MOLECULAR MECHANISMS UNDERLYING THE ...

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v. TABLE OF CONTENTS. Dedication ii. Acknowledgements iii. List of Tables vii. List of Figures viii. Abstract .... sem (data already published in Richey JM et al., 2009)............................ 47. Figure 3.2: ...... Graham TE and Kahn BB. Tissue-specific ...
MOLECULAR MECHANISMS UNDERLYING THE EFFECTS OF CB1 ANTAGONISM IN CANINE MODEL OF OBESITY

by Malini Subramanian Iyer

A Thesis Presented to the FACULTY OF THE USC GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree MASTER OF SCIENCE (BIOCHEMISTRY AND MOLECULAR BIOLOGY)

December 2009

Copyright 2009

Malini Subramanian Iyer

DEDICATION

For my parents, Leena and T. V. K. Subramanian and my brother, Milan Iyer who made my dreams theirs. Also, for my friends and loved ones. Thank you for all your undying support and love.

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ACKNOWLEDGEMENTS I was very fortunate to receive excellent mentorship, guidance and support in Dr. Richard Bergman’s laboratory to put together the work presented in this thesis. I would like to thank the administrative staff at Keck School of Medicine especially, Anne Rice, Elena Camerena and Patricia Corona for their expert guidance through these two years. The amazing warmth and love that Elena radiates makes me feel at home while at work. I would also like to thank all my lab-mates for their support and help. They created the perfect ambience for a budding scientific mind to grow. A special thanks to Orison Woolcott, who taught me to be meticulous and pay attention to detail. I really appreciate the helping hands of Darko Stefanovski and Nicki Harrison and of course the laughters that Ed P and Ed Z bring with them. I would also like to thank Dr. Joyce Richey for being very supportive and the great human being that she is. I would also like to acknowledge my committee members Dr. Zoltan Tokes and Dr. Young Hong for being very encouraging, patient and accommodating. My deepest gratitude to Dr. Morvarid Kabir, who devoted a generous amount of her time in shaping up the work presented in this thesis. I cannot thank her enough for the rigorous training, guidance, patience and perseverance and the faith she had in me. Her teachings have enabled me to grow as a scientist.

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I am most grateful to Dr. Richard Bergman for giving me an opportunity to conduct research in his laboratory, for showing faith in me and inspiring me to dream big and achieve my dreams. He is truly a youth icon and I am very fortunate to get to know him closely. On the personal front, I would like to thank my parents, Leena and T. V. K. Subramanian and my brother, Milan Iyer for giving me wings to realize my dreams and for their undying support, prayers and love through all these years for my life. They are constantly with me even if we are separated by physical distances. I could not have gone through the anxieties of living alone in Los Angeles without the support of all my friends here (especially Neha Dayani, Divya Pathania, Mamta Nanavati, Nikhil Chopra, Pankaj Sunkeri and Sidney Colaco) and back home (especially Pallavi Sawant). Also, a special thanks to Gaurav Verma for his love and support.

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TABLE OF CONTENTS Dedication

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Acknowledgements

iii

List of Tables

vii

List of Figures

viii

Abstract

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Chapter 1: Background

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The pathophysiology of insulin resistance

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Adipose tissue

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The liver

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The Endocannabinoid System

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Rimonabant

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Fat-fed dog model

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Specific Goals

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Chapter 2: Materials and Methods

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Chapter 3: Goal 1: To study the molecular basis of action of Rimonabant on the adipose tissue metabolism

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Results

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Discussion

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Chapter 4: Goal 2: To study the mechanism of action of Rimonabant on liver insulin resistance

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Results

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Discussion

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Chapter 5: Summary and Conclusion

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Chapter 6: Future Directions

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References

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LIST OF TABLES

Table 2.1: PCR program for LightCycler® FastStart DNA Master SYBR Green I reaction. ...................................................................................... 40 Table 2.2: Primer sequences of target genes studied. PPAR-γ, peroxisome proliferator activated receptor-γ; SREBP1c, sterol response element binding protein-1c; C/EBP-α, CCAAT enhancer binding protein-α; LPL, Lipoprotein lipase; IL-6, interleukin-6; TNF- α, tumor necrosis factor- α, MCP-1/CCL2, macrophage chemoattract protein-1/ chemokine (C-C motif) ligand 2; IL-1β, interleukin-1β; IL-1RA, interleukin-1β receptor antagonist; AdipoR1, Adiponectin Receptor1; AdipoR2, Adiponectin Receptor-2; CPT-1α palmitoyltransferase1α, PPAR-α, peroxisome proliferator activated receptor- α; Uncoupling protein 2 (UCP2); Carcinoembryonic antigen-related cell adhesion molecules1 (CEACAM1) .......................................................... 42 Table 2.3: PCR program for LightCycler® TaqMan® Master reaction ............ 43

Table 3.1: Food intake, body weight and abdominal trunk composition in the PL and RIM groups (n = 20) in pre-fat and post-fat periods. SQ, subcutaneous adipose tissue; VIS, visceral adipose tissue. Values are means ± SEM .......................................................................................... 46

