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Abstract This study was conducted to investigate the gene expression in fructosefed rat skeletal muscle by cDNA chip which could provide support to elucidate the molecular mechanisms underlying insulin resistance. The rats were divided into two groups， one of which was normal control and the other was fed with fructoserich diet. The mRNA was isolated and purified from the skeletal muscle of two groups. The mRNA from two kinds of tissue was reverse transcribed to cDNA with Cy3dUTP and Cy5dUTP separately to prepare hybridization probes. The mixed probes were hybridized to cDNA microarray. The microarray was scanned， analyzed and repeated for two times. Among the total 4 096 tested genes， 140 genes were differently expressed， 62 upregulated，78 downregulated， the expression of Ptprd and Gilz and multiple genes of oxidative metabolism is associated in insulin resistance. The differential expression of gene may be related to the pathogenesis of insulin resistance.
Key words cDNA microarray； Gene expression profile； Insulin resistance； Fructosefed rats
"X syndrome"， first described by Reaven[1]in 1988， was characterized by insulin resistance， abdominal obesity， hypertension and dyslipidemia， while the exact mechanism underlying phenomena is still not understood. Insulin resistance and additional features of the metabolic syndrome are under strong genetic and environmental influence[2-5]. Up to now， there have been many candidate genes related to this syndrome proposed in literatures[6-7]. Insulin resistance is the center part of the syndrome involving the interaction of multiple genes and multiple pathways， whose mechanisms cannot be faithfully revealed by conventional method at the level of gene expression. DNA microarrays， or gene chips， allow surveys of gene expression， （i.e.， mRNA expression） in a highly parallel and comprehensive manner. The pattern of gene expression produced， known as the expression profile， depicts the subset of gene transcripts expressed in a cell or tissue. At its most fundamental level， the expression profile can address qualitatively which genes are expressed in disease states[8-10]. Microarrays can be used to characterize the functions of novel genes[11-12]， identify genes in a biologic pathway， analyze genetic variation， and identify therapeutic drug targets[13-15]. Moreover， the expression profile can be used as a tissue or disease "fingerprint".
DNA microarray has made our way to analyze the gene expression profile. It enables us to monitor the expression level of thousands of genes simultaneously and provides us the "transcriptome" profiles of given tissues. Therefore， DNA microarray would be one of the most suitable approaches to address the gene expression alterations that account for insulin resistance. We used standard fructosefed rat model of IR to explore the molecular mechanisms underlying insulin resistance. Materials and Methods
Preparation of insulin resistance model from SpragueDawley rats
Insulin resistance has been reported in several animal models of hypertension， including the spontaneously hypertensive rat and the fructose hypertensive rat[16]. Fructosefed rats （FFR） show an acquired form of hypertension， in which the rise in blood pressure is not genetically determined but is dietinduced[17].
Twenty two SpragueDawley rats （male， 4-5 weeks old， weighing 130-140 g， SPF， purchased from Beijing Vital River Laboratory Animal Co.， Ltd.） were randomly divided into two groups， and in the control group rats were given a normal diet containing 60% carbohydrate，11% fat， and 29% protein. In the fructoserich rats were given a high fructose diet containing 60% fructose， 11% fat， and 29% protein[17]. The rats were maintained under standardized conditions of light and temperature， with free access to animal chow and water. During the period of feeding， blood pressure （BP）， the concentration of serum glucose （FBG） and insulin （INS） were determined. The HOMA model （18-19） was used to evaluate insulin resistance （IR）. At the end of the 8th week， the rats were sacrificed， and soleus muscle samples were removed and frozen in liquid nitrogen.
RNA Preparation and RNA isolation
Soleus muscle from five rats of each group was obtained. The information regarding specimens is displayed in Table 1. Tissue samples were ground into a fine powder in a 10cm ceramic mortar （RNasefree） and Total RNA was isolated using TRIzol Reagent （Moleular Research， Inc.， Carlsbad， Calif.， USA）， according to the protocol supplied by the manufacturer. The quality of the RNA samples was examined on a denaturing agarose gel. Equal amounts of total RNA from five animals in the same experiment group were pooled before mRNA purification. Messenger RNAs were purified using an OligotexdT mRNA Midi Kit （Qiagen， Carlsbad， Calif.， USA）.
