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Endocrinology Vol. 147, No. 5 2357-2367
Copyright © 2006 by The Endocrine Society

Global Profiles of Gene Expression Induced by Adrenocorticotropin in Y1 Mouse Adrenal Cells

Bernard P. Schimmer, Martha Cordova, Henry Cheng, Andrew Tsao, Andrew B. Goryachev, Aaron D. Schimmer and Quaid Morris

Banting and Best Department of Medical Research (B.P.S., M.C., H.C., A.T., A.B.G., Q.M.), Department of Pharmacology (B.P.S.) and Department of Computer Science (Q.M.), University of Toronto, Princess Margaret Hospital and Ontario Cancer Institute (A.D.S.), Toronto, Ontario, Canada M5G 1L6

Address all correspondence and requests for reprints to: Bernard P. Schimmer, Ph.D., Professor, Banting and Best Department of Medical Research, University of Toronto, 112 College Street, Toronto, Ontario, Canada M5G 1L6. E-mail: bernard.schimmer{at}utoronto.ca.


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
ACTH regulates the steroidogenic capacity, size, and structural integrity of the adrenal cortex through a series of actions involving changes in gene expression; however, only a limited number of ACTH-regulated genes have been identified, and these only partly account for the global effects of ACTH on the adrenal cortex. In this study, a National Institute on Aging 15K mouse cDNA microarray was used to identify genome-wide changes in gene expression after treatment of Y1 mouse adrenocortical cells with ACTH. ACTH affected the levels of 1275 annotated transcripts, of which 46% were up-regulated. The up-regulated transcripts were enriched for functions associated with steroid biosynthesis and metabolism; the down- regulated transcripts were enriched for functions associated with cell proliferation, nuclear transport and RNA processing, including alternative splicing. A total of 133 different transcripts, i.e. only 10% of the ACTH-affected transcripts, were represented in the categories above; most of these had not been described as ACTH-regulated previously. The contributions of protein kinase A and protein kinase C to these genome-wide effects of ACTH were evaluated in microarray experiments after treatment of Y1 cells and derivative protein kinase A-defective mutants with pharmacological probes of each pathway. Protein kinase A-dependent signaling accounted for 56% of the ACTH effect; protein kinase C-dependent signaling accounted for an additional 6%. These results indicate that ACTH affects the expression profile of Y1 adrenal cells principally through cAMP- and protein kinase A- dependent signaling. The large number of transcripts affected by ACTH anticipates a broader range of actions than previously appreciated.


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
THE PRINCIPAL function of the adrenal cortex is to produce glucocorticoids and mineralocorticoids—hormones essential for survival. These adrenal hormones regulate a broad range of physiological processes including: ionic balance and pH, cellular metabolism, immune system function, and the response to stress. The pituitary hormone ACTH, a master regulator of adrenocortical function, acutely regulates the synthesis of the corticosteroids—especially the glucocorticoids—by mobilizing cholesterol and delivering it to the inner mitochondrial membrane where it serves as the substrate for CYP11A1 (the cholesterol side chain cleavage enzyme), the first enzyme in the pathway of corticosteroid synthesis. In addition, ACTH regulates cholesterol availability, the synthesis of the enzymes required for steroidogenesis, and the size and structural integrity of the adrenal cortex through a series of actions involving changes in gene expression that occur over many hours. Despite the global effects of ACTH on adrenal structure and function, only a relatively small number of ACTH-regulated transcripts have been identified (1).

The signaling pathways that mediate the actions of ACTH have been studied extensively in a variety of in vitro systems including cell suspensions and primary cell cultures from human, bovine, rat, and mouse adrenal glands and cell lines from minimally deviated tumors such as the mouse Y1 adrenal cell line (2). The consensus of these studies is that the cAMP/protein kinase A signaling cascade mediates most of the effects of ACTH; however, this conclusion is not without debate and other signaling pathways including protein kinase C, Ca2+, cGMP, and MAPK have been implicated as primary or secondary mediators of the steroidogenic actions of the hormone (3, 4, 5). The effects of ACTH on adrenal cell proliferation are especially complex and poorly understood. ACTH added to adrenal cells proliferating in vitro inhibits cell cycle progression, DNA synthesis and mitosis via a cAMP/protein kinase A-mediated process. The growth-inhibitory effects of ACTH appear to mask an underlying proliferative effect, which can be elicited by adding the hormone as a pulse to cells in the early G1 phase of the cell cycle. The proliferative effect of ACTH is not mediated by the cAMP/protein kinase A pathway; rather it appears to act via a protein kinase C-activated MAPK (Erk1/2) signaling cascade (6).

