VCE-004.8, A Multitarget Cannabinoquinone, Attenuates Adipogenesis and Prevents Diet-Induced Obesity
Instituto Maimónides de Investigación Biomédica de Córdoba (IMIBIC), Córdoba, Spain
Departamento de Biología Celular, Fisiología e Inmunología, Universidad de Córdoba, Córdoba, Spain
Hospital Universitario Reina Sofía, Córdoba, Spain
Vivacell Biotechnology España, Córdoba, Spain
Innohealth Group, Madrid, Spain
Dipartimento di Scienze del Farmaco, Università del Piemonte Orientale, Novara, Italy
Emerald Health Pharmaceuticals, San Diego, USA
Abstract
Over the past few years, the endocannabinoid system (ECs) has emerged as a crucial player for the regulation of food intake and energy metabolism, and its pharmacological manipulation represents a novel strategy for the management of metabolic diseases. The discovery that VCE-004.8, a dual PPARγ and CB2 receptor agonist, also inhibits prolyl-hydroxylases (PHDs) and activates the HIF pathway provided a rationale to investigate its effect in in vitro models of adipogenesis and in a murine model of metabolic syndrome, all processes critically regulated by these targets of VCE-004.8. In accordance with its different binding mode to PPARγ compared to rosiglitazone (RGZ), VCE-004.8 neither induced adipogenic differentiation, nor affected osteoblastogenesis. Daily administration of VCE-004.8 (20 mg/kg) to HFD mice for 3-wks induced a significant reduction in body weight gain, total fat mass, adipocyte volume and plasma triglycerides levels. VCE-004.8 could also significantly ameliorate glucose tolerance, reduce leptin levels (a marker of adiposity) and increase adiponectin and incretins (GLP-1 and GIP) levels. Remarkably, VCE-004.8 increased the FGF21 mRNA expression in white and brown adipose, as well as in a BAT cell line, qualifying cannabinoaminoquinones as a class of novel therapeutic candidates for the management of obesity and its common metabolic co-morbidities.
Article notes
Untitled section
Received 2018 May 18; Accepted 2018 Oct 6; Collection date 2018.
Introduction
Obesity and metabolic syndrome (MetS) are interconnected conditions whose prevalence is growing at an alarming rate worldwide. Indeed, while WHO estimated that in 2005 ~300 million people had a BMI ≥ 30 kg/m2, by 2014 > 600 million adults (13% of total population) were obese (see WHO, Global status report on non-communicable diseases 2014, document number WHO/NMH/NVI/15.1, accessible at www.who.int/mediacentre/). Central obesity is the fundamental contributing factor for MetS, whose mean prevalence ranges between 20–25% of the world population, with variations depending on the geography, ethnicity, age and sex1,2. MetS causes >5-fold increase in the risk of type-2 diabetes (T2D) and >2-fold rise in the risk of developing cardiovascular disease, as well as in all-cause mortality2,3. Notably, the phenotypic presentation of MetS and its clinical evolution (e.g., in terms of co-morbidities) is rather variable; MetS being a heterogeneous condition, whose pathophysiological basis, which is likely multifaceted4,5, remains ill defined.
Over the past few decades, the endocannabinoid system (ECs) has emerged as a pivotal component of the homeostatic mechanisms for the control of body weight and metabolism6,7. This system integrates endocannabinoids such as anandamide (AEA) and 2-arachidonoyl-glycerol (2-AG), their receptors (CB1 and CB2), and the enzymatic machinery for their synthesis and metabolic inactivation8. CB receptors are also targeted by natural and synthetic cannabinoids, which mimic (or antagonize) the effects of EC. Notably, while CB1 is widely expressed in the brain, as well as in peripheral tissues, and has been unambiguously related to circuits governing energy balance and metabolic homeostasis6, CB2 has a predominant peripheral expression, and is mostly present in immune cells and involved in modulation of inflammatory responses7. Obesity and MetS have been defined as conditions of over-activation of the ECs, and therapies based on reverse-agonism of CB1 were proven effective to ameliorate the metabolic complications of obesity. Nevertheless, adverse neurological effects related to CB1-mediated central actions led to their demise6,7. Nevertheless, strategies targeting the peripheral actions of EC still hold promise for the management of MetS, being devoid of the adverse central actions of the CB1 reverse-agonists7,9, but the precise role for of CB2 in mediating the metabolic actions of EC remains unclear.
The peroxisome proliferator-activated receptor-γ (PPARγ) is a nuclear receptor that plays key role in regulating a large number of biological functions including lipid metabolism and glucose homeostasis10. PPARγ ligands include a wide array of natural and synthetic molecules, among which the best characterized are glitazones, as exemplified by rosiglitazone (RGZ), which has been extensively used in patients with type-2 diabetes. However, full agonists activators (PPARγ-fa) have undesirable side effects like weight gain, edema, liver injury, cancer, as well as an increased risk of heart failure11. Furthermore, reduction of bone mass and an increased risk of peripheral fractures in glitazone-treated patients have also been observed and associated to the inhibition of bone marrow osteoblastogenesis12. Thus, PPARγ controls bone mass through differentiation of MSCs toward osteoblasts and adipocytes, and RGZ suppresses osteoblast and promotes adipocyte development13. More recently, it has been shown that RGZ stimulates osteoblast differentiation in human MSCs, but this differentiation was followed by oxidative stress and apoptosis, overall resulting in a net loss of osteoblasts in the bone marrow14. Therefore, while the physiologic and therapeutic potential of PPARγ modulation remains high, interest has substantially shifted towards partial ligands, and cannabinoid-type molecules have raised considerable interest as safer alternatives to PPARγ-fa for anti-diabetic drug candidates15.
