Genetic Profiling Defines the Xenobiotic Gene Network Controlled by the Nuclear Receptor Pregnane X Receptor
John M. Rosenfeld,
Reynaldo Vargas, Jr.,
Wen Xie and
Ronald M. Evans
The Salk Institute for Biological Studies (J.M.R., R.M.E.), Gene Expression Laboratory, Howard Hughes Medical Institute (R.M.E.), La Jolla, California 90237; and Center for Pharmacogenetics (W.X.), Department of Pharmaceutical Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania 15213
Address all correspondence and requests for reprints to: Ronald M. Evans, The Salk Institute/Howard Hughes Medical Institute, 10010 North Torrey Pines Road, La Jolla, California 92037. E-mail: evans{at}salk.edu.
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ABSTRACT
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The orphan nuclear receptor pregnane X receptor (PXR) is essential for the transcriptional regulation of hepatic xenobiotic enzymes including the cytochrome 3A isoenzymes. These enzymes are central to the catabolism and clearance of most endogenous sterol metabolites (endobiotics) and a vast diversity of foreign compounds (xenobiotics) including pharmaceuticals, pesticides, and toxins encountered through diet and environmental exposure. To explore a broader role of PXR in the mammalian xenobiotic response, we have conducted a unique microarray gene profiling analysis on liver samples derived from PXR knockout mice and mice expressing a constitutively active variant, VP-hPXR. This genetically guided expression analysis enables targeting and restriction of the PXR response to liver, and is devoid of side effects resulting from drugs and their metabolites. As with pharmacological studies, receptor-dependent genes include both phase I and phase II metabolic enzymes, as well as certain drug and anion transporters as principal PXR targets. Moreover, comparative analysis of data from both genetic and pharmacological arrays reveals a core network that represents a genetic description of the xenobiotic response.
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INTRODUCTION
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THE INDUCTION OF cytochrome P450 (CYP) and other phase I monooxygenases by endo- and xenobiotic compounds defines the prototypical primary hepatic response in rodents and humans (1). These xenobiotics include rifampin, phenobarbital, natural or synthetic steroids, bile acids, industrial pesticides, and numerous classes of chemical inducers. This hepatic response provides an unusual biochemical and molecular interface between mammalian physiology, pharmacology, and toxicology. The nuclear receptors pregnane X receptor (PXR) and constitutive androstane receptor (CAR) were originally established as xenosensors that regulate the genes encoding the CYP3A and CYP2B oxidative enzymes, respectively (2, 3, 4). The biochemical activities of these enzymes are primarily responsible for the metabolic inactivation and subsequent clearance of most pharmaceuticals including statins, thiazolidinediones, and chemotherapeutic agents. PXR, a broad specificity nuclear receptor, can be activated in a ligand-dependent fashion by numerous structurally diverse endo- and xenobiotics (5). CAR, while exhibiting constitutive transcriptional activity in cultured cells, is activated in vivo by cytoplasmic to nuclear translocation in response to treatment with phenobarbital, or the derivative 1,4-bis[2-(3,5-dichloropyridiloxy)]benzene (TCPOBOP) (6, 7). The activity of CAR may also be affected by the presence of endogenous steroid metabolites (8, 9). In addition to distinct differences in the activation of these receptors, they bind distinct but partially overlapping consensus DNA response elements. However, the true extent of the overlap of genomic domains controlled by PXR vs. CAR has not been systemically examined.
To characterize the genetic and physiological domains of these receptors, we and others have generated transgenic knockout (KO) mice for both PXR and CAR (10, 11, 12, 13). As expected, PXR null animals are largely deficient in responding to PXR specific inducers such as pregnenolone carbonitrile (PCN) or dexamethasone (DEX) treatment. CAR-specific and PXR/CAR dual agonists retain their CAR-mediated effects in PXR null animals. We have also "humanized" these mice by introducing transgenes to direct hepatic expression of either the full-length human PXR, or a transcriptionally active variant, termed VP-hPXR. In the VP-hPXR mice, prototypical PXR target genes are constitutively up-regulated (11). These animals provide invaluable tools to identify and characterize the PXR-specific genetic network. Given the difficulty and variability in producing primary cultured hepatocytes combined with the nonhepatic properties of immortalized liver cell lines such as HepG2, the in vivo assessment of activation of the receptor provides a physiologically relevant approach to identifying xenobiotic target genes. Furthermore, use of the constitutively activated VP-hPXR transgene avoids employment of drug activation, which harbors many variables including production of metabolites, frequency of dosing, route of delivery, effective concentration of drugs, receptor independent actions of drugs, hepatic toxicity (i.e. PCN), and pan-receptor activity of certain compounds, such as DEX. For example, various bile acid metabolites can directly activate at least three nuclear receptors, farnesoid X receptor (FXR)/bile acid receptor, PXR, and the vitamin D receptor (VDR), all of which are expressed in the enterohepatic axis (10, 14, 15, 16, 17, 18).
