GPR88 is a critical regulator of feeding and body composition in mice

Lau, Jackie; Farzi, Aitak; Enriquez, Ronaldo F.; Shi, Yan-Chuan; Herzog, Herbert

doi:10.1038/s41598-017-10058-x

Download PDF

Article
Open access
Published: 30 August 2017

GPR88 is a critical regulator of feeding and body composition in mice

Jackie Lau¹,
Aitak Farzi^1,2,
Ronaldo F. Enriquez¹,
Yan-Chuan Shi^1,3^na1 &
…
Herbert Herzog^1,3^na1

Scientific Reports volume 7, Article number: 9912 (2017) Cite this article

2817 Accesses
11 Citations
Metrics details

Subjects

Abstract

GPR88 is an orphan G-protein-coupled receptor with predominant expression in reward-related areas in the brain. While the lack of GPR88 has been demonstrated to induce behavioral deficits, the potential function of the receptor in the control of food intake and energy balance remains unexplored. In this work, the role of GPR88 in energy homeostasis was investigated in Gpr88 ^−/− mice fed either standard chow or high fat diet (HFD). Gpr88 ^−/− mice showed significantly reduced adiposity accompanied with suppressed spontaneous food intake, particularly pronounced under HFD treatment. While energy expenditure was likewise lower in Gpr88 ^−/− mice, body weight gain remained unchanged. Furthermore, deregulation in glucose tolerance and insulin responsiveness in response to HFD was attenuated in Gpr88 ^−/− mice. On the molecular level, distinct changes in the hypothalamic mRNA levels of cocaine-and amphetamine-regulated transcript (Cartpt), a neuropeptide involved in the control of feeding and reward, were observed in Gpr88 ^−/− mice. In addition, GPR88 deficiency was associated with altered expressions of the anorectic Pomc and the orexigenic Npy in the arcuate nucleus, especially under HFD condition. Together, our results indicate that GPR88 signalling is not only important for reward processes, but also plays a role in the central regulatory circuits for energy homeostasis.

Fasting-mimicking diet causes hepatic and blood markers changes indicating reduced biological age and disease risk

Article Open access 20 February 2024

From compulsivity to compulsion: the neural basis of compulsive disorders

Article 09 April 2024

Adipose tissue macrophages secrete small extracellular vesicles that mediate rosiglitazone-induced insulin sensitization

Article 11 April 2024

Introduction

Obesity occurs when chronic increase in energy intake significantly exceeds energy expenditure¹. Current pharmacological treatments for obesity, which primarily aim to suppress energy intake through reducing appetite or dietary fat absorption², have demonstrated limited effectiveness and efficacy³ and can also lead to complex side effects⁴. The discovery of novel and effective pharmacotherapeutic targets is therefore a high priority.

G-protein-coupled receptors (GPCRs) represent the largest membrane receptor family in the mammalian genome, with over 800 genes identified in humans^{5, 6}. Due to the fact that GPCRs are responding to various extracellular signals and thereby modulating diverse physiological processes⁶, more than 40% of clinically approved drugs target GPCRs to modulate their effects^{7, 8}. Despite rapid research progress that led to the deorphanization of more than 300 GPCRs in the past two decades, over 150 GPCRs still remain orphans^{9, 10}, among which a number were indicated as regulators of energy metabolism^{11, 12}, hence offering therapeutic promises for obesity.

One of these orphan GPCR candidates is GPR88. This receptor is predominantly expressed in striatal projection neurons, with high evolutionary conservation between humans and rodents in both primary structure and expression pattern, suggesting critical functional conservation^13,14,15,16. Associated with the reward network in the striatum, GPR88 has been implicated in numerous behaviors linked to neurological conditions in both rodents and humans, namely bipolar disorders, schizophrenia^17,18,19, responses to psychostimulant drugs²⁰ and antidepressants^{21, 22}, as well as learning and social behavior^{23, 24}. In addition to the abundant distribution throughout the striatum including the nucleus accumbens (Acb), caudate putamen (CPu) and olfactory tubercle, GPR88 expression is also enriched in inferior olive in the brainstem, cortex and amygdala^{13,14,15,16, 25, 26}, with minimal to absent expression in peripheral tissues^{13, 26, 27}. Interestingly, many of the GPR88-rich areas are involved in the reward processing system that is integrated and interrelated with the circuits controlling energy balance to direct downstream effects on appetite and food intake^{28, 29}. The functional implication with the anatomical distribution of GPR88 expression suggests a potential role of the receptor in regulating energy homeostasis, an underexplored area of GPR88 research.

The emerging potential of GPR88 in energy homeostatic regulation is supported by several lines of evidence. First, mice lacking Gpr88 globally showed over-represented striatal mRNAs that encoded proteins involved in cell response to nutrient levels and starvation, as revealed by microarray combined with gene ontology analysis¹⁶. In the same study, the most upregulated gene in the striatum of Gpr88 knockout mice compared with controls was the cocaine- and amphetamine-regulated transcript (Cartpt)¹⁶, a key neuropeptide central to the control of appetite and energy balance³⁰. Strikingly, microarray profiling in our Cartpt knockout mouse model³¹ revealed that Gpr88 was amongst the most significantly upregulated GPCR mRNAs in the hypothalamus compared to wild-type mice, despite moderate hypothalamic expression of the receptor^{13, 14, 25}. These correlative findings in the two genetic models indicate a potential function for GPR88 in the energy homeostatic circuit. Furthermore, plausible involvement of GPR88 in energy metabolism was denoted in an investigation of the sensitivity of individual abdominal white adipose depots to ghrelin exposure³², a gastric hormone that stimulates orexigenic hypothalamic neurons and plays a critical regulatory role in lipid storage and distribution^{33, 34}. In contrast with earlier studies reporting the absence or minimal expression of Gpr88 in peripheral tissues in rodents^{26, 27}, Gpr88 mRNA was identified to be more highly expressed in the ghrelin-unresponsive epididymal fat than the ghrelin-responsive retroperitoneal adipose tissue in rats³². The depot-specific Gpr88 expression may attribute to differential energy utilization and lipid handling mechanisms³² involving this receptor. Concordantly, in a separate microarray study, Gpr88 mRNA was upregulated in the hypothalamus following cold exposure in both leptin-deficient and wild-type mice³⁵. The leptin-independent alteration in expression regardless of the nutritional status indicated possible association of GPR88 with the mobilization of fuel reserves in cold-activated thermogenesis³⁵.

In this study, we aimed to elucidate the detailed function of GPR88 in the regulation of energy balance employing a germline Gpr88 knockout mouse model. As previous characterizations of GPR88-deficient models focused mainly on behavioral parameters and psychiatric contexts^{16, 20, 23, 25, 36, 37}, the present work offers the first insights into the physiological roles of this receptor in energy homeostatic control. The metabolic phenotypes as well as the underlying mechanisms were investigated. Effects of high fat diets on the manifestation of GPR88 deficiency were also addressed in comparison with standard chow feeds to examine the potential influence of Gpr88 deletion on diet-induced obesity.