Construction of microarrays and probe preparations
The construction of the microarrays used in this study was carried out following Browns method[20]. The 4 096 microarrays consisted of 4 096 including fulllength and partial complementary DNAs （cDNAs） representing novel， known， and control genes provided by United Gene Holdings. The known genes were selected from the NCBI， Unigene set and cloned into plasmid vector. The novel genes were obtained through systematic fulllength cloning efforts carried out at United Gene Holding. The control spots of nonhuman origin in both the 4 096 chip included the rice U2 RNA gene （eight spots）， the Hepatitis C Virus （HCV） coat protein gene （eight spots）， and spotting solution alone without DNA （32 spots）. The cDNA inserts were amplified by use of the polymerase chain reaction （PCR） using universal primers to plasmid vector sequences and then purified[21]. All PCR products were examined by agarose gel electrophoresis to ensure the quality and the identity of the amplified clones as expected. Then the amplified PCR products were dissolved in a buffer containing 3·SSC solution. The solution with amplified PCR products were spotted onto silylated slides （CEL Associates， Houston， Tex.， USA） using a BioRobotics MicroGrid MGI motion control robot （BioRobotics Ltd.， Cambridge.， UK） fitted with ChipMaker MicroSpotting Technology （TeleChem International， Sunnyvale， Calif.， USA）. Glass slides with spotted cDNA were then hydrated for 2 h in 70% humidity， dried for 0.5 h at room temperature， and UV crosslinked（65 mj/cm）. They were further processed at room temperature by soaking in 0.2% sodium dodecyl sulfate （SDS） for 10 min， distilled H2O for 10 min， and 0.2% sodium borohydride （NaBH4） for 10 min. The slides were dried again and ready for use. The fuorescent cDNA probes were prepared through reverse transcription of the isolated mRNAs and then purified according to the methods of Schena et al.[22-23]. The RNA samples from the control group were labeled with Cy3dUTP and those from FFR with Cy5dUTP. The two color probes were then mixed， precipitated with ethanol and dissolved in 20 μl of hybridization solution[5·SSC （0.75 M NaCl and 0.075 M sodium citrate）， 0.4% SDS， 50% ormamide， and 5·Denhardts Solution （0.1% Ficoll， 0.1% polyvinylpyrrolidone， and 0.1% BSA）]. Hybridization and washing
Microarrays were prehybridized with hybridization solution containing 0.5 mg/ml denatured salmon sperm DNA at 42 ℃ for 6 h. Fluorescent probe mixtures were denatured at 95 ℃ for 5 min， and the denatured probe mixtures were applied onto the prehybridized chip under a cover glass. Chips were hybridized at 42 ℃ for 15-17 h. The hybridized chips were then washed at 60 ℃ for 10 min each in solutions of 2·SSC and 0.2% SDS， 0.1·SSC and 0.2% SDS， and 0.1·SSC， then dried at room temperature.
Detection and Analysis
The chips were scanned with a Genepix Personal 4100A （Axon Instruments， Inc.， Calif.， USA） at two wavelengths to detect emission from both Cy3 and Cy5. The acquired images were analyzed using Genepix pro 4.1 software （Axon Instruments， Inc.， Calif.， U S A）. The intensities of each spot at the two wavelengths represent the quantity of Cy3dUTP and Cy5dUTP， respectively， hybridized to each spot. Ratios of Cy5 to Cy3 were computed for each location on each microarray. Overall intensities were normalized with a correction coefficient obtained using the ratios of 40 housekeeping genes （a list of these gene is available as a supplement at http：// www.biodoor.com/）. Genes were identified as differentially expressed if the absolute value of the natural logarithm of the ratios was >0.69. To minimize artifacts arising from low expression values， only genes with raw intensity values for both Cy3 and Cy5 of >800 counts were chosen for differential analysis.