Use of the genetically activated receptor avoids many of the above problems to create a pharmacologically unbiased profiling data set. As expected, the resulting expression data identify broad components of xenobiotic phase I and II response genes, as well as novel targets that may facilitate phase III endo and xenobiotic elimination. Comparison of the genetically derived data to chemical agonist profiles identifies both new putative target genes, as well as subtle differences in regulation of previously known PXR and CAR gene targets. Our data set also considerably illuminates the roadmap of PXR and CAR specific and overlapping gene targets, further defining the xenobiotic metabolic network.
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RESULTS
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Expression Profiling of VP-hPXR Gain-of-Function Mice
To search for genes affected by PXR activation, we pooled total hepatic RNA from age-matched adult male nontransgenic or VP-hPXR transgenic mice in the mouse PXR (mPXR)+/+ or PXR null background (Fig. 1A
) (11). Two color cDNA microarray comparisons on a collection of approximately 8700 sequence verified IMAGE clones were performed, using fluororeversal confirmation to select differentially expressed clones (see Materials and Methods). Comparisons were performed with first-strand cDNA probes generated from nontransgenic vs. albumin driven VP-hPXR transgenic liver mRNA samples, as well as between liver mRNAs from PXR null mice in the absence vs. presence of VP-hPXR transgene.

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Figure 1. cDNA Expression Profiling of Wild-Type (WT) and PXRKO Albumin (Alb)-VP-hPXR Livers
A, Northern blot analysis of hepatic total RNA from WT and PXRKO transgenics. Blots were hybridized with mPXR and VP-hPXR probes and are controlled for RNA loading by hybridization to 36B4 ribosomal message. B, Overlap of differentially ESTs between WT and PXRKO animals expressing the VP-hPXR transgene. ESTs that passed conservative criteria for differential expression with fluorophor-reversal are presented. Forty-three ESTs were identified by identical GenBank accession numbers, whereas an additional 14 were included based on overlapping/redundant clone content irrespective of accession number. C and D, Distribution and directionality of 271 unique VP-hPXR differentially expressed genes results in 7 classes of gene behavior. ESTs from B were sorted by fold difference of VP-hPXR expressing livers vs. control (positive and negative) in both WT and PXRKO genetic backgrounds. The relationships and overlapping behavior between these ESTs across both experiments is illustrated in C, with classes of genes assigned a letter af in D. E, Hierarchal clustering of 314 identified ESTs in the microarray comparisons of WT -/+ VP-hPXR and PXRKO -/+ VP-hPXR. Clustering was performed using Genespring 4.2 based upon averaged fold difference values for all ESTs validated by fluorophor-reversal and thresholding at a scaled value of 1.3-fold. Genes shown in red are increased in the presence of VP-hPXR, and genes shown in green are decreased, with intensity of color associated with magnitude of fold difference. The positions of genes from classes af are shown with brackets, and the number of ESTs in each class is shown in parentheses.
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Expression analysis of VP-hPXR in the presence of endogenous mPXR (wild type) produced 168 differentially ESTs, with a roughly equal distribution of positively and negatively affected genes across four spot measurements (97 up and 71 down) (Fig. 1
, B and C). Based upon densitometry of predicted genes that validate by Northern blot, true fold changes are often greater than the averaged fluororeversed data, allowing us to consider genes as low as 1.3-fold (as long as they are confirmed by flurophor reversal). Utilizing this filtering criteria, more than 90% of clones identified as differentially expressed using gene calls from flouroreversal-confirmed data can be both detected and directionally confirmed by Northern hybridization (data not shown). In the mPXR null background, 146 gene tags were differentially expressed due to VP-hPXR presence (56 up and 90 down). Based on GenBank expressed sequence tag (EST) accession numbers, 43 tags were differentially expressed in both PXR+/+ and PXR-/- backgrounds. Approximately 14 additional redundant ESTs were detected in both comparisons when clone identities were assigned, resulting in a true overlap of 57 tags (see the first table in the supplemental data published on The Endocrine Societys Journals Online web site at http://mend.endojournals.org; and see Fig. 1B
). The directional relationships among all of these genes is shown schematically in Fig. 1C
, with each subpopulation (7) of predicted gene hits assigned a class or cluster letter af in Fig. 1D
. Class a and e genes are affected by VP-hPXR expression in both the presence and absence of endogenous mPXR, and are predictively more reliable due to repetition of detection (i.e. increase or decrease in eight of eight spot measurements), whereas classes b, c, f, and g report as differentially expressed in one comparison or the other, but not both. Figure 1E
illustrates hierarchal clustering of the differentially expressed tags from both comparisons, based upon averaged fold differences reported for each individual comparison, and the position of genes within these experiment clusters. There are 17 tags of the d class that are of uncertain significance due to the lack of directional consistency, increasing in response to VP-hPXR in the presence of mPXR but decreasing in its absence.
