Abstract
Fat-induced hepatic insulin resistance (FIHIR) in obesity induced by high-fat diet leads to ectopic lipid accumulation and may contribute to the pathogenesis of type 2 diabetes. We examined the alterations in hepatic gene expression involved in FIHIR by using obese insulin-resistant and diabetic hamsters that received high-fat diet with or without low-dose streptozotocin. Microarray analysis and confirmatory real-time RT-PCR indicated that increased mRNA levels of sterol regulatory element-binding proteins (SREBPs) and decreased mRNA levels of liver X receptor (LXRα) and peroxisome-proliferator–activated receptor (PPARα) occurred in FIHIR in insulin-resistant and diabetic hamsters. Expression levels of hepatic LXRα, SREBPs, and PPARα differed significantly between insulin-resistant and diabetic hamsters. Expression of LXRα, SREBPs, and PPARα all change in FIHIR associated with hepatic lipid accumulation in insulin-resistant and diabetic hamsters in which disease is induced by high-fat diet and streptozotocin injection.
Abbreviations: Acaa2, acetyl coenzyme A acyltransferase 2; Acadm, medium-chain acyl coenzyme A dehydrogenase; ACC, acetyl coenzyme A carboxylase; Acox, acyl coenzyme A oxidase; Cpt1, carnitine–palmitoyl transferase 1; CYP7A1, cholesterol 7α hydroxylase; FAS, fatty acid synthase; FIHIR, fat-induced hepatic insulin resistance; Gck, glucokinase; G6Pase, glucose-6-phosphatase; HDL, high-density lipoprotein; HMG CoA, 3-hydroxy-3-methylglutaryl coenzyme A; IRS, insulin receptor substrate; LDL, low-density lipoprotein; LDLR, LDL receptor; LXR, liver X receptor; PEPCK, phosphoenolpyruvate carboxykinase; PGC1α ,peroxisome-proliferator–activated receptor γ coactivator 1α; PPAR, peroxisome-proliferator–activated receptor; SCD1, stearoyl coenzyme A desaturase 1; SREBP, sterol regulatory element-binding protein
Insulin resistance plays a critical role in the development of type 2 diabetes.7,9,27 However, the underlying mechanisms remain poorly understood. Obesity induced by a diet high in saturated fat and cholesterol is the most common and important environmental factor for the insulin resistance of type 2 diabetes.2,6 A potential mechanism is ectopic lipid accumulation caused by abnormalities in lipid metabolism in insulin-sensitive tissues (so-called ‘lipotoxicity’), thereby leading to fat-induced insulin resistance.14,24 The liver, an insulin-sensitive tissue, plays a unique role in controlling carbohydrate, lipid, and energy metabolism by maintaining glucose and lipid concentrations within a normal range. Hepatic insulin resistance contributes greatly to the development of the hyperglycemia, dyslipidemia, hepatic steatosis, and systemic insulin resistance in type 2 diabetes mellitus.13,20 Therefore, the mechanisms involved in hepatic insulin resistance, especially FIHIR are a prerequisite to understand pathogenesis of obesity-related type 2 diabetes.
The genetic susceptibility for diabetes and many characteristic features of lipid metabolism are similar between hamsters and human.28 We previously developed obese insulin-resistant and type 2 diabetic hamster models1,12,16 to study the pathophysiologic features and natural history of obesity-related insulin resistance and type 2 diabetes. Microarray technology is a powerful tool to decipher the complex gene expression profiles associated with various diseases. In the present study, we used microarray technology to determine identify alterations in hepatic gene expression and to explore molecular mechanisms involved in FIHIR in insulin-resistant and type 2 diabetic hamsters. Understanding the gene expression patterns involved in FIHIR in obese insulin-resistant and type 2 diabetic states may provide new targets for dietary or pharmacologic interventions.
Materials and Methods
All procedures involving animal handling and tissue harvesting had been reviewed and approved by the Laboratory Animal Care and Use Committee and Institutional Animal Welfare Committee of the Institute of Laboratory Animal Science.
Animals.