Results

Absence of GPR88 signalling has no effect on body weight gain

Gpr88 ^−/− mice were born at the expected Mendelian ratios with equal gender ratio and litter size as controls (data not shown). In agreement with recent studies^{16, 23}, no significant differences in body weight or appearance were observed at birth between these mice and their control littermates (data not shown). Both male and female mice were studied under chow conditions, while only male mice were subjected to HFD treatment. Based on the data from extensive metabolic characterization, male and female mice demonstrated consistency for the majority of the phenotypic traits, with greater prominence in phenotypes in males. Hence, data for male mice are the main focus, while key data for female mice are included as supplementary figures. In order to study the baseline metabolic characteristics of this Gpr88 ^−/− model, and the effects of high fat dietary intervention, we first measured body weight (BW) gain and body composition under standard chow diet as well as HFD conditions.

Gpr88 ^−/− mice on both chow and HFD gained similar body weight to WT control mice when expressed in absolute value as well as a percentage of initial body weight (Fig. 1A). As expected, HFD-fed Gpr88 ^−/− and WT mice exhibited higher absolute body weight over time compared to mice on chow (Fig. 1A). However, there was no notable diet-related difference in percentage weight gain between mice from these two groups.

Lack of GPR88 signalling results in increased lean mass and augmented loss in fat mass on HFD

To investigate the influence of GPR88 on body composition, DXA analysis was performed. For males from both diet groups, whole body fat mass expressed as a percentage of body weight was reduced in Gpr88 ^−/− mice relative to WT controls at 16 weeks of age, significantly so under the HFD condition (Fig. 1B). This is consistently shown in female counterparts on chow (Figure S1). The lower fat mass in Gpr88 ^−/− mice was also confirmed by decreased mass of dissected white adipose tissue depots for both genders (Figs 1C and S2). No observable difference was detected in the weights of major organs between genotypes despite dietary conditions or genders (Figure S3). In contrast to the reduction in adiposity, whole body lean mass (presented as a percentage of body weight) was significantly increased in Gpr88 ^−/− mice compared to WT under HFD (Fig. 1D), but this was not seen in the chow cohort regardless of gender (Figs 1D and S4). As expected, other than greater baseline adipose masses (Fig. 1B,C), HFD-fed mice also exhibited lower baseline percentage lean mass with respect to chow-fed counterparts of the same genotypes (Fig. 1D). The coinciding of decreased fat mass and elevated lean mass in HFD-fed Gpr88 ^−/− mice (Fig. 1B,D) may be one of the reasons for the resultant unchanged body weight gain (Fig. 1A).

GPR88 signalling is involved in bone homeostasis under HFD conditions

In view of the variations in the body fat and lean contents, the influence of Gpr88 ablation on bone mineral density and content was also examined via DXA scans. No significant genotype difference was observed for either total body BMC (Figs 1E and S5) or BMD (Figures S5 and S6) for mice from either diet or gender groups. Nevertheless, a tendency towards an increased BMC was shown for chow-fed Gpr88 ^−/− mice compared with WT counterparts (Fig. 1E), which may possibly account for the unaltered weight gain (Fig. 1A) despite the lower fat mass in KO mice (Fig. 1B,C). In addition, femur length showed neither genotype- nor diet-related difference (Figure S7). However, consistent with previous reports^{38, 39} and as expected, WT mice displayed significantly greater BMC (Fig. 1E) and BMD (Figure S6) when fed a HFD compared to standard chow. Interestingly, for Gpr88 ^−/− mice, the HFD-induced increase in mineralization was only apparent for BMD (Figure S6) while absent for BMC (Fig. 1E), indicating that mice lacking GPR88 may exhibit altered responsiveness to the effects of high-fat feeding on specific bone parameters.

GPR88 deficiency reduces food intake and energy expenditure independent of diet

In light of the altered body composition, particularly reduced body fat mass, in Gpr88 ^−/− mice, we also investigated the effects of GPR88 deficiency on energy intake and energy expenditure^{1, 29, 40}. Interestingly, 24-hr spontaneous food intake was significantly decreased in Gpr88 ^−/− compared to WT mice regardless of dietary conditions or genders (Figs 2A and S8), probably contributing to the marked decline in fat mass seen in Gpr88 ^−/− mice across diets (Figs 1B,C and S1–2). Consistent with the substantially lower whole body fat mass (Fig. 1B), the reduction in food intake in KO mice relative to WTs was more significant when put on HFD compared to chow (Fig. 2A).

We also examined the other side of the energy balance equation and investigated energy expenditure using open-circuit indirect calorimetry. A substantial decrease in energy expenditure was shown in Gpr88 ^−/− males relative to WT controls on both diets (Fig. 2B,C), significantly so under a standard chow condition, throughout the entire photoperiod and particularly prominent during the dark phase. Such significant decrease was absent in female Gpr88 ^−/− counterparts (Figure S9). This reduced energy expenditure in male Gpr88 ^−/− mice may represent a compensatory response to the decreased food intake (Fig. 2A), resulting in an unaltered overall weight gain between genotypes (Fig. 1A). It is noteworthy that the lesser drop in energy expenditure in HFD-fed KO mice (Fig. 2B,C) correlated with the greater loss of body fat mass in the same mice (Fig. 1B) compared with chow-fed counterparts. However, no significant changes were seen in physical activity for both genders (Figs 2D,E and S10), indicating that the decreased energy expenditure in Gpr88 KO males was not due to any alteration in physical activity on either diet. Similarly, RER, an indicator of metabolic fuel selection, was comparable between Gpr88 ^−/− and WT mice under both diet conditions for both genders (Figs 2D,E and S11), suggesting GPR88 may not be involved in oxidative fuel preference. As expected, HFD-fed males of both genotypes showed a significantly lower RER compared with chow-fed counterparts (Fig. 2G), signifying an enhanced fuel source preference for fat over carbohydrate, likely due to the higher adiposity accrual available under a state of energy surplus.

GPR88 signalling may be involved in feeding under fasting conditions

Additional to evaluating feeding control during the fed state, the impact of GPR88 ablation on food intake was explored at a state of energy deficit induced by fasting. When expressed as absolute caloric energy values, there was no observable difference in fasting-induced food intake between genotypes on either chow or HFD treatment (Figs 3A and S12). In response to 24-hr fast, while the relative weight loss with respect to pre-fasting BW was unaltered between genotypes for the chow cohort (Figs 3B and S13), HFD-fed KO mice experienced substantially greater proportion of weight loss compared to WT (Fig. 3B). Furthermore, Gpr88 ^−/− mice exhibited accelerated BW recovery throughout refeeding with respect to WT controls under both diets, although this was only seen in males (Figs 3B and S13). This pattern of improved weight recovery was more dramatic in HFD cohort, with similar proportion of BW between genotypes at 24 hr after refeeding (Fig. 3B). Interestingly, when expressed as a percentage of body weight, fasting-induced food intake was comparable between Gpr88 ^−/− and WT mice under the chow condition regardless of genders (Figs 3C and S14). However, the genotype difference became statistically significant when challenged with HFD, with significantly increased fasting-induced feeding in Gpr88 ^−/− mice compared to WT controls (Fig. 3C), particularly at 7- and 24-hr time points following refeeding.

