Whole milk is a significant source of nutrients, including fat, protein, minerals and vitamins. Besides its high nutritional value, whole milk contains several bioactive compounds (peptides, conjugated linoleic acid, short chain fatty acids, monounsaturated and polyunsaturated fatty acids and polyphenols including isoflavones, among others) with important beneficial health effects. Thus, whole milk has been recognized as a functional food [1
]. Despite this evidence, there is a prevalent notion that foods with elevated fat content; including whole milk, induces weight gain and are a primary cause of obesity; particularly because of their elevated content of saturated fat. Saturated fat has been associated with increased low-density lipoprotein cholesterol levels, which in turn increase the risk of cardiovascular disease (CVD). For this reason, there is an increasing trend to replace natural high-fat dairy foods for low-fat or non-fat dairy products considered by consumers as “healthier alternatives”. However, recent research reveals that intake of high-fat milk and dairy products have no association with the occurrence of CVD, stroke, coronary heart disease, dyslipidemia or type 2 diabetes [3
]. Moreover, milk intake provides health benefits in subjects with diabetes [5
], obesity [6
] and metabolic syndrome [7
] in particular with fermented dairy [8
]. Despite this body of evidence, the consumption of dairy products remains a subject of debate.
The variation in the beneficial effects of milk from different studies may arise from the huge number of variables that impacts the composition of milk, including the animal species from which it comes, composition of feed and even the animal care and welfare [9
]. The majority of studies involving dairy products have been conducted using cow’s milk. We and others have shown that goat’s milk is also a rich source of nutrients and bioactive compounds [10
]. However, there is scarce evidence regarding the effect of goat’s milk on health [11
]. We have previously demonstrated that goat’s milk nutrient composition and bioactive compounds content varies depending on the composition of dairy goat’s feed [12
]. Thus, the handling and variety of food provided to goats (grazing, organic feeding, strategic supplementation, etc.) determines the quality of milk [10
]. Accordingly, we have demonstrated that in dairy goats, grazing management increases the content of polyunsaturated fatty acids of milk with respect to goats fed a conventional diet. Moreover, inclusion of Acacia farnesiana
(AF) pods boosted the polyphenol content and increased the n
−6 fatty acids ratio [10
], improving the quality and functional potential of milk. Nevertheless, whether the different quality of the milk is reflected on health benefits during metabolic challenges such as a high-fat (HF) diet has not been explored. Thus, the objective of this study was to determine the effect of feeding lyophilized whole milk from goats fed conventional diet (CD), grazing or CD supplemented with AF pods on the inflammatory and metabolic parameters of mice fed a HF diet.
The present work demonstrates that the incorporation of dry whole goat’s milk to a high-fat (HF) diet prevents excessive body weight gain, body fat mass accretion and hepatic steatosis in mice. These beneficial effects were elicited through increased whole-body insulin sensitivity and energy expenditure, improving substrate utilization during the feeding-fasting cycles. The metabolic effects of goat’s milk intake could be attributed to an increase in oxidative fibers in skeletal muscle, augmented UCP1 expression in brown adipose tissue, a reduction in SREBP-1c mediated lipogenesis in liver and increased adipose tissue browning, lipolysis and in situ thermogenesis.
The beneficial effects of goat’s milk on the metabolic profile of mice, despite chronic consumption of a high-energy diet, indicates that goat’s milk contains particular molecules that can modulate metabolic and inflammatory pathways in different organs. Goat’s milk is a significant source of plant-derived phenolic compounds. We and other have previously reported the polyphenol composition of goat’s milk [10
]. We also observed that goat fed influences polyphenol content in milk. Goat fed supplemented with 30% of Acacia farnesiana
pods or grazing increases the polyphenol content in goat’s milk by approximately 2-fold and 1.4-fold, respectively [10
]. This differential polyphenol enrichment was reflected in the metabolic effects induced by the different diets.
