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Am J Physiol Gastrointest Liver Physiol 288: G897-G906, 2005; doi:10.1152/ajpgi.00454.2004
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MUCOSAL BIOLOGY

Immediate early genes of glucocorticoid action on the developing intestine

Barbara M. Agbemafle,1 Thomas J. Oesterreicher,1 Chad A. Shaw,3 and Susan J. Henning2

Departments of 1Pediatrics, 2Molecular and Cellular Biology, and 3Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas

Submitted 7 October 2004 ; accepted in final form 20 December 2004


   ABSTRACT
TOP
 ABSTRACT
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
Prior studies have demonstrated that glucocorticoid hormones elicit functional maturation of the small intestine as evidenced by their ability to induce increases in the expression of various digestive hydrolases, such as sucrase-isomaltase and trehalase. However, these increases have a lag time of ~24 h, suggesting that they are secondary effects of hormone action. To identify candidate primary response genes, we performed microarray analysis on pooled RNA from jejunums of untreated postnatal day 8 mouse pups and from littermates who earlier received dexamethasone 2 h. Fluorescent dye-labeled samples were hybridized in quadruplicate to glass-spotted cDNA microarrays containing 15,000 cDNA clones from the National Institute of Aging cDNA clone set. Analysis of the resulting signals using relatively stringent criteria identified 66 transcripts upregulated and 36 downregulated by 2 h of glucocorticoid treatment. Among the upregulated transcripts, the magnitude of the increase detected by microarray ranged from 1.4- to 16-fold. Selected mRNAs from throughout the range were subsequently analyzed by Northern blot analysis. Of 11 mRNAs chosen all were confirmed, and there was a strong correlation between the magnitude of the increase observed from the microarray analysis and from Northern blot analysis. Additional time points showed that these transcripts peaked between 2 and 6 h and had returned to baseline by 24 h. Gene ontology analysis showed pleiotropic effects of dexamethasone on the developing intestine and pointed to genes in the development category as being likely candidates for mediation of glucocorticoid-induced maturation of intestinal function.

suckling mice; jejunum; sucrase-isomaltase; microarray; primary response genes

AT BIRTH, THE RODENT GASTROINTESTINAL tract is uniquely adapted for digestion of milk diet. Thus hydrolases associated with both luminal and membrane digestion of substances typically found in solid food are either absent or minimal during the suckling period. In the third postnatal week, coincident with the timing of spontaneous weaning, there are dramatic functional changes throughout the gastrointestinal tract and complete functional maturation is achieved during the fourth postnatal week (15). Taking carbohydrate digestion as the example, at birth and during the first two postnatal weeks there is minimal capacity for digestion of starch as a result of very low levels of salivary and pancreatic amylase (that are responsible for the luminal phase of starch digestion) as well as low or undetectable levels of the cognizant brush-border disaccharidases in the small intestine (specifically maltase-glucoamylase and sucrase-isomaltase, which are responsible for the membrane phase of starch digestion). Conversely, lactase activity in the small intestine (responsible for hydrolysis of milk lactose) is very high at birth and through the first two postnatal weeks. During the third postnatal week, brush-border lactase activity declines, and there are dramatic increases in the activities of both salivary and pancreatic amylase, as well as small intestinal maltase-glucoamylase and sucrase-isomaltase. Other aspects of intestinal morphology and function also mature at this time (15).

Numerous studies over the past 30 yr have demonstrated important roles for glucocorticoid hormones in functional maturation of the gastrointestinal tract. There is a developmental surge of serum corticosterone (the endogenous glucocorticoid in rats and mice) at the end of the second postnatal week (11, 14). Moreover, administration of exogenous glucocorticoids during the suckling period causes precocious maturation of many aspects of gastrointestinal structure and function. Because the details of glucocorticoid action have been most thoroughly investigated in the small intestine, we will confine the remainder of our discussion to this tissue. Small intestinal brush-border proteins known to be induced by glucocorticoids include the digestive hydrolases sucrase-isomaltase, maltase-glucoamylase, trehalase, and alkaline phosphatase as well as the bile salt transporter (12, 15). Evidence that these effects are due to direct action of glucocorticoids on the intestinal tissue comes from studies with intestinal explants from fetal or neonatal rats or mice, wherein precocious appearance of sucrase activity and stimulation of maltase activity has been reported (12, 16). Glucocorticoids have also been implicated in the maturation of the human small intestine as evidenced by studies of preterm infants whose mothers received prenatal glucocorticoids (36) as well as from studies with explants of human fetal intestine (3, 37) and xenografts of human fetal intestine (28).

