnr1-/- mice was almost comparable with wild-type mice, but WAT content was greater. Also, these mice became progressively hyperglycemic and failed to secrete insulin, although pancreas architecture was similar to wild-type mice. These findings suggest that Sucnr1 is a sensor for dietary energy and raise the interesting possibility that protocols to modulate Sucnr1 might have therapeutic utility in the setting of obesity.

2

Page 3 of 46 Diabetes

Introduction

G protein-coupled receptors constitute the major and most diverse group of membrane receptors in

eukaryotes (1). Found in the plasma membrane, these receptors are tasked with the recognition and

transmission of messages from the external environment. An ever-increasing number of GPCRs are now

being identified as receptors for metabolites or energy substrates (2), expanding the repertoire of biological

targets to diseases associated with the metabolic syndrome, including hypertension and type II diabetes (3).

Metabolites such as lactate (4), ketone bodies (5) and α-ketoglutarate (6), known primarily to serve

functions distinct to signaling, have been shown to act as ligands for GPCRs. Representative of this new

class of receptor is Gpr91, a receptor for the Krebs cycle intermediate succinate, now termed Sucnr1 for

succinate receptor (7). The Krebs, or citric acid, cycle occurs at the junction between glycolysis and

oxidative phosphorylation (8) and is a key component of aerobic metabolism by providing reducing

equivalents for the electron transport chain. Interestingly, succinate has been known for many years to

increase in tissues during hypoxia (9-11) and may act as a surrogate marker for reduced oxygenation.

Accordingly, Sucnr1 may be activated in times of hypoxic stress such as ischemic injury in liver (12) or

retina (13), or during cardiomyocyte crisis (14). Moreover, dysregulated metabolism, akin to diabetes or

the metabolic syndrome, also has the potential to increase peripheral blood concentrations of succinate to

levels where activation of the Sucnr1 receptor will occur (15, 16). Indeed, the low levels (ca. 2-80 M) of

succinate found in blood plasma (15-18), in comparison with that required for activation (in the region of

180 M (19)), would suggest that Sucnr1 functions more as a sensor of metabolic (or oxidative) damage

(20) rather than a physiological mediator of signaling.

Mounting evidence points to an important role for Sucnr1 during periods of metabolic dysfunction, such as

diabetes-related hypertension, oxygen-induced retinopathy and the metabolic syndrome (20). Interestingly,

obesity is a key component of many metabolic-related diseases (21) and can lead to diabetes,

3

Diabetes Page 4 of 46

hyperlipidemia and cardiovascular disease (21, 22). The effect of Sucnr1 deficiency on body composition and metabolism has not previously been studied. We reasoned that Sucnr1 could be a potential modulator of metabolism since a recent study indicated that this receptor participates in the breakdown (lipolysis) of stored triglycerol in fat (23). To test this hypothesis, we analysed the expression of Sucnr1 in mouse adipose tissue and observed high expression in the white adipocyte compartment. To gain insight into the

(patho)physiological role of Sucnr1, we created mice deficient for this using a knockout-first approach. We show that deficiency of the Sucnr1 gene has metabolic consequences for weight gain and glucose homeostasis. Sucnr1 KO mice have a modest lean phenotype under standard diet conditions, correlating with a reduction in the size of WAT depots, increased energy expenditure and an improved glucose clearence rate. Challenge with high fat diet (HFD) also resulted in a significant decrease in body weights in Sucnr1 KO mice, but only during initial periods. At later periods, body weights of Sucnr1 KO mice were indistinguishable from wild-type littermates but WAT content was increased. This appeared to coincide with a hyperglycemic profile and a reduction in insulin secretion from the pancreas. Collectively, our results point to a potentially important role for Sucnr1 in metabolic disease related with obesity.

Research design and Methods

Generation of Sucnr1-mutant mice, feeding regimes and indirect calorimetry

To create Suncr1-mutant mice, we obtained two sucnr1-targeted embryonic stem (ES) cell clones from the

European Mouse Mutagenesis Consortium (EUCOMM), designated as “knockout-first”, conditional-ready

ES cells (24). This flexible system allows both for gene-trap reporter constructs and also conditional and null alleles to be generated by exposure to the site-specific recombinases cre and flp

(www.knockoutmouse.org). ES cells were injected into C57BL/6 blastocysts and chimeric males were bred to C57BL/6 females to produce germ line transmission. Heterozygous animals were intercrossed and genotyping of F2 progeny detected homozygous mice at the expected Mendelian ratio. Genotyping was performed after weaning, by polymerase chain reaction (PCR) assay with genomic DNA extracted from

4

Page 5 of 46 Diabetes

tail biopsies using the REDExtract-N-Amp Tissue PCR kit (Sigma-Aldrich, Saint Louis, MO, USA).

Genotyping primers were Primer 1: 5’-ACTATAAGCATCACTTCACCACTTCC-3’, Primer 2: 5’-

CAACGGGTTCTTCTGTTAGTCC-3’ and Primer 3: 5’-AAGAACAAATGGTAGAACAGTCACGG-3’.

A PCR product of around 500 nt was obtained from wild type DNA, whereas mutant DNA produced an

amplification product of around 320 nt in size. These “knockout-first” mice were designated gene-trap

(GT) mice. In order to remove the critical exon of the Sucnr1 gene, together with the neomycin cassette,

GT mice were crossed with Sox2-Cre mice (supplied by Dr. Miguel Torres, CNIC), to produce whole body

knockout mice. Genotyping was performed as before using the primers: Primer 4: 5’-

ACTTCCAGTTCAACATCAGCCGCTACA -3’, Primer 5: 5’-

GTGATTCATCTGTATTATTAGATGAGC-3’ and Primer 6: 5’-

CAGCACAACCATCAGAGAAACAATGGACTC-3’. A PCR product of approximately 650 nt indicated

that recombination had occurred to produce a knockout (KO) , and a product of approximately 300nt

identified a wild-type locus. All experiments were carried out using these KO mice.

Mice were housed at the Centro Nacional de Investigaciones Cardiovasculares (CNIC) animal facility

under pathogen-free conditions. Male mice were used for all studies. Mice were given ad libitum access to

food and water unless otherwise noted in experimental methods. Environmental conditions were controlled

to 12/12-h light/dark cycles. Animal studies were approved by the local ethics committee. All animal

procedures conformed to EU Directive 86/609/EEC and recommendation 2007/526/EC regarding the

protection of animals used for experimental and other scientific purposes, enacted under Spanish law

1201/2005. Male Sucnr1 KO mice and wild-type (WT) mice (5-6 weeks old) obtained from heterozygous

mating were fed for 16 weeks with a standard rodent chow diet (SD), containing 13.4% fat (16% energy;

Diet 5K67, LabDiet, Saint Louis, MO, USA) or a high fat diet (HFD) containing 34.9% fat (60.9% energy;

Diet 58Y1, Test Diet, Saint Louis, MO, USA). Body weight was recorded weekly. Separate cohorts of

animals on SD and HFD were utilized for metabolic cage analysis using a 16-chamber indirect calorimetry

5

Diabetes Page 6 of 46

system (PhenoMaster; TSE Systems, Bad Homburg, Germany). Mice were individually housed in the chambers for 5 days, the first 2 days were used for acclimatization and data was analyzed from the last 3 days. Oxygen consumption rate, carbon dioxide production rate, feeding, and total locomotive activity were measured concurrently for each mouse.

Magnetic resonance imaging and spectroscopy analysis

Imaging was performed in the Advanced Imaging Unit at CNIC. Mice on SD or HFD were pre- anesthetized by inhalation of isoflurane/oxygen (2-4%) and monitored by ECG and breathing rhythm

(Model 1025, S.A. Instruments Inc., NY, USA). Animals were positioned supine in a customized bed with a built-in nose cone supplying inhalatory anesthesia (1-2%) and kept at 35-37ºC by a warm air flow.

Images were acquired with an Agilent/Varian 7 Tesla system equipped with a DD2 console and an active shielded 205/120 gradient insert coil with 130 mT/m maximum strength and a volume coil (Rapid

Biomedical GmbH, Rimpar, Germany) for transmit/receive. For MRI, data were collected with a 2D and

3D spin echo sequence. T1 weighted 2D images (Repetition time 380ms, echo time 13 ms, number of averages 4) were acquired to visualize the fat qualitatively in high resolution. 3D T1 weighted spin echo acquisition was also acquired to calculate the body fat to total body weight ratio using 100 ms repetition time, 8 ms echo time, 1 average. In both sequences, the field of view was 90x45x45 mm3 and the reconstruction matrix was 256x256x256. For MRS, the 13C and 1H surface coil was placed over the epididymal fat. 13C spectra were acquired with a repetition time of 1000 ms, 512 accumulations and a spectral width of 18 kHz. The 1H spectra were acquired with 1000 ms of repetition time, 256 scans and a spectral width of 10 kHz. Images were processed using OsiriX (Pixmeo, Geneva, Switzerland).

Quantification of fat composition from 3D images was estimated applying a semi-automatic image thresholding segmentation plugin included in the software and referenced to the total (body) volumes calculated by the same approach. 1H and 13C spectra were processed with MestReNova (Mestrelab

Research, S.L., Santiago de Compostela, Spain). An exponential line broadening (20 Hz for 13C spectrum

6

Page 7 of 46 Diabetes

and 3 Hz for 1H spectrum) was applied before Fourier transformation. Individual contributions of the

signals from carbonylic, olefinic, methylene, and methyl moieties were quantified by integration after

automatic baseline correction. The same process was applied in 1H-spectrum. The areas under each peak

were used to calculate the fractional contribution of saturated (130ppm), monounsaturated (130 and 128

ppm) and doubly (poly) unsaturated (128 ppm) fatty acids, taking as a reference the area under the

carbonylic peak (25). The areas under the peak in the 1H spectrum, total lipids (1.3ppm) and water peak

(4.7 ppm), were used to calculate the percentage of total lipids with respect to water content (26).