The predictive quality of the array data was validated by Northern hybridization and densitometry of normalized blots. As an example of the reliability of our cDNA microarray gene profiling system, 12 of 13 (92%) of the genes from class "a" were validated by Northern blot analysis of samples from both comparisons (see Table 1
and Figs. 2
and 3
, data not shown). Because of the stringency of our thresholding and selection criteria, we have observed that our low false positive rate of detection results in an obligate increase in the false negative rate. For example, several genes that reportedly increased by virtue of VP-hPXR expression in the presence of mPXR (wild type) were not detected as increases in the companion data set obtained in the absence of mPXR. However, when analyzed by Northern blot hybridization, these genes were similarly affected in both genetic backgrounds (e.g. CYP3A11). Thus, the differences between microarray reporting of these RNA samples do not necessarily indicate differential response to VP-hPXR in the absence or presence of endogenous mPXR. Tables 1
and 2
describe a subset of genes increased and decreased (respectively) by VP-hPXR expression, with genes that have been validated by Northern hybridization shown in boldface type. The entirety of fluororeverse filtered differential expression data and full array content are supplied in the first and second tables in the supplemental data, respectively, and the raw custom cDNA array data before fluororeversal comparison and filtering is supplied in the remaining tables in the supplemental data.

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Figure 2. VP-hPXR Expression Influences Transcription of Several Phase I Enzymes
A, Northern hybridizations showing induction of CYP phase I enzymes by VP-hPXR. Ten micrograms of total RNA samples of the indicated genotypes were analyzed by Northern blot hybridization to the indicated cDNA mouse probes. All blots were controlled for loading and transfer by visualization of 28S and 18S ethidium bromide stained nylon filters, as well as by hybridization to mouse ribosomal 36B4 (not shown). B, Regulation of other phase I enzymes by VP-hPXR, as validated by Northern blot. ADH3A2, Alcohol dehydrogenase 3A2; Alb, albumin.
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Figure 3. Regulation of Xenobiotic Phase II Enzymes, Transporters, and Lipid Binding Proteins by VP-hPXR
A, Northern blot demonstrating hepatic induction of transcription of phase II enzymes by VP-hPXR expression. Hydroxysteroid preferring STa2, PAPSS2, UGT1a, GSTa4, putative transmembrane protein (PTG). B, Expression of VP-hPXR negatively affects expression of GST 2, D-arabino-1,4-lactone oxidase similar (GULO), and CAR. C, Induction of transcription of various lipid binding proteins and transporters by hepatic VP-hPXR expression. MTTP, Micosomal triglyceride transfer protein; PMBP, progesterone membrane binding protein; ABCB9, ATP-binding cassette, subfamily B [multidrug resistance (MDR)/transporters associated with antigen presentation/processing (TAP)], member 9; Alb, albumin; INSIG2, insulin-induced gene 2.
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Regulation of Phase I CYPs
As expected, transcription of several CYP genes was increased in the VP-hPXR transgenic mice. These include CYP2B10, CYP3A11, and two occurrences of CYP20 (Table 1
). CYP20, an uncharacterized mouse homolog of human CYP-M, is weakly similar on the protein level to mouse CYP4V3 and CYP3A13. Despite the high degree of similarity between mouse CYP3A11 and CYP3A13 (71% amino acid identity, 76% DNA identity throughout coding region), the CYP20 transcript has no significant nucleotide similarity to either of these transcripts. Both CYP20 and CYP2B10, a prototypic CAR target gene that is also responsive to PXR activators, were detected as a class "a" genes (4, 19). Examples of the relative differences among these and other CYPs known to be regulated by PXR are compared by Northern analysis in Fig. 2A
.
Surprisingly, several distinct CYPs reported as decreases when VP-hPXR was present (Table 2
). These include duplicate ESTs encoding CYP4A10 and mouse CYP4V3, as well as a distinct CYP2C44 isoform. The CYP4A family is involved in mitochondrial and peroxisomal ß- and
-oxidation of long chain fatty acids (including steroids and some xenochemicals), and independently, is a known target of peroxisome proliferator-activated receptor
(PPAR
) in the liver (20, 21, 22, 23). CYP2C44 is most similar to human CYP2C19 (62% amino acid identity), and CYP4V3 is most similar to Drosophila 4C3 (48% amino acid identity). Previous reports have shown the CYP2C19 is strongly inhibited by omeprazole treatment, a known CYP3A4 inducer by virtue of PXR activation (24, 25). The CYP4C/4F enzymes have been implicated in pesticide and leukotriene metabolism, and the mouse CYP4F is also a PPAR
target (26, 27). Two other PPAR
target genes, acyl coenzyme A oxidase (decrease) and carnitine-palmitoyl transferase I (increase), were also affected by VP-hPXR expression (Tables 1
and 2
). This metabolic antagonism or cross-regulation has also been observed in several fibrate and bile acid feeding experiments involving PPAR
and presumptive FXR activation, although both the molecular mechanisms and physiological relevance involving this phenomenon are unclear (28, 29).