Golden Syrian hamsters (Mesocricetus auratus; SiChuan Academy of Medical Sciences, SiChuan, China; age, 5 mo; male and female) were free of all known hamster pathogens and were housed individually under SPF husbandry conditions in a temperature- (18 to 25 °C) and humidity- (40% to 70%) controlled room with a 12:12 dark:light cycle and free access to water and standard laboratory chow (1010 Series, Institute of Laboratory Animal Science, Beijing, China). Hamsters were allowed to adapt to the environment for 2 wk before their use in experiments. Disease in the insulin-resistant and diabetic hamsters was induced as previously described1,12,16 with slight modifications. Briefly, most hamsters were fed high-fat diet containing 20% lard, 10% egg yolk powder, 1% cholesterol, and 0.1% cholic acid (Institute of Laboratory Animal Science) for 4 wk; the remaining hamsters received standard laboratory chow for 4 wk. As in our previous studies, most hamsters fed the high-fat diet spontaneously developed insulin resistance; these hamsters then were divided randomly into 2 groups. One group was injected twice (1 d between injections) with streptozotocin (40 mg/kg IP; Sigma, St Louis, MO) dissolved in vehicle (0.05 mol/L citric acid, pH 4.5) to induce type 2 diabetes; the other group was injected with an equivalent volume of vehicle only. The hamsters fed standard laboratory chow (control animals) also were injected with vehicle only. After treatment, the hamsters were kept on the same diet as that before injection for 2 wk. Diabetic and insulin-resistance states were confirmed through fasting blood glucose levels (diabetic animals, ≥ 9 mmol/L) and oral glucose tolerance tests. After induction of disease, hamsters of the appropriate phenotype were selected randomly to create 3 groups (control, insulin-resistant, and type 2 diabetic) of 10 animals each. All hamsters were maintained in a controlled environment with a 12:12-h light:dark cycle and had free access to food and water throughout the study.
After the 6-wk study, hamsters were fasted for 12 h before being anesthetized with ether, terminally bled, and euthanized by using an appropriate secondary method. Blood samples were obtained from the retro-orbital sinus. Serum was separated by centrifugation at 3000 ×g for 20 min at 4 °C and stored at –80 °C until used for determining metabolic and biochemical parameters. Livers were removed rapidly, weighed, frozen in liquid nitrogen, and stored at –80 °C until analysis.
Oral glucose tolerance tests.
Oral glucose tolerance tests were performed in hamsters that had been fasted overnight. Oral glucose was administered at 2 g/kg. Blood samples were obtained from the retro-orbital sinus of ether-anesthetized hamsters at 0, 30, 60, 120, and 180 min after glucose challenge, and blood glucose and insulin levels were measured.
Blood chemistries.
Serum concentrations of free fatty acids, total cholesterol, low-density lipoprotein (LDL)–cholesterol, high-density lipoprotein (HDL)–cholesterol, and triglycerides were analyzed by using commercial kits (Randox Laboratories, Antrim, UK) in accordance with the manufacturer's instructions in an automatic biochemical analyzer (model 8060, Hitachi, Tokyo, Japan). Total cholesterol and triglyceride concentrations were determined by Trinder-based (CHOD-PAP method and GPO-PAP method) colorimetric end-point assays by using commercial kits (CH200 and TR1697, Randox). Free fatty acid was measured by means of the NEFA colorimetric method (FA115, Randox). HDL–cholesterol and LDL–cholesterol were quantified by a direct clearance method (CH2652 and CH2656, Randox). Blood glucose was measured with a OneTouch Ultra Blood Glucose Monitoring System (LifeScan International, Milpitas, CA). Serum insulin levels were determined by using a rat–mouse insulin ELISA kit (Linco Research, St Charles, MO) in accordance with the manufacturer's protocol.
Histology.
To demonstrate hepatic fat accumulation, liver tissue was fixed in buffered formalin, embedded in paraffin, cut into 5-μm sections, and stained with hematoxylin and eosin for microscopic examination. Hepatic fat accumulation was confirmed by oil red O staining of frozen liver tissue.
Microarray analysis.
Total RNA was extracted from frozen liver tissue by using RNeasy Mini kit (Qiagen, Hilden, Germany). After purification, the quantity and quality of total RNA were determined by spectrophotometry and formaldehyde–agarose gel electrophoresis. Total RNA (5 μg) was reverse-transcribed into cDNA (cDNA Synthesis Kit, Promega, Madison, WI). After purification, cRNA was synthesized from the cDNA (T7 RiboMAX Express Large-Scale RNA Production System, Promega), and cRNA (2 μg) was reverse-transcribed into cDNA. cRNA reverse-transcribed products (2 μg) labeled with either 40 μmol/L dCTP–Cy5 or 40 μmol/L dCTP–Cy3 (Amersham Pharmacia Biotech, Piscataway, NJ) by using Klenow (Takara, Dalian, China), random nonamers as primers, 60 μmol/L dCTP, and 120 μmol/L dATP, dGTP, and dTTP in a final volume of 200 μL. The labeled cDNA was purified (PCR NucleoSpin Extract II Kit, Macherey–Nagel, Düren, Germany) and dried.
