Regulation of Gene Expression in Magnocellular Neurons in Rat Supraoptic Nucleus during Sustained Hypoosmolality
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内分泌学杂志 2005年第3期
Laboratory of Neurochemistry (N.M., T.S., H.G.), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland 20892; Department of Medicine (J.G.V.), Division of Endocrinology and Metabolism, Georgetown University, Washington, D.C. 20007; and Laboratory of Genetics (C.C.X., M.J.B.), National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892
Address all correspondence and requests for reprints to: Harold Gainer, Ph.D., Laboratory of Neurochemistry, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland 20892. E-mail: gainerh@ninds.nih.gov.
Abstract
Hypoosmolality produces a dramatic inhibition of vasopressin (VP) and oxytocin gene expression in the supraoptic nucleus (SON). This study examines the effect of sustained hypoosmolality on global gene expression in the oxytocin and VP magnocellular neurons of the hypothalamo-neurohypophysial system, to identify genes associated with the magnocellular neuron’s adaptation to this physiological condition. Using laser microdissection of the SON, T7-based linear amplification of its RNA, and a 35,319-element cDNA microarray, we compare gene expression profiles between SONs in normoosmolar (control), 1-desamino-[8-D-arginine]-VP-treated normoosmolar, and hypoosmolar rats. We found 4959 genes with statistically significant differences in expression between normosmolar control and the hypoosmolar SONs, with 1564 of these differing in expression by more than 2-fold. These genes serve a wide variety of functions, and most were up-regulated in gene expression in hypoosmolar compared with control SONs. Of these, 90 were preferentially expressed in the SON, and 44 coded for transcription-related factors, of which 15 genes were down-regulated and 29 genes were up-regulated in the hypoosmolar rat SONs. None of these transcription-related factor genes significantly changed in expression after sustained 1-desamino-[8-D-arginine]-VP-treatment alone, indicating that these changes were associated with the hypoosmolar state and not due solely to a decreased activity in the SON. Quantitative in situ hybridization histochemistry was selectively used to confirm and extend these microarray observations. These results indicate that the hypoosmolar state is accompanied by a global, but selective, increase in expression of a wide variety of regulatory genes in the SON.
Introduction
HYPONATREMIA IS THE most common clinical (1, 2) and exercise-induced (3, 4) systemic electrolyte disorder and is potentially life threatening. In most cases, hyponatremia is caused by inappropriate water retention, in which case, hypoosmolality of body fluids also occurs. The hypothalamo-neurohypophysial system (HNS) plays a fundamental role in the maintenance of body fluid and electrolyte homeostasis by secreting vasopressin (VP) and oxytocin (OT) (5, 6). VP and OT are neurohypophysial hormones that are synthesized in the supraoptic nucleus (SON) and paraventricular nucleus of the hypothalamus and transported to, stored in, and released from the posterior pituitary (7, 8). During chronic hyperosmolar conditions, VP and OT mRNA levels increase approximately 2-fold (9, 10) to keep up with the increased secretion of these hormones into the blood for antidiuretic and natriuretic functions. In contrast, during chronic hypoosmolar conditions, VP and OT mRNA levels in the HNS are decreased to 10–20% of those of normonatremic control animals (11, 12), and this down-regulation of VP synthesis is consistent with the osmotic inhibition of VP that results in maximum water diuresis. Although there have been many reports of changes in gene expression in the HNS during hyperosmolality (13, 14, 15, 16, 17, 18, 19, 20, 21, 22), there have been very few studies of gene regulation during hypoosmolar conditions (21, 23).
Several changes have been associated with hypoosmolality. One is down-regulation of the expression of multiple genes in the magnocellular neurons (MCNs) of the SON during periods of low synthesis and secretion of VP and OT (23, 24). The second is the up-regulation of expression of genes that might be involved in the active inhibition of VP and OT synthesis, storage, and secretion. To the best of our knowledge, the glucocorticoid receptor (25) and the estrogen receptor ? (21) are the only genes that have been shown to be up-regulated during chronic hypoosmolality. When we previously screened cDNA libraries for genes that were differentially expressed in the HNS during chronic hyperosmolality and hypoosmolality, we failed to detect any genes that were up-regulated in the hypoosmolar condition (23), but such screening methods are far from comprehensive. Therefore, we decided to employ DNA microarrays and laser-microdissected SON samples (26) to look for changes in gene expression induced by hypoosmolality. Using this approach, we identified 4959 genes with statistically significant differences in expression between normosmolar control and hypoosmolar SONs, with 1564 of these differing in expression by more than 2-fold. These genes serve a wide variety of functions, and most were up-regulated in gene expression in hypoosmolar compared with control SONs. Of these, 90 were preferentially expressed in the SON, and 44 coded for transcription-related factors, of which 15 genes were down-regulated and 29 genes were up-regulated in the hypoosmolar rat SONs. These results indicate that the hypoosmolar state is accompanied by a global, but selective, increase in expression of a wide variety of regulatory genes, which could be involved in the MCN's adaptation to sustained hypoosmolality.
Materials and Methods
Animals
Adult male Sprague Dawley rats, weighing 260–320 g, were housed individually in wire mesh cages in a temperature-controlled room (21–23 C) with lights on from 0700–1900 h. All procedures were carried out in accordance with National Institutes of Health (NIH) guidelines on the care and use of animals and an animal study protocol approved by the Georgetown University Animal Use and Care Committee.
Induction of hyper- and hypoosmolality
To induce hyponatremia, male rats were given 1-desamino-[8-D-arginine]-VP (dDAVP; Aventis Pharmaceuticals, Bridgewater, NJ) at a rate of 5 ng/h using osmotic minipumps (Alzet model 2002; Alza, Palo Alto, CA) implanted sc, and by feeding the rats a dilute preparation (1.0 kcal/ml) of liquid formula (AIN76; Bioserv, Frenchtown, NJ) for 7 d (27, 28). Rats fed with pelleted AIN-76 and allowed access to tap water ad libitum were used as normoosmolar controls. Rats infused with dDAVP at the same rate as the hypoosmolar rats, but fed AIN76 pelleted chow and allowed access to tap water ad libitum, were used as dDAVP-treated normoosmolar rats. To induce hypernatremia, rats were given 2% NaCl solution ad libitum as their only drinking fluid for 7d. The body weights (g), plasma Na+ levels (mM), and plasma osmolalities (mosmol/kg H2O) were measured in blood samples drawn via jugular puncture from each animal after 7 d of treatment and are shown in Table 1.
TABLE 1. Physiological measurements of control, hyperosmolar, dDAVP-treated, and hypoosmolar rats
Tissue isolation, RNA processing, and microarray analysis
In this study, we used laser microdissection (LMD) and microarray techniques described previously (26), with several modifications. These procedures are described below.
Tissues
LMD of the SON.
All the rats were killed starting at 0900 h, by decapitation, and their brains were quickly removed, immediately frozen on dry ice, and stored at –80 C until further processing occurred. The tissue was placed in a cryostat for 10 min at the cutting temperature (–18 C) for temperature equilibration, and 7-μm-thick coronal sections were cut at the SON level, placed on and thawed onto membrane-coated glass slides (glass foil PEN slides; Leica Microsystems Inc., Bannockburn, IL), and immediately placed in a slide box embedded in dry ice. The sections were stored at –80 C until they were used. Before LMD, the tissue was fixed and dehydrated with ethanol as described elsewhere (29). Briefly, the slides were thawed for 45 sec in 75% ethanol and further dehydrated by sequential immersion in 95%, 100%, and again with 100% ethanol for 5 sec each. Then, the slides were cleared twice with xylene for 2 min and dried in a vacuum chamber. All of the solutions used for fixation were prepared with diethylpyrocarbonate water. LMD was performed under dark-field illumination, using a Leica Laser Microdissection Microscope (Leica Microsystems Inc.) (30), immediately after dehydration of the slides. Brains from three animals per each treatment group were individually microdissected. The dissected SONs were collected into 0.5-ml tubes with 70 μl lysis buffer containing guanidine thiocyanate and 0.5 μl ?-mercaptoethanol.
Collection of hypothalamic reference tissue.
Blocks of hypothalamic tissue were obtained from 10 control male rats. After decapitation of the rats at 0900 h, the brains were removed from the skull and placed ventral-side-up on a rubber stopper. Coronal cuts were made rostral to the optic chiasm and caudal to the cerebral peduncle. The hypothalamus was removed from the resulting brain slices by making a cut at the top of the third ventricle and cuts at the lateral margins of the optic tracts. The tissue samples were frozen in liquid nitrogen and stored at –80 C until they were extracted.
RNA extraction
Laser-microdissected SON tissue.
RNA isolation was preformed according to the manufacturer’s protocol, with the Absolutely RNA Microprep Kit (Stratagene, La Jolla, CA) (31). After extraction, total RNA was measured using a Ribogreen RNA quantitation kit (Molecular Probes, Inc., Eugene, OR). The samples and the standard RNAs were excited at 485 nm, and the fluorescence emission intensity was measured at 535 nm using a fluorescence microplate reader (VICTOR 2 1420 Multilabel counter; Wallac Oy, Turku, Finland). Fluorescence emission intensity of the samples was then plotted against an RNA standard curve. The average total RNA per animal (bilateral SON) was 193.2 ng, 113.4 ng, and 90.6 ng for control, dDAVP-treated, and hypoosmolar animals, respectively. Equal amounts of total RNA were pooled from three rats in each treatment group, and 150 ng per group was used as the template for T7-based linear RNA amplification.
Reference hypothalamic tissue.
RNA extraction of the dissected hypothalamic blocks was done with Trizol (Life Technologies, Gaithersburg, MD) (32) followed by a DNaseI (GenHunter, Nashville, TN) treatment. The product was cleaned up using an Absolutely RNA Microprep Kit (Stratagene). Approximately 200 μg of total RNA were obtained from each block, and 5 μg RNA from each of 10 animals was pooled together, and 150 ng of the pool was amplified using T7-based linear RNA amplification. Thus, we used 150 ng of the pooled hypothalamic tissue RNA and the SON RNA in each reaction to obtain consistent amplification efficiency among all the samples.
T7-based RNA amplification
RNA amplification was performed according to the manufacturer’s protocol, using a RiboAmp RNA Amplification Kit (Arcturus, Mountain View, CA). The principles of this amplification method have been described previously (33). The first round of amplification was performed on 150 ng total RNA from the pooled hypothalamic reference and the LMD SON material. For the second round, 500 ng of antisense RNA (aRNA) was collected from each of the samples and used as template. The total amount of the RNA produced was measured with a spectrophometer (Ultrospec 2100 pro UV/Visible spectrophometer; Amersham Biosciences, Piscataway, NJ). The total amounts of RNA produced in the first-round amplification were 10.6, 6.6, 4.0, and 3 μg reference hypothalamic RNA, normoosmolar control SON, dDAVP-treated SON, and hypoosmolar SON, respectively. The total amounts of aRNAs from the second round amplifications were 138, 198, 168, and 180 μg for the hypothalamic reference, control SON, dDAVP-treated SON, and hypoosmolar SON, respectively. The 260/280 ratios for the RNA samples after the second round ranged from 2.2–2.4, and the spectra from OD230 to OD320 were those expected for pure RNA. The length of the aRNAs ranged from 300-1300 bp after the first round and from 300–700 bp after the second round of amplification.