Bo WANG et al. cDNA Microarray Analysis of Insulin Resistanceassociated Genes in Fructosefed Rats
Discussion
In the present study， we examined changes in gene expression in the skeletal muscle tissues of FFR and control rats with a microarray analysis and identified 140 differentially expressed genes， 62 upregulated genes （including11 novel genes）， 78 downregulated genes （including11 novel genes）. In accordance with studies showing， the genes are related to energy metabolism， such as isocitrate dehydrogenase1 （Idh1）， fumarate hydratase （Fh） and insulin signal transduction， such as protein tyrosine phosphatase （Ptprd）， glucocorticoidinduced leucine zipper （Gilz）， fetuin beta （Fetub）. Isocitrate dehydrogenase is crucial for energy and redox status[24]. Fetuinbeta inhibits insulin receptor tyrosine kinase activity， protease inhibitory activities[25].
Insulin plays a pivotal role in the regulation of energy homeostasis including the storage， mobilization， and utilization of free fatty acids （FFAs） and glucose. Loss of insulin responsiveness in insulintarget tissues evokes major metabolic consequences such as hyperinsulinemia， impaired glucose tolerance， and dyslipidemia. The insulin receptor is part of a transmembrane tyrosine kinasemediating intracellular signaling process that leads to the biological actions of insulin. Tyrosine phosphorylation of the cytosolic proteins insulin receptor substrate （IRS）1 and IRS2 produces protein scaffolding for the assembly of other effector proteins containing SH2 domains， thereby generating multisubunit signaling complexes[26]. PTPases is the target enzyme of INSR. PTPases comprise an extensive family of homologous enzymes that regulate various events in cellular signal transduction and metabolism[27]. The enzymes in the PTPase superfamily have in common a conserved domain that contains a reduced cysteine moiety that is required to catalyze phosphotyrosine hydrolysis by the formation of a cysteinylphosphate intermediate[28]. PTPases have been divided into two broad categories： Intracellular （nonreceptortype）， which have a single PTPase domain and additional functional protein segments （e.g. PTP1B）； and transmembrane （receptortype）， which have a general structure like a membrane receptor with an extracellular domain， a single transmembrane segment and one or two tandemly conserved PTPase catalytic domains （e.g. LAR）. To date， PTP1B and LAR have been implicated in potentially having portent roles in the regulation of the insulin action cascade[29-30]. Interest in this homolog arose from identification of their expression in insulinsensitive tissues， their invitro activity toward proteins in the insulin action pathway， and more recently， studies in transgenic and knockout mouse models that have substantiated a role for these two enzymes in the negative regulation of metabolic signaling by insulin. PTP1B and PTPaseLAR that function as negative regulators of the insulin signaling cascade have been identified[31-32]and as novel targets for type 2 diabetes and obesity[33-34]. We found the gene of PTPases was upregulated in the FFR， suggesting its association with insulin resistance. GILZ （glucocorticoidinduced leucine zipper）， one of the GCHinduced genes， codes for a leucine zipper protein and was first isolated as a dexamethasone （DEX）responsive gene from a thymus subtraction library[35]. GILZ overexpression inhibits ERK1/2， MEK， and Raf1 phosphorylation but not JNK phosphorylation. GILZ interferes with Raf activation by a proteintoprotein interaction mechanism. It has been shown that the treatment mast cells with DEX blocked the phosphorylation of RafMEK， and ERK2 without affecting Ras activation[36]. Since proteintoprotein interaction may have important consequences with regards to protein phosphorylation， activation， and trafficking， Ayroldi et al.[37]speculated that GILZ could bind proteins the cascade of MAPKs and inhibit their activation. In insulin resistance， the glucocorticoidinduced leucine zipper was upregulated， perhaps it is a gene associated insulin resistance.
Our data demonstrate that expression of many genes involves in the process of oxidative metabolism is related in insulin resistance， we recognize that microarray approaches are limited， however they are correlation would be verified by other methods. In summary， we demonstrate that expression of Ptprd and Gilz and multiple genes of oxidative metabolism are associated in insulin resistance.
References
[1]
REAVEN GM. Banting Lecture 1988： Role of insulin resistance in human disease[J]. Diabetes， 1988， 37： 1595-1607.
[2]GROOP L， FORSBLOM C， LEHTOVIRTA M， et al. Metabolic consequences of a family history of NIDDM （the Botnia study）： evidence for sexspecific parental effects[J]. Diabetes， 1996， 45： 1585-1593.