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LIST OF FIGURES Figure 1.1: Crosstalk between organs in metabolic syndrome. Signals from the sympathetic nervous system cause a flux of FFA from visceral adipose to the liver causing hepatic insulin resistance and increased lipid accumulation in muscle leading to systemic insulin resistance. Adapted from Bergman R. N., 2007 ........................................................... 4 Figure 1.2: Overview of FA uptake, lipogenesis, and lipolysis. AC, Adenylate cyclase; ACS. acyl-coenzyme A synthetase; aP2, adipocyte fatty acid binding protein; α2-AR, α2-adrenoreceptor; ATP, adenosine triphosphate; α-AR, β-adrenoreceptor; FATP, fatty acid transporter protein; FFA, free fatty acid; GI, inhibitory G protein; GS, stimulatory G protein; GLUT4, insulin-sensitive glucose transporter; glycerol 3-P, glycerol 3-phosphate; IR, insulin receptor; HSL, hormone-sensitive lipase; LPL, lipoprotein lipase; p, phosphorylation; PDE3B, cAMP phosphodiesterase 3B; PKA, protein kinase C. Adapted from Avram et al., 2005 ............................................................... 9 Figure 1.3: Adiponectin and its signaling pathways ......................................... 11 Figure 1.4: Proposed model for ATM polarization and its function in adipose tissue with progressive obesity .................................................... 12 Figure 1.5: Endocrine functions of adipose tissue during insulin resistance. Adapted from Lee DE et al., 2009 ............................................................ 13 Figure 1.6: Different sources of fatty acids contribute to the development of fatty liver ............................................................................................. 16 Figure 1.7: Interactions between liver, muscle and adipose tissue in the control of VLDL secretion (A) Normal state; (B) insulin-resistant state. ........................................................................................................ 18 Figure 1.8: Pharmacology of Rimonabant (SR141716A). ................................ 24 Figure 1.9: Adipocyte fat metabolism. In the first study factors involved in lipid metabolism (PPAR-γ, SREBP1c, C/EBP-α, HSL and ATGL (emphasized by highlighting)) have been investigated. Adapted from Avram et al., 2005 and Rocchi et al., 1999). ............................................. 29 Figure 1.10: Liver Triglyceride metabolism. In the second study factors involved in lipid oxidation (PPAR-α, CPT-1α, UCP2 and others

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(emphasized by highlighting)) have been investigated. Adapted from Postic C and Jean Girard, 2008 and Kohjima et al., 2007 ......................... 31 Figure 2.1: Research Design............................................................................ 35 Figure 3.1: Effect of Rimonabant on food intake, body weight and adiposity: a) Magnetic resonance imaging: Images correspond to scans at the level of the left renal hilum. Fat represented in yellow and nonfat tissue is shown in red/brown. b) Food Intake profile of dogs on high fat diet c) Body weight analysis of dogs treated with RIM. ■, Rimonabant group; ∆, placebo group. Data represented as mean ± sem (data already published in Richey JM et al., 2009). ........................... 47 Figure 3.2: Visceral Adipose Tissue cell size distribution determined using univariate normal decomposition method. Each distribution represented as mean (µ) ± standard deviation (σ). a) Cell distribution at week-6 comprising of one large population of cells (71.85±11.75) and two smaller populations (33.54±7.42 and 98.59±14.12). b) Cell distribution at week0 comprising of two large populations of cells (64.65±11.08 and 90.46±14.09) and one small population (27.11±4.22). c) Cell distribution at week16 in the placebo (HFD + PLW16) and rimonabant (HFD + RIMW16). The placebo group shows two major populations of cells (75.49±11.63 and 96.02±22.14) and one small population (29.61±6.55). The rimonabant group shows only one population of cells (75.75±15.54) .............................................. 49 Figure 3.3: Subcutaneous Adipose Tissue cell size distribution determined using univariate normal decomposition method. Each distribution represented as mean (µ) ± standard deviation (σ). a) Cell distribution at week-6 comprising of one large population of cells (65.53±13.26). b) Cell distribution at week0 comprising of one large population of cells (70.07±15.85). c) Cell distribution at week16 in the placebo (HFD + PLW16) and rimonabant (HFD + RIMW16). The placebo group shows one large population of cells (69.92±10.24) and one small population (90.50±24.12). The rimonabant group shows only one population of cells (66.59±12.78) ...................................................... 50 Figure 3.4: Relative gene expressions of factors involved in lipid metabolism and adipocyte differentiation in the subcutaneous (SQ) and visceral (VIS) adipose tissue at week-6, week0, week16 placebo group (16PL) and week16 rimonabant group (16RIM). a) Peroxisome proliferator activated receptor-γ (PPAR-γ) b) Sterol response element ix