GPR88 knockout mice show differential expression of key hypothalamic peptides in the control of energy balance

To elucidate the central mechanisms underlying the GPR88-deficient phenotypes manifested under the two dietary conditions, hypothalamic expression of several neuropeptides pivotal in appetite control and energy metabolism was profiled. In situ hybridization was performed to determine the transcript expression of Cartpt, Pomc and Npy in the Arc (Fig. 4A), the two sets of first-order neurons that respond to circulating adiposity signals and traditionally classified as anorexigenic and orexigenic, respectively^41,42,43. Messenger RNA levels of Cartpt were also examined in the DMH and LHA of the hypothalamus (Fig. 4A,B), CART-rich regions also known to be involved in feeding behaviors and weight regulation^{44,45,46,47,48}. Significant increase in Cartpt mRNA level was observed in the Arc of Gpr88 ^−/− mice relative to WT controls (Fig. 4C), more prominently under HFD condition. In contrast, Cartpt expression in the DMH was significantly lower in Gpr88 ^−/− than WT mice on HFD (Fig. 4D), while the decrease was less notable in chow-fed KOs. In the LHA, where second-order effector neurons receive projections from the Arc^{43, 44}, Cartpt expression was pronouncedly downregulated in Gpr88 ^−/− mice compared to WT (Fig. 4E), with greater effect under chow condition.

Contrary to the upregulated Arc Cartpt (Fig. 4C), mRNA levels of the colocalized Pomc in the Arc^{49, 50} (Fig. 4F,G) showed a distinct decline in Gpr88 ^−/− relative to WT mice, more substantially when put on HFD (Fig. 4F). Interestingly, the opposite was shown for the expression of the adjacent Arc Npy (Fig. 4H,I), which was significantly upregulated in HFD-fed Gpr88 ^−/− mice only (Fig. 4H), although no difference was detected between genotypes for the chow fed cohort. The expression changes in Gpr88 ^−/− mice on HFD were generally more prominent compared with chow-fed counterparts for all three neuropeptides at the hypothalamic areas examined (Fig. 4C,D,F,H), with the exception of LHA Cartpt (Fig. 4E).

With regard to diet effects, baseline expressions of both Npy (Fig. 4H) and Cartpt (Fig. 4C) in the Arc were both notably downregulated in WT controls when fed HFD compared to standard chow, significantly so for NPY. In contrast, notable upregulation was shown for Arc Pomc (Fig. 4F) and significantly for DMH Cartpt (Fig. 4D) in WT mice on HFD relative to chow diet. Remarkably, the prominent diet-induced effects were absent in GPR88-deficient mice regardless of the genes or areas of interest (Fig. 4), indicating potential resistance to certain neurochemical consequences following chronic high-fat feeding in the absence of GPR88.

GPR88 deficiency alleviates deregulation in glucose tolerance and insulin responsiveness associated with HFD treatment

In light of the well-established link between fat metabolism and glucose homeostasis⁵¹, and based on the decreased fat content in Gpr88 knockout mice, various parameters of glucose metabolism were investigated. Following i.p. glucose challenge, blood glucose levels throughout the 90 min duration were indistinguishable between WT and Gpr88 ^−/− mice on chow (Fig. 5A). In contrast, when fed a HFD, Gpr88 ^−/− mice demonstrated significantly lower blood glucose levels compared with WT during the course of IPGTT (Fig. 5A), despite comparable basal levels upon 6-hr fasting and similarly shaped blood glucose response curves. Although both genotypes showed markedly greater blood glucose levels when put on HFD, Gpr88 ^−/− mice exhibited significantly improved glucose clearance relative to WT (Fig. 5A). Concordantly, the relatively enhanced glucose response indicated for Gpr88 ^−/− mice on HFD was reflected in the strong trend of reduction in the area under the glucose curve with respect to WT (Fig. 5B). Such genotype difference in AUCglucose was absent in the chow cohorts (Fig. 5B). Interestingly, despite differential blood glucose responses in HFD group, no significant difference was shown in the corresponding serum insulin levels during IPGTT between Gpr88 ^−/− and WT mice under both diet conditions (Fig. 5C). The lack of substantial difference was also shown in the area under the insulin curve (AUCinsulin) (Fig. 5D). However, while similarly shaped patterns of insulin response were observed, KO mice on HFD appeared to exhibit a trend of dampened glucose-stimulated insulin secretion compared to WT counterparts (Fig. 5C). This suggests that lower insulin release may be sufficient to efficiently eliminate glucose in GPR88-deficient mice.

Insulin responsiveness was examined using the IPITT test. While chow-fed WT and Gpr88 ^−/− mice displayed comparable blood glucose levels in response to IPITT (Fig. 5E) during 0–30 min, KO mice demonstrated a generally steeper decline, where the blood glucose levels became significantly decreased at the lowest point at 60 min compared to WT (Fig. 5E). Interestingly, when put on HFD, Gpr88 ^−/− mice showed a significant decrease in blood glucose throughout the 90 min period compared with WT, with similar initial fasted blood glucose levels at 0 min (Fig. 5E), as reflected by the corresponding AUCglucose (Fig. 5F). Consistent with insulin levels from IPGTT at a 6-hr fasted state, plasma insulin levels in Gpr88 ^−/− mice during the control fed state were unchanged on chow diet, and significantly lower on HFD, when compared to WT (Fig. 5G). Unlike the higher baseline insulin seen in mice of both genotypes on HFD relative to chow (Fig. 5G), no difference was detected for baseline glucose levels between genotypes or diet groups (Fig. 5H). The improved glucose tolerance in Gpr88 KO mice on HFD was thus attributed to the greater insulin responsiveness, which may be secondary to the higher lean mass⁵² observed compared to WT (Fig. 1D).