Ex vivo lipolysis assay

Mouse epididymal adipose tissue was dissected, weighed, divided into equal pieces and suspended in 400

l Krebs-Ringer Bicarbonate buffer (Sigma-Aldrich) containing 1% fatty acid-free BSA (Sigma-Aldrich).

The tissue samples were treated with either PBS or 25nM isoproterenol, or pretreated with 100M

succinate (for 10 min) or 100ng/mL pertusis toxin (PTX) for 4 hours, before isoproterenol treatment.

Samples were incubated on a shaker at 37ºC and glycerol release was measured using a Glycerol

Determination kit (Cayman Chemical Company, Ann Arbor, MI, USA).

In vivo lipolysis assay

After an overnight fast, mice were injected i.p. with succinate (1.2mg/kg) or the

agonist (R)-N6-(2-phenylisopropyl)-adenosine (PIA) (0.15 nmol/g). Blood was collected before and 15

minutes after injection. Serum non-esterified fatty acid (NEFA) was measured using the NEFA-HR(2) kit

from Wako Chemicals (Richmond, VA, USA).

Tissue collection and blood analysis

At the end of the study, mice were euthanized following an overnight fast. Blood samples were collected

by cardiac puncture and serum was separated by centrifugation. Total serum cholesterol, triglycerides, free

7

Diabetes Page 8 of 46

fatty acids, hepatic aspartate aminotransferase (AST) and alanine aminotransferase (ALT) were determined using an automated analyzer (Dimension RxL Max Integrated Chemistry System, Siemens, Munich,

Germany) and commercially available kits from Siemens (total cholesterol, triglycerides, ALT and AST) and Wako Chemicals (free fatty acids). Diabetes-related biomarkers in serum were analyzed using the Bio-

Plex Pro Mouse Diabetes standard 8-plex + adiponectin kits (Bio-Rad Laboratories, Inc., Berkeley, CA,

USA). Selected tissues were collected and weighed. Tissues were fixed in neutral buffered formalin solution and processed for histological analysis, or snap frozen in liquid nitrogen and stored at -80°C for

RNA and protein extraction.

Histological analysis

Tissues were fixed in 10% buffered formalin (VWR International, Radnor, PA, USA), embedded in paraffin and sectioned at 5m. For morphometric analysis, sections were stained with hematoxylin & eosin according to standard protocols. Adipocyte size (from WAT) and islet cell area and cell number (from pancreas) were determined with ImageJ software (National Institutes of Health, USA). Sections from six animals per group were used and at least 500 adipocytes per animal were measured from multiple fields.

Islet cell area was quantified from at least four sections per pancreas and expressed as the percentage of total pancreas area. Islet cell density was assessed by counting the number of nuclei in a 1720 m2 area from the same sections. Additional sections were subjected to heat-induced epitope retrieval (HIER) in citrate-buffer, pH 6, followed by blocking of endogenous peroxidase activity with hydrogen peroxide prior to the inmunostaining. Sections were incubated overnight with antibodies specific for Sucnr1 (Novus

Biologicals, Littleton, CO, USA), insulin (Cell Signaling Technology, Inc., Danvers, MA, USA), glucagon

(Abcam plc, Cambridge, UK), Ki67 (Master Diagnostica, Granada, Spain) or caspase-3 (R&D Systems

Inc., Minneapolis, MN, USA). For Sucnr1 immunodetection, a tyramide signal amplification kit

(Molecular Probes, Thermo Fisher Scientific, Waltham, MA, USA) was used. For insulin/glucagon double staining, we used fluorescence-labeled secondary antibodies. Insulin, Ki67, and caspase-3 were detected using an automatic inmunostainer (Dako Autostainer Plus; Dako, Glostrup, Denmark) with an HRP-labeled 8

Page 9 of 46 Diabetes

polymer anti-rabbit as secondary antibody (EnVision-HRP; Dako) and the chromogenic substrate DAB

(Dako), followed by counterstaining with Mayer’s hematoxylin.

Western blot analysis

For examination of phospho-Akt in WAT, skeletal muscle and liver samples, fasted mice were injected i.p.

with saline or insulin (1.5U/kg body mass). Extracts were prepared at 10 min post-injection as described

(27). Briefly, tissues were homogenized in 500l ice-cold lysis buffer (1% Triton X-100, 150mM NaCl,

10mM Tris-HCl pH 7.5, 1mM EDTA, 1% Nonidet P-40 and complete mini protease inhibitor cocktail;

Roche, Mannheim, Germany) with a mechanical homogenizer, and debris was cleared by centrifugation at

10,000 g at 4°C for 10 min. The supernatant was collected and the quantity of protein was measured with

the BCA kit (Thermo Fisher Scientific). Protein extracts (40µg of protein) were examined by protein

immunoblot analysis by probing with antibodies to AKT and phospho-Ser473 AKT (Cell Signaling

Technology Inc.). Immunocomplexes were detected with the enhanced chemiluminescence reagent

(Amersham, GE Healthcare Bio-Sciences AB, Uppsala, Sweden).

Glucose tolerance test and insulin tolerance test

For the intraperitoneal glucose tolerance test (IPGTT), mice were fasted overnight (16-18h). Conscious

mice were then injected i.p. with glucose (1.5g/kg body weight). Blood glucose was monitored in samples

obtained from tail punctures before and after glucose administration using a handheld glucometer

(Ascencia EliteTM, Bayer AG, Leverkusen, Germany). To measure insulin levels in response to glucose,

blood was collected at 0 and 10 min post-injection through the submaxilar vein and the resulting serum was

used to measure insulin by ELISA (Millipore Corporation, Billerica, MA, USA). For the intraperitoneal

insulin tolerance test (IPITT), mice were fasted for 2 hours and injected with insulin (0.75U/kg).

Flow cytometry analysis, stromal vascular fraction isolation and preadipocyte differentiation

9

Diabetes Page 10 of 46

The stromal vascular fraction was isolated from WAT by incubating the tissue for 1 h at 37ºC in Krebs buffer (1g tissue/3ml solution) containing 2mg/ml collagenase A (Roche Diagnostics, Basel, Switzerland) and 20mg/mL fatty acid-free BSA (Sigma-Aldrich). Digested tissue was centrifuged at 250 g and the SVF pellet and adipocyte fractions were collected for RNA extraction. For preadipocyte differentiation, the same procedure was followed using subcutaneous WAT. Once the SVF fraction was collected, SVF cells were differentiated to adipocytes ex vivo using a modification of a published protocol (28). Cells were plated (50,000 cells/cm2) and maintained in culture medium (DMEM/F12, 8% FBS, 2mM L-glutamine,

50U/ml penicillin and 50µg/ml streptomycin) for 5 days and differentiation was induced by incubating with culture medium supplemented with 5g/mL insulin, 1g/ml dexamethasone, 25g/ml IBMX, and 1M roxiglitazone. After 2 days, cells were incubated for an additional 2 days in culture medium containing insulin and roxiglitazone only, and were then maintained in culture medium supplemented with only insulin for the remaining duration of differentiation (a further 4 days). For flow cytometry analysis of adipocytes, the same enzyme dissociation procedure was followed for epididymal WAT digestion. Then, adipocytes were recovered by centrifugation (250g, 10 min, 4oC), collected in 1 ml of ice-cold PBS containing 0.25 l of Draq5 (BioStatus Limited, Leicestershire, UK) to stain the cells, and analyzed on a

LSR Fortessa flow cytometer (Becton Dickinson, San Jose, CA). Data were analyzed with FlowJo 1.6 software.

Triglyceride measurement

Hepatic and WAT triglyceride content was measured using tissue from mice fasted overnight, as described

(29). Briefly, total lipids were extracted from samples (50mg) by using an 8:1 mixture of chloroform and methanol (4 h). The extracts were mixed with 1N sulfuric acid and centrifuged (10 min). Triglyceride content was measured with a kit purchased from bioMérieux (bioMérieux Inc., Marcy l'Etoile, France). Oil

Red O staining and measurement of intracellular triglyceride levels were performed as described (28).

Fixed cells or frozen liver sections (10µm) were stained with Oil Red O (Sigma-Aldrich) for 15-20 minutes at room temperature. For quantification, cell monolayers were washed extensively with water to remove 10

Page 11 of 46 Diabetes

unbound dye and 1ml of isopropyl alcohol was added to the culture dish. After 5 min, the absorbance

(510nm) of the extract was measured by spectrophotometry.

Total pancreatic insulin content

Total pancreatic insulin content was measured as described (30). Pancreata were harvested from fed mice,

Polytron homogenized (30 sec) on ice in 5ml cold 2N acetic acid, boiled for 5min, transferred to ice, and

centrifuged at 15,000 g and 4°C for 15 min. Supernatant extracts were then assayed for protein content and

insulin content (ELISA, Millipore Corporation).

RNA isolation and gene expression analysis

Total RNA extraction, cDNA synthesis and quantification were performed by standard methods. The

expression of mRNA was examined by qRT-PCR using a 7900 Fast Real Time thermocycler and Fast

SYBR Green assays (Applied Biosystems, Thermo Fisher Scientific). Three technical replicates were

performed per sample and relative expression was normalized against mouse Srp14. Primer sequences are

given in Supplemental table 1.

Statistical analysis

Calculations were performed using Biogazelle qBase+ and GraphPad Prism 5.0 software (San Diego, CA,

USA), and reported as mean±S.E.M. MRI and MRS data were reported as mean±S.D. Statistical

comparisons were made using repeated-measures ANOVA with Bonferroni posttests for comparisons

between groups at individual time points and Student´s t test for independent samples, as appropriate.

Significance was established as a value of P<0.05.

Results

Sucnr1 is highly expressed in white adipose tissue

11

Diabetes Page 12 of 46

Gene transcription analysis of C57BL/6 wild type mouse tissues revealed high Sucnr1 expression in kidney and liver, with little or no expression in lung tissue (Fig. 1A). These results are consistent with previous work demonstrating high Sucnr1 expression in kidney medulla (7) and also hepatic stellate cells (12).