The identification of only a limited number of ACTH-regulated transcripts and the persistent debate over the central importance of cAMP and protein kinase A in ACTH action prompted us to undertake a global assessment of ACTH action using the Y1 mouse adrenocortical tumor cell line as a model system. Probing the National Institute on Aging (NIA) 15K mouse cDNA microarray (7) for genome-wide changes in mRNA expression, we demonstrate that ACTH affected the accumulation of 1275 annotated transcripts on the array. Most of these transcripts had not been identified as ACTH responsive previously. Transcripts up-regulated in response to ACTH included a subset with functions in steroid biosynthesis and metabolism; transcripts that were down-regulated in response to ACTH included subsets with functions in RNA processing and cell proliferation. These subsets, however, accounted for only a small fraction of the global response to ACTH. The majority of the effects of ACTH on RNA accumulation could be accounted for by activation of the cAMP/protein kinase A pathway, whereas the protein kinase C pathway made a much smaller contribution. Approximately 38% of the ACTH-affected transcripts could not be ascribed to either pathway and are thus candidates for regulation via other signaling pathways.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Cells, cell culture, and RNA isolation
The origin and properties of the ACTH-responsive Y1 mouse adrenocortical tumor cell line used in this study (clone Y1BS1) have been described previously (2). Clone Kin8 is a mutant derivative of Y1BS1 that harbors a dominant inhibitory point mutation in the regulatory subunit of the type 1 enzyme, which renders protein kinase A resistant to activation by cAMP (8, 9). Clone Kin8Cev is a derivative of Kin8 with restored cAMP-responsive protein kinase activity as a consequence of transfection with an expression vector encoding the catalytic subunit of protein kinase A (10). Cells from each clone were plated at a density of 2 x 106 cells/100-mm tissue culture dish, propagated for 3 d in {alpha}MEM as described (11) and treated with ACTH1–24 (Organon Inc., West Orange, NJ) or other pharmacological agents for 24 h as specified. Cells were harvested by scraping in a guanidine thiocyanate buffer and total RNA was isolated by centrifugation through a cushion of 5.7 M CsCl (12). Because there was no evidence of DNA contamination of the RNA in RT-PCR experiments, deoxyribonuclease treatment was considered unnecessary.

Microarray analyses
Transcription profiles were determined by probing cDNA microarrays with Cy3-and Cy5-labeled cDNA prepared from total RNA using a two-color dye hybridization protocol (13). The microarrays and the protocols for labeling of transcripts were obtained from The University Health Network Microarray Centre (Toronto, Ontario, Canada), details of which are available at www.microarrays.ca. Essentially, total RNA (50 µg) was reverse-transcribed using Superscript II according to the supplier’s instructions (Invitrogen Canada, Burlington, Ontario, Canada) in a reaction (40 µl) that included oligo-dT20-dVdN (150 pmol) as primer and Cy3-deoxy (d)-CTP or Cy5-dCTP (25 µM; Invitrogen Canada) as labeling reagent. The fluorescently labeled cDNAs from mock-treated and agonist-treated cells were combined, purified by precipitation with isopropanol, resuspended in 5 µl of nuclease-free water, and used immediately for microarray analysis. A cocktail containing 100 µl digoxygenin Easy Hyb solution (Roche Diagnostics, Laval, Quebec, Canada), 5 µl yeast tRNA (10 mg/ml; Invitrogen Canada) and 5 µl salmon sperm DNA (10 mg/ml; Sigma/Aldrich Canada, Oakville, Ontario, Canada) was added to the fluorescently labeled cDNAs and aliquots of this solution (85 µl) were applied to the microarray slides under coverslips. Slides then were incubated overnight at 37 C in a sealed humidified chamber, washed successively with 1x saline sodium citrate/0.1% sodium dodecyl sulfate at 50 C (three times), 1x SCC at room temperature (twice) and 0.1x SCC (once) and dried by centrifugation. Cy3 and Cy5 signals on the array were quantitated using an Axon GenePix 4000A laser scanner and Axon GenePix software (Molecular Devices, Downingtown, PA). On-slide data analyses, including the assignment of the Cy3 and Cy5 signals to specific cDNAs on each array and the application of the Lowess smoothing function to correct for global differences in Cy3 and Cy5 incorporation were performed with GeneTraffic software (Stratagene, La Jolla, CA). Annotations for the cDNAs spotted on the arrays were retrieved from the Stanford Online Universal Resource for Clones and ESTs (S.O.U.R.C.E.) database (http://genome-www5.stanford.edu/cgi-bin/SMD/source/sourceSearch) in March 2005; only those changes affecting well-annotated transcripts are reported here.