Discussion

While considerable efforts have been made to explore the role of GPR88 in reward and behavioral aspects, our work provides the first evidence that GPR88 also influences the regulation of energy homeostasis at various levels. This is clearly demonstrated in mice lacking GPR88, which showed a significant decrease in adiposity associated with marked reduction in daily spontaneous food intake under chow and high fat diet conditions, without any change in body weight gain. This was also accompanied by a distinct decline in energy expenditure in Gpr88 ^−/− mice compared with controls, with unchanged physical activity and RER. At an energy-deficit state following fasting, refeeding-food intake was substantially increased in Gpr88 ^−/− mice fed a HFD while unaltered for chow-fed counterparts. Moreover, when challenged with HFD, Gpr88 ^−/− mice showed a significant increase in lean mass. This, together with decreased fat mass, could contribute at least partially to the improved insulin responsiveness and thus glucose tolerance seen in Gpr88 ^−/− mice on HFD, which showed unaffected insulin secretion. We also demonstrated that lack of GPR88 has less effect on bone metabolism. Mechanistically, Cartpt expression in Gpr88 ^−/− mice on HFD was increased in the Arc and reduced in the DMH respectively, in line with the anorectic phenotype. However, since lower Pomc and higher Npy mRNA levels in the Arc were also displayed in the same mice, CART may play a more critical role in determining the feeding behavior in GPR88-deficient mice.

The effects of Gpr88 deletion on feeding behavior and body composition consistently suggested the orexigenic potential of this receptor. Although the impact of Gpr88 ablation on appetite regulation was unexplored in previous studies^{16, 20, 23, 25, 36, 37}, mice lacking Gpr88 were reported to show reduced novelty-suppressed feeding³⁷. The altered feeding behaviour³⁷ possibly attributed to the impaired cue-based learning shown in a separate study in a Gpr88 ^−/− mouse model identical to that used in the present work¹⁶, hence indirectly endorsing the decreased basal food intake in the fed state observed herein. Interestingly, in this study, Gpr88 ^−/− mice exhibited decreased spontaneous food intake but increased fasting-induced food intake under HFD, indicating differential roles of GPR88 in the regulation of food consumption under varying states of energy status. Since WT mice typically experience less weight loss following energy deprivation when fed a HFD relative to chow⁵³, the advantage in weight reservation conferred by a fat-rich diet may be abolished in the absence of GPR88.

In the present study, we demonstrated a decrease in energy expenditure in Gpr88 ^−/− mice, which predicts an increased body weight gain⁴⁰. However, this effect was potentially cancelled out by the lower food consumption, leading to an overall unaltered weight gain in Gpr88 ^−/− mice. In spite of an unchanged weight gain in Gpr88 ^−/− mice, the body composition was altered, such that body fat mass was increased and lean mass was reduced when challenged with HFD. The augmented drop in adiposity in Gpr88 ^−/− mice on HFD than chow suggested that GPR88 may function as part of the biological defense of elevated body fat during obesity development²⁹. Interestingly, despite the lower energy expenditure, no change was observed in the RER and physical activity, although other groups have reported involvement of the receptor in locomotor activity and responses^{16, 37, 54}. The discrepancy may be explained partly by the distinct age- and gender-factors involved, as well as the different methods of measurements, as the majority of literature on GPR88 adopted behavioral tests. In addition, alterations in GPR88 expression in various brain regions have been documented in WT mice under various stress conditions and environments⁵⁵, affecting diverse cognitive and emotional processing³⁶. Accordingly, manifestation of GPR88-deficiency on different settings may engage distinctive behavioral and motor responses.

The wide expression of GPR88 in the brain^{13, 14, 54}, together with the evident alterations in aspects of energy homeostasis on a Gpr88-negative background, suggested modulations in the central circuits for energy balance. Intriguingly, despite predominant expression in the striatum^{13, 14, 54}, latest single cell RNA sequencing data revealed minute levels of Gpr88 expression in Npy- and Cartpt/Pomc-containing neurons in the mouse hypothalamus⁵⁶. In line with this, results from the present work also distinctively support the novel association between GPR88 and specific hypothalamic neuropeptides implicated in appetite and weight regulation. First, differential Cartpt mRNA expression was displayed in Gpr88 ^−/− mice at various feeding-related regions, namely a general upregulation in the Arc and downregulation in the DMH and LHA under both diet conditions, in line with the reduced feeding observed. Despite controversies surrounding CART function in feeding control³⁰, increase in the classically anorexigenic Arc Cartpt levels may contribute to the suppressed basal food intake in Gpr88 KO, both parameters with greater genotype difference when fed a HFD. Additionally, among other hypothalamic regions, DMH and LHA have been considered orexigenic or hunger centers, as lesions in each area individually led to hypophagia and weight loss^57,58,59. Since heightened Cartpt transcript levels in the DMH and LHA were linked to elevation in feeding and body weight⁶⁰, the anorectic effects seen in Gpr88 KO may also attribute to the declined Cartpt expression in these two areas, both with indicated involvement in the orexigenic activity of CART^{46, 60, 61}. The varying hypothalamic changes in Cartpt expression in Gpr88 KO, namely higher in the Arc and lower in the DMH and LHA, hence collectively endorse the inhibited spontaneous food intake, which indirectly led to reduced fat mass and increased lean mass, particularly when challenged with HFD treatment. The results conjointly support a novel role of GPR88 as an orexigenic signal. Contrastingly, in spite of the substantially higher expression of the orexigenic Npy and lower levels of the anorexigenic Pomc in the Arc, KO mice demonstrated a hypophagic phenotype. Whilst the suppressed Pomc levels may represent a counter-regulatory response to the elevated Arc Cartpt, CART effects on the overall food intake of Gpr88 ^−/− mice were suggested to be stronger than impacts from the altered expression of either Npy or Pomc. Nevertheless, other possible mechanisms together with the regulations in hypothalamic neuropeptides may have effectively counteracted the anorexigenic outcome of Gpr88 deficiency, resulting in comparable weight gain between genotypes on both diets. GPR88 is thus indicated as a novel component of the complex interplay between the orexigenic or anorexigenic pathways that fine-tune feeding behavior. Further studies characterizing the extensive neurochemical profile of Gpr88 KO mice will provide valuable insights into the inferred function for the receptor.

In conclusion, this work is the first direct evidence for a physiological role of GPR88 in the regulation of energy balance. The data suggest that under a chow-diet condition, GPR88 may be important in the regulation of food intake, adiposity, energy expenditure and bone mineralization. However, active involvement of the receptor was not indicated in other metabolic aspects, such as physical activity or metabolic fuel selection. Under conditions of diet-induced obesity, Gpr88 ablation improved body lean content, weight recovery and feeding following fasting, insulin responsiveness and glucose tolerance. The metabolic changes were mechanistically associated with Cartpt expression that was increased in the Arc and diminished in the DMH respectively. GPR88 in mice is thus proposed to promote fat deposition, enhance appetite as well as energy expenditure. While the manifestation of GPR88 effects may be augmented by dietary manipulation, such as in a state of chronic energy surplus induced by high-fat feeding, ablation of Gpr88 alone was insufficient to influence overall body weight. In other words, stimulation of GPR88 signalling is conjectured to trigger hyperphagia and increase susceptibility to obesity, whereas such obesogenic drive may be counteracted by feedback regulatory mechanisms efficiently to boost metabolism and prevent excessive adipose deposition. This is supported by the dichotomous alterations of hypothalamic neuropeptides with anorexigenic and orexigenic properties in GPR88-deficient mice, implicating an interactive element to GPR88 in the system of energy homeostatic efficiency. Future research elucidating the pharmacology and neurochemical dynamics of GPR88 will shed light on the therapeutic potential of this orphan receptor in obesity treatment. Findings from this study suggest that targeting GPR88 could have beneficial effects in modulating fat accretion, feeding behavior, and glucose homeostasis in obesity-related comorbidities.