A 36 k mouse genome (Mouse Genome version 4.0, Operon, Huntsville, AL) representing approximately 25,000 genes (http://www.operon.com) was printed in arrays on 75 × 25 mm slides with the use of SmartArray (CapitalBio, Beijing, China). According to the manufacturer, the high conservation of genomic sequences and high likelihood of crossreactivity and genomic hybridization between mouse and hamster make it possible to hybridize a mouse microarray with hamster cDNA. 0.9 μg labeled cDNA was added to a total of 30 μL hybridization solution containing 3× SSC, 5× Denhardt solution, 25% formamide, and 0.2% SDS. The labeled cDNA in hybridization solution was added to microarray slides and hybridized at 42 °C for 12 h. After hybridization, slides were washed at 42 °C for 5 min in solution containing 2× SSC and 0.2% SDS and then transferred to 0.2× SSC at room temperature for 5 min. Slides were dried by centrifugation. Liver tissues from 3 hamsters of each group were randomly selected to be used for microarray analysis. All experiments were performed in duplicate. Fluorescence intensities of microarray spots were measured by using a laser scanner (double-channel LuxScan 10KA, CapitalBio, Beijing, China) and image analysis software (GenePix Pro 4.0, Axon Instruments, Foster City, CA). Lowess normalization was applied to the primary data. After normalization, the ratio between the expression levels of control and treated animals was calculated, and differentially expressed genes (greater than or less than 1.5-fold) underwent gene ontology analysis by using publically available databases and software.
Real-time RT-PCR.
For verification of the microarray analysis results, selected genes underwent real-time RT-PCR analysis. Total RNA was extracted from frozen liver tissue (RNeasy Mini kit, Qiagen). The quantity and quality of total RNA were determined by spectrophotometry, and its integrity was assessed by 1% agarose gel electrophoresis. cDNA was synthesized from 1 μg total RNA (iScript cDNA Synthesis Kit, Bio-Rad Laboratories, Hercules, CA) in accordance with the manufacturer's protocol. Specific primers pairs for each gene were designed by using Primer Express software (Applied Biosystems, Foster City, CA) or obtained from previously published papers. The reverse-transcribed products of 50 ng total RNA were amplified by using iQ Syber Green Supermix and iCycler iQ Real-Time PCR Detection System (Bio-Rad Laboratories) according to the manufacturer's instructions. Amplification conditions were: 95 °C for 3 min, followed by 45 cycles of 95 °C for 10 s and 59 °C for 45 s. After amplification, the reaction mixture underwent 80 cycles (10 s each) beginning at 59 °C and increasing by 0.5 °C each cycle for melting curve analysis to check the identity and purity of the amplified products. Each reaction was performed in triplicate. To ensure specific amplification, negative controls were included in the PCR reaction. Real-time PCR efficiency measured before amplification was close to 1. Thus the relative quantification for a target gene in a given sample was calculated according to the 2 – ΔΔCT method.11 β actin was used as the reference gene. The nucleotide sequences of the forward and reverse primers are presented in Table 1.
Table 1.
Primers used for real-time RT-PCR
| Gene | Accession no. | Forward and reverse primers |
| SREBP1a | NM_011480 | 5′ ATGGACGAGCTGGCCTTCGGTGAGGCGGC 3′ |
| 5′ CAGGAAGGCTTCCAGAGAGGA 3′ | ||
| SREBP1c | NM_011480 | 5′ GCTGTTGGCATCCTGCTATC 3′ |
| 5′ TAGCTGGAAGTGACGGTGGT 3′ | ||
| SREBP2 | U12330 | 5′ AGCTGGCAAATCAGAAAAACAAG 3′ |
| 5′ GATTAAAGTCTTCAATCTTCAAGTCCAC 3′ | ||