binding protein-1c (SREBP1c) c) CCAAT enhancer binding protein-α (C/EBP-α d) Lipoprotein lipase (LPL). Data represented as mean ± sem. p values calculated by two-tailed Mann-Whitney’s nonparametric t-test with 95% confidence interval. ........................................ 53 Figure 3.5: Relative gene expressions of factors involved in lipid metabolism in the subcutaneous (SQ) and visceral (VIS) adipose tissue at week-6, week0, week16 placebo group (16PL) and week16 rimonabant group (16RIM). a) Hormone Sensitive lipase (HSL). b) Adipose Triglyceride Lipase (ATGL). Data represented as mean ± sem. p values calculated by two-tailed Mann-Whitney’s nonparametric t-test with 95% confidence interval ......................................... 54 Figure 3.6: FFA measurements in a) visceral and b) subcutaneous adipocytes culture medium at wk-6, wk0, wk16 PL group and wk16 RIM group at 24hrs. ................................................................................. 56 Figure 3.7: Relative gene expressions of inflammatory factors in the subcutaneous (SQ) and visceral (VIS) adipose tissue at week-6, week0, week16 placebo group (16PL) and week16 rimonabant group (16RIM) a) interleukin-6 (IL-6) b) tumor necrosis factor-α (TNF-α) c) CD68 d) Macrophage chemoattract protein-1/ chemokine (C-C motif) ligand 2 (MCP-1/CCL2) e) interleukin-1β (IL-1β) f) interleukin-1β receptor antagonist (IL-1RA). Data represented as mean ± sem. p values calculated by two-tailed Mann-Whitney’s nonparametric t-test with 95% confidence interval ......................................... 59 Figure 3.8: Plasma and mRNA levels of Adiponectin. a) Amount of adiponectin in plasma (µg/mL), blue graph representing placebo group and pink graph representing rimonabant group. b) Relative gene expression of adiponectin in the subcutaneous (SQ) and visceral (VIS) adipose tissue at week-6, week0, week16 placebo group (16PL) and week16 rimonabant group (16RIM). Data represented as mean ± sem. p values calculated by two-tailed Mann-Whitney’s nonparametric t-test with 95% confidence interval. ........................................ 61 Figure 4.1: Liver histology of sections taken at week-6 (w-6) and at week16 (placebo (w16) and rimonabant(w16)). a) H&E staining, 20x b) Oil Red O staining, 40x. Sections at week16 with placebo treatment show small lipid droplets (fat) and with Rimonabant treatment no lipid droplets observed. ........................................................ 72 Figure 4.2: Relative gene expressions of adiponectin receptors in the liver at week-6, week0 and week16 in placebo group rimonabant group x

(Rim). a) Adiponectin Receptor-1 (AdipoR1). Data represented as mean ± sem. p values calculated by two-tailed Mann-Whitney’s nonparametric t-test with 95% confidence interval. * = p< 0.05 vs week6, ** = p< 0.01 vs week-6, # = p< 0.05 vs week0, # # = p< 0.01 vs week0 ...................................................................................................... 73 Figure 4.3: Relative gene expressions of genes involved in lipid oxidation in the liver at week-6, week0 and week16 in placebo group rimonabant group (Rim). a) peroxisome proliferator activated receptor-α (PPAR-α) b) carnitine palmitoyltransferase-1α (CPT-1α) c) uncoupling protein 2 (UCP2) d) Long chain acyl dehydrogenade (LCAD). Data represented as mean ± sem. p values calculated by two-tailed Mann-Whitney’s non-parametric t-test with 95% confidence interval. * = p< 0.05 vs week-6, ** = p< 0.01 vs week-6, # = p< 0.05 vs week0, # # = p< 0.01 vs week0 ............................................ 75 Figure 4.4: Relative gene expressions of inflammatory cytokines a) interleukin-6 (IL-6) b) tumor necrosis factor-α (TNF-α) in the liver at week-6, week0 and week16 in placebo group (16PL) and week16 rimonabant group (16RIM). Data represented as mean ± sem. p values calculated by two-tailed Mann-Whitney’s non-parametric t-test with 95% confidence interval. .................................................................. 76 Figure 4.5: Relative gene expression of Carcinoembryonic antigen-related cell adhesion molecules1 (CEACAM1). Data represented as mean ± sem. p values calculated by two-tailed Mann-Whitney’s nonparametric t-test with 95% confidence interval. * = p30kg/m2 (164). RIM is metabolized by hepatic cytochrome P450 3A4 (CYP3A4) (78) and amidohydrolase and is excreted in bile (163). Due to extensive first pass metabolism of RIM, the oral bioavailability of the drug is low to moderate. 23

Figure 1.8: Pharmacology of Rimonabant (SR141716A) (Adapted from (150,158)). Experimental data in animal models showed that RIM caused a sustained reduction in body weight (126, 131), leading to preclinical studies on the use of RIM in obesity (18). Subsequently, double blind Rimonabant in Obesity (RIO) clinical trials, namely, RIO-Lipids, RIO-Europe, RIO-North America and RIO-Diabetes revealed that RIM significantly reduced waist circumference and total adiposity (37, 125, 157). RIM is proposed to induce weight loss in two phases (8). The early phase involves modulation of food intake. Several studies with RIM have shown that RIM reduces food intake in rodents due to its anorexigenic effects centrally (39, 159). After the early phase, tolerance to anorectic effect of the drug developed, although sustained reduction in body weight was observed throughout the treatment (30). Similar results were observed in dietinduced obese mice (131). RIM has been shown to only transiently decrease food intake 24