For all cases that have been studied, the induction of enzymes and other proteins in the suckling small intestine after glucocorticoid administration appears to be the result of elevated expression of their respective mRNAs (12, 17, 21, 48). For sucrase-isomaltase and trehalase, further studies (13, 47) have indicated that the effect of glucocorticoid on mRNA levels in turn reflects activation of transcription. On the basis of the classical model of glucocorticoid action (10), the simplest mechanism to explain these findings would be one in which the glucocorticoid receptor functioned as a transcriptional activator of these genes. However, available data regarding the time courses of mRNA increases in the small intestine after glucocorticoid administration suggest that this is not the case. Whereas primary response genes display a rapid increase of mRNA reaching a peak or a plateau within 2–6 h (10), mRNAs for sucrase-isomaltase (4, 26) and trehalase (13) show only modest elevation by 24 h after hormone treatment and then rise to plateau levels over the next 3–4 days. Such a pattern is typical of secondary response genes (10) and leads to the hypothesis that transcription of these genes is activated by one or more regulatory genes, which is/are, in turn, directly activated by glucocorticoids. We have recently used electromobility shift assays to demonstrate that the transcription factor GATA-4 is probably one of the factors that mediate glucocorticoid action on the developing intestine (30). However, that study suggested that one or more accessory factors must also be required. To identify these accessory factors, the goals of the current work were 1) to use cDNA microarrays to identify mRNAs rapidly induced by glucocorticoids in the mouse small intestine (designated immediate early genes); 2) to confirm a subset of these by Northern blot analysis; and 3) to study the full time course of expression of selected examples by Northern blot analysis.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
Animals, treatments, and tissue collection. Timed pregnant C57BL/6J mice were received from Jackson Laboratories (Bar Harbor, ME) on days 11–13 of gestation. They were housed individually and provided food (5001 Rodent Diet; PMI Nutrition International, Brentwood, MO) and acidified tap water ad libitum. Our Institutional Animal Care and Use Committee approved all animal housing and protocol details. On postnatal day 8, three pups from separate litters were killed (as zero time untreated controls), and jejunums were collected into RNAlater (Ambion, Austin, TX). Immediately after this, 12 more pups (4 from each of the 3 litters) were injected subcutaneously with 0.4 µg/g body wt of dexamethasone (Dex). Jejunums were collected from Dex-treated littermates at 2, 6, 12, and 24 h after injection. As 24-h untreated controls, four more pups from separate litters were collected at postnatal day 9. The experiment was subsequently repeated with four additional litters, and this time we included littermate controls injected with vehicle (0.8% ethanol in 0.15 M NaCl) at each time point. On the basis of litter size, this necessitated the use of two litters for the 2- and 12-h time points and two separate litters for the 6- and 24-h time points. All jejunums were stored at 4°C in RNAlater (Ambion) until RNA isolation.

RNA isolation and Northern blot analysis. Total RNA was isolated from jejunums by homogenization in guanidinium isothiocyanate and pelleting through a cesium chloride cushion as described elsewhere (24, 26). Northern blots were made by using 10 µg of total RNA per lane on a 1% formaldehyde agarose gel. Each row of samples included a standard comprised of pooled adult mouse jejunal RNA. The RNA was transferred onto uncharged nylon membrane by capillary transfer with 10x SSC and then UV cross linked. The blots for Fig. 1 were probed sequentially with mouse sucrase-isomaltase cDNA (Oesterreicher TJ, unpublished observation) and mouse {beta}-actin cDNA (2). The blots for Fig. 5 were sequentially probed with various cDNAs obtained from National Institute of Aging (NIA) 15K cDNA clone set (38). In all cases, clone inserts were 32P-labeled by random primed oligo-labeling. Prehybridization and hybridization were performed with a solution comprising 1 mM EDTA, 0.25 M sodium phosphate, pH 7.2, 7% SDS, and 0.1 mg/ml denatured salmon sperm DNA. Blots were incubated with prehybridization solution at 65°C for 1 h before incubating with hybridization solution, which included the 32P-labeled probe. After 16- to 18-h hybridization at 65°C, blots were washed once at 65°C for 20 min in 1 mM EDTA, 20 mM sodium phosphate, pH 7.2, and 5% SDS. A second wash was then performed for the same time and temperature with 1 mM EDTA, 20 mM sodium phosphate, pH 7.2, and 1% SDS. Blots were then rinsed with 0.15 M NaCl/0.015 M sodium citrate. Between each probing, blots were stripped with the second wash solution at 90°C for 20 min. No blot was probed >4 times, including the {beta}-actin probe. All blots were subjected to autoradiography and the size of each transcript was interpolated from the 18S and 28S rRNA bands.



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  		Fig. 1. Time course of jejunal sucrase-isomaltase mRNA after dexamethasone (Dex) administration to suckling mice. A: representative audioradiogram of Northern blot showing signals for sucrase-isomaltase mRNA and the constitutive marker {beta}-actin in jejunal RNA from postnatal day 8 (P8) mice that were either untreated or Dex-injected. Numbers under the Dex bar show hour after hormone administration. The second 24 shows the additional control animal taken 24 h after the 0 h control and S shows the pooled adult standard. B: quantitative data from all samples shown as means ± SE for 3–4 pups at each time point. Lack of error bars indicates the SE is smaller than the symbol. Open circles show uninjected control samples at 0 and 24 h. Closed circles and dashed lines show samples from Dex-treated pups whose jejunums were collected at 2, 6, 12, and 24 h after injection. Data are depicted as {beta}-actin normalized values expressed as a percent of adult mouse standard. *P < 0.05 compared with 0 h.