Interestingly, significant expression was also detected in white adipose tissue (WAT) from epididymal fat

(Fig. 1A), ratifying the recent grouping of this gene to an adipose cluster in the adult mouse (23). Analysis of fractionated WAT demonstrated Sucnr1 expression in the mature adipocyte, but not the stromal cell fraction which contains preadipocytes (Fig. 1B). In contrast to WAT, Sucnr1 expression was minimal from brown adipose tissue (BAT) deposits (Fig. 1C).

Generation of Sucnr1GT/GT and Sucnr1-/- mice

To investigate the in vivo function of Sucnr1, we generated Sucnr1-mutant mice by using “knockout-first” targeted ES cell clones obtained from EUCOMM. The targeting vector, directed to intron 1 of the Sucnr1 gene (Fig. 2A), contained a splice acceptor (SA) module from the engrailed-2 (En2) gene, followed by an internal ribosome entry site (IR) which directs translation of a fusion reporter protein with β-galactosidase

(LacZ), which in turn is dependent on transcription of the endogenous Sucnr1 promoter. A separate transcription unit contained a promoter-driven neomycin gene for antibiotic selection. These two modules were flanked by FRT sites, permitting flp-mediated recombination. Additionally, exon 2 of the gene, which was included in the targeting vector, was flanked by loxP sites, allowing conditional ablation of the exon following cre-mediated recombination (31). A third loxP site bordered the neomycin cassette (Fig. 2A), ensuring its removal with exon 2. Thus, depending on mating regimes, either whole body knockout mice or conditional knockouts can be produced (24). In this work we describe only results from the gene trap and whole body-knockout mice.

Two targeted ES cells clones were injected into mouse blastocysts and germ line transmission was confirmed after mating. All mice were on a C57BL/6 background. Mouse genotypes were evaluated by

12

Page 13 of 46 Diabetes

PCR using genomic DNA from tail biopsies, with primers designed to detect correctly targeted events (Fig.

2B, primers 1, 2 and 3). Homozygous offspring from heterozygous Sucnr1GT/+ male and female intercrosses

were viable and exhibited normal development. Whole-body knockout (KO) mice, distinct from gene

trapped (GT) mice by the complete removal of exon 2, were produced following a crossing regime with

Sox2-cre mice. Removal of exon 2 and the neomycin module was confirmed by PCR using primers 4, 5

and 6, giving the expected amplification products for WT and KO (Fig. 2C). Because intronic insertions of

gene trap vectors may allow normal mRNA splicing to some degree, we analyzed endogenous Sucnr1

levels in GT mice to determine whether residual transcripts were expressed. Using primers e1 and e2,

which bridge exons 1-2 (Fig. 2A), PCR amplification of cDNA from different tissues of wild-type mice

yielded a single product with the expected size of approximately 190nt (Fig. 2D). Unexpectedly,

amplification of cDNA from Sucnr1GT/GT mice with the same primer pair yielded a larger single product of

300nt, with no detectable wild-type Sucnr1 expression (Fig. 2D, left panel) suggesting that the splice

acceptor (SA) is not skipped. Introducing an IRES-specific reverse PCR primer (p7), together with primer

e1, resulted in the amplification of an intermediate-sized fragment (220nt), consistent with the proper

functioning of the SA module (Fig. 2D, middle panel). PCR across exons 1-2 in Sucnr1KO/KO (Sucnr1 KO)

mice failed to amplify a reaction product, consistent with the loss of exon 2 (Fig. 2D, right panel). To

determine the origin of the unanticipated 300nt product in Sucnr1GT/GT mice, and exclude the possibility of

PCR artifacts, reactions were performed on mRNA from different tissues of mice and the products were

sequenced. Results from sequencing determined precisely in all cases that the fusion transcript generated

by the proper joining of exon 1 to the SA sequence had caused activation of a cryptic splice donor site

located 115-nt downstream in the En2 sequence, which spliced to the SA of Sucnr1-exon2 (Fig. 2E). This

splicing resulted in a frameshift with premature stop codons within exon 2, predicting termination of a

truncated Sucnr1 translation product. Curiously, this cryptic splice element in the En2 gene has been

previously described in the literature (32, 33), and it seems rather puzzling that a large-scale genetic

13

Diabetes Page 14 of 46

knockout platform would utilize the En2-SA unit with a documented alternative splicing phenomenon.

Because of this incongruity, only KO mice were characterized further.

In accord with mRNA expression, strong and homogenous β-galactosidase staining was observed throughout WAT from knockout mice but not wild-type littermates (Fig. 2F, top panels), indicating robust

β-galactosidase activity in this tissue driven by the endogenous Sucnr1 promoter. Subsequently, immunofluorescence analysis of paraffin-embedded WAT sections revealed that Sucnr1 is present in the plasma membrane of wild-type adipocytes but is not detected in equivalent samples of knockout mice (Fig.

2F, bottom panels). Collectively, these results identify the white adipocyte as a significant reservoir of

Sucnr1 expression and suggest that it might have a functional role in adipocyte metabolism.

Sucnr1 deficiency results in release from succinate-induced inhibition of lipolysis.

Hydrolysis of fat stored as triglycerol (TG) in adipose tissue, termed lipolysis, is tightly controlled by hormones and metabolites that are secreted according to nutritional status (34). Enzymatic breakdown of

TG occurs through a series of steps (35) to release one molecule of glycerol and three molecules of fatty acid. Released fatty acids enter the circulation and can be taken up and oxidized by peripheral tissues.

Interestingly, succinate has been shown to inhibit lipolysis in isolated adipose tissue, presumably through engagement with Sucnr1. To investigate whether lipolysis is perturbed in Sucnr1 KO mice, we dissected

WAT from epididymal fat regions and measured lipolytic activity in explant tissue. Glycerol release, as a metric of lipolysis, was similar in wild-type and Sucnr1 KO mice, both under basal and β-adrenergic agonist (isoproterenol)-stimulated conditions (Fig. 3A). In accord with previous findings (23), addition of succinate (100 M) induced an inhibition of isoproterenol-stimulated glycerol release in WAT explants from wild-type mice, and pretreatment of adipocytes with pertussis toxin blocked the antilipolytic effect of succinate (Fig. 3B). As anticipated, inhibition of lipolysis by succinate was absent in equivalent WAT from

Sucnr1 KO mice (Fig. 3C). Moreover, intraperitoneal injection of succinate (1.2g/kg) provoked a

14

Page 15 of 46 Diabetes

significant decrease in serum levels of NEFA in wild-type mice whereas the decrease in Sucnr1 KO mice

was not significant (Fig. 3D). Further, intraperitoneal injection of the adenosine A1 receptor agonist (R)-

N6-(2-phenylisopropyl)-adenosine (PIA) could inhibit lipolysis both in wild-type and Sucnr1 KO mice

(Fig. 3E), demonstrating that the response to general GPCR-mediated antilipolysis was not perturbed in

Sucnr1 KO mice. Taken together, these results establish that succinate exerts its antilipolytic actions

through Sucnr1 coupled to Gi-type G .

Disruption of Sucnr1 results in a moderately-lean phenotype with reduced WAT compartments

Given that expression of Sucnr1 in WAT alluded to an involvement in energy homeostasis, we assessed

weight gain in wild-type and Sucnr1 KO mice on a standard chow diet (SD). Total body weight did not

differ at weaning (13.1±1.1g for male wild-type vs 13.2±0.6g for male knockout, N=8), and both genotypes

displayed similar weight gains; although, a discernible trend for decreased weight gain in Sucnr1 KO mice

was apparent from 10 weeks of diet (Fig. 3F), which was significant when measured at 50 weeks

(41.6±1.5g for wild-type vs. 35.5±1.9g for Sucnr1 KO mice, P<0.05, Fig. 3G). Analysis of body

composition was performed by dissection of organs and fat pads, nuclear magnetic resonance imaging

(NMRI) and magnetic resonance spectroscopy (MRS). After 18-20 weeks on diet, mice were killed and

organ weights were measured. No differences between genotypes were found in the weights of heart,

spleen, liver and BAT at the end of the study (not shown); however, evident differences were found in the

WAT depots. Accordingly, retroperitoneal, subcutaneous and epididymal fat mass was significantly

reduced in Sucnr1 KO mice relative to wild-type littermates (Fig. 3H). Further, compared with total body

weight, cumulative fat content was significantly reduced in Sucnr1 KO animals (Fig. 3I). Visual inspection

of NMRI images of wild-type and Sucnr1 KO animals suggested a greater percentage of abdominal fat

mass in wild-type animals relative to Sucnr1 KO littermates (Fig. 3J), and quantification analysis of axial

slices demonstrated a trend for reduction (Fig. 3J). In the same experimental setting, 13C-NMR spectra of

glycerides were recorded over the entire abdominal region (Supplemental Fig. 1A). Quantification of the

15

Diabetes Page 16 of 46

spectra (25) showed that the fractional contribution of saturated fatty acids to the total pool of glycerides was significantly increased in Sucnr1 KO animals (0.583±0.292 vs. 0.481±0.189, P<0.05 for Sucnr1 KO vs. wild-type, respectively), whereas monounsaturated and polyunsaturated fatty acids were comparable between genotypes. Finally, 1H-MRS were also acquired from the abdominal region to assess lipid content

(26). As depicted in representative spectra of mice, the ratio of water to fat content was altered in Sucnr1

KO mice relative to control littermates (Supplemental Fig. 1B), and area under the curve measurements revealed a significant decrease in fat content in Sucnr1 KO mice (Fig. 3K). Collectively, these results are consistent with the fat weight analysis and strongly suggest that Sucnr1 KO mice have a reduced WAT content.

In agreement with the decreased size of the different anatomical WAT compartments in SD-fed Sucnr1 KO mice, histological analysis of hematoxylin-eosin-stained WAT established a significant decrease in adipocyte size relative to wild-type mice (Fig. 3L). Further, flow cytometry analysis of disaggregated adipocytes from epididymal WAT revealed a significant decrease in adipocyte size, measured as forward scatter (Fig. 3M). These changes were mirrored by a reduction in the concentration of adipose triglycerides

(Fig. 3N). As the decrease in adipose mass in Sucnr1 KO mice can result from a reduction in adipocyte size and/or decreased differentiation, we examined the expression of related to adipocyte differentiation.