Among the polyphenols found in goat’s milk, gallic acid, chlorogenic acid, ferulic acid and catechins are the most abundant [10
], which have demonstrated to have antioxidant properties [32
], increase in energy expenditure in mice [35
] and humans [36
] and anti-inflammatory properties [37
]. Thus, the polyphenol content in goat’s milk could be directly responsible of the increase in energy expenditure. We have previously demonstrated that polyphenols such as genistein increases energy expenditure in mice through modulation of AMPK and the thermogenic program of subcutaneous adipose tissue [38
]. The activation of AMPK in skeletal muscle and liver of mice fed goat’s milk was associated with lower lipid content in both tissues, increased mitochondrial content in skeletal muscle and whole-body glucose tolerance. Thus, the polyphenol content of goat’s milk could exert these metabolic activities by the stimulation of AMPK activity.
Moreover, the effect of polyphenols in metabolic tissues could also be attributed to the activation of metabolic nuclear receptors [39
]. For instance, nuclear receptor PPARγ2 is the master regulator of adipose tissue functions, controlling adipocyte differentiation, lipid storage, adipokine secretion and immune activities of resident macrophages in adipose tissue [40
]; PPARδ governs substrate utilization and oxidative metabolism in skeletal muscle by activating the transcriptional program for mitochondrial biogenesis [41
]. Interestingly, we found a significant increase in PPARγ2 expression in adipose tissue, and PPARδ in skeletal muscle of mice fed goat’s milk, suggesting that some of the polyphenols present in goat’s milk are able to activate these nuclear receptors in metabolic tissues. The reduction in adipocyte hypertrophy, increased UCP-1 and adiponectin expression and reduced macrophage infiltration in adipose tissue was likely due to activation of PPARγ2 by goat’s milk polyphenols. Similarly, the increase in mitochondrial activity and reduction of lipid deposition in skeletal muscle fibers was probably result of the combined action of AMPK activation, and PPARδ transcriptional activity.
Another type of molecules in goat’s milk which are able to modulate metabolism and inflammation are fatty acids. The consumption of specific monounsaturated (MUFA) or polyunsaturated (PUFA) fatty acids can exert beneficial metabolic effects. The 16:1n-7 and 18:1n-9 MUFAS and 20:5(n
-3) and 22:6(n
-3) PUFAS are known to promote blood pressure control, adequate coagulation, enhanced endothelial function and preservation of insulin sensitivity, having beneficial effects on the prevention and treatment of metabolic syndrome [41
]. MUFA-rich diets can improve glycemic control while diets rich in n
-3 PUFA such as EPA and DHA can improve plasma TG levels, and favor the resolution of inflammation [42
]; whereas high intake of the n
-6 PUFA arachidonic acid (AA) induces low-grade inflammation, oxidative stress, endothelial dysfunction and atherosclerosis [44
]. According to this scenario, the lower body fat mass (Figure 1
E), the higher insulin sensitivity (Figure 2
E), the lower fatty acid accumulation on liver (Figure 6
G,H), and finally, the input of n
-3 PUFA anti-inflammation (Figure 6
O) of goat’s milk prevented the establishment of metabolic syndrome in our mice as showed our results.
Interestingly, it has been demonstrated that the substitution of saturated with monounsaturated fatty acid attenuates hyperinsulinemia and pancreatic islet dysfunction [45
]. Thus, it is possible that the specific fatty acid profile of goat’s milk could be responsible (Figure 6
D–F) of the decrease in hyperinsulinemia and pancreatic islet hypertrophy observed in mice fed these diets (Figure 2
E,G,H), which is in contrast with lard that has a high content in saturated long fatty acids. In fact, deletion of Elov16 enzyme that elongates fatty acids protects pancreatic islets from the hypertrophy induced by high-fat diets [46
]. Moreover, the high content of EPA, ALA and DHA, could modulate insulin secretion by a G-protein-receptor-mediated release of glucagon-like peptide 1 (GLP-1) by enteroendocrine L-cells [47
], and insulin sensitivity pathways in other tissues [48
], decreasing the stress on pancreatic islets and, therefore, pancreatic islets hypertrophy.