Studies on the pathogenic mechanisms of metabolic disease have documented that obesity is a chronic hypoxic state16 that triggers adaptive responses mediated by hypoxia-inducible factor (HIF)-1α and HIF-2α and aimed at restoring oxygen homeostasis16,17. The mechanism by which oxygen controls HIF-1α and HIF-2α stabilization has been clarified by the identification of prolyl-hydroxylases (PHDs), non-heme Fe(II) dioxygenases that require molecular oxygen and 2-oxoglutarate to hydroxylate HIF-1α and HIF-2α. Under normoxic conditions, hydroxylated HIF is ubiquitinated by an E3-ubiquitin ligase and targeted for degradation by the 26S proteasome18. Despite a plethora of studies addressing the roles of HIFs in adipose dysfunction19–22, the involvement of HIF-1α and HIF-2α in obesity remains controversial. On one hand, hypoxia is thought to exacerbate macrophage-mediated inflammation in obesity, and activation of the HIF pathway might contribute to the obese phenotype. However, other studies have shown that hypoxia actually promotes body weight reduction. In fact, hypomorphic mice for PHD2 (Hif-p4h-2), where the expression of PHD2 is significantly reduced in different tissues, showed cardioprotection via induction of the expression of genes involved in glucose metabolism, cardiac function and blood pressure. In addition, the weight of Hif-p4h-2 mice was significantly lower than that of wild-type mice23. Subsequent studies have shown that Hif-p4h-2 mice have less adipose tissue, higher glucose tolerance, better insulin sensitivity, lower plasma cholesterol levels and are protected against HFD-induced hepatic steatosis24, and similar results were observed with the pharmacological inhibition of PHD2. Moreover, erythropoietin, whose gene is regulated by HIF, has been shown to prevent adipogenesis and improve obesity, insulin resistance and adipose tissue inflammation in HFD mice25,26. These findings have provided a rationale for the evaluation of PHD-HIF modulators in the management of MetS.
In our search for multi-target compounds of potential therapeutic utility, we have documented the beneficial effects of cannabinoquinones in chronic degenerative diseases. In particular, the cannabidiol aminoquinone VCE-004.8 was shown to possess dual CB2 and PPARγ agonism, also inhibiting PHD1 and PHD2 activities and activating the HIF pathway27,28. This pharmacological profile makes VCE-004.8 of interest for the management of obesity and MetS, and we present data that validate this assumption.
Results
VCE-004.8 is a selective PPARγ modulator
We have previously found that VCE-004.8 binds and activates PPARγ28, and were interested to analyze whether or not this compound was able to activate other PPAR family members. We found that VCE-004.8, at non-toxic concentrations, selectively induced PPARγ-dependent transcriptional activity, although with lower potency than RGZ (PPARγ: p < 0.001 RGZ vs untreated; p = 0.0407 VCE-004.8 vs untreated; Fig. 1a,b), suggesting that VCE-004.8 is a selective agonist of the PPARγ isoform.
PPARγ has a large ligand-binding pocket (LBP), and the diversity of modes in which ligands can be accommodated is associated to distinct biological profiles. The LBP extends from the C-terminal helix H12 to the β-sheet S1/S2 and is divided into AF-2 and β-sheet sub-pockets29. Based on different PPARγ complex structures, it has been proposed that full agonists, such as RGZ, bind to both sub-pockets, establishing hydrogen bonds with residues Tyr473 (H12) on AF-2 (also called canonical binding site) and Ser342 (S1/S2) on β-sheet sub-pocket (also called alternative binding site), whereas partial agonists only significantly bind to the alternate site30,31. Docking experiments based on the crystal structures 3B0R, 4EMA, 5Y20 and 5LGS deposited in the Protein Data Bank (PDB) were carried out on VCE-004.8. As depicted in Fig. 1c, molecular docking with 3B0R indicated that in the absence of T0070907, an irreversible PPARγ antagonist covalently binding to Cys285 into the PPARγ LBP canonical binding site, VCE-004.8 binds to Ser342 in Ω-loop β3 (alternative site) with a predicted Ki of 448.03 nM. Docking analysis using 4EMA and 5Y20 predicts a similar binding pattern, with calculated Ki of 95.59 nM and 67.68 nM, respectively. In addition, VCE-004.8 also showed a predicted binding to I218 in Helix 3, rationalizing its higher affinity to crystal 5Y20. Docking analysis (3B0R) in the presence of T0070907 and RGZ, which bind to the canonical site, did not displace the hydrogen bonding interaction of VCE-004.8 with Ser342 (Fig. 1c), rather enhancing the binding its affinity to the alternative site (Ki 236.22 nM in the presence of T0070907 and Ki 121.55 nM in the presence of RGZ). Interestingly, in the presence of RGZ, VCE-004.8 could also interact with the canonical binding site, suggesting that VCE-004.8 could, in principle, mediate biological activities through both the canonical and the alternative LBP PPARγ sites. To assess this, the potential functionality of the canonical and alternative PPARγ sites involved in the response to VCE-004.8 were investigated. Luciferase reporter assays were used to study the participation of the canonical and alternative binding sites in the response to VCE-004.8 in comparison with RGZ. As expected, pre-incubation with the selective inhibitor of the canonical PPARγ site, T0070907, effectively blocked RGZ-induced PPARγ transactivation (p < 0.001 RGZ + T0070907 vs RGZ; Fig. 1d). Conversely, T0070907 did not block VCE-004.8-induced PPARγ transcriptional activity (Fig. 1e). These findings are consistent with the fact that RGZ activates PPARγ by acting mainly, but not exclusively, through the canonical binding site31.