Although expression levels of the adipogenic transcription factors, peroxisome proliferator-activated receptor gamma (Pparγ) and CCAAT/enhancer-binding protein alpha (Cebpα), together with the late differentiation marker fatty acid binding protein 4 (Fabp4), tended to be slighlty lower in WAT taken from

Sucnr1 KO mice, this decrease was not significant (Fig. 3O). Moreover, the differentiation ability of preadipocytes extracted from the SVF of adult mice was comparable between both groups, as measured by

Oil Red O staining of neutral lipids (Fig. 3P), and by expression of the adipocyte marker genes Pparγ, protein delta homolog-1 (Pref1), and sterol regulatory element-binding protein-1c (Srebp1c), although a non-significant increase in Pparγ and Srebp1c expression was observed in adipocytes from Sucnr1 KO

16

Page 17 of 46 Diabetes

mice (Fig. 3Q). These results, taken together with the findings of low levels of Suncr1 expression in SVF, a

reduction in adipose tissue mass and adipocyte size and decreased lipid content, collectively suggest that

Sucnr1 deletion does not alter adipogenesis, but rather results in decreased lipid accumulation and smaller

adipocytes.

To further evaluate the metabolic changes caused by Sucnr1 deletion, we measured energy expenditure by

indirect calorimetry. Interestingly, the rate of VO2 consumption in the Sucnr1 KO group was consistently

higher than wild-type counterparts (Fig. 4A). The respiratory exchange ratio (RER; VO2/VCO2) of Sucnr1

KO mice was also significantly higher than wild-type mice during the dark cycle (Fig. 4B,E), indicating

that perhaps less tissue fat is available for oxidation in these mice. Alternatively, the increased RER values

may suggest an increase in whole body utilization of carbohydrates and protein over lipids. Surprisingly,

food intake was increased in Sucnr1 KO mice compared with wild-type (Fig. 4C,F), and energy

expenditure was greater during the dark cycle (Fig. 4D,G), with no change in locomotor activity between

the two genotypes (Fig. 4H). This increase in food intake together with the reduction in fat mass could be

due to evident increases in energy expenditure. Though we were unable to find differences in BAT

expansion between wild-type and Sucnr1 KO mice, dysregulated energy expenditure often results in over-

expression of uncoupling proteins to dissipate energy. However, analysis of uncoupling protein expression

revealed comparable levels of UCP2 and UCP3 in skeletal muscle and liver (Fig. 4I). Interestingly,

although changes did not reach significance, there was a trend for lower UCP1 expression in BAT tissue of

Sucnr1 KO mice, together with eleveated levels of UCP1 and UCP2 expression in WAT tissue (Fig. 4I),

suggesting perhaps compensatory mechanisms. Collectively, these results suggest that deletion of Sucnr1

results in substantial alterations in energy expenditure and disposition.

High fat diet-feeding leads to increased fat deposition in Sucnr1 KO mice and hepatic steatosis

17

Diabetes Page 18 of 46

We next challenged mice with HFD to provoke obesity. HFD-feeding led to increased weight in both genotypes; however, Sucnr1 KO mice gained weight at a slower rate than wild-type littermates, which was significant after only approximately 3 weeks of feeding (25.7±0.3 g vs. 28.6±0.5g, P=0.0006). Variance in body weight widened until week 14 when differences became less pronounced and weight curves were superimposable (Fig. 5A). Predictably, animals on HFD were substantially heavier than standard diet-fed animals at the end of the study (compare Fig. 5A and Fig. 3F), and this correlated with an increase in the weight of WAT and BAT compartments and also liver. Surprisingly, although Sucnr1 KO mice on HFD were generally leaner than wild-type counterparts, the weight of WAT stores at the end of the study was significantly increased (Fig. 5B), whereas adipocyte size was comparable (Supplemental Fig. 2). This finding was in contrast to that observed under standard diet, where Sucnr1 KO mice had significantly less

WAT (Fig. 3H,I). In a second cohort of HFD-fed mice used for NMRI analysis, body weights of Sucnr1

KO mice after 20 weeks on diet were found to be significantly lower than equivalent wild-type mice (Fig.

5C), in keeping with the overall observations. Although no differences were found in the weight of different anatomical WAT compartments between groups in this cohort (Fig. 5D), the proportion of fat as a percentage of total body weight was significantly higher in Sucnr1 KO animals, as determined by measurement of combined fat depots (Fig. 5E). Inspection of NMRI images indicated comparable abdominal fat volume in both groups (Fig. 5F), and quantitative assessment of fat from axial slices revealed no differences (Fig. 5F). A more accurate quantification was carried out using 1H-MRS, to determine lipid content. In this case, area under the curve measurements revealed a significant increase in fat content in Sucnr1 KO mice (Fig. 5G), in keeping with the findings from the first cohort.

Results from indirect calorimetry at 8 weeks on HFD revealed no significant differences in VO2 consumption or RER (Fig. 5H) in Sucnr1 KO mice compared with wild-type control, although ingestion of the HFD reduced RER values in both groups relative to SD. Again, total food consumption was modestly increased in Sucnr1 KO mice, although this did not reach significance (Fig. 5H). Furthermore, locomotor

18

Page 19 of 46 Diabetes

activity was not significantly different between groups (data not shown). These results indicated that the

initial slower rate of weight gain in Sucnr1 KO mice under HFD was not attributable to alterations in

energy expenditure, food intake, or activity.

Changes in adipose mass were reflected in alterations of adipokine levels in serum of animals. Compared

with wild-type littermates, the reduced quantity of adipose tissue in Sucnr1 KO mice under SD was

paralleled by decreased circulating levels of the obesity indicator leptin (Fig. 5I). This finding is in keeping

with the increased feeding of Sucnr1 KO animals on SD (Fig. 4C,F) and the satiety effect of this hormone

(36). In contrast, HFD-feeding induced a >10-fold increase in serum leptin, which was not significantly

different between Sucnr1 KO and wild-type mice (Fig. 5I). In addition, a small but significant decrease in

serum levels of the insulin-sensitizing hormone adiponectin was observed for Sucnr1 KO mice under both

dietary regimes (Fig. 5I). However, serum levels of the adipokines resistin and plasminogen activator

inhibitor-1 (PAI-1), although increased in HFD, were not statistically different between genotypes (Fig.

5I). Obesity in humans and animal models is often associated with increased circulating lipids, and ectopic

lipid accumulation in nonadipose tissues including liver (37). Consistent with this phenotype, both fasted

serum levels of NEFAs and cholesterol were elevated in wild-type mice and Sucnr1 KO mice fed HFD for

18 weeks, whereas TG concentrations remained in the normal range (Fig. 5J). In accord with the measured

lipolytic rates in explants (Fig. 3A), no differences in plasma parameters were observed between genotypes.

Although no morphologic alterations were found in liver between groups fed a standard diet, hepatic

steatosis was induced in both genotypes under HFD, evidenced by hematoxylin-eosin-staining of abundant

vacuolar vesicles in liver sections, which were confirmed as lipid droplets by Oil Red O staining (Fig. 5K).

Additionally, hepatic triglyceride content in both genotypes was significantly increased under HFD,

consistent with the fatty changes to liver (Fig. 5L); however, no significant differences in liver TG content

were found between Sucnr1 KO and wild-type mice under either diet. Further, HFD levels of AST and

ALT were found to be significantly increased in Sucnr1 KO mice compared with wild-type mice,

19

Diabetes Page 20 of 46

suggesting increased hepatocyte damage (Fig. 5M); the origin of these differences is not known. Consistent with the increased lipid load in liver, expression analysis revealed changes in relevant genes (Supplemental

Fig. 3), including the lipogeneic transcription factor sterol regulatory binding protein 1c (Srebp-1c), and its target stearyol CoA desaturase-1 (Scd1), which were induced under HFD in both genotypes; however, other genes involved in triglyceride synthesis, fatty acid synthase (Fas) and stearyol CoA desaturase (Acc), were unaltered in HFD-fed mice. Similarly, expression of the fatty acid transporter CD36 was upregulated under HFD in both genotypes, although expression was significantly reduced in Sucnr1 KO mice compared with wild-type littermates on standard diet. Additionally, a modest but significant increase in the expression of a second FA transporter, fatty acid binding protein 4 (Fabp4), was found in Sucnr1 KO but not wild-type mice under HFD diet, whereas expression of the fatty acid transport protein 2 (Fatp2) was downregulated in Sucnr1 KO mice under HFD. In contrast to these changes, no differences were found between genotypes for the expression of genes related to FA oxidation, although carnitine palmitoyltransferase 1a (Cpt1a) and Cpt1b were downregulated under HFD in both genotypes.

Collectively, these data indicate that although the absence of Sucnr1 results in subtle changes to liver function metrics compared with wild-type mice, HFD appeared to cause comparable steatosis.

Suncnr1 knockout mice are hyperglycemic under HFD with reduced insulin secretion

Although the metabolic phenotype of Sucnr1 KO mice appeared modest, the evident differences in adiposity and weight gain prompted us to evaluate glucose and insulin homeostasis. These parameters were measured in mice after 16 weeks on diet. Compared with standard diet, HFD led to an increase in both fasted and fed levels of serum glucose in Sucnr1 KO mice and wild-type littermates (Fig. 6A). Serum glucose was comparable between genotypes in standard diet; however, despite their similar final body weights in HFD, Sucnr1 KO mice had significantly higher levels of fasting blood glucose, whereas fed glucose was unaltered (Fig. 6A right panel). Nevertheless, Sucnr1 KO mice showed similar levels of fasting insulin as those from wild-type mice in HFD, which were elevated compared with those in SD (Fig.