 


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  		Fig. 5. Representative Northern blots of selected transcripts. Each panel shows jejunal RNA (10 µg) from individual P8 mice that were either untreated (C), or were injected with vehicle (V) or Dex (D) and then killed 2, 6, 12, and 24 h later. The last lane (S) is a pooled standard of jejunal RNA prepared from adult mice of the same strain. Gene numbers are those assigned in Table 1 and thus are inversely correlated to the fold increase detected by microarray. Arrows show the size of each transcript. Gene names are shown on the far right, and for unknown genes, the H numbers given are the unique identifiers from the NIA 15K clone set.

 
Signals from Northern blots were quantified by phosphorimaging. To correct for loading variation, these data were expressed as a ratio of the hybridization signal of the band of interest to that of the constitutive marker {beta}-actin on the same blot. In Figs. 1 and 7, this ratio (i.e., the normalized mRNA level) was then expressed as a percentage of adult mouse standard from the same blot. In Fig. 6, because some of the transcripts were not detectable in the adult tissue, the normalized mRNA levels at each time point were expressed as a percentage of the peak value for that set. Statistical significance was assessed by one-way or two-way ANOVA, followed by Fisher's least significant difference test using Minitab program. For graphical presentation, values for individual animals from each experimental group were calculated as means ± SE. The number of animals per group is given in the figure legends.



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  		Fig. 7. Comparison of expression levels of selected transcripts in suckling compared with adult mouse jejunum. For each transcript, {beta}-actin normalized values were expressed as a percentage of the pooled adult standard on the same Northern blot. Data are shown as means ± range (N = 2). Open bars show peak value observed for that transcript (i.e., value at 2 or 6 h as per Fig. 6) and gray bars show vehicle-treated control mice from the same time point.

 


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  		Fig. 6. Quantitative data for time courses determined from Northern blot analysis. For each blot, {beta}-actin normalized values obtained by phosphorimaging were expressed as a percentage of the peak value from that blot. Solid lines represent vehicle-treated samples, and dashed lines show Dex-treated samples. Axes show time in hours after injection. Data are shown as means ± range (N = 2). Lack of error bars indicates the range was smaller than the symbol. For gene 9, only the 6.0-kb transcript is plotted.

 
Microarray analysis. Equal amounts of total jejunal RNA from mice (n = 3 per group) that were either untreated (0 h controls) or Dex-treated (2 h) were pooled and given to the Baylor College of Medicine Microarray Core Facility. In the Core, the two pooled samples of RNA were used for generation of Cy3 and Cy5 (PA23001 and PA25001; Amersham Biosciences, Piscataway, NJ) dye-labeled cDNAs. The labeled cDNAs (Cy3 = control and Cy5 = Dex) were combined and hybridized to quadruplicate microarray chips which were prepared in the Core using the NIA 15K mouse embryo cDNA set (38). Protocols for preparation of chips and probes and for hybridization can be found on the Core website (http://www.bcm.edu/mcfweb/protocols.htm). Quality control on each print batch was assessed by hybridization with M13RV-TXRed (fluorescent dye-coupled oligo) to check the DNA spotting pattern and by hybridization with control probes made from Universal Mouse Reference RNA (Stratagene, La Jolla, CA) vs. normal mouse liver.

Microarrays were scanned by using a GeneTAC UC4 scanner (Genomic Solutions, Ann Arbor, MI) at a resolution of 10 µm/pixel. Two .tif files were generated for each slide, one for Cy3 and one for Cy5. Quantification was performed with GLEAMS (NuTec Health Systems, Alpharetta, GA) to obtain a text data file for each channel. Before any hypothesis test was done, the raw data were normalized to remove systematic effects, such as abnormal backgrounds and heterogenous distribution of intensities on the chip. The log ratio of the Cy5 intensity and Cy3 intensity of each spot was calculated. Thresholding of the data was done by excluding spots or groups of spots with too-low intensities in both channels and those with too-high background-intensity ratios. The loess-based normalization and MAD-based scaling methods similar to those proposed by Yang et al. (45) were used to remove spatial effect, print tip effects, and intensity-related artifact, and make different chips comparable. Both Z-statistics and T-statistics were calculated. Our criteria for identifying genes as differentially expressed were as follows: 1) either the T-statistic or the Z-statistic has a marginal P value of <0.05, and 2) the mean difference of the normalized log ratio values is > 0.5. We find empirically that this rule gives a very low false detection rate. Full details of the data from the microarray chips can be found in the GEO database (http://www.ncbi.nih.gov/geo) under accession no. GSE1826.