Esterases and Other Phase I Enzymes Affected by VP-hPXR Expression
In addition to the regulation of CYP enzyme genes, a number of carboxyesterase like ESTs including carboxylesterase 3 (triacylglycerol hydrolase), as well as two carboxyesterase 2 encoding ESTs, were up-regulated (Table 1
and Fig. 2B
). These two esterase proteins are 44% identical throughout their length, and the representative EST sequences exhibit very short regions of weak nucleotide similarity. Esterases such as these are involved in the activation of certain prodrugs as well as metabolism of natural substrates, and at least one related family member (egasyn, esterase 22) is inducible by androgens (30). Interestingly, the ß-D-glucoronidase that associates with egasyn in the microsome is also induced in our data set and is also inducible by androgens (see supplemental data and Ref. 31). While the molecular details of this regulation are unknown, androgen induction of these genes could be exerted either by the androgen receptor directly (present in all samples, data not shown), or possibly by androgen or androgen metabolite activation of PXR. This is relevant because androgens are also substrates for the CYP enzymes discussed above, and we have observed that androstenedione is an efficacious PXR activator (data not shown). The expression of a fourth esterase, male specific esterase 31 was decreased in both comparisons (see Table 2
and Ref. 32). This enzyme is most similar to carboxylesterase 2 (43% amino acid identity). Thus, constitutive hPXR activation has both positive and negative affects on the regulation of multiple classes of phase I enzymes.
A number of dehydogenases were also induced by VP-hPXR expression. These include alcohol dehydrogenase 3A2 [ADH3A2, or fatty aldehyde dehydrogenase (Aldh4)] and aldehyde dehydrogenase 1a7 (Aldh1a7) (Table 1
). Aldh1a7 is phenobarbital inducible and is also known to isomerize retinaldehyde to generate retinoids (33, 34). ADH3A2 is a microsomal oxidoreductase known to be inducible by dioxin and clofibrate (35) (Fig. 2B
). Phase I enzymes negatively affected by PXR activation include flavin containing monooxygenase 5 (FMOC5), as well as multiple occurrences of hydroxysteroid dehydrogenase-4,
<5>-3-ß (HSD3ß4) and hydroxysteroid dehydrogenase-1,
<5>-3-ß (HSD3ß1) (Table 2
). The 3ßHSDs consist of a multigene family of enzymes involved in the conversion of pregnenolone and its metabolites to progesterones and androstenedione. In addition to their sexually dimorphic expression in the liver and kidney, isoforms of this enzyme are likely to be involved in the production of androstane metabolites that may function as PXR and/or CAR ligands (36, 37).
Regulation of Phase II Enzymes
In addition to the phase I targets, a number of phase II conjugating enzymes are also regulated in response to VP-hPXR expression (Table 1
and Fig. 3A
). For example, we found increased expression of hydroxysteroid preferring sulfotransferase 2 (STa2) and 3'-phosphoadenosine 5'-phosphosulfate synthase 2 (PAPSS2). These increases were accompanied by decreased expression of an EST clone related to mouse STa2 (AA277580, 58% over 231 amino acids). PAPSS2 is responsible for production of the organic sulfate donor PAPS that is required for sulfonation. The coregulation of both sulfotransferase isoforms and PAPSS2 suggests that PXR may function as a master regulator for the xenobiotic sulfonation cascade. The expression of uridine diphosphate-glucuronosyltransferase 1A (UGT1A) is also increased in the VP-hPXR mice. Both UGT1A and STa2 are involved in steroid, thyroid and retinoid hormone and drug metabolism, and are subject to detailed analysis in subsequent studies demonstrating direct involvement of PXR (Xie, W., and R. M. Evans, manuscript submitted) (38). We also observed: 1) increased expression of glutathione-S-transferase (GST) a4, but decreased expression of GST
2; 2) increased expression of putative transmembrane protein, a gene that is similar to members of the membrane-bound O-acyl transferase (MBOAT) family; and 3) down-regulation of betaine-homocysteine methyltransferase (Tables 1
and 2
and Fig. 3
, A and B). Collectively, these observations suggest a global impact of VP-hPXR expression upon all branches of phase II metabolism, including regulation of glutathione, glucoronosyl, sulfo-, methyl-, and acyl-transferases.
Interestingly, CAR expression is suppressed by VP-hPXR expression in our samples, whereas PCN (a PXR agonist) was recently described to increase CAR expression (Fig. 3B
, see below) (39). This apparent discrepancy in directional regulation of CAR by PXR may be a consequence of the constitutive signaling that occurs in our transgenic mice because we have also observed positive regulation of CAR by PXR activation in acute ligand treatment experiments (data not shown). Given a hierarchal coupling of PXR transcriptional regulation of CAR activity, this could have a significant impact on the expression of CAR-regulated genes, as well as a subset of PXR-regulated genes.