20

Page 21 of 46 Diabetes

6B). To directly assess whether glucose homeostasis was dysregulated in Sucnr1 KO mice, we performed

glucose tolerance tests (GTT) and insulin tolerance tests (ITT). Interestingly, in the SD group,

intraperitoneal challenge with 1.5g/kg glucose resulted in faster clearance in Sucnr1 KO mice, as glucose

concentrations remained significantly lower compared with wild-type mice (Fig. 6C left panel). This is in

keeping with the general leaness of KO animals and higher RER values (Fig. 4B,E), and suggested

improved insulin sensitivity that promotes carbohydrate utilization. As anticipated, glucose clearance

deteriorated in the HFD group (Fig. 6D left panel). However, in marked contrast to the findings under

standard diet, Sucnr1 KO mice fed a HFD developed a clear impairment in glucose elimination compared

with wild-type mice, with manifest hyperglycemia 120 mins after glucose injection. Notably, this

decreased ability to lower blood glucose was not apparent in Sucnr1 KO mice at 11 weeks on HFD

(Supplemental Fig. 4), suggesting a progressive glucose intolerance concurring with the increased WAT

weight. Abnormal glucose homeostasis could result from either a defect in insulin sensitivity of the

peripheral tissues, or a defect in insulin secretion. ITTs showed that although both genotypes exhibited

decreased insulin sensitivity under HFD, Sucnr1 KO mice exhibited comparable insulin sensitivity to wild-

type litermates, as demonstrated by a quick decline in plasma glucose after an acute insulin injection (Fig.

6C and D, right panels). Furthermore, insulin was shown to induce phosphorylation of the major insulin-

signaling protein, Akt (on Ser 473) in liver, WAT and skeletal muscle, to similar intensities in Sucnr1 KO

and wild-type mice on HFD (Fig. 6E). Thus, these results pointed to a defect in insulin secretion as the

origin of the hyperglycemia in HFD-fed knockout mice. To consider this, we repeated the glucose

tolerance test and measured circulating insulin levels at baseline and 10 min after a glucose load (1.5g/kg).

Whereas wild-type mice showed a characteristic increase in insulin levels at t=10 min, Sucnr1 KO mice

failed to secrete insulin, although GLP-1 levels were similar in both genotypes (Fig. 6F). Collectively,

these results imply that while Sucnr1 KO mice have significantly enhanced glucose tolerance under

standard diet, the HFD causes a sufficient deficiency in insulin secretion to cause glucose intolerance.

21

Diabetes Page 22 of 46

Guided by these findings, we examined islet anatomy and endocrine cell size in pancreatic tissue sections of HFD-fed mice (Fig. 6G). As expected, morphometric analysis revealed that high fat feeding increased islet cell size, and this increase was comparable in both genotypes (Fig. 6H). Moreover, β cell number was also similarly increased in Sucnr1 KO and wild-type mice under HFD, compared with SD (Fig. 6I). Also, total (acid-extracted) pancreatic insulin concentration was similar between genotypes on HFD (Fig. 6J).

Immunohistochemistry staining with an antibody to insulin showed that the morphologic features of wild- type and knockout islets were comparable (Fig. 6K, left panels), and detailed analysis of the islets revealed a normal cell architecture shared between genotypes, with positive immunostaining for glucagon (α cells) in the periphery, while the area of anti-insulin staining was observed mostly in the central region (Fig. 6K, right panels). Examination of β cell proliferation with an antibody to Ki67 indicated a similar and low

(<1%) frequency of Ki67-positive cells in both wild-type and knockout mice, and very few apoptotic

(caspase-3-positive) β cells were detected in either genotype (Fig. 6L). Thus, our results are consistent with an insulin secretory defect in Sucnr1 KO mice.

Discussion

Impaired cellular metabolism is a defining hallmark of many disease states and can affect homeostatic signaling processes. As the Krebs cycle is the central metabolic pathway in aerobic organisms, it is particularly significant that succinate, an intermediate metabolite of this pathway, has an alternative occupation as a signaling molecule for Sucnr1 coupling.

Information regarding the function of Sucnr1 is limited. Previous studies have shown that Sucnr1 is distributed in organs with high metabolic demand, including the kidney and liver (20). Signaling of Sucnr1 appears to be an early response to hyperglycemic conditions in the kidney and leads to activation of the intrarenal renin-angiotensin system, resulting in hypertension and potential tissue injury (38). Here we show that Sucnr1 is expressed in high levels in the adipocyte, and that loss of Sucnr1 leads to dichotomous

22

Page 23 of 46 Diabetes

effects on body weight and metabolism. Although not conspicuously different during early growth, after

16-20 weeks on standard diet (at 21-25 weeks of age) Sucnr1 KO mice exhibited a modestly-lean

phenotype compared with wild-type mice, with significantly reduced levels of plasma leptin and reduced

white adipose tissue mass containing smaller adipocytes and decreased triglyceride content. This decrease

in adiposity was not associated with ectopic triglyceride storage in liver or plasma (Fig. 5) or skeletal

muscle (not shown), but correlated with a significant increase in glucose tolerance and an elevated

metabolic activity, including increased energy expenditure, which might partly explain why Sucnr1 KO

mice were lean despite hyperphagia. However, this phenotype was seen in the setting of normal levels of

BAT content and tissue expression of uncoupling proteins, which are often elevated in models of increased

energy expenditure (39). Decreased weight gain in Sucnr1 KO mice was also observed in the HFD study,

particularly during the initial 10 weeks. This finding supports our observations on SD and strongly suggests

that leaness is a primary outcome of Sucnr1 deletion. Since adipogenesis was not affected by deletion of

Sucnr1, and an antilipolytic effect of succinate had been previously described, this metabolically-

favourable phenotype might be explained in part by the release from succinate-inhibited lipolysis. Notably,

experiments both in vitro and in vivo verified that succinate inhibited the breakdown of triglycerides,

although basal and isoproterenol-induced lipolysis was unchanged in Sucnr1 KO animals. This phenotype,

in part, is consistent with other mouse models of “unrestrained” lipolysis, and show that release from Gi-

coupled inhibition of fat mobilization results in leaness (40-42) and increased energy expenditure (42).

After prolonged high fat feeding, Sucnr1 KO mice displayed a rather more complex phenotype,

presumably a result of nutritional stress induced by the HFD. Under these conditions, end-of-study body

weights of Sucnr1 KO mice were, in the main, comparable with wild-type controls but WAT was

significantly heavier. Furthermore, after 16 weeks on HFD, Sucnr1 KO mice had significantly greater

levels of blood glucose and failed to secrete insulin in GTTs; however, pancreas architecture was not

different to wild-type mice. Ostensibly, this hyperglycemic state may have resulted from the failure to

buffer serum glucose, although this inference is tempered by the result that insulin sensitivity was

23

Diabetes Page 24 of 46

unchanged in Sucnr1 KO mice. Still, compensatory mechanisms such as neuronal or endocrine modulation may account for this discrepancy between insulin secretion and resistance.

Although our original hypothesis presupposed that a lean phenotype would result from augmented WAT lipolysis, our findings of increased metabolic activity, under basal conditions, in Sucnr1 KO mice points to a more systemic effect of Sucnr1 deletion. Whether these phenotypes are triggered directly by differences in adipose mass in Sucnr1 KO mice, or through a more circuitous route, awaits further study. Nevertheless, adiponectin levels, which are typically inversely correlated with obesity were decreased in Sucnr1 KO mice and might reflect specific changes in adipocytokine signaling (43), leading us to hazard that a hyperglycemic phenotype might occur when fat content reaches a critical mass.

Many mechanisms can account for leaness, but they all generally result from deregulation of energy balance, as noted here. We can speculate on several potential mechanisms that may promote this phenotype in Sucnr1 KO mice (44): these could include hypothalamic signal transduction (45), reduced intestinal absorption of foods leading to decreased energy availability (46), enhanced energy metabolism in peripheral tissues, or a defect in adipose tissue storage capability. It remains to be determined whether one or more of these mechanisms are operating in our model.

Finally, it should be noted that an underlying concept in Sucnr1 signaling is hypoxia-induced modulation of receptor engagement through local increases in succinate levels. This is particulary manifest in ischemic retinopathy, where microvascular degeneration results in an abnormal hypoxia-driven succinate-induced neovascularization through Sucnr1-dependent upregulation of proangiogenic factors (13,47). Interestingly, hyperglycemia can also result in regional increases in succinate (16,47), most likely through over- activation of the Kreb´s cycle (48). Indeed, adipose tissue succinate has been shown to increase (2-fold) in mice under HFD (49), and hypoxia has been detected during expansion of adipose tissue in obesity (50,51),

24

Page 25 of 46 Diabetes

doubtless occuring when vascularization is insufficient to maintain oxygen levels. Thus increases in

succinate, hypoxia and /or hyperglycemia might trigger Sucnr1-induced signaling at the level of the

adipocyte. Clearly, because Sucnr1 is expressed in organs with high metabolic demands, tissue-selective

knockouts will be required to identify the specific cell type(s) in which Sucnr1 plays a direct role;

nevertheless, our results indicate that activation of Sucnr1 may have therapeutic implications in the

treatment of obesity-related disorders.

Acknowledgements

Author contributions: A.M.C. and K.J.M. conceived the project, performed experiments, interpreted data

and wrote the paper. S.E., B.G.G., M.B., A. dM. and P.S. performed experiments and interpreted data.

A.M.C. is the guarantor of this manuscript.

We thank Guadalupe Sabio and Tamas Rözer for helpful discussions. We also thank Roisin Brid Doohan,

Ana Belén Ricote and Jesús María Ruiz-Cabello for technical assistance, all from CNIC. This work was

supported in part by a research grant from the Ministerio de Ciencia e Innovación (MICINN), SAF2009-

07965 (to K.J.M.) and SAF2010-15239 to B.G.G. The CNIC is supported by the Ministerio de Economía y

Competitividad and the Pro-CNIC Foundation.

Additional information

Supplementary information accompanies this paper (Supplementary Table and Supplementary Figures 1-

4).

Competing financial interests

The authors declare no competing financial interests.