The list of differentially expressed genes was ordered by fold difference and then divided into an upregulated Dex (Up-Dex) and downregulated (Down-Dex) list for presentation and further analysis. The most recent annotation (March 2004) of the NIA 15K cDNA clone set (http://www.bcm.edu\mcfweb) was used to identify genes in each list and correct gene abbreviations were obtained from http://www.ncbi.nlm.nih.gov/projects/Locuslink. The complete list of differentially expressed transcripts, together with the statistics, can be found at http://ajpgi.physiology.org/cgi/content/full/00454.2004/DC1.

We also performed Gene Ontology (GO)-based enrichment analysis to assess the content of our experimentally derived lists. The GO is a threefold controlled vocabulary for characterizing the biological properties of gene products (genes) and has been well described elsewhere (50). The GO data structure can be freely obtained from the GO website: http://www.geneontology.org. Annotation data for the clones on the NIA array can be obtained through http://lgsun.grc.nia.nih.gov. We have developed our own software for performing content analysis on gene lists using the GO data structure (50). Briefly, we instantiate the GO as an ordered graph and locate the genes in the list as nodes in the graph. We then identify the paths through the GO required to reach annotations for the genes in our list. Genes located at or below terms in the GO share evidence for the biological property identified by the term, so by tabulating counts at each node and comparing them to a reference model of random counts, we can identify unusually overabundant terms. We have successfully used the software in previous publications (42, 50).

To compare gene lists, we used a distance metric on gene lists according to the mapping of the lists against the GO data structure. This distance calculation provides more information than a "gene-overlap" calculation because it uses the GO annotations to group similar genes into GO categories. This approach is able to identify commonalities even in situations in which the gene lists themselves do not overlap highly. Briefly, the distance metric calculates a Kullback-Leibler distance at each level of the GO and averages these GO-level distances to provide an overall distance calculation between lists (42). Once we have obtained pairwise distances between lists, we are able to compute dendrograms between lists using standard methods.


   RESULTS
TOP
 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 GRANTS
 REFERENCES
 
Time course of Dex induction of sucrase-isomaltase mRNA. Most studies of precocious maturation of the rodent small intestine after administration of glucocorticoids during the first or second postnatal week have used three or more days of glucocorticoid treatment. In the few cases in which a time course has been included, the earliest point has typically been 24 h. At this time, mRNA levels for sucrase-isomaltase (4, 26) and trehalase (13) are only 20–40% of the plateau levels seen after 3–4 days of glucocorticoid treatment. Although this slow rise has led to the general idea that genes such as trehalase and sucrase-isomaltase are not direct response genes, to date there have in fact been no studies at time points earlier than 24 h. Thus our first goal was to assess the expression of sucrase-isomaltase mRNA as a marker of functional maturation of the jejunum at early times after Dex administration to suckling mice. As shown in Fig. 1A and as reported previously (4) sucrase-isomaltase mRNA was not detectable in untreated controls at postnatal day 8. In Dex-treated pups, sucrase-isomaltase mRNA remained undetectable through 2 h. Longer exposures of the blots showed a faint signal at 6 h. Quantitative analysis (Fig. 1B) indicated that the rise of sucrase-isomaltase mRNA became statistically significant only at 12 h and then continued to increase, reaching ~20% adult levels by 24 h after Dex administration. This time course for sucrase-isomaltase mRNA confirms our previous assertion that such genes do not appear to exhibit a direct response to glucocorticoid hormones.

Microarray analysis at 2 h after Dex treatment. Because the goal of the microarray studies was to identify candidate primary response genes that may mediate glucocorticoid-induced functional maturation of the small intestine, we chose a very early time point (2 h) at which we knew (from Fig. 1) that there was no detectable increase of sucrase-isomaltase mRNA. The Cy5-labeled cDNA prepared from RNA isolated from 2-h Dex-treated jejunums was competitively hybridized to NIA 15K cDNA microarray chips with Cy3-labeled cDNA from jejunal RNA of zero time untreated control mice. RNA samples used were the same ones previously analyzed in Fig. 1.

The microarray analysis detected a total of 66 transcripts that were significantly increased after a 2-h Dex treatment and 36 transcripts that were significantly decreased at this time. Interestingly, both categories had a large proportion of unknown genes: 31 of 66 (47%) in the "up" set and 22 of 36 (61%) in the "down" set. The percentages of unknown genes in both categories are significantly higher than that within the 15K cDNA clone set on the chips (12.5% as of August 2004, as estimated by BLAT of NIA sequence set against the MM4 build of the human genome and consideration of the annotations within the University of California-Santa Cruz Genome Browser database).

Table 1 shows the fold change for known transcripts in the upregulated set. As can be seen, the use of quadruple chips allowed statistically significant increases as low as 1.4-fold to be detected. Reliability of the data is also attested by the facts that 1) in the one instance in which there were duplicate cDNAs on the chips (Ccrn41), the fold increase was quite close (4.6- and 5.4-fold), putting these data adjacent to one another in the ordered list; and 2) among the known transcripts that were increased by Dex, there are several that have been previously reported to be rapidly induced in response to glucocorticoid in either intestine or other tissues: specifically, Fos (4), Sgk1 (6), Pfkb3 (25), Glul (1), and Timp3 (23).