We cannot discard other mechanisms that may involve other components through which goat’s milk exert its beneficial effect, such as micro RNAs contained in exosomes [50
], or bioactive peptides [51
]. Exosomes have been found in the skim and fat fraction of human, goat and bovine milk and are able to enter normal or tumor cells decreasing the expression of the miRNA’s target genes [50
]. However, further research is needed to establish whether the goat’s milk used in this study preserved its exosome or bioactive peptide content, and to evaluate if contributed to the observed beneficial effect.
Altogether our results demonstrate that the incorporation of goat’s milk decreased body weight and body fat mass, improved glucose tolerance, prevented adipose tissue hypertrophy and hepatic steatosis in mice fed a HF diet, through an increase in energy expenditure, augmented oxidative fibers in skeletal muscle, and reduced inflammatory markers. Therefore, goat’s milk can be considered a non-pharmacologic strategy to improve the metabolic alterations induced by a HF diet. A summary diagram of the effects in mice metabolism by incorporating dry whole goat milk in a high fat diet is shown in Figure 7
Finally, to obtain a reference dose for future clinical studies, the body surface area (BSA) normalization method can be used to convert the dose information for mice to equivalent human intake [52
]. For instance, in the present study consuming a 3.5 g/day of feed containing dry whole goat milk from a conventional diet would provide mice with 0.56 mg/day of bioactive phenolic (Figure 1
C, Table 1
). This amount of bioactive phenolic for mice of ~25-g body weight in average corresponds to 22.4 mg/kg per day, which multiplied by the animal Km factor (3) and divided by the human Km factor (37) will give a human dose equivalent of 1.81 mg/kg per day. The Km factor is obtained by dividing body weight (kg) and BSA (m2
) and used for drug dose conversion between mg/kg and mg/m2
, and its value for different animal species is available in the literature [52
]. Accordingly, for an average human adult of 60 kg, the intake of bioactive phenolic from goat milk would correspond to ~108.6 mg/day. Thus, considering, that fresh goat milk contains ~150 mg phenolic/L [10
] then the calculated intake would correspond to 0.72 L of fresh milk. This means that the human equivalent dose (~108.6 mg/day) could be supplied by daily consumption of 2.8 glasses/cups of fresh goat milk (250 mL per glass or cup). Furthermore, the source of the feed diet in goats enhances the content of bioactive phenolic in fresh milk as high as 230 mg/L in grazing diet and 300 mg/L in supplemented Acacia farnesiana
pods diets [10
] like those used in the present study. Thus, in these cases the calculated human intake would correspond to only 0.36–0.47 L of fresh milk which is about daily consumption of 1.4–1.8 glasses/cups of fresh goat milk. Alternatively, freeze dried whole goat milk powder corresponding to the calculated human intake of fresh milk could be incorporated as part of a solid diet in similar fashion as described in the present study.
4. Materials and Methods
Male C57BL/6 mice of 5 weeks of age and weighing 20–23 g were obtained from the Experimental Research Department and Animal Care Facility at the Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán (DIEB-INCMNSZ) and housed in micro isolator cages at 23 °C with a 12-h on/12-h off light-dark cycle (7:00 AM–7:00 PM). All animal procedures were conducted in accordance with the recommendations and procedures from the National Institutes of Health guide for care and use of Laboratory Animals [54
]. The Animal Care Committee of the Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán (CINVA-INCMNSZ) approved the study (Approval number NAN-1904-18-19-1).
