Potential Role of Melanocortin 4 Receptor in Physical

POTENTIAL ROLE OF MELANOCORTIN 4 RECEPTOR IN PHYSICAL

ACTIVITY ENERGY EXPENDITURE IN RATS:

EFFECT OF CALORIE RESTRICTION

A dissertation submitted

to Kent State University in partial

fulfillment of the requirements for the

degree of Doctor of Philosophy

Tariq Almundarij

December 2015

Except for previously published materials

B.Sc., Al qassim University, Saudi Arabia 2005

M.A., Kent State University, USA, 2012

Ph.D. Kent State University, USA,2015

Approved by

Dr. Colleen Novak, Chair, Doctoral Dissertation Committee

Dr. Eric Mintz, Member, Doctoral Dissertation Committee

Dr. Gary Koski Member, Doctoral Dissertation Committee

Dr. Jacob Barkley, Member, Doctoral Dissertation Committee

Dr. John Gunstad, Member, Doctoral Dissertation Committee

Accepted By,

Dr Laura Leff Chair, Department of Biological Science

Dr. James L. Blank Dean, College of Arts and Science

Abstract

Tariq, Almundarij, PhD, December 2015 Physiology

POTENTIAL ROLE OF MELANOCORTIN 4 RECEPTOR IN PHYSICAL

ACTIVITY ENERGY EXPENDITURE IN RATS: EFFECT OF CALORIE

RESTRICTION (173 PP)

The prevalence of obesity around the world has increased in recent years. Obesity results from imbalance between calories in and energy expenditure. Total daily energy expenditure (EE), including resting energy expenditure and non-resting energy expenditure, are critical factors that contribute for individual differences in body weight, and are affected by genetic predisposition. The brain serves to regulate energy balance homeostasis via number of neuroendocrine regulators; one of these is the brain melanocortin system, which includes the melanocortin 4 receptor (MC4R). Melanocortin

4 receptor mutation is one of the few known monogenic causes of obesity in humans.

MC4R is also the target of numerous genetic variants that contribute to human obesity.

Central MC4R plays a critical role in controlling energy homeostasis, increasing energy expenditure, and decreasing food intake. Here, I investigate the contribution of physical activity and EE to obesity in rats lacking functional MC4R, and test the hypothesis that

MC4R signaling underlies differential weight loss during calorie restriction. Although rats lacking functional MC4R did not show lower EE under free-fed conditions, they lost significantly less weight during calorie restriction. During weight loss, adaptive

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thermogenesis occurs where EE is suppressed beyond what is predicted for the smaller body size. Prolonged food restriction in rats resulted in reduced in daily EE, including resting and non-resting EE. These decreases in EE were significant even when the reductions in body weight and lean mass were taken into account. Similarly, the caloric need for moderate-level treadmill activity was decreased by 50% calorie restriction, as were baseline and activity-related muscle thermogenesis, though the ability to increase muscle thermogenesis above baseline levels was not compromised. When sympathetic nervous system drive was measured by assessing norepinephrine turnover (NETO), 50% calorie restriction was found to decrease NETO in three of the four muscle groups examined, while increasing NETO in white adipose tissue. Central activation of MC4R in the ventromedial hypothalamus stimulated this brain-muscle pathway, enhancing activity

EE, and this was not compromised by 50% calorie restriction. These data suggest that suppressed activity EE contributes to adaptive thermogenesis during energy restriction; this may stem from decreased SNS drive to skeletal muscle, increasing locomotor efficiency and reducing skeletal muscle thermogenesis. The capacity to increase activity

EE in response to central MC4R activation is retained, however, presenting a potential target for pharmacotherapy intervention.

TABLE OF CONTENTS

Page

Appendix 1: List of Figures………………………………...…….…………………….viii

Appendix 2: List of Tables…………………………………...…………………..………x

Appendix 3: List of Abbreviations ………………………………………………….…...xi

Acknowledgements……………………………………...………………………………xiv

: Introduction ...... 1

Obesity ...... 1

Energy expenditure and adaptive thermogenesis ...... 3

Melanocortin system ...... 6

Melanocortin receptors ...... 7

POMC and AgRP neuron regulation ...... 11

MC-hypothalamic regulation of energy balance ...... 12

Arcuate nucleus (ARC) ...... 14

Ventromedial hypothalamus (VMH) ...... 15

Other hypothalamic regions ...... 18

Melanocortin 4 receptors ...... 20

Melanocortin-4 receptor (MC4R) deficiency in human obesity ...... 23

Autonomic nervous system and energy balance ...... 26

Sympathetic nervous system-MC4R regulation ...... 28

Rat model ...... 30

Aims ...... 30

: MC4R loss of function in rats...... 32

Study 1: MC4R loss-of-function affects body weight, lean and fat mass, food

intake, physical activity, respiratory exchange ratio (RER), and EE...... 35

Methods...... 35

Results ...... 38

Study 2: Calorie restriction in MC4R loss-of-function rats...... 43

Methods...... 43

Results ...... 44

Study 3: The effect of MC4R loss-of-function on molecular pathways supporting

metabolism in skeletal muscle and brown adipose tissue (BAT) ...... 49

Experimental Methods ...... 52

Results ...... 54

Discussion ...... 56

: Long-term calorie restriction induces adaptive thermogenesis in different components of energy expenditure ...... 63

Methods ...... 65

Results ...... 71

Discussion ...... 79

: Long-term calorie restriction reduces sympathetic nervous system outflow to skeletal muscle ...... 82

Experimental design ...... 85

Results ...... 89

Discussion ...... 91

: The ability of VMH-MC4R signaling to increase activity EE with long- term calorie restriction ...... 94

Methods ...... 96

Results ...... 99

Discussion ...... 103

: General discussion ...... 107

Future perspectives ...... 112

References ...... 115

vii

Appendix 1: List of Figures

Figure 1: Components of total daily energy expenditure (TDEE) in humans and rats...... 5

Figure 2: The leptin-melanocortin system and regulation of food intake and energy

expenditure...... 13

Figure 3 : Illustration of a coronal section of a rat brain...... 17

Figure 4: Rat brain regions involved in energy homeostasis...... 21

Figure 5: The structure of MC4R...... 22

Figure 6: The five molecular classifications of the MC4R mutants...... 25

Figure 7 : The central melanocortin system decreases parasympathetic (PSNS) and

increases sympathetic (SNS) outflow...... 29

Figure 8: Effects of MC4R deletion on body weight, body composition, food intake, and

spontaneous physical activity...... 39

Figure 9 : Effects of MC4R deletion on 24-hr energy expenditure (EE) and activity EE,

and also 24-hr and activity-related respiratory exchange ratio (RER)...... 41

Figure 10: Weight loss during 50% food restriction in rats homozygous (HOM) or

heterozygous (HET) for the non-functional melanocortin 4 receptor (MC4R),

compared to wild-type rats (WT)...... 47

Figure 11: 21 days of 50% calorie restriction (CR) significantly suppressed both resting

and non-resting energy expenditure (EE)...... 73

viii

Figure 12: 50% CR also significantly decrease both 24-hr RER (A) and spontaneous

physical activity ...... 74

Figure 13 : When physical activity was controlled using a treadmill, there was a

significant suppression in energy expenditure after 21 days of 50% CR...... 75

Figure 14 : Activity-induced muscle thermogenesis and calorie restriction (CR)...... 78

Figure 15: Timeline injection of aMPT ...... 88

Figure 16: 21 days of 50% daily calorie restriction (CR) significantly suppressed skeletal

muscle norepinephrine turnover (NETO), and indicator of sympathetic nervous

system drive...... 90

Figure 17 : Ventromedial hypothalamus (VMH) microinjection site...... 97

Figure 18: 50% daily calorie restriction (CR) did not significantly change the effect of

ventromedial hypothalamic (VMH) melanocortin 4 receptor (MC4R) activation on

enhancement of activity energy expenditure in rats...... 102

Appendix 2: List of Tables

Table 1: Melanocortin receptor (MCR) subtypes and their functions...... 10

Table 2 : Body composition and calorimetry measures from measurement of 24-hr

energy expenditure (EE), and activity EE (treadmill test); Rats homozygous (HOM)

or heterozygous (HET) for non-functional melanocortin 4 receptor (MC4R), or wild-

type rats (WT)...... 42

Table 3: Body weight and composition before and after 21 days of 50% calorie

restriction (CR), and after 14 days of ad libitum recovery from CR ...... 48

Table 4: Quantitative PCR analysis and protein expression of medial gastrocnemius

(gastroc) and quadriceps femoris (quads)...... 55

Table 5: Graded treadmill test ...... 69

Table 6: Changes in body composition, energy expenditure, and physical activity after 21

...... 72

Table 7: The melanocortin 4 receptor (MC4R) agonist induced changes in gas exchange

before and after 21 days of 50% calorie restriction (CR)...... 101

Appendix 3: List of Abbreviations

50% calorie restriction ------50% CR

Adrenocorticotropic hormone ------ACTH

Agouti-related protein ------AgRP

Arcuate nucleus of the hypothalamus ------ARC

Analysis of covariance ------ANCOVA

Analysis of variance ------ANOVA

+ ATP-sensitive potassium channels------K ATP

Brown adipose tissue ------BAT

Basal metabolic rate ------BMR

Body mass index ------BMI

Brain-derived neurotrophic factor ------BDNF

Central nervous system ------CNS

Cocaine- and amphetamine-regulated transcript ------CART

Calorie restriction (figures and tables only) ------CR

Dihydroxybenzylamine------DHBA

Dorsomedial hypothalamus ------DMH

Energy expenditure ------EE

Epididymal white adipose tissue------EWAT

Glyceraldehyde phosphate dehydrogenase ------GAPDH

Heterozygous for mutant MC4R allele------HET

Homozygous for mutant MC4R allele------HOM

Lateral gastrocnemius------Lateral gastroc

Lateral hypothalamus ------LH

Medial gastrocnemius ------Med gastroc

Mediator of RNA polymerase II transcription subunit 1------MED1

Melanocortin 3 receptor------MC3R

Melanocortin 4 receptor------MC4R

Melanocortin 5 receptor------MC5R

Melanocortin------MC

Melanotan II ------MTII

α-Melanocyte stimulating hormone ------α-MSH

α-methyl-p-tyrosine------aMPT

Neuropeptide Y ------NPY

Norepinephrine turnover------NETO

Norepinephrine------NE

Non-exercise activity thermogenesis ------NEAT

Nucleus of the solitary tract ------NTS

Parasympathetic nervous system ------PSNS

Paraventricular nucleus ------PVN

Proopiomelanocortin ------POMC

Quadriceps ------Quads

Respiratory exchange ratio ------RER

xii

Respiratory quotient ------RQ

Sprague–Dawley ------SD

Sympathetic nervous system ------SNS

Thermic effect of food ------TEF

Total daily energy expenditure ------TDEE

Ventromedial hypothalamus ------VMH

Wild type ------WT

xiii

ACKNOWLEDGEMENTS

I would like to express my deepest gratitude to my advisor Dr. Colleen Novak, for the continuous support of my PhD study and research and encouragement throughout my graduate study. I have been amazingly fortunate to have an advisor who gave me the freedom to explore on my own and at the same time the guidance to recover when my steps faltered. Her guidance helped me in all the time of research and writing of this dissertation. I am grateful for the time she spent on me from the beginning to the end. I hope that one day I would become as good an advisor to my students as Dr Novak has been to me.

Besides my advisor, I’m deeply grateful to my committee members, Dr. Eric

Mintz, Dr. Gary Koski, and Dr. Jacob Barkley for their encouragement, support, and guidance throughout my graduate study.

I’m also grateful to my lab mates, Chaitanya, Sromona, Charu, and Mark for their help, feedback, and productive discussions during our lab meetings. Special thanks to

Lydia for providing a perfect environment to work and helping me to learn new techniques for my molecular studies.

Last but not least, I would like to thank my wife Sumayyah Alsaqabia, for her support, patience, and enthusiasm as she is always the vital reason for me to accomplish my PhD. To my wonderful parents, I also would like to thank my father, Ibrahim

Almundarij, my mother Al Johara Al seef, and my grandmother, Meznah Al Saqabi for their encouragement and support. Beside my parents, I would like to thank my uncle

xiv

Abdulaiziz Almundarij for his support and encouragement throughout my undergraduate study. My gratitude is extended to my daughter, Remas, and my sons Ibrahim and Khalid for their patience throughout my PhD study.

: Introduction

Obesity

Obesity is one of the most common health problems in developed countries (Leibel,

Rosenbaum, & Hirsch, 1995; Moghimi-Dehkordi et al., 2013). The prevalence of obesity around the world has increased in recent years. Obesity results from an imbalance between food intake and energy expenditure and is defined in humans by body mass index (BMI) (Romero-Corral et al., 2008). Human obesity is subdivided into three

2 categories based on BMI, used as an indication of body fat, moderate Class I: 30 kg/m ≤

2 2 BMI < 35 kg/m , severe Class II: 35 kg/m2 ≤ BMI < 40 kg/m , and morbid Class III:

BMI ≥ 40 kg/m2 (Lehnert, Sonntag, Konnopka, Riedel-Heller, & Konig, 2013). High

BMI is associated with increased risk of a multitude of diseases, including high blood pressure, high blood cholesterol, heart disease, type 2 diabetes, and many forms of cancer, as well as higher mortality (Farooqi & O'Rahilly, 2008; Flegal, Graubard,

Williamson, & Gail, 2005; Flegal, Kit, Orpana, & Graubard, 2013; Fontaine, Redden,

Wang, Westfall, & Allison, 2003; Ogden, Carroll, Kit, & Flegal, 2012; Visscher et al.,

2004). Since a high BMI increases the risk of serious disease, high BMI is also associated with increased healthcare services and cost. In the U.S. healthcare spending was estimated to reach around 190 billion USD in association with obesity and obesity-related diseases (Lehnert et al., 2013). In 2005, the U.S. spent around 20% of its healthcare cost 1

on obesity and obesity-related issues (Cawley & Meyerhoefer, 2012; Lehnert et al.,

2013).

A Western diet and sedentary lifestyle are the most important environmental factors that contribute to obesity (Brown et al., 2004). There are many other factors that may increase the likelihood of obesity, including genetic factors, physical activity, and a person’s total daily energy expenditure (TDEE), all potentially contributing to weight gain. Under normal conditions, the most important determinants of TDEE are body weight and body composition, with smaller contributions made by age, sex, and race

(Schoeller, 1998; Shetty, 2005). Essentially, more energy expenditure (EE) is required to support a larger individual because they have more body weight to support and to move around. There is little unaccounted-for variance in TDEE under normal conditions. Under conditions of energy restriction, on the other hand, minor differences in TDEE and response to energy restriction can have a more meaningful impact on energy balance due to reduction in body weight and body composition (Reinhardt et al., 2015; Schoeller,

1998). Thus, there is a need to understand physiological and genetic factors favoring energy conservation and their interaction with an obesogenic environment which can alter TDEE, directly influencing weight gain or weight loss in association with obesity propensity.

Energy expenditure and adaptive thermogenesis

An individual’s TDEE consists of resting energy expenditure (REE) which roughly corresponds to basal metabolic rate (BMR), and non-resting energy expenditure (NREE).

The largest component of TDEE is BMR, which accounts for about 60% of TDEE in humans, and represents the energy needed to sustain vital functions such as breathing and circulation (Donahoo, Levine, & Melanson, 2004). Non-resting EE can be sub-divided into thermic effect of food (TEF), accounting for 10% of TDEE, and activity EE, accounting for about 30% of TDEE. Activity EE can be further sub-divided into exercise activity thermogenesis and non-exercise activity thermogenesis (NEAT), which is a person’s daily activity such as walking and standing, as shown in Figure 1 (Leibel et al.,

1995; Novak & Levine, 2007; Trexler, Smith-Ryan, & Norton, 2014). While reduced

BMR is not consistently related to obesity or obesity propensity, non-resting EE is directly related to the development of positive energy balance and accruing fat (Levine,

Eberhardt, & Jensen, 1999). Non-resting EE varies between individuals, and those who show high non-resting EE are prone to be lean compared to those who show lower non- resting EE in an obesogenic environment (Levine, 2002; Tou & Wade, 2002).