[3]BECKNIELSEN H， GROOP LC. Metabolic and genetic characterization of prediabetic states： sequence of events leading to noninsulindependent diabetes mellitus[J]. J Clin Invest， 1994， 94： 1714-1721.
[4]GROOP L， ORHOMELANDER M. The dysmetabolic syndrome. J Intern Med， 2001， 250： 105-120.
[5]POULSEN P， VAAG A， KYVIK K， et al. Genetic versus environmental aetiology of the metabolic syndrome among male and female twins[J]. Diabetologia， 2001； 44：537-543.
[6]RUAN H， POWNALL HJ， LODISH HF. Troglitazone antagonizes tumor necrosis factoralphainduced reprogramming of adipocyte gene expression by inhibiting the transcriptional regulatory functions of NFkappaB[J]. J Biol Chem， 2003， 278（30）： 28181-28192.
[7]IEMITSU M， MIYAUCHI T， MAEDA S， et al. Cardiac hypertrophy by hypertension and exercise training exhibits different gene expression of enzymes in energy metabolism[J]. Hypertens Res， 2003， 26（10）： 829-837. [8]GOLUB TR， SLONIM DK， TAMAYO P， et al. Molecular classification of cancer： class discovery and class prediction by gene expression monitoring[J]. Science， 1999， 286： 531-537.
[9]KIM HL. Comparison of oligonucleotidemicroarray and serial analysis of gene expression （SAGE） in transcript profiling analysis of megakaryocytes derived from CD34+ cells[J]. Exp Mol Med， 2003， 35： 460-466.
[10]CHUNG HW， PARK SW， CHUNG JB， et al. Differences in genetic expression profiles between youngage and oldage gastric adenocarcinoma using cDNA microarray for endocrine disruptor study[J]. Oncol Rep， 2004， 12： 33-39.
[11]AITMAN TJ， GLAZIER AM， WALLACE CA， et al. Identification of Cd36 （Fat） as an insulinresistance gene causing effective fatty acid and glucose metabolism in hypertensive rats[J]. Nature Genet， 1999， 21： 76-83.
[12]AITMAN TJ， GOTODA T， EVANS AL， et al. Quantitative trait loci for cellular defects in glucose and fatty acid metabolism in hypertensive rats[J]. Nature Genet， 1997， 16： 197-201.
[13]NAPOLI C， LERMAN LO， SICA V， et al. Microarray analysis： a novel research tool for cardiovascular scientists and physicians[J]. Heart， 2003， 89： 597-604.
[14]SCHWAENEN C， WESSENDORF S， KESTLER HA， et al. DNA microarray analysis in malignant lymphomas[J]. Ann Hematol， 2003， 82： 323-332.
[15]GRANT GM， FORTNEY A， GORRETA F， et al. Microarrays in cancer research[J]. Anticancer Res， 2004， 24： 441-448.
[16]REAVEN GM. Insulin resistance， hyperinsulinemia， hypertriglycemia and hypertension[J]. Diabetes Care， 1991， 14： 195-202.
[17]HWANG I， HO H， HOFFMAN B， et al. Fructose induced insulin resistance and hypertension in rats[J]. Hypertension， 1987， 10： 512-516.
[18]BONORA E， KIECHL S， WILLEIT J， et al.Populationbased incidence rates and risk factors for type 2 diabetes in white individuals： the bruneck study[J]. Diabetes，2004， 53： 1782-1789.
[19]MURAKAMI K， SHIGEMATSU Y， HAMADA M， et al. Insulin resistance in patients with hypertrophic cardiomyopathy[J]. Circ J， 2004， 68： 650-655.
[20]BROWN P .In： http：//cmgm.stanford.edu/pbrown/protocols/index.html .
[21]SAMBROOK J， FRITSCH EF， MANIATIS T. Molecular cloning： a laboratory manua （2nd）[M]. Cold Spring Harbor Laboratory Press， New York.
[22]SCHENA M， SHALON D， DAVIS RW， et al. Quantitative monitoring of gene expression patterns with a complementary DNA microarray[J]. Science， 1995， 270： 467-470.