Regulation of Transport Proteins, Transporters, and Phase III Targets
The expression of a number of cytosolic and secreted transport proteins, as well as membrane-bound transporters, was also affected by PXR activation. These include the up-regulation of genes encoding lipocalin 2 (GST-like, also known as prostaglandin D2 synthase), microsomal triglyceride transfer protein, an EST similar to progesterone membrane binding protein, and transcobalamin 2 (Table 1
and Fig. 3C
). The first three have been associated with binding or transport of various classes of lipids, whereas transcobalamin 2 is involved in vitamin B12 transport. We also noted up-regulation of an EST similar to ATP-binding cassette, subfamily B [multidrug resistance (MDR)/transporters associated with antigen presentation/ processing (TAP)], member 9 (ABCB9). ABCB9 proteins are components of transporters that are associated with lysosomes (40). In addition, several unclassifiable or unknown ESTs with short regions of similarity to ABC and MHC proteins were also detected, that are of unknown relevance to steroid metabolism. These ESTs exhibit the similar expression patterns and transcript size on Northern blots, with induction by VP-hPXR but only in the presence of mPXR (Fig. 3C
, and data not shown). Up-regulation of various transporters including organic anion polypeptide transporter 2, MDR1, and multidrug resistance protein 2 (MRP2, ABCC2) by nuclear receptors has been previously reported, although were not detected on our array (see the first and second tables in supplemental data) (10, 41, 42, 43, 44). Presumably, these tranporters are active in the cellular export and elimination of conjugated metabolites that result from phase I and II processing of endo- and xenobiotics. S100A8, [also known as calgranulin A, or migration inhibitory factor-related protein 8 (MRP8)], a calcium binding protein involved in immune cell recruitment, was also dramatically up-regulated in both samples (Fig. 3C
). In myeloid cells and keratinocytes, the heterodimer of S100A8 and S100A9 (MRP14) facilitates uptake of arachidonic acid by the oxidized low-density lipoprotein/fatty acids transporter CD36, which is also induced by VP-hPXR expression (45). Interestingly, we also observed strong induction of insulin-induced gene 2, a membrane protein that can regulate sterol regulatory element binding protein processing (46). Indeed, several sterol regulatory element binding protein known target genes were up-regulated in the VP-hPXR expressing livers, consistent with an increase in cholesterol and fatty acid synthesis that may be subject to subsequent metabolic feedback regulation of this pathway.
Multiple components of heme metabolism and iron transport were also affected by VP-hPXR expression. These include an increased expression of the coproporphyrinogen oxidase, a heme biosynthetic enzyme that may support increases in CYP synthesis, with accompanying decreases in certain hemoglobin chains (Tables 1
and 2
). Additionally, two ESTs representing serrotransferrins, the major serum iron transport proteins, decreased, as did hepcidin C, a peptide induced by iron excess that is differentially affected in hepatocyte nuclear factor 4
and CCAAT/enhancer binding protein
KO livers (47, 48). The negatively regulated genes are less coherent as a group in regards to metabolic control and may reflect secondary affects resulting from constitutively up-regulated CYP synthesis. One exception may be the coordinate decreases in urate oxidase, and an L-gulonolactone oxidase similar tag (94% identical to rat GULO), an enzyme absent in humans, but required for rodent ascorbic acid synthesis (Fig. 3B
). The degradation products of these three pathways, heme, uric acid, and ascorbic acid, constitute the sum of antioxidant activities in mouse and humans (49, 50).
Comparison of VP-hPXR, mPXR, and CAR Expression Profiles
One of the unique advantages that the albumin-VP-hPXR animals provide is expression of the experimentally activated human xenobiotic receptor in the genetic absence of mPXR. In total, our data provide a readout of human receptor-dependent hepatic gene targets that eliminates nongenomic complications of drug treatment of animals or cells that may affect receptor-independent gene targets. Several pharmacological expression studies describing various hPXR, mPXR, and mouse CAR gene targets have been recently published. For example, one study compared the hepatic effects of phenobarbital delivered ip for 12 h on wild-type and CAR KO animals by comparative cDNA microarray expression profiling (13). A different study was performed using both PXR and CAR KO animals to determine direct and indirect effects of PCN and TCPOBOP ip treatment over 28 h on a directed collection of 23 xenobiotic mouse gene targets using quantitative real-time PCR (39). Yet a third study examined the expression effects of rifampin treatment on primary human hepatocytes, on several platforms focused on xenobiotic P450 enzyme families (51).
Given the amount of expression data these studies represent, a comparison, or mapping of gene expression patterns derived from one receptor interrogation onto the other should suggest a general model for the base set of genes that respond to PXR or CAR activation. In reality, the pharmacokinetic differences in these drugs, along with the varied treatment times and dosing regimes renders it difficult to compare array or expression data obtained through these different platforms. Nonetheless, we found a substantial number of overlapping genes obtained in our data set vs. the CAR-phenobarbital (PB) study, as well as the PXR-PCN and CAR-TCPOBOP studies. For example, of the 38 differentially expressed genes presented in the CAR-PB cDNA microarray study, 12 of 38 identical tags were also identified in one or both of our VP-hPXR data sets, and 20 of 38 responded to PB treatment independent of genetic CAR presence. Further inspection of their cDNA content via web site publication revealed an extensive (but not complete) degree of EST clone content overlap from custom IMAGE consortium libraries. Several of the VP-hPXR and CAR-PB coincident genes were directionally consistent in their expression behavior (i.e. Cyp2B10 increases in both, Cyp3A11 increases in both), whereas others were opposite in behavior (i.e. ADH3A2 increasing with VP-hPXR, decreasing with PB). Additionally, a subset of the genes that overlap were also affected by VP-hPXR and by PB only in CAR null animals (i.e. intestinal calcium binding protein). We have subsequently included the PCN-PXR and CAR-TCPOBOP results onto the comparative map of the two unbiased screens for PXR and CAR gene targets. We find collectively that these expression studies, while overlapping and thus validating each other significantly, also provide a roadmap for determining PXR vs. CAR gene dependence and specificity of regulation, as well as direct vs. presumably indirect PXR and CAR activation effects.
