Coupling of GnRH Concentration and the GnRH Receptor-Activated Gene Program

Tony Yuen, Elisa Wurmbach, Barbara J. Ebersole, Frederique Ruf, Robert L. Pfeffer and Stuart C. Sealfon

Department of Neurology (T.Y., E.W., B.J.E., R.L.P., S.C.S.) Fishberg Research Center for Neurobiology (S.C.S.), Graduate School of Biological Sciences (F.R.) and Department of Pharmacology (S.C.S.), Mount Sinai School of Medicine, New York, New York 10029

Address all correspondence and requests for reprints to: Stuart C. Sealfon, M.D., Neurology Box 1137, Mount Sinai School of Medicine, New York, New York 10029. E-mail: Stuart.Sealfon{at}mssm.edu.


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
The initial waves of gene induction caused by GnRH in the LßT2 gonadotrope cell line have recently been identified using microarrays. We now investigate the relationship of the concentration of GnRH to the level of biosynthesis induced. Using an optimized custom cDNA microarray, we show that a large number of genes are induced in a concentration-dependent fashion. Detailed time course studies of the induction of six induced transcripts using quantitative real-time PCR suggest that the amplitude, but not the temporal pattern, depends on the concentration of GnRH. The early genes appear to show a delay in gene induction, followed by a linear phase of increase. The relationship of rate of synthesis and GnRH concentration was studied by mathematical modeling of the induction of two genes, gly96 and tis11. In both cases, only the rates of increase, but not the lag times, are influenced by the concentration of GnRH exposure. Western blot analyses for c-Jun and Egr1 show that the levels of nuclear protein for these transcription factors also depend on the concentration of GnRH. These studies indicate that, despite the complex signaling network connecting the receptor to the activated genes, the biosynthetic rate of RNA polymerase at induced genes is correlated with the concentration of GnRH at the GnRH receptor.


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
THE GnRH receptor (GnRHR) is a rhodopsin-family G protein coupled receptor located on the pituitary gonadotrope. Activation of this receptor by the hypophysial decapeptide hormone GnRH mediates the biosynthesis and secretion of the gonadotropins LH and FSH. GnRH is normally released in a pulsatile manner, and normal secretory and biosynthetic function depends on the pattern of receptor stimulation.

To understand the mechanisms underlying control of gonadotropin biosynthesis, we have begun to explore the signal transduction and gene network structure both experimentally and computationally. To address the many parameters that require study for generating and testing models of this system, we are focusing our efforts on the LßT2 gonadotrope cell line (1). We are mapping the global transcriptional program activity by GnRH in these cells using microarray technologies (2). We find that GnRH induces activation of a complex gene program consisting of two distinct waves of gene activation within the first 6 h of receptor stimulation. In the first wave, more than four dozen genes are activated, with significant elevation in the level of the transcripts detectable at 1 h. Using microarrays, we have also identified about a dozen transcripts expressed only in the second wave, which are elevated after the first hour of receptor stimulation (Ebersole, B. J., T. Yuen, E. Wurmbach, and S. Sealfon, unpublished data).

Hypothalamic GnRH is normally released in a pulsatile manner, and the pattern of GnRH activation of downstream genes in the pituitary gonadotrope, such as LHß or FSHß, is determined by the pattern with which GnRH stimulates the gonadotrope GnRH. The mechanisms by which these downstream tertiary genes respond preferentially to particular patterns of receptor stimulation have not been identified, although studies of the induction of gonadotrope genes by calcium pulses suggest that the frequency detector lies distal to the receptor (3, 4). There are three component features of GnRHR stimulation that could contribute to the encoding of the specific stimulus to the genome: amplitude (concentration), frequency, and pulse duration. In the present study, we investigate the relationship of the level of GnRH exposure to the subsequent rate of early and intermediate gene induction.