Quantitative RT-PCR
Transcripts were quantitated by RT-PCR using the 7300 Real Time PCR System with resident software (Applied Biosystems, Foster City CA). Total RNA (5 µg) was reverse transcribed as above in 20-µl reactions containing oligo-dT18 primer (100 pmol). Aliquots of the RT reaction (1 µl) were amplified over 40 cycles in 25-µl reactions containing gene-specific forward and reverse primers (5 pmol each; Table 1Go) and the double-stranded DNA binding dye SYBR Green I as provided in the Platinum SYBR Green qPCR SuperMix UDG system (Invitrogen Canada). In each amplification cycle, samples were heated at 95 C for 15 sec to denature the template and incubated at 60 C for 60 sec for 40 cycles to anneal and extend the gene-specific primers. The identity and purity of the resultant PCR products were confirmed by the uniformity of dissociation curves obtained from the amplified products after the quantitative PCR cycles and by electrophoresis of the amplified product before and after digestions with diagnostic restriction endonucleases. Transcript concentrations were determined by comparing the threshold cycle obtained for each transcript to the threshold cycles obtained with cDNA standards and normalizing the data to the levels of transketolase RNA; as determined by quantitative RT-PCR, the levels of transketolase did not change under these conditions of treatment (data not shown).


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  		TABLE 1. Gene-specific primers used for quantitative RT-PCR

 
Statistical analyses
For microarray data, the effects of treatment on the relative abundance of individual transcripts were evaluated using a two-class (unpaired) analysis which compared the ratios of Cy3 to Cy5 signals obtained using RNA from replicate treated and control cells, respectively, to the ratios of signals obtained using RNA samples from a group of independent control cells (n = 6) separately labeled with Cy3 and Cy5. The two-class analysis controls for gene-specific variances in the data—e.g. variances caused by preferential labeling of transcripts with either the Cy3 or Cy5 dye (14). In experiments where hypothesis testing involved responses to single agonists, significantly affected transcripts (up-regulated and down-regulated) were identified using the SAM (Statistical Analysis of Microarray) algorithm (15) with a false discovery rate (FDR) cutoff at 0.05. In those experiments where hypothesis testing involved responses to multiple agonists and different cell lines, e.g. identification of cAMP/protein kinase A-regulated transcripts, P values for each transcript under the different test conditions were combined using the multiple univariate combination method of Fisher (16), and the FDR was determined using the Benjamini-Hochberg procedure (17).

The set of transcripts significantly affected by ACTH in microarray experiments (FDR < 0.05) was tested for enrichment in specific categories relative to the representation of these categories on the NIA 15K mouse cDNA array using Fisher’s exact test. Transcripts were categorized according to Gene Ontology (GO) Biological Process (BP), GO Molecular Function (MF), and tissue enrichment based on data compiled previously (18, 19). The GO hierarchy was downloaded from the Gene Ontology database (20), and mouse gene annotations were downloaded from Mouse Genome Informatics (MGI). The gene symbols corresponding to the annotated genes on the NIA 15K mouse cDNA array were mapped to MGI IDs downloaded from the MGI Database in June 2005 (18). The MGI GO annotations were augmented to include all those implied by annotations in a more specific category. In the GO analysis, categories with fewer than ten genes were excluded based on a statistical power analysis, and those with more than 200 genes were excluded because they were not specific to distinct physiological processes or molecular functions. Probes assigned XM IDs in the Zhang et al. study (19) were mapped to MGI marker IDs in two steps. First, the 60-oligomer probe sequences were mapped to the GenBank sequences associated with each MGI marker using BLAT [BLAST (basic local alignment and search tool)-like search tool] (21). A FASTA file containing the GenBank sequences and a database report associating MGI marker IDs with these sequences were downloaded from MGI in June 2004. A probe was deemed a hit to a GenBank sequence if BLAT reported a match between them at least 20 bp in length, with no insertions or deletions and no more than one mismatching nucleotide. A probe was deemed a match to a MGI marker if it satisfied three criteria: it hit at least one of the GenBank sequences associated with the marker, it hit no sequence associated with a different marker, and it was the only probe that satisfied the first two criteria for the marker. A list of the XM ID to MGI marker ID matches can be found on our web site at http://www.utoronto.ca/schimmer/supplements/supplements.html.

For quantitative RT-PCR experiments, statistical significance among group means was determined using Peritz’s multicomparison F test (22).


