Four-day-old rat pups that are raised artificially on a high-carbohydrate (HC) milk formula immediately develop hyperinsulinemia, which persists into adulthood without any further nutritional stimulus. cDNA array analysis was used to identify large-scale changes in gene expression patterns in islets from 12- and 100-day-old HC rats in response to the HC dietary modification during the suckling period. It was observed that the expression of several genes that belong to clusters involved in β-cell development and/or β-cell function was significantly upregulated in islets from 12- and 100-day-old HC rats. It is inferred that in addition to predicted changes in gene expression, for example preproinsulin gene, global changes in gene expression contribute to the hyperinsulinemic state in the HC rat.

Studies from animal models and human epidemiological data suggest that nutritional interventions (e.g., malnutrition, protein deprivation) during fetal and early postnatal periods permanently affect metabolic capacities and consequently influence the susceptibility to several adult-onset pathological conditions, such as type 2 diabetes, obesity, and hypertension (1). Feeding a high-carbohydrate (HC) milk formula to rat pups by gastrostomy during the suckling period results in the immediate onset of hyperinsulinemia, which persists into adulthood without any further nutritional stimulus (2). Both the HC nature of the milk formula and the overlap of the nutritional intervention with the ontogenic period of the pancreas in the rat suggest that several adaptive responses should occur in the pancreas of the HC rats in response to this nutritional stimulus. Earlier reports from this laboratory showed several adaptations at the biochemical and cellular levels (such as alterations in the insulin secretory pattern and the number and size of islets) in the endocrine pancreas of 12-day-old HC rats (3,4). These adaptations support the immediate onset of hyperinsulinemia in the HC rats. In addition, we recently observed an upregulation of preproinsulin gene transcription in islets from 12-day-old HC rats compared with islets from 12-day-old mother-fed (MF) rats (4a). Because of the persistent nature of the hyperinsulinemic state both during the period of the nutritional intervention and later after its withdrawal, it is to be anticipated that significant molecular adaptations in HC islets may be primarily responsible for the hyperinsulinemia in the HC rats. In the present study, therefore, we hypothesized that in addition to the predicted changes at the molecular level (for example, increased gene transcription of preproinsulin and related transcription factors that regulate insulin promoter activity) global changes in gene transcription in islets occur to support the immediate onset of hyperinsulinemia in 12-day-old HC rats. It was further hypothesized that several of the early changes at the molecular level will be programmed into adulthood.

Gene expression patterns are crucial for maintaining and altering phenotypes of cells. Parallel analysis of the transcriptional activity of a large number of genes could reflect patterns that are necessary to cause and support these adaptive responses. Recent technological advances in methods for large-scale study of gene expression include open and focused closed systems that make possible the identification of a large number of genes that are differentially expressed under various conditions (5). Gene expression arrays allow the monitoring of a large number of genes simultaneously. A rat cDNA array was used in the present study to identify differential gene expression patterns in islets isolated from 12- and 100-day-old HC rats and to compare them with the gene expression patterns in islets from age-matched MF rats to evaluate these hypotheses.

Animal protocol.

The Institutional Animal Care and Use Committee approved all animal protocols. Timed pregnant Sprague-Dawley rats were obtained from Zivic Miller Laboratories (Zellenople, PA). The newborn pups were pooled and assigned to each mother (12 pups/dam) until postnatal day 4. On postnatal day 4, pups were randomly assigned to control MF and experimental (HC) groups. In the MF group, pups were reared by their nursing mothers, whereas pups in the experimental group were reared artificially on an HC formula (56% of the calories derived from carbohydrate compared with 8% in rat milk), as detailed elsewhere (6). Intragastric cannulas were placed under light anesthesia, and the pups were reared artificially on the HC milk formula in isolation from their dams, as described previously (6). On postnatal day 24, control and experimental pups were weaned onto a laboratory stock diet. Food and water were provided ad libitum. On days 12 and 100, the rats were killed by decapitation. Pancreatic islets were isolated from 12- and 100-day-old rats by a modification of the method described previously (7). For 12-day-old animals, islets for each experiment were obtained by pooling islets isolated from six pups with the same dietary treatment. These pups included both sexes and were derived randomly from several different litters. For experiments on 100-day-old animals, only male rats were used for isolation of islets, and for each experiment islets were pooled from two rats.

Screening of cDNA arrays.

Total RNA was isolated from islets from 12- and 100-day-old HC and age-matched MF rats using the TRIzol reagent-phenol-chloroform procedure (Gibco BRL, Rockville, MD). cDNA was prepared using 4 μg of total RNA in a 10-μl volume containing 50 mmol/l Tris-HCl (pH 8.3), 75 mmol/l KCl, 3 mmol/l MgCl2, 0.5 mmol/l dNTP mixture except dATP, 5 mmol/l dithiothreitol, gene-specific CDS primer mix (Clontech Labs, Palo Alto, CA), and Maloney murine leukemia virus reverse transcriptase (Clontech Labs) in the presence of 35 μCi [α-32P] dATP (3000 Ci/mmol; Amersham, Piscataway, NJ). After incubation at 50°C for 25 min, the reaction was stopped by addition of 0.01 mol/l EDTA (pH 8.0). Radiolabeled cDNA was purified using Chroma Spin-200 DEPC-H2O columns (Clontech Labs).

The Atlas rat 1.2 arrays were obtained from Clontech Labs. Two arrays, one each for MF and HC samples, were treated simultaneously under identical conditions according to manufacturer’s instructions to obtain gene expression patterns. The membranes were hybridized (5–6 × 106 cpm/membrane) with the cDNA probe (equivalent to 4 μg of total RNA), washed, and exposed to a phosphorimager screen. The image was analyzed using AtlasImage 1.0 software and normalized using the internal control (ribosomal protein S29 40S subunit gene). The result for each gene is expressed as fold change for HC rats compared with age-matched MF controls taken as 1.