Microarray fabrication
Mouse cDNA microarrays were printed on poly-L-lysine-coated slides. The cDNA libraries that were used to print the array were provided by Dr. Bento Soares, University of Iowa (http://genome.uiowa.edu/projects/BMAP/) (adult whole-brain cDNA library) and Dr. Minoru Ko, National Institute on Aging, NIH (http://lgsun.grc.nia.nih.gov/cDNA/cDNA.html) (embryonic brain cDNA library). Plasmids were extracted from the bacteria using QiaPrep Turbo kits (Qiagen, Valencia, CA) and a BioRobot 8000 (Qiagen). The cDNA inserts were amplified with modified M13 primers (M13F 5'-GTTGTAAAACGACGGCCAGTG-3' and M13R 5'-CACACAGGAAACAGCTATG-3') and purified with MultiScreen PCR plates (Millipore, Bedford, MA). The PCR products were diluted in 50% dimethylsulfoxide to an average concentration of 200 ng/μl. These products (5 μl each) were transferred to 384-well plates (Genetix, St. James, NY) and printed using an OmniGrid arrayer (GeneMachines, San Carlos, CA). The printed slides were aged for a week and then postprocessed before hybridization. Detailed descriptions of these procedures can be viewed at http://cmgm.stanford.edu/pbrown/mguide/index.html. To validate the dissection of the SON and to confirm the response of the SON neurons to the physiological manipulations studied, we added rat VP and OT cDNAs to the arrays.
Microarray properties
The 35,319 elements printed include 11,720 product-defined clones and 23,599 product undefined clones. The number of unigene clusters represented is 26,000. In a preliminary study, we found that cross-hybridization of mouse- and rat hypothalamic RNAs on this array is 94%, indicating that it is appropriate for gene expression analysis of the rat hypothalamus (26).
Probe labeling with amine-modified random primers
Probes were synthesized from 2 μg amplified RNA. The SON was labeled with Cy-5, and the reference (whole hypothalamus) was labeled with Cy-3. The labeling was performed as described previously (34, 35) with minor modifications. Briefly, the RNA was combined with 4 μg amine-modified random primer (amine-C6-TNNNNNN; Sigma Genosys, The Woodlands, TX) and 5 U ribonuclease inhibitor (RNAsin; Promega, Madison, WI) in a total vol of 18.5 μl, incubated at 70 C for 10 min, and chilled on ice for 10 min. The primer/RNA solution was then added to 6 μl of 5x first-strand buffer (Life Technologies), 0.6 μl of 50x aminoallyl deoxy (d) UTP/dNTPs [25 mM dATP, dGTP, and dCTP; 15 mM dTTP; and 10 mM aminoallyl dUTP (Sigma, St. Louis, MO)], 3 μl 0.1-M dithiothreitol, and 2 μl SuperScript II reverse transcriptase (Life Technologies) and incubated at 42 C for 2 h. The reaction was terminated with 10 μl 0.5-M EDTA, and the RNA was hydrolyzed with 10 μl 1-N NaOH at 65 C for 30 min. The solution was neutralized with 10 μl 1-M HCl, and a MinElute PCR purification kit (Qiagen) was used to purify the products. The samples were concentrated to 9 μl in a vacuum centrifuge, and then 1 μl 1-M sodium bicarbonate (pH 9.3), was added to the cDNA solution, followed by 4.5 μl dye solution [NHS-ester Cy3 or Cy5 (Amersham Biosciences), 62.5 μg/μl in dimethylsulfoxide]. The resulting solution was mixed, by pipeting it up and down several times, and incubated at room temperature for 1 h in the dark. The labeling reaction was stopped with 4.5 μl 4-M hydroxylamine hydrochloride (Sigma). The contents of the tube were mixed, briefly centrifuged, and incubated for 30 min at room temperature in the dark. The probes were purified using a QIAquick PCR purification kit (Qiagen). The products were concentrated to 17 μl in a vacuum centrifuge. Then, 4.5 μl of 20x saline sodium citrate (SSC), 2 μl of poly (A) (A60mer, 10 mg/ml; Sigma Genosys), 1 μl human Cot-1 DNA (10 mg/ml; Life Technologies), and 1 μl yeast tRNA (4 mg/ml; Life Technologies) were added, and the probes were denatured at 98 C for 2 min. The arrays were prehybridized in 5x SSC, 0.1% sodium dodecyl sulfate (SDS), 1% BSA solution at 42 C for 1 h, washed in H2O for 2 min, rinsed in isopropanol, and centrifuged at 800 rpm for 2 min to dry them. The denatured probes were combined with 20 μl of 2x hybridization buffer (50% formamide, 10x SSC, 0.2% SDS). The hybridization solution was pipeted onto the array, cover slips were applied, and the slides were placed in a hybridization chamber (Corning, Corning, NY). They were incubated in a 42-C water bath for 16 h, the cover slips were removed, and the arrays were washed in 2x SSC plus 0.1% SDS, in 0.5x SSC plus 0.01% SDS, and 0.06x SSC for 5 min each. The slides were centrifuged at 800 rpm for 2 min to dry them before scanning. Dye swapping was not performed in our analysis because we previously established that the modified indirect labeling method used here with amine-modified random primer did not have dye bias (34). In addition, we performed comparisons by hybridizing each of our treatment group samples against a reference sample, and we analyzed the fold changes of the expression ratio for each gene. We always used the same dyes on the reference and treatment groups, consistent with reference-designed array studies where a reverse labeling, to exclude dye bias, is not necessary (36, 37).
Array scanning and data analysis
The arrays were scanned with a GenePix 4000A scanner (Axon, Foster City, CA) at 10-μm resolution. The photomultiplier tube (PMT) voltage settings were varied to obtain the maximum signal intensities with less than 1% probe saturation. The color images were formed by assigning the SON intensity in red and the hypothalamic reference intensity in green (see Fig. 3). The resulting images were analyzed using IPLab (Scanalytics, Fairfax, VA) and ArraySuite (National Human Genome Research Institute, NIH, Bethesda, MD) software, and the ratios of the red over the green intensity for all targets were determined. Calibrated ratios were obtained by a normalization method based on the ratio statistics (38, 39). To determine the reliability of each ratio measurement, a set of quality indicators were used: 1) association of a sufficiently large numbers of pixels with the element; 2) flat local background; 3) uniform signal consistency within the target area; and 4) unsaturation of the majority of the signal pixels. Based on these indicators, a quality rank was calculated ranging from 1 to 0, and genes with quality rank scores less than 0.1 were excluded from our analysis. A detailed description of this procedure is provided elsewhere (38, 39). Also, genes with intensities lower than 250 [4 x (the average background + 3 SD)] of the arrays in this experiment) in the red (SON) channel were excluded from the analysis. The labeled control SON samples were hybridized in triplicate, and the labeled dDAVP-treated SON and hypoosmolar SON samples were hybridized in quadruplicate. In summary, we used three arrays for the control and four arrays each for the dDAVP-treated and sustained-hypoosmolar conditions. The control arrays were done in triplicate, and the dDAVP-treated and hypoosmolar were done in quadruplicate. Replicates are defined as hybridization replicates. We used three animals per treatment, and the samples were pooled before amplification. Statistical analysis to compare the three experimental groups was performed by ANOVA using mAdb program (CIT/BMAS, NIH). A 95% confidence interval was used throughout the experiments to detect differentially expressed genes.
FIG. 3. Scanned image of a DNA array hybridized with Cy3- (shown as a green signal) or Cy5- (shown as a red signal) labeled cDNA probes, which were generated from amplified whole-rat hypothalamus reference and laser-microdissected rat SON RNA, respectively, is shown in A. The expression ratio data for the VP gene under various conditions is shown in B. In A, eight panels of a 48-panel array are shown, where two panels contain either the VP or the OT target cDNAs (arrows indicate the printed spot for the VP and OT genes.) The red signal indicates genes that are expressed at relatively greater levels in the SON compared with the total hypothalamus reference sample, and the green signal indicates genes that are expressed at relatively greater levels in the hypothalamus compared with the SON. Yellow indicates genes that are approximately equivalently expressed in both of the tissues. In B, VP gene expression ratios that were obtained from the array in the control, dDAVP-treated, or hypoosmolar conditions are shown. Data are shown as means ± SEM. **, P < 0.05 in an ANOVA analysis.
We used the method of multidimensional scaling (MDS) to display the overall similarities and differences among treatment groups in a three-dimensional Euclidean space. The positions of each group in the Euclidean space are determined in such a way that the Euclidean distances between groups corresponds as closely as possible to 1 minus the Pearson correlation coefficients between the logarithm of intensity ratios for the group (40). The MDS was preformed using the MATLAB software (The MathWorks, Inc., Natick, MA).
In situ hybridization histochemistry (ISHH)
In this study, we used a quantitative ISHH protocol, described elsewhere (41), with minor variations. The rat heteronuclear (hn) VP probe (kindly provided by Dr. Thomas Sherman, Georgetown University, Washington, D.C.) was a 735-bp fragment of intron 1 of the rat VP gene subcloned into pGEM-3 vector (Promega) (42). T7 and SP6 primers were used to PCR-amplify the fragment, and the resulting PCR product was used as a template for riboprobe synthesis. Some plasmids that contained selected expressed clones on the array were studied further by ISHH. First we sequenced the plasmid to confirm the annotation. Then, the plasmids were PCR-amplified using either T7 and T3 primers or a gene-specific primer sequence with the T7 or T3 recognition sequence on the 5' end. See Table 2 for PCR primer designs, lengths, and encompassing regions for these clones. The PCR products were used to prepare both the sense and the antisense probes ranging in size from 500–650 bp. Hybridization of the sense probes was performed as negative control. Riboprobe synthesis was performed using 30–40 ng of PCR product, 50 μCi of [-35S]-uridine 5'-triphosphate (PerkinElmer Life Sciences, Inc., Boston, MA), and 10 mM dithiothreitol along with the reagents in the MAXIscript in vitro transcription kit (Ambion, Inc., Austin, TX). Serial 10-μm brain sections were cut in a cryostat, placed onto poly-L-lysine-coated slides (Fisher Scientific Company, Newark, DE), dried on a slide warmer for 10–30 min at 37 C, and stored at –80 C. Before hybridization, the sections were fixed in 4% formaldehyde for 10 min at room temperature, rinsed once and washed twice for 5 min in 1x PBS, put into 0.1 M triethanolamine-HCl (pH 8.0) containing 0.25% acetic anhydride for 10min at room temperature, rinsed with 2x SSC buffer, transferred through graded ethanol (75–100%), and air-dried. Hybridization was carried out in 80 μl hybridization solution (20 mM Tris-Cl, pH 7.4; 1 mM EDTA, pH 8.0; 300 mM NaCl; 50% formamide; 10% dextran sulfate; 1x Denhardt’s solution; 100 μg/ml salmon sperm DNA; 250 μg/ml yeast total RNA; 250 μg/ml yeast tRNA; 0.0625% SDS; 0.0625% sodium thiosulfate) containing 106 cpm denatured S35-labeled riboprobe. After an overnight incubation at 55 C, the sections were washed 4 times in 4x SSC, incubated in TNE buffer [10 mM Tris-Cl, pH 8.0; 0.5 M NaCl; 0.25 mM EDTA, pH8.0] containing 20 μg/ml ribonuclease A, for 30 min at 37 C, and then washed twice in 2x SSC and twice in 0.1x SSC at 65 C. The sections were rinsed in graded ethanol solutions and then air-dried. Finally, the sections were apposed to a low-energy storage phosphor screen (Amersham Biosciences) for 1–14 d and developed using a phosphor imager (Storm 860, Amersham Biosciences). To evaluate the levels of mRNA or hn RNA in the SONs (42), the average densities and unit areas per SON of phosphor screen were measured in the sections from each rat bilaterally, using the Image Quant software version 5.2 (Amersham Biosciences). Statistical significance of differences between groups was determined by one-way ANOVA followed by Fisher’s protected least-significant-difference test or Student’s test. Differences between groups were considered statistically significant at P < 0.05. Experiments were repeated on four animals, and results are expressed in mean ± SEM.