Materials and Methods

Animals and grouping

All research and animal care procedures were approved by the Garvan Institute/St. Vincent’s Hospital Animal Ethics Committee and were in agreement with the Australian Code of Practice for the Care and Use of Animals for Scientific Purposes. The Gpr88 knockout mice (Gpr88 ^−/−) were a generous gift from Prof. Richard Palmiter (University of Washington, USA), with targeting strategies described in detail previously¹⁶. All mice were housed under conditions of controlled temperature of 22 °C and illumination (12:12 hr light-dark cycle, lights on at 07:00 hr). Mice were provided with ad libitum access to water and either standard chow diet (8% calories from fat, 21% calories from protein, 71% calories from carbohydrate, 2.6 kilocalorie (kcal)/g; Gordon’s Specialty Stock Feeds, Yanderra, NSW, Australia) or high fat diet (HFD, 23% calories from fat, 19.4% calories from protein, 48.2% calories from carbohydrate, 4.7% calories from crude fibre, 4.7% calories from acid detergent fibre, 4.78 kcal/g; Gordon’s Specialty Feeds, Glen Forrest, WA, Australia) according to grouping. Both male and female mice were used for all experiments under chow conditions, whereas only male mice were subjected to HFD treatment.

All mice were initially fed a standard laboratory chow diet. At 8 weeks (wks) of age, subsets of mice from both the Gpr88 knockout (KO; Gpr88 ^−/−)¹⁶ and wild-type (WT) groups were subjected to HFD feeding for 10 wk until sacrifice at 18 wk of age. The remaining subsets of mice continued on the standard chow diet. The same experimental procedures were performed on both chow- and HFD-fed groups in an age-matched manner.

Determination of body weight and food intake

All Gpr88 ^−/− and WT mice fed on standard chow diet or HFD were subject to the same experimental procedures as follows. Body weight was measured weekly throughout the duration of studies. Mice were assessed for spontaneous/basal food intake in the fed state as well as for fasting-induced food intake in response to 24-hr fasting at 12 wks of age. In brief, mice were transferred from group housing on soft bedding to individual cages with paper towel bedding for 3 nights of acclimatization. Basal daily food intake was determined as the average of duplicate readings obtained over two consecutive 24-hr periods. Twenty four-hr fasting-induced food intake was subsequently measured at 1, 3, 7, and 24 hr after refeeding with the respective types of diet, while the corresponding body weight was recorded in parallel.

Indirect calorimetry of energy expenditure and fuel source preference

All mice from both chow- and HFD-fed groups were evaluated for metabolic parameters and physical activity at 16 wk of age. For energy metabolism, metabolic rate was measured by indirect calorimetry using an 8-chamber open-circuit calorimeter (Oxymax series; Columbus Instruments, Columbus, OH, USA). Mice were housed individually in specially built Plexiglas cages (20.1 × 10.1 × 12.7 cm). Temperature was maintained at 22 °C with airflow of 0.6 L/min. Mice were singly housed for 3 days in home cages prior to acclimatization in Plexiglas cages for 24 hr before commencement of recording. Monitoring was subsequently performed for 24 hr in the metabolic chambers. Mice were provided with ad libitum access to water and food of respective diet types. Body weight was measured and food given in excess was weighed before and after the recording period for the quantification of daily food intake after subtraction of spillage. Oxygen consumption (VO₂) and carbon dioxide production (VCO₂) were measured every 27 min. The respiratory exchange ratio (RER) was calculated as the quotient of VCO₂/VO₂, with 100% carbohydrate oxidation represented by the value of 1.0 and 100% fat oxidation the value of 0.7. Energy expenditure (kcal heat produced) was determined as calorific value (CV) x VO₂, where CV is 3.815 + 1.232 x RER. Data obtained for the 24-hr monitoring period were averaged at 1-hr intervals for energy expenditure and RER.

Body composition and bone densitometry analysis

All mice from both chow- and HFD-fed groups were subjected to an initial body composition analysis using the dual-energy X-ray absorptiometry (DXA, Lunar PIXImus2 mouse densitometer; GE Healthcare, Waukesha, WI, USA) system at 10 wk of age. A second DXA scan was performed 6 wk after initial DXA measurements at 16 wk of age, immediately following completion of the indirect calorimetry assessment of energy metabolism and physical activity. Animals were anesthetized with isoflurane for the scanning procedure to determine whole body bone mineral density (BMD), bone mineral content (BMC), fat and lean mass, where lean mass corresponds to non-fat and non-bone tissue content. The head of the animal was excluded while the tail included for the analysis.

Glucose metabolism studies

All mice from both chow- and HFD-fed cohorts were examined by intraperitoneal glucose tolerance test (IPGTT) and insulin tolerance test (IPITT). IPGTT and IPITT were conducted at 14 and 17 wk of age respectively. For IPGTT, mice were subjected to 6-hr fasting where food was removed from cage hoppers at 09:00 hr and injection of a dose of a 10% D-glucose solution (1.0 g/kg body weight; Astra Zeneca, North Ryde, NSW, Australia) was performed 6 hr later into the peritoneal cavity. For IPITT, mice were subjected to 5-hr fasting where food was removed from cage hoppers at 10:00 hr and injection of a dose of insulin (0.5 IU/kg body weight) (Novo Nordisk Pharmaceuticals, Baulkham Hills, NSW, Australia) was performed 5 hr later into the peritoneal cavity. For both tests, tail vein blood was collected at 0, 15, 30, 60, 90 min following glucose or insulin injection and glucose concentrations were measured using a glucometer (Accu-Check II; Roche, Castle Hill, NSW, Australia). For IPGTT, insulin levels were subsequently quantified using a sensitive rat insulin radioimmunoassay (RIA) kit (Millipore, Billerica, MA, USA). Glucose and insulin tolerance curves constructed for the glucose levels obtained during IPGTT and IPITT respectively are presented in terms of absolute values. Area under the glucose (AUCglucose) or insulin (AUCinsulin) concentration curves between 0 and 90 min after glucose injection during IPGTT were plotted after subtraction of the initial concentrations prior to injection.

Tissue collection

Following completion of studies, all mice from both chow- and HFD-fed groups were sacrificed at 18 wk of age. Animals were culled between 13:00 to 17:00 hr through cervical dislocation followed by decapitation. Brains were promptly collected and frozen on dry ice, then stored at −80 °C until subsequent analysis as described below. The white adipose tissue (WAT) depots from the inguinal, epididymal or periovarian (gonadal), retroperitoneal and mesenteric regions were removed and weighed. Tissue weights are normalized and expressed as a percentage of body weight.