Effect of VCE-004.8 on adipogenic and osteoblastogenic differentiation
Our initial results strongly suggested that, in contrast to RGZ, VCE-004.8 is a PPARγ partial ligand agonist. Since PPARγ is a master regulator of adipogenesis32, we studied the ability of VCE-004.8 to influence MSCs differentiation into adipocytes. To this purpose, MSCs were cultured in adipogenic medium (AM) for either 7 days or 21 days to study, respectively, the mRNA expression of adipogenic markers or detect lipid droplets. In the event, hMSC treated with VCE-004.8 showed fewer and smaller lipid droplets (Fig. 2a,b). In addition, VCE-004.8 prevented mitotic expansion of hMSCs (Fig. 2c) and the reduction in the number of cells was not caused by cytotoxicity (Fig. 2d). VCE-004.8 induced lower expression of the adipogenic differentiation markers PPARγ, aP2a, ADIPOQ, LPL and CEBPA (PPARγ2: p = 0.0415; aP2a: p < 0.0001; Fig. 2e) as compared to cells treated with the PPARγ-fa, RGZ (PPARγ2: p < 0.0001; aP2a: p < 0.0001; ADIPOQ: p < 0.0001; LPL: p < 0.0001; CEBPA: p < 0.0001; Fig. 2e). Interestingly, the effect of VCE-004.8 on adipocyte differentiation was prevented by T0070907 (PPARγ2: p = 0.0012; aP2a: p < 0.0001; ADIPOQ: p < 0.0003; Fig. 2e), suggesting that this PPARγ ligand can signal through both the canonical and alternative LBP binding site (Fig. 2e compared to Fig. 1e).
There is evidence that glitazones, like RGZ, suppress MSC osteoblast development through the PPARγ pathway, mechanistically rationalizing the observation of bone loss after prolonged use of this class of drugs33. However, other authors have shown that RGZ does not interfere directly with osteoblastogenesis in hMSCs14. Nevertheles, we found that VCE-004.8 neither inhibited osteoblast mineralization, nor suppressed the expression of osteogenic differentiation markers, such as Runx2 and ALP, in hMSC differentiated in an osteoblastogenic medium (OM) for 21 days (Supplementary Fig. 1). Altogether, these data indicate that VCE-004.8 qualifies as a partial PPARγ ligand, being significantly less adipogenic than RZG and not interfering with osteoblasts differentiation.
Discussion
Obesity and metabolic syndrome (MetS) are reaching pandemic proportions worldwide, and their associated co-morbidities represent an enormous medical and economic burden for our society37. The recognition of the multi-factor nature of these diseases and the involvement of numerous deregulated signaling systems in their insurgence have prompted the search of strategies based on poly-pharmaceutical agents that simultaneously target various key pharmacological end-points38,39. This polyvalent approach is less prone to the complications associated to multi-drug therapies and has the potential to alleviate the combined deregulation of different factors (food intake, glucose metabolism, energy expenditure) associated to the insurgence of MetS and its complications.
Cannabinoids, as exemplified by 9Δ-THC and CBD, are well known and clinically validated multi-target agents, whose biological profile can be modulated by structural modifications. Thus, CBD is a poor PPARγ agonist, unable to bind CB2 and to activate the HIF pathway, but oxidation of its resorcinol core increases PPARγ binding, and the introduction of an additional nitrogen substituent beneficially affects chemical stability and induces CB2 binding and PHDs inhibitory activity27,28. A comprehensive investigation on the biological profile of these compounds (cannabinoid aminoquinones) showed that they could bind to both the canonical and the alternative sites of PPARγ, but also that PPARγ alone was unable to fully recap their biological profile, in accordance with their polypharmacology40. Eventually, the benzylamino adduct of the quinone form of CBD (VCE-004.8) emerged from these studies as a potential candidate for pleiotropic pharmacological interventions, and we present compelling evidence that VCE-004.8 has potential for the management of obesity and MetS, being capable to positively affect all the main manifestations of the disease.
Conclusive evidence for the optimal profile of VCE-004.8 in the management of metabolic disease came from our pharmacological studies in a validated murine model of HFD-induced obesity and its associated complications. Indeed, male mice fed on HFD for up to 15-weeks displayed all cardinal manifestations of obesity and MetS, including increased BW, increased calorie intake, increased fat mass and adiposity, hepatic steatosis, elevated serum triglycerides, increased basal glucose and insulin levels, as well as perturbed glucose tolerance and (modestly) worse insulin sensitivity. Chronic treatment with a single daily dose of VCE-004.8 for three weeks was sufficient to revert nearly all of these adverse metabolic alterations, since VCE-004.8 treated HFD-animals showed (i) significantly lower BW gain, (ii) reduced fat mass and adiposity –together with increased % lean mass-, (iii) reduced steatosis, (iv) normalized circulating triglycerides and basal glycemia, (v) reduced basal insulinemia, and (vi) significantly improved glucose tolerance and insulin sensitivity. As a whole, these actions overcome all major complications of obesity and MetS and define an ideal profile for the design of novel pharmacological treatments based on VCE-004.8 or its derivatives.
A beneficial impact on additional hormonal alterations associated to MetS was also observed in the HFD rodent model of obesity and MetS. In addition to basal hyperinsulinemia, mice fed HFD for 15 weeks showed significantly increased leptin and PAI-1 levels, together with lower circulating concentrations of adiponectin, ghrelin and glucagon. While some of these endocrine perturbations might be compensatory, others, such as the enhanced leptin and reduced adiponectin levels, could potentially contribute to the metabolic alterations associated to obesity41,42. Notably, repeated administration of VCE-004.8 to HFD mice decreased leptin and increased adiponectin levels; with an overall change in the leptin-to-adiponectin ratio that could rationalize the observation of an improved glycemic profile42. Furthermore, VCE-004.8 could also lower resistin levels in HFD mice, further contributing to the decrease of insulin resistance. Interestingly, the body weight loss caused by VCE-004.8 in HFD mice, was not associated to an elevation of serum levels of ghrelin, thus preventing ghrelin-induced compensatory hyperphagic responses, and a worsening of insulin resistance43,44. On the other hand, the effect of VCE-004.8 on PAI-1 levels is striking and may reflect the effect of this cannabinoquinone on the HIF pathway activation45. Although this observation cannot be underestimated in terms of future clinical development, neither micro-vascular thrombosis episodes nor coagulation alterations have been reported for other PHDs inhibitors in preclinical models or Phase 2/3 clinical trials24,46.