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  		Table 1. Known transcripts increased by dexamethasone

 
The distribution of the fold changes within the entire set of upregulated transcripts (Fig. 2A) shows that 28 of 66 transcripts displayed very modest increases (1.4- to 1.9-fold). A somewhat larger group (34 transcripts) had intermediate increases in the range 2.0- to 4.9-fold and only four transcripts displayed increases greater than fivefold. Figure 2A also shows that unknown transcripts were distributed through the low and intermediate levels of upregulation, but were not found in the highest group.



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  		Fig. 2. Distribution of fold change detected by microarray. Solid bars or portions of bars show known genes and open bars or portions of bars show unknown genes. A: transcripts upregulated by Dex; B: transcripts downregulated by Dex.

 
Table 2 shows fold change for known transcripts that were downregulated by Dex, and Fig. 2B shows the distribution of fold changes in the entire downregulated set. As can be seen, no genes were found to be strongly repressed by Dex treatment. The fold changes all fell in the range of 0.35 to 0.74, i.e., showing transcripts in the Dex-treated animals being in the range of 35 to 74% of those found in control samples. As can be seen in Fig. 2B, the majority of the downregulated transcripts (29 of the 36) had levels in the range of 50 to 74% of the untreated control. Unknown genes were found through most of the range in the downregulated set.


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  		Table 2. Known transcripts decreased by dexamethasone

 
GO analysis. Results obtained from the microarray were further analyzed by custom software (50) designed to make use of the GO database (http://www.geneontology.org). There were a total of 28 annotated genes in the upregulated category and only 9 in the downregulated. Figure 3 shows that in the upregulated group of transcripts, one was involved in rhythmic behavior, 4 each in signal transduction, cell death, and development, 5 each in cell proliferation and regulation of transcription, and 14 in metabolism. Within the downregulated group, the majority (6 transcripts) were once again found in the metabolism category, 3 in transport, and 1 each in biogenesis and regulation of transcription. The names of the genes represented in the various categories of Fig. 3 are listed in Table 3. As commonly occurs in GO analysis, some genes (e.g., Gadd45{gamma}) appear in multiple categories. The analysis included two unknown genes (in the metabolism category of the Down-Dex list) that have presumably been placed in the GO on the basis of function predicted by sequence domains.



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  		Fig. 3. Gene Ontology (GO) of microarray results. Ordinate shows number of transcripts in each of the biological process GO categories shown at bottom. Bars above the axis represent transcripts that were upregulated after 2 h of Dex treatment and bars below the axis represent transcripts that were downregulated. Solid portions of bars show known transcripts and open portions of bars show unknown transcripts.

 

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  		Table 3. Identification of Dex-altered transcripts in each gene ontology category

 
In addition to the content analysis of our gene lists, we used the GO to compare our results with those from Clerch et al. (8) who performed microarrays to identify transcripts that were altered in postnatal mouse lung in response to 6 h of Dex. The results are presented in the dendrogram shown in Fig. 4. To compute the dendrogram, we mapped each list onto the GO data structure, and then computed a distance metric according to the relative GO content of each list, as discussed in MATERIALS AND METHODS. The result is a four-leaf dendrogram in which the lowest join is between the Clerch Up-Dex list (8) and our Up-Dex list, indicating significant similarity in the types of genes induced by glucocorticoids in the two tissues.



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  		Fig. 4. Comparison of Dex effects on postnatal small intestine and lung. On the basis of GO content, our upregulated Dex (Up-Dex) and downregulated Dex (Down-Dex) lists were compared with those of Clerch et al. (8) with postnatal mouse lung. The dendrogram shows that the two most similar lists in terms of GO content are our Up-Dex and the Clerch Up-Dex list (8). The Clerch Down-Dex (8) and our Down-Dex are less similar, but very little GO annotation is available for these small lists (only one gene in the case of Clerch Down-Dex Ref. 8).

 
Northern blot analysis of selected upregulated transcripts. Northern blot analysis was used to confirm microarray analysis of a subset of 11 upregulated transcripts from Table 1. These transcripts were purposefully chosen to include examples from the low, medium, and high range of the fold increase detected by microarray and to include both known and unknown genes. In addition to confirming that these transcripts were increased by 2-h Dex, a further goal of the Northern blot analysis was to define the complete time course of the response of each transcript to Dex. As can be seen in Fig. 5, all 11 transcripts behaved in a manner consistent with the microarray results in being increased above untreated controls within 2 h of the Dex injection. For all known genes, the size of the transcript detected by Northern blot analysis (and shown on Fig. 5) agreed with published values. The three unknown genes chosen all had relatively large transcripts, which may explain, in part, why they are not yet annotated.