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
ACTH regulated transcripts in the Y1 mouse adrenocortical cell line
Transcripts isolated from Y1 mouse adrenocortical cells stimulated with ACTH1–24 (20 nM) and from mock-treated controls were differentially labeled with Cy3- and Cy5-dCTP and compared by microarray analysis to identify ACTH-induced changes in RNA accumulation. A representative experiment (Fig. 1Go) demonstrates the effects of ACTH on the expression profile of Y1 adrenal cells. Cy3- and Cy5-labeled cDNA pools from mock-treated Y1 cells produced signals at 5412 of the 5655 unique annotated cDNAs on the NIA 15K mouse cDNA array that were, for the most part, tightly clustered around a log2 ratio of 0. The greatest variance in ratios of Cy3- and Cy5-labeled transcripts from the control set was seen among weakly labeled genes where signal to noise ratios were lower and variations were random and not gene specific. In contrast, the log2 signal intensity ratios obtained comparing labeled cDNAs from ACTH-treated and untreated Y1 cells deviated from 0 for a subset of genes regardless of labeling intensity, reflecting transcripts that either increased or decreased after treatment. The results of replicate experiments (n = 6) were analyzed for ACTH-induced changes using the SAM algorithm from Stanford University (15) with a FDR cut-off set at 0.05. ACTH significantly affected the expression of 1275 of these annotated transcripts—i.e. 23.5% of the transcripts represented on the array—of which 588 increased in response to the hormone and 687 decreased. Responses to ACTH ranged from 8.7-fold to 0.46-fold relative to unstimulated controls (supplemental Table 1 published on The Endocrine Society’s Journals Online web site at http://endo.endojournals.org). Among the ACTH-regulated transcripts were 19 that had been identified previously as ACTH-responsive using other methods (Table 2Go).


Figure 1
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  		FIG. 1. Effects of ACTH on transcript accumulation in Y1 adrenal cells. A and B, Total RNA was isolated from mock-treated Y1 mouse adrenocortical tumor cells and from Y1 cells treated with ACTH1–24 for 24 h (A) or from two different batches of mock-treated Y1 cells (B) and reverse transcribed in the presence of Cy5- and Cy3-dCTP, respectively. The labeled cDNAs were combined and hybridized to the NIA 15K mouse cDNA microarray and quantitated for dye incorporation as described in Materials and Methods. Results are expressed as the average log2 ratio of the intensities of the Cy3 and Cy5 signals for each transcript vs. the log2 product of the intensities/2, a measure of the intensity of the combined signals. The red line indicates the best fit of the data after normalization using the Lowess smoothing function; the red and green crosses indicate transcripts that increased and decreased after ACTH treatment respectively. C, Comparisons of ACTH-affected transcripts with transcripts corresponding to signatures of the cAMP/protein kinase A- and protein kinase C-dependent signaling pathways. Results were compiled from data in supplemental Tables 1–3; the numbers correspond to the number of affected transcripts in each category. PKA, Protein kinase A; PKC, protein kinase C.

 

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  		TABLE 2. ACTH-induced changes confirmed by microarray analysis

 
Quantitative analysis of ACTH-regulated transcripts
Several ACTH-regulated transcripts and several transcripts that were not significantly affected by ACTH on the microarrays were selected for further examination by quantitative RT-PCR (Table 3Go). These experiments confirmed that ACTH increased the accumulation of transcripts encoding Cyp11a1, Nr5a1, Mc2r, Sat1, Ptp4a3, Inha, Alas1, Hmox1, Ftl1, and Tfrc and decreased the levels of Alad, Avpr1, Fech, and MaoA. Except for the larger fold-changes that seemed dampened on the microarrays, the changes in transcript levels determined using the microarrays correlated with the changes measured by quantitative RT-PCR (P ≤ 0.003 overall). For some of these transcripts, the maximal effects of ACTH were seen within 4 h of stimulation; for others, 24 h of stimulation was required to achieve a statistically significant effect. An exception was Hmox2, which showed no response to ACTH when assayed by quantitative RT-PCR, but which exhibited a 29% increase after ACTH treatment when tested against the 15K mouse cDNA array. This disparity may have resulted from a false-discovery error or from cross-hybridization of Hmox1 transcripts to regions of similarity in the arrayed Hmox2 cDNA. Inasmuch as the microarray data included several ACTH-regulated transcripts linked to heme and iron metabolism, quantitative RT-PCR was used to evaluate several other transcripts involved in heme metabolism or iron homeostasis that seemed unaffected by ACTH on the microarrays. Quantitative RT-PCR confirmed that ACTH did not affect the levels of the other transcripts with functions in heme biosynthesis, i.e. Hmbs, Urod, Uros, Cpox, and Ppox, nor did it affect the levels of Fth1.