A person or animal gains weight when they consume more energy than they expend, while they lose weight when energy intake is lower than EE. TDEE correlates with body weight and body composition. In general, EE increases as body weight and lean and fat mass increase. As you might expect, EE decreases with weight loss, along with the loss of total mass and lean mass (Leibel et al., 1995). In addition, further

suppression of EE is often seen during weight loss. This phenomenon is called adaptive thermogenesis. With respect to weight loss and calorie restriction, adaptive thermogenesis is the decrease in EE beyond what is predicted from the reduction in body weight and body composition (Major, Doucet, Trayhurn, Astrup, & Tremblay, 2007;

Rosenbaum, Hirsch, Gallagher, & Leibel, 2008; Tremblay, Royer, Chaput, & Doucet,

2013).

Adaptive thermogenesis promotes survival during prolonged food shortage, protecting energy stores from further depletion. Adaptive thermogenesis is a good predictor to obesity treatment in that people who tend to lose more weight have less adaptive thermogenesis (Reinhardt et al., 2015; Rosenbaum & Leibel, 2010; Tremblay et al.,

2013). Adaptive thermogenesis varies among individuals, and it relies on three factors: metabolic condition (lean vs obese), autonomic nervous system outflow, and the neuroendocrine system (Rosenbaum & Leibel, 2010). One potential factor regulating adaptive thermogenesis is the brain melanocortin 4 receptor (MC4R). Energy balance hormones such as leptin act in part through the brain melanocortin system to regulate energy balance (Schwartz et al., 1997; Seeley et al., 1997), and to impact autonomic nervous system outflow (Rahmouni, Haynes, Morgan, & Mark, 2003; Sohn et al., 2013), making this system a good candidate to regulate adaptive thermogenesis.

Figure 1: Components of total daily energy expenditure (TDEE) in humans and rats (Novak & Levine, 2007). BMR, basal metabolic rate;

EEA, energy expenditure of activity; EAT, activity thermogenesis; NEAT, non-exercise activity thermogenesis; TEF, thermic effect of food; REE, resting energy expenditure; NREE, non-resting energy expenditure.

Melanocortin system

The melanocortin system consists of melanocortin agonist and antagonist/inverse agonist peptides. The agonist peptides include alpha, beta, and gamma melanocyte- stimulating hormone (α-MSH, β-MSH, γ-MSH) and adrenocorticotropic hormone

(ACTH) (Gantz & Fong, 2003; Tao, 2010). These peptides have different affinities for the different receptor subtypes (Gantz & Fong, 2003). The antagonist and inverse agonist peptides are agouti and agouti-related peptide (AgRP)(Corander, Fenech, & Coll, 2009;

Mizuno & Mobbs, 1999; Tao, 2010; Varela & Horvath, 2012). The melanocortin peptides are synthesized from pro-opiomelanocortin (POMC) which is prohormone precursor protein that is synthesized and expressed in several tissues including the pituitary gland, arcuate nucleus of hypothalamus (ARC), nucleus of the solitary tract (NTS), as well as in several peripheral tissues (Wardlaw, 2011). POMC is cleaved into peptides including

MSH, ACTH, and β-endophin. These peptides have different physiological functions ranging from pigmentation to adrenal stimulation to homeostatic regulation (Coll,

Farooqi, Challis, Yeo, & O'Rahilly, 2004; Millington, 2007; Pritchard, Turnbull, &

White, 2002; Wardlaw, 2011).

Arcuate POMC neurons play a critical role in the regulation energy homeostasis through the release of POMC-derived peptides, particularly α-MSH, which then binds to melanocortin receptors. These POMC-derived peptides decrease food intake and increase energy expenditure and physical activity (Pritchard et al., 2002). POMC overexpression

protects mice from obesity, while neural POMC deletion leads to obesity (Wardlaw,

2011; Yaswen, Diehl, Brennan, & Hochgeschwender, 1999).

Another important member of melanocortin system which also plays a physiological role in the regulation energy balance in the ARC is AgRP. AgRP is considered to be an antagonist and an inverse agonist of the melanocortin receptors. In other words, AgRP acts on the MC receptor to reduce the activity the downstream intracellular signaling cascades (Haskell-Luevano & Monck, 2001; Low, 2011;

Nijenhuis, Oosterom, & Adan, 2001). Like neurons synthesizing melanocortin peptides,

AgRP neurons are also found in the arcuate nucleus of the hypothalamus, a separate population of neurons from POMC neurons, and where POMC neurons suppress appetite and increase EE, AgRP neurons have orexigenic effects. It has been shown that deletion

AgRP neurons in the ARC in mice causes starvation, while AgRP overexpression increases food intake (de Backer et al., 2011; Gropp et al., 2005; Luquet, Perez, Hnasko,

& Palmiter, 2005; Mizuno & Mobbs, 1999; Varela & Horvath, 2012). Therefore, both

POMC and AgRP neurons regulate energy balance through the actions of peptides on

MC receptors.

Melanocortin receptors

There are five melanocortin receptors, numbered MC1R to MC5R, each having different function throughout the body. The MC1R is considered the classical MSH

receptor and is located in cutaneous melanocytes, keratinocytes, fibroblasts, and endothelial cells where it plays a critical role in pigmentation (Gantz & Fong, 2003). In addition to those cells, MC1R is also expressed in leukocytes, where it has anti- inflammatory effects. This type of receptor has a high affinity for α-MSH (Gantz & Fong,

2003). The MC2R is found in cells of the zona reticularis and zona fasiculata of the adrenal cortex and acts as the adrenocortical ACTH receptor. This receptor plays a key role in steroidogenesis. In addition to the adrenal cortex, MC2R is also expressed in adipose tissues in mice and humans where it plays a role in lipolysis in mice, but the function in humans is not yet clear. MC2R is bound only by ACTH and has no affinity for the other melanocortin peptides (Gantz & Fong, 2003).

MC3R, MC4R, and MC5R are the melanocortin receptors present in the adult mammalian brain, and each impacts energy balance. Mutations in both MC3R and MC4R have been associated with human obesity (Butler et al., 2000). MC3R is also expressed in peripheral tissues including the gastrointestinal tract and placenta (Gantz & Fong, 2003).

MC3R has a high affinity for γ-MSH, while MC4R has a high affinity for α-MSH(Gantz

& Fong, 2003). Data from knockout mice deficient in MC3R show that deletion of this receptor results in an increased adiposity and reduced energy expenditure (Butler et al.,

2000; Mencarelli et al., 2008; Renquist et al., 2012), similar to mice lacking MC4R

(Huszar et al., 1997). Lastly, MC5R is expressed in human peripheral tissues such as adrenal gland, adipocytes, and leukocytes. MC5R is known to regulate sebaceous gland secretion (Gantz & Fong, 2003). It is also expressed in the central nervous system.

Although MC5R has a limited distribution in the brain, regional differences in expression levels have been seen in lean compared to obesity-prone rats (Shukla, Britton, Koch, &

Novak, 2012), and variants of MC5R have been seen in association with human obesity

(Chagnon et al., 1997).

Table 1: Melanocortin receptor (MCR) subtypes and their functions (Adan et al., 2006;

Gantz & Fong, 2003).

Receptor Agonist Antagonist Function subtype (primary) /inverse agonist

Pigmentation, MC1R α-MSH Agouti anti-inflammatory

MC2R ACTH Agouti Adrenal steroidogenesis

MC3R γ-MSH Agouti/AGRP Energy homeostasis

MC4R α-MSH Agouti/AGRP Energy homeostasis

MC5R α-MSH Agouti Exocrine gland secretion

POMC and AgRP neuron regulation

Arcuate POMC and AgRP neurons are part of one brain pathway important in the central actions of the well-known hormone leptin, which offers an example of how this system functions during calorie restriction and positive energy balance. Leptin is a protein released primarily from white adipose tissue, which plays an important role in regulation of energy homeostasis (Choi et al., 2008; Mistry, Swick, & Romsos, 1997;

Schwartz et al., 1997). Once leptin is secreted into the circulation, it acts on the ARC and binds to its receptors (Ob-Rb) (Shimizu, Inoue, & Mori, 2007). As mentioned above, within the ARC, there are two separate cell populations that are highly responsive to leptin. One cell type contains POMC and cocaine-and amphetamine-regulated transcript

CART (anorexigenic), while the other has neuropeptide Y (NPY) and AgRP (orexigenic)

.(Schwartz et al., 1997); both POMC/CART and AgRP/NPY regulate food intake and energy expenditure (Gautron & Elmquist, 2011). For example, during the fed state, increased circulating insulin and leptin levels stimulate synthesis of the POMC precursor, leading to increased release of α-MSH, which then binds MC4R in regions including the

PVN, inducing satiety. In addition, in the fed state, activation of insulin and leptin receptors on the orexigenic neurons will inhibit AgRP release. The reciprocal actions of

AgRP and MC peptides during the fed state will decrease food intake and increase energy expenditure. On the other hand, in states of negative energy balance such as calorie restriction, a decrease in circulating insulin and leptin suppresses synthesis of the POMC precursor, while increasing activation of the opposing AgRP/NPY neurons (Mizuno et

al., 1998). Consequently, AgRP expression and release are increased, which leads to inhibition of MC4R signaling in the PVN and other brain regions, also increasing availability of MC4R as long-term changes in melanocortin release can alter the availability of MC4R (e.g., through up-regulation) (Harrold, Widdowson, & Williams,

1999). As a result, food intake increases and energy expenditure is reduced (Figure 2)

(Corander et al., 2009).

MC-hypothalamic regulation of energy balance

The regulation of energy balance in the brain is complex, with multiple, redundant homeostatic and non-homeostatic (e.g., reward, sensory, cognitive) factors influenced by energy balance cues and contributing to appetite. The non-homeostatic cues are mainly processed in cortico-limbic structures including the prefrontal cortex and the ventral striatum (Berthoud, 2006). The non-homeostatic processing represents interactions with environmental factors including food reward and emotion which can ultimately lead to obesity (Berthoud, 2006). Since this dissertation mainly focuses in a physiological response, I will focus on the hypothalamus and homeostatic regulation of energy balance, where MC peptides primarily exert their influences. Regions important for these homeostatic processes include the ARC, the paraventricular nucleus of hypothalamus

(PVN), ventromedial hypothalamus (VMH), lateral hypothalamus (LH), and dorsomedial nucleus of hypothalamus (DMH) (Figure 4) (Berthoud, 2006).

Figure 2: The leptin-melanocortin system and regulation of food intake and energy expenditure though leptin triggering of POMC neurons to produce α-

MSH and inhibition of AgRP (Barsh & Schwartz, 2002). Copyright permission from Nature Publishing Group.

Arcuate nucleus (ARC)

As mentioned above, there are two separate cells populations in the ARC which regulate energy balance and are responsive to energy-balance cues, one cell type contains

POMC and CART (anorexigenic), while the other is characterized by neuropeptide Y

(NPY) and AgRP (orexigenic) (Dhillo et al., 2002; Schwartz et al., 1997). Genetic deletion of arcuate POMC or overexpressions of arcuate AgRP both lead to obesity, while POMC overexpression and AgRP deletion prevent obesity in laboratory animals

(Greenman et al., 2013; Gropp et al., 2005; Wardlaw, 2011). Additionally, ARC lesions also lead to obesity in rodents (McNay, Briançon, Kokoeva, Maratos-Flier, & Flier, 2012;

Olney, 1969). Furthermore, both of these neuron types are sensitive to peripheral circulating fuels include glucose and fatty acid as well as hormone levels, for example injection of leptin directly into the ARC induces anorexigenic responses (Bjørbæk, 2009;

Chari, Lam, & Lam, 2010), while intracerebroventricular (ICV) administration of ghrelin, and ghrelin actions on ARC AgRP neurons, activate orexigenic responses (Nakazato et al., 2001; Q. Wang et al., 2014). These neuronal populations (POMC/CART and

NPY/AgRP neurons) send projections to other hypothalamic nuclei including the PVN,

VMH, LH, and DMH (Hakansson, Brown, Ghilardi, Skoda, & Meister, 1998;

Schneeberger, Gomis, & Claret, 2014). The consensus is that the ARC plays a critical role in the integration of signals that control of energy homeostasis.

Ventromedial hypothalamus (VMH)

There is now ample evidence that the VMH plays important roles in glucose homeostasis, lipolysis, autonomic nervous system regulation, and the regulation of respiratory exchange ratio (RER; similar to respiratory quotient, RQ) (K. W. Kim et al.,

2011; King, 2006; Lindberg, Chen, & Li, 2013; Miyaki et al., 2011; Takahashi &

Shimazu, 1981; Toda et al., 2009). The VMH was once described as the “satiety center”

(Abizaid, Gao, & Horvath, 2006; King, 2006). VMH lesions increase food intake and promote the development of obesity (Grundmann et al., 2005; Satoh et al., 1997). The

VMH receives projections from first-order neurons (ARC) (Millington, Tung, Hewson,

O'Rahilly, & Dickson, 2001). The VMH cells also express MC3/4R and once MC3/4R are stimulated in VMH, food intake decreases and EE increases (Abizaid et al., 2006). In addition to that, the VMH also expresses brain-derived neurotrophic factor (BDNF) which is known to regulate energy balance, for example deletion of BDNF neurons in

VMH results in obesity (Unger, Calderon, Bradley, Sena-Esteves, & Rios, 2007; C.

Wang, Bomberg, Billington, Levine, & Kotz, 2010; Xu et al., 2003). Furthermore, microinjections of the MC3/4R agonist α-MSH or a nonspecific MC3/4R agonist

(Melanotan II, MTII) into the VMH increase glucose uptake in peripheral tissues including skeletal muscles, heart, and brown adipose tissue (BAT). On the other hand, microinjection of the MC3/4R antagonist SHU9119 opposes the actions of MTII and also increases adiposity as well (Toda et al., 2009). Taken together, these finding indicate that

the VMH plays a critical role in energy homeostasis beyond simply acting as a “satiety center.”

Figure 3 : Illustration of a coronal section of a rat brain. Highlighted showing ventromedial hypothalamus (VMH). Adapted from The rat brain in stereotaxic coordinates (Watson).

Other hypothalamic regions

Another region in hypothalamus which regulates energy homoeostasis is the paraventricular nucleus of hypothalamus (PVN), located on either side of the 3rd ventricle. The PVN consists of two major subregions, magnocellular (large cell) and parvocellular (small cell) (Hill, 2012). The parvocellular region produces peptides including cortocotropin-releasing hormone (CRH) and thyrotropin-releasing hormones

(TRH). These peptides are known to have anorexigenic effects (Valassi, Scacchi, &

Cavagnini, 2008). Additionally, the parvocellular region also modulates the autonomic nervous system by sending projections to nucleus of the solitary tract (NTS), the parasympathetic preganglionic neuron region known as the dorsal motor nucleus of the vagus (DMV), and the sympathetic preganglionic intermediolateral cell column (IML) of the spinal cord (Hill, 2012). Both the magnocellular and parvocellular regions express melanocortin receptors including MC3R and MC4R (Ghamari-Langroudi, Srisai, &

Cone, 2011; Hill, 2012). The PVN receives a strong projection from ARC neurons

(Cowley et al., 1999), and this projection is commonly used as the exemplar modulator of the “anorexigenic” arm of the homeostatic process where, once peripheral hormones such as leptin induce ARC POMC/CART neurons to release α-MSH, α-MSH binds to MC3R or MC4R receptors in the PVN, resulting in decreased food intake and increased energy expenditure. PVN lesions and genetic deletion of MC3/4R in PVN result in obesity

(Ghamari-Langroudi et al., 2011; Weingarten, Chang, & McDonald, 1985). Moreover, injection of the nonspecific melanocortin agonist MTII into the PVN leads to decreased

food intake (Giraudo, Billington, & Levine, 1998). In addition, re-expression of PVN-

MC4R in MC4R knock-out mice enhanced the obese phenotype by ≈60%, while viral vector-induced reduction in MC4R expression in the PVN resulted in obesity in rats

(Balthasar et al., 2005; Garza, Kim, Liu, Zhang, & Lu, 2008).