| LXRα | AJ132601 | 5′ TCAGCATCTTCTCTGCAGACCGG 3′ |
| 5′ TCATTAGCATCCGTGGGAACA 3′ | ||
| LXRβ | NM_009473 | 5′ AAGCAGGTGCCAGGGTTCT 3′ |
| 5′ TGCATTCTGTCTCGTGGTTGT 3′ | ||
| PPARα | NM_011144 | 5′ TGAGGAAGCCGTTCTGTGAC 3′ |
| 5′ GGTGTCATCTGGATGGTTGC 3′ | ||
| HMG–CoA reductase | X00494 | 5′ AGATACTGGAGAGTGCCGAGAAA 3′ |
| 5′ TTTGTAGGCTGGGATGTGCTT 3′ | ||
| HMG CoA synthase | L00326 | 5′ CCTGGGTCACTTCCTTTGAATG 3′ |
| 5′ GATCTCAAGGGCAACGATTCC 3′ | ||
| LDLR | NM_010700 | 5′ CCAACCTGAAGAATGTGGTG 3′ |
| 5′ CAGGTCCTCACTGATGATGG 3′ | ||
| CYP7A1 | NM_007824 | 5′ AGCAACTAAACAACCTGCCAGTACTA 3′ |
| 5′ GTCCGGATATTCAAGGATGCA 3′ | ||
| Gck | NM_010292 | 5′ AGAGCAGATCCTGGCAGAGT 3′ |
| 5′ TGGTTCCTCCCAGGTCTAAG 3′ | ||
| FAS | NM007988 | 5′ CACAGATGATGACAGGAGATGG 3′ |
| 5′ TCGGAGTGAGGCTGGGTTGAT 3′ | ||
| SCD1 | NM009127 | 5′ TGGGTTGGCTGCTTGTG 3′ |
| 5′ GCGTGGGCAGGATGAAG 3′ | ||
| ACC | AF356089 | 5′ ACACTGGCTGGCTGGACAG 3′ |
| 5′ CACACAACTCCCAACATGGTG 3′ | ||
| PGC1α | BC066868 | 5′ TCTGGAACTGCAGGCCTAACTC 3′ |
| 5′ GCAAGAGGGCTTCAGCTTTG 3′ | ||
| PEPCK | NM_011044 | 5′ GAGTTCCTGCCTCTCTCCAC 3′ |
| 5′ TTCCACGAACTTCCTCACTG 3′ | ||
| G6Pase | U00445 | 5′ CATCAATCTCCTCTGGGTGGC 3′ |
| 5′ TGTTGCTGTAGTAGTCGGTGTCC 3′ | ||
| Acox | NM_053115 | 5′ CCAGGACAGAGGTTCTTGGT 3′ |
| 5′ TCTCAGGAAGGACTTGGCTT 3′ | ||
| Cpt1 | NM_013495 | 5′ CTCAGTGGGAGCGACTCTTCA 3′ |
| 5′ GGCCTCTGTGGTACACGACAA 3′ | ||
| Acadm | NM_007382 | 5′ TGACGGAGCAGCCAATGA 3′ |
| 5′ ATGGCCGCCACATCAGA 3′ | ||
| Acaa2 | NM_177470 | 5′ GTGTGGAGGAACAGAGAGCA 3′ |
| 5′ TGCCCACAAAGTATCTTCCA 3′ | ||
| β actin | AY618569 | 5′ AGAGGGAAATCGTGCGTGAC 3′ |
| 5′ CAATAGTGATGACCTGGCCGT 3′ |
Statistical analysis.
Data are expressed as mean ± SD. Statistical difference was assessed by using 2-tailed Student t tests and 1-way ANOVA; statistical significance was defined as having a P value of less than 0.05. Analyses were performed by using SPSS 13.0 for Windows software (SPSS, Chicago, IL).
Results
Metabolic characterization of insulin-resistant and diabetic hamsters.
The phenotypic and metabolic characterizations of insulin-resistant and type 2 diabetic hamsters are presented in Table 2. At the end of the experiments, insulin-resistant and diabetic hamsters weighed significantly more than did control hamsters, insulin-resistant and diabetic hamsters did not differ in body weight. Liver weight was higher in both the insulin-resistant and diabetic groups than in the control group. Compared with values for control hamsters, serum lipid levels (free fatty acids, total cholesterol, LDL–cholesterol, and triglycerides) were significantly higher in both insulin-resistant and diabetic hamsters. Blood glucose was significantly increased in the diabetic groups compared with control or insulin resistant. Blood glucose concentrations in control and diabetic hamsters after streptozotocin treatment are shown in Figure 1. Compared with control hamsters, insulin-resistant and diabetic hamsters exhibited hyperinsulinemia and relative hyperinsulinemia, respectively. Compared with those of the control group, blood glucose concentrations were higher (Figure 2 A) and areas under the insulin and glucose curves were larger (Figure 2 C, D) during oral glucose tolerance tests, and the index of insulin resistance was higher in insulin-resistant and diabetic hamsters. Given these basal metabolic data, the hamsters were representative of 3 metabolic phenotypes: normoinsulinemic and normoglycemic (control), hyperinsulinemic and relatively hyperglycemic (insulin-resistant state), and relatively hyperinsulinemic or normoinsulinemic and hyperglycemic (diabetic state).
Table 2.
