This research aims to discover the effect of active compounds in Sulehe in the form of isoflavones, PUFAs, and gingerol against PPAR-γ expression in a rat model of insulin resistance.

Research design

This test of the potential of Sulehe diet for improving insulin resistance to PPAR-γ expression is a true experimental laboratory in vivo study with a post-test only group design approach. This study used 24 healthy male Sprague Dawley rats aged 12 weeks and weighing 150–200 g. Rats were divided into six experimental groups: (1) negative control (C−), (2) positive control (C+), (3) soy milk 5000 mg/kg BB diet, (4) ginger 500 mg/kg BB diet, (5) Sulehe (soy milk 2500 mg/kg BB + ginger 250 mg) diet, 6) Sulehe (soy milk 5000 mg/kg BB + ginger 500 mg) diet.

PPAR-γ activity examination

Insulin resistance was induced in rats using a high-fat and fructose diet (DTLF) method; their blood glucose levels were measured using a glucometer (Onetouch Ultra 2 (Lifescan Inc, USA) to confirm insulin resistance. Measurement of insulin resistance using HOMA-IR method (homeostatic model assessment - insulin resistance) which obtained by multiplying fasting glucose (mg/dL) with fasting insulin level (ng/mL)/405. Rats were insulin resistance if the value of HOMA-IR is 2. HOMA β was obtained by the formula (360 x Insulin levels): (Fasting glucose (mg/dl) - 63) x %.

A small drop of blood, obtained by pricking the skin with a lancet, was placed on a disposable test strip glucometer to calculate the blood glucose level. Level of glucose was displayed in units of mg/dl or mmol/l.

Western blot

Soy milk, ginger, and Sulehe were given once a day using a feeding tube, for 30 consecutive days. PPAR-γ activity was examined using a western blot method with rat skeletal muscle tissue samples. Each tissue samples was suspended with a buffer containing 20mM Tris-HCl, 1mM EDTA, and 0.1 mM PMSF. The cell suspension was centrifuged at 12,000 rpm for 5 minutes, at 4°C then centrifuged again at 15,000 rpm for 1 hour at 4°C. The sample was reconstituted with 15% SDS-PAGE gel. The electrophoresis gel was washed with distilled water and soaked in a blotting buffer. The nitrocellulose (NC) membrane was soaked with Phosphate Buffer Saline (PBS) for 10 minutes at room temperature and immersed in blotting buffer before blotting process. The further transfer was carried out for 12 hours at 25 volts at 4°C. The membrane was then blocked in PBS-T Skim milk 5% for 1 hour while shaking and washed 3x5 minutes in PBS-T. The membrane was incubated with primary antibodies in PBS-T Skim 5% (1: 200) overnight at 4°C and washed 3x5 minutes with TBS. The membrane was then incubated with secondary antibody Alkaline Phosphatase (AP) conjugated (1: 2500 in TBS) for 1 hour at room temperature and washed with PBS-T for 4x5 minutes. Further protein or antigen bands detection was conducted with the addition of Western Blue substrate (in dark room) to the membrane overnight. The reaction was stopped by washing the membrane with distilled water.

Ethical review

This study has been approved by Animal Care and Use Committee University of Brawijaya No. 687/KEP/UB signed on Jan 20, 2017.

Statistical analysis

The data were analyzed for normality and homogeneity. The data used to conclude are group data with Shapiro–Wilk normality test values > 0.05 and with homogeneity of variance test values > 0.05. Data were analyzed by one-way ANOVA, followed by a least significant difference (BNT) test to determine the significant differences between treatments (p < 0.05).

The results of this study are presented below: (1) descriptive statistical analysis, (2) homogeneity test results, (3) normality test results, and (4) one-way ANOVA test results.

Descriptive statistics analysis

The results of analysis of PPAR-γ descriptive statistics are presented in Table 1.

Table 1. Descriptive statistics analysis

The PPAR-γ level in normal rats was 578 ± 82.02. The Sulehe diet given to group 6 (soybean milk 5000 mg/kg BB + ginger 500 mg/kg BB) yielded the highest mean level of PPAR-γ, 1158 ± 53.74. The lowest average, 449.5 ± 118.09, was found in the group given only 500 mg ginger (Figure 1).