in the canine models too (134). Hence, RIM has a food intake independent mechanism to reduce body weight. Genetically obese and diet-induced obese mouse models have been studied widely to unravel the mechanisms of weight loss induced by the blockade of the CB1 receptor. Studies have also shown that RIM reduces adiposity in rodents especially in the visceral fat (65). In RIO clinical trials side effects such as insomnia, nausea, diarrhea and dizziness were observed. (163). In RIO-Lipids, RIO-Europe and RIO-North America, RIM was withdrawn from phase III clinical trials, due to development of psychiatric disorders, especially depression in 6-7% of individuals treated with RIM (120, 163). However, additional data on RIM safety is likely to emerge in 2-3 years upon completion of several human clinical trials namely, CRESCENDO, examining RIM effect on cardiovascular infarctions; STRADIVARIUS, examining prolonged RIM effect on metabolic syndrome and atherosclerosis; VENUS, testing chronic RIM effect on weight loss and TG changes; and SYMPHONY and SOLO, testing anti-obesity efficacy of RIM (Reviewed by Vemuri V. K et al., 2008 (158)).

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Fat-fed dog model Animal models have been long used for the studies of obesity and insulin resistance. In our laboratory, the obese dog model was developed to understand the pathophysiology of type 2 diabetes. Dogs demonstrate visceral obesity similar to humans and are also genetically more homogenous to humans than rodents. Also, like humans, dogs demonstrate wide variance in the deposition of body fat in a natural population. One of the major advantages of the dog model system is the easy accessibility to the portal vein, making longitudinal studies more feasible. Such measurements are appealing in rodents as also, non-human primates (Reviewed in (13)). Kirkness E. F. et al. in 2003, demonstrated that the dog genome exhibits relatively higher degree of homology and conservation with the human genome as compared to the rodents, allowing extrapolation of canine molecular biology studies to the etiology of human diseases (87). Insulin resistance in vivo in animal models can be induced in many different ways including genetic alterations (used in rodent models), pancreatectomy, infusion of hormones (like growth hormone) or fat-feeding. In our laboratory fat-feeding was used to induce insulin resistance due to overwhelming evidences associating obesity and insulin resistance. Rocchini et al., 1997, developed the insulin-resistant fat-fed model by feeding Mongrel dogs normal diet supplemented with ~0.9 kg of cooked beef fat, which lead to ~50% reduction in insulin sensitivity by the 3rd week of the feeding regimen accompanied by ~13% increase in body weight (136). In our laboratory, Mittelman S. D. et al., 2000 developed the fat-fed dog model by using a more moderate feeding regimen

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that consisted of diets supplemented with 2g/kg of body weight of cooked bacon grease for 12 weeks resulting in the development of insulin resistance within the 1st week of feeding regimen, accompanied by compensatory hyperinsulinemia by 3rd week

and

reduction in hepatic insulin clearance (11, 108). Kim S. P. et al., 2007 (83) developed another dog model with 6 weeks of hypercaloric high fat feeding and approximately 60% increase in calories from fat, to induce insulin resistance. In the following studies we used this hypercaloric high fat fed model with the same feeding regimen for 6 weeks followed by treatment with continued high fat feeding for another 16 weeks.

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Specific Goals Experimental and clinical data on the effect of endocannabinoid system blockade by RIM have shown that RIM reduces body weight, accompanied by reduction in waist circumference and total adiposity (37, 125, 126, 131, 157). Our laboratory studied the effect of RIM in our obese fat fed canine model. In a recently published physiology data Richey J.M. et al., in our laboratory showed that RIM reduces accumulation of fat in the visceral and subcutaneous depots in the fat fed dog model (134). We intended to study the molecular mechanisms underlying the physiological phenomena by which RIM prevents adiposity and insulin resistance by acting on the peripheral system. Clearly one of the main targets of RIM action is the adipose tissue. Since, RIM has been shown to reduce body weight in other animal models (32, 68, 131, 134), we can hypothesize that RIM modulates the lipid turnover rate and the genes involved in lipid accumulation in the adipose tissue. In the first study, we will examine the effects of RIM on the adipose tissue metabolism. Changes in lipid accumulation in the adipose tissue per fat cell can be hypothesized to bring about changes in fat-cell size. In the following study, we intend to microscopically study the fat cell size distributions. To study the RIM effect on the adipose tissue metabolism, we will study gene expression of transcription factors (PPAR-α, SREBP1c) involved in lipid accumulation and enzymes involved in lipid mobilization (HSL, ATGL) in both the VIS as well as SQ fat depots (Figure 1.9). To study various adipokines secreted by adipocytes treated with RIM, we will to culture adipocytes from both the fat depots up to 24hrs and study factors released by the cells in the medium. Due to overwhelming evidences linking insulin resistance and inflammation,

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the following study will also examine RIM effect on adipose tissue inflammation. Finally, RIM has been shown to increase the release of adiponectin in many animal models. We intend to study this effect of RIM in the canine model by studying the gene expression profile of adiponectin in the fat tissue.

Figure 1.9: Adipocyte fat metabolism. In the first study factors involved in lipid metabolism (PPAR-γ, SREBP1c, C/EBP-α, HSL and ATGL (emphasized by highlighting)) have been investigated. Adapted from Avram et al., 2005 and Rocchi et al., 1999 (2,135).