Basal metabolic characterization of control, insulin-resistant, and diabetic hamsters after 6 wk of treatment
| Control | Insulin-resistant | Diabetic | |
| Body weight (g) | 124.6 ± 10.9 | 146.3 ± 7.7a | 144.4 ± 9.3a |
| Liver weight (g) | 3.68 ± 0.76 | 5.66 ± 1.05a | 6.21 ± 0.72a |
| Liver weight (% of body weight) | 2.9 ± 0.4 | 3.9 ± 0.5a | 4.3 ± 0.2ab |
| Blood glucose (mg/dL) | 81.54 ± 11.0 | 118.08 ± 16.26a | 183.24 ± 21.24ab |
| Plasma insulin (ng/mL) | 0.90 ± 0.10 | 1.89 ± 0.24a | 1.46 ± 0.20ab |
| Plasma triglyceride (mg/dL) | 169.03 ± 29.21 | 830.13 ± 71.69a | 869.96 ± 66.38a |
| Plasma free fatty acids (mmol/L) | 1.35 ± 0.29 | 6.39 ± 0.85a | 6.83 ± 0.92a |
| Plasma low-density lipoproteins (mmol/L) | 1.91 ± 0.31 | 10.1 ± 0.95a | 11.25 ± 1.71ab |
| Plasma high-density lipoproteins (mmol/L) | 1.50 ± 0.16 | 1.15 ± 0.20a | 1.03 ± 0.18a |
| Plasma total cholesterol (mmol/L) | 6.41 ± 0.56 | 14.32 ± 1.77a | 15.42 ± 1.93a |
| Index of insulin resistance (fasting glucose level [mmol/L] × fasting insulin level [mU/L]) | 102.02 ± 16.72 | 312.65 ± 72.07a | 373.4 ± 84.7ab |
Data were means ± SD (n = 10).
P < 0.05 versus control group.
P < 0.05 between values for insulin-resistant and diabetic groups.
Figure 1.
Blood glucose concentration (mean ± SD; n = 10) control (diamonds) and diabetic (triangles) hamsters after streptozotocin injection.
Figure 2.
(A) Blood glucose concentration, (B) serum insulin concentrations, (C) area under the curve (AUC) for blood glucose concentration, and (D) serum insulin AUC during oral glucose tolerance tests of control (diamonds), insulin-resistant (squares), and diabetic (triangles) hamsters. Data are given as mean ± SD (n = 10 animals per group); values for AUC were calculated for each hamster and averaged. *, P < 0.05 compared with value for control group; #, P < 0.05 compared with value for insulin-resistant group.
Hepatic lipid accumulation in insulin-resistant and diabetic hamsters.
We did not directly measure hepatic lipid content in our animal models, but the histologic study indicated similar hepatic steatosis in insulin-resistant and diabetic hamsters (Figures 3 and 4).
Figure 3.
Hepatic fat accumulation in control, insulin-resistant, and diabetic hamsters. Hepatic fat accumulation is identifiable as microvesicular or macrovesicular steatosis in hepatocytes. (A) Normal liver architecture in control hamster. Hepatic fat accumulation in (B) insulin-resistant and (C) diabetic hamsters. Hematoxylin and eosin stain; bar, 125 μm.
Figure 4.
Hepatic fat accumulation in control, insulin-resistant, and diabetic hamsters. Hepatic fat accumulation in each group is further confirmed by oil red O stain. Vesicular steatosis in hepatocytes is stained red. (A) Normal liver architecture in control hamster. Hepatic fat accumulation in (B) insulin-resistant and (C) diabetic hamsters. Oil red O stain; bar, 125 μm.
Hepatic gene expression in insulin-resistant and diabetic hamsters.
The microarray analysis indicated that the mRNA expression of approximately 7.7% (1913) and 12.5% (3113) of the 25,000 genes evaluated were at least 1.5-fold upregulated or downregulated, respectively, in insulin-resistant and diabetic hamsters overall compared with control hamsters. The number of differentially expressed genes was higher in the diabetic group than in the insulin-resistant group.
In the insulin-resistant group, mRNA levels of approximately 1087 (4.3%) genes were upregulated and 826 (3.3%) genes showed decreased expression among the 1913 differentially expressed genes. In comparison, the diabetic group showed increased expression of 1773 (7.1%) genes and decreased mRNA levels of 1340 (5.4%) genes among the 3113 differentially expressed genes. The results of gene ontology analysis indicated that 212 metabolism-related genes associated with diabetes among those differentially expressed in insulin-resistant hamsters and 256 of those in diabetic animals were mainly involved in hepatic lipid metabolism, glucose metabolism, hormonally regulated signaling pathways, and various transcription and nuclear factors. Among these 212 and 256 genes, 159 (75 upregulated and 84 downregulated) were differentially expressed in both insulin-resistant and diabetic hamsters; a partial list is given in Table 3. However, the remaining 150 differentially expressed genes were upregulated in the insulin-resistant group (22 genes) or diabetic group (46 genes) only and downregulated in the insulin-resistant group (31 genes) or diabetic group (51 genes) only (Figure 5).