In addition to an improved metabolic and endocrine profile in HFD-induced obese mice, VCE-004.8 could also induce positive metabolic responses in lean mice fed with control diet, including reduced BW gain, fat mass and adiposity, decreased basal glycaemia, improved glucose tolerance and enhanced insulin sensitivity in the absence of obesogenic challenges. Administration of VCE-004.8 to lean mice enhanced UCP-1 expression in iWAT, with browning and enhanced thermogenesis, and increased basal insulin and incretin (GIP and GLP-1) levels. These beneficial effects on the metabolic profile took place in the absence of detectable changes in calorie intake, suggesting the induction of mechanisms for body weight loss and metabolic improvement independent on feeding. The direct and indirect insulinotropic activity of VCE-004.8 is of special interest and warrants further investigation. In this context, it is worth considering that HIF-1α stabilization mediates insulin secretion by pancreatic β cells47 and accordingly we found that VCE-004.8 induced HIF-1α and insulin secretion in the pancreatic acinar-derived AR42J cells (Supplementary Fig. 3). Moreover, GIP and GLP-1 have been target of pleiotropic strategies to improve the management of metabolic syndrome38,39. Since the stimulatory effects of VCE-004.8 on GIP and GLP-1 were lost in obese animals, a state of resistance to its incretin-secretagogue actions might be associated to obesity, and the elusive mechanistic bases for this effect are worth further investigation.
Our studies unveiled also that VCE-004.8 influences the gene expression and circulating levels of FGF21, as putative mechanism for some of its metabolic effects. In recent years, FGF21 has emerged as master regulator of body weight, glucose homeostasis and insulin sensitivity48,49, it being produced in various key metabolic tissues, including the liver and BAT. Our data document the ability of VCE-004.8 to induce FGF21 expression in BAT and iWAT of lean mice in vivo, and to enhance FGF21 mRNA levels in a murine BAT cell line in vitro. These findings are in line with previous reports showing that PPARγ ligands can enhance FGF21 expression in adipose tissues36,48. Notably, in lean individuals, FGF21 has been shown to increase insulin sensitivity49. Thus, the above stimulatory responses may contribute to the improved glycemic profile of lean mice treated with VCE-004.8. Intriguingly, while fasting is known to potently enhance FGF21 levels, as major mechanisms to coordinate adaptive responses to starvation50, obesity has been shown to cause also an enhancement of FGF21 levels in rodents and humans34,35, suggesting a state of “FGF21 resistance”, defined by elevated FGF21 levels and impaired FGF21 receptor function51, which might contribute to the aggravation of metabolic state in conditions of obesity. In good agreement, in our studies, HFD caused an elevation of FGF21 levels, associated to increased FGF21 mRNA expression in liver and WAT, while VCE-004.8 administration normalized serum FGF21 concentrations and iWAT FGF21 gene expression; the latter is compatible with an alleviation of the state of FGF21 resistance linked to obesity. Admittedly, however, the effects of VCE-004.8 on FGF21 appear to be tissue-specific, since it did not enhance FGF21 expression in the liver and eWAT of lean mice nor did it normalize FGF21 mRNA levels in these tissues in HFD animals.
In conclusion, structural modification of the phytocannabinoid chemotype has the potential to reshape their biological profile, emphasizing specific areas of their pleiotropic pharmacological potential. We provide evidence that VCE-004.8 is a selective partial PPARγ agonist lacking adipogenic activity that alleviates metabolic perturbations and inflammatory parameters associated to obesity. VCE-004.8 induced a significant reduction in body weight gain, total fat mass, adipocyte volume, plasma triglycerides levels, and liver steatosis in HFD mice. In addition, VCE-004.8 improved sensitivity to insulin in obese mice and regulated the expression of other metabolic biomarkers. Therefore, our findings establish that specific targeting of PPARγ, CB2 and HIF pathway with VCE-004.8 could represent a potential therapeutic approach to obesity and T2D, without the harmful effects on adipogenesis and osteoblastogenesis associated with PPARγ full agonists.
Conclusions
Structural modification of the phytocannabinoid chemotype has the potential to reshape their biological profile, emphasizing specific areas of their pleiotropic pharmacological potential. We provide evidence that the cannabidiol aminoquinone VCE-004.8 is a selective partial PPARγ agonist lacking adipogenic activity that alleviates metabolic perturbations and inflammatory parameters associated to obesity. VCE-004.8 induced a significant reduction in body weight gain, total fat mass, adipocyte volume, plasma triglycerides levels, and liver steatosis in HFD mice. In addition, VCE-004.8 improved sensitivity to insulin in obese mice and regulated the expression of other metabolic biomarkers. Therefore, our findings establish that specific targeting of PPARγ, CB2 and HIF pathway with VCE-004.8 may be a therapeutic approach for the management of obesity and T2D, without the harmful effects on adipogenesis and osteoblastogenesis associated with PPARγ full agonists.
Material and Methods
Cell lines
Immortalized murine primary brown adipocytes (pBAT) were kindly provided by Prof Francesc Villarroya (University of Barcelona, Spain). pBAT cells were maintained in DMEM with 10% FBS, 2% HEPES, 20 mM L-glutamine, and antibiotics at 37 °C in 5% CO2 (Klein et al., 2012). For differentiation, cells were cultured in 6-well plates (250,000 cells/well) and T3 (1 nM) and insulin (20 nM) were added to the media (Growth media) for 24 hours. Then, IBMX (500 μM), dexamethasone (500 nM) and indomethacin (125 μM) were added to the growth media for 48 h (Differentiation media), before changing back to the growth media with just T3 and insulin for an additional 48 h to allow acquisition of a differentiated morphology. Treatment with RGZ (1 µM) and VCE-004.8 (1 µM) in the presence and the absence of T0070907 (5 µM) started at the same time as the differentiation process. Pancreatic acinar-derived AR42J cells were maintained in Dulbecco’s Modified Eagle’s Medium (DMEM), containing 4.5 g/L of glucose, 0.5 g/L of L-glutamine, supplemented with 10% FBS and 1% (v/v) penicillin/streptomycin (Sigma-Aldrich, USA) at 37 °C in a humidified atmosphere containing 5% CO2. Cytotoxicity assays were performed using standard YOYO-1 and MTT methods.