As described above, the VMH was conceptualized as a satiety center because lesions of the VMH caused obesity (“VMH obesity”). Conversely, lesions of the lateral hypothalamus (LH) had the opposite effect, inducing hypophagia and reducing body weight (Bernardis & Bellinger, 1993; Corbett & Keesey, 1982). Therefore, the LH was conceptualized as the hunger center (Abizaid et al., 2006). The LH receives afferent input from the ARC POMC and AgRP neurons, and the LH also expresses MC4R. As a result, pharmacological inhibition of MC4R does not change food intake, but AgRP overexpression in the LH causes hyperphagia (Cui et al., 2012). Several neuropeptides present in the LH, including melanin-concentrating hormone, neurotensin, and especially hypocretin (orexin), impact energy balance. Orexin peptides are known to increase both food intake and EE (Novak & Levine, 2007), and microinjections of orexin into the LH increase food intake (Dube, Kalra, & Kalra, 1999). Orexin cells project to multiple regions including the PVN and ARC, and microinjections of orexin in those areas stimulate food intake and increase EE (Novak & Levine, 2009).

The dorsomedial hypothalamus (DMH) is involved in controlling energy balance.

Lesions of the DMH result in hypophagia (Aravich & Sclafani, 1983; Zheng, Kim, Chao,

& Bi, 2013). It has been shown that both DMH and ARC highly express neuropeptide Y

which is known to have orexigenic effects (Yang et al., 2009; Zheng et al., 2013).

Consequently, overexpression of NPY in the DMH causes hyperphagia and increases

BMI in rats (Zheng et al., 2013), while knockdown of NPY in the DMH protects rats from obesity (Yang et al., 2009). These nuclei are all interconnected, for example both the DMH and ARC send projections to the PVN (Bi, Robinson, & Moran, 2003). In addition to NPY, the DMH also expresses MC4R, and genetic deletion of MCR4 in the

DMH in mice increases expression of DMH NPY (M. S. Kim et al., 2000).

Melanocortin 4 receptors

MC4R is one of a family of G protein-coupled receptors, known to have seven transmembrane domains, three intracellular loops, and three extracellular loops. Once α-

MSH binds to this G protein-coupled receptor (MC4R), it activates stimulatory G proteins (Gs), which increases the second messenger cyclic adenosine monophosphate

(cAMP) and activate adenylyl cyclase (AC), (Mountjoy, 2015) increasing protein kinase

A (PKA) activity. In addition, MC4R acts through the Gq/phospholipase C (PLC) signal pathway to increase intracellular calcium levels (Figure 5) (Farooqi & O'Rahilly, 2008;

Logan & Pepper, 2010; Mountjoy, 2015).

Figure 4: Rat brain regions involved in energy homeostasis (Barsh & Schwartz,

2002), with copyright permission from Nature Publishing Group.

Figure 5: The structure of MC4R (Farooqi & O'Rahilly, 2008).

Melanocortin 4 receptor is widely expressed in the brain, particularly in the thalamus, hypothalamus, hippocampus, brainstem, and spinal cord. Within the hypothalamus,

MC4R is highly expressed in the PVN, VMH, DMH, and LH (Fu & van den Pol, 2008;

Girardet & Butler, 2014; Tao, 2010; Toda et al., 2009). As mentioned above, the primary role of MC4R in those areas of hypothalamus is to regulate energy homeostasis.

Pharmacological administration of AgRP into PVN significantly increases food intake for around 24 hours and inhibits the actions of α-MSH (Tao, 2010). Cone and colleagues

(1997) used ICV administration of MTII, an analog of α-MSH and a mixed MCR3/4/5 agonist, in four different models of obese mice (Fan, Boston, Kesterson, Hruby, & Cone,

1997). They demonstrated that MTII decreases the hyperphagia in obese mice, while coadministration of SHU9119, an antagonist of MC3/4R, opposes the actions of MTII

(Tao, 2010). This led them to conclude that AgRP acts as an inverse agonist, opposing the functional actions of α-MSH on MC4R (Fan et al., 1997), while α-MSH is the primary ligand for MC4R (Tao, 2010). Taken together, these findings from pharmacological studies implicate MC receptors and their endogenous ligands in the homeostatic control of energy balance and thus the response to food restriction.

Melanocortin-4 receptor (MC4R) deficiency in human obesity

MC4R deficiency is one of the most common monogenic causes of human obesity, in other words, a single defect altering the function of the MC4R gene can lead to obesity (Mul, van Boxtel, et al., 2012). The prevalence of MC4R mutations depends on

ethnic background (Tao, 2010). For example, in British Caucasians, up to 6% of early- onset morbidly obese individuals have MC4R mutations (Tao, 2010). On the other hand,

0% of obese Belgians, including children and adults, have mutations in MC4R. In

Germany, 1.9% of obese children and adolescents have mutations in MC4R. Lastly, in

North America, 2.3% of obese people have mutations in MC4R (Tao, 2010). However, mutation in a single gene that causes obesity is rare, and targets of monogenic mutations including leptin, leptin receptors, POMC, and MC4R together represent only ≤5% of severe obesity. Obesity risk tends to be more affected by many genes (polygenic rather than monogenic) (Choquet & Meyre, 2011; Hinney & Hebebrand, 2008; Hinney, Vogel,

& Hebebrand, 2010).

There are five classifications of mutations in MC4R:

Class I: Null mutation: This type of mutation occurs when protein synthesis is defective or degenerated, and as a result, the receptor protein levels are decreased (Tao, 2010).

Class II: Intracellularly trapped mutants: The mutant receptors are produced but are retained intracellularly, specifically in the endoplasmic reticulum. This type of mutation occurs due to misfolding, detected by the cell’s quality control system. This class has been reported as the largest of MC4R mutations (Tao, 2010).

Class III: Binding defective mutants: This type of mutation occurs on cell surface with a decreased binding affinity. As a result, the signal is impaired (Tao, 2010).

Class IV: Signaling defective mutants: Defect in signal transduction (Tao, 2010).

Class V: Variants with unknown defects (Tao, 2010).

Figure 6: The five molecular classifications of the MC4R mutants (Tao,

2005, 2010). Copyright permission from Elsevier.

Autonomic nervous system and energy balance

The autonomic nervous system consists of two divisions, the sympathetic nervous system (SNS) and parasympathetic nervous system (PSNS). The physiological function of the SNS is to regulate “fight and flight” responses in addition to homeostatic regulatory functioning, while PSNS controls “rest and digest”(McCorry, 2007). Many tissues are innervated by both SNS and PSNS but these systems tend to oppose each other’s functions (Tentolouris, Liatis, & Katsilambros, 2006). In other words, each system is dominant under certain conditions, while the other is inhibited. For example during physical activity or emergency situations, the SNS will be dominant to increase blood flow to skeletal muscle and decrease flow to the gastrointestinal tract while increasing heart rate and respiration. In contrast, the PSNS will be dominant during rest and digestion to promote energy storage (McCorry, 2007). Both SNS and PSNS contain two main neurons, preganglionic neurons which secrete acetylcholine to activate cholinergic receptors, and postganglionic neurons. The SNS postganglionic neurons release primarily norepinephrine which binds to adrenergic receptors including subtypes

1, 2, 1, 2, and 3 to exert its actions. Most PSNS postganglionic neurons release acetylcholine (McCorry, 2007). Lastly, in addition to sympathetic postganglionic norepinephrine neurotransmitter release, stimulation of the adrenal medulla cells will result in systemic adrenalin secretion. This consists of 20% norepinephrine and 80% epinephrine (McCorry, 2007). The hypothalamus and brain melanocortin system are both important regulators autonomic control.

Within the hypothalamus, the VMH, PVN, and DMH influence the activity of the

SNS, while the LH influences primarily PSNS actions (Girardet & Butler, 2014;

Lindberg et al., 2013). Consequently, it has been shown that lesioning the VMH decreases sympathetic outflow, while LH lesions oppose the effect (Arase, Sakaguchi, &

Bray, 1987; King, 2006; Lindberg et al., 2013; Yoshida, Kemnitz, & Bray, 1983).

Hypothalamic administration of leptin and insulin also increase SNS activity (Snitker,

Macdonald, Ravussin, & Astrup, 2000). Metabolic conditions such as negative or positive energy balance can alter the activity of the SNS. In general, the autonomic nervous system opposes weight changes. During weight gain, SNS activity increases to raise TDEE, while during weight loss, PSNS activity increases and SNS activity lowers to attenuate TDEE (Arone, Mackintosh, Rosenbaum, Leibel, & Hirsch, 1995; Bray, 1992;

Messina et al., 2013; Schwartz, Baskin, Kaiyala, & Woods, 1999; Snitker et al., 2000;

Tataranni, Young, Bogardus, & Ravussin, 1997). One target of the SNS control of metabolism is skeletal muscle. Previous data from our laboratory have shown that microinjection of the mixed MC receptor agonist MTII into the VMH leads to increased

SNS outflow to skeletal muscle and increased muscle thermogenesis and activity-related

EE. Relatively little consideration is given to the potential role of SNS modulation of muscle to meaningfully impact EE.

Sympathetic nervous system-MC4R regulation

As mentioned above, central MC4R plays a critical role in controlling energy homeostasis, increasing energy expenditure and decreasing food intake (Butler, 2006;

Corander et al., 2009; Logan & Pepper, 2010; Mul, van Boxtel, et al., 2012; Seeley,

Drazen, & Clegg, 2004). Furthermore, MC4R has been shown to regulate the autonomic nervous system (Fan, Voss-Andreae, Cao, & Morrison, 2005; Girardet & Butler, 2014;

Sohn et al., 2013). Notably, MC4R is expressed in SNS preganglionic neurons in the

IML, and MC4R is also present in PSNS preganglionic neurons in the DMV. Direct activation of MC4R in these preganglionic neurons leads to activation of the SNS and inhibition of the PSNS (Berglund et al., 2014; Fan et al., 2005; Geerling et al., 2014;

Girardet & Butler, 2014; Sohn et al., 2013). Activation of sympathetic and suppression of parasympathetic outflow by MC4R both contribute to MC4R modulation of thermogenesis and other metabolic functions (Song et al., 2008). Given the response of brain melanocortins to negative energy balance (Breen, Conwell, & Wardlaw, 2005;

Harrold, Widdowson, et al., 1999; Harrold, Williams, & Widdowson, 1999), and its modulation of autonomic outflow, weight loss-induced to suppression of SNS activity may stem from decreased MC4R activation (Rosenbaum & Leibel, 2010). Consistent with this, obese individuals with MC4R mutations are not hypertensive, suggesting that they are resistant to the compensatory SNS responses associated with obesity, highlighting the relevance of MC4R in the regulation of the autonomic nervous system in humans (Girardet & Butler, 2014; Sohn et al., 2013).

Figure 7 : The central melanocortin system decreases parasympathetic (PSNS) and increases sympathetic (SNS) outflow

(Sohn et al., 2013). With copyright permission from Elsevier.

Rat model

In order to investigate the role of MC4R in energy balance and how MC4R affects body weight, I use rats deficient in functional MC4R, including rats homozygous (HOM) and heterozygous (HET) for the mutation, as well as wild-type (WT) rats (Mul, van

Boxtel, et al., 2012; Stepp, Osakwe, de Chantemele, & Mintz, 2013; Tallam, Stec, Willis, da Silva, & Hall, 2005). The HOM rats (loss of MC4R function) have severe early-onset obesity and are prone to have other associated metabolic and cardiovascular disorders

(Mul, van Boxtel, et al., 2012; Stepp, Osakwe, de Chantemele, et al., 2013; Tallam et al.,

2005). These rats act as an animal model of monogenic obesity and allow us to study the role of MC4R in energy expenditure during the fed state as well as the effect of negative energy balance (Mul, van Boxtel, et al., 2012; Stepp, Osakwe, de Chantemele, et al.,

2013; Tallam et al., 2005). Therefore, I used these rats to test the hypothesis that MC4R impacts body weight through its actions on energy expenditure.

Aims

In general, this dissertation contains four Aims. The first Aim focuses on MC4R- loss-of-function rats in free-fed conditions as well as in negative energy balance, and continues to examine the impact of MC4R loss of function on molecular pathways supporting metabolism in skeletal muscle and brown adipose tissue. The second and third

Aims investigate the impact of long-term calorie restriction and the contribution of different components of energy expenditure to adaptive thermogenesis, as well as changes in SNS outflow to skeletal muscle during calorie restriction. Lastly, Aim 4 30

focuses on intra VMH-MC4R activation during negative energy balance, testing the hypothesis that reduced responsiveness of the VMH to MC4R stimulation underlies the suppressed activity-related EE to muscle seen during energy restriction.

: MC4R loss of function in rats

Many redundant and overlapping systems serve to regulate energy balance homeostasis. Included in these is the brain melanocortin system. Melanocortin 4 receptor mutation or loss of function in humans is one of the few known monogenic causes of obesity (Beckers et al., 2010; Girardet & Butler, 2014; Meehan et al., 2006; Mencarelli et al., 2008; Mul, Begg, et al., 2012; Mul, Spruijt, Brakkee, & Adan, 2013; Mul, van Boxtel, et al., 2012). MC4R is also the target of numerous genetic variants that contribute to obesity in humans (Choquet & Meyre, 2011; Farooqi & O'Rahilly, 2008; Hinney &

Hebebrand, 2008; Hinney et al., 2010; Logan & Pepper, 2010; Meehan et al., 2006).

Activation of brain MC4R increases energy expenditure and decreases food intake, playing a critical role in controlling energy homeostasis (Butler, 2006; Corander et al.,

2009; Mul, van Boxtel, et al., 2012; Karen K. Ryan et al., 2014; Seeley et al., 2004).

MC4R functions in the brain to directly influence both appetite TDEE (Mul et al., 2013;

Mul, van Boxtel, et al., 2012; Skibicka & Grill, 2009). Rats losing functional MC4R are hyperphagic, obese, and prone to have leptin and insulin resistance, having higher levels of circulating leptin and insulin (Mul, Begg, et al., 2012; Mul, van Boxtel, et al., 2012).

Rats lacking functional MC4R are also normotensive despite their obesity, consistent with lower sympathetic tone (Stepp, Osakwe, Belin de Chantemele, & Mintz, 2013). The rats’ behavior is also different; these rats have a preference for a high-fat diet, and are less behaviorally responsive to a mixed melanocortin receptor agonist (Mul, van Boxtel, et al., 2012). It is possible that suppressed energy expenditure may contribute to the obese

phenotype seen in association with altered MC4R function in rats. In mice, there is a difference in feed efficiency (weight gain per kcal consumed) between wild-type (WT) and MC4R-knockout mice (Girardet & Butler, 2014), implying that EE might be lower in the knockout mice. Similarly, rats lacking functional MC4R show increased feed efficiency without any difference in absorption (Mul, Begg, et al., 2012; Mul, van Boxtel, et al., 2012). There is not yet any study measuring energy expenditure in these rats.

As described earlier, TDEE is composed of resting and non-resting EE. Once body weight is considered, the most variable part of EE between individuals is NEAT

(Donahoo et al., 2004; Levine, 2002; Levine et al., 1999). There is a negative correlation between physical activity level and body weight where lean people and lean animal tend to be more physically active (Novak & Levine, 2007). Also, individuals who show high

NEAT resist fat gain with positive energy balance, but those who fail to increase NEAT are likely to gain fat (Levine, 2002; Levine et al., 1999). While obesity has increased over the years, the amount of physical activity has also decreased (Archer et al., 2013; Joosen,

Gielen, Vlietinck, & Westerterp, 2005; Lanningham-Foster, Nysse, & Levine, 2003).

Though the specific contribution of lower non-resting EE to obesity propensity has been the cause of some controversy, it is clear that lean people show higher physical activity levels, and the ability to raise NEAT with increased caloric intake protects against fat gain (Johannsen, Welk, Sharp, & Flakoll, 2008; Levine et al., 1999; Levine et al., 2005).

Animal studies have revealed possible genes and neural pathways that may connect

genetic background to daily physical activity levels, and a lot of these point to the brain melanocortin system, especially MC4R (Mul, van Boxtel, et al., 2012).