In situ hybridization analysis of major hypothalamic neuropeptides

In situ hybridization was conducted on brain sections of WT (n ≥ 7) and Gpr88 ^−/− (n ≥ 5) mice from chow- and HFD-fed groups to determine mRNA expression of Cartpt, proopiomelanocortin (Pomc) and neuropeptide Y (Npy) at the hypothalamus following procedures as previously described^{31, 62}. Briefly, matching coronal brain sections (25 µm) collected from the WT and Gpr88 ^−/−mice were prepared from specific brain levels with respect to the bregma to represent the hypothalamic areas involved in the regulation of energy homeostasis. Brain sections from mice of both genotypes and diet groups were processed in parallel for quantitative comparison. Detection of the mRNA expression was performed for Cartpt, Npy, and Pomc in the arcuate nucleus (Arc), as well as Cartpt in the dorsomedial hypothalamic nucleus (DMH) and lateral hypothalamic area (LHA). The cryosections were hybridized with [α-³⁵S]-thio-dATP (PerkinElmer, Boston, MA, USA) radiolabelled DNA oligonucleotides complementary to mouse Cartpt (5′-TCCTTCTCGTGGGACGCATCATCCACGGCAGAGTA GATGTCCAGG-3′), Npy (5′-GAGGGTCAGTCCACACAGCCCCATTCGCTTG TTACCTAGCAT-3′), and Pomc (5′-TGGCTGCTCTCCAGGCACCAGC TCCACACATCTATGGA-GG-3′). Hybridization signals on sections were visualized by exposure to BioMax MR film (Kodak, Rochester, NY, USA) for 7–10 days and digitalized images from the scanned autoradiograms were acquired. For structural details, the brain sections were photoemulsion-dipped and superficially counterstained with haematoxylin, with which regions of interest were visualized and captured into digital images acquired by bright-field microscopy. Quantification of the mRNA expression levels of respective genes was performed by measuring the relative optical densities (RODs) within the brain areas of interest outlined with consistent defined dimensions across corresponding sections on the photomicrographs using the National Institutes of Health ImageJ 1.61 software (written by Wayne Rasband; available from anonymous FTP at zippy.nimh.nih.gov). Background labelling was considered uniform with signal levels below 5% of specific signal levels and was subtracted from the resultant signal density. Data are evaluated and presented as percentage of ROD averaged from at least three sections per mRNA assessed per animal.

Statistical analysis

All data are presented as means ± SEM. Differences amongst mouse groups of various genotypes and dietary treatments were assessed by ANOVA or repeated-measures ANOVA combined with Bonferroni post-hoc analysis where appropriate. Energy expenditure, RER and physical activity over the continuous 24-hr period were averaged for the whole 24-hr period, as well as the 12-hr light and dark phases individually. Comparison of energy expenditure (kcal/hr) between groups was performed by the analysis of covariance (ANCOVA) with lean mass as the covariate. The adjusted means of energy expenditure at a common lean mass for the comparison were generated by ANCOVA as presented. Statistical analyses were performed with GraphPad Prism 6 for Mac OS X (GraphPad Software, Inc. CA, USA) and SPSS for Mac OS X version 16.0.1 (SPSS Inc., Chicago, IL, USA). Statistical significance was defined as p-value ≤ 0.05.

Data availability

The datasets generated and analysed during the current study are available from the corresponding author on reasonable request.

