Department of Internal Medicine (Divisions of Hypothalamic Research and of Endocrinology & Metabolism), The University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, TX 75390-9077, United States
The peptide hormone ghrelin regulates a variety of eating behaviors. Not only does it potently increase intake of freely-available food, but also shifts food preference toward diets rich in fat, enhances operant responding for food rewards, and induces conditioned place preference for food rewards. Here, we postulated that ghrelin also enables cue-potentiated feeding, in which eating is enhanced upon presentation of a food-conditioned stimulus. To test this hypothesis, a novel cue-potentiated feeding protocol adapted for use in mice was designed and validated, and then the effects of pharmacologic ghrelin receptor (GHSR) antagonism and GHSR transcriptional blockade (as occurs in GHSR-null mice) were assessed. Sated C57BL/6J mice indeed demonstrated cue-potentiated intake of grain-based pellets specifically upon presentation of a positive conditioned stimulus (CS+) but not a negative conditioned stimulus (CS-). Treatment with a GHSR antagonist blocked potentiated feeding in sated C57BL/6J mice in response to the CS+. In contrast, while GHSR-null mice also lacked a potentiation of feeding specifically in response to the CS+, they displayed an enhanced intake of pellets in response to both the positive and negative conditioned stimuli. The pattern of immediate early gene expression within the basolateral amygdala - a brain region previously linked to cue-potentiated feeding - paralleled the observed behavior of these mice, suggesting uncharacteristic activation of the amygdala in response to negative conditioned stimuli in GHSR-null mice as compared to wild-type littermates. Thus, although the observed disruptions in cue-potentiated feeding are different depending upon whether GHSR activity or GHSR expression is blocked, a key role for GHSRs in establishing a specific positive cue-food association has now been established.
"Egecioglu et al. showed that GHSR knockout mice have a suppressed intake of the rewarding food in a free choice (CHD/rewarding food) paradigm and a reduced accumbal dopamine release induced by rewarding foods (Egecioglu et al., 2010). We recently subjected GHSR-null mice to a cue-potentiated feeding protocol, in which cue-potentiated feeding was demonstrated by enhanced intake of grain-based pellets selectively upon presentation of a positive conditioned stimulus (Walker et al., 2012). While wild-type mice demonstrated cue-potentiated feeding behavior, GHSR-null mice lacked this behavior. "
[Show abstract][Hide abstract] ABSTRACT: Ghrelin is an octanoylated peptide hormone, produced by endocrine cells of the stomach, which acts in the brain to increase food intake and body weight. Our understanding of the mechanisms underlying ghrelin's effects on eating behaviors has been greatly improved by the generation and study of several genetically manipulated mouse models. These models include mice overexpressing ghrelin and also mice with genetic deletion of ghrelin, the ghrelin receptor [the growth hormone secretagogue receptor (GHSR)] or the enzyme that post-translationally modifies ghrelin [ghrelin O-acyltransferase (GOAT)]. In addition, a GHSR-null mouse model in which GHSR transcription is globally blocked but can be cell-specifically reactivated in a Cre recombinase-mediated fashion has been generated. Here, we summarize findings obtained with these genetically manipulated mice, with the aim to highlight the significance of the ghrelin system in the regulation of both homeostatic and hedonic eating, including that occurring in the setting of chronic psychosocial stress.
Frontiers in Neuroscience 07/2013; 7(7):121. DOI:10.3389/fnins.2013.00121 · 3.66 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Professor Richard F. Thompson and his highly influential work on the brain substrates of associative learning and memory have critically shaped my research interests and scientific approach. I am tremendously grateful and thank Professor Thompson for the support and influence on my research and career. The focus of my research program is on associative learning and its role in the control of fundamental, motivated behaviors. My long-term research goal is to understand how learning enables environmental cues to control feeding behavior. We use a combination of behavioral studies and neural systems analysis approach in two well-defined rodent models to study how learned cues are integrated with homeostatic signals within functional forebrain networks, and how these networks are modulated by experience. Here, I will provide an overview of the two behavioral models and the critical neural network components mapped thus far, which include areas in the forebrain, the amygdala and prefrontal cortex, critical for associative learning and decision-making, and the lateral hypothalamus, which is an integrator for feeding, reward and motivation.
Neurobiology of Learning and Memory 10/2010; 95(2):152-8. DOI:10.1016/j.nlm.2010.10.003 · 3.65 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Animals use current, past, and projected future states of the organism and the world in a finely tuned system to control ingestion. They must not only deal effectively with current nutrient deficiencies, but also manage energy resources to meet future needs, all within the constraints of the mechanisms of metabolism. Many recent approaches to understanding the control of ingestive behavior distinguish between homeostatic mechanisms concerned with energy balance, and hedonic and incentive processes based on palatability and reward characteristics of food. In this review, I consider how learning about environmental cues influences homeostatic and hedonic brain signals, which may lead to increases in the affective taste properties of food and desire to over consume. Understanding these mechanisms may be critical for elucidating the etiology of the obesity epidemic.
Trends in Neurosciences 01/2013; 36(2). DOI:10.1016/j.tins.2013.01.002 · 13.56 Impact Factor
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