Transient transfections and luciferase assays
To analyse PPARs transcriptional activities HEK-293T cells were cultured in 24-well plates and transiently co-transfected with either GAL4-PPARγ, GAL4-PPARδ, and GAL4-PPARα vectors together with the luciferase reporter vectors GAL4-luc (firefly luciferase) and pRL-CMV (renilla luciferase) using Roti©-Fect (Carl Roth, Karlsruhe, Germany). After stimulation, the luciferase activities were quantified using Dual-Luciferase Assay (Promega, Madison, WI, USA).
Docking analysis and calculation of theoretical PPARγ-binding affinity
Ligand docking, and binding properties were calculated by using the AutoDock452 and the Vina software53 with the virtual screening tool PyMOL54. The receptor models used were the PDB references 3B0R55, 4EMA56, 5Y2O57, and 5LGS58. Search space for the docking was set around the binding sites described previously30,31.
Mesenchymal stem cells (MSCs) differentiation
The Reina Sofia University Hospital Review Board approved this study and the procedures followed were in accordance with the ethical standards of the ethic committee from Hospital Reina Sofía (Córdoba, Spain) and with the Declaration of Helsinki. The Hematology Service recruited bone marrow donors. All subjects gave their informed consent so that the bone marrow aliquots extracted for clinical purposes could also be used for mesenchymal bone marrow research. MSCs were seeded in α-MEM containing, 15% FCS, 2 mM Glutamine, 1 ng/ml bFGF and antibiotics. Adipogenic (AD) and osteoblast differentiation (OD) was performed as described elsewhere59. Treatments with RGZ and VCE-004.8 were initiated at day 0 of the differentiation process. At day 21, adipogenesis and osteoblastogenesis were analyzed by staining the cell with either Oil Red O or Alizarin Red, respectively. Images captured with the light microscope were analyzed with the ImageJ Software (NIH; Bethesda, MD, USA) and mineralization was quantified by removing the staining solution and absorbance was read at 405 nm.
Animals and experimental design
Six-week old male C57BL/6 mice, obtained from Charles Rivers Laboratories (l’Arbresle, France), were pair-housed at 20–22 °C, under constant conditions of light (14 hours of light; lights on at 7:00 am), and free access to food (see below) and water. All experiments were performed in accordance with European Union guideline and approved by the Animal Research Ethic Committee of Córdoba University (2014PI/025). Procedures were designed to minimize the number of animals used and their suffering. At 8 weeks of age, the animals were randomly assigned in two groups (N = 20) to receive either a standard diet (CD) (A04 SAFE Diets, Augy, France), or high-fat diet (HFD) (45% of calories from fat, D12451 Research Diets, New Brunswick, NJ), for 15 weeks. Body weight (BW) and food intake (FI) were monitored once weekly along the first 12 weeks, and twice a week during treatment period. Additionally, energy intake was calculated in the different experimental groups, using the kcal/g index provided by manufacturer. In order to assess the potential metabolic effects of VCE-004.8, mice were treated by daily intraperitoneal injection of this compound during three weeks, from week 12 onwards, in CD and HFD groups (n = 10/group). Control animals received the corresponding vehicle injections (n = 10/group). Body composition analyses were performed by quantitative magnetic resonance (QMR), using the EchoMRI™ 700 analyzer (Houston, TX, software v.2.0). MRI scans were taken before starting diet exposure, at the start of treatment (week 12; see Supplementary Fig. 2), and at the end of experimental procedures (week 15). At the end of the experiment, mice were euthanized and blood and brown adipose tissue (BAT), white adipose tissue (WAT,) and liver were collected. Tissues were snap-frozen on dry ice and/or fixed in 4% formalin for further analysis of molecular expression and histology, respectively.
Immunohistochemistry and Western Blots
Liver tissues were processed and 5 μM-thick paraffin-embedded tissue sections were stained with hematoxylin and eosin (H&E). A semi-quantitative score was assigned to evaluate the extent of steatosis according to the Kleiner system (0, <5%; 1, 5–33%; 2, 33–66%; and 3, >66%)60. For IHC analysis, 7 μM-thick paraffin-embedded tissue sections of inguinal white (iWAT) adipose tissue were used. Antigen retrieval was performed in 37 °C trypsin (pH 7.8) for 1 h or 10 mM sodium citrate buffer (pH 6) at 95 °C for 10 min. Sections were incubated with F4/80 antibody (1:50; MCA497, Bio-Rad) or UCP-1 antibody (1:500; ab10983, Abcam) overnight at 4 °C, respectively. Then, the slides were incubated for 1 h at room temperature with the appropriate biotin-conjugated secondary antibody (Merck Millipore). Reaction was stained with DAB substrate kit (Merck Millipore), and subsequent counterstaining with hematoxylin and mounting. Samples were analysed with a Leica DM2000 microscope and pictures were taken with a Leica MC190 camera. For Western blots, proteins were isolated from brown (BAT) and inguinal white (iWAT) adipose tissues; 30 μg samples were boiled at 95 °C in Laemmli buffer and electrophoresed in 10% SDS/PAGE gels. Separated proteins were transferred (20 V for 30 min) to PVDF membranes and blocked in 0.1% Tween 20 in TBS solution containing 5% non-fat dry milk for 1 h at room temperature. Membranes were incubated with the UCP-1 antibody overnight at 4 °C (1:2000). For loading control, α-tubulin levels were assayed in the same samples (1:10.000; DM-1A, Sigma,). Membranes were washed and incubated with the appropriate horseradish peroxidase-conjugated secondary antibody for 1 h at room temperature and detected by chemiluminescence system (GE Healthcare Europe GmbH, Freiburg, Germany). To measure the steady state levels of HIF-1α protein in AR42J cells we used the anti-HIF-1α mAb (610959) that was obtained from BD Biosciences (Madrid, Spain).