We are particularly interested in determining whether the signaling network coupling the occupancy of the receptor to changes in the activity of RNA polymerase at activated promoters provides a switch-like or a graded response to changes in GnRHR occupancy. The first wave of gene induction, which consists of activation of the early genes, occurs downstream of a complex network of cellular signaling. This signaling network comprises G proteins, activation of multiple phospholipases including PLC, PLA2, and PLD, calcium mobilization, and sequential activation of multiple protein kinases including PKC and MAPK cascades (5, 6, 7, 8, 9). The terminal MAPK activation causes the activation of constitutively present transcription factors, such as ETS factors, and the induction of the early response genes. To more fully understand the global response properties of the signaling network connecting the GnRHR and the transcriptome, we investigated the relationship of the concentration of GnRH at the receptor to the level of gene induction, using a custom cDNA microarray, quantitative real-time PCR (QRTPCR), and Western blot analysis.


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Microarray Study of Gene Program Concentration Dependence
We have developed an optimized candidate gene approach to cDNA microarray studies called focused microarray analysis (FMA) (2). In FMA, the genes to be assayed are selected and are studied in triplicate spotted arrays using an optimized protocol and outlier detection algorithm. FMA provides sensitive, specific, and quantitative assessment of the regulated genes (10). We previously used FMA to characterize the composition of the early gene program activated by GnRH in LßT2 cells (2).

In the present study, this early gene array was used to investigate whether the global gene program activated by GnRH showed differential induction with varying concentrations of GnRH exposure. LßT2 cells were exposed to vehicle, low GnRH (4 nM GnRH) or high GnRH (100 nM) for 1 h. These concentrations were selected to reflect the variations in GnRH concentrations that cause the greatest difference in activation of a well characterized proximal signal transduction response, PLC-mediated inositol phosphate accumulation mediated by the mouse receptor (Fig. 1Go and Ref. 11). The resulting RNA samples were hybridized in pairs (vehicle against low GnRH and low GnRH against high GnRH) to microarrays containing 956 cDNAs spotted in triplicate, including a large number of early genes. As shown in the overlays and scatterplots in Fig. 2Go, most of the genes assayed had indistinguishable levels of expression.



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Figure 1. Concentration-Response of GnRHR Coupling to PLC in LßT2 Cells

Cells were treated with GnRH, and inositol phosphate accumulation was determined. The curve fit gives an EC50 of 22 nM GnRH and a slope index (analogous to the Hill coefficient) of 1.1.

 


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Figure 2. cDNA Microarray Hybridization Overlays and Scatterplots

Microarrays were hybridized with RNA obtained from cells treated with vehicle, 4 nM GnRH, or 100 nM GnRH for 40 min. A, False color overlay from hybridization with RNA from vehicle (green)- and 4 nM GnRH (red)-treated cells. The triplicate features corresponding to egr1 are indicated. B, Overlay from hybridization with RNA from 4 nM GnRH (green)-treated and 100 nM GnRH (red)-treated cells. C and D, Scatterplots showing all data (background-subtracted signal intensity) obtained from the experiments shown in panels A and B, respectively. Most measurements lie along the line y = x and are not regulated. The triplicate data points corresponding to egr1 measurements in both scatterplots are encircled. The complete microarray data sets can be found in the tables, which are published as supporting information on The Endocrine Society’s Journals Online web site, http://mend.endojournals.org/.

 
Although some triplet data points corresponding to obviously regulated genes are identifiable on the scatterplot (see Fig. 2Go), statistical analysis is more sensitive for identifying regulated transcripts. We used a t test-based outlier detection algorithm to identify which of the genes previously found to be inducible by GnRH (2) were also regulated in these comparisons of cells treated with different GnRH concentrations. A large number of genes show a graded induction in response to changes in GnRH concentration (Fig. 3Go). These results suggest that the level of the early gene responses induced in LßT2 cells are sensitive to the concentration of GnRH.



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Figure 3. Concentration Dependence of GnRH-Stimulated Gene Induction Determined by Microarray

The graph shows the fold-change determined by microarray between vehicle and 4 nM GnRH-treated cells (white bars) and between vehicle and 100 nM GnRH-treated cells (black bars). Note that the 100 nM fold-change values plotted were calculated from the data in both hybridizations shown in Fig. 2Go. Only genes previously determined to be regulated by 100 nM GnRH in comparison to vehicle (2 ) and showing a significant difference in the vehicle per 4 nM GnRH microarray or the 4 nM GnRH per 100 nM GnRH microarray are shown.