4.2. Experimental Diets
Animals were randomly assigned into five groups (n
= 6) receiving one of the following isoenergetic experimental diets: (1) Control; (2) High-fat (HF); (3) HF + dry whole milk from goats fed a conventional diet (HFCD); (4) HF + dry whole milk from goats fed on grazing (HFG); (5) HF + dry whole milk from goats fed a conventional diet supplemented with 30% of Acacia farnesiana
pods (HFAF). Goat’s milk was collected and lyophilized according to Delgadillo-Puga et al. [10
]. Diets were administered in dry from, and their composition was adjusted according to the recommendations of AIN 93 [55
] (Table 1
). The study had a duration of twelve weeks where all animals had ad libitum access to water and their respective experimental diet. Body weight was measured once a week and, food intake was measured every other day during the study. Body composition, energy expenditure, glucose and insulin tolerance were evaluated as indicated below at week 10, 11 and 12, respectively as indicated below.
At the end of the study, mice were deprived of food six hours previous to the euthanasia mice were deprived of food. Euthanasia was performed by exposing mice to a lethal dose of sevoflurane (fluoromethyl-2,2,2-trifluoro-1-(trifluoromethyl)ethyl ether). Total blood volume was drawn from the posterior vena cava using a 1 mL syringe coated with heparin. Serum was separated by centrifugation for 10 min at 1800× g at 4 °C. Then subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), brown adipose tissue (BAT), liver, pancreas, skeletal muscle (soleus and gastrocnemius) were rapidly removed and divided in smalls parts. Some samples were frozen in liquid nitrogen and stored at −80 °C. The rest of the samples were fixed in ice-cold 4% (w/v) paraformaldehyde in phosphate buffer saline (PBS) for histological analyses as described below.
4.3. Total Phenolic Content and Chemical Composition Analysis of Experimental Diets
Total phenolic content of the diets was determined by the Folin–Ciocalteu colorimetric method described by Singleton et al. [56
]. Briefly, experimental diets were diluted in methanol:water (80:20) and extracted according to Delgadillo-Puga et al. [10
], Then, 3 mg of diets extracts were diluted in 1 mL of distilled water. Five hundred µL of each stock solution was transferred into a volumetric flask and 3% HCL was added to a final volume of 5 mL. From the resulting solution, an aliquot of 100 µL was mixed with a 2 mL of 2% NaCO3
solution and allowed to stand during two minutes. Then, 100 µL of Folin–Ciocalteu reagent (previously diluted 1:1 v/v with water) were added to the solution and incubated at room temperature for 30 min protected from light. Absorbance was measured at 765 nm in a 3.0 mL UV-Quartz cell (Hach Co. cat. 48228-00, Loveland, CO, USA) using a UV spectrophotometric equipment (Beckman, DU-70, Brea, CA, USA). A calibration curve of gallic acid was prepared to estimate the total polyphenols concentration. Results were expressed as mg of gallic acid equivalents (GAE) per 100 g of diet (Table 1
4.4. Serum Determinations
Serum glucose, cholesterol and triacylglycerols (Tg) were determined using a unicel DxC 600 analyzer (Beckman Coulter, Brea, CA, USA). Insulin (cat. 80-INSMS-EO1, ALPCO, Salem, NH, USA) and leptin (cat. KMC228, Thermo Fisher Scientific, Waltham, MA, USA) were determined by ELISA assays according with the manufacturer’s recommendations.
4.5. Lipid Extraction, Derivatization and Fatty Acids Quantification
Total lipids from diets and liver were extracted with chloroform-methanol (0.09 g of sample) according to the method described by Folch [57
] and the fatty acids then methylated as previously described [58
]. The concentration of fatty acids in the diets or liver was determined by gas chromatography (GC) after an organic extraction and its derivatization to methyl esters. The samples were injected into a DB-225 MS 30 m × 0.25 mm × 0.25 µm analytical column (Agilent, Santa Clara, CA, USA) coupled to an auto-sampler (Agilent 6850).