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  		TABLE 3. Measurements of ACTH effects on transcript accumulation by quantitative RT-PCR

 
Functional enrichment of the ACTH-regulated transcripts
The ACTH-affected transcripts identified by microarray analysis were analyzed for specific biological processes and molecular functions using GO-BP and GO-MF annotations (20) assigned to these transcripts by MGI (18). Of the 1275 affected transcripts, 1065 had GO-MF annotations; 999 of these also had GO-BP annotations (supplemental Table 1). The ACTH-regulated transcripts were deemed enriched for a specific function when the number of transcripts associated with each function was greater than the number that might be expected from random chance. Considered as a whole, the 1275 transcripts were not significantly enriched for any GO-BP category relative to their representation on the array. When the up-regulated and down-regulated transcripts were considered separately, the transcripts that increased in response to ACTH were significantly enriched (FDR < 0.05) only for those with functions in steroid biosynthesis and metabolism. Table 4Go lists the 14 transcripts from the ACTH-regulated set that were assigned to these pathways on the basis of GO-BP annotations. An additional nine ACTH-regulated transcripts involved in steroid biosynthesis and metabolism but not identified as such in the Gene Ontology database are also included in Table 4Go. The transcripts down-regulated in response to ACTH were significantly enriched (FDR < 0.05) for those with functions in DNA replication and aspects of cell division including cell cycle regulation and for those with functions in of RNA processing, including mRNA processing and RNA splicing and nuclear transport (Table 5Go). A total of 133 different transcripts were represented in the categories above. None of the up-regulated transcripts were enriched for functions in GO-MF categories. The down-regulated transcripts were enriched for functions in the GO-MF category structural constituent of ribosome (GO:0003735), likely a manifestation of the growth-inhibiting effect of ACTH (23); and for functions in the GO-MF category isomerase activity (GO:0016853), particularly those associated with protein folding. A total of 55 different transcripts were represented in these GO-MF categories (data not shown).


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  		TABLE 4. Functional annotations of up-regulated transcripts

 

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  		TABLE 5. Functional annotations of down-regulated transcripts

 
Comparison of the set of ACTH-regulated transcripts with transcript profiles characteristic of 55 different mouse tissues
Transcripts characteristic of each of 55 different mouse tissues, including the adrenal gland, were defined as transcripts that were more abundant in the tissue queried than in any of the 54 other mouse tissues surveyed based on a tissue-profiling study of mouse gene expression (19). We queried the set of transcripts affected by ACTH in Y1 adrenal cells against the profiles of the 55 different tissues represented in the NIA 15K mouse cDNA array and found that the up-regulated set was significantly enriched (P < 0.0001, Fisher’s exact test) for transcripts most abundant in the adrenal gland but not for transcripts most abundant in any of the other 54 tissues. Of the well-annotated transcripts on the NIA 15K mouse cDNA array, 41 were considered to be characteristic of the adrenal gland by these criteria; 14 of these were up-regulated by ACTH and are listed in Table 6Go. The transcripts that were down-regulated in response to ACTH contained a subset of 130 that were characteristic of embryonic tissues at different stages of development and a subset of 13 that were characteristic of bone marrow. A large proportion of these (45%, P ≤ 0.00025) were associated with the categories represented in Table 5Go—including DNA replication, cell division, and cell cycle regulation, RNA processing and RNA splicing—possibly reflecting the proliferative activities inherent in these tissues (data not shown).


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  		TABLE 6. Transcripts up-regulated by ACTH that are characteristic of the mouse adrenal gland

 
Protein kinase C-regulated transcripts
To identify protein kinase C-affected changes in RNA accumulation, Y1 adrenal cells were treated with the protein kinase C activator phorbol 12-myristate 13-acetate (PMA) (0.1 µM, n = 6), with 4-{alpha}-PMA (0.1 µM, n = 4), a PMA epimer that does not activate protein kinase C or with PMA in the presence of the protein kinase C inhibitor GF109203X (2 µM, n = 4; Ref.24). These concentrations of activator and inhibitor maximally affected protein kinase C activity in Y1 adrenal cells (Wang, L., and B. P. Schimmer, unpublished observations). The effects of the various treatments on transcript accumulation were analyzed using the NIA 15K mouse cDNA microarray and significant changes were calculated using the SAM algorithm. PMA affected the levels of 514 annotated transcripts on the array. More than 80% of these—i.e. 419 (328 up-regulated, 91 down-regulated)—fulfilled our additional experimental criteria for a protein kinase C- regulated data set—i.e. unaffected by 4-{alpha}-PMA and unresponsive to PMA in the presence of the protein kinase C inhibitor GF109203X (supplemental Table 2).

cAMP-regulated and protein kinase A-dependent transcripts
To identify transcripts regulated via the cAMP/protein kinase A pathway, Y1 adrenal cells were stimulated with forskolin (10 µM, n = 6) or 8BrcAMP (3 mM, n = 6), two different effectors of the cAMP pathway, and global changes in transcript levels were assessed using the NIA 15K mouse cDNA array. Similar experiments (n = 4) were carried out with a protein kinase A-defective mutant derivative of the Y1 cell line (clone Kin8) and a Kin8 transformant with restored cAMP-responsive protein kinase A activity (Kin8Cev) to test the dependence of these changes on protein kinase A. The results obtained under each experimental condition were combined and used to construct a set of transcripts affected at a FDR ≤ 0.05 (see Materials and Methods). This analysis identified 1569 transcripts that responded to agonists of the cAMP/protein kinase A pathway in parent Y1 cells and in the Kin8Cev transformant. Of these, 99%—i.e. 1554 transcripts (922 up-regulated and 632 down-regulated)—were resistant to forskolin in mutant Kin8 cells and thus fulfilled our criteria of a cAMP/protein kinase A-regulated pathway (supplemental Table 3). Included in this list were 194 transcripts (12.5%) that were similarly affected by protein kinase C-dependent signaling (Fig. 1CGo).