 
Concentration Dependence of Gene Induction Time Courses
The relationship between the concentration of GnRH and the subsequent level of early genes induced was studied by QRTPCR. A detailed time course of the induction of five induced early genes, egr1, pip92, tis11, c-fos, and gly96, was performed with different concentrations of GnRH exposure. The resulting gene trajectories demonstrate that the temporal pattern of induction is unaffected by concentration (Figs. 4Go, 5AGo, and 7Go). In these figures, the solid lines connecting the points were added only as visual aids to identify the different concentrations; because of the uncertainty of the measurements, their fine oscillations should be regarded as spurious. Therefore, the overall shapes of these gene trajectories are similar at differing concentrations of GnRH exposure. However, their amplitudes are not: all of the genes studied show a direct correlation of the concentration of GnRH and the levels of transcript induced.



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Figure 4. Trajectories of Three Induced Early Genes at Different GnRH Concentrations

LßT2 cells were exposed to either vehicle, 4 nM GnRH, 20 nM GnRH, or 100 nM GnRH, and the levels of each gene were determined by QRTPCR. A, egr1 Induction. B, pip92 Induction. C, tis11 Induction. Each time point represents the mean number of transcripts of three to six replicate samples at the labeled concentrations; the error bars indicate the SEMs. Note that while the amplitudes of the responses are sensitive to the concentration of GnRH, the general pattern of induction is independent of concentration.

 


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Figure 5. Trajectories of c-fos, nab2, and pai1 at Different GnRH Concentrations

The pattern of induction of an early gene (c-fos), an intermediate gene (nab2), and a sustained early gene (pai1) were compared in cells treated with vehicle, 0.8 nM GnRH, 4 nM GnRH, 20 nM GnRH, and 100 nM GnRH. A, c-fos Induction. B, nab2 Induction. C, pai1 Induction. Each time point represents the mean number of transcripts of five to six replicate samples at the labeled concentrations; the error bars indicate the SEMs.

 


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Figure 7. Modeling Experimental Data on gly96 and tis11 Induction by GnRH

The patterns of induction of gly96 and tis11 were determined in cells treated with different concentrations of GnRH. The data plotted represent the baseline-subtracted level of gene expression. Each point represents the mean value of six replicate samples at each time point, and the error bars represent their SD values. The resulting data were fit by means of unweighted nonlinear regression to the model described in the text, with the solid curves showing the resulting fits for gly96 induction with 4 nM GnRH (panel A), 20 nM GnRH (panel B), and 100 nM GnRH (panel C); and for tis11 induction with 4 nM GnRH (panel D) and 100 nM GnRH (panel E).

 
There are two waves of gene induction within the first 6 h after GnRH exposure to LßT2 cells. The delay in the induction of secondary genes presumably results from a requirement for the synthesis of new transcription factors for their activation. We were interested in determining whether the induction of a secondary gene, which is even further separated from receptor activation, also showed an amplitude of induction that was dependent on the concentration of GnRH exposure. We therefore compared the dynamics of induction of the primary c-fos gene, the sustained primary gene pai1, and the secondary nab2 gene, the product of which is potentially important in modulating the subsequent induction of the LHß gene (12). The levels of these transcripts in LßT2 cells were studied after exposure to various concentrations of GnRH for up to 4 h (Fig. 5Go). In independent experiments, the rate at which nab2 returns to baseline levels varies. Because of this variability, our results do not exclude variations in the time course of nab2 induction with changes in the concentration of GnRH. Overall, we find that the trends are repeated: to within the limits of error, all genes studied in detail show concentration-dependent levels of induction but, aside from a single time point in nab2 (120 min), concentration-independent shapes.

Concentration Dependence of Protein Synthesis
Genome-wide expression allows study of the response of the transcriptome to a stimulus. The ultimate effect of this altered transcription requires alterations in the levels of protein expression. Alterations in the transcriptome after GnRHR activation do not necessarily predict alterations in the proteome. Protein expression has many loci for regulatory control in addition to modulation of mRNA expression, including translation, processing, and degradation. For example, GnRH has been reported to regulate translation in {alpha}T3–1 cells (13). Thus, the ability for alterations in the gene program to predict changes in protein expression requires experimental validation. We have studied whether the concentration dependence of the gene program was reflected in a similar concentration dependence of the levels of induced proteins for Egr1 and c-Jun. The results of these experiments are shown in Fig. 6Go. For physiologically relevant levels of GnRH, we find that the nuclear levels of Egr1 and c-Jun detected 2 h after constant GnRH exposure are correlated to GnRH concentration. The levels of both proteins are increased by 1 nM GnRH and further increased at 10 nM GnRH. c-Jun expression shows still further increases at 100 nM GnRH. At supraphysiological levels of GnRH (1 µM), there is an apparent reduction in the level of c-Jun relative to that seen at lower concentrations. These data indicate that the increase in the protein levels of Egr1 and c-Jun are influenced by the concentration of GnRH acting at the receptor.