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Kim S. P. et al., in our laboratory showed primacy of hepatic insulin resistance in the fat-fed dog model (85). Hence, another target of the CB1 antagonist in improving insulin sensitivity is clearly the liver. Kim S. P. et al., in a recent study showed that RIM improves primarily hepatic insulin sensitivity conferring overall insulin-sensitivity in our canine fat-fed model (81). Studies in our laboratory also showed that RIM improves plasma adiponectin levels. Hence, we hypothesized that adiponectin secreted by the fat plays a role in sensitizing hepatocytes to insulin. To study this direct adiponectin effect on liver, in the second study, we will study the expression of adiponectin receptors (AdipoR1, and AdipoR2) as well as their downstream effectors, mainly PPAR-α. Studies have shown that PPAR-α is involved in the oxidation of fat (139, 155). Hence, we hypothesized that RIM increases fat oxidation in the liver. Thus, we will examine the gene expression of factors involved in fatty acid oxidation, namely PPAR-α (regulates genes involved in fat oxidation) and CPT-1α (regulates the entry of fatty acids into the mitochondria for oxidation) (88). PPAR-α, a transcription factor regulating many genes is involved in fat oxidation in the liver. Studies involving agonists of PPAR-α have shown that in the liver, PPAR-α regulates mitochondrial genes for uncoupling proteins, namely UCP2 (80, 112, 147, 154). Hence, we further intended to study UCP2 to understand the mechanisms of RIM effect on fat oxidation (Figure 1.10).

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Figure 1.10: Liver Triglyceride metabolism. In the second study factors involved in lipid oxidation (PPAR-α, CPT-1α, UCP2 and others (emphasized by highlighting)) have been investigated. Adapted from Postic C and Jean Girard, 2008 and Kohjima et al., 2007 (88, 128)

Goal 1: To study the molecular basis of action of rimonabant on the adipose tissue metabolism. In this study we examined the molecular effects of RIM on VIS and SQ adipose tissue. In order to study this we analyzed: 31

1. Visceral and subcutaneous fat cell size and distribution. 2. Factors involved in lipid accumulation and adipocyte differention (PPAR-γ, SREBP-1c and C/EBP-α) and TG hydrolysis (HSL and ATGL). 3. FFA released by adipocytes in the culture medium 4. Factors responsible for adipocyte inflammation (IL-6, TNF-α, CD68, MCP1/CCL2, IL-1β and IL1RA) 5. Adiponectin gene expression.

Goal 2: To study the molecular mechanism of action of rimonabant on liver insulin resistance. In this study, we aimed to elucidate the mechanism by which RIM increased plasma adiponectin levels leading to improved hepatic insulin sensitivity and decreased lipid accumulation in liver. Inorder to achieve this aim we analyzed: 1) Liver histology 2) The expression of adiponectin receptors AdipoR1 and AdipoR2 and their downstream effectors PPAR-α, CPT-1α, UCP2 and LCAD 3) Inflammation in the liver

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CHAPTER 2: MATERIALS AND METHODS Animals Twenty male mongrel dogs (body weight 29 ± 0.9 kg) were housed in the Keck School of Medicine, University of Southern California (USC) vivarium under controlled kennel conditions (12:12-h light-dark cycle). Animals were surgically outfitted with chronic indwelling catheters for blood sampling and infusions. Experimental protocols were approved by the University Institutional Animal Care and Use Committee.

Diet Upon arrival, dogs underwent a period of acclimatization for three weeks, during which time they were fed a standard diet. The standard diet consisted of one can of Hill’s Prescription Diet (Hill’s Pet Nutrition, Inc, Topeka, KS) and 825 g of dry chow (Wayne Dog Food, Alfred Mills, Chicago, IL). This standard diet was given as 3-week acclimatization, weight maintenance diet and consisted of (~3885 kcal/d, 39% carbohydrates, 33% lipids and 27% proteins). Meals were presented daily for 3 hours, from 9:00 a.m. to 12:00 p.m. After 3 weeks of standard diet we fed the dogs high-fat diet (HFD) which consisted of ~5527 kcal/d (28% carbohydrates, 53% lipids and 19% proteins), representing an approximate 60% increase in calories from fat. The 3-hour daily feeding period was maintained. Food intake measurements were recorded daily and body weight measurements were recorded weekly. Previously we have shown that 6 weeks of fat 33

feeding promotes a consistent increase of fat in the abdominal trunk and subcutaneous fat rendering the dog insulin resistant (83). Thus, the HFD was maintained for a minimum of 6 weeks (9 ± 2 wks) period prior to any treatment (Figure 2.1).

Treatment After establishment of obesity with the HFD, dogs were randomly divided into two groups: RIM (n = 11) or placebo (PL) (n = 9) (Figure 2.1). Animals were matched for body weight (31.7 ± 1.3 and 31.8 ± 1.5 kg; RIM versus PL group, respectively). RIM (Sanofi-Aventis, Paris, France) was encapsulated (AMC Pharmacy, Burbank, CA) and administered orally at 1.25 mg/kg/day, while placebo-treated animals received inert capsules. The dose of RIM was chosen based on a pilot study carried out in a small group of dogs (n=5), testing different doses ranging from 5-1.25 mg/kg. We chose 1.25 mg/kg, as this dose did not produce any observable clinical adverse effects.