Intraperitoneal glucose and insulin tolerance tests, and triglyceride determinations
The animals were ip injected with a bolus of 2 g of glucose per kg BW, after a 5 h period of food deprivation, and blood glucose levels were determined at 0, 20, 60 and 120 min after injection. For ITT, the animals were subjected to ip injection of 1 U of insulin (Sigma Aldrich) per kg body weight, after a 5 h fasting. Blood glucose levels were measured at 0, 20, 60 and 120 minutes. All glucose concentrations were measured using a handheld glucometer (Accu-Check Advantage®; Roche Diagnostics). In addition, serum triglyceride levels were assayed, using a GPO-POD assay kit (Triglyceride Liquid kit 992320, Quimica Analitica Aplicada SA, Spain).
Real-time PCR
For gene expression, cells were collected at day 7 (MSCs) or 14 (HPAs) of differentiation and total RNA was extracted using the High Pure RNA Isolation kit (Roche Diagnostics, Switzerland). For tissues, mRNA was extracted using the FavorPrep™ Tissue Total RNA Purification Mini Kit (Favorgen Biotech Corp., Ping-Tung, Taiwan) and Qiagen RNeasy Lipid Kit (Qiagen, Hilden, Germany). For real-time PCR analysis, RNA was reverse transcribed and the HPRT or GAPDH gene was used to standardize mRNA expression in each sample. The primers used in this study are indicated in Supplementary Table S2.
Statistical analysis
In vitro data are expressed as mean ± SD and In vivo results are represented as mean ± SEM. Statistical analyses were performed on data distributed in a normal pattern, using Student’s t tests or Analysis of Variance (ANOVA). P < 0.05 was taken as the minimum level of significance. Statistical analysis was performed using GraphPad Prism® version 6.01.
Electronic supplementary material
Untitled section
Acknowledgements
This work was supported by grants SAF2014-53763-P, SAF2017-87701-R (EM) and BFU2014-57581-P and BFU2017-83934-P (M.T.-S.) (Ministerio de Economía y Competitividad, Spain; co-funded with EU funds from FEDER Program); Project PIE14-00005 (Flexi-Met, Instituto de Salud Carlos III, Ministerio de Sanidad, Spain); Project P12-FQM-01943 (M.T.-S.; Junta de Andalucía, Spain). CIBER Fisiopatología de la Obesidad y Nutrición is an initiative of Instituto de Salud Carlos III. Senior authors are indebted with Prof. Francesc Villarroya (University of Barcelona, Spain) and Prof. Angela M. Valverde (Instituto de Investigaciones Biomedicas Alberto Sols, Madrid, Spain) for provision of the pBAT cell line, important for conduction of some of the experiments included in this study. None of the funding bodies played any role in the study design, data collection and analysis, the decision to publish, or the preparation of the manuscript. BP is a predoctoral fellow supported by the i-PFIS program, Instituto de Salud Carlos III (IFI15/00022; European Social Fund “investing in your future”).
Untitled section
Competing Interests
The authors declare no competing interests.
Footnotes
Footnote Group
Electronic supplementary material
Supplementary information accompanies this paper at 10.1038/s41598-018-34259-0.
References
Untitled section
References
- 1.Borch-Johnsen, K. In The Metabolic Syndrome - Pharmacology and Clinical Aspects (ed H. Beck-Nielsen) Ch. 2, 7–16 (Springer-Verlag, 2013).
- 2.Kaur J. A comprehensive review on metabolic syndrome. Cardiology research and practice. 2014;2014:943162. doi: 10.1155/2014/943162.
- 3.Alberti KG, et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation. 2009;120:1640–1645. doi: 10.1161/CIRCULATIONAHA.109.192644.
- 4.Lopez-Miranda J, et al. Dietary fat, genes and insulin sensitivity. Journal of molecular medicine. 2007;85:213–226. doi: 10.1007/s00109-006-0138-1.
- 5.McCarthy MI. Genomics, type 2 diabetes, and obesity. The New England journal of medicine. 2010;363:2339–2350. doi: 10.1056/NEJMra0906948.
- 6.Simon V, Cota D. Mechanisms In Endocrinology: Endocannabinoids and metabolism: past, present and future. European journal of endocrinology. 2017;176:R309–R324. doi: 10.1530/EJE-16-1044.
- 7.Shrestha N, et al. Peripheral modulation of the endocannabinoid system in metabolic disease. Drug discovery today. 2018;23:592–604. doi: 10.1016/j.drudis.2018.01.029.
- 8.Pertwee RG, et al. International Union of Basic and Clinical Pharmacology. LXXIX. Cannabinoid receptors and their ligands: beyond CB(1) and CB(2) Pharmacological reviews. 2010;62:588–631. doi: 10.1124/pr.110.003004.
- 9.Richey JM, Woolcott O. Re-visiting the Endocannabinoid System and Its Therapeutic Potential in Obesity and Associated Diseases. Current diabetes reports. 2017;17:99. doi: 10.1007/s11892-017-0924-x.
- 10.Tontonoz P, Spiegelman BM. Fat and beyond: the diverse biology of PPARgamma. Annual review of biochemistry. 2008;77:289–312. doi: 10.1146/annurev.biochem.77.061307.091829.
- 11.Rosen CJ. Revisiting the rosiglitazone story–lessons learned. The New England journal of medicine. 2010;363:803–806. doi: 10.1056/NEJMp1008233.
- 12.Grey A. Diabetes medications and bone. Current osteoporosis reports. 2015;13:35–40. doi: 10.1007/s11914-014-0250-z.