Tables 35

summarize the results of this comparative mapping effort. Briefly, the 38 PB-derived target genes described by Ueda et al. (13) were filtered for 1) detection of identical ESTs in one or both of the VP-hPXR data sets and 2) PB-affected genes that require CAR presence. Quantitative PCR results were then compared with the list of genes identified as VP-hPXR targets in this study, and the remaining genes from the CAR-PB study. By comparing the results from these various platforms, we were able to segregate and make predictions about genes that were detected multiply, based upon directional behavior. A predictive assumption is made in regards to genes affected negatively by VP-hPXR with a bias toward positive transcriptional roles for PXR and CAR. For example, GST
2 is down-regulated by VP-hPXR expression and has been detected as a positive target of ligand induced CAR activity in another study (52). Thus, we would predict that GST
activity is a CAR-specific target and was decreased in our samples possibly due to PXR effects upon CAR expression. Table 3
shows genes that are specifically affected positively by VP-hPXR or PXR-dependent PCN activity. Table 4
shows genes that are affected (both positively and negatively) by CAR-dependent PB or TCPOBOP treatment. Table 5
shows genes that can be induced by either receptor. Genes that are negatively affected by VP-hPXR, PCN, PB, or TCPOBOP (i.e. CYP4A10, IGF binding protein-1) independent of receptor presence are assumed to be indirect gene targets, and have been subsequently filtered from these comparisons.
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DISCUSSION
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The nuclear receptors PXR and CAR (as well as the aryl hydrocarbon receptor) are transcription factors that function as metabolic sensors to control endo and xenobiotic metabolism in the liver. With respect to the nuclear receptors, both natural and synthetic chemical activators have been used to explore the induction of the target genes that define the hepatic phases IIII xenobiotic response. Similar to paradigms derived from steroid hormone action, however, these chemicals can elicit genomic affects that do not involve physical binding of the administered compound to the nuclear receptor ligand binding domain, or otherwise directly affect receptor transactivation function. This is clearly evidenced by the number of genes affected by phenobarbital treatment of the murine liver independent of CAR expression. Although these ancillary nongenomic affects may be important from a cellular biological perspective, they complicate the functional analysis of the nuclear receptor in question. This is particularly important with respect to PXR and CAR because they exhibit partially redundant and overlapping functions that can only be discriminated by use of receptor selective inducers. By careful selection of criteria that allow data sets obtained by different expression platforms to be combined, we can define both the chemical and genetic target genes of these receptors, and evolve a roadmap regarding xenobiotic response gene networks.
We have explored the consequence of expression of a genetically activated hPXR transgene in both the presence and absence of endogenous mPXR. Differentially expressed genes identified by these comparisons are specific to the DNA binding and transactivation capacity of the PXR transgene. Advantages of this type of approach include 1) in vivo tissue specificity; 2) elimination of uncontrollable variables of drug treatment (absorption, distribution, metabolism and excretion); and 3) receptor specificity of the interrogation. Disadvantages include 1) the potential downstream consequences of continuous production of CYP and other direct gene targets involved in the response; and 2) the possibility of false positives do to use of a distinct repertoire of coactivator molecules used by the viral protein 16 (VP16) activation domain vs. the ligand-transformed receptor activation function-2 domain. It may be argued that, in vivo, this system is constitutively active with respect to routine clearance of steroid metabolites and xenochemicals that are continually present. With regards to the mechanism of activation of the receptor, we cannot discount the possibility that some of the targets may be specific to the presence of VP16, although this transgene clearly behaves similar to chemically induced receptor with regards to the transcriptional induction of phase I enzyme targets. Once the VP16-derived targets are identified, their activity can be compared with chemically treated samples to confirm validity, as we have demonstrated above.
In the mouse liver, VP-hPXR predictably activates phase I CYPs, as well as certain dehydrogenases and esterases (summarized in Fig. 4
). Additionally, certain GSTs, UGTs, sulfotransferases, and acetyltransferases are induced to carry out phase II conjugation of metabolites from phase I oxygenation. This includes induction of enzymes responsible for cofactor production for these distinct phase II reactions. Ultimately, the conjugated metabolites must be exported to complete the elimination process. Representative genes from all three phases can be activated by both PXR and CAR. However, we have observed that several genes in this network are differentially regulated by these receptors, often in opposing transcriptional directions. In our expression data, these differences may reflect secondary consequences from perturbing CAR expression by VP-hPXR expression, resulting in a potential decrease in CAR-regulated genes (e.g. FMOC5). Yet CAR inducers such as PB also exhibit negative transcriptional effects upon certain PXR-regulated genes, such as ADH3A2, which at present, is more difficult to interpret or mechanistically explain. Furthermore, PB treatment can have positive transcriptional affects upon putative PXR target genes independent of the presence of CAR (e.g. Table 3
, CBI/ERp72). Because PB is not known to activate mPXR, we conclude that the PB-dependent affects must result from alternate PB signaling pathways that do not directly involve these nuclear receptors.