Table 3.
Partial list of upregulated (>1.5-fold; positive numbers) or downregulated (<1.5-fold; negative numbers) hepatic genes associated with glucose and lipid metabolism in insulin-resistant and diabetic hamsters compared with control animals
| fold change in expression |
||||
| Accession no. | Gene name | insulin-resistant | diabetic | Regulatora |
| NM_007988 | fatty acid synthase (Fasn) | 4.16 | 5.89 | SREBP 1 |
| BE865030 | acetyl coenzyme A carboxylase (Acac) | 2.13 | 3.42 | SREBP 1 |
| NM_009127 | Stearoyl CoA desaturase 1 (Scd1) | 4.97 | 6.67 | SREBP 1 |
| NM_053115 | acyl coenzyme A oxidase | −1.78 | −2.45 | PPARα |
| NM_013495 | carnitine palmitoyltransferase 1, liver (Cpt1) | −1.81 | −2.51 | PPARα |
| NM_007382 | acetyl coenzyme A dehydrogenase, medium chain (Acadm) | −1.76 | −2.42 | PPARα |
| NM_177470 | acetyl coenzyme A acyltransferase 2 | −1.82 | −2.61 | unknown |
| NM_007824 | cytochrome P450, family 7, subfamily a, polypeptide 1 (Cyp7a1) | −1.82 | −2.84 | LXRα |
| BM937289 | 3 hydroxy 3 methylglutaryl coenzyme A reductase (Hmgcr) | 2.24 | 3.23 | SREBP 2 |
| NM_145942 | 3 hydroxy 3 methylglutaryl Coenzyme A synthase (Hmgcs) | 3.02 | 5.13 | SREBP 2 |
| NM_010700 | low-density lipoprotein receptor (Ldlr) | 1.86 | 2.76 | SREBP 2 |
| NM_010292 | glucokinase (Gck) | −1.97 | −2.91 | SREBP 1, LXRα |
| NM_008061 | glucose 6 phosphatase, catalytic (G6pc) | 2.19 | 2.67 | LXRα |
| NM_011044 | phosphoenolpyruvate carboxykinase 1, cytosolic (Pck1) | 2.08 | 3.79 | LXRα |
| NM_011480 | sterol regulatory element binding factor 1 (Srebf1) | 3.86 | 4.82 | LXRα |
| XM_127995 | sterol regulatory element binding factor 2 (Srebf2) | 2.58 | 3.31 | unknown |
| NM_013839 | nuclear receptor subfamily 1, group H, member 3 (Nr1h3) | −1.96 | −2.69 | LXRα |
| NM_009473 | nuclear receptor subfamily 1, group H, member 2 (Nr1h2) | no change | no change | unknown |
| NM_011144 | peroxisome proliferator activated receptor α (Ppara) | −1.90 | −2.91 | unknown |
| NM_008904 | peroxisome proliferative activated receptor, γ coactivator 1α (Ppargc1a) | 1.90 | 2.91 | LXRα |
Indicates the predominant regulator(s) of the gene, as determined in subsequent analyses
Figure 5.
The numbers of genes whose mRNA expression is upregulated (↑) or downregulated (↓) in insulin-resistant (IR) and diabetic (T2DM) hamsters compared with that in control animals. In the bottom ovals, the overlapping region contains the up- and downregulated genes in common between the insulin-resistant and diabetic groups. The nonoverlapping region denotes the number of unique genes up or downregulated in insulin-resistant and diabetic groups.
Altered gene expression of the key hepatic regulators LXRα, SREBPs, and PPARα and several of their target genes in insulin-resistant and diabetic hamsters.
Expression of SREBP genes (SREBP1, SREBP2) genes was upregulated in the insulin-resistant and diabetic hamsters compared with the control group (Table 3). mRNA levels of target genes of SREBP1c implicated in fatty acid synthesis, including fatty acid synthase (FAS), acetyl coenzyme A carboxylase (ACC), and stearoyl coenzyme A desaturase 1 (SCD1), and of target genes of SREBP2 involved in cholesterol metabolism, including 3-hydroxy-3-methylglutaryl coenzyme A (HMG CoA) synthase, HMG CoA reductase, and low-density lipoprotein receptor (LDLR), were increased in the insulin-resistant and diabetic groups. In addition, the expression of phosphoenolpyruvate carboxykinase (PEPCK), glucose-6-phosphatase (G6Pase) and peroxisome proliferator-activated receptor γ coactivator 1α (PGC1α), which are regulated by LXRα, was increased in insulin-resistant and diabetic hamsters. The expression of all of these genes was higher in the diabetic group than the insulin-resistant group (Table 3).