Contributions of the cAMP/protein kinase A and protein kinase C signaling pathways to ACTH action
The 1275 transcripts affected by ACTH included 563 that only met the criteria for cAMP/protein kinase A-dependent regulation, 71 that only met the criteria for protein kinase C-dependent regulation and 152 that were common to both signaling pathways (Fig. 1CGo). Approximately 38% of the ACTH-regulated transcripts were not assignable by these criteria and are candidates for regulation via other signaling pathways. The global effects of ACTH thus appeared to overlap to a much greater extent with the cAMP/protein kinase A pathway than with the protein kinase C pathway, and this preferential association of ACTH action with cAMP/protein kinase A-dependent signaling was mirrored in the subsets of ACTH-regulated transcripts linked to specific biological processes (Tables 4Go and 5Go) and to transcripts most abundantly expressed in the adrenal gland (Table 6Go).


   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
In vivo, the continuous exposure of the adrenal cortex to ACTH and other proopiomelanocortin-derived peptides has a tonic effect on gene expression that is essential for the maintenance of its steroidogenic machinery, steroidogenic capacity, cellular architecture, and size (25, 26). In isolated adrenal cells and in adrenal cell cultures maintained in the absence of ACTH, this tonic effect is manifested by the coordinate induction of the enzymes and other proteins required for steroidogenesis upon addition of the hormone. In this study, the global actions of ACTH and other agonists on RNA accumulation were assessed in the Y1 mouse adrenocortical cell line, a widely used experimental system that shares many features associated with normal cells from the mouse adrenal cortex (2). Cells were stimulated with 20 nM ACTH, and effects were measured after a 24-h stimulation. This concentration of ACTH maximally activates cAMP and MAPK signaling (27, 28) and produces maximum effects on steroidogenesis (28), proliferation (29), and Odc1 induction (30); the 24-h time period was chosen because the hormone is known to have a delayed inductive effect on most genes involved in steroidogenesis and because much of the work published previously has used similar time points of induction (e.g. Ref.25). As determined by quantitative RT-PCR (Table 3Go), the ACTH-induced changes reported here included both intermediate- and late-onset effects.

In the Y1 adrenal cell line, ACTH affected the levels of 1275 different transcripts, a number limited in part by the annotated genes represented on the NIA 15K mouse cDNA array. For example, Cyp11b1, Cyp11b2, and Cyp21a1, ACTH- regulated transcripts required for corticosteroid biosynthesis in the mouse, were not part of the annotated set on the array and thus were not examined in this study. Although previous studies of ACTH action, for the most part, have focused on up-regulated transcripts (25), our experiments indicate that approximately half of the affected transcripts decreased in concentration after treatment with the hormone. Whether these global effects of ACTH are due to changes in gene expression or RNA stability cannot be distinguished on the microarrays. Most of the 1275 affected transcripts have not been documented as ACTH-responsive previously and their contributions to hormone action merit further investigation. For a vast majority of affected transcripts, the ACTH-induced changes detected by microarray analysis were 2-fold or less (Table 3Go and supplemental Table 1). Part of this is due to the documented tendency of the microarray analysis to underestimate the fold-changes in transcript accumulation (31, 32). Nonetheless, the data suggest that an appreciable portion of ACTH action may involve relatively small changes in transcript accumulation that are usually overlooked in other types of experiments but that have been shown to be of physiological significance in other settings (e.g. Ref.33).