Quantification of mRNA levels.

For quantification of mRNA levels of specific genes, a semiquantitative reverse transcriptase (RT)–polymerase chain reaction (PCR) protocol was used. Total RNA was isolated from islets obtained from 12- and 100-day-old HC and age-matched MF control rats using the TRIzol reagent-phenol-chloroform procedure. cDNA was prepared using 6 μg of total islet RNA and 20 pmol of random hexamers in a 30-μl solution containing 50 mmol/l Tris-HCl (pH 8.4), 75 mmol/l KCl, 4 mmol/l MgCl2, 10 mmol/l dithiothreitol, 0.125 mmol/l of each dNTP, and 200 units of Moloney murine leukemia virus RT (Gibco BRL). After incubation for 1 h at 42°C, the reaction mixture was heated to 70°C for 15 min to inactivate the RT. The cDNA was stored at −20°C.

The levels of specific mRNAs were determined using a semiquantitative PCR-based assay as described previously (8,9). A semiquantitative RT-PCR assay (8,9), in which a same amount of competitor template was added to each reaction, was used to compare the levels of specific mRNAs in islets from HC and MF rats. This internal standard was amplified using the same primers as the experimental cDNA target and was designed to generate a PCR product that was distinguished easily from the cDNA target because of its difference in size. All competitor DNAs for measuring the mRNAs for preproinsulin, GLUT 2, insulin receptor substrate (IRS)-1, IRS-2, islet factor-1 (Isl-1), regenerating protein III (REG III), and acetyl CoA carboxylase (ACC) were prepared by introducing a small internal deletion into the cloned cDNA using a PCR-based mutagenesis procedure (10). Pancreatic duodenal transcription factor-1 (PDX-1; also known as STF-1) competitor DNA was prepared by digesting the cloned PDX-1 cDNA with ApaI and Mlu 1, filling it in with Klenow-DNA-polymerase, and religating it. All competitor DNAs were cloned into pGEM-3Z vector (Promega, Madison, WI). PCR reactions were carried out in a 50-μl volume containing cDNA, competitor DNA, dNTPs, 10 pmol of a pair of oligonucleotide primers (Table 1), 50 mmol/l KCl, 10 mmol/l Tris-HCl (pH 8.4), 1.5 mmol/l MgCl2, and 1 unit of Taq DNA polymerase. The PCR products were separated by electrophoresis in a 2% agarose gel, analyzed by Bio-Rad Gel Doc 1000 and Molecular Analyst Software for quantitative analysis, and normalized using competitor controls. The results are expressed as the fold change in HC animals compared with age-matched MF controls.

The Atlas rat 1.2 array used in this study has ∼1,200 genes inclusive of housekeeping genes and negative controls: λ DNA, puc 18 DNA, and M13mp18 (+) strand DNA. Nine housekeeping genes were included in this array. The gene expression of six of the housekeeping genes, namely, glyceraldehyde-3-phosphate dehydrogenase, tubulin α-1, ornithine decarboxylase, ribosomal protein S29 40S subunit, hypoxanthine-guanine phosphoribosyl transferase, and polyubiquitin, did not differ significantly between the two groups. In contrast, the expression levels of the other housekeeping genes (cytoplasmic β actin, phospholipase A2 precursor, and myosin heavy chain) were increased in HC islets compared with age-matched MF islets. Expression levels of each gene included in the array was normalized to the expression of ribosomal protein S29 40S subunit gene (a housekeeping gene provided in the array) for each group of rat.

The genes included in the Atlas rat 1.2 array are grouped into several clusters, each containing a group of genes that have related functions. For analysis of differential gene expression in islets, RNA isolated from islets obtained from 12- and 100-day-old MF and HC rats was reverse-transcribed, and the labeled cDNA was hybridized with the membrane containing the gene array, as described above. The experiment was repeated twice using cDNA prepared from two sets of rats using new membranes each time. Figures 1 and 2 show representative images indicating changes in gene expression pattern for RNA isolated from islets from 12- and 100-day-old islets from MF and HC rats, respectively. A majority of the genes included in the array were not significantly altered between the two groups of rats on days 12 and 100. The expression level of only one gene (mast cell protease 1 precursor; ratio of HC-to-MF gene expression = 0.01) was downregulated in islets from 12-day-old HC rats compared with age-matched MF islets. For 100-day-old rats, ADP ribosylation factor 4 and granzyme M precursor were downregulated in HC islets compared with MF islets (HC-to-MF ratio = 0.3 and 0.1, respectively). The significance of the downregulation of these genes in this rat model is not clear. Gene expression levels greater than twofold for HC islets compared with MF are summarized in Table 2 and are the mean of two independent experiments.

Recently, we demonstrated that the HC nutritional modification induces significant structural adaptations in the islets of 12-day-old HC rats (11). Important among these are an increase in the number of small-sized islets, an increase in the area staining immunopositive for insulin, and a decrease in the number of medium- and large-sized islets (11). In addition, alterations in the rate of apoptosis, neogenesis, and IGF-II expression have been indicated in HC islets (11). In the rat, the late fetal and early postnatal periods are critical periods in the development of the endocrine pancreas (12). It seems that in 12-day-old HC rats, as a result of the replacement of the nature-programmed rat milk (principally fat-derived calories) by the HC milk formula (principally carbohydrate-derived calories), the natural development of the endocrine pancreas is modified to accommodate the altered nutritional environment.