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Figure 2.1: Research Design

Food Intake, Body weight and Metabolic Parameters We performed daily recordings of food intake throughout the study as well as weekly recordings of body weight. Food intake data for each specific week are presented as averages of the 7-day recording for that week. All animals underwent various metabolic assessments in random order, prior to fat feeding (week-6); after fat feeding (week0) and after treatment (week16). These assessments included euglycemic hyperinsulinemic clamp (EGC) that allowed for quantification of insulin sensitivity. The clamp studies were performed in 18 hour fasted dogs that were fully conscious and resting comfortably in a Pavlov sling. Biopsies were taken at the end of each phase and adipocytes were 35

isolated. All analyses were performed on blood samples drawn after an overnight fast (~12 hours) and stored at -80ºC until analysis.

Adipocyte isolation Adipocytes were isolated and investigated from the SQ and VIS depots prior to the beginning of the HFD (week–6), after induction of increased body weight and adiposity and prior to initiation of drug (week0), and thereafter at weeks 16 of treatment (week 16). Adipocytes were isolated according to the method of Rodbell (138), in a Krebs-Ringer bicarbonate buffer (pH 7.4) containing 3.5% bovine serum albumin, plus 1 mg/ml collagenase. Digestion took place in a shaking water bath for 40 min at 37°C. The suspension was then filtered and the cellular filtrate obtained was washed 3 times with 15 ml of Krebs buffer. Between 0.5 to 1ml of pure cells were obtained and re-suspended in 6ml Krebs buffer. An aliquot (10ul) of cells was placed on a glass slide and 300-1000 cells were photographed and measured using the Olympus CKX41 inverted microscope. Cell diameter and number were counted by Image-Pro Express software (Media Cybernetics, MD).

Adipocyte Cell Size and Distribution Adipocytes were photographed using the Olympus CKX41 inverted microscope and cell diameter was measured by Image-Pro Express software (Media Cybernetics, MD). To determine whether several populations of adipocytes could be identified in either depot, 36

we employed the univariate normal mixture decomposition method developed by Stanislav Kolenikov for STATA 10, StataCorp, College Station TX. The multiple normal distribution model that best explained the data was chosen based on the lowest p-value of the chi2 test.

Adipocyte cell culture For cell culture, after digestion of tissue in Krebs-Ringer bicarbonate buffer, the products of digestion were filtered through a sterile nylon mesh and the mature adipocytes were allowed to float. Floating adipocytes were then washed in Hank’s solution and subsequently with culture medium. Pure cells were then suspended in Dulbecco’s modified Eagle’s medium/F-12 (DMEM; 5.5mM glucose) containing 20mM N-2hydroxyetylpiperazine-N’-2-ethansulphonic acid 1% fetal bovine serum, 2% bovine serum albumin (BSA), 62.5U/mL penicillin and 62.5ug/mL streptomycin, pH 7.4 and incubated in 50mL polypropylene tubes (Falcon) at 370C under 5% CO2 (22, 99). Adipocytes were cultured either in non-stimulated basal conditions or stimulated either with 100nM rimonabant (20µL) or 100nM anandamide (20µL). The medium was aspirated and the cells were suspended in new medium every day. The aspirated medium was stored at -20oC for measurements of factors released by adipocytes in the medium.

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RNA Isolation RNA isolation from the frozen tissue was carried out using single step Guanidium thiocynate-phenol-chloroform extraction method originally devised by Chomczynski P. and Sacchi N. in 1986 (27, 28). Guanidium thiocynate-phenol-chloroform is sold as TRI Reagent® by Sigma-Aldrich, Inc., St Louis, MO (trademark Molecular Research Center,Inc., Cincinnati, OH). Approximately 100mg of the frozen tissue (adipose tissue and liver) was mechanically homogenized in 1mL TRI reagent® (50% phenol, 30% Guanidium thiocynate). Chloroform in volumes equal to 1/5th of the total volume was then added to form a biphasic mixture. The upper aqueous phase of the mixture comprises of proteins (denatured by phenol), lipids (denatured by chloroform), DNase, RNase and rRNA from ribosomes (denatured by Guanidium thiocynate); whereas DNA partitions at the interphase. The aqueous phase was carefully separated without disturbing the interphase and RNA was precipitated using 2-Propanol (Sigma-Aldrich, Inc., St Louis, MO). The RNA pellet was then washed with 100% and 75% Ethanol and dried to remove traces of alcohol. Depending on the size of the pellet, RNA was dissolved in 20-80µL of DEPC (Diethylpyrocarbonate)-treated nuclease free water (Ambion, Inc., Austin, TX). The amount and purity of RNA was measured by determining the optical density (OD) of each sample using U.V. Spectrophotometer (Beckman Coulter, Inc., Fullerton, CA). Total RNA was quantified by absorbance measurement at 260nm.The OD260/OD280 38

measurement of all preparations ranged between 1.8 and 2.1, indicating the purity of the samples.