25

Diabetes Page 26 of 46

References

1. Flower DR, Attwood TK: Integrative bioinformatics for functional genome annotation: trawling for G protein- coupled receptors. Seminars in Cell & Developmental Biology 2004;15:693-701

2. Smith NJ: Low affinity GPCRs for metabolic intermediates: challenges for pharmacologists. Frontiers in Endocrinology 2012;3:1

3. Blad CC, Tang C, Offermanns S: G protein-coupled receptors for energy metabolites as new therapeutic targets. Nature Reviews Drug Discovery 2012;11:603-619

4. Cai TQ, Ren N, Jin L, Cheng K, Kash S, Chen R, Wright SD, Taggart AK, Waters MG: Role of GPR81 in lactate- mediated reduction of adipose lipolysis. Biochemical and Biophysical Research Communications 2008;377:987-991

5. Taggart AK, Kero J, Gan X, Cai TQ, Cheng K, Ippolito M, Ren N, Kaplan R, Wu K, Wu TJ, Jin L, Liaw C, Chen R, Richman J, Connolly D, Offermanns S, Wright SD, Waters MG: (D)-beta-Hydroxybutyrate inhibits adipocyte lipolysis via the nicotinic acid receptor PUMA-G. The Journal of Biological Chemistry 2005;280:26649-26652

6. Tokonami N, Morla L, Centeno G, Mordasini D, Ramakrishnan SK, Nikolaeva S, Wagner CA, Bonny O, Houillier P, Doucet A, Firsov D: alpha-Ketoglutarate regulates acid-base balance through an intrarenal paracrine mechanism. The Journal of Clinical Investigation 2013;123:3166-3171

7. He W, Miao FJ, Lin DC, Schwandner RT, Wang Z, Gao J, Chen JL, Tian H, Ling L: Citric acid cycle intermediates as ligands for orphan G-protein-coupled receptors. Nature 2004;429:188-193

8. Krebs HA: Rate control of the tricarboxylic acid cycle. Advances in Enzyme Regulation 1970;8:335-353

9. Ashrafian H, Czibik G, Bellahcene M, Aksentijevic D, Smith AC, Mitchell SJ, Dodd MS, Kirwan J, Byrne JJ, Ludwig C, Isackson H, Yavari A, Stottrup NB, Contractor H, Cahill TJ, Sahgal N, Ball DR, Birkler RI, Hargreaves I, Tennant DA, Land J, Lygate CA, Johannsen M, Kharbanda RK, Neubauer S, Redwood C, de Cabo R, Ahmet I, Talan M, Gunther UL, Robinson AJ, Viant MR, Pollard PJ, Tyler DJ, Watkins H: Fumarate is cardioprotective via activation of the Nrf2 antioxidant pathway. Cell Metabolism 2012;15:361-371

10. Hohl C, Oestreich R, Rosen P, Wiesner R, Grieshaber M: Evidence for succinate production by reduction of fumarate during hypoxia in isolated adult rat heart cells. Archives of Biochemistry and Biophysics 1987;259:527-535

11. Iles RA, Barnett D, Strunin L, Strunin JM, Simpson BR, Cohen RD: The effect of hypoxia on succinate metabolism in man and the isolated perfused dog liver. Clinical Science 1972;42:35-45

12. Correa PR, Kruglov EA, Thompson M, Leite MF, Dranoff JA, Nathanson MH: Succinate is a paracrine signal for liver damage. Journal of Hepatology 2007;47:262-269

13. Sapieha P, Sirinyan M, Hamel D, Zaniolo K, Joyal JS, Cho JH, Honore JC, Kermorvant-Duchemin E, Varma DR, Tremblay S, Leduc M, Rihakova L, Hardy P, Klein WH, Mu X, Mamer O, Lachapelle P, Di Polo A, Beausejour C, Andelfinger G, Mitchell G, Sennlaub F, Chemtob S: The succinate receptor GPR91 in neurons has a major role in retinal angiogenesis. Nature Medicine 2008;14:1067-1076

14. Aguiar CJ, Andrade VL, Gomes ER, Alves MN, Ladeira MS, Pinheiro AC, Gomes DA, Almeida AP, Goes AM, Resende RR, Guatimosim S, Leite MF: Succinate modulates Ca(2+) transient and cardiomyocyte viability through PKA-dependent pathway. Cell Calcium 2010;47:37-46

15. Sadagopan N, Li W, Roberds SL, Major T, Preston GM, Yu Y, Tones MA: Circulating succinate is elevated in rodent models of hypertension and metabolic disease. American Journal of Hypertension 2007;20:1209-1215

26

Page 27 of 46 Diabetes

16. Toma I, Kang JJ, Sipos A, Vargas S, Bansal E, Hanner F, Meer E, Peti-Peterdi J: Succinate receptor GPR91 provides a direct link between high glucose levels and renin release in murine and rabbit kidney. The Journal of Clinical Investigation 2008;118:2526-2534

17. Krebs HA: Chemical composition of blood plasma and serum. Annual Review of Biochemistry 1950;19:409-430

18. Nordmann J, Nordmann R: Organic acids in blood and urine. Advances in Clinical Chemistry 1961;4:53-120

19. Smith NJ: Low affinity GPCRs for metabolic intermediates: challenges for pharmacologists. Frontiers in Endocrinology 2012;3:1

20. Ariza AC, Deen PM, Robben JH: The succinate receptor as a novel therapeutic target for oxidative and metabolic stress-related conditions. Frontiers in Endocrinology 2012;3:22

21. Kaplan NM: The deadly quartet. Upper-body obesity, glucose intolerance, hypertriglyceridemia, and hypertension. Archives of Internal Medicine 1989;149:1514-1520

22. Wilson PW, D'Agostino RB, Sullivan L, Parise H, Kannel WB: Overweight and obesity as determinants of cardiovascular risk: the Framingham experience. Archives of Internal Medicine 2002;162:1867-1872

23. Regard JB, Sato IT, Coughlin SR: Anatomical profiling of G protein-coupled receptor expression. Cell 2008;135:561-571

24. Skarnes WC, Rosen B, West AP, Koutsourakis M, Bushell W, Iyer V, Mujica AO, Thomas M, Harrow J, Cox T, Jackson D, Severin J, Biggs P, Fu J, Nefedov M, de Jong PJ, Stewart AF, Bradley A: A conditional knockout resource for the genome-wide study of mouse gene function. Nature 2011;474:337-342

25. Künnecke B, Verry P, Bénardeau A, von Kienlin M: Quantitative body composition analysis in awake mice and rats by magnetic resonance relaxometry. Obesity Research 2004;12:1604-1615

26. Corbin IR, Furth EE, Pickup S, Siegelman ES, Delikatny EJ: In vivo assessment of hepatic triglycerides in murine non-alcoholic fatty liver disease using magnetic resonance spectroscopy. Biochimica et Biophysica Acta 2009;1791:757-763

27. Petersen PS, Jin C, Madsen AN, Rasmussen M, Kuhre R, Egerod KL, Nielsen LB, Schwartz TW, Holst B: Deficiency of the GPR39 receptor is associated with obesity and altered adipocyte metabolism. FASEB Journal : official publication of the Federation of American Societies for Experimental Biology 2011;25:3803-3814

28. Zhang HH, Huang J, Duvel K, Boback B, Wu S, Squillace RM, Wu CL, Manning BD: Insulin stimulates adipogenesis through the Akt-TSC2-mTORC1 pathway. PloS One 2009;4:e6189

29. Sabio G, Kennedy NJ, Cavanagh-Kyros J, Jung DY, Ko HJ, Ong H, Barrett T, Kim JK, Davis RJ: Role of muscle c-Jun NH2-terminal kinase 1 in obesity-induced insulin resistance. Molecular and Cellular Biology 2010;30:106-115

30. Hinke SA, Navedo MF, Ulman A, Whiting JL, Nygren PJ, Tian G, Jimenez-Caliani AJ, Langeberg LK, Cirulli V, Tengholm A, Dell'Acqua ML, Santana LF, Scott JD: Anchored phosphatases modulate glucose homeostasis. The EMBO Journal 2012;31:3991-4004

31. Testa G, Schaft J, van der Hoeven F, Glaser S, Anastassiadis K, Zhang Y, Hermann T, Stremmel W, Stewart AF: A reliable lacZ expression reporter cassette for multipurpose, knockout-first alleles. Genesis 2004;38:151-158

32. Adham IM, Khulan J, Held T, Schmidt B, Meyer BI, Meinhardt A, Engel W: Fas-associated factor (FAF1) is required for the early cleavage-stages of mouse embryo. Molecular Human Reproduction 2008;14:207-213

33. Galy B, Ferring D, Benesova M, Benes V, Hentze MW: Targeted mutagenesis of the murine IRP1 and IRP2 genes reveals context-dependent RNA processing differences in vivo. RNA 2004;10:1019-1025

27

Diabetes Page 28 of 46

34. Zechner R, Zimmermann R, Eichmann TO, Kohlwein SD, Haemmerle G, Lass A, Madeo F: FAT SIGNALS--lipases and lipolysis in lipid metabolism and signaling. Cell Metabolism 2012;15:279-291

35. Schweiger M, Schreiber R, Haemmerle G, Lass A, Fledelius C, Jacobsen P, Tornqvist H, Zechner R, Zimmermann R: Adipose triglyceride lipase and hormone-sensitive lipase are the major enzymes in adipose tissue triacylglycerol catabolism. The Journal of Biological Chemistry 2006;281:40236-40241

36. Frederich RC, Hamann A, Anderson S, Lollmann B, Lowell BB, Flier JS: Leptin levels reflect body lipid content in mice: evidence for diet-induced resistance to leptin action. Nature Medicine 1995;1:1311-1314

37. Maruhama Y, Ohneda A, Tadaki H, Ohtsuki M, Yanbe A: Hepatic steatosis and the elevated plasma insulin level in patients with endogenous hypertriglyceridemia. Metabolism: Clinical and Experimental 1975;24:653-664

38. Peti-Peterdi J: High glucose and renin release: the role of succinate and GPR91. Kidney International 2010;78:1214-1217