Several genes, in clusters encompassing cell cycle regulators, DNA-binding and chromatin proteins, transcription factors and DNA-binding proteins, oncogenes and tumor suppressors, immune system proteins, and apoptosis are related directly or indirectly to cellular development and hence could contribute to the ontogenesis of the pancreas. Examination of the gene expression patterns (HC-to-MF ratio) for islets from 12-day-old rats (Table 2) indicates that several genes that belong to clusters indicated above are significantly upregulated in HC islets compared with islets from age-matched MF (control) rats and contribute to the changes in the size and number of cells in the islets of the HC rats. For example, cyclin, proliferating cell nuclear antigen (PCNA), proto-oncogenes, and REG III gene expressions are increased in HC islets and support the above observations on morphometric changes in the pancreas of 12-day-old HC rats. Cyclins increase cell proliferation rates and regulate cell cycle (13). Levels of PCNA are indicative of actively proliferating cells (14). Human REG has been shown to be mitogenic for pancreatic β and ductal cells (15). High-mobility group (HMG) proteins regulate chromatin structure and function (16). They regulate the correct three-dimensional configuration of protein-DNA complexes and play a key role in DNA transcription (16). HMG-1 gene expression is significantly increased in islets from 12-day-old HC rats and may contribute to the increased transcription of several genes observed in this study. Proto-oncogenes are strongly mitogenic (17), and an increase in their gene expression is consistent with the altered cellular changes observed in the pancreas of 12-day-old HC rats.

In addition to the genes whose expression levels are elevated in 12-day-old HC islets, the expression of a number of other genes is upregulated in islets from 100-day-old HC rats in the clusters indicated above. In the case of genes whose expression is increased in both 12- and 100-day-old HC islets, the HC-to-MF ratio is higher in islets from 100-day-old HC rats compared with that from 12-day-old HC rats for a majority of the genes (Table 2). In an earlier study, hypertrophy and hyperplasia of the β-cells in 100-day-old HC rats compared with β-cells in age-matched MF rats was observed (4). In contrast to the suckling period, when a nutritional stimulus is present in the form of an HC milk formula for augmented islet function, in 100-day-old HC rats, this dietary stimulus is absent because both MF and HC rats are raised on a laboratory diet from the time of weaning. Earlier reports on the size and number of adult HC islets (4) indicate that morphometric alterations support the ability of the islets from 100-day-old HC rats to sustain the chronic hyperinsulinemic state. The results from the gene array studies suggest that extensive and increased gene expression patterns belonging to clusters that modulate cellular changes (cell cycle regulators, DNA-binding and chromatin proteins, transcription factors and DNA-binding proteins, oncogenes and tumor suppressors, apoptosis-related proteins, etc.) in these islets are necessary for the persistence of the chronic hyperinsulinemic state in 100-day-old HC rats.

The clusters of genes that may be implicated to have a role in the insulin secretory process of the β-cells include ion channel and transport proteins, receptors, modulators, effectors and intracellular transducers, extracellular cell signaling, and communication and metabolic pathways. It seems that because this is not an islet-specific array, many genes reported to be related directly to the insulin secretory mechanism of the islets possibly are not on the array. It is interesting to note, however, that several other genes that belong to the aforementioned gene clusters are upregulated in 12-day-old HC islets; hence, it is apparent that a wide array of altered gene expression is necessary to support the altered insulin secretory pattern observed in islets from 12-day-old HC rats. We demonstrated extensive metabolic adaptations in 12-day-old HC islets that support the altered insulin secretory capacity of these islets. These include 1) a distinct leftward shift in the response to a glucose load; 2) increased activity of the low-Km hexokinase; 3) ability to secrete insulin in the presence of Ca2+ channel inhibitors; 4) ability to secrete insulin in the absence of glucose and under simultaneous stringent Ca2+-deprived conditions; 5) increased response to glucagon-like peptide-1 and acetylcholine, indicating augmented response to protein kinase A– and C–mediated pathways for insulin secretion; and 6) reduced response to norepinephrine-mediated responses (3,18). These extensive adaptations necessitate a wide array of gene expression alterations. Among the genes that appear on the array, only a few have a direct reported role in insulin secretion. The increase in ACC gene expression is consistent with the predicted role for fatty acyl-CoAs in insulin secretion by β-cells (19) and may modulate insulin secretion by the HC islets. The increase in cytochrome oxidase gene expression possibly suggests increased mitochondrial respiration, leading to increased ATP synthesis. An increase in the mRNA levels of cytochrome oxidase-II in islets from 12-day-old HC rats has been reported (20). Sodium channels have been implicated to influence insulin secretion by β-cells (21), and increased gene expression of sodium channels suggest that these channels may regulate insulin secretion by the HC islets. The large-scale increases in gene expression patterns in clusters that could have a role in the metabolic regulation of insulin secretion suggest that several other genes have a role in the adaptive response of the HC islets.