The brain melanocortin system and MC4R in particular seems to make an important contribution to individual variation in obesity propensity, weight gain, and

TDEE particularly non-resting EE (Girardet & Butler, 2014; Shukla et al., 2012; Zegers,

Van Hul, Van Gaal, & Beckers, 2012). The development of a rat model that lacks functional MC4R lets us investigate the function of this receptor in energy balance and behavior in rats (Mul, Begg, et al., 2012; Mul et al., 2013; Mul, van Boxtel, et al., 2012;

K. K. Ryan et al., 2014). Lower levels of physical activity were observed in these rats in most cases (Mul, van Boxtel, et al., 2012). The potential contribution of decreased EE to the obese phenotype in the MC4R-deficient rats has not been directly investigated. Here,

I measured 24-hr EE as well spontaneous physical activity and activity EE in rats homozygous for the non-functional MC4R (HOM), and rats with one (HET) or two (WT) functional copies of the MC4R gene. In this case, mutation in the G protein-coupled receptor (MC4R) in rats was generated by inducing a premature stop codon in helix 8

(Mul, van Boxtel, et al., 2012).

In addition to EE and physical activity, molecular pathways important in cellular metabolism and fuel uptake and utilization were examined in skeletal muscle and BAT.

Lastly, I investigated the ability of food restriction to impact weight loss and adiposity in these rats.

Study 1: MC4R loss-of-function affects body weight, lean and fat mass, food

intake, physical activity, respiratory exchange ratio (RER), and EE.

Here, I examined 24-hour EE, spontaneous physical activity, and respiratory exchange ratio (RER, which is similar to the respiratory quotient, RQ; VCO2/VO2), adiposity, body weight, and food intake in male rats: WT (n=5), HET (n=8), and HOM

(n=8).

Methods

Animals

Adult male HOM, HET, and WT rats (n=8/group) (Mul, Begg, et al., 2012; Mul, van Boxtel, et al., 2012; Spradley, Palei, & Granger, 2013; Stepp, Osakwe, de

Chantemele, et al., 2013) were obtained from Taconic. Rats were housed on a 12:12 light:dark cycle with lights-on at 0700 (EST) and provided ad libitum access to water and

(before calorie restriction) to food (5P00 MRH 3000, T.R. Last Co. Inc). Animal protocols were approved by the Kent State University Institutional Animal Care and Use

Committee. Body weights were measured using as Denver Instruments XP-1500 balance.

Body composition measurement

Body composition was determined using an EchoMRI-700 (EchoMRI, Houston,

TX). This instrument measures fat and lean mass in grams (Nixon et al., 2010), and I then used these values in the analysis of EE.

Calorimetry

Before calorimetry measurements, rats were acclimated for 2 days in the calorimetry chamber and room. 24-hr energy expenditure was measured using a 4- chamber Oxymax FAST system (Columbus Instruments, Columbus, OH). Rats were weighed and placed into the calorimetry chamber with food and water. Measurements were ended at least 25 hours later, and the first hour of data were not included in the final analysis, which included physical activity and gas exchange data from 1200 on day 1 to

1200 on day 2, due to evidence that the animals might have been agitated or more active soon after they are placed in the chamber, and to allow the chamber air to settle. Energy expenditure was measured by the calorimeter at 30-sec intervals, and physical activity was measured at 10-sec intervals. Rats and food were weighed at the end of the calorimetry test. Genotype distribution to the 4 calorimetry chambers was randomized.

For analysis of 24-hr EE, 3 WT rats (of the original total of 8) were eliminated from this analysis because their date of birth was 3 weeks earlier than the other rats at the time of calorimetry and thus they were significantly larger than the rest of the WT rats at this time. Body weights among WT rats were not different in later experiments, however.

Energy expenditure during low levels of activity (treadmill walking) was measured using

an enclosed treadmill attached to the calorimeter. Before the day of the treadmill test, each rat was acclimated to the treadmill for 10 min. Rats were weighed and then placed into the treadmill and allowed to rest uninterrupted without access to food for 2 hrs while gas exchange data were collected; 2 hrs without food is likely to be sufficient to avoid the thermic effect of food from what little the rats may have eaten earlier to this time during the light phase of the cycle (Tremblay et al., 2013). However, thermic effect of food could not be quantified during the 24-hours EE measurement. Over the course of this 2 hrs, rats showed the expected pattern of behavior where physical activity and EE increased in the first few min then fell gradually, reaching a constant state. After this, the rats walked on the treadmill at 0° incline and 7 m/min for 30 min, during what time steady-state activity EE data were collected (Gavini et al., 2014). 1 WT and 2 HET rats were excluded from the analysis because they refused to walk.

Analyses and statistics

Energy expenditure data (kcal/hr) were analyzed using analysis of covariance

(ANCOVA), with body weight and lean mass as the covariates in separate analyses.

Activity and RER data collected during calorimetry were analyzed using a 1-way analysis of variance (ANOVA) with genotype as the independent variable and using the LSD test for post-hoc comparisons. For treadmill resting and walking gas exchange data, resting

EE, total EE during the 30-min activity bout, and activity EE (total - resting EE) were analyzed using ANCOVA.

Results

MC4R-deficient rats showed greatly enhanced adiposity, body weight, and food intake, and low levels of spontaneous physical activity

Table 2 details data the body composition data at the time of calorimetry. The extra body weight in HOM rats was mostly due to extra fat accumulation (Figure 8, Table

2). Also, I observed that MC4R loss of function resulted in hyperphagia and low levels of spontaneous physical activity.

Figure 8: Effects of MC4R deletion on body weight, body composition, food intake, and spontaneous physical activity. Compared to wild-type (WT) rats and rats heterozygous for the nutation (HET), rats homozygous for the mutation (HOM) rats showed greater body weight (A), fat mass (B), and lean mass (C). (D) HOM rats showed greater daily energy intake, but HET and WT rats did not differ from each other in food intake. (E) HOM rats were significantly less physically active than either WT or HET rats. *Significantly different from HOM rats, **significantly different from HET rats, p<0.05.

MC4R deletion impacted RER but not energy expenditure

As shown in Figure 9, 24-hr EE did not differ between genotypes when either total body weight or lean mass were was taken into account as covariates in separate analyses. Body weight and lean mass each accounted for a significant amount of variance in 24-hr EE. Without accounting for differences in mass, absolute total 24-hr EE was highest in the HOM rats, while VO2 (ml/kg/hr) was lowest, due to their much larger body mass (the calculation for VO2 involves dividing by body mass (Table 2, Figure10 A, B, and D). When activity EE was measured using treadmill walking (Table 2, Figure 9 D), no EE variable was significantly different between genotypes once body weight were taken into account as a covariate. For 24-RER, as shown in Figure 9 C, there was a significantly elevated RER in HOM rats. For RER on the treadmill test, as shown in

(Table 2) there were trends (0.10>p>0.05) toward higher RER in both HOM and HET compared to WT rats during both resting (the last 90 min) and during walking. Only during the first 10 min of activity was the RER significantly lower in WT rats compared to HOM rats (Figure 9 E). RER was significantly lower in WT compared to all other rats combined over the course of the 30 min of treadmill walking (Table 2).

Figure 9 : Effects of MC4R deletion on 24-hr energy expenditure (EE) and activity EE, and also 24- hr and activity-related respiratory exchange ratio (RER). (A, B, and D) When body weight and lean mass were taken into account using covariance, no differences were seen between genotypes in energy expenditure during the 24-hr and activity energy expenditure (treadmill) tests. (C) RER

(VCO2/VO2), an indicator of substrate use, was significantly higher in rats lacking MC4R (HOM) compared to wild-type (WT) rats or rats heterozygous for the allele (HET) during 24-hr calorimetry.

(E) During the first 10 min of activity (after 2-hr food restriction), RER of HOM rats was higher than

WT rats’ RER, indicating a lower reliance on lipids compared to WT rats. *Significantly different from HOM rats, **significantly different from HET rats, p<0.05.

EE (treadmill test); Rats

type type rats (WT). RER, respiratory

hr hr energy expenditure (EE), and activity

functional functional melanocortin 4 receptor (MC4R), or wil

ignificantly different from HOM, p<0.05. HOM, different from ignificantly

/VO 2

Body Body composition and calorimetry measures from measurement of 24 42

: :

Table homozygous (HOM) or heterozygous (HET) for non (VCO ratio exchange

Study 2: Calorie restriction in MC4R loss-of-function rats

Here, I test the hypothesis whether MC4R loss of function rats regulate body weight differently during negative energy balance. To test this hypothesis, I measured changes in body weight and body composition before and after rats were subjected to 21 days of calorie restriction.

Methods

Weight loss during calorie restriction

In male rats, WT (n=8), HET (n=8), and HOM (n=8), daily food intake was measured in each rat for 7 days, and the average food intake was calculated omitting the days of highest and lowest food intake for each rat. Rats were then fed 50% of their daily ad libitum food intake for 21 days (50% CR). Body composition was measured 2 days before the onset of 50% CR as well as on the 21st day of calorie restriction. Body weight was measured daily before food was given at 1200hr ± 1hr. After the end of 50% CR, rats were again given ad libitum access to food. Body weight and food intake were measured daily for one week and every 2-3 days for another week. Body composition was measured after 14 days of ad libitum feeding at 1200hr ± 1hr.

Analyses and statistics

Calorie restriction was analyzed using a mixed repeated-measures ANOVA to compare body weight and composition before vs. after 50% CR, with planned

comparisons (with using a Bonferroni correction, p<0.017 for 3 groups) of weight loss between genotype. One body weight value for one rat was lost; this was estimated using imputation for the ANOVAs, but not used in the post-hoc tests or planned analyses.

Results

Partial or full MC4R deletion is protective during food restriction

Weight loss occurred with 50% CR, as shown in Figure 10. Body weight loss differed with genotype, with main effects of genotype and time and a significant interaction. Even though HOM rats were heavier at baseline, they did not lose significantly more grams of body weight during calorie restriction (weight loss: HOM,

76.36g; HET, 72.84g; WT, 83.26g). Planed comparisons revealed that WT rats lost significantly more weight (in grams) than HET rats (p=0.0026). When weight loss was calculated as percent baseline body weight, the ANOVA showed significant main effects of time and genotype and a significant interaction. Final percent weight lost was significantly different between each genotype, with WT rats losing the highest proportion of their baseline weight, HOM rats losing the least, and HET between the other genotypes. Correlation coefficients were calculated to figure out if baseline differences in energy balance (e.g., weight gain during baseline food intake measurements) predicted weight loss during CR. There was no significant correlation between weight gain (g) during baseline feeding and weight loss (g) during CR within genotype or overall.

Body composition analysis revealed that HOM rats more favorably maintained 44

lean mass. This was also true of HET rats to a lesser extent. Repeated-measures comparisons revealed a significant difference in calorie restriction-induced fat loss and change in percent body fat between genotypes, as well as main effects of genotype and calorie restriction. HOM rats lost significantly more grams of fat than either WT or HET rats lost (though this was a significantly lower proportion of baseline fat mass in HOM rats fat mass; Table 3). Significant interactions and main effects were also found for the calorie restriction-induced change in lean mass, with WT rats losing significantly more grams of lean mass and a greater proportion of their baseline total lean mass compared to either HET or HOM rats. HET rats also lost more lean mass than HOM rats. Overall, the proportion of body mass composed of lean mass increased with calorie restriction in all rats, but this fat-to-lean-mass proportion changed less in HOM rats. Baseline grams of body fat did not significantly depend on (correlate with) change in body mass with calorie restriction (r=0.12), except when HOM are considered alone, in which case HOM rats with more initial body fat lost more weight (r= -0.71; p<0.05). Proportion of weight loss as lean mass was significantly different between genotypes, and this was significantly correlated with both baseline body fat (r= -0.78) and baseline percent body fat (r= -0.82), where rats heavier at baseline lost less lean mass proportionally, with non- significant trends within each genotype.

After 14 days of ad libitum fed recovery from food restriction, all genotypes had recovered to within 4 grams of their baseline body weights (Table 3). The analysis of body weights during recovery feeding showed a significant interaction as well as main

effects of genotype and refeeding. There was a significant interaction in daily (but not cumulative) weight regain, and WT rats gained significantly more weight than both other genotypes on the first day of ad libitum feeding after calorie restriction, and slightly but significantly less on the 6th day. Measured daily food intakes during this time revealed a main effect of group, and HOM consumed more food overall. No interaction was found, and WT rats (which showed faster weight regain) did not consume more food during recovery feeding, including on the first day of refeeding (genotype means were all between 38 to 39.5 g intakes this day). Recovery of body composition was biased toward lean mass during weight regain, where lean mass was regained faster than fat mass (Table

3). Rats had recovered all or nearly all of their lean mass after 2 weeks of ad libitum feeding, but fat mass levels were 8-45 g below baseline values (group means were 17-30 g below baseline) at this time, with HOM rats having a greater deficit in fat mass relative to baseline values compared to WT or HET rats. HOM rats also had a greater recovery of lean mass (relative to baseline values) compared to WT rats.

Figure 10: Weight loss during 50% food restriction in rats homozygous (HOM) or heterozygous (HET) for the non-functional melanocortin 4 receptor (MC4R), compared to wild-type rats (WT). (A) HOM rats lost less weight as a percent of their baseline body weight compared to HET or WT rats. (C) WT rats lost more weight than HET rats; these groups did not show differences in baseline food intake or body weight. Loss of fat mass

(E) and lean mass (D) differed with genotype, where HOM rats lost most of their body weight as fat, and WT lost approximately half of their body weight as lean mass (B).

*Significantly different from HOM rats, **significantly different from HET rats, p<0.05.

Table 3: Body weight and composition before and after 21 days of 50% calorie restriction (CR), and after 14 days of ad libitum recovery from CR; Mean (SEM)

BW: Body weight. Rats homozygous (HOM) or heterozygous (HET) for non-functional melanocortin 4 receptor (MC4R), or wild-type rats (WT). *Significantly different from HOM, **significantly different from HET; p<0.05.

Study 3: The effect of MC4R loss-of-function on molecular pathways

supporting metabolism in skeletal muscle and brown adipose tissue (BAT)

I tested the hypothesis whether deficiencies in MC4R affect molecular control of metabolism in tissues which are important to whole-animal EE. I focused on skeletal muscle because muscle contributes to TDEE and represents approximately 40% of the total body weight and accounts for 20-30% of the total resting oxygen uptake (Gavini et al., 2014; Zurlo, Larson, Bogardus, & Ravussin, 1990). I determined mRNA and protein expression of components of molecular pathways known to alter energy substrate use, uptake, and conservation in skeletal muscle and BAT.

Uncoupling proteins (UCP) are the proteins in the mitochondrial inner membrane that uncouple oxidative phosphorylation from ATP production and cause the dissipation of heat. There are many forms of UCP. UCP1 is manly expressed in brown adipose tissue and responsible for thermogenesis (Erlanson-Albertsson, 2003). It is known that UCP1 is regulated by neuroendocrine systems and the SNS (Tao, 2010), thus activation of SNS outflow by leptin and α-MSH induces BAT UCP1 to generate the heat, suggesting that the obese rats lacking MC4R (HOM) may have lower UCP1 gene expression in BAT (Ste

Marie, Miura, Marsh, Yagaloff, & Palmiter, 2000; Tao, 2010). This may contribute to their obesity. The other forms of UCP relevant to this study are UCP2 and UCP3. UCP2 is widely expressed in many tissues including in white adipose tissues (WAT), whereas

UCP3 is limited to skeletal muscles (Argyropoulos et al., 1998). Unlike UCP1, both

UCP2 and UCP3 not only have mitochondrial uncoupling function (Cadenas et al., 1999), but also have functions in lipid handling (Samec, Seydoux, & Dulloo, 1998). It has been shown that long-term food restriction increases muscle UCP2 and UCP3 expression, likely due to the function of UCP2 and UCP3 in lipid handling rather than thermogenesis in skeletal muscles (Samec et al., 1998). To see if muscle UCPs might contribute to obesity in HOM rats, I examined the expression of UCP2 and UCP3 in the muscle of

HOM, HET, and WT rats in the fed state.

SERCAs (sarco/endoplasmic reticulum Ca2+- ATPases). There are two types of muscles fibers in skeletal muscle, type1 myosin heavy chain (MCH I) and type 2 (MCH

II). MCH I are slow-twitch, red oxidative fibers, and use fat oxidation as a fuel source.