[23]SCHENA M， SHALON D， HELLER R， et al. Parallel human genome analysis： microarraybased expression monitoring of 1000 genes[J]. PNAS， 1996， 93：10614-10619. [24]BENDERDOUR M， CHARRON G， DEBLOIS D， et al. Cardiac mitochondrial NADP+isocitrate dehydrogenase is inactivated through 4hydroxynonenal adduct formation： an event that precedes hypertrophy development[J]. J Biol Chem， 2003， 278： 45154-45159.
[25]http：//rgd.mcw.edu/tools/genes/genes.view.
[26]WHITE MF. The insulin signalling system and the IRS proteins[J]. Diabetologia， 1997， 40： S2-S17.
[27]TONKS NK， NEEL BG. Combinatorial control of the specificity of protein tyrosine phosphatases[J]. Curr Opin Cell Biol ， 200；113：182-195.
[28]ZHANG Z . Protein tyrosine phosphatases： prospects for therapeutics[J]. Curr Opin Chem Biol， 2001， 5： 416-423.
[29]GOLDSTEIN BJ， BITTNERKOWALCZYK A， WHITE MF， et al. Tyrosine dephosphorylation and deactivation of insulin receptor substrate1 by proteintyrosine phosphatase 1B. Possible facilitation by the formation of a ternary complex with the Grb2 adaptor protein[J]. J Biol Chem， 2000， 275： 4283-4289.
[30]GOLDSTEIN BJ. Proteintyrosine phosphatases： emerging targets for therapeutic intervention in type 2 diabetes and related states of insulin resistance[J]. J Clin Endocrinol Metab， 2002， 87： 2474-2480.
[31]HIRATA AE， ALVAREZROJAS F， CARVALHEIRA JB， et al. Modulation of IR/PTP1B interaction and downstream signaling in insulin sensitive tissues of MSGrats[J]. Life Sci， 2003， 73： 1369-1381.
[32]LIU G. Protein tyrosine phosphatase 1B inhibition： opportunities and challenges[J]. Curr Med Chem， 2003， 10： 1407-1421.
[33]MOONEY RA， LEVEA CM. The leukocyte common antigenrelated protein LAR： candidate PTP for inhibitory targeting[J]. Curr Top Med Chem， 2003， 3： 809-819.
[34]RAMACHANDRAN C， KENNEDY BP. Protein tyrosine phosphatase 1B： a novel target for type 2 diabetes and obesity[J]. Curr Top Med Chem， 2003， 3： 749-757.
[35]DADAMIO F， ZOLLO O， MORACA R， et al. A new dexamethasoneinduced gene of the leucine zipper family protects T lymphocytes from TCR/CD3activated cell death[J]. Immunity， 1997， 7： 803-812.
[36]RIDER LG， HIRASAWA N， SANTINI F， et al. Activation of the itogenactivated protein kinase cascade is suppressed by low concentrations of dexamethasone in mast cells[J]. J. Immunol， 1996， 157： 2374-2380.
[37]AYROLDI E， ZOLLO O， MACCHIARULO A， et al. Glucocorticoidinduced leucine zipper inhibits the Rafextracellular signalregulated kinase pathway by binding to Raf1[J]. Mol Cell Biol， 2002， 22： 7929-7941.
Editor： Yingzhi GUANG Proofreader： Xinxiu ZHU
Key words cDNA microarray； Gene expression profile； Insulin resistance； Fructosefed rats
"X syndrome"， first described by Reaven[1]in 1988， was characterized by insulin resistance， abdominal obesity， hypertension and dyslipidemia， while the exact mechanism underlying phenomena is still not understood. Insulin resistance and additional features of the metabolic syndrome are under strong genetic and environmental influence[2-5]. Up to now， there have been many candidate genes related to this syndrome proposed in literatures[6-7]. Insulin resistance is the center part of the syndrome involving the interaction of multiple genes and multiple pathways， whose mechanisms cannot be faithfully revealed by conventional method at the level of gene expression. DNA microarrays， or gene chips， allow surveys of gene expression， （i.e.， mRNA expression） in a highly parallel and comprehensive manner. The pattern of gene expression produced， known as the expression profile， depicts the subset of gene transcripts expressed in a cell or tissue. At its most fundamental level， the expression profile can address qualitatively which genes are expressed in disease states[8-10]. Microarrays can be used to characterize the functions of novel genes[11-12]， identify genes in a biologic pathway， analyze genetic variation， and identify therapeutic drug targets[13-15]. Moreover， the expression profile can be used as a tissue or disease "fingerprint".