Similar to the situation observed for the clusters of genes related to cellular development, comparison with the gene expression in islets in 12-day-old HC rats reveals that the number of genes in each of the above clusters related to metabolic adaptations whose expression is upregulated is increased in 100-day-old HC rats (Table 2). For example, cholecystokinin receptor gene expression is significantly increased only in islets from 100-day-old HC rats compared with age-matched MF islets. Cholecystokinin modulates insulin secretion by β-cells via activation of protein kinase C and mobilization of Ca2+ from intracellular calcium stores (22). Hence, an increase in its receptor expression in islets from 100-day-old HC rats supports cholinergic activation of insulin secretion by these islets. G-proteins link the receptors of several hormones to signal transduction systems, e.g., adenylyl cyclase, ion channels, phospholipase, and distal sites in insulin exocytosis in islets (23). Gene expression of several G-protein–related factors is significantly upregulated in islets from 100-day-old HC rats, indicating that they possibly contribute to the persistence of hyperinsulinemia in these HC rats. The increase in cofilin (12 days) and secretogranin (100 days) may relate to the distal steps in the exocytotic process of insulin secretion (24). Insulin has been shown to regulate its own biosynthesis (25). The increase in gene expression of insulin receptor–related receptor α and extracellular signal–regulated kinase-1 suggests that these pathways may be upregulated because of the chronic hyperinsulinemic condition of these rats. Heat shock proteins are induced in response to a wide variety of environmental and pathophysiological stressful stimuli and participate in a wide array of cellular activities, including cytoprotection (26). Heat shock protein 70 gene expression is significantly increased in islets from 100-day-old HC rats, indicating that chronic hyperinsulinemia per se or other factors associated with hyperinsulinemia in the HC rats may be a stress situation for islets in these rats. Overall, it seems that for the programming of the adaptations to the HC dietary intervention during the suckling period into adulthood, extensive changes in gene expression patterns are essential.

Gene array analyses indicate semiquantitative changes in expression patterns of a vast number of genes in a single experiment. To quantify precisely the changes in gene expression, we chose from the array two genes that have a direct relevance to islet function. As indicated earlier, the REG III gene has been shown to be a mitogenic factor for islets (15). Because there are distinctive changes in the cellular development of the HC islets during the suckling period, REG III mRNA levels were quantified using a semiquantitative PCR-based assay. ACC has been reported to be an important modulator of islet insulin secretion (27); hence, its gene expression was also quantified by a semiquantitative PCR technique. The levels of both REG III mRNA and ACC mRNA were significantly increased in islets from 12- and 100-day-old HC rats compared with the levels in age-matched MF rats (Figs. 3 and 4). In addition to these two genes that appear on the array preproinsulin gene, PDX-1, Isl-1, and GLUT 2, the IRS-1 and -2 mRNA levels were measured in islets from 12- and 100-day-old MF and HC rats. The expression levels of preproinsulin and PDX-1 genes are expected to be increased in HC islets because they have a direct relevance to the hyperinsulinemic state of the HC rats. Preproinsulin gene expression was significantly increased in HC islets from both 12- and 100-day-old HC rats (Figs. 3 and 4). PDX-1 is an important transcription factor that orchestrates the ontogeny of the pancreas during the developmental period. PDX-1 in early embryogenesis commits the primordial progenitor cell to the endocrine lineage (28). In addition, it augments preproinsulin gene transcription (29). Its gene expression is significantly increased in both the 12- and 100-day-old HC islets (Figs. 3 and 4), suggesting that it may play a significant role in the ontogeny of the HC pancreas during the suckling period and may also facilitate the onset and persistence of the hyperinsulinemic state in the HC rats by its effects on the preproinsulin promoter. Isl-1 is a transcription factor that influences pancreatic organ development as well as insulin gene expression (28), and its mRNA level is significantly increased in both 12- and 100-day-old HC islets (Figs. 3 and 4). We demonstrated previously that GLUT 2 protein content was significantly increased in islet extracts from 12-day-old HC rats (3). Here, we report that its mRNA levels are significantly increased in islet extracts from both 12- and 100-day-old HC rats compared with age-matched control rats (Figs. 3 and 4), suggesting that increased glucose transport into these islets possibly leads to increased glucose metabolism and hence increased insulin secretion. Several lines of evidence have been put forth recently to suggest the possibility of an autocrine action of insulin on β-cells. Functional insulin receptors and IRSs identical to those found in peripheral tissues have been identified in both clonal and primary β-cells (30,31). Exogenous insulin added directly to normal islets causes transcriptional upregulation of the preproinsulin gene (32). Macfarlane et al. (33) recently found that PDX-1 binding to cognate DNA is stimulated in human islets by added insulin, apparently mimicking the effect of glucose. IRS-1 and -2 are downstream signals in the insulin signaling pathway (34). The mRNA levels of both IRS-1 and IRS-2 are significantly increased in islets from both 12- and 100-day-old HC rats (Figs. 3 and 4). Considering that circulating insulin levels are significantly higher in both 12- and 100-day-old HC rats and that mRNA levels of IRS-1 and -2 are significantly higher in HC islets, it can be suggested that insulin may exert an autocrine effect on its biosynthesis in these islets.

The adaptive responses observed in both 12- and 100-day-old HC rats in response to the HC nutritional intervention during the suckling period warrant extensive changes in the protein synthetic machinery. This is supported by the large increase seen in gene expression of the clusters belonging to protein turnover, translation, and RNA processing in islets from both 12- and 100-day-old HC rats.

Other salient features of the gene array analysis of islet mRNA from MF and HC rats reported in this study include the increased gene expression of receptor-linked tyrosine phosphatases in 12-day-old HC islets. Their specific contribution to the onset of hyperinsulinemia in these rats is not clear.

Collectively, the results from the cDNA array analysis of islet gene expression patterns from 12- and 100-day-old MF and HC rats indicate that several clusters of genes involved in a wide variety of cellular functions (e.g., cell cycle regulation, protein synthesis, ion channels, and metabolic pathways) are upregulated in HC islets and may contribute to the immediate onset and persistence of hyperinsulinemia in HC rats. To our knowledge, this is the first report on global changes in gene expression pattern in islets in response to a dietary modification (HC milk formula) during the suckling period. The wide spectrum of changes in gene expression pattern suggest that in addition to the predicted changes in gene expression of preproinsulin and related transcription factors, adaptive responses at the level of expression of several clusters of genes are induced simultaneously. The increased gene expression observed for islets from 100-day-old HC rats suggests that additional gene expression patterns may be necessary to program the early adaptations into adulthood. The gene array used in this study is not specific for islet gene expression and is a fairly small-sized array. The use of a larger islet-specific cDNA array (commercially unavailable at present) will provide more extensive information on the differential gene expression in islets between MF and HC rats. Such information will aid in assessing the molecular changes that support the immediate onset and persistence of hyperinsulinemia in this rat model.