One way to predict functions of transcripts within large data sets is to identify clusters that are associated with specific biological processes or molecular functions (20), an approach that uses the coordinate expression of functionally related transcripts to predict pathway-specific regulatory networks (e.g. Ref.34). Not surprisingly, the set of transcripts that increased in response to ACTH included transcripts with functions in steroid biosynthesis and metabolism, including cholesterol synthesis, cholesterol mobilization, and steroid hormone biosynthesis. Some of these had been described as ACTH-responsive previously (Table 2Go); most, however, had not, thus indicating that ACTH plays a more extensive role in maintaining adrenal steroidogenic capability than previously appreciated. A second approach is to identify transcripts that are abundant in specific tissues because they tend to be enriched for functions typically associated with those tissues (19). The transcripts up-regulated in response to ACTH included a cluster of 14 that was most abundantly expressed in the adrenal gland compared with 54 other tissues examined (Table 6Go). Whereas adrenal gland-specific transcripts might be derived from both the steroidogenic and nonsteroidogenic portions of the gland, the 14 up-regulated by ACTH are likely to be specific to the adrenal cortex and, by inference, important for steroidogenesis. Indeed, the contributions of four members of this group—Nr5a1, Star, Bzrp, and Hsd3b1—to steroidogenesis have already been documented (Table 4Go). Although the contributions of the remaining 10 members to adrenal function have not been investigated, it is possible to speculate on the roles of a few. Alas1 is the rate-limiting enzyme in heme biosynthesis and may serve to maintain a supply of heme for the prosthetic groups of the steroidogenic cytochrome P450s that are induced in response to ACTH. This hypothesis is supported by previous observations indicating that heme availability limits adrenal corticosteroid biosynthesis (35). Fads1 (36), Pank3 (37), and Mod1 (38) are all involved in aspects of intermediary metabolism, and in this general capacity may generate reduced nicotinamide adenine dinucleotide phosphate, a cofactor required for the mixed function oxidase activities of the steroidogenic cytochromes.

The transcripts that decreased in response to ACTH had functions that clustered to aspects of cell proliferation, including DNA replication, mitotic cell cycle, and cell division, and to aspects of RNA processing and nuclear transport. The down-regulation of transcripts associated with cell proliferation seems consistent with the known growth-inhibitory actions of ACTH on cells of the adrenal cortex (e.g. Ref.8); however, the extent to which these changes were directly responsible for the growth-inhibitory effects of the hormone is uncertain. The effects of ACTH on transcripts with functions in RNA processing including RNA splicing are especially intriguing. Alternative splicing of precursor mRNA is thought to affect between one and two thirds of mouse genes and to greatly expand the number of proteins encoded by the mouse genome. Alternative splicing can influence protein function, protein-protein interactions, cell proliferation and other aspects of cell regulation independent of gene expression (39). Although effects of ACTH on alternative splicing have not been demonstrated directly, recent findings that ACTH down-regulates hnrpb1 (one of the pre-mRNA binding proteins involved in alternative splicing) at the protein level in adrenocortical cells (40) lends additional support to this hypothesis.

The ability of ACTH to stimulate cAMP accumulation and activate protein kinase C in Y1 adrenal cells and in adrenocortical cells from a variety of species has been documented (41, 42). In this study, the contributions of the cAMP/protein kinase A and protein kinase C pathways to ACTH action were evaluated using pharmacological probes of each pathway. Together, the ability of ACTH to activate each pathway and the ability of pharmacological agonists to mimic the effects of ACTH are criteria classically used to assess the contributions of second messengers to hormone action (reviewed in Ref.41). Forskolin, a well-characterized activator of most isoforms of adenylyl cyclase including those expressed in the Y1 cell line (43), and the active cAMP analog 8BrcAMP were used to probe the cAMP/protein kinase A pathway. The protein kinase C-dependent signaling cascade was probed using the phorbol ester PMA, a well-characterized activator of most protein kinase C isoforms, including the isoforms ({alpha} and {epsilon}) that are most abundant in Y1 adrenal cells (44). Although these reagents are commonly used activators of their respective pathways, each has other activities (45, 46, 47) that prompted the inclusion of several additional criteria to validate their modes of action. Accordingly, protein kinase A-specific effects of forskolin were further evaluated in a protein kinase A-defective Y1 mutant (clone Kin8) and in a Kin8 transformant with cAMP-responsive protein kinase activity restored. Protein kinase C-specific effects of PMA were assessed with 4-{alpha}-PMA, an epimer that has the same physicochemical properties as PMA but is unable to activate protein kinase C, and GF109203X, an inhibitor that affects the actions of PMA on protein kinase C but not on other PMA receptors (47). By these criteria, activators of the cAMP/protein kinase A signaling pathway affected a much larger number of transcripts than did activators of the protein kinase C pathway in the adrenal cell line and signaling via the cAMP/protein kinase A pathway accounted for over 55% of the global effects of ACTH on gene expression, whereas signaling via the protein kinase C-dependent pathway was much less important. Indeed, only 6% of ACTH action could be assigned specifically to the protein kinase C signaling pathway (Fig. 1CGo).

Despite the ability of ACTH to activate the cAMP/protein kinase A-signaling cascade, the hormone affected only 45% of the transcripts comprising the signature of the cAMP/protein kinase A pathway (Fig. 1CGo). The most likely explanation for the inability of ACTH to reproduce the complete cAMP/protein kinase A signature may be related to the inability of ACTH to sustain the cAMP/protein kinase A signal. After a relatively brief exposure to ACTH, desensitization sets in and cAMP levels fall due to an uncoupling of the ACTH receptor from the adenylyl cyclase system. In contrast, pharmacological agonists of the cAMP/protein kinase A pathway act downstream of this step and have activities that are more sustained (48).