39. Silva JE: THermogenic mechanisms and their hormonal regulation. Physiological Review 2006;86:435-4464

40. Ahmed K, Tunaru S, Tang C, Muller M, Gille A, Sassmann A, Hanson J, Offermanns S: An autocrine lactate loop mediates insulin-dependent inhibition of lipolysis through GPR81. Cell Metabolism 2010;11:311-319

41. Bjursell M, Admyre T, Goransson M, Marley AE, Smith DM, Oscarsson J, Bohlooly YM: Improved glucose control and reduced body fat mass in 2-deficient mice fed a high-fat diet. American Journal of Physiology Endocrinology and Metabolism 2011;300:E211-220

42. Jaworski K, Ahmadian M, Duncan RE, Sarkadi-Nagy E, Varady KA, Hellerstein MK, Lee HY, Samuel VT, Shulman GI, Kim KH, de Val S, Kang C, Sul HS: AdPLA ablation increases lipolysis and prevents obesity induced by high-fat feeding or leptin deficiency. Nature Medicine 2009;15:159-168

43. Patane G, Caporarello N, Marchetti P, Parrino C, Sudano D, Marselli L, Vigneri R, Frittitta L: Adiponectin increases glucose-induced insulin secretion through the activation of lipid oxidation. Acta Diabetologica 2013;50:851-857

44. Xia Z, Stanhope KL, Digitale E, Simion OM, Chen L, Havel P, Cianflone K: Acylation-stimulating protein (ASP)/complement C3adesArg deficiency results in increased energy expenditure in mice. Journal of Biological Chemistry 2004;279:4051-4057

45. Nogueiras R, López M, Diéguez C: Regulation of lipid metabolism by energy availability: a role for the central nervous system. Obesity Reviews 2010;11:185-201

46. Khalifeh-Soltani A, McKleroy W, Sakuma S, Cheung YY, Tharp K, Qiu Y, Turner SM, Chawla A, Stahl A, Atabai K: Mfge8 promotes obesity by mediating the uptake of dietary fats and serum fatty acids. Nature Medicine 2014; Acylation-stimulating protein (ASP)/complement C3adesArg deficiency results in increased energy expenditure in mice:175-183

47. Hu J, Wu Q, Li T, Chen Y, Wang S: Inhibition of high glucose-induced VEGF release in retinal ganglion cells by RNA interference targeting G protein-coupled receptor 91. Experimental Eye Research 2013;109:31-39

48. Brownlee M: The pathobiology of diabetic complications: a unifying mechanism. Diabetes 2005;54:1615-1625

49. Cummins TD, Holden CR, Sansbury BE, Gibb AA, Shah J, Zafar N, Tang Y, Hellmann J, Rai SN, Spite M, Bhatnagar A, Hill BG: Metabolic remodeling of white adipose tissue in obesity. American Journal of Physiology Endocrinology and Metabolism 2014;307:E262-277

28

Page 29 of 46 Diabetes

50. Elias I, Franckhauser S, Ferre T, Vila L, Tafuro S, Munoz S, Roca C, Ramos D, Pujol A, Riu E, Ruberte J, Bosch F: Adipose tissue overexpression of vascular endothelial growth factor protects against diet-induced obesity and insulin resistance. Diabetes 2012;61:1801-1813

51. Regazzetti C, Peraldi P, Gremeaux T, Najem-Lendom R, Ben-Sahra I, Cormont M, Bost F, Le Marchand-Brustel Y, Tanti JF, Giorgetti-Peraldi S: Hypoxia decreases insulin signaling pathways in adipocytes. Diabetes 2009;58:95-103

29

Diabetes Page 30 of 46

FIGURE LEGENDS

Figure 1. Sucnr1 tissue distribution. A: Relative expression of Sucnr1 in mouse tissues (Lu, lung; H, heart; Li, liver; K, kidney; WAT, white adipose tissue), determined by qRT-PCR. Expression levels

(Log10) were relative to that in lung tissue arbitrarily chosen as 1 (N=3 mice). B: Relative expression of

Sucnr1 in the stromal vascular fraction (SVF) and adipocytes (ADIP) isolated from epididymal adipose tissue, examined by qRT-PCR. Adiponectin (ADP) and Macrophage scavenger receptor 1 (Msr1) served as positive controls for adipocyte and stromal fractions respectively (N=4 mice). C: Relative expression of

Sucnr1 in WAT and brown adipose tissue (BAT) compartments, examined by qRT-PCR (N=3 mice). Data represent mean ± s.e.m.

Figure 2. Generation of Sucnr1-deficient mice. A: Diagram of the EUCOMM targeting vector including the loxP-flanked exon, and Sucnr1 wild-type locus. Primers for genotyping correct targeting events are shown by large arrows (1-7); exon-spanning primers are shown by small arrows. Black boxes represent exons. B,C: PCR analysis of gene trap (GT), knockout (KO) and wild-type (WT) alleles. D: Amplification of exons from mRNA produced from liver, kidney and WAT of WT, GT and KO mice. Larger product amplifed with primers e1+e2 was extracted for sequencing analysis. E: Schematic representation of alternative splicing around the knockout-first cassette. Correct splicing is denoted by a solid line; the alternative transcript is denoted by a broken line (not to scale). F: Representative β-galactosidase staining of intact adipose tissue from WT and KO mice (200X magnification) demonstrating high LacZ expression in KO mice which was absent in WT mice. WAT was counterstained with nuclear fast Red; immunohistochemical staining of WAT (200X magnification) with an antibody to SUCNR1 confirms its expression in WT but not KO tissue.

Figure 3. Lipolysis, body weight measurement, fat distribution and adipocyte content of Suncr1- deficient mice A: Measurement of lipolysis in WAT explants from Sucnr1-deficent mice (KO) and wild- type littermates (WT). Lipolysis was determined by measuring glycerol released from adipocytes in the

30

Page 31 of 46 Diabetes

absence (-) or presence (+) of 25 nM isoproterenol for 4 h (N=4 mice per group). Results are expressed as

mg glycerol per litre released, per mg tissue. B: WAT explants of wild-type mice were pretreated or not for

4 h with pertussis toxin (PTX, 100 ngml-1) prior to the addition of succinate (100 M), followed 10 min

later by isoproterenol (25 nM). Lipolysis was determined by glycerol release as in A. A representative

experiment from 4 is shown. C: Lipolysis was measured in WAT explants from Sucnr-1-deficient and

wild-type littermates. Explants were incubated with isoproterenol (25 nM) plus/minus succinate (100 M),

and glycerol release was determined after incubation for 3 h. Results show the percentage activity with

succinate (N=4 mice per group). D: Fasted mice were injected i.p. with succinate (1.2g/kg). Serum NEFA

was measured before and 15 min after injection (N=6 mice per group). E: Fasted mice were injected i.p.

with PIA (0.15 nmol/g). Serum NEFA was measured before and 15 min after injection (N=6 mice per

group). F: Body weight changes in male Suncr1-deficent mice (KO) and wild-type (WT) littermates fed a

standard diet (SD) for 16 weeks (N=8-12 mice per group). G: Body weights of male Suncr1-deficient mice

(KO) and wild-type (WT) littermates fed a SD for 50 weeks (N=8-12 mice per group). H: WAT weight

measurements after 20 weeks on diet (N=8-12 per group). I: Total fat weight taken as a percentage of body

weight after 20 weeks on diet (N=8-12 per group). J: NMRI analysis of body fat content and quantification

of several measurements (N=7 mice per group). Results were expressed as proportion of fat volumes vs.

total mouse volume (fat vol/total vol). K: Lipid quantification. 1H spectra of abdominal compartments from

wild-type and Sucnr1 KO mice (N=7 mice per group). Area under the curves were used to calculate the

portion of lipids with respect to water content. L: Representative H&E-stained sections (200X

magnification) of paraffin-embedded epididymal WAT from mice after 18 weeks of diet, and average

adipocyte size (N=8 mice per group). M: Flow cytometry analysis of epididymal adipocytes (N=6 mice per

group). N: Triglyceride (TG) content in epididymal fat from SD-fed mice (N=6 mice per group). O:

Relative expression of adipogenesis genes in epididymal WAT after 18 weeks on SD, determined by qRT-

PCR analysis; Peroxisome proliferator-activated receptor gamma (Pparγ), CCAAT/enhancer-binding

protein alpha (Cebpα), fatty acid binding protein 4 (Fabp4) (N=6 mice per group). P: Representative

31

Diabetes Page 32 of 46

images of Oil Red O-stained adipocytes differentiated from stromal vascular cells collected from wild-type and Sucnr1-deleted mice, and absorbance measurement (510nm) of Oil Red O staining (N=4 mice per group). Q: Relative expression of adipogenesis genes in differentiated adipocytes from SD-fed mice, determined by qRT-PCR analysis; Pparγ, Preadipocyte factor 1 (Pref1), Sterol Regulatory Element-

Binding Protein 1c (Srebp1c). (N=4 mice per group). Data represent mean ± s.e.m. Body weight analysis was assessed by repeated measures ANOVA. *P<0.05, **P<0.01, ***P<0.001.

Figure 4. Indirect calorimetry and UCP expression. Age-matched mice after 20 weeks of SD were individualy placed in metabolic cages (PhenoMaster) and allowed to acclimatize for 48 h before readings were taken (N=7-8 mice per group). A: Mean whole body oxygen consumption rate. B: RER (VCO2/O2).

C: Mean food intake (g). D: Mean energy expenditure (kcal.h.kg-1). E: Mean RER over dark and light cycles F: Mean food intake over dark and light cycles. G: Mean energy expenditure over dark and light cycles. H: Total ambulatory activity (sum of horizontal and vertical counts) over dark and light cycles

Measurements were recorded on a cycle of dark (D, 8:00PM to 8:00AM) and light (L; 8:00AM to

8:00PM). I: Relative expression of uncoupling protein 1 (UCP1), UCP2 and UCP3 in tissues (N=5-7 per group). Data represent mean ± s.e.m. *P<0.05, **P<0.01, ***P<0.001.