TABLE 2. Primer design and sequence information for the riboprobes used in the ISHH analysis
Results
Physiological treatments and the status of the animals
Table 1 shows the physiological effects of the experimental treatments on the rats studied. As expected, there was a significant increase in plasma osmolality and sodium concentration in the hyperosmolar rats and a decrease in the plasma osmolality and sodium concentration in the hypoosmolar rats. Both the hyperosmolar and hypoosmolar rats showed significant, but equivalent, decreases in body weight. There were no significant differences in body weight, plasma osmolality, or sodium concentration between the normoosmolar controls and the dDAVP-infused normoosmolar rats.
VP transcription levels after osmotic perturbation
We used an intronic VP probe for ISHH to measure hn VP RNA as an index of the transcription of VP in the SON (42) under the four conditions shown in Table 1. Figure 1 compares the effect of hyperosmolality (Fig. 1B), dDAVP treatment without hypoosmolality (Fig. 1C), and dDAVP treatment with hypoosmolality (Fig. 1D) to the control VP hn RNA expression (Fig. 1A) in the rat SON. Quantitative analysis of the hn VP RNA levels showed a 238 ± 9.9% increase in VP hn RNA in the hyperosmolar rats, a fall to 20 ± 6.1% in the hypoosmolar rats, and no significant change in the dDAVP-treated normoosmolar rats compared with control animals (Fig. 2). Thus, our physiological treatments affected VP expression just as one might have expected based on earlier reports (22, 42, 43).
FIG. 1. ISHH images illustrating the expression level of hn VP RNA in (A) control, (B) hyperosmolar, (C) dDAVP-treated, and (D) hypoosmolar rats. Note the prominent changes of expression in the SON under hyperosmolar (B) and hypoosmolar (D) conditions. Arrow in A, SON; arrowhead in A, suprachiasmatic nucleus (SCN).
FIG. 2. Quantitative ISHH analysis of the levels of hn VP RNA of control, hyperosmolar, dDAVP-treated, and hypoosmolar rats using ISHH intronic VP riboprobes (see Materials and Methods). Average values from four rats are shown as a percent of the controls. Statistical significance of difference between groups was calculated by one-way ANOVA followed by Fisher’s protected least-significant-difference test. *, P < 0.05 compared with the control rat hn VP RNA. Note the large increase and decrease of transcription under hyperosmolar and hypoosmolar conditions, respectively, and no significant change in the dDAVP-treated condition.
Microarray analysis
Our principal focus was to identify genes that are altered in expression in the rat SON after sustained hypoosmolality. The SONs from the control, dDAVP-treated, and hypoosmolar rats were laser microdissected, as described in Materials and Methods. Fluorescent probes generated from the amplified hypothalamic reference and laser-microdissected SON RNAs were hybridized on a microarray containing 35,319 cDNAs. The SON probes were labeled with Cy-5 (assigned a red fluorescence signal when the image was processed), and the hypothalamus reference probe was labeled with Cy-3 (assigned a green fluorescence signal when the image was processed). The control SON and hypothalamic reference probes both had high occupancy rates on the array (Fig. 3A). The rat VP and OT spots, which were added to the array, gave clear red signals confirming the preferential expression of these two genes in the SON vs. the whole hypothalamus (Fig. 3A, arrows). Ratios of gene expression levels (expression ratio) between samples can be calculated and used to detect sample-to-sample differences for a given gene in a microarray analysis (38, 39). The expression ratio that we used in this study is the normalized signal intensity for a particular gene in the SON sample, divided by the normalized signal intensity in the hypothalamic reference sample (26). The calculated expression ratio (SON/hypothalamic intensity ratio) of the VP gene spot in the control SON, as expected, was very high (44.0 ± 5.2). In the hypoosmolar rats, it decreased to 20% of the control values (Fig. 3B), which was roughly comparable with the extent of inhibition of hn RNA expression observed in the ISHH analysis (Fig. 2). The change in the VP expression ratio in the dDAVP-treated group was not significantly different from the controls, thereby confirming the ISHH results shown in Figs. 1 and 2.
We also performed a MDS analysis, which represents the correlation of all the data points between both the replicates in the same treatment group and different treatment groups in terms of their position in three-dimensional Euclidian spaces (40). The MDS analysis (Fig. 4) showed a good correlation between replicates in the same treatment group, with each of the treatment groups falling into a significant well-defined cluster. As expected, the control and hypoosmolar groups fell into two separate clusters, which are far apart from each other. Surprisingly, the dDAVP-treated group, which was similar in plasma osmolality (Table 1) and VP hn RNA expression level (Fig. 2) to the control group, fell into a distinct cluster residing in between that of the control and hypoosmolar groups, suggesting that there was a significant pharmacological effect of the dDAVP on gene expression in the SON (see Discussion). Overall, the MDS data show that the expression ratio data derived from the arrays are highly reproducible within the same treatment groups.
FIG. 4. MDS of control (black closed circle), dDAVP-treated (white closed circle), and hypoosmolar (striped circle) array data analyzed in three-dimensional Euclidean space (see data analysis in Materials and Methods). Each circle represents all 36,000 genes in an individual array, and the three-dimensional distance between the groups of arrays shows that they represent distinct groups (see text).
Validation of microarray data by quantitative ISHH analysis of selected genes
Figure 5 shows examples of quantitative ISHH analyses for four selected genes (see also Table 3) that were found, by the microarray analysis, to undergo significant changes in gene expression during hyponatremia. Sections from the SON region of the hypothalamus were taken from rats exposed to the three conditions that we used in the microarray experiments as well as from hyperosmolar rats (see Materials and Methods). Table 3 summarizes the entire set of comparisons between the microarray and ISHH data shown for genes with expression ratios ranging from 0.6–44. The ISHH results for all of the genes evaluated were consistent with the changes that were observed on the microarrays in the hypoosmolar condition. The data in Table 3 also shows ISHH data for these genes in the SON under hyperosmolar conditions (see Table 1), all of which underwent prominent up-regulation in the hyperosmolar state (Fig. 5, A–C, and Table 3), as might be expected. Interestingly, the LIM-domain-only (LMO)4 gene, which was up-regulated in the hypoosmolar condition, was also up-regulated in the hyperosmolar rat SON in the ISHH analysis (Fig. 5D, Table 3), and this was observed by both microarray and ISHH analysis. None of the genes shown in Table 3 significantly changed in expression in the dDAVP-treated normoosmolar rat SON vs. the control SON in the array analysis (data not shown). The changes in gene expression in hypoosmolar rats, based on data from the ISHH and the array studies, were highly correlated (r = 0.945), whereas the same changes in the dDAVP-treated normoosmolar rats were poorly correlated (r = 0.464). This suggests that the changes in gene expression identified during hypoosmolar conditions are not due to the dDAVP, which was also present in the hypoosmolar rats to produce the antidiuresis necessary to maintain the experimental hypoosmolality.
FIG. 5. Quantitative ISHH data showing changes in mRNA levels in the SON in response to hyperosmolar and hypoosmolar conditions and dDAVP treatments. The mRNA levels for: (A) C1q (C1q domain containing 1), (B) rho GDI (rho, GDI ?), (C) PIPPIN (PIPPIN cold shock protein), and (D) Lmo4 (Lim-only 4) mRNA are shown in control (white bar), hyperosmolar (black bar), dDAVP-treated (light gray bar), and hypoosmolar (dark gray bar) conditions. Statistical significance of difference between groups was calculated by one-way ANOVA followed by the Student’s test. *, P < 0.05 compared with the control rat mRNA. Average values are shown as a percent of the controls. Bars, Means ± SEM from four rats.
TABLE 3. Summary of ISHH data and its comparison with array data
Specific gene expression changes during hyponatremia
ANOVA was performed on all of the genes that met our quality criteria (see Materials and Methods), and P < 0.05 was taken to reflect statistically significant changes. In total, there were 4959 transcripts in the SON that significantly differed between the control and hypoosmolar rats. Of these, 2169 genes had control>hypoosmolar expression; and 2790 genes, including the previously reported glucocorticoid receptor gene, had control
TABLE 4. Preferentially expressed genes in the SON that are down-regulated more than 50% in hypoosmolar as compared with normoosmolar control rats
TABLE 5. Preferentially expressed genes in the SON that are up-regulated more than 2-fold in hypoosomolar as compared with normoosmolar control rats
Tables 4 and 5 list a subset of the 1564 genes that met both of the above criteria, i.e. they changed their expression by 2-fold, and are also preferentially expressed (i.e. have expression ratios 3.4) in the SON. These include the tyrosine hydroxylase mRNA, which fell more in response to hypoosmolality than any other transcript that is preferentially expressed in the SON (Table 4). The C1q domain containing 1, rho GDP dissociation inhibitor (GDI) ?, and encephalopsin genes decreased in expression in the hypoosmolar group as much as the VP gene did. Of the genes up-regulated more than 2-fold (Table 5), half were unclassifiable expressed sequence tags (ESTs), or annotated genes of unknown function, such as Murr 2 and nucleosome assembly protein-like 5. Superoxide dismutase 1, which breaks down reactive oxygen species formed in excess in hypermetabolic states (44), showed a 333% increase in the hypoosmolar group compared with the control. The functional annotation of the genes in Tables 4 and 5 is also shown, as a percentage of the total, in a pie-chart format as Supplemental Fig. 1S, A and B, respectively. Genes that significantly differed more than 2-fold between the hypoosmolar and control groups, but showed expression ratios less than 3.4, are shown in the Supplemental Tables 1S and 2S for 593 down-regulated and 812 up-regulated genes, respectively.
Transcription/translation-related genes modified in expression during hyponatremia
We were especially interested in identifying genes that might regulate transcription and translation in the MCNs of hyponatremic animals, so we specifically searched for genes that were annotated as transcription/translation-related genes using either the Gene Ontology program (45) (see website; http://cgap.nci.nih.gov/Genes/GOBrowser), or directly from the scientific literature. Table 6 lists 15 transcription/translation-related genes that were down-regulated more than 2-fold in hypoosmolar vs. control rats. PIPPIN, an RNA binding protein that functions in protein translation (46, 47); and putative homeodomain transcription factor, two genes which were not previously known to be expressed in the SON (48, 49); and c-fos, a marker of neuronal activity, were the most down-regulated of the transcription/translation-related genes in the hypoosmolar group compared with the controls (Table 6). Table 7 lists 29 transcription/translation-related genes that were up-regulated more than 2-fold in the hypoosmolar rats. Interestingly, there were many more transcription/translation-related genes that were up-regulated between 2-fold and 3-fold under hypoosmolar conditions compared with down-regulated genes.