DNA microarray has made our way to analyze the gene expression profile. It enables us to monitor the expression level of thousands of genes simultaneously and provides us the "transcriptome" profiles of given tissues. Therefore， DNA microarray would be one of the most suitable approaches to address the gene expression alterations that account for insulin resistance. We used standard fructosefed rat model of IR to explore the molecular mechanisms underlying insulin resistance. Materials and Methods
Preparation of insulin resistance model from SpragueDawley rats
Insulin resistance has been reported in several animal models of hypertension， including the spontaneously hypertensive rat and the fructose hypertensive rat[16]. Fructosefed rats （FFR） show an acquired form of hypertension， in which the rise in blood pressure is not genetically determined but is dietinduced[17].
Twenty two SpragueDawley rats （male， 4-5 weeks old， weighing 130-140 g， SPF， purchased from Beijing Vital River Laboratory Animal Co.， Ltd.） were randomly divided into two groups， and in the control group rats were given a normal diet containing 60% carbohydrate，11% fat， and 29% protein. In the fructoserich rats were given a high fructose diet containing 60% fructose， 11% fat， and 29% protein[17]. The rats were maintained under standardized conditions of light and temperature， with free access to animal chow and water. During the period of feeding， blood pressure （BP）， the concentration of serum glucose （FBG） and insulin （INS） were determined. The HOMA model （18-19） was used to evaluate insulin resistance （IR）. At the end of the 8th week， the rats were sacrificed， and soleus muscle samples were removed and frozen in liquid nitrogen.
RNA Preparation and RNA isolation
Soleus muscle from five rats of each group was obtained. The information regarding specimens is displayed in Table 1. Tissue samples were ground into a fine powder in a 10cm ceramic mortar （RNasefree） and Total RNA was isolated using TRIzol Reagent （Moleular Research， Inc.， Carlsbad， Calif.， USA）， according to the protocol supplied by the manufacturer. The quality of the RNA samples was examined on a denaturing agarose gel. Equal amounts of total RNA from five animals in the same experiment group were pooled before mRNA purification. Messenger RNAs were purified using an OligotexdT mRNA Midi Kit （Qiagen， Carlsbad， Calif.， USA）.
Construction of microarrays and probe preparations
The construction of the microarrays used in this study was carried out following Browns method[20]. The 4 096 microarrays consisted of 4 096 including fulllength and partial complementary DNAs （cDNAs） representing novel， known， and control genes provided by United Gene Holdings. The known genes were selected from the NCBI， Unigene set and cloned into plasmid vector. The novel genes were obtained through systematic fulllength cloning efforts carried out at United Gene Holding. The control spots of nonhuman origin in both the 4 096 chip included the rice U2 RNA gene （eight spots）， the Hepatitis C Virus （HCV） coat protein gene （eight spots）， and spotting solution alone without DNA （32 spots）. The cDNA inserts were amplified by use of the polymerase chain reaction （PCR） using universal primers to plasmid vector sequences and then purified[21]. All PCR products were examined by agarose gel electrophoresis to ensure the quality and the identity of the amplified clones as expected. Then the amplified PCR products were dissolved in a buffer containing 3·SSC solution. The solution with amplified PCR products were spotted onto silylated slides （CEL Associates， Houston， Tex.， USA） using a BioRobotics MicroGrid MGI motion control robot （BioRobotics Ltd.， Cambridge.， UK） fitted with ChipMaker MicroSpotting Technology （TeleChem International， Sunnyvale， Calif.， USA）. Glass slides with spotted cDNA were then hydrated for 2 h in 70% humidity， dried for 0.5 h at room temperature， and UV crosslinked（65 mj/cm）. They were further processed at room temperature by soaking in 0.2% sodium dodecyl sulfate （SDS） for 10 min， distilled H2O for 10 min， and 0.2% sodium borohydride （NaBH4） for 10 min. The slides were dried again and ready for use. The fuorescent cDNA probes were prepared through reverse transcription of the isolated mRNAs and then purified according to the methods of Schena et al.[22-23]. The RNA samples from the control group were labeled with Cy3dUTP and those from FFR with Cy5dUTP. The two color probes were then mixed， precipitated with ethanol and dissolved in 20 μl of hybridization solution[5·SSC （0.75 M NaCl and 0.075 M sodium citrate）， 0.4% SDS， 50% ormamide， and 5·Denhardts Solution （0.1% Ficoll， 0.1% polyvinylpyrrolidone， and 0.1% BSA）]. Hybridization and washing
Microarrays were prehybridized with hybridization solution containing 0.5 mg/ml denatured salmon sperm DNA at 42 ℃ for 6 h. Fluorescent probe mixtures were denatured at 95 ℃ for 5 min， and the denatured probe mixtures were applied onto the prehybridized chip under a cover glass. Chips were hybridized at 42 ℃ for 15-17 h. The hybridized chips were then washed at 60 ℃ for 10 min each in solutions of 2·SSC and 0.2% SDS， 0.1·SSC and 0.2% SDS， and 0.1·SSC， then dried at room temperature.