4.6. Body Composition and Energy Expenditure Measurement
Body composition (lean and fat mass) was evaluated in each mouse using magnetic resonance (EchoMRI; Echo Medical Systems, Houston, TX, USA). Energy expenditure was measured by indirect calorimetry in an Oxymax Lab Animal Monitoring System (CLAMS; Columbus Instruments, Columbus, OH, USA). Animals were individually housed in Plexiglas cages with an open flow system connected to CLAMS for 24 h. Prior to the test, animals were acclimatized for 24 h, fasted for 12 h in the light period and fed during the dark period. Throughout the test, O2 consumption (VO2, mL/kg/h or mL/kg lean mass/h) and CO2 production (VCO2, mL/kg/h) were measured sequentially during 90 s. Multiple linear regression was performed to evaluate the slopes of change of VO2 (mL/h) per unit change of body weight or lean mass. The respiratory exchange ratio (RER) was calculated as the average ratio of produced CO2 to O2 inhaled (VCO2/VO2).
4.7. Intraperitoneal Glucose and Insulin Tolerance Test
The intraperitoneal glucose tolerance test (ipGTT) was performed by an intraperitoneal administration of a glucose load (2 g/kg body weight) after 6 h of fasting. The intraperitoneal insulin tolerance test (ipITT) was performed by an intraperitoneal administration of an insulin load (0.5 UI/kg body weight) after 6 h of fasting. In both test, blood glucose was determined using a blood glucose monitoring system (Freestyle Optium, Abbott Laboratories, Lake Forest, IL, USA) with blood samples collected from the tail vein 0, 15, 30, 45, 60, 90, and 120 min after the glucose administration [59
4.8. Histological Analysis of Liver, Pancreas, White and Brown Adipose Tissue
Samples of liver, pancreas and adipose tissues were fixed in PBS-buffered 4% paraformaldehyde, dehydrated, embedded in paraffin and cut into 4 µm slices. Sections were stained with hematoxylin and eosin (H&E) and observed under a Leica DM750 microscope (Leica, Wetzlar, Germany) using a 20X lens. Analysis of adipocyte area was performed using Adiposoft software as previously described [60
]. Measurement of pancreatic islet areas was carried out with ImageJ software (National Institutes of Health, Bethesda, MD, USA). Two different images of each tissue were analyzed after calibration of the software using the scale bar with a length of 100 µm. Perimeter of each islet was drawn manually and total areas were analyzed by each treatment.
4.9. Mitochondria Abundance and Lipid Content in Skeletal Muscle
To visualize mitochondrial abundance and lipid content in skeletal muscle; gastrocnemius and soleus muscles were embedded in optimal cutting temperature compound and rapidly frozen by immersion into liquid nitrogen and kept at −80 °C. Muscle succinate dehydrogenase (SDH) activity was determined according to Yamamoto et al. [61
] and Kalmar et al. [62
]. Briefly, frozen sections (12 μm) were mounted in positively charged slides (Kling-On SFH1103, BIOCARE Medical, Concord, CA, USA) and incubated in SDH staining solution (0.55 mM nitro-blue tetrazolium and 0.05 mM sodium succinate) and incubated at 37 °C for 60 min. Afterwards, the slides were washed with deionized water and sequentially dehydrated (2 min) in 30%, 60% and 90% acetone. Then, the slides were rehydrated (2 min) with 60% and 30% acetone in deionized water. Digital photographs were taken from each section at 20× magnification as described above, and positive fibers (blue) were quantified with Image J software as described previously [63
To evaluate lipid content in muscle fibers, frozen slides were rapidly fixed by immersion in ice-cold PBS-buffered 4% paraformaldehyde for 10 min, washed in deionized water and incubated for 30 min with the lipophilic dye BODIPY 493/503 (790389, Sigma-Aldrich, 20 µg/mL in PBS). Slides were washed in PBS and mounted with an aqueous mounting medium with DAPI (ProLong Gold Antifade Mountant P36931, Invitrogen, Carlsbad, CA, USA). Digital photographs were taken from each section at 20X magnification under fluorescence illumination. DAPI (nuclei) and BODIPY (fat) images were merged and fat content quantified using ImageJ software.