TABLE 6. Transcription factor and nuclear protein genes that decrease in expression more than 2-fold under hypoosmolar conditions
TABLE 7. Transcription factor and nuclear protein genes that increase in expression more than 2-fold under hypoosmolar conditions
Discussion
Our goal in this study was to identify genes in the SON whose expression was altered by hypoosmolar conditions. Several previously detected, as well as novel, genes in the SON that were up-regulated and down-regulated during hypoosmolality were identified (see Tables 4–7). Among these genes, VP, OT (9, 10, 11, 12), and tyrosine hydroxylase (50, 51) were previously known to be present and osmotically regulated in the SON. This is the first report showing that tyrosine hydroxylase expression is down-regulated during hypoosmolality. Most of the other genes shown in Tables 4–7 were not previously known to be expressed in the SON.
The hypoosmolar rat model
The hypoosmolar condition in this model was induced by an infusion of the VP V2 receptor agonist dDAVP in association with water loading by a liquid diet. Therefore, in this study, we employed a second control consisting of an animal that was infused with the same amount of dDAVP (dDAVP-treated) as the hypoosmolar animals but was fed solid chow. These non-water-loaded rats remained normoosmolar despite the dDAVP infusion (28). This control allowed us to look for genes that responded solely to the infusion of dDAVP. The MDS analysis (Fig. 4) shows that each of our treatment groups fell into independent defined clusters. This suggests that the dDAVP treatment itself did influence gene expression in the SON. Throughout this study, when we identified genes in the SON that changed between the control and the hypoosmolar conditions, we also determined whether these genes significantly changed between the control and the dDAVP-treated normoosmolar conditions. We found that virtually none of these genes overlapped. Because dDAVP does not appreciably cross the blood brain barrier (52, 53), and the V2 receptor is not present in the SON (54, 55), these data suggest the possibility of an indirect action of the dDAVP from the periphery. In any case, all of the changes observed were relatively small, and we did not observe a statistically significant change between the control and the dDAVP-treated normoosmolar condition for VP transcription (Fig. 2). For the novel genes we analyzed in this study, virtually all of the genes that failed to show significant changes between the control and the dDAVP treatment on the array gave similar results in the ISHH analysis.
To confirm that the physiological conditions we used succeeded in altering VP gene transcription in the SON, we first performed ISHH using an exonic VP probe. VP mRNA showed a 166% increase in the hyperosmolar rat SON, a 59% decrease in the hypoosmolar rat SON, and no significant change in the dDAVP-treated normoosmolar rat SONs in comparison with control SONs (data not shown). A more direct estimate of VP gene transcription was made by using an intronic probe for hn VP RNA, which is unaffected by cytoplasmic mRNA degradation and turnover (42). The resulting data are shown in Figs. 1 and 2, and illustrate that the experimental conditions used appropriately altered VP transcription.
SON genes regulated by osmolality
In a recent microarray study (13), change in gene expression during chronic dehydration was used as a criterion to identify functionally interesting genes in the SON. Using hand-dissection of the SON and an array containing 1152 gene sequences, nine genes regulated by dehydration were identified. Four of these genes were also represented on our DNA array. Of these, only IL-6 (shown in Supplemental Table 1S) had a greater-than-2-fold decrease in expression during sustained hypoosmolality. The other three genes, eukaryotic translation initiation factor 5A, showed significant changes but did not meet our criterion of more than 2-fold change; protein kinase-AMP-activated, ?2 noncatalytic subunit, and PI-3-kinase-related kinase SMG-1 did not show significant changes between the control and hypoosmolar rats.
We performed ISHH on several of the genes that were identified as having very high expression ratios, all of which were also robustly functionally regulated (Table 3). Our false-positive rates were 0% for criterion 1 and 20% for criterion 2. Of particular interest are C1q domain containing 1, rho GDI ?, and encephalopsin because of their very large changes in gene expression in response to osmotic perturbations in both directions. All of these genes decreased in expression in the SON in the hypoosmolar state. C1q domain containing 1 (also known as EEG-1) was recently identified as a novel growth-related gene involved in hematopoetic differentiation (56). The fact that this gene’s expression is suppressed in the hypoosmolar condition suggests that it may also be involved in regulation of the VP and/or OT MCNs. The rho GTI ? rho GDI regulates the GTP-bound and GDP-bound state cycle of rho GTP-binding protein by decreasing the rate of dissociation from rho GTPases, which play important roles in neuronal morphogenesis (57). Previous results from our laboratory showed that MCNs dramatically adjust their cell volumes during both hyper- and hypoosmolar conditions (24). It is possible that the rho GDI may be involved in these morphological transformations.
Encephalopsin (also called Panopsin) is a member of the rhodopsin/G protein-coupled receptor gene superfamily. It is specifically expressed in the mammalian brain (58, 59). In this study, we used the rat genomic sequence that corresponded to the region (3'UTR sequence of the mouse encephalopsin) spotted on the array to produce a probe for ISHH. The ISHH showed a strong hybridization in the SON, paraventricular nucleus, and subfornical region in the rat brain (data not shown), which differed from a previous ISHH study on mouse encephalopsin. This difference could be due to an unknown splice variant in this gene. In our study, both the SON and the subfornical region showed a prominent increase and decrease in expression during the hyperosmolar and hypoosmolar states.
Genes involved in transcriptional regulation during sustained hypoosmolality that underwent 2-fold or greater changes are shown in Tables 6 and 7. In Table 3, we show the results from both ISHH and array assays for PIPPIN and putative homeodomain transcription factor (PHTF1). PIPPIN is a brain-specific RNA binding protein in the rat, which controls the recruitment of mRNA to the translational machinery (46, 47). PHTF1 is a putative homeobox gene that is well conserved not only in vertebrates but also in Drosophila (48, 49). Although this gene is ubiquitously expressed in the brain, there is a possibility that it contributes to the transcriptional regulation of the VP and/or OT genes, because no changes were observed in other regions of the brain under hyper- and hypoosmolar conditions. Calreticulin is a multifunctional protein that acts as a major Ca binding protein in the lumen of the endoplasmic reticulum. It is also located in the nucleus, interacts with DNA binding domains of estrogen receptor ?, inhibits transcriptional activities (60), and is able to act as a modulator of gene transcription. The decrease of the calreticulin mRNA expression in the SON during hypoosmolar conditions (Table 4) may be related to the reported increase in ER? under these conditions (21).
Another transfactor of interest is the LMO-4 gene, a novel member of the LMO subfamily of LIM domain containing transcription factors (61). It dramatically increased in expression under hypoosmolar conditions (Tables 3 and 7). The reported functions of this gene are the inhibition of differentiation in normal cells in the tumoriogenesis of breast cancers and T cell leukemia by interacting with DNA binding transcription factors or cofactors (62, 63), and also the inhibition of neuritogenesis in neuroblastoma cells (64). In a recent study, target disruption of this gene in mice caused a defect in the neural tube development (65, 66). The ISHH results of LMO-4 shown in Fig. 5 confirmed the array results showing up-regulation of expression in the hypoosmolar condition. Interestingly, LMO-4 is barely expressed in the SON in control and dDAVP-treated rats, but is substantially up-regulated in both hyper- and hypoosmolar animals, in contrast to most other genes, which showed a pattern of opposite regulation during these disparate physiological conditions. One of the functions of LIM domain is to mediate protein-protein interaction, which may have either positive or negative effects on transcription, depending on the counterpart with which it reacts (67, 68). Further studies should be directed to find the transcription factors and cofactors interacting with the LMO-4 gene in the SON and to determine the specific transcriptional regulation mechanism.
Three genes with prominent preferential expression in the SON were borderline, with respect to meeting the criterion of a greater-than-2-fold change in gene expression under hypoosmolar conditions on the array. These are EST similar to FLJ20037(69), zinc finger protein 312, and guanine nucleotide binding protein stimulating (previously described in Ref.18), and each underwent significant changes in expression in both hypoosmolar rats when evaluated by ISHH analysis (Table 7). Zinc finger protein 312 (also known as forebrain embryonic zinc finger, Fez), containing six C2H2 zinc fingers, is a highly conserved gene (70, 71, 72) and is of particular interest. This gene had the highest expression ratio among all the transcription factors expressed in the SON found on the array. Its only reported function, to date, relates to the development of the forebrain (72, 73), but its preferential expression in the SON suggests that further study of this gene in relation to VP and OT gene expression in the adult is warranted. Both zinc finger protein 312 (Fez) and LMO-4 gene are novel transfactors identified in the SON in this study, and they may also participate in regulating OT- and VP-gene expression in the SON, and other specific properties of the MCNs.
Conclusions
We found that hypoosmolality, known to be associated with a profound down-regulation of both OT and VP gene expression, was also accompanied by both up- and down-regulation of a large number of genes in the SON. A significant number of these genes were also regulated by hyperosmolality, suggesting that the changes observed were a result of true osmotic regulation rather than due to nonspecific effects, e.g. stress, or secondary treatment effects such as weight loss and others. Many previous studies have indicated that hypoosmolality inhibits both electrical activity (74) and peptide synthesis (11) in MCNs and, most remarkably, that the MCNs decrease both cellular and nuclear volume by 30–40% during sustained hypoosmolar conditions (24). The latter finding is consistent with the view that hypoosmolality produces a global decrease in transcriptional and translational activity in these neurons. Hence, our finding of decreases in expression of a large number of genes present on the array was expected. However, the finding that even more genes increased in expression under conditions of hypoosmolality was surprising. This finding that many genes are up-regulated in the SON during hypoosmolality raises the interesting possibility that these genes participate in the dramatic shut-off of peptide and structural protein synthesis in the SON, to maintain the MCNs in a quiescent state. The identification of a large number of transcription factor genes in the SON that are osmotically regulated (Tables 4–7) provides us with a group of candidate genes that might control OT and VP transcription, as well as other properties of the MCN phenotypes. The complex and global nature of the regulation of a cellular phenotype is not unprecedented. In a recent study, Odom et al. (75) reported that a member of the hepatocyte nuclear family of transcription factors functioned as a master regulator of global hepatocyte and pancreatic islet transcription and function. Another study, using microarrays, identified sets of known and novel genes that regulated the development of specific cellular phenotypes in the endocrine pancreas (76). It is also possible that there are sets of so-called master genes that control the global regulation of gene transcription in the MCNs during their adaptation to sustained osmotic perturbations. A general mechanism that could be involved in the global transcriptional activation and inactivation in the MCNs is chromatin remodeling. Posttranslational modification of core histones appears to be generally involved in regulating transcriptional activity (77, 78, 79), and one study has shown that chromatin remodeling occurs in the suprachiasmatic nucleus in response to a physiological stimulus in vivo (80). Future studies should be directed at the relationship of specific gene expression and chromatin remodeling in MCNs in the SON during their adaptation to sustained osmotic challenges.
Note Added in Proof
All of the unpublished, associated data from this study is accessible at the following web site: http://intramural.nimh.nih.gov/research/log/index2.html.
Acknowledgments
We thank Dr. Ying Tian (Georgetown University) for help with preparation of the animals; Dr. Eva Mezey, Ms. Sharon Key [National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH)], and Dr. W. Scott Young III (NIMH, NIH) for their help with ISHH; Dr. Yidong Chen (NHGRI, NIH) for his help with statistical analysis for microarray data; Catherine Campbell (NINDS, NIH) for her suggestions about microarray analysis; Mr. Raymond L. Fields (NINDS, NIH) for his technical assistance; and Mr. James W. Nagle and Ms. Debbie Kauffman (NINDS, DNA sequencing Facility) for DNA sequencing.