Figure 5. Analysis of mice under high fat diet. A: Body weight changes in male Suncr1-deficient mice

(KO) and wild-type (WT) littermates fed HFD for 16 weeks (N=8-12 mice per group). B: Organ weight measurements after 18 weeks on diet (N=8-12 per group). C: Body weight changes in male Suncr1- deficient mice (KO) and wild-type (WT) littermates fed HFD for 20 weeks (N=8 mice per group). D: WAT weight measurements after 20 weeks on diet (N=8 per group). E: Total fat weight taken as a percentage of body weight after 20 weeks on diet (N=8 per group). F: NMRI analysis of body fat content and quantification of several measurements (N=7 mice per group). Results were expressed as proportion of fat volumes vs. total mouse volume (fat vol/total vol). G: Lipid quantification. 1H spectra of abdominal compartments from wild-type and Sucnr1 KO mice (N=7 mice per group). Area under the curves were used to calculate the portion of lipids with respect to water content. H: Indirect calorimetry of age-matched

32

Page 33 of 46 Diabetes

mice after 8 weeks of HFD was performed as in Fig. 3. Mean whole body oxygen consumption, mean RER

over dark and light cycles and mean food intake over dark and light cycles. I: Serum levels of adipokines

measured in fasted mice at end of study (N=8-12 mice per group). J: Serum levels of non-esterified fatty

acids (NEFA), triglycerides (TG) and total cholesterol (CHOt) from Sucnr1-deficient mice (KO) and wild-

type (WT) littermates after 18 weeks on diets (N=8-12 mice per group). K: Representative H&E-stained

and Oil Red O-sections of paraffin-embedded liver taken from WT and KO mice after 18 weeks on diets

(100X magnification). L: Hepatic triglyceride content after 16 h fasting (N=8-12 mice per group). M:

Serum measurement of ALT and AST from Sucnr1-deficient mice (KO) and wild-type (WT) littermates

after 18 weeks on HFD (N=8-12 mice per group). Body weight analysis was assessed by repeated measures

ANOVA. Data represent mean ± s.e.m., *P<0.05, **P<0.01, ***P<0.01.

Figure 6. Sucnr1 KO mice show diet-dependent alteration in glucose homeostasis. A: Plasma levels of

fasting (16 h) and fed glucose in Sucnr1-deficient mice (KO) and wild-type (WT) littermates under

standard diet (left) and high fat diet (right) (N=8-12 mice per group). B: Plasma insulin levels after 16 h

fast (N=8-12 mice per group). C,D: Plasma glucose during glucose tolerance test (IPGTT, left) and insulin

tolerance test (IPITT, right) in standard diet (C) and HFD (D) (N=8-12 mice per group). E:

Phosphorylation of Akt (ser473) in liver, WAT and skeletal muscle of HFD mice. After an overnight fast,

mice were injected with PBS (-) or insulin (+, 1.5 units/kg) for 10 min. F: Serum insulin and GLP-1

concentrations measured from fasted wild-type (WT) and Sucnr1-deficient (KO) mice on HFD, measured

after i.p. glucose (1.5g/kg) injection (N=8 mice per group). G: Representative H&E-stained sections of

paraffin-embedded pancreas taken from WT and KO mice after 18 weeks on diets (100X magnification),

used to determine islet area and β-cell number. H: Quantification of islet size measured as a percentage of

total pancreas area (N=6 mice per group). I: Quantification of β-cell density was assesed by counting the

number of nuclei in a 1,740-m2 islet centre area (N=6 mice per group). J: Insulin content from acid-

extracted pancreata of HFD-fed mice (N=12 mice per group). K: Representative insulin immunostaining

(40X magnification) of pancreas from Sucnr1-deleted mice and wild-type littermates on HFD (left panels).

33

Diabetes Page 34 of 46

Immunofluorescence detection (100X magnification) of insulin (green) and glucagon (red) in islets from from Sucnr1-deleted mice and wild-type littermates on HFD (right panels). I: Representative Ki67 and caspase-3 staining of pancreas from Sucnr1-deleted mice and wild-type littermates on HFD. Islets are denoted by a dotted line, immunopositive cells are marked with an arrow. Data represent mean ± s.e.m.

IPGTT/IPITT analysis was assessed by repeated measures ANOVA *P<0.05, ***P<0.001.

34

Page 35 of 46 Diabetes

140x57mm (300 x 300 DPI)

Diabetes Page 36 of 46

Page 37 of 46 Diabetes

Diabetes Page 38 of 46

179x149mm (120 x 120 DPI)

Page 39 of 46 Diabetes

Diabetes Page 40 of 46

160x178mm (299 x 299 DPI)

Page 41 of 46 Diabetes

McCreath et al. Supplemental Figures. 1.A

Triglyceride composition analysis in abdominal fat. In vivo 13C spectrum acquired over abdominal fat depots. 13C spectrum shows the principal resonances of glycerides. The resonances can be attributed to (1) carbonylic (resonance 172ppm), (2+3) olefinic and polyolefinic (130 and 128 ppm), (4) the three carbon moieties in glycerol (resonance ≈ 60 ppm), and (5) methylene (30ppm). The areas under each peak were used to calculate the fractional contribution of saturated (130ppm), monounsaturated (130 and 128 ppm) and doubly (poly) unsaturated (128 ppm) fatty acids, taking as a reference the area under the carbonylic peak. A representative spectrum is shown from each genotype. Analysis was performed on 7 mice from each genotype.

Diabetes Page 42 of 46

1.B

1H-spectrum: water (4.7 ppm) and lipid (1.3 ppm) peak. The areas under the peaks were used to calculate the portion of lipids with respect to water content. Analysis was performed on 7 mice from each genotype.

Page 43 of 46 Diabetes

2.

Representative H&E-stained sections (200X magnification) of paraffin-embedded epididymal WAT from mice after 18 weeks of diet, and average adipocyte size (N=8 mice per group).

3.

Induction of hepatic steatosis by HFD. Expression profiling in liver of Sucnr1-deficient (KO) and wild-type mice (WT) under standard diet (C) and HFD (H). The expression level of each gene in wild-type mice is set to 1 (N=6 mice in each group). The gene functions are indicated at the top. Data represent mean ± s.e.m., *P<0.05, **P<0.01, ***P<0.001.

Diabetes Page 44 of 46

4.

Plasma glucose during glucose tolerance test (IPGTT) at 11 weeks on HFD. N=4-11 mice per group.

Page 45 of 46 Diabetes

Supplemental Table McCreath et al.

Oligonucleotide primers for qPCR

Gene Gene name Forward primer Reverse primer symbol Srebpc1 Sterol regulatory AGTTCTCAGATGCCCTTGGA TCATGTAGGAATACCCTCCTC1 elememt binding transcript factor 1 FAS Fatty acid synthase AGTGGCAGTGGTCTTCGAGT GGCCTTGATCATCACTGGAT1 Cpta2 Carnitine ATGTGGACCTGCATTCCTTC GAACTTGCCCATGTCCTTGT1 palmitoyltransferase 1B Fabp4 Fatty acid binding TGGAAGCTTGTCTCCAGTGA AATCCCCATTTACGCTGATG2 protein 4 Msr1 Macrophage CTGGACAAACTGGTCCACCT TCCCCTTCTCTCCCTTTTGT3 scavenger protein 1 Ucp1 Uncoupling protein 1 GTACCAAGCTGTGCGATGTC TCAGCTGTTCAAAGCACACA4

Ucp2 Uncoupling protein 2 TGAGACCTCAAAGCAGCCTC TCCTGCTACCTCCCAGAAGA4 Ucp3 Uncoupling protein 3 GCTACCTAATGGAGTGGAGCC TATGGAGGTCCGAGGAGAGA4

Adp Adiponectin TCCTGGAGAGAAGGGAGAGA CTTTCCTGCCAGGGGTTC2 Sucnr1 Succinate receptor 1 TGTTGGCCTACTGGAGAAGC CTGTTGCCAACCAATTCTCA4

4 Pparg Peroxisome GATGCACTGCCTATGAGCAC TCTTCCATCACGGAGAGGTC proliferator activated receptor gamma Pref1 Preadipocyte factor 1 ACGGGAAATTCTGCGAAATA CTTTCCAGAGAACCCAGGTG4 Acox2 Acyl-CoA oxidase 2 CCTTCCTAGACCTGCTTCCC TGTCCGTCATAACAGCCAAG4 Acadm Acyl-CoA AGCTCTAGACGAAGCCACGA GCGAGCAGAAATGAAACTCC4 dehydrogenase Cpta1 Carnitine GCCCATGTTGTACAGCTTCC AGTGGCCTCACAGACTCCAG4 palmitoyltransferase 1A Fatp2 Solute carrier family TCTGCTGCACTGCTTTCAAT CATCCTTTTTCAGGGTTGGA4 27 (fatty acid transporter) membrane CD36 CD36 molecule, GCGACATGATTAATGGCACA CCTGCAAATGTCAGAGGAAA4 thrombospondin receptor Scd1 Stearoyl-Coenzyme A GCTCTACACCTGCCTCTTCG CAGCCGAGCCTTGTAAGTTC4 desaturase Acca Acetyl-CoA AGTGGCAGTGGTCTTCGAGT GGCCTTGATCATCACTGGAT4 decarboxylase subunit alpha

1. Na, T.Y. et al. Positive cross-talk between hypoxia inducible factor-1α and liver X receptor α induces formation of triglyceride-loaded foam cells. Arterioscler. Thromb. Vasc. Biol. 31:2949- 2956 (2011). Diabetes Page 46 of 46

2. Petersen, P.S. et al. Deficiency of the GPR39 receptor is associated with obesity and altered adipocyte metabolism. FASEB J. 25:3803-3814 (2011).

3. Rufell, D. et al. A CREB-C/EBPβ cascade induces M2 macrophage-specific gene expression and promotes muscle injury repair. Proc. Natl. Acad. Sci. USA 106:17475-17480 (2009).

4. qPrimer depot: http://mouseprimerdepot.nci.nih.gov/