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Figure 6. Western Blot Showing Concentration Dependence of Egr1 and c-Jun Induction by GnRH

LßT2 cells were treated with the concentrations of GnRH indicated and, after 2 h, nuclear protein was isolated for Western blot analysis with antisera against Egr1 and c-Jun.

 
Mathematical Modeling of Gene Induction
The relationship between the occupancy of the GnRHR and the level of activity of RNA polymerase at specific promoters was explored computationally and experimentally. The studies described above suggest that the level of gene expression is coupled to the degree of occupancy of the GnRHR. Analysis of the relationship of GnRHR concentration-response and activation of PLC, as reflected in inositol phosphate accumulation, demonstrate that the concentration-response curve shows a Hill coefficient of approximately 1, indicating that the occupied receptor is linked to the level of activity of PLC in an apparently noncooperative manner (see Fig. 1Go).

We established a mathematical model to study the relationship of GnRH concentration to the level activity of RNA polymerase at two induced early genes, gly96 and tis11. These were selected for study because they exhibit a somewhat more sustained phase of increase than many other early genes. After the introduction of GnRH, their expression levels, after an initial lag, were seen to increase at linear rates for about 2 h and about 45 min, respectively. To reflect this observation, we used the following simple empirical model:

where P(t) is the expression level of the gene transcript at time t, P0 is the baseline level of gene expression, V is the rate of synthesis of the gene transcript induced by a particular concentration of GnRH, and tL is the time lag between the introduction of GnRH at the membrane and the increase in the rate of synthesis at the target gene. Based on the apparent linearity of the initial phase of gene accumulation, we neglect any changes in the rate of degradation of gene product that occur during this short period after the introduction of GnRH.

We applied this model to experimental data on the induction of gly96 and tis11 by GnRH and find that the model provides a reasonable fit (Fig. 7Go). Each point in the figure represents the mean value of six replicate samples at each time value, and the error bars represent their SD values. The resulting data were fit using unweighted nonlinear regression to the model described in the text to determine the lag times and rates of synthesis of the gene transcripts, with the solid curves showing the resulting fits.

The lag times after GnRH exposure appear to be relatively independent of the concentration of GnRH and are approximately 8–10 min for both gly96 and tis11 in these experiments. The rate of gene synthesis is dependent on the concentration of GnRH. For gly96 the rates are calculated to be about 80 transcripts/min/sample at 4 nM GnRH, about 170 transcripts/min/sample at 20 nM GnRH and about 250 transcripts/min/sample at 100 nM GnRH. For tis11 the rates are calculated to be about 9,600 transcripts/min/sample at 4 nM GnRH and about 86,000 transcripts/min/sample at 100 nM GnRH. Based on the number of cells we assayed in each sample, we can estimate the rate of transcription of each individual LßT2 cell. We thereby determine, for example, that the maximal rate of gly96 transcription in the average cell exposed to 100 nM GnRH is less than one transcript/minute. If we assume two cycles of cell division after plating, a 50% RNA recovery, and a 10% efficiency of reverse transcriptase, we arrive at the result that the maximal rate of gly96 synthesis achieved at 100 nM GnRH is only approximately 0.35 transcript/min. Although this calculation is highly provisional due to the need to estimate many parameters, it provides a useful starting point for further study. It is also important to note that we are studying populations of cells, and our data do not distinguish between two possible responses to increases in GnRH: increases in the rate of transcription per cell and increases in the proportion of cells activating transcription for the genes assayed (see Discussion).