- 13.Benvenuti S, et al. Rosiglitazone stimulates adipogenesis and decreases osteoblastogenesis in human mesenchymal stem cells. Journal of endocrinological investigation. 2007;30:RC26–30. doi: 10.1007/BF03350807.
- 14.Bruedigam C, et al. A new concept underlying stem cell lineage skewing that explains the detrimental effects of thiazolidinediones on bone. Stem cells. 2010;28:916–927. doi: 10.1002/stem.405.
- 15.Capelli D, et al. Structural basis for PPAR partial or full activation revealed by a novel ligand binding mode. Scientific reports. 2016;6:34792. doi: 10.1038/srep34792.
- 16.Hosogai N, et al. Adipose tissue hypoxia in obesity and its impact on adipocytokine dysregulation. Diabetes. 2007;56:901–911. doi: 10.2337/db06-0911.
- 17.Lefere S, et al. Hypoxia-regulated mechanisms in the pathogenesis of obesity and non-alcoholic fatty liver disease. Cellular and molecular life sciences: CMLS. 2016;73:3419–3431. doi: 10.1007/s00018-016-2222-1.
- 18.Rabinowitz MH. Inhibition of hypoxia-inducible factor prolyl hydroxylase domain oxygen sensors: tricking the body into mounting orchestrated survival and repair responses. Journal of medicinal chemistry. 2013;56:9369–9402. doi: 10.1021/jm400386j.
- 19.Halberg N, et al. Hypoxia-inducible factor 1alpha induces fibrosis and insulin resistance in white adipose tissue. Molecular and cellular biology. 2009;29:4467–4483. doi: 10.1128/MCB.00192-09.
- 20.Jiang C, et al. Disruption of hypoxia-inducible factor 1 in adipocytes improves insulin sensitivity and decreases adiposity in high-fat diet-fed mice. Diabetes. 2011;60:2484–2495. doi: 10.2337/db11-0174.
- 21.Lee KY, Gesta S, Boucher J, Wang XL, Kahn CR. The differential role of Hif1beta/Arnt and the hypoxic response in adipose function, fibrosis, and inflammation. Cell metabolism. 2011;14:491–503. doi: 10.1016/j.cmet.2011.08.006.
- 22.Zhang X, et al. Adipose tissue-specific inhibition of hypoxia-inducible factor 1{alpha} induces obesity and glucose intolerance by impeding energy expenditure in mice. The Journal of biological chemistry. 2010;285:32869–32877. doi: 10.1074/jbc.M110.135509.
- 23.Hyvarinen J, et al. Hearts of hypoxia-inducible factor prolyl 4-hydroxylase-2 hypomorphic mice show protection against acute ischemia-reperfusion injury. The Journal of biological chemistry. 2010;285:13646–13657. doi: 10.1074/jbc.M109.084855.
- 24.Rahtu-Korpela L, et al. HIF prolyl 4-hydroxylase-2 inhibition improves glucose and lipid metabolism and protects against obesity and metabolic dysfunction. Diabetes. 2014;63:3324–3333. doi: 10.2337/db14-0472.
- 25.Liu Y, et al. Nonerythropoietic Erythropoietin-Derived Peptide Suppresses Adipogenesis, Inflammation, Obesity and Insulin Resistance. Scientific reports. 2015;5:15134. doi: 10.1038/srep15134.
- 26.Alnaeeli M, et al. Erythropoietin signaling: a novel regulator of white adipose tissue inflammation during diet-induced obesity. Diabetes. 2014;63:2415–2431. doi: 10.2337/db13-0883.
- 27.Navarrete C, et al. Hypoxia mimetic activity of VCE-004.8, a cannabidiol quinone derivative: implications for multiple sclerosis therapy. Journal of neuroinflammation. 2018;15:64. doi: 10.1186/s12974-018-1103-y.
- 28.del Rio C, et al. The cannabinoid quinol VCE-004.8 alleviates bleomycin-induced scleroderma and exerts potent antifibrotic effects through peroxisome proliferator-activated receptor-gamma and CB2pathways. Scientific reports. 2016;6:21703. doi: 10.1038/srep21703.
- 29.Zoete V, Grosdidier A, Michielin O. Peroxisome proliferator-activated receptor structures: ligand specificity, molecular switch and interactions with regulators. Biochimica et biophysica acta. 2007;1771:915–925. doi: 10.1016/j.bbalip.2007.01.007.
- 30.Waku T, et al. The nuclear receptor PPARgamma individually responds to serotonin- and fatty acid-metabolites. The EMBO journal. 2010;29:3395–3407. doi: 10.1038/emboj.2010.197.
- 31.Hughes TS, et al. An alternate binding site for PPARgamma ligands. Nature communications. 2014;5:3571. doi: 10.1038/ncomms4571.
- 32.Lecka-Czernik B, et al. Divergent Effects of Selective Peroxisome Proliferator-Activated Receptor-gamma2 Ligands on Adipocyte Versus Osteoblast Differentiation. Endocrinology. 2002;143:2376–2384. doi: 10.1210/endo.143.6.8834.
- 33.Lecka-Czernik B. Bone loss in diabetes: use of antidiabetic thiazolidinediones and secondary osteoporosis. Current osteoporosis reports. 2010;8:178–184. doi: 10.1007/s11914-010-0027-y.
- 34.Berti L, et al. Fibroblast growth factor 21 is elevated in metabolically unhealthy obesity and affects lipid deposition, adipogenesis, and adipokine secretion of human abdominal subcutaneous adipocytes. Molecular metabolism. 2015;4:519–527. doi: 10.1016/j.molmet.2015.04.002.
- 35.Morrice N, et al. Elevated Fibroblast growth factor 21 (FGF21) in obese, insulin resistant states is normalised by the synthetic retinoid Fenretinide in mice. Scientific reports. 2017;7:43782. doi: 10.1038/srep43782.