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Address all correspondence and requests for reprints to: Harold Gainer, Ph.D., Laboratory of Neurochemistry, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland 20892. E-mail: gainerh@ninds.nih.gov.
Abstract
Hypoosmolality produces a dramatic inhibition of vasopressin (VP) and oxytocin gene expression in the supraoptic nucleus (SON). This study examines the effect of sustained hypoosmolality on global gene expression in the oxytocin and VP magnocellular neurons of the hypothalamo-neurohypophysial system, to identify genes associated with the magnocellular neuron’s adaptation to this physiological condition. Using laser microdissection of the SON, T7-based linear amplification of its RNA, and a 35,319-element cDNA microarray, we compare gene expression profiles between SONs in normoosmolar (control), 1-desamino-[8-D-arginine]-VP-treated normoosmolar, and hypoosmolar rats. We found 4959 genes with statistically significant differences in expression between normosmolar control and the hypoosmolar SONs, with 1564 of these differing in expression by more than 2-fold. These genes serve a wide variety of functions, and most were up-regulated in gene expression in hypoosmolar compared with control SONs. Of these, 90 were preferentially expressed in the SON, and 44 coded for transcription-related factors, of which 15 genes were down-regulated and 29 genes were up-regulated in the hypoosmolar rat SONs. None of these transcription-related factor genes significantly changed in expression after sustained 1-desamino-[8-D-arginine]-VP-treatment alone, indicating that these changes were associated with the hypoosmolar state and not due solely to a decreased activity in the SON. Quantitative in situ hybridization histochemistry was selectively used to confirm and extend these microarray observations. These results indicate that the hypoosmolar state is accompanied by a global, but selective, increase in expression of a wide variety of regulatory genes in the SON.
Introduction
HYPONATREMIA IS THE most common clinical (1, 2) and exercise-induced (3, 4) systemic electrolyte disorder and is potentially life threatening. In most cases, hyponatremia is caused by inappropriate water retention, in which case, hypoosmolality of body fluids also occurs. The hypothalamo-neurohypophysial system (HNS) plays a fundamental role in the maintenance of body fluid and electrolyte homeostasis by secreting vasopressin (VP) and oxytocin (OT) (5, 6). VP and OT are neurohypophysial hormones that are synthesized in the supraoptic nucleus (SON) and paraventricular nucleus of the hypothalamus and transported to, stored in, and released from the posterior pituitary (7, 8). During chronic hyperosmolar conditions, VP and OT mRNA levels increase approximately 2-fold (9, 10) to keep up with the increased secretion of these hormones into the blood for antidiuretic and natriuretic functions. In contrast, during chronic hypoosmolar conditions, VP and OT mRNA levels in the HNS are decreased to 10–20% of those of normonatremic control animals (11, 12), and this down-regulation of VP synthesis is consistent with the osmotic inhibition of VP that results in maximum water diuresis. Although there have been many reports of changes in gene expression in the HNS during hyperosmolality (13, 14, 15, 16, 17, 18, 19, 20, 21, 22), there have been very few studies of gene regulation during hypoosmolar conditions (21, 23).
Several changes have been associated with hypoosmolality. One is down-regulation of the expression of multiple genes in the magnocellular neurons (MCNs) of the SON during periods of low synthesis and secretion of VP and OT (23, 24). The second is the up-regulation of expression of genes that might be involved in the active inhibition of VP and OT synthesis, storage, and secretion. To the best of our knowledge, the glucocorticoid receptor (25) and the estrogen receptor ? (21) are the only genes that have been shown to be up-regulated during chronic hypoosmolality. When we previously screened cDNA libraries for genes that were differentially expressed in the HNS during chronic hyperosmolality and hypoosmolality, we failed to detect any genes that were up-regulated in the hypoosmolar condition (23), but such screening methods are far from comprehensive. Therefore, we decided to employ DNA microarrays and laser-microdissected SON samples (26) to look for changes in gene expression induced by hypoosmolality. Using this approach, we identified 4959 genes with statistically significant differences in expression between normosmolar control and hypoosmolar SONs, with 1564 of these differing in expression by more than 2-fold. These genes serve a wide variety of functions, and most were up-regulated in gene expression in hypoosmolar compared with control SONs. Of these, 90 were preferentially expressed in the SON, and 44 coded for transcription-related factors, of which 15 genes were down-regulated and 29 genes were up-regulated in the hypoosmolar rat SONs. These results indicate that the hypoosmolar state is accompanied by a global, but selective, increase in expression of a wide variety of regulatory genes, which could be involved in the MCN's adaptation to sustained hypoosmolality.
Materials and Methods
Animals
Adult male Sprague Dawley rats, weighing 260–320 g, were housed individually in wire mesh cages in a temperature-controlled room (21–23 C) with lights on from 0700–1900 h. All procedures were carried out in accordance with National Institutes of Health (NIH) guidelines on the care and use of animals and an animal study protocol approved by the Georgetown University Animal Use and Care Committee.
Induction of hyper- and hypoosmolality
To induce hyponatremia, male rats were given 1-desamino-[8-D-arginine]-VP (dDAVP; Aventis Pharmaceuticals, Bridgewater, NJ) at a rate of 5 ng/h using osmotic minipumps (Alzet model 2002; Alza, Palo Alto, CA) implanted sc, and by feeding the rats a dilute preparation (1.0 kcal/ml) of liquid formula (AIN76; Bioserv, Frenchtown, NJ) for 7 d (27, 28). Rats fed with pelleted AIN-76 and allowed access to tap water ad libitum were used as normoosmolar controls. Rats infused with dDAVP at the same rate as the hypoosmolar rats, but fed AIN76 pelleted chow and allowed access to tap water ad libitum, were used as dDAVP-treated normoosmolar rats. To induce hypernatremia, rats were given 2% NaCl solution ad libitum as their only drinking fluid for 7d. The body weights (g), plasma Na+ levels (mM), and plasma osmolalities (mosmol/kg H2O) were measured in blood samples drawn via jugular puncture from each animal after 7 d of treatment and are shown in Table 1.
TABLE 1. Physiological measurements of control, hyperosmolar, dDAVP-treated, and hypoosmolar rats
Tissue isolation, RNA processing, and microarray analysis
In this study, we used laser microdissection (LMD) and microarray techniques described previously (26), with several modifications. These procedures are described below.
Tissues
LMD of the SON.
All the rats were killed starting at 0900 h, by decapitation, and their brains were quickly removed, immediately frozen on dry ice, and stored at –80 C until further processing occurred. The tissue was placed in a cryostat for 10 min at the cutting temperature (–18 C) for temperature equilibration, and 7-μm-thick coronal sections were cut at the SON level, placed on and thawed onto membrane-coated glass slides (glass foil PEN slides; Leica Microsystems Inc., Bannockburn, IL), and immediately placed in a slide box embedded in dry ice. The sections were stored at –80 C until they were used. Before LMD, the tissue was fixed and dehydrated with ethanol as described elsewhere (29). Briefly, the slides were thawed for 45 sec in 75% ethanol and further dehydrated by sequential immersion in 95%, 100%, and again with 100% ethanol for 5 sec each. Then, the slides were cleared twice with xylene for 2 min and dried in a vacuum chamber. All of the solutions used for fixation were prepared with diethylpyrocarbonate water. LMD was performed under dark-field illumination, using a Leica Laser Microdissection Microscope (Leica Microsystems Inc.) (30), immediately after dehydration of the slides. Brains from three animals per each treatment group were individually microdissected. The dissected SONs were collected into 0.5-ml tubes with 70 μl lysis buffer containing guanidine thiocyanate and 0.5 μl ?-mercaptoethanol.
Collection of hypothalamic reference tissue.
Blocks of hypothalamic tissue were obtained from 10 control male rats. After decapitation of the rats at 0900 h, the brains were removed from the skull and placed ventral-side-up on a rubber stopper. Coronal cuts were made rostral to the optic chiasm and caudal to the cerebral peduncle. The hypothalamus was removed from the resulting brain slices by making a cut at the top of the third ventricle and cuts at the lateral margins of the optic tracts. The tissue samples were frozen in liquid nitrogen and stored at –80 C until they were extracted.
RNA extraction
Laser-microdissected SON tissue.
RNA isolation was preformed according to the manufacturer’s protocol, with the Absolutely RNA Microprep Kit (Stratagene, La Jolla, CA) (31). After extraction, total RNA was measured using a Ribogreen RNA quantitation kit (Molecular Probes, Inc., Eugene, OR). The samples and the standard RNAs were excited at 485 nm, and the fluorescence emission intensity was measured at 535 nm using a fluorescence microplate reader (VICTOR 2 1420 Multilabel counter; Wallac Oy, Turku, Finland). Fluorescence emission intensity of the samples was then plotted against an RNA standard curve. The average total RNA per animal (bilateral SON) was 193.2 ng, 113.4 ng, and 90.6 ng for control, dDAVP-treated, and hypoosmolar animals, respectively. Equal amounts of total RNA were pooled from three rats in each treatment group, and 150 ng per group was used as the template for T7-based linear RNA amplification.
Reference hypothalamic tissue.
RNA extraction of the dissected hypothalamic blocks was done with Trizol (Life Technologies, Gaithersburg, MD) (32) followed by a DNaseI (GenHunter, Nashville, TN) treatment. The product was cleaned up using an Absolutely RNA Microprep Kit (Stratagene). Approximately 200 μg of total RNA were obtained from each block, and 5 μg RNA from each of 10 animals was pooled together, and 150 ng of the pool was amplified using T7-based linear RNA amplification. Thus, we used 150 ng of the pooled hypothalamic tissue RNA and the SON RNA in each reaction to obtain consistent amplification efficiency among all the samples.
T7-based RNA amplification
RNA amplification was performed according to the manufacturer’s protocol, using a RiboAmp RNA Amplification Kit (Arcturus, Mountain View, CA). The principles of this amplification method have been described previously (33). The first round of amplification was performed on 150 ng total RNA from the pooled hypothalamic reference and the LMD SON material. For the second round, 500 ng of antisense RNA (aRNA) was collected from each of the samples and used as template. The total amount of the RNA produced was measured with a spectrophometer (Ultrospec 2100 pro UV/Visible spectrophometer; Amersham Biosciences, Piscataway, NJ). The total amounts of RNA produced in the first-round amplification were 10.6, 6.6, 4.0, and 3 μg reference hypothalamic RNA, normoosmolar control SON, dDAVP-treated SON, and hypoosmolar SON, respectively. The total amounts of aRNAs from the second round amplifications were 138, 198, 168, and 180 μg for the hypothalamic reference, control SON, dDAVP-treated SON, and hypoosmolar SON, respectively. The 260/280 ratios for the RNA samples after the second round ranged from 2.2–2.4, and the spectra from OD230 to OD320 were those expected for pure RNA. The length of the aRNAs ranged from 300-1300 bp after the first round and from 300–700 bp after the second round of amplification.