First strand cDNA preparation (reverse transcription) First strand cDNA was synthesized according to manufacturer’s protocol (Invitrogen, Carlsbarg, CA). In brief, 2µL of total RNA was primed using non-specific (random hexamers). RT-PCR reaction was catalyzed by SuperScript™ II Reverse Transcriptase (RT) (Invitrogen, Carlsbarg, CA) using GeneAmp PCR System 2400 Thermocycler (Applied Biosystems, Inc., Foster City, CA). The sensitivity of the reaction was improved using RNase H digestion of the cDNA product to remove residual mRNA.

Real-Time PCR Amplification of cDNA was carried using LightCycler® 2.0 instrument (Roche Applied Science, Indianapolis, IN) in 20µL glass capillaries. For 18S rRNA, housekeeping gene used for sample normalization, SYBR Green I kit was used. The SYBR Green reaction was designed to a final volume of 10µL reaction mixture containing 100 fold diluted cDNA, LightCycler® FastStart DNA Master SYBR Green I mix (Roche Applied Science, Indianapolis, IN), MgCl2 (3mM final concentration) and 0.5µL each of 18S rRNA forward (5’GGA TGC GTC CAT TTA TCA GA 3’) and reverse primers (5’ATC

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GGC CCG AGG TTA TCT 3’). LightCycler for 18S rRNA SYBR Green I reaction was programmed as follows (in that order) (Table 2.1): Program

Analysis

Cycles

Segment

Mode

Temp o

Time

Ramp Rate

C

o

C/s

PreIncubation

-

1

-

95

10min

20

PCR

Quantification

45

Denaturation

95

10s

20

Annealing

65

5s

20

Extension

72

10s

20

Denaturation

97

10s

20

Annealing

65

10s

20

Melting

97

1s

0.2

-

40

30s

20

Melting

Melting

Curve

Curves

Cooling

-

1

1

Table 2.1: PCR program for LightCycler® FastStart DNA Master SYBR Green I reaction. For other genes of interest, cDNA was amplified using ‘Universal probe system’. The reaction was designed to a final volume of 10µL reaction mixture containing 100 fold diluted cDNA, LightCycler® TaqMan® Master Mix (Roche Applied Science, Indianapolis, IN), universal library specific probes and 1µL each of forward and reverse primers (Table 2.2). All primers and universal probes were designed in Roche Applied Science

website:

(https://www.roche-applied-

40

science.com/sis/rtpcr/upl/acenter.jsp?id=030000). The LightCycler reaction for TaqMan kit was programmed as follows (in that order) (Table 2.3): Primer PPAR-γ

Primer Sequence Forward 5’-ACAGGACAACCTGCTACAAGC-3’ Reverse

SREBP-1c

C/EBP-α

HSL

ATGL

IL-6

TNF- α

CD68

MCP-1/CCL2

IL-1β

IL-1RA

Adiponectin

54

5’-TGATGTTAACGGCCTCCAG-3’

Forward 5’AGAGATGGCACCCCTGGT-3’ Reverse

46

5’-GTAACTTGCAGTCCACCGATT-3’

Forward 5’-GCCTGGCCTGTGTCAAGT-3’ Reverse

62

5’-CAGCCTCTGAATTGAGATCTTCT-3’

Forward 5’-TGCAAAACAGATGCGGATAA-3’ Reverse

86

5’-GGATGCGTTCTGACCTGAG-3’

Forward 5’-AGCCAGATGCAATTATTTCTCC-3’ Reverse

53

5’-GGGTCTCCCTTTGGCAAG-3’

Forward 5’-GCAGTACAACGTGTCCTTTCC-3’ Reverse

9

5’-CGGGGTAGGGAAAGCAGTA-3’

Forward 5’-GCCGTCTCCTACCAGACAAA-3’ Reverse

34

5’-CTGTCCTGTGCTGCCTACAG-3’

Forward 5’-CTCCACAAGCGCCTTCTC-3’ Reverse

81

5’-ACAGTCGTCGTGCGGTCT-3’

Forward 5’-GCCATGATGGTGCCCTAC-3’ Reverse

19

5’-AAGCTGTCCTTCCCTGCTC-3’

Forward 5’-TCTGGCAGAAGACAACATGG-3’ Reverse

8

5’-GGCCAGGGAGCTGATACC-3’

Forward 5’GGCTCCTGGTCTGGAAGG-3’ Reverse

78

5’-TGGCAAAGAGCTGAGAGGAC-3’

Forward 5’-TGCTTCTGACAACCATGAAAA-3’ Reverse

UPL probe

85

5’-CAGTGTCACCCTTAGGACCAAC-3’ 41

Primer AdipoR1

Primer Sequence Forward 5’-TCCCCTGGCTCTATTACTCCT-3’ Reverse

AdipoR2

CPT-1α

PPAR- α

UCP2

LCAD

CEACAM1

1

5’-GGCATTTGTTTTTATTCCTTGC-3’

Forward 5’-TTCCAGAACATCACCCTGAA-3’ Reverse

23

5’-CCTGGAACCGGACCTTTACTA-3’

Forward 5’-GGGAAATGTATTGGTGCCATAG-3’ Reserve

5

5’-GCGATCTCCACAGCAAATG-3’