Quantitative data from the Northern blot analysis are shown in Fig. 6. As can be seen, all 11 transcripts showed peak levels between 2 and 6 h of Dex treatment and in all cases, transcript levels had returned close to baseline by 24 h. The time courses with vehicle-injected mice show that none of the transcripts increased simply in response to the handling and injection. In other words, all changes seen in the Dex-treated mice reflect specific effects of the hormone. Two-way ANOVA analysis of the data in Fig. 6 showed the effect of Dex treatment to be statistically significant for each transcript (P < 0.05) except for gene 39 (P = 0.061). The latter is due solely to a wide variation in the zero time values for gene 39 because if this point is eliminated, the two-way ANOVA for gene 39 shows the Dex effect to be highly significant (P = 0.001). The variability of the zero time values for gene 39 most likely reflects the fact that this transcript is very weakly expressed as can be seen in Fig. 5, in which the signal was barely detectable even after long exposure. In contrast, gene 48 (Tgfb1t4), which is an abundant transcript (Fig. 5), showed less variability and a statistically significant Dex effect, although the magnitude of the response was less than that for gene 39.

To assess the quantitative relationship between the microarray data and the Northern blots, the fold increases detected by microarray at 2 h were plotted against those detected by Northern blot analysis at 2 h (data not shown). Regression analysis with all 11 transcripts showed a significant (P = 0.001) but somewhat weak (R2 = 0.78) correlation. However, there was clearly a single outlier (gene 2, Ndrg1), and when this was removed, a stronger correlation was observed (R2 = 0.90) and the regression was described by the equation y = 0.8 x + 1.0 where y = microarray value and x = Northern value. As can be seen, the slope of the regression line was close to unity, indicating no systematic bias of the quantitative data from the microarrays compared with the Northern blots.

Comparison between suckling and adult expression of selected transcripts. Examination of the Northern blot data shown in Fig. 5, as well as longer exposures of the same blots, reveals that for most transcripts studied, the signals observed in both untreated controls and vehicle-treated suckling mice are approximately equivalent to those seen in the adult standard. The notable exception is gene 1 (Fkbp5) for which no signal was detectable with the adult RNA, even after very long exposures. It is also apparent from Fig. 5 that for most transcripts, the levels elicited by Dex treatment are substantially higher than those seen in the adult jejunum. To quantitatively assess the relationship between control and peak values observed in the suckling mice with control levels in adult mice, the {beta}-actin normalized values for each transcript (except Fkbp5) were expressed as a percentage of the pooled adult standard run on the same blot. The data shown in Fig. 7 confirm the qualitative observations from the Northern blot analysis, namely that for all of these transcripts, control levels in the postnatal day 8 mice are either equivalent to or higher than those seen in the adult. This indicates that, in contrast to the situation shown for sucrase-isomaltase mRNA in Fig. 1, none of these genes display increased levels of expression during the transition from suckling to adulthood. Given the pattern for control mice, it is not surprising that the peak values observed after Dex treatment all exceed adult levels and for the majority (6 of 10), the peak levels are more than fourfold higher than levels seen in adult tissue.


   DISCUSSION
TOP
 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
GRANTS
 REFERENCES
 
In this study, we have successfully used cDNA microarrays to identify transcripts that are rapidly up- and downregulated in the suckling mouse jejunum in response to Dex treatment. Although custom cDNA microarrays are often viewed as less reliable and sensitive than commercial oligonucleotide arrays, we found that by the use of quadruple chips and rigorous quality control, the cDNA arrays are, in fact, highly sensitive, allowing detection of increases as small as 1.4-fold and decreases as small as 0.7-fold. In addition, we have shown that the cDNA microarray data are highly reliable because, of the 11 upregulated transcripts chosen for confirmation by Northern blot analysis, all 11 were confirmed as being upregulated. There was also overall a good quantitative correlation between the fold changes observed by microarray and by Northern blot analysis. The fact that the microarray experiment was done on a separate set of animals from those used for the Northern blot analysis also demonstrates the biological reproducibility of the findings. In addition to their sensitivity and reliability, a further point in favor of cDNA microarrays for studies of this type (two sample comparisons) is that the two samples are hybridized simultaneously to the same chip, thus simplifying normalization and analysis.

Given the well-known fact that glucocorticoid hormones have pleiotropic actions on all tissues in the body, it is not surprising that the GO analysis showed the Dex-affected transcripts to be distributed through various categories. As to be expected, on the basis of the housekeeping roles of glucocorticoids, the majority of transcripts on both the "up" and "down" lists were found in the metabolism category. Apart from that, there were only two other categories (transport and transcription) that featured in both the upregulated and the downregulated set of transcripts. As can be seen from Fig. 3, five categories (rhythmic behavior, signal transduction, cell death, proliferation, and development) included only upregulated transcripts, and one category (biogenesis) included only a downregulated transcript. The potential relationship between the overall patterns and the influence of glucocorticoids on intestinal development is discussed below.