    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
In the present study we demonstrate for several genes examined in detail that the amplitude of the biosynthetic program induced by GnRH in LßT2 cells is directly determined by the concentration of GnRH exposure. The complex and interconnected signaling network transduces the level of receptor occupancy into the level of activity of RNA polymerase at the activated genes. Indeed, the concentration-response curve measured at a proximal signal mediator such as PLC may be similar to that measured at the level of gene induction.

The physiological effects achieved through activation of the GnRHR are known to be sensitive to the precise pattern of receptor stimulation. Our studies of the transcriptional program are directed toward elucidating the mechanisms through which a tertiary gene such as LHß recognizes that the membrane receptor has been activated in a specific pattern. The present study indicates that the signaling circuitry connecting the membrane and the proximal gene network transmits a biosynthetic signal that continues to contain information concerning the concentration of GnRH.

Although it may appear obvious that the gene responses show a graded response to gradual changes in GnRH concentration, one can imagine other possibilities and, in fact, the present data are not definitive. A priori, it would be equally likely that the induction of the genes in the first two waves show an all-or-none response to activation of the receptor. A thresholding gate might arise either from the signaling cascade or the process of gene activation itself. Each cell contains only two copies of most activated genes and the process of activation, whereby RNA polymerase is allowed to begin transcription, is not necessarily well designed to provide finely graded responses. Our estimate of the transcription rate per cell for gly96 suggests the gene activation is inefficient in comparison with the potential rate of activity of the polymerase. Furthermore, it is important to recognize that the present studies are based on populations of cells. As shown by Ferrell and Machleder (14) in their study of progesterone activation of MAPK in oocytes, the graded signaling responses measured in a population of cells may mask an all-or-none response occurring at the level of the single cell. Thus the true nature of the dynamics of the gene response will require the extension of these studies to the level of the single cell.

Our present results suggest that assaying the transcriptional program can provide a reliable assay of the signal transduction responses of the cell after GnRHR activation. The GnRHR is coupled to an interconnected signaling network. A particular stimulus at the receptor (i.e. a specific concentration of GnRHR delivered in a specific temporal pattern) will lead to a characteristic change in the level of activity of the various signaling components. However, monitoring the effects of this stimulus on the cell’s signaling network is beyond the capacity of conventional signal transduction assays, which provide quantitative data on only a limited number of signaling components. We show that the amplitude of the transcriptional program is directly influenced by the concentration of GnRH at the receptor. Thus, monitoring this transcriptional program represents a global assay of the changes in cell signaling that have occurred.

Quantitative assays of the amplitude and temporal dynamics of the transcriptional changes that occur after a specific concentration and pattern of GnRH exposure to the gonadotrope provides two interrelated but distinct types of information. On the one hand, these data provide information on the unfolding of the biosynthetic program that occurs in response to this stimulus. However, in addition to this information about the proteins induced, the amplitude and dynamics of the gene program also provide a snapshot of the changes in cellular signaling that occur. In this case, the gene promoters are acting as signal transduction sensors, analogous to transfectable gene reporters (e.g. Refs. 15 and 16), that provide feedback on the changes in cell signaling that have occurred after receptor activation. We describe genes that are assayed to monitoring receptor-stimulated signaling as "intrinsic reporters of cell signaling" (IRC) (17).

We have developed a simple model of gene induction and find that it adequately describes the initial phase of induction of gly96 and tis11. Our model provides a mechanism through which the rate of synthesis of genes induced by GnRH can be estimated from the level of gene expression at a single time point. Thus the model provides a useful starting point for studies to investigate the cooperativity of coupling between the occupancy of the GnRHR and the increased rate of gene synthesis that results.

Through the use of genome-profiling techniques we have characterized the first two waves of genes induced by constant GnRH exposure (2) and, in the present report, determined the effects of altering GnRH concentration on this gene program. These studies represent an initial map of the transcriptionally modulated factors potentially involved in signaling between the cell membrane and downstream genes such as LHß. The characteristic responses of this signal transduction and genetic network to pulses of GnRH and to perturbations in pulse frequency and duration remains to be defined. We have set the stage for systematic studies of the response of this gene network to patterned stimulation of the GnRHR and for testing hypotheses about network function through mathematical modeling (Krakauer, D., K. Page, and S. C. Sealfon, unpublished data). We expect these studies to clarify the mechanisms through which complex, temporally encoded signals can be reliably transmitted from the hypothalamic GnRH neurons to their ultimate downstream gene targets, the tertiary genes that are so deeply embedded in the gonadotrope’s genetic network.