In our study utilizing a genetically activated receptor, we identified 271 differentially expressed tags, several of which were detected multiply. Upon elimination of EST redundancy and unclassifiable tags, this translates to approximately 150 unique genes. For comparison, the Ueda et al. (13) phenobarbital study identified 168 differentially expressed tags, one half of which were similarly affected despite genetic CAR KO. This comparison clearly highlights the benefit of a targeted activated receptor transgene that avoids potential and possibly hidden side effects of drug treatment. Furthermore, chemical profiling of this receptor system includes complications that could arise from treatment with pan agonists such as bile acids, that can affect FXR, PXR, and most recently, VDR (10, 17, 18). Additional receptor-independent effects are also seen with the ultrapotent CAR agonist TCPOBOP, as well as the mPXR gold standard, PCN (a glucocorticoid antagonist). This potential lack of receptor specificity is virtually eliminated in our VP transgenic approach. However, the activated receptor is not problem free, as long-term maximal induction of the xenobiotic response could result in secondary, potentially indirect effects, such as such as effects upon glucose and lipid or lipoprotein metabolism. Also, potent activation of PXR should (via induction of CYP3A) increase the clearance of steroids, which could have secondary systemic effects on steroid synthesis that may be detected by array analysis.
Both PXR and CAR KO mice are viable and exhibit no gross phenotype in the liver. We have profiled liver RNA from age matched wild-type and PXR null littermates, and found very subtle differences between these two genotypes in the basal, unchallenged xenobiotic state (data not shown). This observation is consistent with our previous report that the basal expression of the known PXR target gene CYP3A remains unchanged in PXR null mice (11). This may reflect the functional redundancy between CAR and PXR in xenobiotic regulation regarding endobiotic metabolism, where differences between the two receptor activities can only be discerned by specific xenobiotic challenge. We do, however, observe a number of the genes such as carboxyesterase 2 (Fig. 2B
) are up-regulated upon loss of PXR. This could be explained by several possibilities, including that in the absence of xenobiotic challenge, mPXR occupies response elements within the promoters of these target genes, and that genetic elimination of this receptor relieves a repressive state. Another possibility is that, upon PXR elimination, other nuclear receptors such as CAR or VDR could occupy these response elements and promote basal expression. Most of the genes that were detected in our study were regulated similarly by VP-hPXR in both the presence and genetic absence of mPXR, although a few genes were differentially affected in a mPXR dependent manner (e.g. HSD3b4). Although few changes were detected when direct comparisons between wild-type and PXR null livers were obtained, we speculate that certain metabolic hepatic remodeling might occur that renders certain target genes differentially responsive to VP-hPXR and/or CAR. In either event, it is clear that multiple receptors define the sensitivity of this system, and that future pharmacological and genetic expression profiling of single and compound PXR and CAR KO animals should provide more supportive evidence regarding overlapping and exclusive metabolic roles for these receptors in mice and ultimately, the human xenobiotic response pathway.
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MATERIALS AND METHODS
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RNA Isolation
Wild-type and PXR null adult males that carry the albumin-VP-hPXR transgene were generated and genotyped as previously described (11). All experiments involving animals were conducted in accordance with the NIH standards for the use and care of animals. Age-matched adult male littermates of the indicated genotype were euthanized, livers homogenized in Trizol, and extraction of total RNA performed according to the manufacturers instructions (Invitrogen Life Technologies, Inc., Gaithersburg, MD). Total RNA from two livers of each genotype was pooled, and poly A+ mRNA purified using the Amersham Biosciences (Piscataway, NJ) mRNA purification kit. Quality of the RNA samples was determined spectrophotometrically, as well as visually by migration in formaldehyde denaturing agarose gels.
Fluorescent cDNA Probe Labeling and Hybridization
For each sample, 1 µg of polyA+ mRNA was labeled with Cy3 and Cy5-deoxy-CTP (Amersham Biosciences) using Superscript II (Invitrogen Life Technologies, Inc.) in a first-strand cDNA reaction utilizing both oligo-deoxythymidine and random primers (Amersham Biosciences). Residual mRNA was degraded by treatment with ribonuclease H (Invitrogen Life Technologies, Inc.), followed by NaOH hydrolysis and HEPES neutralization (Sigma, St. Louis, MO). First-strand cDNA product was purified using QIAGEN (Valencia, CA) PCR purification columns, and the concentration and extent of labeled first-strand cDNA probe quantitated by spectrophotometric absorbance at OD550 (
= 0.15, Cy3), OD650 (
= 0.25, Cy5), and OD260. Twenty picomoles of each labeled Cy3 species were combined with equimolar amounts of Cy5 labeled probe, lyophilized, and resuspended in hybridization buffer (Amersham Biosciences) with 50% formamide (Sigma). Samples were hybridized to PCR product spotted Amersham Pharmacia Biotech Type 7 cDNA slides (described below) in Corning, Inc. (Corning, NY) chambers at 42 C for 18 h, and washed in 2x and 0.1x saline sodium citrate (SSC) with 0.2% sodium dodecyl sulfate (SDS) according to the manufacturers instructions, dried, and scanned.
