Peripheral oxytocin suppresses food intake and causes weight loss in diet-induced obese rats.

Growing evidence suggests that oxytocin plays an important role in the regulation of energy balance and that central oxytocin administration induces weight loss in diet-induced obese (DIO) animals. To gain a better understanding of how oxytocin mediates these effects, we examined feeding and neuronal responses to oxytocin in animals rendered obese following exposure to either a high-fat (HFD) or low-fat diet (LFD). Our findings demonstrate that peripheral administration of oxytocin dose-dependently reduces food intake and body weight to a similar extent in rats maintained on either diet. Moreover, the effect of oxytocin to induce weight loss remained intact in leptin receptor-deficient Koletsky (fa(k)/fa(k)) rats relative to their lean littermates. To determine whether systemically administered oxytocin activates hindbrain areas that regulate meal size, we measured neuronal c-Fos induction in the nucleus of the solitary tract (NTS) and area postrema (AP). We observed a robust neuronal response to oxytocin in these hindbrain areas that was unexpectedly increased in rats rendered obese on a HFD relative to lean, LFD-fed controls. Finally, we report that repeated daily peripheral administration of oxytocin in DIO animals elicited a sustained reduction of food intake and body weight while preventing the reduction of energy expenditure characteristic of weight-reduced animals. These findings extend recent evidence suggesting that oxytocin circumvents leptin resistance and induces weight-loss in DIO animals through a mechanism involving activation of neurons in the NTS and AP, key hindbrain areas for processing satiety-related inputs.

Alterations in activity and energy expenditure contribute to lean phenotype in Fischer 344 rats lacking the cholecystokinin-1 receptor gene.

CCK is hypothesized to inhibit meal size by acting at CCK1 receptors (CCK1R) on vagal afferent neurons that innervate the gastrointestinal tract and project to the hindbrain. Earlier studies have shown that obese Otsuka Long-Evans Tokushima Fatty (OLETF) rats, which carry a spontaneous null mutation of the CCK1R, are hyperphagic and obese. Recent findings show that rats with CCK1R-null gene on a Fischer 344 background (Cck1r(-/-)) are lean and normophagic. In this study, the metabolic phenotype of this rat strain was further characterized. As expected, the CCK1R antagonist, devazepide, failed to stimulate food intake in the Cck1r(-/-) rats. Both Cck1r(+/+) and Cck1r(-/-) rats became diet-induced obese (DIO) when maintained on a high-fat diet relative to chow-fed controls. Cck1r(-/-) rats consumed larger meals than controls during the dark cycle and smaller meals during the light cycle. These effects were accompanied by increased food intake, total spontaneous activity, and energy expenditure during the dark cycle and an apparent reduction in respiratory quotient during the light cycle. To assess whether enhanced responsiveness to anorexigenic factors may contribute to the lean phenotype, we examined the effects of melanotan II (MTII) on food intake and body weight. We found an enhanced effect of MTII in Cck1r(-/-) rats to suppress food intake and body weight following both central and peripheral administration. These results suggest that the lean phenotype is potentially driven by increases in total spontaneous activity and energy expenditure.

Mapping Molecular Datasets Back to the Brain Regions They are Extracted from: Remembering the Native Countries of Hypothalamic Expatriates and Refugees.

This article focuses on approaches to link transcriptomic, proteomic, and peptidomic datasets mined from brain tissue to the original locations within the brain that they are derived from using digital atlas mapping techniques. We use, as an example, the transcriptomic, proteomic and peptidomic analyses conducted in the mammalian hypothalamus. Following a brief historical overview, we highlight studies that have mined biochemical and molecular information from the hypothalamus and then lay out a strategy for how these data can be linked spatially to the mapped locations in a canonical brain atlas where the data come from, thereby allowing researchers to integrate these data with other datasets across multiple scales. A key methodology that enables atlas-based mapping of extracted datasets-laser-capture microdissection-is discussed in detail, with a view of how this technology is a bridge between systems biology and systems neuroscience.