FIG. 1.

Phosphorimage of cDNA arrays probed with 32P-labeled cDNA prepared from RNA of islets isolated from 12-day-old MF and HC rats. Arrow indicates ribosomal protein S29 40S subunit gene.

FIG. 1.

Phosphorimage of cDNA arrays probed with 32P-labeled cDNA prepared from RNA of islets isolated from 12-day-old MF and HC rats. Arrow indicates ribosomal protein S29 40S subunit gene.

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FIG. 2.

Phosphorimage of cDNA arrays probed with 32P-labeled cDNA prepared from RNA of islets isolated from 100-day-old MF and HC rats. Arrow indicates ribosomal protein S29 40S subunit gene.

FIG. 2.

Phosphorimage of cDNA arrays probed with 32P-labeled cDNA prepared from RNA of islets isolated from 100-day-old MF and HC rats. Arrow indicates ribosomal protein S29 40S subunit gene.

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FIG. 3.

Expression of mRNA of preproinsulin, PDX-1, ACC, REG III, Isl-1, GLUT 2, IRS-1, and IRS-2 in islets isolated from 12-day-old MF and HC rats. The mRNA level was quantified by a semiquantitative RT-PCR assay. A: Representative gel photomicrographs for the mRNA levels of preproinsulin, PDX-1, ACC, REG III, Isl-1, GLUT2, IRS-1, and IRS-2. The upper band corresponds to the cDNA for each gene, and the lower band corresponds to the competitor DNA for the same gene. B: The means of relative densitometric values from quantification of mRNA levels. The expression value for the mRNA of each gene from MF islets was arbitrarily taken as 1. The values are the means ± SE of four independent experiments.

FIG. 3.

Expression of mRNA of preproinsulin, PDX-1, ACC, REG III, Isl-1, GLUT 2, IRS-1, and IRS-2 in islets isolated from 12-day-old MF and HC rats. The mRNA level was quantified by a semiquantitative RT-PCR assay. A: Representative gel photomicrographs for the mRNA levels of preproinsulin, PDX-1, ACC, REG III, Isl-1, GLUT2, IRS-1, and IRS-2. The upper band corresponds to the cDNA for each gene, and the lower band corresponds to the competitor DNA for the same gene. B: The means of relative densitometric values from quantification of mRNA levels. The expression value for the mRNA of each gene from MF islets was arbitrarily taken as 1. The values are the means ± SE of four independent experiments.

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FIG. 4.

Expression of mRNA of preproinsulin, PDX-1, ACC, REG III, Isl-1, GLUT 2, IRS-1, and IRS-2 in islets isolated from 100-day-old MF and HC rats. A: Representative gel photomicrographs for the mRNA levels of preproinsulin, PDX-1, ACC, REG III, Isl-1, GLUT 2, IRS-1, and IRS-2. The upper band corresponds to the cDNA for each gene, and the lower band corresponds to the competitor DNA for the same gene. B: The means of relative densitometric values from quantification of mRNA levels. The expression value for the mRNA of each gene from MF islets was arbitrarily taken as 1. The values are mean ± SE of four independent experiments.

FIG. 4.

Expression of mRNA of preproinsulin, PDX-1, ACC, REG III, Isl-1, GLUT 2, IRS-1, and IRS-2 in islets isolated from 100-day-old MF and HC rats. A: Representative gel photomicrographs for the mRNA levels of preproinsulin, PDX-1, ACC, REG III, Isl-1, GLUT 2, IRS-1, and IRS-2. The upper band corresponds to the cDNA for each gene, and the lower band corresponds to the competitor DNA for the same gene. B: The means of relative densitometric values from quantification of mRNA levels. The expression value for the mRNA of each gene from MF islets was arbitrarily taken as 1. The values are mean ± SE of four independent experiments.