Data Analysis
Slides were produced, scanned, and analyzed by The Salk Institute Laboratory of Functional Genomics. The clone collection is an IMAGE Consortium GEM-5214 collection, with approximately 8700 sequence verified mouse EST clones (listed in the second table in supplemental data). Two slide subarrays are spotted in duplicate with a Molecular Dynamics, Inc. (Sunnyvale, CA) Microarray Generation III Spotter, and images acquired with the Generation III Array Scanner. Image data were quantified using Molecular Dynamics, Inc. ArrayVision software. Fluorophor-reversal was used to select genes that report as differentially expressed in a directionally consistent fashion across four measured spots. Differential expression is defined as a greater than 1.3 averaged fold difference using background subtracted, scaled, fluorophoreversal confirmed data. Gene reports were filtered using Spot software to identify and average values from forward and fluororeversed data sets (53). Curation of the clone content from Genbank EST IMAGE clone accession numbers was performed using the Stanford University SOURCE database, as well as NCBI Unigene Build No. 119 (Released on 2003-01-25), Locuslink, and basic local alignment search tool (BLAST) resources. For CYP identities, the following P450 home pages were consulted: http://www.imm.ki.se/CYPalleles/default.htm and http://drnelson.utmem.edu/CytochromeP450.html.
Clustering of data passing the filter criteria of Spot (reports as present in both channels, greater than 1.3 average fold difference, fluororeversal confirmed with directional consistency) was performed using Silicon Genetics Genespring version 4.2.
Northern Hybridization
Ten micrograms of total RNA from pooled livers was resolved by denaturing formaldehyde-agarose gels (1% wt/vol), UV treated, transferred to nylon membranes (Schleicher & Schuell, Keene, NH) by standard Northern blotting in 10x SSC, cross-linked and photographed under UV to assess equivalent transfer. All ESTs were acquired from Incyte Corp. (Palo Alto, CA). cDNA probes for Northern hybridizations were generated by PCR amplification from the appropriate EST clone using universal primers (Amersham Pharmacia Biotech; and other oligos) and subsequent purification of gel verified PCR products using Roche (Indianapolis, IN) High Pure PCR purification columns. Probes were labeled with
-32P-deoxy-CTP using the high prime random prime labeling kit (Roche), with purification of labeled probe on G-25 purification columns (Pharmacia). Hybridizations were performed at 65 C in 10% Dextran sulfate, 1 M NaCl, 0.25% SDS, 100 µg/ml denatured salmon sperm DNA (Sigma) with washing to 65 C 0.1x SSC, 0.1% SDS. All clones were sequence verified by basic local alignment search tool (BLAST) search of NCBI/Genbank and Celera Discovery System databases using Applied Biosystems, Inc. (Foster City, CA). Prism data acquired by The Salk Institute Sequencing and Quantitative PCR facility. Membranes were imaged by exposure to XAR film (Eastman Kodak, Rochester, NY) and/or a Molecular Dynamics, Inc. PhosphorImager, normalized by hybridization to the mouse ribosomal 36B4 message, and signals analyzed using ImageQuant software (Molecular Dynamics, Inc.).
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ACKNOWLEDGMENTS
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We thank The Salk Institutes Laboratory of Functional Genomics for cDNA microarray slide processing and analysis. We also thank Jun Sonoda for critical reading of the manuscript, Mike Nelson for assistance with animal breeding and genotyping, and Melissa Baker of the Sequencing Facility for assistance in validating EST content.
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FOOTNOTES
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This work was supported by the Howard Hughes Medical Institute (R.M.E.). W.X. is supported by the Competitive Medical Research Fund of The University of Pittsburgh Medical Center Health System. R.M.E. is an Investigator of the Howard Hughes Medical Institute at The Salk Institute for Biological Studies and March of Dimes Chair in Molecular and Developmental Biology.
Present address for J.M.R.: Genome Biosciences, 28835 Single Oak Drive, Temecula, California 92590.
Abbreviations: ABC, ATP binding cassette; CAR, constitutive androstane receptor; CYP, cytochrome P450; DEX, dexamethasone; EST, expressed sequence tag; FMOC5, flavin containing containing monooxygenase 5; FXR, farnesoid X receptor; GST, glutathione-S-transferase; hPXR, human PXR; HSD, hydroxysteroid dehydrogenase; KO, knockout; mPXR, mouse PXR; PAPSS2, 3'-phosphoadenosine 5'-phosphosulfate synthase 2; PB, phenobarbital; PCN, pregnenolone carbonitrile; PPAR
, peroxisome proliferator-activated receptor
; PXR, pregnane X receptor; SDS, sodium dodecyl sulfate; SSC, saline sodium citrate; STa2, sulfotransferase a2; TCPOBOP, 1,4-bis[2-(3,5-dichloropyridiloxy)]benzene; UGT, uridine diphosphate-glucuronosyltransferase; VDR, vitamin D receptor; VP16, viral protein 16; VP-hPXR, transcriptionally active variant of hPXR.
Received for publication December 16, 2002.
Accepted for publication March 19, 2003.
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