Compared with those of control animals, the mRNA levels of LXRα and PPARα were decreased markedly in insulin-resistant and diabetic hamsters, whereas the expression of LXRβ was unchanged in both groups. In addition, the expression of target genes of PPARα, including acyl coenzyme A oxidase (Acox), carnitine–palmitoyl transferase 1 (Cpt1), and medium-chain acyl coenzyme A dehydrogenase (Acadm) and of genes regulated by LXRα, including cholesterol 7α hydroxylase (CYP7A1) and glucokinase (Gck), was decreased in the insulin-resistant and diabetic groups compared with the control group. The magnitude of the decreased expression was greater for diabetic hamsters than insulin-resistant animals (Table 3).
Confirmation of the mRNA levels of hepatic LXRα, SREBPs, and PPARα and several of their target genes by real-time RT-PCR.
To confirm the altered gene expression of LXRα, SREBPs, and PPARα and several of their target genes in insulin-resistant and diabetic hamsters, we evaluated 21 key genes, including LXRs, SREBPs, and PPARα, by quantitative real-time RT-PCR analysis. mRNA levels of SREBPs (SREBP1a, SREBP1c, and SREBP2) were increased and those of LXRα and PPARα were decreased in insulin-resistant and diabetic hamsters, but those of LXRβ did not differ between the 2 groups (Figure 6 A). In addition, gene expression of PEPCK, G6Pase, FAS, ACC, SCD1, LDLR, HMG CoA synthase, HMG CoA reductase, and PGC1α was increased but that of CYP7A1, Gck, Acox, Cpt1, Acadm, and acetyl CoA acyltransferase 2 (Acaa2) was decreased in both insulin-resistant and diabetic groups compared with the control group (Figure 6 B, C). In addition, the expression of SREBPs, LXRα, and PPARα and some of their targets differed between insulin-resistant and diabetic hamsters.
Figure 6.
(A through C) Quantification of differentially expressed hepatic LXRs, SREBPs, and PPARα and various of their target genes in insulin-resistant (open bars) and diabetic (solid bars) hamsters. Gene expression (mean ± SD, n = 10) was quantified relative to that in control animals. *, P < 0.05 compared with value for insulin-resistant hamsters.
Discussion
High-fat diet increases hepatic lipid metabolite (diacylglycerol) content, thus activating a serine kinase cascade that includes protein kinase Cϵ; leading to decreased kinase activity of insulin receptor, IRS1 and 2, phosphoinositide 3 kinase, and protein kinase B; and thus causing hepatic insulin resistance.18 Although the molecular mechanism of FIHIR has been demonstrated, the hepatic gene alterations involved in FIHIR are unclear as yet. The results presented here show an abnormal pattern of expression of LXRα, SREBPs, and PPARα associated with FIHIR in insulin-resistant and diabetic states.
In the present study, although microarray results did not undergo statistical analysis, the results of gene ontology analysis of the micoarray data revealed some important metabolism-related genes associated with diabetes for confirmation with real-time RT-PCR. Not all results obtained by the micoarray hybridizations were confirmed by the real time RT-PCR. Only verified data were considered suitable for interpretation. Accordingly, we selected several metabolism-related genes associated with diabetes whose mRNA levels changed significantly or remained unchanged as references for real-time RT-PCR analysis to help reveal the gene products involved in the molecular mechanisms of FIHIR. Our results suggest that the combined abnormal expression of SREBPs, LXRα, and PPARα and their target genes may be involved in molecular mechanisms of FIHIR in obese insulin-resistant and type 2 diabetic hamsters by increasing hepatic lipid metabolite content (Figure 7).
Figure 7.
Metabolic effects of LXRα, SREBPs (1a, 1c, and 2), and PPARα. The figure shows a simplified model of potential regulatory mechanisms of LXRα, SREBPs (1a, 1c, and 2), and PPARα. Solid arrows indicate enhanced stimulatory effects, whereas dotted line arrows indicate weakened stimulatory or inhibitory effects. LXRα induces hepatic glucose utilization, lipogenesis, and bile acid biosynthesis and inhibits hepatic gluconeogenesis. SREBPs induce lipid biosynthesis and cholesterol uptake and biosynthesis. PPARα induces hepatic fatty acid oxidation. Possible molecular mechanisms underlying the induction of FIHIR in insulin-resistant and diabetic hamsters are shown.