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TABLE 1

Sequences of PCR primers and PCR conditions for the analysis of specific mRNAs

mRNAGenBank accession no.Primer sequences (5′–3′)PCR reaction conditions
Size of PCR product
DenAnnExtCyccDNA (bp)Competitor (bp)
Insulin J00747 TGCCCAGGCTTTTGTCAAACAGCACCTT CTCCAGTGCCAAGGTCTGAA 95 65 72 25 187 165 
PDX-1 S67435 CCACACAGCTCTACAAGGACC CGTTGTCCCGCTACTACGTTTC 95 62 72 28 614 529 
ACC J03808 ACATTAAGATGGCGGATCGACT TCAGCTTGAACCTGTC 95 52 72 30 520 460 
Reg III D23676 TCCTTCAACAATGTGTCCTG CAGCCTTGTCATGTACATC 95 56 72 30 572 495 
Isl-1 S69329 AGCAGCAACCCAACGAC TGTATCTGGGAGCTGAGAGG 95 45 72 28 272 230 
GLUT 2 J03145 TAGCAACTGGGTCTGCAAT GTAGTCCTACACTCATG 95 45 72 28 339 292 
IRS-1 X58375 TATGCCTTCTTCACGATGC GGCATCATCTCTGTATATTC 95 53 72 30 539 471 
IRS-2 AF087674 AGCTGGTGGTAGTCATACCC CAGGTTCATATAGTCAGAG 95 52 72 30 390 332 
mRNAGenBank accession no.Primer sequences (5′–3′)PCR reaction conditions
Size of PCR product
DenAnnExtCyccDNA (bp)Competitor (bp)
Insulin J00747 TGCCCAGGCTTTTGTCAAACAGCACCTT CTCCAGTGCCAAGGTCTGAA 95 65 72 25 187 165 
PDX-1 S67435 CCACACAGCTCTACAAGGACC CGTTGTCCCGCTACTACGTTTC 95 62 72 28 614 529 
ACC J03808 ACATTAAGATGGCGGATCGACT TCAGCTTGAACCTGTC 95 52 72 30 520 460 
Reg III D23676 TCCTTCAACAATGTGTCCTG CAGCCTTGTCATGTACATC 95 56 72 30 572 495 
Isl-1 S69329 AGCAGCAACCCAACGAC TGTATCTGGGAGCTGAGAGG 95 45 72 28 272 230 
GLUT 2 J03145 TAGCAACTGGGTCTGCAAT GTAGTCCTACACTCATG 95 45 72 28 339 292 
IRS-1 X58375 TATGCCTTCTTCACGATGC GGCATCATCTCTGTATATTC 95 53 72 30 539 471 
IRS-2 AF087674 AGCTGGTGGTAGTCATACCC CAGGTTCATATAGTCAGAG 95 52 72 30 390 332 

Den, denaturation; Ann, annealing; Ext, extension; Cyc, cycles.

TABLE 2

Identification of genes upregulated in islets from 12- and 100-day-old HC rats compared with age-matched MF rats