Fig. 1. Histogram of GLUT4, PPAR-gamma, and serine expression for each experimental treatment.

Fig. 3. Western blotting results for PPAR-γ, GLUT4, and serine for each treatment group.

Western blotting of ppar-γ

Fig. 2. Western blot of GLUT4, PPAR-γ, and Ser-636 for each treatment group

Least significant difference (LSD) statistics results

a. Normality test results

A Shapiro–Wilk test was used because of n < 50. The results obtained are shown in Table 2.

Table 2. Normality test

The results of the normality test on the PPAR-γ variable show a sig value > 0.05, concluding that the data have a normal distribution.

b. Homogeneity test results

This test used Levene’s test, and results are shown in Table 3.

Table 3. Homogeneity test

The homogeneity results indicate that the PPAR-γ variable is not homogeneous (p-value < 0.000).

c. One-way ANOVA test results

Normality of terms was fulfilled, and the variety of data already known. The test was continued to determine whether there were differences in overall results based on the treatment provided (Table 4 and 5).

Table 4. ANOVA test results

Table 5. Summary of ANOVA test results

Based on the ANOVA test results, there were differences in all four treatments (sig ANOVA < 0.05). The significant differences for each treatment can be seen in the following LSD post hoc results (Table 6).

Table 6. Descriptive statistics analysis

From Table 7, it can be seen that there was a significantly different PPAR-γ result only for the combination of soy milk + ginger 500 mg, with a difference value is −345.5. The results of this study show that PPAR-γ expression increased in insulin resistance-modeled rats, but Sulehe (soy milk 5000 mg + ginger 500 mg) showed a higher rate of PPAR-γ than the insulin resistance model. From these results, it is clear that the treatment provided in this study up-regulates PPAR-γ activity. PPAR-γ is important in the proliferation and differentiation of adipocytes, through the activity of free fatty acid influx into adipocytes, and decreases cytokine expression [19]. This statement explains that the combination Sulehe therapy blocks serine-636 phosphorylation and improves insulin sensitivity, as evidenced by increased PPAR-γ post-treatment activity in the combination therapy group. This explains that Sulehe consumption during treatment inhibits the access of inflammatory cytokines through the PPAR-γ activation pathway.

Table 7. Summary of post hoc LSD results

As described by Kintscher and Law, the loss of PPAR-γ activity in skeletal muscle results in insulin resistance conditions through impaired insulin levels in adipose and liver tissue [20]. This was validated by the results of this study, in that the PPAR-γ activity in the non-treated DM control group was higher than that in the normal group (578). This could be explained by the brief induction of the high-fat diet during the manufacture of insulin resistance models so that acute induction will increase PPAR-γ activity as a form of homeostatic compensation [12], but there is no explanation regarding the procedure of making an insulin resistance model. PPAR-γ agonist application gives a more direct effect on skeletal muscle. This explains why the Sulehe diet affected PPAR-γ in skeletal muscle (rat insulin resistance model) compared to other experimental groups. In fact, the expression of PPAR-γ in skeletal muscle is only about 5–10% of its expression level in adipose tissue, and PPAR deficiency in muscle causes secondary insulin resistance in adipose and liver tissue. This study suggests further study on the importance of looking at the comparison of PPAR-γ in adipose tissue and a liver peripheral resistance model after administration of Sulehe [20].

Based on the results of this study, it can be concluded that Sulehe or combination of soy milk and ginger at certain concentration could increase PPAR-γ expression significantly. Hence, Sulehe could be an alternative diet for people with type 2 diabetes melitus to reduce the insulin resistence.

Source of funding. This research had no financial funding.

Conflict of interests. Authors declare no explicit and potential conflicts of interests associated with the publication of this article.

Author’s involvement. Wiwik Handayani developed the study design and edited manuscript, Sri Andarini collected the data and performed statistical analysis, Diana Lyrawati drafted and edited the manuscript, and Achmad Rudijanto performed laboratory testing and edited the manuscript.