- 36.So WY, Leung PS. Fibroblast Growth Factor 21 As an Emerging Therapeutic Target for Type 2 Diabetes Mellitus. Medicinal research reviews. 2016;36:672–704. doi: 10.1002/med.21390.
- 37.Wang YC, McPherson K, Marsh T, Gortmaker SL, Brown M. Health and economic burden of the projected obesity trends in the USA and the UK. Lancet. 2011;378:815–825. doi: 10.1016/S0140-6736(11)60814-3.
- 38.Finan B, et al. A rationally designed monomeric peptide triagonist corrects obesity and diabetes in rodents. Nature medicine. 2015;21:27–36. doi: 10.1038/nm.3761.
- 39.Jall S, et al. Monomeric GLP-1/GIP/glucagon triagonism corrects obesity, hepatosteatosis, and dyslipidemia in female mice. Molecular metabolism. 2017;6:440–446. doi: 10.1016/j.molmet.2017.02.002.
- 40.Garcia C, et al. Benefits of VCE-003.2, a cannabigerol quinone derivative, against inflammation-driven neuronal deterioration in experimental Parkinson’s disease: possible involvement of different binding sites at the PPARgamma receptor. Journal of neuroinflammation. 2018;15:19. doi: 10.1186/s12974-018-1060-5.
- 41.Lopez-Jaramillo P, et al. The role of leptin/adiponectin ratio in metabolic syndrome and diabetes. Hormone molecular biology and clinical investigation. 2014;18:37–45. doi: 10.1515/hmbci-2013-0053.
- 42.Stofkova A. Leptin and adiponectin: from energy and metabolic dysbalance to inflammation and autoimmunity. Endocrine regulations. 2009;43:157–168.
- 43.Poher AL, Tschop MH, Muller TD. Ghrelin regulation of glucose metabolism. Peptides. 2018;100:236–242. doi: 10.1016/j.peptides.2017.12.015.
- 44.Vestergaard ET, Jessen N, Moller N, Jorgensen JO. Acyl Ghrelin Induces Insulin Resistance Independently of GH, Cortisol, and Free Fatty Acids. Scientific reports. 2017;7:42706. doi: 10.1038/srep42706.
- 45.Liao H, Hyman MC, Lawrence DA, Pinsky DJ. Molecular regulation of the PAI-1 gene by hypoxia: contributions of Egr-1, HIF-1alpha, and C/EBPalpha. FASEB journal: official publication of the Federation of American Societies for Experimental Biology. 2007;21:935–949. doi: 10.1096/fj.06-6285com.
- 46.Gupta N, Wish JB. Hypoxia-Inducible Factor Prolyl Hydroxylase Inhibitors: A Potential New Treatment for Anemia in Patients With CKD. American journal of kidney diseases: the official journal of the National Kidney Foundation. 2017;69:815–826. doi: 10.1053/j.ajkd.2016.12.011.
- 47.Zehetner J, et al. PVHL is a regulator of glucose metabolism and insulin secretion in pancreatic beta cells. Genes & development. 2008;22:3135–3146. doi: 10.1101/gad.496908.
- 48.Kliewer SA, Mangelsdorf DJ. Fibroblast growth factor 21: from pharmacology to physiology. The American journal of clinical nutrition. 2010;91:254S–257S. doi: 10.3945/ajcn.2009.28449B.
- 49.Owen BM, Mangelsdorf DJ, Kliewer SA. Tissue-specific actions of the metabolic hormones FGF15/19 and FGF21. Trends in endocrinology and metabolism: TEM. 2015;26:22–29. doi: 10.1016/j.tem.2014.10.002.
- 50.Owen BM, et al. FGF21 contributes to neuroendocrine control of female reproduction. Nature medicine. 2013;19:1153–1156. doi: 10.1038/nm.3250.
- 51.Tanajak P. Letter to the Editor: Parameters, Characteristics, and Criteria for Defining the Term “FGF21 Resistance”. Endocrinology. 2017;158:1523–1524. doi: 10.1210/en.2017-00056.
- 52.Morris GM, et al. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. Journal of computational chemistry. 2009;30:2785–2791. doi: 10.1002/jcc.21256.
- 53.Trott O, Olson AJ. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. Journal of computational chemistry. 2010;31:455–461. doi: 10.1002/jcc.21334.
- 54.Baugh EH, Lyskov S, Weitzner BD, Gray JJ. Real-time PyMOL visualization for Rosetta and PyRosetta. PloS one. 2011;6:e21931. doi: 10.1371/journal.pone.0021931.
- 55.Hughes TS, et al. Ligand and receptor dynamics contribute to the mechanism of graded PPARgamma agonism. Structure. 2012;20:139–150. doi: 10.1016/j.str.2011.10.018.
- 56.Liberato MV, et al. Medium chain fatty acids are selective peroxisome proliferator activated receptor (PPAR) gamma activators and pan-PPAR partial agonists. PloS one. 2012;7:e36297. doi: 10.1371/journal.pone.0036297.
- 57.Lee MA, Tan L, Yang H, Im YG, Im YJ. Structures of PPARgamma complexed with lobeglitazone and pioglitazone reveal key determinants for the recognition of antidiabetic drugs. Scientific reports. 2017;7:16837. doi: 10.1038/s41598-017-17082-x.
- 58.Brusotti G, et al. Betulinic acid is a PPARgamma antagonist that improves glucose uptake, promotes osteogenesis and inhibits adipogenesis. Scientific reports. 2017;7:5777. doi: 10.1038/s41598-017-05666-6.
- 59.Diaz-Alonso J, et al. VCE-003.2, a novel cannabigerol derivative, enhances neuronal progenitor cell survival and alleviates symptomatology in murine models of Huntington’s disease. Scientific reports. 2016;6:29789. doi: 10.1038/srep29789.
- 60.Kleiner DE, et al. Design and validation of a histological scoring system for nonalcoholic fatty liver disease. Hepatology. 2005;41:1313–1321. doi: 10.1002/hep.20701.