Detection and Analysis
The chips were scanned with a Genepix Personal 4100A （Axon Instruments， Inc.， Calif.， USA） at two wavelengths to detect emission from both Cy3 and Cy5. The acquired images were analyzed using Genepix pro 4.1 software （Axon Instruments， Inc.， Calif.， U S A）. The intensities of each spot at the two wavelengths represent the quantity of Cy3dUTP and Cy5dUTP， respectively， hybridized to each spot. Ratios of Cy5 to Cy3 were computed for each location on each microarray. Overall intensities were normalized with a correction coefficient obtained using the ratios of 40 housekeeping genes （a list of these gene is available as a supplement at http：// www.biodoor.com/）. Genes were identified as differentially expressed if the absolute value of the natural logarithm of the ratios was >0.69. To minimize artifacts arising from low expression values， only genes with raw intensity values for both Cy3 and Cy5 of >800 counts were chosen for differential analysis.
Bo WANG et al. cDNA Microarray Analysis of Insulin Resistanceassociated Genes in Fructosefed Rats
Discussion
In the present study， we examined changes in gene expression in the skeletal muscle tissues of FFR and control rats with a microarray analysis and identified 140 differentially expressed genes， 62 upregulated genes （including11 novel genes）， 78 downregulated genes （including11 novel genes）. In accordance with studies showing， the genes are related to energy metabolism， such as isocitrate dehydrogenase1 （Idh1）， fumarate hydratase （Fh） and insulin signal transduction， such as protein tyrosine phosphatase （Ptprd）， glucocorticoidinduced leucine zipper （Gilz）， fetuin beta （Fetub）. Isocitrate dehydrogenase is crucial for energy and redox status[24]. Fetuinbeta inhibits insulin receptor tyrosine kinase activity， protease inhibitory activities[25].
Insulin plays a pivotal role in the regulation of energy homeostasis including the storage， mobilization， and utilization of free fatty acids （FFAs） and glucose. Loss of insulin responsiveness in insulintarget tissues evokes major metabolic consequences such as hyperinsulinemia， impaired glucose tolerance， and dyslipidemia. The insulin receptor is part of a transmembrane tyrosine kinasemediating intracellular signaling process that leads to the biological actions of insulin. Tyrosine phosphorylation of the cytosolic proteins insulin receptor substrate （IRS）1 and IRS2 produces protein scaffolding for the assembly of other effector proteins containing SH2 domains， thereby generating multisubunit signaling complexes[26]. PTPases is the target enzyme of INSR. PTPases comprise an extensive family of homologous enzymes that regulate various events in cellular signal transduction and metabolism[27]. The enzymes in the PTPase superfamily have in common a conserved domain that contains a reduced cysteine moiety that is required to catalyze phosphotyrosine hydrolysis by the formation of a cysteinylphosphate intermediate[28]. PTPases have been divided into two broad categories： Intracellular （nonreceptortype）， which have a single PTPase domain and additional functional protein segments （e.g. PTP1B）； and transmembrane （receptortype）， which have a general structure like a membrane receptor with an extracellular domain， a single transmembrane segment and one or two tandemly conserved PTPase catalytic domains （e.g. LAR）. To date， PTP1B and LAR have been implicated in potentially having portent roles in the regulation of the insulin action cascade[29-30]. Interest in this homolog arose from identification of their expression in insulinsensitive tissues， their invitro activity toward proteins in the insulin action pathway， and more recently， studies in transgenic and knockout mouse models that have substantiated a role