MHCI are a more efficient fiber, whereas MCH II are fast-twitch, white glycolytic fibers, which tend to use glucose as a fuel source and are less efficient but more powerful

(Baldwin et al., 2011). SERCAs are channels with enzymatic and have ability to drive

Ca2+ from the cytosol into the sarcoplasmic reticulum using ATP, but ATP use and Ca2+ transport can be uncoupled and energy is released as heat (Baldwin et al., 2011; Fajardo et al., 2013). There are two types of SERCAs, SERCA 1 and SERCA 2. SERCA1 is present in greater amounts in type 2 fibers while SERCA2 is more prevalent and found in higher amounts in type 1 fibers (Baldwin et al., 2011). I examined the expression of

SERCAs in quad and medial gastroc skeletal muscle of rats lacking MC4Rs.

Muscle ATP-sensitive potassium (KATP) channels are found in several tissues including cardiac muscle, smooth muscle, kidney, pancreas, and particularly in skeletal muscle

(Flagg, Enkvetchakul, Koster, & Nichols, 2010). There are two genes that encode KATP channels in skeletal muscle, KCNJ8 encodes the Kir6.1 protein, and KCNJ11 encodes the

Kir6.2 protein (Flagg et al., 2010). KATP channels have a physiological role in skeletal muscles, and they allow potassium to flow into the skeletal muscle cells and protect skeletal muscles from energy depletion (Alekseev et al., 2010). Previous data show that muscle-specific KATP-knockout mice are lean and have high activity EE and muscle thermogenesis, suggesting that muscle KATP channels normally play a critical role in energy conservation (Alekseev et al., 2010; Koganti et al., 2015). I measured skeletal muscle KATP subunit expression in rats deficient in functional MC4R.

Mediator of RNA polymerase II transcription subunit1 (MED1). Transcription coactivator MED1 is a nuclear receptor. Along with skeletal muscle expression, MED1 is present in tissues including brain, heart, and adipose tissues (Jia, Viswakarma, & Reddy,

2014). MED1 functions in skeletal muscles to prevent muscles from energy depletion during energy restriction, reducing energy expenditure (W. Chen, Zhang, Birsoy, &

Roeder, 2010). Mice with a skeletal muscle-specific inactivation of MED1 are obesity resistant (W. Chen et al., 2010), suggesting that skeletal muscle MED1 has a critical role in energy homeostasis.

Experimental Methods

In male rats, WT (n=8), HET (n=8), and HOM (n=8) were euthanized by rapid decapitation. Tissues were collected and rapidly frozen in liquid nitrogen, then stored at -

80°C. These studies specifically focus on medial gastrocnemius (gastroc) and quadriceps femoris (quad) muscle groups.

mRNA extraction and qPCR

Skeletal muscle (quad and medial gastroc) of approximately 50 mg were collected from the frozen samples and homogenized using TRI reagent (Ambion Technologies).

An Ambion ribopure kit was used to extract the total mRNA from the homogenized tissue. Nanodrop (ND-1000; Nanodrop Technologies) was used to measure the purity of the mRNA and A260/280 ratio to be within 1.8 – 2.1. This diluted mRNA was used to prepare cDNA. The mRNA was diluted using elution buffer to reach a final concentration of 100 μg/μl (+/-10 μg/μl). An Applied Biosystems kit was used to prepare the PCR master mix, and PCR conditions corresponding cycling at 25°C for 10 minutes, 48°C for

30 minutes, 95°C for 5 minutes, and holding at 4°C. The final cDNA concentration after dilution with nuclease-free water was 100μg/μl. This cDNA was used for quantitative

PCR (qPCR) expression of UCP1, UCP2, UCP3, SERCA1, SERCA2, KCNJ8, KCNJ11,

MED1, and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) as a control. The relative expression was calculated using comparative Ct method (ΔCt) using WT as the reference value (defined as 100%).

Protein quantification and Western blot

Protein was extracted from muscles (quad and medial gastroc) using a homogenization buffer which included protease inhibitors. Protein concentrations were measured using a Bradford assay (Biorad DC assay kit). Samples containing equal amounts of protein and equal volume were loaded on a SDS PAGE gel, and gel electrophoresis completed at voltage (150V) for 30-40 minutes. Then, the gel was transferred onto a PVDF membrane. The membrane was blocked with 5% milk for 1-2 hour at room temperature, after that, probed with the primary antibody overnight at 4°C.

The secondary antibody was added on the next day and incubated at room temperature for 1-2 hour. After 20-25 min of washing with buffer, the blots were developed using a chemiluminiscence detector using an Amersham kit (GE Healthcare, UK; 2ml solution A,

50μl solution B). The expression levels relative to actin & Coomasie Brilliant blue dye as protein loading controls (S. L. Eaton et al., 2013; Samantha L. Eaton et al., 2015;

Welinder & Ekblad, 2011) were plotted as a percent of the reference value (with WT as

100%).

Analyses and statistics

I used a one-way ANOVA to compare qPCR and Western blot results between genotypes.

Results

Muscle and BAT

Genotype affected mRNA expression as measured using qPCR, but only in quad muscles, not gastroc muscles. Quad muscle mRNA expression of KCNJ11, SERCA1,

SERCA 2a, and UCP2 were different between genotypes, where HOM rats showed significantly higher expression levels than WT and HET rats (Table 4). MED1 mRNA in

Quad muscle was significantly higher in HOM rats than only WT but not HET rats

(Table 4). UCP1 mRNA in BAT was significantly lower in HOM than WT and HET.

Western blot protein analysis showed that there was no significant effect of genotype in quad muscles or gastroc muscles (Table 4). There was a trend in gasroc UCP2 where

HET tended to be higher than HOM and WT (p=0.051). In med gasroc, SERCA1,

MED1, KCNJ11, and KCNJ8 were not reliably detected. In Quad, SERCA1, KCNJ11, and KCNJ8 were not reliably detected.

Table 4: Quantitative PCR analysis and protein expression of medial gastrocnemius (gastroc) and quadriceps femoris (quads).

*Significantly different from HOM, p<0.05.

Discussion

MC4R deficiency is one of a few main contributors to both monogenic and polygenic human obesity. Like what is found in mice, rats lacking functional MC4R are severely obese (Mul, Begg, et al., 2012; Mul, van Boxtel, et al., 2012). Here, I examined the possible contribution of EE in both 24-h EE and activity EE to this obese phenotype, and also ability of food restriction to influence adiposity in these rats. The HOM rats were hyperphagic and displayed very low levels of daily spontaneous physical activity.

Notably, there were no differences in EE observed once body weight and composition were considered. The rats heterozygous for the altered MC4R gene appeared approximately equal to the WT rats in most respects, with two exceptions. Firstly, compared to WT rats, HET rats had a significantly greater fat-to-lean mass ratio without a significant difference in body weight. This is similar to other reports, though a few differences in food intake or body weight between WT and HET rats have occurred (Mul,

Begg, et al., 2012; Mul, van Boxtel, et al., 2012). Secondly, the HET rats lost less weight than WT rats even though their food intake, calorie restriction, and baseline body weights were very similar. Thus, there is a significant influence of heterozygosity of MC4R that is not obvious when examining body weight alone during baseline conditions. HOM rats displayed unusual conservation of body mass despite their very large size. Animals with compromised MC4R function would likely be well suited to conditions of unpredictable food availability (Cone, 2000; Diane et al., 2012; Reinhardt et al., 2015) .

HOM rats show extreme adiposity as well as elevated food intake and altered feed efficiency, but no change in feed conversion efficiency (Mul, Begg, et al., 2012; Mul, van

Boxtel, et al., 2012). Collectively, it follows that lowered EE is a possible contributor to obesity in these rats. However, my measurement of 24-hr EE with regression-based adjustment for body weight (Tschop et al., 2012) did not show any differences in EE associated with loss of MC4R function. Activity-induced EE was unaffected by genotype, too (Table 2). Although no genotype difference was seen in EE, calorimetry revealed an unusually elevated RER in the HOM (Figure 9 C). This is consistent with a reliance on glucose for fuel in HOM, as well as lowered fat oxidation and high lipogenesis, but acute factors such as physical activity and food intake will also influence

RER (Miyaki et al., 2011; Ramos-Jiménez et al., 2008). There was a trend toward increased RER in both the HOM and HET rats even during 2 hour food restriction and significantly lower RER in WT during treadmill activity (Table 2). Thus fat oxidation is likely higher during activity in WT rats, and lower in HOM and HET rats, consistent with the known role of MC4R in regulating autonomic outflow. MC4R influences autonomic outflow at the levels of the hypothalamus and preganglionic neurons (Sohn et al., 2013).

MC4R stimulates sympathetic and suppresses parasympathetic outflow to several systems including white adipose tissue, where MC receptor activation is known to induce lipolysis (M. N. Brito, Brito, Baro, Song, & Bartness, 2007; Shrestha et al., 2010; Song,

Jackson, Harris, Richard, & Bartness, 2005). Pharmacological blockade of MC4R and

genetic disruption of MC4R in mice leads to the promotion of the expression of genes known to activate lipogeneses, and decrease expression of genes promoting lipolysis (M.

N. Brito et al., 2007; Nogueiras et al., 2007). This corresponds to the fat accumulation seen in HOM rats and the moderately elevated body fat of HET rats. On the other hand, the significant loss of adipose tissue during food restriction implies that the ability of calorie restriction to cause fat mobilization was not reduced in either HOM or HET rats.

HOM rats did not exhibit detectably low metabolic rates or lower activity EE despite having lower levels of spontaneous physical activity during calorimetry (Figure 8

E, Table 2). It is unlikely that low daily activity levels are secondary to the elevated body mass in the HOM rats. Because body size contributes relatively more to activity EE

(Gavini et al., 2014) than to basal or resting EE, it is likely that the low activity levels in

HOM rats were offset by their much higher body weights, increasing their overall activity

EE. The suppressed activity levels seen in HOM rats are compatible with the known role of melanocortin receptors in modulating physical activity (Butler & Cone, 2003; Shukla et al., 2012; Skibicka & Grill, 2008). For example, mice with deletions in melanocortin receptors show low levels of physical activity (A. S. Chen et al., 2000), and melanocortin receptor agonists increase physical activity levels (Shukla et al., 2012; Shukla et al.,

2015).

During baseline feeding conditions, HET rats did not differ from WT rats in body weight, energy expenditure, and spontaneous physical activity (Figure 8 A, E; Figure 9A,

B). The response to calorie restriction, on the other hand, differed with genotype. As a

percent of baseline body weight, WT rats lost significantly more weight than HET rats, which in turn lost more than HOM rats. Furthermore, HOM rats did not lose significantly more grams of body weight than the other genotypes despite their having much higher baseline weights and baseline energy requirements (Figure 10 C). The genotype difference in weight loss was not an artifact of food allocation calculations for calorie restriction, where the greater energy needs or weight gain in HOM rats might have introduced a bias where they would have essentially gotten more food, relative to their actual energy needs, compared to WT or HET rats. Weight gain during baseline measurement of food intake (which would indicate positive energy balance) did not correlate with less weight loss during calorie restriction. This is particularly true for HET and HOM rats, which showed no group difference in weight gain during measurement of food intake. When comparing WT with HET rats, even though rats of these genotypes started out at very similar body weights and energy needs, WT rats lost more grams of body weight than HET rats (Figure10A).

With calorie restriction-induced weight loss, lean mass was lost along with fat mass, but HOM rats lost significantly more fat mass than WT rats and HET rats, and WT rats lost more lean mass than HET rats and HOM rats (Figure 10, Table 3). Baseline fat mass may contribute to the ability to maintain lean mass during calorie restriction

(Forbes, 2000). However, HET rats and WT rats had only a moderate difference in baseline adiposity (Figure 8 B, Figure 10 B, E) but showed a sizable difference in their ability to maintain lean mass during food restriction. This again suggests that MC4R

affects fat loss during calorie restriction, even after baseline body composition-related confounds are considered. The ability of HOM rats to maintain body weight and lean mass implies that, relative to WT, these rats would likely have increased fitness in an environment where food is limited or insecure. Moreover, the HET rats displayed an intermediate phenotype in their conservation of weight and lean mass, despite their similarity to WT rats in nearly every other way. It is likely that even a single copy of the mutant allele could give a survival advantage during food deficits, making it more likely that the mutant allele would remain in the rat population. The consistent association between genetic mutations and variants in MC4R with human obesity supports this idea

(Girardet & Butler, 2014; Loos, 2011; Zegers et al., 2012). Lastly, unlike weight and fat loss, recovery from calorie restriction was approximately equal among genotypes, except that WT rats initially showed faster weight regain (Table 3).

Because of the correlation between MC4R function and both physical activity and skeletal muscle (data from our laboratory not yet published), I investigated the possible differences in muscle energetic pathways associated with MC4R genotype. Genotype affected only quad and BAT gene expression. No differences were observed in molecular energetic pathways examined here in gastrocnemius muscle (Table 4). Quad muscle showed significantly higher kcnj11, SERCA1, SERCA 2a, and UCP2 mRNA expression in HOM rats compared to both HET and WT (Table 4). For MED1 mRNA in quad muscle, HOM rats had significantly higher levels than WT but not HET rats (Table 4).

The difference in UCP2 could contribute to the function of UCP2 in lipid handling. HOM

rats showed increased expression of energy conservation mechanisms in quad (kcnj8, kcnj11, MED1), but also increased levels of SERCA 1 and SERCA 2a, which are thought to contribute to thermogenesis and inefficiency (Baldwin et al., 2011; Fajardo et al.,

2013). The levels of SERCA may not directly correspond with energetic efficiency, though, as shown by the increase in muscle SERCA in people who have been calorie restricted (Baldwin et al., 2011). Protein levels of quad MED1, SERCA 2a, and UCP2 and 3 did not differ between genotypes, however. Additionally, BAT showed significantly lower UCP1 expression in HOM rats compared to both HET and WT (Table

4). While low BAT UCP1 might suggest low metabolism, as described above, I found no difference in daily EE in HOM rats. Unfortunately, I found insufficient BAT in HOM rats to measure UCP protein levels.

Overall, MC4R plays a critical role in energy balance. It elevates EE and lowers food intake. Surprisingly, I found that rats deficient in functional MC4R did not show detectable differences in EE, but rather that increased food intake played a disproportionate role in the obesity seen in HOM rats, despite suggestions from previous work on these rats that the rats lacking MC4R may have a lower metabolic rate (Mul,

Begg, et al., 2012; Mul, van Boxtel, et al., 2012).

During food restriction, however, rats with normal MC4R function showed a lack of conservation of body mass, especially lean mass, whereas, rats with one or two copies of the mutant allele showed conservation of body mass and lean mass during 50% CR.

However differences in RER and weight loss suggested differential autonomic control

with altered MC4R function. In the next few Chapters, I further tested this hypothesis by examining the effects of calorie restriction on energy balance, autonomic outflow, and response to melanocortin receptor activation in outbred rats.

: Long-term calorie restriction induces adaptive thermogenesis in

different components of energy expenditure

As described in Chapter 1, long-term calorie restriction reduces all components of

TDEE including both resting and non-resting EE. This occurs because of the decrease in energy requirements along with phenomenon called adaptive thermogenesis. Adaptive thermogenesis has the result of countering extra weight loss or weight maintenance and impairs the success of the diet. Adaptive thermogenesis after calorie restriction has been reported in laboratory animals (Ravussin et al., 2011) and in humans where at least part of this adaptation occurs in non-resting EE, particularly in activity thermogenesis

(Goldsmith et al., 2010; Muller & Bosy-Westphal, 2013; Rosenbaum et al., 2003).

Briefly, adaptive thermogenesis means that it takes fewer calories to support the same body weight or do the same work, even after the change in body composition is taken into account (Dulloo, Jacquet, Montani, & Schutz, 2012). Adaptive thermogenesis is highly regulated by many factors including metabolic condition (lean vs obese), obesity propensity, diet, and cold temperature (Lowell & Spiegelman, 2000; Rosenbaum

& Leibel, 2010), impacting both autonomic and neuroendocrine systems. Additionally, based on my data in Chapter 2 showing that rats lacking functional MC4R lose less weight during calorie restriction, I hypothesize that MC4R impacts adaptive thermogenesis, consistent with the ability of HOM rats to conserve body mass.