4.10. Lipid Content in Liver
To visualize hepatic neutral lipids, frozen liver samples were sectioned with a cryostat (8 μm) and stained with 0.5% Oil Red O (ORO) in propylene glycol (Sigma-Aldrich). For the quantitative analysis of the ORO staining, images were converted to an 8-bit grayscale in ImageJ according to Mehlem et al. [64
] and the integrated density was measured, which is the product of area and mean gray value.
4.11. Quantitation of Tumor Necrosis Factor Alpha (TNF-α) in Adipose Tissue
Subcutaneous and visceral adipose tissue punches were homogenized with 500 mL of cold lysis buffer (Merck), centrifuged and stored at −80 °C until analyzed. Content of TNF-α was measured using a 96-well plate of Milliplex MAP kit, with a mouse cytokine/chemokine multiplex magnetic bead panel (Cat. MCYTOMAG-70K, Merck, Kenilworth, NJ, USA). Samples were analyzed in a MAGPIX luminometer and the concentration of TNF-α calculated with a 5-parameter polynomial standard curves ranging from 0.65 to 10,000 pg/mL using the xPonent 4.2 software (Luminex Corporation, Austin, TX, USA). All samples from each treatment were analyzed simultaneously to minimize error.
4.12. Immunohistochemistry of UCP-1 in Brown and White Adipose Tissues and Macrophages in Subcutaneous Adipose Tissue
The adaptive thermogenesis marker uncoupling protein one (UCP-1) and macrophage marker F4/80 were determined in 4 μm thick sections of formalin-fixed paraffin embedded tissue according to Leal-Díaz et al. [63
] and Méndez-Flores et al. [65
] with some modifications. Endogenous peroxidase was blocked with 3% H2
solution. Then, non-specific background staining was avoided with the immunohistochemistry background blocker (Enzo Life Sciences Inc., Farmingdale, NY, USA). Brown and white adipose tissues were incubated with rabbit monoclonal anti-mouse UCP-1 (Abcam, Cambridge, MA, USA) and subcutaneous adipose tissue was incubated with F4/80 IgG2a,k antibody (Santa Cruz Biotechnology, Dallas, TX, USA) diluted at 10 µg/mL for 40 min at room temperature. Binding was identified with Universal Dako labelled streptavidin biotin reagent + peroxidase for primary antibodies from rabbit, mouse and goat (Dako, Glostrup, Denmark). Slides were incubated with streptavidin peroxidase for 15 min, followed by incubation with the peroxidase substrate 3,3′-diaminobenzidine (DAB; SIGMA-Aldrich) for 10 min. The sections were counterstained with hematoxylin, dehydrated with alcohol and xylene, and mounted in resin. Instead of primary antibody, negative controls were performed with normal human serum diluted 1:100 and with the IHC universal negative control reagent specifically designed to work with rabbit, mouse, and goat antibodies (IHC universal negative control reagent, Enzo Life Sciences, Inc.). Instead of the primary antibody the reactive blank was incubated with saline-egg albumin (Sigma-Aldrich). Controls excluded nonspecific staining or endogenous enzymatic activities. We examined at least two different sections of each tissue. Digital photographs were taken from each section at 40X magnification as described above.