for these two enzymes in the negative regulation of metabolic signaling by insulin. PTP1B and PTPaseLAR that function as negative regulators of the insulin signaling cascade have been identified[31-32]and as novel targets for type 2 diabetes and obesity[33-34]. We found the gene of PTPases was upregulated in the FFR， suggesting its association with insulin resistance. GILZ （glucocorticoidinduced leucine zipper）， one of the GCHinduced genes， codes for a leucine zipper protein and was first isolated as a dexamethasone （DEX）responsive gene from a thymus subtraction library[35]. GILZ overexpression inhibits ERK1/2， MEK， and Raf1 phosphorylation but not JNK phosphorylation. GILZ interferes with Raf activation by a proteintoprotein interaction mechanism. It has been shown that the treatment mast cells with DEX blocked the phosphorylation of RafMEK， and ERK2 without affecting Ras activation[36]. Since proteintoprotein interaction may have important consequences with regards to protein phosphorylation， activation， and trafficking， Ayroldi et al.[37]speculated that GILZ could bind proteins the cascade of MAPKs and inhibit their activation. In insulin resistance， the glucocorticoidinduced leucine zipper was upregulated， perhaps it is a gene associated insulin resistance.
Our data demonstrate that expression of many genes involves in the process of oxidative metabolism is related in insulin resistance， we recognize that microarray approaches are limited， however they are correlation would be verified by other methods. In summary， we demonstrate that expression of Ptprd and Gilz and multiple genes of oxidative metabolism are associated in insulin resistance.
References
[1]
REAVEN GM. Banting Lecture 1988： Role of insulin resistance in human disease[J]. Diabetes， 1988， 37： 1595-1607.
[2]GROOP L， FORSBLOM C， LEHTOVIRTA M， et al. Metabolic consequences of a family history of NIDDM （the Botnia study）： evidence for sexspecific parental effects[J]. Diabetes， 1996， 45： 1585-1593.
[3]BECKNIELSEN H， GROOP LC. Metabolic and genetic characterization of prediabetic states： sequence of events leading to noninsulindependent diabetes mellitus[J]. J Clin Invest， 1994， 94： 1714-1721.
[4]GROOP L， ORHOMELANDER M. The dysmetabolic syndrome. J Intern Med， 2001， 250： 105-120.
[5]POULSEN P， VAAG A， KYVIK K， et al. Genetic versus environmental aetiology of the metabolic syndrome among male and female twins[J]. Diabetologia， 2001； 44：537-543.
[6]RUAN H， POWNALL HJ， LODISH HF. Troglitazone antagonizes tumor necrosis factoralphainduced reprogramming of adipocyte gene expression by inhibiting the transcriptional regulatory functions of NFkappaB[J]. J Biol Chem， 2003， 278（30）： 28181-28192.
[7]IEMITSU M， MIYAUCHI T， MAEDA S， et al. Cardiac hypertrophy by hypertension and exercise training exhibits different gene expression of enzymes in energy metabolism[J]. Hypertens Res， 2003， 26（10）： 829-837. [8]GOLUB TR， SLONIM DK， TAMAYO P， et al. Molecular classification of cancer： class discovery and class prediction by gene expression monitoring[J]. Science， 1999， 286： 531-537.
[9]KIM HL. Comparison of oligonucleotidemicroarray and serial analysis of gene expression （SAGE） in transcript profiling analysis of megakaryocytes derived from CD34+ cells[J]. Exp Mol Med， 2003， 35： 460-466.
[10]CHUNG HW， PARK SW， CHUNG JB， et al. Differences in genetic expression profiles between youngage and oldage gastric adenocarcinoma using cDNA microarray for endocrine disruptor study[J]. Oncol Rep， 2004， 12： 33-39.
[11]AITMAN TJ， GLAZIER AM， WALLACE CA， et al. Identification of Cd36 （Fat） as an insulinresistance gene causing effective fatty acid and glucose metabolism in hypertensive rats[J]. Nature Genet， 1999， 21： 76-83.
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