Accession no.Protein/geneFold induction
Day 12Day 100
Cell cycle regulators    
 D14014 G1/S-specific cyclin D1 (CCND1)  8.7 
 D16308 G1/S-specific cyclin D2 (CCND2); vin-1 proto-oncogene  5.3 
 Y00047 PCNA; cyclin 3.7  
DNA-binding and chromatin proteins    
 M64986 HMG protein 1; heparin binding protein P30 8.9* 
Transcription factors and DNA-binding proteins    
 X63594 1-κB α chain; RL/IF-1 gene product  19.6 
Oncogenes and tumor suppressors    
 D13374 Nucleoside diphosphate kinase B, c-myc–related transcription factor  4.4 
 D44481 Crk adaptor protein (CRK-II); proto-oncogene c-crk 2.1 8.4* 
 D30040 rac-α Serine/threonine kinase (RAC-PK-α); PKB  5.9 
RNA processing, turnover and transport    
 D17711 dC-stretch binding protein (CSBP); HNRNP K 6.2 4.5 
Ion channel and transport proteins    
 U37026 Sodium channel SCNB2, β 2 subunit, brain  6.8 
 X97041 Potassium channel Kir6.2, inward rectifier, ATP-sensitive  3.6 
 M85299 Sodium/hydrogen exchange protein 1 3.1  
 M28647 Na+/K+ ATPase α 1 subunit 2.4 7.5* 
 D10874 Vacuolar ATP synthase 16-kDa proteolipid subunit; ATP6C 2.9 8.6* 
 J02701 Sodium/potassium-transporting ATPase β 1 subunit (ATP1β1) 4.8  
 D13123 ATP synthase lipid-binding protein P1 precursor  2.6 
Trafficking and targeting proteins    
 U75581 Adipocyte fatty acid-binding protein (AFABP; FABP4)  3.4 
 J02998 ras-Related protein rab1A 4.8 4.6 
Immune system proteins    
 X16956 Microglobulin; β-2-microglobulin + prostaglandin receptor F2a 2.6 10* 
 U11760 ATPase, transitional endoplasmic reticulum  6.1 
 D23676 Islet of Langerhans regenerating protein III 4.6 25* 
Translation    
 X87106 Ribosomal protein L10 6.6 2.7 
 X53504 Ribosomal protein L12 7.6 10 
 J02646 Eukaryotic translation initiation factor 2 α subunit (EIF-2-α) 4.6 3.9 
Protein turnover    
 V01233 Carboxypeptidase D precursor (CPD)  4.1 
 D29683 Endothelin-converting enzyme 8.2  
 X02601 Polypeptide, 53 kDa, growth factor induced 8.3 8.1 
 U46034 Stromelysin 3; matrix metalloproteinase 11 (MMP11) 4.6 8.8 
 Y00697 Cathepsin L 5.4 2.6 
 J02897 Proteasome component C3 6.2  
 D30804 Proteasome subunit RC6-1  14.9 
 L31884 Tissue inhibitor of metalloproteinase 2 (TIMP2) 7.9  
 M32247 Calcium binding protein 2 (CABP2); ERP72 6.8 5.2 
 M27882 Pancreatic secretory trypsin inhibitor I precursor (PSTI-I); PSTI-II 4.5 3.2 
Apoptosis-associated proteins    
 M64723 Clusterin (CLU); testosterone-repressed prostate message 2 4.9 5.4 
Cytoskeleton and motility proteins    
 X62908 Cofilin 7.5  
Receptors (by ligands)    
 U59809 IGF II receptor (M6P/IGFR2) 5.8  
 M88096 Cholecystokinin receptor  9.6 
 L10073 5-Hydroxytryptamine (serotonin) receptor 5B; 5HT5b  4.5 
Receptors (by activities)    
 L11586 Leukocyte common antigen-related tyrosine phosphatase (LAR)  
 L19181 Receptor-linked protein tyrosine phosphatase (PTP-PS) 3.7  
 D38222 Tyrosine phosphatase-like protein; negative regulator of PTPases 5.3 2.2 
 U10699 Lysosphingolipid, G protein-coupled receptor  
Modulators, effectors, and intracellular transducers    
 M61177 Extracellular signal-regulated kinase 1 (ERK1); MAPK1 2.6 7.6* 
 M90661 Insulin receptor-related receptor-α (sIRR-1) 3.8 
 U34959 GTP-binding protein G(i)/G(s)/G(t) β subunit 2 (GNB2)  4.3 
 M17528 Guanine nucleotide-binding protein G(l) α 2 subunit (GNAI2)  3.1 
 M17525 GTP-binding protein (G-α-8)  8.8 
 M83676 rab12, ras-Related GTPase  3.1 
 D85760 Guanine nucleotide-binding protein α 12 subunit GNA12  3.6 
 D10666 NVP; neural visinin-like Ca2+-binding protein  
 D17615 14-3-3 protein ζ/δ; PKC inhibitor protein-1  2.9 
 M84416 14-3-3 protein ε; PKC inhibitor protein-1  2.7 
 L12384 ADP-ribosylation factor 5 (ARF5) 3.5  
Extracellular cell signaling and communication    
 M60921 BTG2 protein precursor; NGF-inducible anti-proliferative protein PC3  30 
 M32167 Glioma-derived vascular endothelial cell growth factor  12.3 
 D90219 C-type natriuretic peptide precursor (CNP; NPPC)  
 M17523 Peptide YY precursor (PYY)  3.8 
 M18416 Early growth response protein 1 (EGR1); NGFI-A  7.9 
 L08831 Gastric inhibitory polypeptide precursor 2.3 20.7* 
 U02983 Secretogranin 3 (Sg3) 2.7 7* 
Metabolic pathways    
 M12919 Fructose-bisphosphate aldolase A (ALDOA); muscle-type aldolase  3.7 
 D10952 Cytochrome c oxidase subunit Vb & VIa precursor (COX5B) 3.7 5.3 
 X14209 Cytochrome c oxidase, subunit IV, mitochondrial  2.8 
 X64827 Cytochrome c oxidase, subunit VIIIh 2.4 2.7 
 M19044 Mitochondrial ATP synthase beta subunit precursor (ATP5B)  
 X59737 Creatine kinase, ubiquitous, mitochondrial  2.8 
 J03808 Acetyl-CoA carboxylase (ACC); biotin carboxylase 2.9 2.9 
 M33936 Cytochrome P450 4A3 (CYP4A3);P450-LA-omega 3  9.2 
 M17086 cAMP-dependent protein kinase type I-α regulatory chain  2.7 
 M34445 67-kDa glutamic acid decarboxylase (GAD67); GAD1 5.7 
 X13817 Calmodulin (CALM; CAM) 5.3 4.5 
 D10854 NADP+ alcohol dehydrogenase; aldehyde reductase (ALR) 6.8* 
Stress response proteins    
 Z27118 Heat shock 70-kDa protein (HSP70)  12.1 
Accession no.Protein/geneFold induction
Day 12Day 100
Cell cycle regulators    
 D14014 G1/S-specific cyclin D1 (CCND1)  8.7 
 D16308 G1/S-specific cyclin D2 (CCND2); vin-1 proto-oncogene  5.3 
 Y00047 PCNA; cyclin 3.7  
DNA-binding and chromatin proteins    
 M64986 HMG protein 1; heparin binding protein P30 8.9* 
Transcription factors and DNA-binding proteins    
 X63594 1-κB α chain; RL/IF-1 gene product  19.6 
Oncogenes and tumor suppressors    
 D13374 Nucleoside diphosphate kinase B, c-myc–related transcription factor  4.4 
 D44481 Crk adaptor protein (CRK-II); proto-oncogene c-crk 2.1 8.4* 
 D30040 rac-α Serine/threonine kinase (RAC-PK-α); PKB  5.9 
RNA processing, turnover and transport    
 D17711 dC-stretch binding protein (CSBP); HNRNP K 6.2 4.5 
Ion channel and transport proteins    
 U37026 Sodium channel SCNB2, β 2 subunit, brain  6.8 
 X97041 Potassium channel Kir6.2, inward rectifier, ATP-sensitive  3.6 
 M85299 Sodium/hydrogen exchange protein 1 3.1  
 M28647 Na+/K+ ATPase α 1 subunit 2.4 7.5* 
 D10874 Vacuolar ATP synthase 16-kDa proteolipid subunit; ATP6C 2.9 8.6* 
 J02701 Sodium/potassium-transporting ATPase β 1 subunit (ATP1β1) 4.8  
 D13123 ATP synthase lipid-binding protein P1 precursor  2.6 
Trafficking and targeting proteins    
 U75581 Adipocyte fatty acid-binding protein (AFABP; FABP4)  3.4 
 J02998 ras-Related protein rab1A 4.8 4.6 
Immune system proteins    
 X16956 Microglobulin; β-2-microglobulin + prostaglandin receptor F2a 2.6 10* 
 U11760 ATPase, transitional endoplasmic reticulum  6.1 
 D23676 Islet of Langerhans regenerating protein III 4.6 25* 
Translation    
 X87106 Ribosomal protein L10 6.6 2.7 
 X53504 Ribosomal protein L12 7.6 10 
 J02646 Eukaryotic translation initiation factor 2 α subunit (EIF-2-α) 4.6 3.9 
Protein turnover    
 V01233 Carboxypeptidase D precursor (CPD)  4.1 
 D29683 Endothelin-converting enzyme 8.2  
 X02601 Polypeptide, 53 kDa, growth factor induced 8.3 8.1 
 U46034 Stromelysin 3; matrix metalloproteinase 11 (MMP11) 4.6 8.8 
 Y00697 Cathepsin L 5.4 2.6 
 J02897 Proteasome component C3 6.2  
 D30804 Proteasome subunit RC6-1  14.9 
 L31884 Tissue inhibitor of metalloproteinase 2 (TIMP2) 7.9  
 M32247 Calcium binding protein 2 (CABP2); ERP72 6.8 5.2 
 M27882 Pancreatic secretory trypsin inhibitor I precursor (PSTI-I); PSTI-II 4.5 3.2 
Apoptosis-associated proteins    
 M64723 Clusterin (CLU); testosterone-repressed prostate message 2 4.9 5.4 
Cytoskeleton and motility proteins    
 X62908 Cofilin 7.5  
Receptors (by ligands)    
 U59809 IGF II receptor (M6P/IGFR2) 5.8  
 M88096 Cholecystokinin receptor  9.6 
 L10073 5-Hydroxytryptamine (serotonin) receptor 5B; 5HT5b  4.5 
Receptors (by activities)    
 L11586 Leukocyte common antigen-related tyrosine phosphatase (LAR)  
 L19181 Receptor-linked protein tyrosine phosphatase (PTP-PS) 3.7  
 D38222 Tyrosine phosphatase-like protein; negative regulator of PTPases 5.3 2.2 
 U10699 Lysosphingolipid, G protein-coupled receptor  
Modulators, effectors, and intracellular transducers    
 M61177 Extracellular signal-regulated kinase 1 (ERK1); MAPK1 2.6 7.6* 
 M90661 Insulin receptor-related receptor-α (sIRR-1) 3.8 
 U34959 GTP-binding protein G(i)/G(s)/G(t) β subunit 2 (GNB2)  4.3 
 M17528 Guanine nucleotide-binding protein G(l) α 2 subunit (GNAI2)  3.1 
 M17525 GTP-binding protein (G-α-8)  8.8 
 M83676 rab12, ras-Related GTPase  3.1 
 D85760 Guanine nucleotide-binding protein α 12 subunit GNA12  3.6 
 D10666 NVP; neural visinin-like Ca2+-binding protein  
 D17615 14-3-3 protein ζ/δ; PKC inhibitor protein-1  2.9 
 M84416 14-3-3 protein ε; PKC inhibitor protein-1  2.7 
 L12384 ADP-ribosylation factor 5 (ARF5) 3.5  
Extracellular cell signaling and communication    
 M60921 BTG2 protein precursor; NGF-inducible anti-proliferative protein PC3  30 
 M32167 Glioma-derived vascular endothelial cell growth factor  12.3 
 D90219 C-type natriuretic peptide precursor (CNP; NPPC)  
 M17523 Peptide YY precursor (PYY)  3.8 
 M18416 Early growth response protein 1 (EGR1); NGFI-A  7.9 
 L08831 Gastric inhibitory polypeptide precursor 2.3 20.7* 
 U02983 Secretogranin 3 (Sg3) 2.7 7* 
Metabolic pathways    
 M12919 Fructose-bisphosphate aldolase A (ALDOA); muscle-type aldolase  3.7 
 D10952 Cytochrome c oxidase subunit Vb & VIa precursor (COX5B) 3.7 5.3 
 X14209 Cytochrome c oxidase, subunit IV, mitochondrial  2.8 
 X64827 Cytochrome c oxidase, subunit VIIIh 2.4 2.7 
 M19044 Mitochondrial ATP synthase beta subunit precursor (ATP5B)  
 X59737 Creatine kinase, ubiquitous, mitochondrial  2.8 
 J03808 Acetyl-CoA carboxylase (ACC); biotin carboxylase 2.9 2.9 
 M33936 Cytochrome P450 4A3 (CYP4A3);P450-LA-omega 3  9.2 
 M17086 cAMP-dependent protein kinase type I-α regulatory chain  2.7 
 M34445 67-kDa glutamic acid decarboxylase (GAD67); GAD1 5.7 
 X13817 Calmodulin (CALM; CAM) 5.3 4.5 
 D10854 NADP+ alcohol dehydrogenase; aldehyde reductase (ALR) 6.8* 
Stress response proteins    
 Z27118 Heat shock 70-kDa protein (HSP70)  12.1 
*