References

Rosen, E. D. & Spiegelman, B. M. Adipocytes as regulators of energy balance and glucose homeostasis. Nature 444, 847–853 (2006).
Article ADS CAS PubMed PubMed Central Google Scholar
Eckel, R. H. Clinical practice. Nonsurgical management of obesity in adults. N. Engl. J. Med. 358, 1941–1950 (2008).
CAS PubMed Google Scholar
Lucchetta, R. C. et al. Systematic review and meta-analysis of the efficacy and safety of amfepramone and mazindol as a monotherapy for the treatment of obese or overweight patients. Clinics (Sao Paulo) 72, 317–324 (2017).
Article Google Scholar
Nguyen, N. et al. A review of unmet needs in obesity management. Obes. Surg. 22, 956–966 (2012).
Article CAS PubMed Google Scholar
Fredriksson, R., Lagerstrom, M. C., Lundin, L. G. & Schioth, H. B. The G-protein-coupled receptors in the human genome form five main families. Phylogenetic analysis, paralogon groups, and fingerprints. Mol. Pharmacol. 63, 1256–1272 (2003).
Article CAS PubMed Google Scholar
Katritch, V., Cherezov, V. & Stevens, R. C. Diversity and modularity of G protein-coupled receptor structures. Trends Pharmacol. Sci. 33, 17–27 (2012).
Article CAS PubMed Google Scholar
Garland, S. L. Are GPCRs still a source of new targets? J. Biomol. Screen. 18, 947–966 (2013).
Article CAS PubMed Google Scholar
Kinch, M. S., Hoyer, D., Patridge, E. & Plummer, M. Target selection for FDA-approved medicines. Drug Discov. Today 20, 784–789 (2015).
Article PubMed Google Scholar
Ngo, T. et al. Identifying ligands at orphan GPCRs: current status using structure-based approaches. Br. J. Pharmacol. 173, 2934–2951 (2016).
Article CAS PubMed Google Scholar
Davenport, A. P. et al. International Union of Basic and Clinical Pharmacology. LXXXVIII. G protein-coupled receptor list: recommendations for new pairings with cognate ligands. Pharmacol. Rev. 65, 967–986 (2013).
Article CAS PubMed PubMed Central Google Scholar
Ahmad, R., Wojciech, S. & Jockers, R. Hunting for the function of orphan GPCRs - beyond the search for the endogenous ligand. Br. J. Pharmacol. 172, 3212–3228 (2015).
Article CAS PubMed Google Scholar
Nagata, K., Katayama, Y., Sato, T., Kwon, Y. & Kawabata, T. Toward the next step in G protein-coupled receptor research: a knowledge-driven analysis for the next potential targets in drug discovery. J. Struct. Funct. Genomics 17, 111–133 (2017).
Article Google Scholar
Mizushima, K. et al. A Novel G-Protein-Coupled Receptor Gene Expressed in Striatum. Genomics 69, 314–321 (2000).
Article CAS PubMed Google Scholar
Massart, R., Guilloux, J.-P., Mignon, V., Sokoloff, P. & Diaz, J. Striatal GPR88 expression is confined to the whole projection neuron population and is regulated by dopaminergic and glutamatergic afferents. Eur. J. Neurosci. 30, 397–414 (2009).
Article PubMed Google Scholar
Van Waes, V., Tseng, K. Y. & Steiner, H. GPR88 - a putative signaling molecule predominantly expressed in the striatum: Cellular localization and developmental regulation. Basal Ganglia 1, 83–89 (2011).
Article PubMed PubMed Central Google Scholar
Quintana, A. et al. Lack of GPR88 enhances medium spiny neuron activity and alters motor- and cue-dependent behaviors. Nat. Neurosci. 15, 1547–1555 (2012).
Article CAS PubMed PubMed Central Google Scholar
Ogden, C. A. et al. Candidate genes, pathways and mechanisms for bipolar (manic-depressive) and related disorders: an expanded convergent functional genomics approach. Mol. Psychiatry 9, 1007–1029 (2004).
Article CAS PubMed Google Scholar
Del Zompo, M. et al. Association study in three different populations between the GPR88 gene and major psychoses. Mol. Genet. Genomic Med. 2, 152–159 (2014).
Article PubMed Google Scholar
Brandish, P. E. et al. Regulation of Gene Expression by Lithium and Depletion of Inositol in Slices of Adult Rat Cortex. Neuron 45, 861–872 (2005).
Article CAS PubMed Google Scholar
Ingallinesi, M. et al. Local inactivation of Gpr88 in the nucleus accumbens attenuates behavioral deficits elicited by the neonatal administration of phencyclidine in rats. Mol. Psychiatry (2014).
Conti, B. et al. Region-specific transcriptional changes following the three antidepressant treatments electro convulsive therapy, sleep deprivation and fluoxetine. Mol. Psychiatry 12, 167–189 (2006).
Article PubMed Google Scholar
Boehm, C. et al. Effects of antidepressant treatment on gene expression profile in mouse brain: cell type-specific transcription profiling using laser microdissection and microarray analysis. J. Neurochem. 97, 44–49 (2006).
Article CAS Google Scholar
Zhang, K., Hill, K., Labak, S., Blatt, G. J. & Soghomonian, J. J. Loss of glutamic acid decarboxylase (Gad67) in Gpr88-expressing neurons induces learning and social behavior deficits in mice. Neuroscience 275, 238–247 (2014).
Article CAS PubMed Google Scholar
Alkufri, F., Shaag, A., Abu-Libdeh, B. & Elpeleg, O. Deleterious mutation in GPR88 is associated with chorea, speech delay, and learning disabilities. Neurol. Genet. 2, e64 (2016).
Article PubMed PubMed Central Google Scholar
Logue, S. F. et al. The orphan GPCR, GPR88, modulates function of the striatal dopamine system: A possible therapeutic target for psychiatric disorders? Mol. Cell. Neurosci. 42, 438–447 (2009).
Article CAS PubMed Google Scholar
Becker, J. A. J. et al. Transcriptome analysis identifies genes with enriched expression in the mouse central extended amygdala. Neuroscience 156, 950–965 (2008).
Article CAS PubMed PubMed Central Google Scholar
Ghate, A. et al. Identification of novel striatal genes by expression profiling in adult mouse brain. Neuroscience 146, 1182–1192 (2007).
Article CAS PubMed Google Scholar
Myers, M. G. Jr., Munzberg, H., Leinninger, G. M. & Leshan, R. L. The geometry of leptin action in the brain: more complicated than a simple ARC. Cell Metab. 9, 117–123 (2009).
Article CAS PubMed PubMed Central Google Scholar
Guyenet, S. J. & Schwartz, M. W. Clinical review: Regulation of food intake, energy balance, and body fat mass: implications for the pathogenesis and treatment of obesity. J. Clin. Endocrinol. Metab. 97, 745–755 (2012).
Article CAS PubMed PubMed Central Google Scholar
Lau, J. & Herzog, H. CART in the Regulation of Appetite and Energy Homeostasis. Front. Neurosci. 8 (2014).
Lau, J., Shi, Y. C. & Herzog, H. Temperature dependence of the control of energy homeostasis requires CART signaling. Neuropeptides (2016).
Davies, J. S. et al. Ghrelin induces abdominal obesity via GHS-R-dependent lipid retention. Mol. Endocrinol. 23, 914–924 (2009).
Article CAS PubMed PubMed Central Google Scholar
Cowley, M. A. et al. The Distribution and Mechanism of Action of Ghrelin in the CNS Demonstrates a Novel Hypothalamic Circuit Regulating Energy Homeostasis. Neuron 37, 649–661 (2003).
Article CAS PubMed Google Scholar
Burger, K. S. & Berner, L. A. A functional neuroimaging review of obesity, appetitive hormones and ingestive behavior. Physiol. Behav. 136, 121–127 (2014).
Article CAS PubMed PubMed Central Google Scholar
Jaroslawska, J., Chabowska-Kita, A., Kaczmarek, M. M. & Kozak, L. P. Npvf: Hypothalamic Biomarker of Ambient Temperature Independent of Nutritional Status. PLOS Genetics 11, e1005287 (2015).
Article PubMed PubMed Central Google Scholar
Meirsman, A. C. et al. Mice Lacking GPR88 Show Motor Deficit, Improved Spatial Learning, and Low Anxiety Reversed by Delta Opioid Antagonist. Biol. Psychiatry 79, 917–927 (2016).
Article CAS PubMed Google Scholar
Meirsman, A. C., Robe, A., de Kerchove d’Exaerde, A. & Kieffer, B. L. GPR88 in A2AR Neurons Enhances Anxiety-Like Behaviors. eNeuro 3 (2016).
Sawin, E. A. et al. Differential Effects of Dietary Fat Content and Protein Source on Bone Phenotype and Fatty Acid Oxidation in Female C57Bl/6 Mice. PLoS One 11, e0163234 (2016).
Article PubMed PubMed Central Google Scholar
Ionova-Martin, S. S. et al. Reduced size-independent mechanical properties of cortical bone in high-fat diet-induced obesity. Bone 46, 217–225 (2010).
Article CAS PubMed Google Scholar
Galgani, J. & Ravussin, E. Energy metabolism, fuel selection and body weight regulation. Int. J. Obes. (Lond.) 32(Suppl 7), S109–119 (2008).
Article CAS Google Scholar
Elmquist, J. K., Maratos-Flier, E., Saper, C. B. & Flier, J. S. Unraveling the central nervous system pathways underlying responses to leptin. Nat. Neurosci. 1, 445–450 (1998).
Article CAS PubMed Google Scholar
Barsh, G. S. & Schwartz, M. W. Genetic approaches to studying energy balance: perception and integration. Nat. Rev. Genet. 3, 589–600 (2002).
CAS PubMed Google Scholar
Schwartz, M. W., Woods, S. C., Porte, D., Seeley, R. J. & Baskin, D. G. Central nervous system control of food intake. Nature 404, 661–671 (2000).
CAS PubMed Google Scholar
Elias, C. F. et al. Leptin Differentially Regulates NPY and POMC Neurons Projecting to the Lateral Hypothalamic Area. Neuron 23, 775–786 (1999).
Article CAS PubMed Google Scholar
Douglass, J., McKinzie, A. & Couceyro, P. PCR differential display identifies a rat brain mRNA that is transcriptionally regulated by cocaine and amphetamine. J. Neurosci. 15, 2471–2481 (1995).
CAS PubMed Google Scholar
Abbott, C. R. et al. Evidence of an Orexigenic Role for Cocaine- and Amphetamine-Regulated Transcript after Administration into Discrete Hypothalamic Nuclei. Endocrinology 142, 3457–3463 (2001).
Article CAS PubMed Google Scholar
Koylu, E. O. et al. Immunohistochemical localization of novel CART peptides in rat hypothalamus, pituitary and adrenal gland. J.Neuroendocrinol. 9, 823–833 (1997).
Article CAS PubMed Google Scholar
Kristensen, P. et al. Hypothalamic CART is a new anorectic peptide regulated by leptin. Nature 393, 72–76 (1998).
Article ADS CAS PubMed Google Scholar
Elias, C. F. et al. Leptin Activates Hypothalamic CART Neurons Projecting to the Spinal Cord. Neuron 21, 1375–1385 (1998).
Article CAS PubMed Google Scholar
Vrang, N., Larsen, P. J., Clausen, J. T. & Kristensen, P. Neurochemical Characterization of Hypothalamic Cocaine-Amphetamine-Regulated Transcript Neurons. J. Neurosci. 19, RC5 (1999).
CAS PubMed Google Scholar
Modan, M. et al. Hyperinsulinemia. A link between hypertension obesity and glucose intolerance. J. Clin. Invest. 75, 809–817 (1985).
Article CAS PubMed PubMed Central Google Scholar
Kwankaew, J., Saetung, S., Chanprasertyothin, S., Leelawattana, R. & Rattarasarn, C. Lean mass inversely predicts plasma glucose levels after oral glucose load independent of insulin secretion or insulin sensitivity in glucose intolerance subjects. Endocr. J. 61, 77–83 (2014).
Article CAS PubMed Google Scholar
Dudele, A. et al. Effects of ambient temperature on glucose tolerance and insulin sensitivity test outcomes in normal and obese C57 male mice. Physiol. Rep. 3 (2015).
Logue, S. F. et al. The orphan GPCR, GPR88, modulates function of the striatal dopamine system: A possible therapeutic target for psychiatric disorders? Mol. Cell. Neurosci. 42, 438–447 (2009).
Article CAS PubMed Google Scholar
Ubaldi, M. et al. Biomarkers of hippocampal gene expression in a mouse restraint chronic stress model. Pharmacogenomics 16, 471–482 (2015).
Article CAS PubMed Google Scholar
Romanov, R. A. et al. Molecular interrogation of hypothalamic organization reveals distinct dopamine neuronal subtypes. Nat. Neurosci. 20, 176–188 (2017).
Article CAS PubMed Google Scholar
Bellinger, L. L., Castonguay, T. W. & Bernardis, L. L. Hormone and somatic changes in rats pair-fed to growth retarded dorsomedial hypothalamic nuclei-lesioned rats. Brain Res. Bull. 34, 117–124 (1994).
Article CAS PubMed Google Scholar
Bellinger, L. L. & Bernardis, L. L. The dorsomedial hypothalamic nucleus and its role in ingestive behavior and body weight regulation: lessons learned from lesioning studies. Physiol. Behav. 76, 431–442 (2002).
Article CAS PubMed Google Scholar
Hirvonen, M. D. & Keesey, R. E. The specific locus and time course of the body protein adjustments produced in rats by lesions of the lateral hypothalamus. Physiol. Behav. 60, 725–731 (1996).
Article CAS PubMed Google Scholar
Yu, Y., South, T., Wang, Q. & Huang, X. F. Differential expression of hypothalamic CART mRNA in response to body weight change following different dietary interventions. Neurochem. Int. 52, 1422–1430 (2008).
Article CAS PubMed Google Scholar
Hou, J., Zheng, D.-Z., Zhou, J. Y. & Zhou, S. W. Orexigenic effect of cocaine- and amphetamine-regulated transcript (CART) after injection into hypothalamic nuclei in streptozotocin-diabetic rats. Clin. Exp. Pharmacol. Physiol. 37, 989–995 (2010).
Article CAS PubMed Google Scholar
Shi, Y. C. et al. Arcuate NPY Controls Sympathetic Output and BAT Function via a Relay of Tyrosine Hydroxylase Neurons in the PVN. Cell Metab. 17, 236–248 (2013).
Article CAS PubMed Google Scholar