Microarray fabrication
Mouse cDNA microarrays were printed on poly-L-lysine-coated slides. The cDNA libraries that were used to print the array were provided by Dr. Bento Soares, University of Iowa (http://genome.uiowa.edu/projects/BMAP/) (adult whole-brain cDNA library) and Dr. Minoru Ko, National Institute on Aging, NIH (http://lgsun.grc.nia.nih.gov/cDNA/cDNA.html) (embryonic brain cDNA library). Plasmids were extracted from the bacteria using QiaPrep Turbo kits (Qiagen, Valencia, CA) and a BioRobot 8000 (Qiagen). The cDNA inserts were amplified with modified M13 primers (M13F 5'-GTTGTAAAACGACGGCCAGTG-3' and M13R 5'-CACACAGGAAACAGCTATG-3') and purified with MultiScreen PCR plates (Millipore, Bedford, MA). The PCR products were diluted in 50% dimethylsulfoxide to an average concentration of 200 ng/μl. These products (5 μl each) were transferred to 384-well plates (Genetix, St. James, NY) and printed using an OmniGrid arrayer (GeneMachines, San Carlos, CA). The printed slides were aged for a week and then postprocessed before hybridization. Detailed descriptions of these procedures can be viewed at http://cmgm.stanford.edu/pbrown/mguide/index.html. To validate the dissection of the SON and to confirm the response of the SON neurons to the physiological manipulations studied, we added rat VP and OT cDNAs to the arrays.
Microarray properties
The 35,319 elements printed include 11,720 product-defined clones and 23,599 product undefined clones. The number of unigene clusters represented is 26,000. In a preliminary study, we found that cross-hybridization of mouse- and rat hypothalamic RNAs on this array is 94%, indicating that it is appropriate for gene expression analysis of the rat hypothalamus (26).
Probe labeling with amine-modified random primers
Probes were synthesized from 2 μg amplified RNA. The SON was labeled with Cy-5, and the reference (whole hypothalamus) was labeled with Cy-3. The labeling was performed as described previously (34, 35) with minor modifications. Briefly, the RNA was combined with 4 μg amine-modified random primer (amine-C6-TNNNNNN; Sigma Genosys, The Woodlands, TX) and 5 U ribonuclease inhibitor (RNAsin; Promega, Madison, WI) in a total vol of 18.5 μl, incubated at 70 C for 10 min, and chilled on ice for 10 min. The primer/RNA solution was then added to 6 μl of 5x first-strand buffer (Life Technologies), 0.6 μl of 50x aminoallyl deoxy (d) UTP/dNTPs [25 mM dATP, dGTP, and dCTP; 15 mM dTTP; and 10 mM aminoallyl dUTP (Sigma, St. Louis, MO)], 3 μl 0.1-M dithiothreitol, and 2 μl SuperScript II reverse transcriptase (Life Technologies) and incubated at 42 C for 2 h. The reaction was terminated with 10 μl 0.5-M EDTA, and the RNA was hydrolyzed with 10 μl 1-N NaOH at 65 C for 30 min. The solution was neutralized with 10 μl 1-M HCl, and a MinElute PCR purification kit (Qiagen) was used to purify the products. The samples were concentrated to 9 μl in a vacuum centrifuge, and then 1 μl 1-M sodium bicarbonate (pH 9.3), was added to the cDNA solution, followed by 4.5 μl dye solution [NHS-ester Cy3 or Cy5 (Amersham Biosciences), 62.5 μg/μl in dimethylsulfoxide]. The resulting solution was mixed, by pipeting it up and down several times, and incubated at room temperature for 1 h in the dark. The labeling reaction was stopped with 4.5 μl 4-M hydroxylamine hydrochloride (Sigma). The contents of the tube were mixed, briefly centrifuged, and incubated for 30 min at room temperature in the dark. The probes were purified using a QIAquick PCR purification kit (Qiagen). The products were concentrated to 17 μl in a vacuum centrifuge. Then, 4.5 μl of 20x saline sodium citrate (SSC), 2 μl of poly (A) (A60mer, 10 mg/ml; Sigma Genosys), 1 μl human Cot-1 DNA (10 mg/ml; Life Technologies), and 1 μl yeast tRNA (4 mg/ml; Life Technologies) were added, and the probes were denatured at 98 C for 2 min. The arrays were prehybridized in 5x SSC, 0.1% sodium dodecyl sulfate (SDS), 1% BSA solution at 42 C for 1 h, washed in H2O for 2 min, rinsed in isopropanol, and centrifuged at 800 rpm for 2 min to dry them. The denatured probes were combined with 20 μl of 2x hybridization buffer (50% formamide, 10x SSC, 0.2% SDS). The hybridization solution was pipeted onto the array, cover slips were applied, and the slides were placed in a hybridization chamber (Corning, Corning, NY). They were incubated in a 42-C water bath for 16 h, the cover slips were removed, and the arrays were washed in 2x SSC plus 0.1% SDS, in 0.5x SSC plus 0.01% SDS, and 0.06x SSC for 5 min each. The slides were centrifuged at 800 rpm for 2 min to dry them before scanning. Dye swapping was not performed in our analysis because we previously established that the modified indirect labeling method used here with amine-modified random primer did not have dye bias (34). In addition, we performed comparisons by hybridizing each of our treatment group samples against a reference sample, and we analyzed the fold changes of the expression ratio for each gene. We always used the same dyes on the reference and treatment groups, consistent with reference-designed array studies where a reverse labeling, to exclude dye bias, is not necessary (36, 37).
Array scanning and data analysis
The arrays were scanned with a GenePix 4000A scanner (Axon, Foster City, CA) at 10-μm resolution. The photomultiplier tube (PMT) voltage settings were varied to obtain the maximum signal intensities with less than 1% probe saturation. The color images were formed by assigning the SON intensity in red and the hypothalamic reference intensity in green (see Fig. 3). The resulting images were analyzed using IPLab (Scanalytics, Fairfax, VA) and ArraySuite (National Human Genome Research Institute, NIH, Bethesda, MD) software, and the ratios of the red over the green intensity for all targets were determined. Calibrated ratios were obtained by a normalization method based on the ratio statistics (38, 39). To determine the reliability of each ratio measurement, a set of quality indicators were used: 1) association of a sufficiently large numbers of pixels with the element; 2) flat local background; 3) uniform signal consistency within the target area; and 4) unsaturation of the majority of the signal pixels. Based on these indicators, a quality rank was calculated ranging from 1 to 0, and genes with quality rank scores less than 0.1 were excluded from our analysis. A detailed description of this procedure is provided elsewhere (38, 39). Also, genes with intensities lower than 250 [4 x (the average background + 3 SD)] of the arrays in this experiment) in the red (SON) channel were excluded from the analysis. The labeled control SON samples were hybridized in triplicate, and the labeled dDAVP-treated SON and hypoosmolar SON samples were hybridized in quadruplicate. In summary, we used three arrays for the control and four arrays each for the dDAVP-treated and sustained-hypoosmolar conditions. The control arrays were done in triplicate, and the dDAVP-treated and hypoosmolar were done in quadruplicate. Replicates are defined as hybridization replicates. We used three animals per treatment, and the samples were pooled before amplification. Statistical analysis to compare the three experimental groups was performed by ANOVA using mAdb program (CIT/BMAS, NIH). A 95% confidence interval was used throughout the experiments to detect differentially expressed genes.
FIG. 3. Scanned image of a DNA array hybridized with Cy3- (shown as a green signal) or Cy5- (shown as a red signal) labeled cDNA probes, which were generated from amplified whole-rat hypothalamus reference and laser-microdissected rat SON RNA, respectively, is shown in A. The expression ratio data for the VP gene under various conditions is shown in B. In A, eight panels of a 48-panel array are shown, where two panels contain either the VP or the OT target cDNAs (arrows indicate the printed spot for the VP and OT genes.) The red signal indicates genes that are expressed at relatively greater levels in the SON compared with the total hypothalamus reference sample, and the green signal indicates genes that are expressed at relatively greater levels in the hypothalamus compared with the SON. Yellow indicates genes that are approximately equivalently expressed in both of the tissues. In B, VP gene expression ratios that were obtained from the array in the control, dDAVP-treated, or hypoosmolar conditions are shown. Data are shown as means ± SEM. **, P < 0.05 in an ANOVA analysis.
We used the method of multidimensional scaling (MDS) to display the overall similarities and differences among treatment groups in a three-dimensional Euclidean space. The positions of each group in the Euclidean space are determined in such a way that the Euclidean distances between groups corresponds as closely as possible to 1 minus the Pearson correlation coefficients between the logarithm of intensity ratios for the group (40). The MDS was preformed using the MATLAB software (The MathWorks, Inc., Natick, MA).
In situ hybridization histochemistry (ISHH)
In this study, we used a quantitative ISHH protocol, described elsewhere (41), with minor variations. The rat heteronuclear (hn) VP probe (kindly provided by Dr. Thomas Sherman, Georgetown University, Washington, D.C.) was a 735-bp fragment of intron 1 of the rat VP gene subcloned into pGEM-3 vector (Promega) (42). T7 and SP6 primers were used to PCR-amplify the fragment, and the resulting PCR product was used as a template for riboprobe synthesis. Some plasmids that contained selected expressed clones on the array were studied further by ISHH. First we sequenced the plasmid to confirm the annotation. Then, the plasmids were PCR-amplified using either T7 and T3 primers or a gene-specific primer sequence with the T7 or T3 recognition sequence on the 5' end. See Table 2 for PCR primer designs, lengths, and encompassing regions for these clones. The PCR products were used to prepare both the sense and the antisense probes ranging in size from 500–650 bp. Hybridization of the sense probes was performed as negative control. Riboprobe synthesis was performed using 30–40 ng of PCR product, 50 μCi of [-35S]-uridine 5'-triphosphate (PerkinElmer Life Sciences, Inc., Boston, MA), and 10 mM dithiothreitol along with the reagents in the MAXIscript in vitro transcription kit (Ambion, Inc., Austin, TX). Serial 10-μm brain sections were cut in a cryostat, placed onto poly-L-lysine-coated slides (Fisher Scientific Company, Newark, DE), dried on a slide warmer for 10–30 min at 37 C, and stored at –80 C. Before hybridization, the sections were fixed in 4% formaldehyde for 10 min at room temperature, rinsed once and washed twice for 5 min in 1x PBS, put into 0.1 M triethanolamine-HCl (pH 8.0) containing 0.25% acetic anhydride for 10min at room temperature, rinsed with 2x SSC buffer, transferred through graded ethanol (75–100%), and air-dried. Hybridization was carried out in 80 μl hybridization solution (20 mM Tris-Cl, pH 7.4; 1 mM EDTA, pH 8.0; 300 mM NaCl; 50% formamide; 10% dextran sulfate; 1x Denhardt’s solution; 100 μg/ml salmon sperm DNA; 250 μg/ml yeast total RNA; 250 μg/ml yeast tRNA; 0.0625% SDS; 0.0625% sodium thiosulfate) containing 106 cpm denatured S35-labeled riboprobe. After an overnight incubation at 55 C, the sections were washed 4 times in 4x SSC, incubated in TNE buffer [10 mM Tris-Cl, pH 8.0; 0.5 M NaCl; 0.25 mM EDTA, pH8.0] containing 20 μg/ml ribonuclease A, for 30 min at 37 C, and then washed twice in 2x SSC and twice in 0.1x SSC at 65 C. The sections were rinsed in graded ethanol solutions and then air-dried. Finally, the sections were apposed to a low-energy storage phosphor screen (Amersham Biosciences) for 1–14 d and developed using a phosphor imager (Storm 860, Amersham Biosciences). To evaluate the levels of mRNA or hn RNA in the SONs (42), the average densities and unit areas per SON of phosphor screen were measured in the sections from each rat bilaterally, using the Image Quant software version 5.2 (Amersham Biosciences). Statistical significance of differences between groups was determined by one-way ANOVA followed by Fisher’s protected least-significant-difference test or Student’s test. Differences between groups were considered statistically significant at P < 0.05. Experiments were repeated on four animals, and results are expressed in mean ± SEM.