In terms of the numbers of transcripts up- and downregulated rapidly in response to Dex treatment, our data are well within the ranges reported in other studies of glucocorticoid action on various cells and tissues. Our literature search revealed a total of seven microarray studies (8, 20, 32, 33, 43, 44, 49) that were comparable in the sense that they examined changes of gene expression in the immediate early period after glucocorticoid treatment (with actual times being from 30 min to 10 h). The numbers of upregulated transcripts in these studies ranged from 21–90 compared with our 66. In all except one case, there were markedly fewer transcripts rapidly downregulated by glucocorticoid, the range being 4 to 111, compared with our 36. The closeness of these numbers is even more remarkable considering that the studies in the literature included both custom cDNA microarrays and commercial oligonucleotide microarrays and utilized three different forms of glucocorticoid (Dex, triamcinolone, and methylprednisolone). Most of the prior studies (32, 33, 43, 44, 49) were performed in vitro on either mouse or human cell lines known to be responsive to glucocorticoid. Only two prior studies (8, 20) have used microarray analysis to study immediate early effects of glucocorticoids in vivo. Specifically, Jin et al. (20) used oligonucleotide microarrays to assess changes in hepatic gene expression at various times after administration of methylprednisolone to adult rats. They found a total of 32 genes to be rapidly induced (with peak levels ranging from 30 min to 10 h) and 111 genes to be repressed. The other in vivo study is that by Clerch et al. (8) in which suckling mice (postnatal day 4) received Dex 6 h before collection of lung tissue for RNA analysis by oligonucleotide microarrays. A total of 74 transcripts were found to be upregulated (very close to our 66) and 11 to be downregulated (significantly fewer than our 36). The latter discrepancy probably reflects the fact that Clerch et al. (8) used a cutoff of –1.7 equivalent to 0.59-fold on our scale. As can be seen in Fig. 2, had we used this cutoff, 20 downregulated transcripts would have been eliminated, bringing the total to 16, which is very comparable to that observed by Clerch et al. (8).

Of all the published glucocorticoid/microarray studies, we view that by Clerch et al. (8) to be the most relevant comparison with ours because it is the only one done with mouse tissue in vivo. Moreover, it utilized suckling animals and thus is focused on the same period of development as our study, and it examines lung tissue that has both epithelial and stromal components analogous to the small intestine. For all these reasons, we chose the Clerch et al. (8) study for a more detailed comparison with our microarray data. GO analysis of the two data sets showed the upregulated transcripts to have a high degree of concordance, indicating that, in a global sense, glucocorticoids have very similar effects on these two developing tissues. The fact that there was not such close agreement between the downregulated transcripts in the two data sets is almost certainly the result of their being too few annotated genes in these sets (9 for intestine and only 1 for lung). In summary, from the data available from prior studies of immediate early effects of glucocorticoids, our data with postnatal mouse intestine show close agreement in terms of the numbers of genes up- and downregulated (8, 20, 32, 33, 43, 44, 49) and show even closer agreement with the one other in vivo mouse study (8), both in terms of the number of genes and the biological content of gene expression.

The time courses observed in the 11 upregulated transcripts that we chose for further study by Northern blot analysis were remarkably consistent. In all cases, the mRNA levels peaked between 2 and 6 h and then returned to baseline by 24 h. Such patterns are most likely a reflection of circulating concentrations of Dex after administration. Although we have been unable to find published data on the pharmacokinetics of Dex in mice, studies in rats have shown the half-life after intravenous injection to be on the order of 5 h (22, 41). Assuming similar kinetics in mice, we predict there would be relatively rapid entry of Dex to the bloodstream after subcutaneous injection, and by 24 h, circulating concentrations of Dex would have declined to minimal levels. Thus the time courses observed for our 11 transcripts (Fig. 6) are consistent with a simple model of glucocorticoid action in which transcriptional activity of the glucocorticoid receptor is driven primarily by ligand concentration (20). In contrast, the time course observed for sucrase-isomaltase mRNA (Fig. 1) clearly reflects a more complex (presumably secondary) mode of action.