Forward 5’-ACAGGTGCCTTGGCTGTG-3’ Reserve

26

5’-CAGGACGTACTCCCACAGGT-3’

Forward 5’-GGAGCTAGATGACAGCGACA-3’ Reverse

2

5’-GCCCCCAAGAAGAATAATC-3’

Forward 5’-ATGGGCATGAACGCAGAG-3’ Reverse

76

5’-CAGGACACAGACGATGGAGA-3’

Forward 5’-CCCAAACATCTCCTTTGTGG-3’ Reverse

UPL probe

47

5’-AGTGCAGTTTCAAATTTTTGGTT-3’

Table 2.2: Primer sequences of target genes studied. PPAR-γ peroxisome proliferator activated receptor- γ; SREBP1c, sterol response element binding protein-1c; C/EBP-α, CCAAT enhancer binding protein- α; LPL, Lipoprotein lipase; IL-6, interleukin-6; TNF-α, tumor necrosis factor-α; MCP-1/CCL2, macrophage chemoattract protein-1/ chemokine (C-C motif) ligand 2; IL-1β interleukin-1β; IL-1RA, interleukin-1β receptor antagonist; AdipoR1, Adiponectin Receptor-1; AdipoR2, Adiponectin Receptor-2; CPT-1α palmitoyltransferase-1α; PPAR- α peroxisome proliferator activated receptor-α; Uncoupling protein 2 (UCP2); Carcinoembryonic antigen-related cell adhesion molecules1 (CEACAM1)

42

Program

Analysis Mode

Cycles

Segment

Temp o

Time

Ramp Rate oC/s

C

Pre-Incubation

-

1

-

95

10min

20

PCR

Quantification

45-55

Denaturation

95

10s

20

Annealing

60

30s

20

Extension

72

1s

20

-

40

30s

20

Cooling

-

1

Table 2.3: PCR program for LightCycler® TaqMan® Master reaction The Roche LightCycler® software version 4.05.415 calculates the concentration of the sample using ∆∆CT method. These results were further analyzed by relative quantification.

FFA Assay: FFA released in the medium by the cultured adipocytes was measured colorimetrically using Free Glycerol Reagent A (Sigma-Aldrich, Inc., St Louis, MO). In this reaction, glycerol and FFA in the sample are phosphorylated by glycerol kinase (GK) using ATP to form glycerol-1-phosphate (G-1-P) and ADP. G-1-P is oxidized to dihydrogen acetone phosphate (DAP) and hydrogen peroxide (H2O2) by glycerol phosphate oxidase (GPO). Peroxidase (POD) then couples H2O2 with 4-aminoantipyrine (4-APP), N-ethyl-N-(3-sulfopropyl)-m-anisidine (ESPA) and sodium to produce quinoneimine dye with absorbance maximum at 550nm, which is directly proportional to the TG concentration in the sample. 43

Glycerol + ATP

G-1-P + ATP

G-1-P + O2

DAP + H2O2

H2O2 + 4-APP + ESPA

Quinoneimine dye (λ550nm) + H2O2

FFA concentration in the sample was determined using Glycerol Standard (Sigma-Aldrich, Inc., St Louis, MO). 20mL of adipocyte medium was incubated with reconstituted Free Glycerol Reagent A for 20mins. The reaction was stopped by placing the microtiter plate in ice. The absorbance was read at 550nm using EMax® Microplate Reader (Molecular Devices, Sunnyvale, CA) with SOFTmax® Pro softaware (Molecular Devices, Sunnyvale, CA). From the absorbance the concentration of FFA was calculated and expressed in mM/106 cells.

Histology of Liver Biopsies of the liver were taken and fixed in 10% formalin (Sigma, St. Louis, MO). Thin slices of the tissue were embedded in paraffin and stained either with haematoxylin and eosin (H&E) or Oil Red O by the Liver Core Facility (University of Southern California, Los Angeles, CA). Photographs of slides stained with H&E were observed under 20x magnification and those stained with Oil Red O under 40x.

44

CHAPTER 3: GOAL 1: TO STUDY THE MOLECULAR BASIS OF ACTION OF RIMONABANT ON THE ADIPOSE TISSUE METABOLISM

In this study we intended to examine the molecular effects of RIM on VIS and SQ adipose tissue. In order to study this we analyzed: 1. Visceral and subcutaneous fat cell size and distribution. 2. Factors involved in lipid accumulation and adipocyte differentiation (PPAR-α, SREBP-1c and C/EBP-α) and TG hydrolysis (HSL, ATGL). 3. FFA released by adipocytes in the culture medium, in order to study the overall lipid turnover. 4. Factors responsible for adipocyte inflammation (IL-6, TNF-α, CD68, MCP1/CCL2, IL-1β and IL1RA) 5. Adiponectin gene expression

45

RESULTS General characteristics of fat fed animal model The effects of fat feeding on food intake, body weight and adiposity are presented in Table 3.1. As previously reported, 6 weeks of fat feeding is sufficient to observe increased caloric intake resulting in increases in body weight and adiposity in both visceral and subcutaneous fat depots. Pre-fat

Post-fat

p-value

Food intake (kcal/d)

2335 ± 295

2683 ± 134