Additionally, previous observations in our laboratory and other laboratories have shown that activation of brain MC receptors stimulates muscle thermogenesis and muscle 63

metabolism (Tanaka et al., 2007; Toda et al., 2009). Individual differences in non-resting

EE and NEAT are predictive of fat loss in response to food restriction (Levine et al.,

1999; Levine et al., 2005), and physical activity is observed to be higher in the lean compared to obese phenotype (Levine et al., 1999; Levine et al., 2005). Therefore, I tested the hypothesis that adaptive thermogenesis occurs in low- to moderate-level physical activity, termed non-exercise activity thermogenesis (NEAT). I also hypothesize that long-term calorie restriction reduces non-resting EE and gastrocnemius (gastroc) muscle thermogenesis, using muscle heat dissipation to assess muscle thermogenesis.

Methods

Transponder implantation

8 SD rats underwent to transponder implantation surgery under isoflurane anesthesia. A short incision was made on both hind limbs. Sterile temperature transponders (IPTT-300; Bio Medic Data Systems) were implanted adjacent to the

(gastroc) muscle group of both hind limbs to measure the heat dissipated by skeletal muscle during activity. Care was taken to place the transponders so as not to disrupt locomotor function. Rats were allowed to recover for at least 1 week before the graded treadmill test was performed. All procedures and handling were in accordance with and approved by Kent State University’s Institutional Animal Care and Use Committee.

Food intake and calorie restriction

After recovery from surgery, daily food intake of each animal was calculated after measuring their baseline food intake for 7 days. Based on the average daily food intake of each rat, the 50% food consumption of each rat was calculated individually. 50% CR was performed on each rat for 21 days. Body weight was measured and animals were fed daily at noon (EST) with precision of +/-1 hr. Body composition measurement was done once before calorie restriction (during baseline) and again after 19 days of calorie restriction, using magnetic resonance spectroscopy using an EchoMRI-700.

Energy expenditure and graded treadmill test

Rats were acclimated for two days in the calorimetry room and chamber (cage) before the energy expenditure measurement. I used an Oxymax FAST system (Columbus

Instruments, Columbus, OH) to measure energy expenditure and physical activity for each animal with a temporal resolution of 30 seconds, which helped me to analyze different components of EE (resting EE and non-resting EE). The rats were monitored for

24 hrs, and data from noon (EST) of day 1 to noon on day 2 were analyzed. The first 1-2 hrs of data were not used for my analysis to prevent any error in the data due to the fact that the animals might have been agitated or more active immediately after they are sealed in the chamber, and also to allow the chamber air to settle. Energy expenditure was measured by the calorimeter at 30-second intervals (except for reference measurements) for a period of 24 hrs, and physical activity was measured at 10-sec intervals. Energy expenditure was separated into resting EE and non-resting EE (in animals housed without wheels or other sources of exercise, activity EE consists entirely

NEAT) using CLAX software (Gavini et al., 2014). CLAX software was used to calculate the resting EE based on the lowest EE, after eliminating the 5 lowest episodes of EE. From there, non-resting EE was calculated using the formula: TDEE = resting EE

+ non-resting EE (Gavini et al., 2014), therefore non-resting EE = TDEE - resting EE.

Because most of the adaptive thermogenesis in activity EE is seen in low or moderate levels of activity in humans (Rosenbaum et al., 2003), after measuring resting EE and

NEAT, I measured low-level treadmill activity EE. At least 1 day after a 10-min treadmill

acclimation period, rats were placed in the treadmill and allowed to acclimate without food for 2 hrs. Given the time of day, 2 hrs without food is likely to be sufficient to avoid the thermic effect of food from what little the rats may have eaten prior to this time during the light phase of the cycle (Tremblay et al., 2013). However, thermic effect of food could not be directly quantified during the 24-hr EE measurement. Over the course of this 2-hr period, rats showed a predictable pattern of behavior, where physical activity and EE would rise then fall gradually, reaching a steady resting state. After the 2-hr resting period, the treadmill was started at 7 m/min for 30 min, and activity EE data were collected (Gavini et al., 2014) .

Two days after of measuring EE during treadmill walking, the rats were subjected to a second graded treadmill test to determine skeletal muscle heat dissipation during controlled physical activity levels. The rats were acclimated to the treadmill for 10 min in the days prior to the test as well as immediately before the test. Gastroc temperatures in each leg were recorded at baseline and at set intervals during a five-level graded treadmill test. Starting at 7 m/min, 0° incline, temperature was measured at 2, 5, and 10 min, 15 min (9 m/min at 0° incline), 20 min (9 m/min, 10° incline), 25 min (11 m/min, 10° incline), and 30 min (11 m/min, 20° incline). The test was stopped at end of 35 min

(Table 5) (Gavini et al., 2014).

In summary, studies measuring 24-hr energy expenditure (EE), including resting

EE and non-resting EE, and also a graded treadmill muscle-temperature test, were

conducted once during baseline food intake and then again after 21 days of calorie restriction for comparison to baseline EE and muscle thermogenesis.

Table 5: Graded treadmill test

Data Analysis:

Paired t-tests (1-tailed) were used to compare RER and activity variables before and after calorie restriction. Again, because of the dominant influence of body weight on

EE, ANCOVA was used to compare EE (kcal/hr) variables before and after calorie restriction, with body weight and lean mass as covariates in separate analyses. Muscle temperature during treadmill activity was analyzed using repeated-measures ANOVA, with feeding condition and time on treadmill as the independent variables.

Results

Calorie restriction induces adaptive thermogenesis in resting and activity EE, increasing muscle work efficiency and decreasing muscle activity thermogenesis

As shown in Table 6, 21 days of 50% CR significantly reduced rats’ body weight, body fat, and lean mass. As predicted, physical activity was also significantly lower after calorie restriction. Accordingly, I saw a significant reduction in total EE (41.55% ±

1.06%) as well as in both resting EE (39.67% ± 1.36%) and non-resting EE (48.23% ±

2.44%). These differences were also found after either body weight or lean mass were taken into consideration using ANCOVA (Figure 11). Treadmill-activity EE also significantly decreased after calorie restriction (by 31.21% ± 2.57%) with lean mass as the covariate (Figure 13). Consistent with my predictions, 24-hr RER was significantly reduced after calorie restriction (Figure 12), as was treadmill-activity RER (before calorie restriction, 0.86 ± 0.01; after calorie restriction, 0.79 ± 0.01).

Table 6: Changes in body composition, energy expenditure, and physical activity after 21 days of 50% calorie restriction. (Mean±SEM).

*Significant change from ad libitum conditions, p<0.05.

Figure 11: 21 days of 50% calorie restriction (CR) significantly suppressed both resting and non-resting energy expenditure (EE). Total EE (A, B), resting EE (C, D), and non-resting EE (E, F) were each significantly suppressed after CR when covariate analysis was used to factor out differences in body weight (A, C, E) or lean mass (B,

D, F). *Significantly lower than ad libitum-fed conditions, p<0.05.

Figure 12: 50% CR also significantly decrease both 24-hr RER (A) and spontaneous physical activity (B). *Significantly lower than ad libitum-fed conditions, p<0.05.

Figure 13 : When physical activity was controlled using a treadmill, there was a significant suppression in energy expenditure after 21 days of 50% CR. *Significantly lower than ad libitum-fed conditions, p<0.05.

All rats finished the 35-min graded treadmill test before calorie restriction, and 6 of the 8 rats finished after calorie restriction, with the remaining 2 rats completing 30 min of the test. Gastroc temperature averaged over both legs during treadmill activity showed a significant interaction between calorie restriction and time on the treadmill. 50% CR significantly suppressed baseline and activity-induced muscle thermogenesis, with less calorie restriction-related suppression observed as the intensity and duration of the treadmill activity increased (Figure 14). I also found main effects of time on treadmill and calorie restriction. Gastroc temperature was higher before calorie restriction compared to after calorie restriction in both the right and left legs at each time point except for the 35-min time point in the left leg and the 2-min time point in the right leg.

Change in gastroc temperature from baseline (i.e., before the treadmill was started) was analyzed separately. Increase in gastroc temperature over the course of the treadmill test showed a significant interaction between calorie restriction and time on treadmill, and a main effect of time on treadmill, but not a main effect of calorie restriction. In the 50% calorie restriction condition, compared to before calorie restriction, the increase in gastroc temperature from baseline (induction of muscle thermogenesis) was lower at the beginning of the treadmill-walking test but higher at the end of the treadmill-walking test. These same main effects and interactions were seen in the analyses for just the left gastroc and just the right gastroc temperature changes. In the right gastroc, in the increase from resting (baseline) temperature at 30 min was higher in the rats after calorie restriction compared to before calorie restriction, with a trend in the

same direction for the time points between 20 and 35 min. In short, calorie restriction lowered both baseline and activity-induced muscle temperature, but the ability to induce muscle thermogenesis was not compromised overall, in fact the change in temperature relative to baseline was significantly greater in the right gastroc on at least one time point.

Figure 14 : Activity-induced muscle thermogenesis and calorie restriction (CR). (A) When physical activity was controlled using a treadmill, there was a significant suppression in overall gastrocnemius muscle thermogenesis after CR compared to before CR. (B) On the other hand, the increase muscle thermogenesis from resting levels was not compromised by CR for higher intensity activity.

*Significantly different from ad libitum conditions, p<0.05.

Discussion

Long-term (21-day) calorie restriction induced adaptive thermogenesis in rats’ EE.

This involved all components of total EE including both resting and non-resting EE

(Figure 11). Calorie restriction suppressed physical activity levels (Table 6 , Figure 12

B), but it also reduced the energy demands of low-intensity physical activity, even when activity levels remained consistent and the change in body composition was considered

(Figure 13). This shows the relevance of reduced activity thermogenesis to the adaptive thermogenesis observed during energy restriction. This is consistent with what has been observed in laboratory animals (Diane et al., 2012; Ravussin et al., 2011; Smyers, Bachir,

Britton, Koch, & Novak, 2015) and also human studies (Rosenbaum et al., 2008;

Rosenbaum & Leibel, 2010; Rosenbaum et al., 2003). In humans, adaptive thermogenesis in resting EE appears to occur in later stages of food restriction and a few differences are seen between individuals (Zauner et al., 2000). Additionally, muscle work efficiency is also suppressed after several weeks of calorie restriction and shows differences between people (Goldsmith et al., 2010; Rosenbaum et al., 2005; Rosenbaum et al., 2008;

Rosenbaum et al., 2003). Part of the adaptive thermogenesis in non-resting EE is due to the calorie restriction-induced suppression of physical activity levels, an effect seen only after several days or weeks of calorie restriction in rats (Smyers et al., 2015). Similarly, several weeks of energy restriction is needed to affect skeletal muscle work efficiency in people (Goldsmith et al., 2010; Rosenbaum et al., 2003). The differential timing of adaptive thermogenesis during calorie restriction suggests that the differential targeting of

physiological systems (e.g., skeletal muscle) or a different magnitude of suppression of these systems over the course of long-term food restriction.

As shown in Figure 14, 21-day calorie restriction decreased skeletal muscle thermogenesis, especially at the lower speed and workload. This may be partly due to an increase in muscle work efficiency (locomotor efficiency) (Goldsmith et al., 2010) as skeletal muscles use fat as fuel source during low levels of exercise (Goldsmith et al.,

2010). Physiologically, elevated use of fat as source of fuel during low levels of activity following weight loss could be due to the elevated ability of skeletal muscle to oxidize fat and suppress or attenuate glucose oxidation (Goldsmith et al., 2010; Kelley, 2005). This implies, after adaptive thermogenesis, activity demands fewer calories, even after the loss of body weight is taken into account. This is consistent with the change I observed in

RER, which is decreased after weight loss (Figure 12 A). On the other hand, at higher workloads, the skeletal muscle may lose efficiency due to the increase energy demand

(Baldwin et al., 2011; Goldsmith et al., 2010; Rosenbaum et al., 2003). These changes in muscle fuel utilization at different levels of activity or workload could reflect an interaction with calorie restriction on the reliance on fat oxidation over glucose oxidation

(Goldsmith et al., 2010; Kelley, 2005; Stannard, 2011).

Overall, total, resting, and non-resting EE all decreased after 21 days of calorie restriction. This adaptive thermogenesis in non-resting EE is due to decreased activity thermogenesis including altered muscle work efficiency. My findings suggest that increased muscle work efficiency at low levels of activity contribute to the adaptive

thermogenesis seen in non-resting EE. This is consistent with human studies (Goldsmith et al., 2010), and suggests that skeletal muscle is a good target system when considering interventions to counter adaptive thermogenesis in activity-related EE.

: Long-term calorie restriction reduces sympathetic nervous system

outflow to skeletal muscle

As described in Chapter 1, the autonomic nervous system opposes changes in body weight, meaning that during calorie restriction SNS outflow is suppressed (Arone et al., 1995; Dulloo, Young, & Landsberg, 1988; Snitker et al., 2000). It has been shown that negative energy balance reduces SNS outflow to heart, liver, kidney, BAT, and pancreas, but increases SNS outflow to WAT (Bartness, Shrestha, Vaughan, Schwartz, &

Song, 2010; N. A. Brito, Brito, & Bartness, 2008; Giordano et al., 2005). This makes sense because these changes would mobilize free fatty acids during high energy demand

(M. N. Brito et al., 2007; Dulloo et al., 1988; Giordano et al., 2005). As I showed in

Chapter 3, long-term calorie restriction suppresses all components of total energy expenditure including resting-EE and non-resting EE, inducing adaptive thermogenesis.

Changes in either resting or non-resting EE, or both, would implicate adaptations in skeletal muscle. Changes in muscle energetics are associated with altered economy of activity (Baldwin et al., 2011; Goldsmith et al., 2010; Rosenbaum & Leibel, 2010;

Rosenbaum et al., 2003). Overall, skeletal muscle represents approximately 40% of the total body weight and also contributes to 30% of resting energy use and most of the additional energy used during physical activity (Gavini et al., 2014; Kedryn K Baskin,

2015; Zurlo et al., 1990). Therefore, changes in autonomic nervous system actions, and

SNS modulation of muscle, have been implicated in human adaptive thermogenesis

(Rosenbaum et al., 2005; Rosenbaum & Leibel, 2010).

Dulloo and colleagues (1988) have shown that SNS outflow is altered in BAT and

WAT but not in skeletal muscle during short-term calorie restriction (Dulloo et al., 1988;

Giordano et al., 2005). In this case, short-term calorie restriction consisted of a 2-day fast.

They did not consider that the effects of food restriction on physical activity and activity-

EE differ according to the duration of the restriction. Short-term calorie restriction (1-3 days) vs. long-term calorie restriction (3 weeks) induce different effects. In the short term, food deprivation actually increases physical activity (Smyers et al., 2015) which is likely a foraging response. On the other hand, long-term restriction (weeks) clearly suppresses physical activity and increases fuel economy of activity (muscle work efficiency), promoting energy conservation, with individual differences in the speed of these adaptations (Smyers et al., 2015).

To the best of my knowledge, the possible impact of the SNS on muscle thermogenesis during longer-term calorie restriction has never been considered. To do this, I used a method of measuring norepinephrine (NE) turnover (NETO) to assess SNS drive to skeletal muscles. In this method, blockade of NE synthesis was done using α- methyl-para-tyrosine (aMPT), the competitive inhibitor of tyrosine hydroxylase (TH).

After aMPT administration, the level of NE content in tissues declines in a linear fashion

(Vaughan et al., 2014). Therefore, higher NE turnover reflects increased SNS, and lower

NE turnover reflects decreased SNS outflow (Dulloo et al., 1988). Here, I investigated the underlying cause of the changes in muscle work efficiency seen after calorie

restriction, and I hypothesize that SNS outflow to skeletal muscle is suppressed during long-term energy restriction.