TABLE 2. Primer design and sequence information for the riboprobes used in the ISHH analysis
Results
Physiological treatments and the status of the animals
Table 1 shows the physiological effects of the experimental treatments on the rats studied. As expected, there was a significant increase in plasma osmolality and sodium concentration in the hyperosmolar rats and a decrease in the plasma osmolality and sodium concentration in the hypoosmolar rats. Both the hyperosmolar and hypoosmolar rats showed significant, but equivalent, decreases in body weight. There were no significant differences in body weight, plasma osmolality, or sodium concentration between the normoosmolar controls and the dDAVP-infused normoosmolar rats.
VP transcription levels after osmotic perturbation
We used an intronic VP probe for ISHH to measure hn VP RNA as an index of the transcription of VP in the SON (42) under the four conditions shown in Table 1. Figure 1 compares the effect of hyperosmolality (Fig. 1B), dDAVP treatment without hypoosmolality (Fig. 1C), and dDAVP treatment with hypoosmolality (Fig. 1D) to the control VP hn RNA expression (Fig. 1A) in the rat SON. Quantitative analysis of the hn VP RNA levels showed a 238 ± 9.9% increase in VP hn RNA in the hyperosmolar rats, a fall to 20 ± 6.1% in the hypoosmolar rats, and no significant change in the dDAVP-treated normoosmolar rats compared with control animals (Fig. 2). Thus, our physiological treatments affected VP expression just as one might have expected based on earlier reports (22, 42, 43).
FIG. 1. ISHH images illustrating the expression level of hn VP RNA in (A) control, (B) hyperosmolar, (C) dDAVP-treated, and (D) hypoosmolar rats. Note the prominent changes of expression in the SON under hyperosmolar (B) and hypoosmolar (D) conditions. Arrow in A, SON; arrowhead in A, suprachiasmatic nucleus (SCN).
FIG. 2. Quantitative ISHH analysis of the levels of hn VP RNA of control, hyperosmolar, dDAVP-treated, and hypoosmolar rats using ISHH intronic VP riboprobes (see Materials and Methods). Average values from four rats are shown as a percent of the controls. Statistical significance of difference between groups was calculated by one-way ANOVA followed by Fisher’s protected least-significant-difference test. *, P < 0.05 compared with the control rat hn VP RNA. Note the large increase and decrease of transcription under hyperosmolar and hypoosmolar conditions, respectively, and no significant change in the dDAVP-treated condition.
Microarray analysis
Our principal focus was to identify genes that are altered in expression in the rat SON after sustained hypoosmolality. The SONs from the control, dDAVP-treated, and hypoosmolar rats were laser microdissected, as described in Materials and Methods. Fluorescent probes generated from the amplified hypothalamic reference and laser-microdissected SON RNAs were hybridized on a microarray containing 35,319 cDNAs. The SON probes were labeled with Cy-5 (assigned a red fluorescence signal when the image was processed), and the hypothalamus reference probe was labeled with Cy-3 (assigned a green fluorescence signal when the image was processed). The control SON and hypothalamic reference probes both had high occupancy rates on the array (Fig. 3A). The rat VP and OT spots, which were added to the array, gave clear red signals confirming the preferential expression of these two genes in the SON vs. the whole hypothalamus (Fig. 3A, arrows). Ratios of gene expression levels (expression ratio) between samples can be calculated and used to detect sample-to-sample differences for a given gene in a microarray analysis (38, 39). The expression ratio that we used in this study is the normalized signal intensity for a particular gene in the SON sample, divided by the normalized signal intensity in the hypothalamic reference sample (26). The calculated expression ratio (SON/hypothalamic intensity ratio) of the VP gene spot in the control SON, as expected, was very high (44.0 ± 5.2). In the hypoosmolar rats, it decreased to 20% of the control values (Fig. 3B), which was roughly comparable with the extent of inhibition of hn RNA expression observed in the ISHH analysis (Fig. 2). The change in the VP expression ratio in the dDAVP-treated group was not significantly different from the controls, thereby confirming the ISHH results shown in Figs. 1 and 2.
We also performed a MDS analysis, which represents the correlation of all the data points between both the replicates in the same treatment group and different treatment groups in terms of their position in three-dimensional Euclidian spaces (40). The MDS analysis (Fig. 4) showed a good correlation between replicates in the same treatment group, with each of the treatment groups falling into a significant well-defined cluster. As expected, the control and hypoosmolar groups fell into two separate clusters, which are far apart from each other. Surprisingly, the dDAVP-treated group, which was similar in plasma osmolality (Table 1) and VP hn RNA expression level (Fig. 2) to the control group, fell into a distinct cluster residing in between that of the control and hypoosmolar groups, suggesting that there was a significant pharmacological effect of the dDAVP on gene expression in the SON (see Discussion). Overall, the MDS data show that the expression ratio data derived from the arrays are highly reproducible within the same treatment groups.
FIG. 4. MDS of control (black closed circle), dDAVP-treated (white closed circle), and hypoosmolar (striped circle) array data analyzed in three-dimensional Euclidean space (see data analysis in Materials and Methods). Each circle represents all 36,000 genes in an individual array, and the three-dimensional distance between the groups of arrays shows that they represent distinct groups (see text).
Validation of microarray data by quantitative ISHH analysis of selected genes
Figure 5 shows examples of quantitative ISHH analyses for four selected genes (see also Table 3) that were found, by the microarray analysis, to undergo significant changes in gene expression during hyponatremia. Sections from the SON region of the hypothalamus were taken from rats exposed to the three conditions that we used in the microarray experiments as well as from hyperosmolar rats (see Materials and Methods). Table 3 summarizes the entire set of comparisons between the microarray and ISHH data shown for genes with expression ratios ranging from 0.6–44. The ISHH results for all of the genes evaluated were consistent with the changes that were observed on the microarrays in the hypoosmolar condition. The data in Table 3 also shows ISHH data for these genes in the SON under hyperosmolar conditions (see Table 1), all of which underwent prominent up-regulation in the hyperosmolar state (Fig. 5, A–C, and Table 3), as might be expected. Interestingly, the LIM-domain-only (LMO)4 gene, which was up-regulated in the hypoosmolar condition, was also up-regulated in the hyperosmolar rat SON in the ISHH analysis (Fig. 5D, Table 3), and this was observed by both microarray and ISHH analysis. None of the genes shown in Table 3 significantly changed in expression in the dDAVP-treated normoosmolar rat SON vs. the control SON in the array analysis (data not shown). The changes in gene expression in hypoosmolar rats, based on data from the ISHH and the array studies, were highly correlated (r = 0.945), whereas the same changes in the dDAVP-treated normoosmolar rats were poorly correlated (r = 0.464). This suggests that the changes in gene expression identified during hypoosmolar conditions are not due to the dDAVP, which was also present in the hypoosmolar rats to produce the antidiuresis necessary to maintain the experimental hypoosmolality.
FIG. 5. Quantitative ISHH data showing changes in mRNA levels in the SON in response to hyperosmolar and hypoosmolar conditions and dDAVP treatments. The mRNA levels for: (A) C1q (C1q domain containing 1), (B) rho GDI (rho, GDI ?), (C) PIPPIN (PIPPIN cold shock protein), and (D) Lmo4 (Lim-only 4) mRNA are shown in control (white bar), hyperosmolar (black bar), dDAVP-treated (light gray bar), and hypoosmolar (dark gray bar) conditions. Statistical significance of difference between groups was calculated by one-way ANOVA followed by the Student’s test. *, P < 0.05 compared with the control rat mRNA. Average values are shown as a percent of the controls. Bars, Means ± SEM from four rats.
TABLE 3. Summary of ISHH data and its comparison with array data
Specific gene expression changes during hyponatremia
ANOVA was performed on all of the genes that met our quality criteria (see Materials and Methods), and P < 0.05 was taken to reflect statistically significant changes. In total, there were 4959 transcripts in the SON that significantly differed between the control and hypoosmolar rats. Of these, 2169 genes had control>hypoosmolar expression; and 2790 genes, including the previously reported glucocorticoid receptor gene, had control
TABLE 4. Preferentially expressed genes in the SON that are down-regulated more than 50% in hypoosmolar as compared with normoosmolar control rats
TABLE 5. Preferentially expressed genes in the SON that are up-regulated more than 2-fold in hypoosomolar as compared with normoosmolar control rats
Tables 4 and 5 list a subset of the 1564 genes that met both of the above criteria, i.e. they changed their expression by 2-fold, and are also preferentially expressed (i.e. have expression ratios 3.4) in the SON. These include the tyrosine hydroxylase mRNA, which fell more in response to hypoosmolality than any other transcript that is preferentially expressed in the SON (Table 4). The C1q domain containing 1, rho GDP dissociation inhibitor (GDI) ?, and encephalopsin genes decreased in expression in the hypoosmolar group as much as the VP gene did. Of the genes up-regulated more than 2-fold (Table 5), half were unclassifiable expressed sequence tags (ESTs), or annotated genes of unknown function, such as Murr 2 and nucleosome assembly protein-like 5. Superoxide dismutase 1, which breaks down reactive oxygen species formed in excess in hypermetabolic states (44), showed a 333% increase in the hypoosmolar group compared with the control. The functional annotation of the genes in Tables 4 and 5 is also shown, as a percentage of the total, in a pie-chart format as Supplemental Fig. 1S, A and B, respectively. Genes that significantly differed more than 2-fold between the hypoosmolar and control groups, but showed expression ratios less than 3.4, are shown in the Supplemental Tables 1S and 2S for 593 down-regulated and 812 up-regulated genes, respectively.
Transcription/translation-related genes modified in expression during hyponatremia
We were especially interested in identifying genes that might regulate transcription and translation in the MCNs of hyponatremic animals, so we specifically searched for genes that were annotated as transcription/translation-related genes using either the Gene Ontology program (45) (see website; http://cgap.nci.nih.gov/Genes/GOBrowser), or directly from the scientific literature. Table 6 lists 15 transcription/translation-related genes that were down-regulated more than 2-fold in hypoosmolar vs. control rats. PIPPIN, an RNA binding protein that functions in protein translation (46, 47); and putative homeodomain transcription factor, two genes which were not previously known to be expressed in the SON (48, 49); and c-fos, a marker of neuronal activity, were the most down-regulated of the transcription/translation-related genes in the hypoosmolar group compared with the controls (Table 6). Table 7 lists 29 transcription/translation-related genes that were up-regulated more than 2-fold in the hypoosmolar rats. Interestingly, there were many more transcription/translation-related genes that were up-regulated between 2-fold and 3-fold under hypoosmolar conditions compared with down-regulated genes.