    MATERIALS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Cell Culture and RNA Sample Preparation
LßT2 cells obtained from Pamela Mellon (University of California, San Diego, CA) were maintained at 37 C in 5% CO2 in humidified air in DMEM (Mediatech, Herndon, VA) containing 10% FBS (Gemini, Calabasas, CA) (1). For microarray experiments, approximately 5 x 107 cells were seeded in 15-cm dishes and medium was replaced 24 h later with DMEM containing 25 mM HEPES (Mediatech), 10% charcoal-stripped FBS (HyClone Laboratories, Inc., Logan, UT), and glutamine. On the next day, the cells were treated with the indicated concentrations of GnRH or vehicle and were returned to the CO2 incubator for 40 min, at which point the medium was replaced with 10 ml lysis buffer (4 M guanidinium thiocyanate, 25 mM sodium citrate (pH 7.0), 0.5% N-lauroyl-sarcosine, and 0.1 M 2-mercaptoethanol). RNA was isolated according to the method of Chomczynski and Sacchi (19). For QRTPCR experiments, cells were seeded in 12-well plates at 750,000 cells per well. The medium was replaced 24 h later as above, and the next day cells were treated with indicated concentrations of GnRH for the indicated times. Total RNA was isolated with the StrataPrep96 kit (Stratagene, La Jolla, CA) using a modification described previously (17).

Accumulation of [3H]Inositol Phosphates
LßT2 cells were seeded in 24-well plates at a density of 300,000 cells/well. Twenty-four hours later, the medium was changed to DMEM containing 25 mM HEPES (Mediatech), 10% charcoal-stripped FBS (HyClone Laboratories, Inc.), glutamine, and 1 µCi/ml of [3H]-myo-inositol (NEN Life Science Products, Boston, MA), and the cells were grown for an additional 18 h. Accumulation of [3H]inositol phosphates in response to varying concentrations of GnRH for 30 min was measured and data were analyzed as described previously (20).

Western Blot
Nuclear extracts were prepared from cells treated with GnRH as indicated for 2 h grown in 100-mm dishes (seeded at 1 x 107 cells per dish) as described in Ref. 21 . The protein concentration in the extract was determined with the BCA reagent (Pierce Chemical Co., Rockford, IL), and samples were diluted to equalize the protein concentration. Proteins were separated on 4–12% NuPage polyacrylamide gels (Invitrogen, Carlsbad, CA) and transferred to a polyvinylidene difluoride membrane by semidry blotting. The membrane was washed three times for 10 min with 10 mM Tris-HCl (pH 8.0), 109 mM NaCl, 0.1% Tween-20 (TBST) and blocked for 1 h with TBST containing 5% milk protein (MTBST). For detection of Egr1, the membrane was incubated with anti-Egr1 (# sc-110, Santa Cruz Biotechnology, Inc., Santa Cruz, CA) diluted 1:2000 overnight at 4 C. For detection of c-Jun, the membranes were incubated overnight at 4 C with anti-c-Jun diluted 1:1000 in TBST containing 5% BSA (PhosphoPlus Antibody Kit, Cell Signaling Technology, Beverly, MA). The membranes were washed three times for 10 min with TBST and blocked with MTBST for 30 min, and incubated with secondary antibody diluted 1:5000 in MTBST (donkey antirabbit Ig linked to horse radish peroxidase, Amersham Life Sciences, Piscataway, NJ). Immunoreactive bands were visualized with the ECLplus detection system (Amersham Pharmacia Biotech, Arlington, IL).

cDNA Microarray Development, Probe Labeling, and Hybridization
The design, quality control, validation, and detailed protocols for use and analysis of this microarray have been described elsewhere (2) (see Fig. 3Go). Briefly, this array contains 956 clones selected mostly from an NIA 15K library (22) or purchased from Research Genetics, Inc. (Huntsville, AL). Plasmid inserts were amplified by PCR, products were confirmed by agarose gel electrophoresis and purified. The dried product was spotted in 50% DMSO (three hits per feature, three features per gene) with a GMS 417 Arrayer (Affymetrix, Santa Clara, CA) on CMT-GAPS-coated glass slides (Corning, Inc., Corning, NY). DNA was fixed at 85 C for 2 h.