Experimental design

I assessed SNS outflow to muscle using the method of NETO (Vaughan et al.,

2014). 25 Sprague-Dawley rats were divided into 2 groups, ad libitum-fed rats and calorie-restricted rats. Daily food intake of each animal was calculated after measuring their baseline food intake for 7 days. Based on the average daily food intake of each rat, the 50% food consumption of each rat was calculated individually. Rats were subjected to

50% calorie restriction for 21 days. Body weight was measured and animals were fed daily at noon (EST) with a precision of +/-1 hr. Body composition measurement was done once before calorie restriction (during baseline) and again after 21 days of calorie restriction (on the 21st day) using magnetic resonance spectroscopy with an EchoMRI-

700.

NETO was measured to assess sympathetic drive to white adipose tissue

(epididymal white adipose tissue, EWAT) and skeletal muscle including quad, lateral and medial gastroc, and soleus (Vaughan et al., 2014). Briefly, this method uses aMPT, a competitive inhibitor of tyrosine hydroxylase, the rate-limiting enzyme in catecholamine biosynthesis, to decrease NE synthesis. After aMPT administration, the endogenous tissue levels of NE decline at a rate proportional to the initial NE concentrations and depending on NE release (Vaughan et al., 2014). SNS outflow can be assessed by comparing tissue NE concentration between rats reviving aMPT with no-aMPT controls.

Both ad libitum-fed rats and calorie restricted rats were divided into rats receiving aMPT and no-aMPT controls, with one-half of the rats assigned to receive the competitive NE

synthesis inhibitor aMPT (n=6 ad libitum-fed rats, n=7 CR rats), while the remaining rats did not receive aMPT.

On the day of the study, aMPT (125 mg aMPT/kg body weight, 25 mg/ml) was injected into the assigned group at each 4 and 2 hours before euthanasia by rapid decapitation (Figure 15). All rats were euthanized by rapid decapitation between 1200 and 1500, 4 h after first aMPT injection (Figure 15). Skeletal muscle groups removed included medial and lateral gasroc, quadriceps, and soleus. I also collected EWAT. BAT was collected but insufficient BAT was found in the calorie-restricted rats for a valid analysis. All tissue was rapidly frozen in liquid nitrogen (Vaughan et al., 2014). Muscle and WAT NE content were measured using HPLC. Briefly, tissue was thawed and homogenized in a solution dihydroxybenzylamine (internal standard) in 0.2M perchloric acid (PCA) with 1 mg/ml ascorbic acid (AA). Next, centrifugation for 15 min at 7,500 g at 4°C, alumina was used to extract the catecholamine solution which was eluted with

PCA/AA and assayed using high performance liquid chromatography with electrochemical detection (HPLC-EC, Coulochem III) using Mobile Phase MD-TM and a reverse phase MD 150x3.2 column. The following formula was used to calculate NETO, with a greater aMPT-associated decrease in tissue NE reflected in higher NETO values:

(Vaughan et al., 2014)

k = (lg[NE]0 - lg[NE]4)/(0.434 × 4)

K = k[NE]0

Where k is the constant rate of NE efflux (also known as fractional turnover rate)

[NE]0 is the initial NE concentration or from 0-h group (control)

[NE]4 is the final NE concentration or from 4-h group (αMPT)

K = NETO

Data Analysis:

NETO data were analyzed using separate unpaired t-tests (2-tailed) to compare NETO values between ad libitum and 50% calorie restricted feeding conditions.

Figure 15: Timeline injection of aMPT (Vaughan, Zarebidaki, Ehlen, & Bartness, 2014).

Results

Calorie restriction decreases SNS drive to skeletal muscle, while increasing NETO in white adipose tissue

Calorie restricted rats lost weight (from 419.9g±7.6g to 343.3g±6.4g), fat mass (from

39.0g±2.2g to 17.1g±2.0g), and lean mass (from 312.5g±6.0g to 271.2g±4.9g). This applied to the rats that received aMPT (n=7) and to no-aMPT control rats (n=5), with no significant differences between the groups. Over the same time period, ad libitum-fed rats gained weight (from 412.5 ± 4.8g to 447.9 ± 6.8g), fat mass (from 36.6g ± 2.0g to 41.6g

± 1.8g), and lean mass (from 309.4g ± 3.2g to 333.3 ± 6.3g), with no significant differences between ad libitum-fed aMPT rats (n=7) and ad libitum-fed no-aMPT controls (n=5).

As shown in Figure 16, 21 days of 50% calorie restriction significantly decreased

NETO in the quad, soleus, and medial gastroc, but not in the lateral gastroc. NETO was significantly increased in EWAT after 50% calorie restriction (Figure 16 D).

Figure 16: 21 days of 50% daily calorie restriction (CR) significantly suppressed skeletal muscle norepinephrine turnover (NETO), and indicator of sympathetic nervous system drive. CR induced a significant decrease in

NETO in (A) medial gastrocnemius, (B) quadriceps, and (C) soleus muscle groups. (D) On the other hand, 50% CR significantly increased NETO in epididymal white adipose tissue. *Significantly different from ad libitum- fed rats, p<0.05.

Discussion

As described in Chapter 3, three weeks of calorie restriction (long-term) increased muscle work efficiency. This could contribute to adaptive thermogenesis in non-resting energy expenditure. Suppressed SNS outflow has been implicated in this effect but the effects of calorie restriction on SNS drive to muscle have not yet been documented. Here, measuring catecholamine turnover, I demonstrate a significant reduction in SNS drive to skeletal muscle after 21 days of food restriction (Figure 16), an effect not seen during short-term energy restriction (1-3) days (Dulloo et al., 1988). This supports the idea that

SNS drive to muscle is suppressed over longer-term calorie restriction. This is likely to impact the function of skeletal muscle, contributing to adaptive thermogenesis in both resting and activity EE.

Clinical studies have suggested that a low SNS outflow accompanies the suppressed activity EE seen after several weeks of energy restriction in people (Baldwin et al., 2011; Rosenbaum et al., 2005; Rosenbaum, Leibel, & Hirsch, 1997; Rosenbaum,

Murphy, Heymsfield, Matthews, & Leibel, 2002). Other studies measuring NETO after short-term (2-day) fasting in laboratory animals, on the other hand, found an increase in

SNS outflow to white adipose tissue, but no change SNS outflow to skeletal muscle

(Dulloo et al., 1988). This study has been referenced to refute the idea that changing food availability in general does not affect SNS drive to muscle. Because of the longer duration of calorie restriction needed to impact skeletal muscle work efficiency in humans (Baldwin et al., 2011; Goldsmith et al., 2010; Rosenbaum et al., 2003), it stands

to the reason that exposure to more days of calorie restriction would likely also affect

SNS outflow to skeletal muscle. In fact, I found that rats that underwent 21 days of 50% calorie restriction showed significantly reduced NETO in three of the four muscle groups examined (Figure 16). As expected, white fat (EWAT) showed higher NETO in the calorie restricted rats (Figure 16 D). This is consistent with other studies which show that

SNS drive to WAT is increased with energy restriction (N. A. Brito et al., 2008;

Giordano et al., 2005). It stands to the reason that when the metabolic fuels in the circulation do not meet the energy need of the animal, glucose is used first, and then if glucose is not sufficient due to calorie restriction or another reason, the body switches to mobilize free fatty acids from WAT via lipolysis, which then serves to elevate circulating lipids for use as fuel (N. A. Brito et al., 2008; Giordano et al., 2005). This is consistent with the decreased RER seen in rats after 21 days of 50% calorie restriction (Figure 12 A in Chapter 3). This system-specific impact of 50% CR on NETO also implicates at least some role for neural catecholamines, rather than exclusively circulating catecholamine hormones which would be expected have similar effects on all organs (Tentolouris et al.,

2006). Altogether, these data point to system-specific autonomic adaptations during energy restriction that differ according to the role of each system in energy conservation and metabolic fuel regulation, but also to the demands placed on each system depending on the severity of the energy restriction. This is especially relevant to skeletal muscle because the effect of calorie restriction on physical activity and muscle work efficiency depends on the duration of calorie restriction, where activity (and therefore energy need)

increases after short-term calorie restriction but slowly decreases after that (Smyers et al.,

2015) as physical activity and locomotor efficiency both change to support fuel conservation (Goldsmith et al., 2010; Rosenbaum et al., 2003).

A potential mediator of this adaption in skeletal muscles is the neuroendocrine response to negative energy balance. Calorie restriction will reduce body weight and composition of both fat mas and lean mass, leading to decreased leptin and decreased activation of the leptin-melanocortin pathway, including MC4R, ultimately reducing SNS outflow to skeletal muscles. Importantly, previous data have shown that MC4R-knockout mice show less hypertension (Karen K. Ryan et al., 2014; Sohn et al., 2013; Tallam et al.,

2005). As I demonstrated in Chapter 2, MC4R-deficient rats lose less weight during long- term calorie restriction. Moreover, data from our laboratory have shown that central administration of a melanocortin receptor agonist increases SNS outflow to peripheral tissues including skeletal muscles, BAT, and WAT, and also decrease locomotor efficiency (M. N. Brito et al., 2007; N. A. Brito et al., 2008; Girardet & Butler, 2014;

Penn, Jordan, Kelso, Davenport, & Harris, 2006; Rahmouni et al., 2003; Sohn et al.,

2013). Activation of this pathway may be suppressed by calorie restriction. Alternatively, being able to reverse calorie restriction-induced activity-related adaptive thermogenesis by activating the leptin-melanocortin pathway might promote maintenance of weight loss and long-term success of diets.

: The ability of VMH-MC4R signaling to increase activity EE with

long-term calorie restriction

When considering potential modulators of adaptive thermogenesis, the brain melanocortin system is a likely contributor. Genetic alterations in melanocortin peptides, their receptors, and their upstream and downstream modulators are commonly identified as contributors to both monogenic and polygenic human obesity (Choquet & Meyre,

2011; Hinney et al., 2010; Mul, Begg, et al., 2012; Mul et al., 2013; Mul, van Boxtel, et al., 2012; Vaisse, Clement, Guy-Grand, & Froguel, 1998). MC4R is particularly relevant to human obesity (Hinney & Hebebrand, 2008; Logan & Pepper, 2010; Zegers et al.,

2012). It is also an important regulator of autonomic control of metabolism (Berglund et al., 2014; Rossi et al., 2011; Sohn et al., 2013; Song et al., 2008; Stepp, Osakwe, de

Chantemele, et al., 2013). MC4R is expressed in the brain including in the hypothalamus, where it is present in the PVN, VMH, DMH, and LH, where MC4R plays a critical role in the regulation of energy balance by decreasing food intake and increasing EE (Butler,

2006; Corander et al., 2009; Mul, van Boxtel, et al., 2012; Karen K. Ryan et al., 2014;

Seeley et al., 2004).

There is now ample evidence that the VMH plays a distinct role in regulating glucose homeostasis, lipolysis, autonomic nervous system regulation, and the regulation of RER (or RQ) (K. W. Kim et al., 2011; King, 2006; Lindberg et al., 2013; Miyaki et al.,

2011; Takahashi & Shimazu, 1981; Toda et al., 2009). For example, it has been shown that lesions of the VMH lead to increased RER and decreased glucose uptake, increasing 94

lipogenesis in peripheral tissues by activating parasympathetic drive and decreasing SNS outflow (K. W. Kim et al., 2011; King, 2006; Lindberg et al., 2013; Miyaki et al., 2011;

Rissanen, Franssila-Kallunki, & Rissanen, 2001; Takahashi & Shimazu, 1981, 1982;

Toda et al., 2009). Furthermore, electrical activation of the VMH elevates glucose uptake in peripheral tissues including skeletal muscle, BAT, and heart, also increases fatty acid oxidation, leading to reduced RQ (Miyaki et al., 2011; Sudo, Minokoshi, & Shimazu,

1991). Therefore, the VMH is a good candidate for a potential modulator of calorie restriction-induced changes in muscle metabolism, which may contribute to adaptive thermogenesis in activity EE.

Previous investigations from our laboratory have found that activation of VMH melanocortin receptors enhances energy use during activity, and that this is less effective in obesity-prone rats. Furthermore, as described in Chapter 2, rats lacking functional

MC4R are better able to conserve body weight and lean mass during calorie restriction.

Altogether, this evidence implicates altered MC4R function in the metabolic changes seen during calorie restriction, especially the with respect to skeletal muscle energy use.

Therefore, the aim of this study was to measure the influence of calorie restriction on the ability of MC4R signaling to enhance activity-related EE. I used a specific MC4R agonist in rats to investigate the role of MC4R in the modulation of muscle work efficiency, and test the hypothesis that energy restriction alters economy of activity through decreasing the response to central activation of MC4R.

Methods

Surgery

Stereotaxic surgery was performed to implant guide cannulae aimed at the VMH. 15

Sprague-Dawley rats were placed in the stereotaxic apparatus under anesthesia with inhaled isoflurane. The following coordinates were used for VMH: anterior-posterior, -

2.5mm; medial-lateral, +0.5mm; dorsal-ventral, -6mm (from dura) using an injection needle with a 3mm projection (final dorsal-ventral, -9mm (from dura) (Figure 17)

(Gavini et al., 2014). Guide cannulae were affixed to the skull using a sterile wound clip and dental cement, and rats were then allowed to recover before the start of the study

(Gavini et al., 2014). At the completion of the study, injection sites were determined histologically, and only data from rats with injection sites within 250 µm of the VMH were included in the analyses.

Figure 17 : Ventromedial hypothalamus (VMH) microinjection site.

Adapted from The rat brain in stereotaxic coordinates (Watson).

Food intake and calorie restriction

MC4R agonist microinjection

Body composition was measured in rats before calorie restriction and on the 19th day of 50% CR using magnetic resonance spectroscopy using an EchoMRI-700. On the day of the study, each rat was microinjected either with the MC4R agonist Cyclo(b-Ala-

His-D·Phe-Arg-Trp·Glu)NH2 (Phoenix Pharmaceuticals) or with vehicle (artificial cerebrospinal fluid, aCSF) into the VMH at the dose of 20pmoles/200nl (200nl volume; similar to the effective dose of the mixed melanocortin agonist Melanotan II, as shown by data from other studies in the lab)(Gavini et al., 2014). Rats were given microinjections of the MC4R agonist or vehicle in random order, before calorie restriction and on day 21 and 26 of calorie restriction. After injection, the rats were acclimated in enclosed treadmill or normal cages for 2 h without food. Gas exchange was measured with air supplied to the treadmill at 2.59-3.3 LPM, using the same calorimetry measurement method as described in Chapter 2 and Chapter 3. After 2hrs of resting, the treadmill was

started at 7 m/min for 30 min, during which time steady-state, low-level activity EE data was collected, as described above in Chapter 3(Gavini et al., 2014) .

Data Analysis

Intra-VMH MC4R agonist-induced changes in treadmill calorimetry variables were compared using a 2X2 repeated-measures ANOVA with the within-subjects independent variables of (1) vehicle vs. agonist treatment, and (2) before vs. after calorie restriction.

To rule out the confounding effect of body weight on EE, ANCOVA was used to analyze the effect of the MC4R agonist on EE.

Results

The ability of VMH MC4R activation to increase activity EE is not compromised by calorie restriction.

11 rats had correct cannula placement, and full datasets (treadmill EE for both ad libitum and calorie restriction conditions and for both vehicle and MC4R agonist treatments) were collected for 8 of these rats. 21 days of 50% CR significantly decreased body weight (from 403.1 ± 5.9 to 364.3 ± 6.7), lean mass (from 309.5g ± 4.8g to 228.3g

± 4.7g), and fat mass (from 34.7g ± 1.5g to 12.5g ± 1.1g). As shown in Figure 18 and

Table 7, there was a main effect of the MC4R agonist on EE. Intra-VMH microinjections of the MC4R agonist induced significant increases in EE, VO2, and VCO2, but not RER.

There was also a significant main effect of calorie restriction. 21 days of 50% CR significantly decreased rats’ EE, VO2, VCO2, and RER (Table 7). There were no 99

significant interactions, in other words the ability of the MC4R agonist to alter treadmill- activity EE did not significantly change with calorie restriction.

Using body weight as the covariate (significant effect of body weight on EE), there were significant main effects of the MC4R agonist and of calorie restriction. Intra-

VMH MC4R microinjection significantly increased EE, and 21 days of 50% CR significantly decreased EE. Again, there was no interaction. When the vehicle-stimulated treadmill-EE was analyzed with body weight as the covariate, there was a significant effect of calorie restriction where EE was significantly lower after calorie restriction compared to before calorie restriction.