Download references

Acknowledgements

The authors are grateful to Prof. Richard Palmiter (Howard Hughes Medical Institute and Department of Biochemistry, University of Washington, USA) for providing the Gpr88 ^−/− mice as a kind gift, and also for the editorial work. We thank the staff of the Garvan Institute Biological Testing Facility for facilitation of these experiments. This research was supported by the National Health and Medical Research Council of Australia (NHMRC) with a research grant, a Research Fellowship to H.H., and a Postgraduate Scholarship to J.L.

Author information

Yan-Chuan Shi and Herbert Herzog jointly supervised this work.

Authors and Affiliations

Neuroscience Division, Garvan Institute of Medical Research, St Vincent’s Hospital, Sydney, 2010, Australia
Jackie Lau, Aitak Farzi, Ronaldo F. Enriquez, Yan-Chuan Shi & Herbert Herzog
Institute of Experimental and Clinical Pharmacology, Medical University of Graz, Graz, Austria
Aitak Farzi
Faculty of Medicine, UNSW Australia, Sydney, 2052, Australia
Yan-Chuan Shi & Herbert Herzog

Authors

Jackie Lau
View author publications
You can also search for this author in PubMed Google Scholar
Aitak Farzi
View author publications
You can also search for this author in PubMed Google Scholar
Ronaldo F. Enriquez
View author publications
You can also search for this author in PubMed Google Scholar
Yan-Chuan Shi
View author publications
You can also search for this author in PubMed Google Scholar
Herbert Herzog
View author publications
You can also search for this author in PubMed Google Scholar

Contributions

H.H. and Y.C.S. supervised the project. H.H. and J.L. conceived and designed the experiments. J.L. and A.F. performed the experiments and data analysis. R.F.E. provided technical assistance for the animal work. J.L. wrote the main manuscript. All the authors contributed to the discussion and revision of the content.

Corresponding authors

Correspondence to Yan-Chuan Shi or Herbert Herzog.

Ethics declarations

Competing Interests

The authors declare that they have no competing interests.

Additional information

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Supplementary figures

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Cite this article

Lau, J., Farzi, A., Enriquez, R.F. et al. GPR88 is a critical regulator of feeding and body composition in mice. Sci Rep 7, 9912 (2017). https://doi.org/10.1038/s41598-017-10058-x

Download citation

Received: 06 June 2017
Accepted: 20 July 2017
Published: 30 August 2017
DOI: https://doi.org/10.1038/s41598-017-10058-x

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.