TABLE 6. Transcription factor and nuclear protein genes that decrease in expression more than 2-fold under hypoosmolar conditions
TABLE 7. Transcription factor and nuclear protein genes that increase in expression more than 2-fold under hypoosmolar conditions
Discussion
Our goal in this study was to identify genes in the SON whose expression was altered by hypoosmolar conditions. Several previously detected, as well as novel, genes in the SON that were up-regulated and down-regulated during hypoosmolality were identified (see Tables 4–7). Among these genes, VP, OT (9, 10, 11, 12), and tyrosine hydroxylase (50, 51) were previously known to be present and osmotically regulated in the SON. This is the first report showing that tyrosine hydroxylase expression is down-regulated during hypoosmolality. Most of the other genes shown in Tables 4–7 were not previously known to be expressed in the SON.
The hypoosmolar rat model
The hypoosmolar condition in this model was induced by an infusion of the VP V2 receptor agonist dDAVP in association with water loading by a liquid diet. Therefore, in this study, we employed a second control consisting of an animal that was infused with the same amount of dDAVP (dDAVP-treated) as the hypoosmolar animals but was fed solid chow. These non-water-loaded rats remained normoosmolar despite the dDAVP infusion (28). This control allowed us to look for genes that responded solely to the infusion of dDAVP. The MDS analysis (Fig. 4) shows that each of our treatment groups fell into independent defined clusters. This suggests that the dDAVP treatment itself did influence gene expression in the SON. Throughout this study, when we identified genes in the SON that changed between the control and the hypoosmolar conditions, we also determined whether these genes significantly changed between the control and the dDAVP-treated normoosmolar conditions. We found that virtually none of these genes overlapped. Because dDAVP does not appreciably cross the blood brain barrier (52, 53), and the V2 receptor is not present in the SON (54, 55), these data suggest the possibility of an indirect action of the dDAVP from the periphery. In any case, all of the changes observed were relatively small, and we did not observe a statistically significant change between the control and the dDAVP-treated normoosmolar condition for VP transcription (Fig. 2). For the novel genes we analyzed in this study, virtually all of the genes that failed to show significant changes between the control and the dDAVP treatment on the array gave similar results in the ISHH analysis.
To confirm that the physiological conditions we used succeeded in altering VP gene transcription in the SON, we first performed ISHH using an exonic VP probe. VP mRNA showed a 166% increase in the hyperosmolar rat SON, a 59% decrease in the hypoosmolar rat SON, and no significant change in the dDAVP-treated normoosmolar rat SONs in comparison with control SONs (data not shown). A more direct estimate of VP gene transcription was made by using an intronic probe for hn VP RNA, which is unaffected by cytoplasmic mRNA degradation and turnover (42). The resulting data are shown in Figs. 1 and 2, and illustrate that the experimental conditions used appropriately altered VP transcription.
SON genes regulated by osmolality
In a recent microarray study (13), change in gene expression during chronic dehydration was used as a criterion to identify functionally interesting genes in the SON. Using hand-dissection of the SON and an array containing 1152 gene sequences, nine genes regulated by dehydration were identified. Four of these genes were also represented on our DNA array. Of these, only IL-6 (shown in Supplemental Table 1S) had a greater-than-2-fold decrease in expression during sustained hypoosmolality. The other three genes, eukaryotic translation initiation factor 5A, showed significant changes but did not meet our criterion of more than 2-fold change; protein kinase-AMP-activated, ?2 noncatalytic subunit, and PI-3-kinase-related kinase SMG-1 did not show significant changes between the control and hypoosmolar rats.
We performed ISHH on several of the genes that were identified as having very high expression ratios, all of which were also robustly functionally regulated (Table 3). Our false-positive rates were 0% for criterion 1 and 20% for criterion 2. Of particular interest are C1q domain containing 1, rho GDI ?, and encephalopsin because of their very large changes in gene expression in response to osmotic perturbations in both directions. All of these genes decreased in expression in the SON in the hypoosmolar state. C1q domain containing 1 (also known as EEG-1) was recently identified as a novel growth-related gene involved in hematopoetic differentiation (56). The fact that this gene’s expression is suppressed in the hypoosmolar condition suggests that it may also be involved in regulation of the VP and/or OT MCNs. The rho GTI ? rho GDI regulates the GTP-bound and GDP-bound state cycle of rho GTP-binding protein by decreasing the rate of dissociation from rho GTPases, which play important roles in neuronal morphogenesis (57). Previous results from our laboratory showed that MCNs dramatically adjust their cell volumes during both hyper- and hypoosmolar conditions (24). It is possible that the rho GDI may be involved in these morphological transformations.
Encephalopsin (also called Panopsin) is a member of the rhodopsin/G protein-coupled receptor gene superfamily. It is specifically expressed in the mammalian brain (58, 59). In this study, we used the rat genomic sequence that corresponded to the region (3'UTR sequence of the mouse encephalopsin) spotted on the array to produce a probe for ISHH. The ISHH showed a strong hybridization in the SON, paraventricular nucleus, and subfornical region in the rat brain (data not shown), which differed from a previous ISHH study on mouse encephalopsin. This difference could be due to an unknown splice variant in this gene. In our study, both the SON and the subfornical region showed a prominent increase and decrease in expression during the hyperosmolar and hypoosmolar states.
Genes involved in transcriptional regulation during sustained hypoosmolality that underwent 2-fold or greater changes are shown in Tables 6 and 7. In Table 3, we show the results from both ISHH and array assays for PIPPIN and putative homeodomain transcription factor (PHTF1). PIPPIN is a brain-specific RNA binding protein in the rat, which controls the recruitment of mRNA to the translational machinery (46, 47). PHTF1 is a putative homeobox gene that is well conserved not only in vertebrates but also in Drosophila (48, 49). Although this gene is ubiquitously expressed in the brain, there is a possibility that it contributes to the transcriptional regulation of the VP and/or OT genes, because no changes were observed in other regions of the brain under hyper- and hypoosmolar conditions. Calreticulin is a multifunctional protein that acts as a major Ca binding protein in the lumen of the endoplasmic reticulum. It is also located in the nucleus, interacts with DNA binding domains of estrogen receptor ?, inhibits transcriptional activities (60), and is able to act as a modulator of gene transcription. The decrease of the calreticulin mRNA expression in the SON during hypoosmolar conditions (Table 4) may be related to the reported increase in ER? under these conditions (21).
Another transfactor of interest is the LMO-4 gene, a novel member of the LMO subfamily of LIM domain containing transcription factors (61). It dramatically increased in expression under hypoosmolar conditions (Tables 3 and 7). The reported functions of this gene are the inhibition of differentiation in normal cells in the tumoriogenesis of breast cancers and T cell leukemia by interacting with DNA binding transcription factors or cofactors (62, 63), and also the inhibition of neuritogenesis in neuroblastoma cells (64). In a recent study, target disruption of this gene in mice caused a defect in the neural tube development (65, 66). The ISHH results of LMO-4 shown in Fig. 5 confirmed the array results showing up-regulation of expression in the hypoosmolar condition. Interestingly, LMO-4 is barely expressed in the SON in control and dDAVP-treated rats, but is substantially up-regulated in both hyper- and hypoosmolar animals, in contrast to most other genes, which showed a pattern of opposite regulation during these disparate physiological conditions. One of the functions of LIM domain is to mediate protein-protein interaction, which may have either positive or negative effects on transcription, depending on the counterpart with which it reacts (67, 68). Further studies should be directed to find the transcription factors and cofactors interacting with the LMO-4 gene in the SON and to determine the specific transcriptional regulation mechanism.
Three genes with prominent preferential expression in the SON were borderline, with respect to meeting the criterion of a greater-than-2-fold change in gene expression under hypoosmolar conditions on the array. These are EST similar to FLJ20037(69), zinc finger protein 312, and guanine nucleotide binding protein stimulating (previously described in Ref.18), and each underwent significant changes in expression in both hypoosmolar rats when evaluated by ISHH analysis (Table 7). Zinc finger protein 312 (also known as forebrain embryonic zinc finger, Fez), containing six C2H2 zinc fingers, is a highly conserved gene (70, 71, 72) and is of particular interest. This gene had the highest expression ratio among all the transcription factors expressed in the SON found on the array. Its only reported function, to date, relates to the development of the forebrain (72, 73), but its preferential expression in the SON suggests that further study of this gene in relation to VP and OT gene expression in the adult is warranted. Both zinc finger protein 312 (Fez) and LMO-4 gene are novel transfactors identified in the SON in this study, and they may also participate in regulating OT- and VP-gene expression in the SON, and other specific properties of the MCNs.
Conclusions
We found that hypoosmolality, known to be associated with a profound down-regulation of both OT and VP gene expression, was also accompanied by both up- and down-regulation of a large number of genes in the SON. A significant number of these genes were also regulated by hyperosmolality, suggesting that the changes observed were a result of true osmotic regulation rather than due to nonspecific effects, e.g. stress, or secondary treatment effects such as weight loss and others. Many previous studies have indicated that hypoosmolality inhibits both electrical activity (74) and peptide synthesis (11) in MCNs and, most remarkably, that the MCNs decrease both cellular and nuclear volume by 30–40% during sustained hypoosmolar conditions (24). The latter finding is consistent with the view that hypoosmolality produces a global decrease in transcriptional and translational activity in these neurons. Hence, our finding of decreases in expression of a large number of genes present on the array was expected. However, the finding that even more genes increased in expression under conditions of hypoosmolality was surprising. This finding that many genes are up-regulated in the SON during hypoosmolality raises the interesting possibility that these genes participate in the dramatic shut-off of peptide and structural protein synthesis in the SON, to maintain the MCNs in a quiescent state. The identification of a large number of transcription factor genes in the SON that are osmotically regulated (Tables 4–7) provides us with a group of candidate genes that might control OT and VP transcription, as well as other properties of the MCN phenotypes. The complex and global nature of the regulation of a cellular phenotype is not unprecedented. In a recent study, Odom et al. (75) reported that a member of the hepatocyte nuclear family of transcription factors functioned as a master regulator of global hepatocyte and pancreatic islet transcription and function. Another study, using microarrays, identified sets of known and novel genes that regulated the development of specific cellular phenotypes in the endocrine pancreas (76). It is also possible that there are sets of so-called master genes that control the global regulation of gene transcription in the MCNs during their adaptation to sustained osmotic perturbations. A general mechanism that could be involved in the global transcriptional activation and inactivation in the MCNs is chromatin remodeling. Posttranslational modification of core histones appears to be generally involved in regulating transcriptional activity (77, 78, 79), and one study has shown that chromatin remodeling occurs in the suprachiasmatic nucleus in response to a physiological stimulus in vivo (80). Future studies should be directed at the relationship of specific gene expression and chromatin remodeling in MCNs in the SON during their adaptation to sustained osmotic challenges.
Note Added in Proof
All of the unpublished, associated data from this study is accessible at the following web site: http://intramural.nimh.nih.gov/research/log/index2.html.
Acknowledgments
We thank Dr. Ying Tian (Georgetown University) for help with preparation of the animals; Dr. Eva Mezey, Ms. Sharon Key [National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH)], and Dr. W. Scott Young III (NIMH, NIH) for their help with ISHH; Dr. Yidong Chen (NHGRI, NIH) for his help with statistical analysis for microarray data; Catherine Campbell (NINDS, NIH) for her suggestions about microarray analysis; Mr. Raymond L. Fields (NINDS, NIH) for his technical assistance; and Mr. James W. Nagle and Ms. Debbie Kauffman (NINDS, DNA sequencing Facility) for DNA sequencing.
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