Total RNA (20 µg) from each sample was labeled with either Cy3 or Cy5 using the Atlas indirect labeling kit (CLONTECH Laboratories, Inc., Palo Alto, CA) as indicated by the manufacturer. After array prehybridization [6x saline sodium citrate (SSC), 0.5% SDS, 1% BSA at 42 C for 45 min], the probe was denatured and hybridized in 24 µl 50% formamide, 6x SSC, 0.5% SDS, 5x Denhardt’s with 2.4 µg salmon sperm DNA, 10 µg poly dA at 42 C for 16 h. After 10 min washes in 0.1x SSC, 0.1% SDS, and twice in 0.1x SSC the slide was scanned using the GMS 418 Scanner (Affymetrix).

cDNA Microarray Data Analysis
Scanned microarray data were exported as TIFF files to Genepix (Axon Instruments, Union City, CA), and spot registration was optimized manually as suggested by the developer. The median background-subtracted feature intensity was used for further analysis. Overall differences in the signal intensity of the two wavelengths measured on each slide ({lambda} = 532 nm and {lambda} = 635 nm) were corrected using the loess function in S-Plus 6.0 (Insightful Corp., Seattle, WA). Predictors were generated using a symmetric distribution, span = 0.75 (23). The ratios of the resulting corrected data for each feature were used for subsequent analysis. Coefficient of variations of the triplicate measurements on each array were determined as previously described (2). The fold-change (Fa) values were determined directly from the vehicle per 4 nM GnRH microarray for low concentration responses. The Fa values in these experiments for vehicle vs. 100 nM GnRH were determined from the product of the Fa values from the vehicle per 4 nM GnRH microarray and the 4 nM GnRH/100 nM GnRH microarray.

Outlier Detection
cDNA array genes were identified as regulated based on an algorithm described in detail elsewhere (2). Briefly, t values for the log transform ratios (logFa) were determined for triplicate data from each slide. Genes were considered to be concentration sensitive if they showed Fa > 1.3, t > 3, and signal intensity for at least one fluorophore >1% of the median signal intensity value and were previously found to be regulated by microarray and QRTPCR (2).

QRTPCR
We used a previously described protocol (17). Briefly, 5 µg total RNA were converted into cDNA and 1/400 (~250 pg) was used for 40 cycle three-step PCR in an ABI Prism 7700 (PE Applied Biosystems, Foster City, CA) in 20 mM Tris, pH 8.4, 50 mM KCl, 3 mM MgCl2, 200 µM deoxynucleoside triphosphates, 0.5x SYBR Green I (Molecular Probes, Inc., Eugene, OR), 200 nM each primer, and 0.5 U Platinum Taq (Invitrogen). Amplicon size and reaction specificity were confirmed by agarose gel electrophoresis. The number of target copies in each sample was interpolated from its detection threshold (CT) value using a plasmid or purified PCR product standard curve included on each plate. Each transcript in each sample was assayed five times, and the median CT values were used to calculate the Fp values (fold-change ratios between experimental and control samples for each gene) used in the analysis. Data validity by modeling of reaction efficiency and analysis of measurement precision is described elsewhere (10).

Mathematical Modeling
Curve fitting and simulations were performed using nonlinear least squares regression in S-Plus 6.0 (Insightful Corp.).


    ACKNOWLEDGMENTS
 
We thank Pamela Mellon for providing the LßT2 cells, Luis Quadri (Cornell Medical Center) for generously providing access to instrumentation, and Irina Ivanova for expert technical assistance.


    FOOTNOTES
 
This work was supported by NIH Grant RO1 DK-46943 and a Howard Hughes Medical Institute Award.

T.Y. and E.W. contributed equally to this study.

Abbreviations: FMA, Focused microarray analysis; GnRHR, GnRH receptor; MTBST, TBST containing milk protein; QRTPCR, quantitative real-time PCR; SSC, saline sodium citrate; TBST, Tris-buffered saline with Tween-20.

Received for publication December 21, 2001. Accepted for publication February 25, 2002.


    REFERENCES
 TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 

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