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Table 7: The melanocortin 4 receptor (MC4R) agonist induced changes in gas exchange before and after 21 days of 50% calorie restriction (CR). Mean±SEM.

*Significant increase over vehicle levels (p<0.05); **Significant main effect of CR (p<0.05), N=8 rats that completed all conditions.

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Figure 18: 50% daily calorie restriction (CR) did not significantly change the effect of ventromedial hypothalamic (VMH) melanocortin 4 receptor (MC4R) activation on enhancement of activity energy expenditure in rats. Activation of

MC4R by the microinjections of the MC4R agonist (20pmoles/200nl) into the

VMH significantly increased the energy expenditure (EE) of walking on a treadmill at 7 meters/min for 30 min. After CR, the MC4R activation still significantly enhanced treadmill-activity EE. There was no significant impact of 50% CR on the magnitude of this effect. *Significantly greater than vehicle, p<0.05.

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Discussion

The suppressed activity EE, muscle thermogenesis, and SNS outflow to muscle with 3 weeks of 50% calorie restriction (described in Chapters 3 and 4) may stem from central adaptations, including changes in the brain melanocortin system (Harrold,

Widdowson, et al., 1999; Harrold, Williams, et al., 1999; Mizuno et al., 1998). The brain melanocortin peptides and receptors are important regulators of autonomic control of metabolism (Berglund et al., 2014; Sohn et al., 2013; Song et al., 2008; Stepp, Osakwe, de Chantemele, et al., 2013) and of muscle energy uptake and use (Tanaka et al., 2007;

Toda et al., 2009). Also, changes in this peptide system are seen in association with energy restriction (Harrold, Widdowson, et al., 1999; Harrold, Williams, et al., 1999;

Mizuno et al., 1998). Therefore, I hypothesized that the adaptations in activity EE seen after calorie restriction may stem from altered responsiveness of this melanocortin pathway.

As shown in Figure 18, activation of MC4R in the VMH increased the rats’ EE during controlled treadmill walking activity, consistent with what is seen when using the mixed melanocortin receptor agonist Melanotan-II (unpublished data from our laboratory). As predicted, activity EE decreased with calorie restriction, consistent with the data from Chapter 3 showing that calorie restriction suppresses all components of total energy expenditure including both resting and non-resting energy expenditure

(Figure 11 Chapter 3). Even after calorie restriction, however, central MC4R activation was still able to significantly increase activity EE. The MC4R-induced increase in

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activity-related EE was not significantly altered by calorie restriction (Figure 18). This suggests that the suppressed activity EE, and probably the lowered muscle thermogenesis and SNS drive, are unlikely to be due to the inability of brain melanocortins to stimulate this brain-SNS-muscle pathway during calorie restriction. It is more likely that an upstream mediator or modulator of this system is changed during calorie restriction.

As described in Chapter 1, during fasting, the decrease in circulating insulin and leptin suppresses synthesis of the POMC precursor, and increased activation of the opposing AgRP/NPY neurons (Mizuno et al., 1998) would be predicted to decrease α-

MSH release. This suggests that a calorie restriction-associated decrease in the release of

α-MSH leads to MC4R up-regulation in the VMH, consistent with studies showing increased MC4R binding after energy restriction, and decreased receptor mRNA expression due to enhanced POMC expression (Harrold, Widdowson, et al., 1999;

Harrold, Williams, et al., 1999; G. Li, Zhang, Cheng, & Scarpace, 2007; Y. Z. Li &

Davidowa, 2004). This implies that there is increased availability of MC4R because of these effects of long-term changes in melanocortin release on the availability of MC4R

(e.g., up-regulation) (Harrold, Widdowson, et al., 1999). Despite this, VMH responsiveness to MTII was found to be suppressed by food deprivation (Li, Davidowa

2004). Others have shown that the decreased circulating insulin and leptin during food restriction increases activation of the opposing AgRP/NPY neurons (Mizuno et al., 1998).

Consequently, the level of AgRP expression and release is increased, which leads to

AgRP binding to MC4R and acts as inverse agonist, having the opposite action on the

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intracellular signaling as the agonist (Haskell-Luevano & Monck, 2001; Low, 2011;

Nijenhuis et al., 2001). I found that the MC4R-specific agonist was able to induce equivalent muscle thermogenesis before and after 50% CR. It is possible that the calorie restriction-induced change in VMH response to melanocortin peptides is offset by the ability of the MC4R agonist to counter AgRP effects.

Previous data from our lab showed that VMH-MTII (non-specific, mixed melanocortin receptor agonist) induced a significant decrease in RER, which means that

MTII likely increases fat oxidation during activity-related EE. This is consistent with other evidence that the VMH promotes fat utilization during exercise (Miyaki et al.,

2011). On the other hand, my findings indicated that the MC4R-specific agonist microinjected into the same region did not significantly lower RER in either negative or positive energy balance. This implies that another melanocortin receptor, or combined stimulation, may be more import to the mobilization of fatty acids as fuel in muscle.

Similarly, compared to the MC4R agonist, MTII also induced a greater percentage increase in activity-related EE.

As described in Chapter 2, rats with the MC4R gene deletion are hyperphegic and have increases in both lean and fat mass during positive energy balance. In contrast to MC4R-deficient rats, mice with MC3R gene deletion are not hyperphegic but they decreased lean mass and increase fat mass (Renquist et al., 2012). On the other hand, during negative energy balance MC4R-deficient rats showed a better response to calorie restriction in that they conserved body mass and lean mass. This implies that MC4R-

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deficient rats mobilize lipid from white adipose tissue and maintain their lean mass, though measurement of the change in RER with calorie restriction would be needed to confirm this. In contrast to MC4R-deficint rats, MC3R-knockout mice showed less response to negative energy balance with respect to fat mobilization, meaning that

MC3R-knockout mice maintained their adipose tissue by decreasing the release of free fatty acids from white adipose tissue during fasting (Renquist et al., 2012). This may explain why the mixed melanocortin agonist MTII lowered RER, but the MC4R-specific agonist did not. Altogether, combined stimulation of VMH melanocortin receptors leads to lowered RER, and this could be via MC3R, unlike specific stimulation of VMH-

MC4R which showed no significant different in RER.

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: General discussion

Weight gain and obesity are often a result of imbalance between energy intake and total daily energy expenditure (Romero-Corral et al., 2008). In human health, excess body fat increases the risk of many diseases and risk factors such as high blood pressure, high blood cholesterol, heart disease, type 2 diabetes, and many forms of cancer, and increases mortality (Farooqi & O'Rahilly, 2008; Flegal et al., 2005; Flegal et al., 2013;

Fontaine et al., 2003; Ogden et al., 2012; Visscher et al., 2004). During weight loss, minor differences in total daily energy expenditure can make a difference in weight loss and weight maintenance on a diet (Schoeller, 1998). Maintenance of body weight is influenced by a number of factors including homeostatic factors which are primarily processed in the hypothalamus. These pathways, such as the brain leptin-melanocortin pathway, are known to regulate food intake and energy balance and interact with environmental factors like the obesogenic environment (Greenway, 2015). Failure to control these factors leads to gain weight. In other words, gene mutations, particularly in

MC4R, along with an obesogenic environment make it hard for individuals to maintain their body weight, leading to obesity.

On the other hand, under weight loss programs, higher energy expenditure leads to improved weight loss. But maintaining a reduced body weight is challenging. There is variation between individuals in maintaining reduced body weight, and some individuals find it harder than others to lose weight and maintain weight loss during calorie restriction. This occurs because TDEE decreases with weight loss and this is secondary to 107

the loss of body composition including fat mass and lean mass (Leibel et al., 1995).

Further suppression of EE is often seen during weight loss is associated with a compensatory phenomenon called adaptive thermogenesis (Major et al., 2007;

Rosenbaum et al., 2008; Tremblay et al., 2013). Adaptive thermogenesis is a defense mechanism to protect energy stores from further depletion (Tremblay et al., 2013).

Adaptive thermogenesis varies among individuals, and it is regulated by neuroendocrine systems and the autonomic nervous system (Rosenbaum & Leibel, 2010). Here, I examined the potential involvement of MC4R in the regulation of adaptive thermogenesis, SNS, and muscle. This will contribute to the understanding of physiological and genetic factors favoring energy conservation and their interaction with an obesogenic environment.

I found that rats deficient in functional MC4R did not show detectable differences in EE, but rather that elevated food intake played a disproportionate role in the obesity seen in HOM rats. The elevated RER seen in HOM rats is consistent with lower fat oxidation and elevated adipose tissue accumulation and glucose oxidation. During food restriction, however, rats with normal MC4R function showed a lack of conservation of body mass, especially lean mass, and MC4R loss-of-function led the rats to conserve body mass. This suggests that MC4R gene mutations could contribute to a thrifty phenotype, as rats deficient in functional MC4R would be predicted to show more adaptive thermogenesis, leading these rats to lose less weight and conferring a survival advantage during calorie restriction (Reinhardt et al., 2015). This is consistent with other

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previous observations indicating that male juvenile JCR:LA-cp rats (mutation in leptin receptors) show a greater adaptive thermogenic response during calorie restriction (Diane et al., 2012), leading these rats to lose less weight (Diane et al., 2012). Taken together with these studies, my data imply that MC4R regulates body weight differently in the fed state than during negative energy balance.

Long-term food deprivation was modeled using 21-day calorie restriction. This induced adaptive thermogenesis in rats. This involved all components of total EE including both resting and non-resting EE. Calorie restriction suppressed physical activity levels, but it also reduced the energy demand of low-intensity physical activity, even when activity levels remained consistent and the change in body composition was considered. This implies that more consideration should be given to activity EE and non- resting EE in general when studying individual differences in weight loss and weight maintenance. Calorie restriction also decreased skeletal muscle thermogenesis, especially at the lower speed and workload. This may be partly due to an increase in muscle work efficiency or locomotor efficiency (Goldsmith et al., 2010) as skeletal muscles use fat as fuel source during low levels of exercise. On the other hand, at higher workloads, the skeletal muscle may lose efficiency due to the increase energy demand during high workload (Baldwin et al., 2011; Goldsmith et al., 2010; Rosenbaum et al., 2003). This is constant with human-subject data shown increased muscle work efficiency at low levels of activity but not at higher workloads (Goldsmith et al., 2010). This suggests increased muscle work efficiency at low levels of activity contribute to the adaptive thermogenesis

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seen in non-resting EE, and implies that moderate physical activity could be targeted in weight-loss studies and interventions.

Declines in total energy expenditure during long-term calorie restriction is influenced strongly by skeletal muscles because skeletal muscle accounts for a considerable amount of body mass and EE, both activity EE and resting EE (Gavini et al.,

2014; Kedryn K Baskin, 2015; Zurlo et al., 1990). Therefore, changes in autonomic nervous system action, in this case SNS action, on muscle have been implicated in adaptive thermogenesis (Rosenbaum et al., 2005; Rosenbaum & Leibel, 2010). Increased adaptive thermogenesis in activity EE (muscle work efficiency) depends on the duration of food restriction. Unlike short-term food restriction, long-term energy restriction

(weeks) clearly suppresses physical activity, and muscle work efficiency, and lowers

SNS drive to muscle, promoting energy conservation. There may also be individual differences in the speed of these adaptations (Smyers et al., 2015). In addition, measuring catecholamine turnover, I documented a significant reduction in SNS drive to skeletal muscle after 21 days of food restriction (Figure 16). Previously, it was only shown that short-term energy restriction (2-day fast) did not significantly affect SNS outflow to muscle (Dulloo et al., 1988). My findings imply that skeletal muscle makes a considerable contribution to both resting and activity EE through SNS modulation

(Gavini et al., 2014; Kedryn K Baskin, 2015; Zurlo et al., 1990), and that suppressed SNS drive to skeletal muscles could be contributing to both aspects of activation adaptive thermogenesis (resting and non-resting) after long-term calorie restriction.

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Maintaining a reduced body weight is difficult in the face of decreased resting and non-resting energy expenditure. This occurs because of a large change in muscle work efficiency and decreased SNS outflow to skeletal muscles (Leibel et al., 1995;

Rosenbaum & Leibel, 2010; Rosenbaum et al., 2003). A potential mediator of these processes is the central melanocortin system, which regulates not only energy homeostasis but also autonomic outflow. Importantly, previous data have shown that

MC4R-knockout mice show less hypertension, consistent with the absence of an obesity- associated compensatory increase in SNS drive (Karen K. Ryan et al., 2014; Sohn et al.,

2013; Tallam et al., 2005). Previous data from our laboratory show that central administration of melanocortin receptor agonists increase SNS outflow to peripheral tissues and skeletal muscles (M. N. Brito et al., 2007; N. A. Brito et al., 2008; Girardet &

Butler, 2014; Penn et al., 2006; Rahmouni et al., 2003; Sohn et al., 2013). Even though I saw suppressed activity thermogenesis and muscle SNS outflow after calorie restriction, I found that MC4R activation was still able to enhance activity EE. In other words, the

MC4R-induced increase in activity-related EE was not significantly altered by calorie restriction (Figure 18). This is consistent with human data indicating that leptin administration during a weight loss program in humans reverses adaptive thermogenesis and helps people to maintain their reduced body weight (Rosenbaum et al., 2005). This suggests that the suppressed activity EE, and likely the lowered muscle thermogenesis and SNS drive, was not due to the inability of brain melanocortins to stimulate this brain-

SNS-muscle pathway during calorie restriction.

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Future perspectives

In my studies I found that MC4R regulates body weight differently in the fed state vs. during negative energy balance. During positive energy balance, the obesity seen in rats deficient in functional MC4R was probably due more to their high food intake than a significantly lowered metabolic rate. The elevated RER seen in HOM rats is consistent with lower fat oxidation and elevated adipose tissue accumulation and glucose oxidation.

On the other hand, during negative energy balance, the MC4R mutation in HET/HOM rats may give a fitness advantage due to the enhanced adaptive thermogenesis response.

However, this study on calorie restriction focused only on body composition loss after calorie restriction. I would conduct a similar study to investigate the effect of 21 days of calorie restriction on resting and non-resting energy EE. This would tell us if there is an alteration in the ability of MC4R-deficient rats to quickly respond to energy shortage by decreasing both non-resting EE and resting EE. Similarly, I would investigate the possibility that the autonomic nervous system is different in the MC4R-defincient rats. I would predict that the mutant rats may have low SNS outflow to skeletal muscles. I would also predict that there may be a faster adaptation of the autonomic nervous system to calorie restriction in the MC4R-deficient rats.

Similar to what is found in human studies, I found that 21-day calorie restriction decreased skeletal muscle temperature and activity EE (muscle work efficiency), and this effect is seen at low levels of activity or workload. It would be interesting to also investigate non-resting EE in an enclosed treadmill (calorimetry) at a high workload to

112

see if this is affected by calorie restriction. In general, our studies point to adaptation or flexibility in muscle work efficiency at low but not high workloads.

Lastly, I found that a MC4R-specific agonist reverses adaptive thermogenesis and increases muscle work efficiency, even during long-term calorie restriction. This implies that this pathway would be a good target for intervention. I could see if daily administration of melanocortin receptor agonists could enhance weight loss during calorie restriction. I did not find significant effect on RER after administration of the

MC4R-specific agonist in the VMH before and after 21 days of calorie restriction.

Because previous data from our laboratory has shown combined central stimulation of melanocortin receptors (by MTII) increases SNS outflow to skeletal muscles and decreases RER, it would be interesting to investigate the effect of combined stimulation of melanocortin receptors with a mixed agonist (MTII) after 21 days of calorie restriction.

Along with other melanocortin receptor-specific agonists (MC3R, MC5R), this would tell us the activation of different receptors may be more effective in combating adaptive thermogenesis compared to the specific MC4R agonist.

Overall, these finding give evidence of how to link the activity of the brain melanocortin system to adaptive thermogenesis. Once MC4R activation is decreased, this may induce a greater adaptive thermogenic response. As a result, these individuals may be prone to have a resistance to weight loss. Also, these findings give a great an

113

opportunity to develop a pharmaceutical approach to obesity focusing on MC4R during calorie restriction.

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