Together, the cAMP/protein kinase A and protein kinase C pathways appeared to account for approximately 60% of the effects of ACTH. It is possible that we have underestimated the contributions of these two pathways to ACTH action due to limitations of the pharmacological probes in these studies as noted above or by the restrictive criteria used to identify each signature. For example, the cAMP/protein kinase A signature is derived from a statistical analysis that is designed to reduce type 1 errors when combining the results of the four different tests used to define this pathway. While providing a level of certainty regarding the cAMP/protein kinase A signature, this approach may underestimate the total number of transcripts assigned to this pathway. In addition, differences in the mechanisms of action of forskolin and 8BrcAMP, phenotypic variations between Y1 and Kin8Cev cells and residual cAMP-dependent protein kinase activity in the Kin8 mutant (8) may lead to the inappropriate exclusion of some transcripts from the cAMP/protein kinase A signature. Two such transcripts, Cyp11a1 and Odc1, had markedly compromised levels of basal and cAMP-stimulated expression in the Kin8 mutant in Northern blot experiments (49, 50) but were excluded from the cAMP/protein kinase A signature on the basis of a residual response in the Kin8 mutant that was detectable in the microarray experiments. Alternatively, the possibility that other signaling pathways mediate the actions of ACTH on selected transcripts cannot be excluded.

Because Y1 adrenal cells do not express Cyp21a1 (51), they do not synthesize corticosterone and instead produce the physiologically inactive metabolites 20{alpha}-hydroxyprogesterone and 11ß-20{alpha}-dihydroxyprogesterone in response to ACTH (reviewed in Ref.2). Thus, it is unlikely that these steroid products contribute to the effects observed here. It is nonetheless possible that other tertiary messengers act downstream of the cAMP/protein kinase A pathway to mediate the effects of ACTH as reviewed elsewhere (3, 4, 5). Although our studies have not addressed the contributions of tertiary messengers to these global actions of ACTH, our ACTH-regulated data set includes a number of transcripts involved in transcription control and in cell signaling (supplemental Table 1), some of which may act down-stream of ACTH to influence the expression profile of these cells.

The results presented here provide a reference set of ACTH-affected transcripts and reference signatures of the cAMP/protein kinase A and protein kinase C signaling pathways. These should provide useful starting points for more detailed studies on the scope of ACTH action in the adrenal cortex and on the signaling pathways that mediate the hormone’s effects. Our observation that ACTH affects the accumulation of a large number of transcripts suggests that the hormone causes a significant remodeling as the cells switch from the basal to hormone-stimulated state.


   Acknowledgments
 
We thank Aled Edwards (University of Toronto, Toronto, Canada) for access to the GeneTraffic software package, and Benjamin Blencowe (University of Toronto, Toronto, Canada) for helpful discussions.


   Footnotes
 
This work was supported by the National Cancer Institute of Canada with funds from the Canadian Cancer Society and by The Canadian Institutes of Health Research through research grants (to B.P.S.).

Current address for A.B.G.: Systems Biology Group, Bioinformatics Institute, Singapore

Annotations for gene symbols, including gene names, can be retrieved from the Stanford Online Universal Resource for Clones and ESTs (S.O.U.R.C.E.) database (http://genome-www5.stanford.edu/cgi-bin/SMD/source/sourceSearch).

The supplemental information provided with this article is also available on our web site at http://www.utoronto.ca/schimmer/supplements/supplements.html.

M.C. and A.T. have nothing to declare. H.C. carried out this work while an employee of the University of Toronto; currently he is employed by Pfizer Canada Inc. B.P.S. receives royalties from McGraw-Hill Inc. for his contributions to Schimmer BP, Parker KL 2005 Adrenocorticotrophic hormone; adrenocortical steroids and their synthetic analogs; inhibitors of the synthesis and actions of adrenocortical hormones. In: Brunton L, Lazo J, Parker K, eds. Goodman and Gilman’s the pharmacological basis of therapeutics. 11th ed. New York: McGraw-Hill, Inc.; 1587–1612.

First Published Online February 16, 2006

Abbreviations: BLAT, BLAST (basic local alignment and search tool)-like alignment tool; CYP11A1, cholesterol side chain cleavage enzyme; FDR, false discovery rate; GO, Gene Ontology; GO-BP, GO Biological Process; GO-MF, GO Molecular Function; MGI, Mouse Genome Informatics; PMA, phorbol 12-myristate 13-acetate; SAM, Statistical Analysis of Microarrays.

Received December 2, 2005.

Accepted for publication February 8, 2006.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

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