4.13. Liver, Muscle and Adipose Tissue Gene Expression by Quantitative-Polymerase Chain Reaction (PCR)
(a) Nucleic acid extraction. Total RNA was extracted using a Power SYBR Green Cells-to-Ct kit (Catalog 4402953, Invitrogen). Briefly, frozen tissues were homogenized in ice-cold dissociating reagent in a TissueLyser (Qiagen, Germantown, MD, USA) in order to disintegrate the tissue to release nucleic acids. (b) RNA integrity check. Total RNA was resolved by electrophoresis in a 1.5% agarose gel in 1× borate solution at 100 volts for 50 min. (c) Retrotranscription for cDNA synthesis. Retrotranscription was carried out using the RT Master Mix included in the kit, under the following conditions: incubation at 37 °C for 60 min, then 95 °C for 5 min for inactivation of the RT enzyme. (d) Real time PCR. The analysis was carried out using the LightCycler 480 Instrument II real-time PCR equipment (Roche, Basel, Switzerland) under the following amplification conditions. Enzyme activation: 1 cycle at 95 °C for 10 min, PCR: 55 cycles at 95 °C for 15 s, 60 °C 1 min. Dissociation curve: default configuration of the equipment, finally 1 cooling cycle at 4 °C indefinitely. After Real-time PCR reaction, quantification cycle (Cq) was determined for each sample from the amplification plot. ∆∆Cq value was calculated by subtraction of the 36b4 Cq from each sample Cq and used for data analysis. PCR primers for SREBP1, PPARδ, AMPK, PPARγ2, adiponectin and leptin were synthesized by Sigma-Aldrich. Primers were designed using Primer-BLAST (NCBI, NIH) (Table 2
Tissues were homogenized at 4 °C in ice-cold RIPA buffer containing phosphate-buffered saline (PBS), 1% IGEPAL, 0.5% sodium deoxycholate, 0.1% sodium dodecyl sulphate, 1 mM sodium fluoride, 2 mM sodium orthovanadate, and 1 tablet/10 mL of protease inhibitor mixture (Complete Mini, Roche Diagnostics) in a TissueLyser (Qiagen). The samples were incubated on ice for 30 min, centrifuged at 17,400× g for 15 min at 4 °C, and the supernatant was transferred to a new tube and stored at −80 °C until use. Protein concentration was determined with the Lowry method. Protein samples (40 µg) were separated on a 10% SDS-polyacrylamide gel and transferred to a polyvinylidene difluoride (PVDF) membranes (Hybond-P, Amersham, GE Healthcare, Chicago, IL, USA) using a wet electroblotting System (Bio-Rad, Hercules, CA, USA). The membranes were blocked for 1 h with 5% non-fat dry milk, and incubated with primary antibody diluted in blocking solution overnight. Primary antibodies were as follows: AMPKa 1/2 (Santa Cruz Biotechnology, dilution 1:3000 liver and 1:1500 skeletal muscle), p-AMPK, Th2-172 (Santa Cruz Biotechnology, dilution 1:1000 liver and skeletal muscle), JNK (Merck Millipore, Burlington, MA, USA) dilution 1:1000 liver), p-JNK (Thr183/Tyr185, Thr221/Tyr223) (Cell Millipore dilution 1:1000 liver), UCP-1 (abcam dilution 1:1000 brown adipose tissue), GAPDH (Abcam 1:100 brow adipose tissue), HSL (Cell Signaling Danvers, MA, USA, dilution 1:2000 white adipose tissue), p-HSL (Cell Signaling dilution 1:2000 white adipose tissue). The membranes were washed three times with TBS-T for 10 min and then incubated with horseradish peroxidase-conjugated secondary antibody (goat anti-rabbit or rabbit anti-goat 1:3500) for 1.5 h. Visualization was performed using a chemiluminescent detection reagent (Millipore, MA, USA). Digital images of the membranes were obtained by a ChemiDoc MP densitometer and processed by Image Lab software (Bio-Rad). The results are reported as phosphorylated/total protein ratio. A value of 1 was arbitrarily assigned to the control group, which were used as a reference for the other conditions.
4.15. Statistical Analyses
Data is expressed as mean ± standard error of the means (S.E.M.). Shaphiro-Wilk normality test was used to check data distribution. All groups were analyzed by one-way ANOVA followed by Tukey multiple comparison post hoc test using GraphPad Prism 7.0 (GraphPad Software, San Diego, CA, USA). The differences were considered statistically significant at p < 0.05. Mean values with different lowercase letters show statistical differences between each other.