For each group, expression of each gene was normalized to the expression of ribosomal protein S29 40S subunit provided as a housekeeping gene in the array. The results are fold increases of gene expression in islets from HC rats compared with age-matched MF rats. *Indicates the genes having relative expression levels significantly higher in islets from 100-day-old HC rats compared with islets from 12-day-old HC rats.

This work was supported in part by National Institute of Child Health and Human Development Grant HD-11089 and National Institute of Diabetes and Digestive and Kidney Diseases Grant DK-51601.

The authors are grateful to Dr. Paresh Dandona and Husam Ghanim of the Department of Medicine, School of Medicine and Biomedical Sciences, State University of New York at Buffalo, for help with the analysis of the data from the gene array experiments.

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Address correspondence and reprint requests to Mulchand S. Patel, Department of Biochemistry, School of Medicine and Biomedical Sciences, State University of New York at Buffalo, 140 Farber Hall, 3435 Main St., Buffalo, NY 14214. E-mail: mspatel@buffalo.edu.

Received for publication 6 June 2000 and accepted in revised form 16 May 2001.

ACC, acetyl CoA carboxylase; HC, high-carbohydrate; HMG, high-mobility group; IRS, insulin receptor substrate; Isl-1, islet factor-1; MF, mother-fed; PCNA, proliferating cell nuclear antigen, PDX-1, pancreatic duodenal transcription factor-1; REG, regenerating protein; RT-PCR, reverse transcriptase–polymerase chain reaction.