As explained in the Introduction, a major goal of these studies was to identify glucocorticoid primary response genes that might be plausible candidates for mediating the maturational effects of these hormones on the small intestinal epithelium. Despite the plethora of descriptive studies over the past 30 yr documenting the ability of glucocorticoids to elicit intestinal maturation in the postnatal period, there are to date very few hints as to the underlying molecular mechanisms. What is known is that many genes that normally display increased expression during the third postnatal week can be precociously induced by glucocorticoids during the first and second weeks (12, 15). On the basis of the slow rise of marker mRNAs, such as sucrase-isomaltase mRNA and trehalase mRNA (4, 13, 26), it was hypothesized that glucocorticoids must rapidly activate expression of one or more regulatory genes whose protein products in turn activate transcription of genes, such as sucrase-isomaltase and trehalase. Interestingly, studies from both our laboratory (27) and the Traber laboratory (39) provided evidence that the regulatory genes involved in glucocorticoid-induced precious maturation during the first two postnatal weeks are distinct from those involved in normal maturation during the third postnatal week. In view of this, it is not surprising that HNF1{alpha}, which appears to be the transcription factor primarily responsible for activation of sucrase-isomaltase expression during normal development (5), was not among our list of genes upregulated in response to Dex, despite the fact that this cDNA was present on the chips. On the other hand, because our prior studies had identified GATA-4 protein as being rapidly elevated in both nuclear and whole cell extracts of jejunums from Dex-treated mice (30), we had expected to see GATA-4 mRNA on the "Up-Dex" list from the current microarray studies. To check whether this represented an example of a false negative, we performed a Northern blot analysis for GATA-4 mRNA and found no elevation in Dex-treated jejunums compared with control jejunums (data not shown). Thus GATA-4 appears to be regulated at the protein level rather than the mRNA level and cannot be considered a primary glucocorticoid response gene.

Examination of the categorical list of transcripts that were rapidly upregulated by Dex (Table 3) illustrates the complexity and diversity of glucocorticoid effects on this tissue. For example, transcripts in the cell proliferation GO category are most likely to account for the fact that in addition to stimulating maturation, glucocorticoids are also known to stimulate proliferation of the suckling intestinal epithelium (18, 46). Transcripts found in the cell death GO category are probably also related to the changes in cell kinetics that occur after glucocorticoid administration. We predict that the transcripts most likely to be responsible for epithelial maturation will be among those in the development category. Of these, Ndrg1 and Ndrg2 are of particular interest because they belong to a new family of differentiation-related genes (7, 29, 31). Their expression has not been previously reported in postnatal small intestine. However, in human colon, Ndrg1 is expressed only in the highly differentiated surface epithelial cells, and in colon carcinoma cells, Ndrg1 is strongly induced during in vitro differentiation (40). Moreover in rat brain tissue, increases of Ndrg2 mRNA have been reported to be associated with glucocorticoid-induced neuronal differentiation (29). Although the mechanism of action has not yet been elucidated (35), the fact that Ndrg1 protein is found in the nucleus under some conditions (40) would be consistent with the ability to mediate glucocorticoid induction of secondary response genes.

One of the greatest benefits of microarray studies is that they uncover new relationships that can lead to novel hypotheses. In this regard, in addition to the candidate genes discussed above, we feel there is one additional transcript of particular interest, namely Fkbp5 (also known as Fkbp51). As can be seen in Table 1 and Fig. 6, Fkbp5 showed by far the strongest response to Dex in our study. Interestingly, the related gene Fkbp4 (also known as Fkbp52), was on the microarray chips but showed no change in response to Dex. Fkbp4 and Fkbp5 are members of the immunophilin family and were originally identified as cytoplasmic proteins capable of binding immunosuppressant drugs such as Fk506. More recently, Fkbp4 and Fkbp5 have been shown to be associated with glucocorticoid receptor complexes and to regulate nuclear translocation of the glucocorticoid receptor (9). In the absence of hormone, glucocorticoid receptor is maintained in the cytoplasm by association with heat shock protein 90 and Fkbp5. Hormone binding elicits an interchange of Fkbp5 and Fkbp4 within the glucocorticoid receptor heterocomplex, which in turn stimulates nuclear translocation (9). Conversely, elevated expression of Fkbp5 blocks nuclear translocation and thus leads to diminished hormone glucocorticoid responsiveness (34). The two immunophilins play a similar regulatory role in the intracellular trafficking of the progesterone receptor complex and induction of Fkbp5 by progesterone has been proposed as a negative feedback mechanism to limit progesterone action (19). By analogy, we speculate that the rapid Dex-induced increase of Fkbp5 mRNA observed in the suckling small intestine in our study may represent a mechanism to protect tissues against daily transient fluctuations of circulating glucocorticoid in response to stress. In the case of the small intestine, this would prevent precocious maturation during the normal suckling period, thus ensuring optimal capacity for digestion of the milk diet. Furthermore, we propose that sustained elevation of glucocorticoid is not associated with increased expression of Fkbp5, thus allowing induction of intestinal maturation. Exploration of these new levels of complexity of glucocorticoid action on the developing intestine should provide a fertile area of future research.


   GRANTS
TOP
 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
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REFERENCES
 
This work was supported by National Institute of Child Health and Human Development Grant HD-14094. The microarrays were performed in the Baylor College of Medicine Microarray Core facility, which is supported, in part, by the Gulf Coast Digestive Disease Center by National Institute of Diabetes and Digestive and Kidney Diseases Grant DK-56338.


   ACKNOWLEDGMENTS
 
The authors thank Sue Venables for special assistance with the microarrays, as well as Christopher Fisk for performing the BLAT searches.


   FOOTNOTES
 

Address for reprint requests and other correspondence: S. J. Henning, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030 (E-mail: shenning{at}bcm.tmc.edu)

The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.


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