The results indicate that the expression of hepatic LXRα, CYP7A1, and Gck decreased but that of hepatic PEPCK, G6Pase, and PGC1α increased in insulin-resistant and diabetic hamsters. These alterations imply that decreased LXRα expression is not enough to suppress hepatic expression of gluconeogenic genes, including PEPCK, G6Pase, and PGC1α, or to induce glucokinase expression and promote hepatic glucose utilization. Decreased expression of LXRα may contribute to the increased hepatic gluconeogenesis. At the same time, increased expression of hepatic PEPCK, G6Pase, and PGC1α contributes to insulin resistance, glucose intolerance, and the development of obesity-related diabetes.3,19,21,23,25 In addition, the reduced expression of LXRα and the overexpression of SREBP1c17 decrease the expression of CYP7A1, which in turn attenuates the biosynthesis of bile acid and contributes to hepatic accumulation of cholesterol and the development of FIHIR. Hepatic LXRβ, whose mRNA levels remained unchanged, seems to be uninvolved in FIHIR in insulin-resistant and diabetic hamsters. Therefore, the reduced expression of hepatic LXRα and the changes in the expression of its target genes contribute to abnormal hepatic glucose and lipid metabolism, FIHIR, and obesity-related diabetes in insulin-resistant and type 2 diabetic hamsters.
In the present study, mRNA expression of hepatic SREBPs (SREBP1a, SREBP1c, and SREBP2), FAS, ACC, SCD1, LDLR, HMG CoA synthase, and HMG CoA reductase was increased in insulin-resistant and diabetic hamsters. The overexpression of hepatic SREBPs primarily was due to feeding of high-fat diet,10 thus perhaps accounting for increased expression of SREBPs in the face of decreased expression of LXRα decreases. Activated SREBP1c drives the transcription of genes involved in de novo lipogenesis (such as ACC, SCD1, and FAS) and regulates the rate of triglyceride synthesis and hepatic triglyceride storage.29 Therefore, overexpression of SREBP1c may be involved in the pathogenesis of hepatic lipid accumulation that causes hepatic insulin resistance. Overexpression of SREBP1c also causes or exacerbates insulin resistance by directly suppressing IRS2 gene transcription to inhibit hepatic insulin signaling.4 Activated SREBP2 drives genes expression of LDLR, HMG CoA synthase, and HMG CoA reductase to enhance cholesterol uptake and biosynthesis.15 Overexpression of SREBP1a seems to be involved in both pathways.8 Therefore, overexpression of SREBPs and their target genes may lead to abnormal lipid metabolism and fat accumulation, which in turn contribute to FIHIR in insulin-resistant and type 2 diabetic hamsters.
Our results indicate that the expression of hepatic PPARα, Acox, Cpt1, Acadm, and Acaa2 was decreased in insulin-resistant and diabetic hamsters. The resulting decreased expression of hepatic PPARα apparently does not effectively drive the transcription of genes involved in the peroxisomal and mitochondrial oxidation of fatty acids (such as Acox, Cpt1, and Acadm). Some studies5,26,30 have indicated that the expression of PPARα and fatty acid oxidation-related genes (for example, Acox) decreases before lipid accumulation develops in type 2 diabetic models. At the same time, the decreased hepatic PPARα expression induces hepatic lipid accumulation and hepatic insulin resistance.22 Therefore, decreased expression of hepatic PPARα and PPARα-responsive genes leads to reduction of hepatic fatty acid β oxidation and contributes to hepatic fat accumulation, thus leading to or exacerbating hepatic insulin resistance.
We have demonstrated altered expression of hepatic SREBPs, LXRα, and PPARα and their target genes in response to high-fat diet and streptozotocin treatment. These changes in gene expression indicate that obesity induced by high-fat diet leads to abnormal hepatic glucose and lipid metabolism and hepatic lipid accumulation, thus contributing to occurrence and development of hepatic insulin resistance and type 2 diabetes. Our study suggests that relationships of aberrant glucose and lipid metabolism, hepatic fat accumulation, insulin resistance, and type 2 diabetes at the molecular level.
Acknowledgments
We thank Kerang Shou and Hong Gao for assistance with the animal work and technical help. We thank Hao Yang of the Beijing Proteome Research Center and Xiaobing Zhang of CapitalBio, Beijing, China. We also thank the study participants.
References
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