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and Department of Chemistry and Biology, Ryerson. University, Toronto, Ontario, Canada M5B 2K3. Industrial and municipal processes may produce and...
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Environ. Sci. Technol. 2004, 38, 6396-6406

Gene Expression Profiles for Detecting and Distinguishing Potential Endocrine-Disrupting Compounds in Environmental Samples DONG-YU WANG,† BRUCE MCKAGUE,† STEVEN N. LISS,‡ AND E L I Z A B E T H A . E D W A R D S * ,† Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Ontario, Canada M5S 3E5, and Department of Chemistry and Biology, Ryerson University, Toronto, Ontario, Canada M5B 2K3

Industrial and municipal processes may produce and release endocrine-disrupting compounds (EDCs) into the environment, but the exact nature of their effects is difficult to investigate. EDCs typically exert their effect by affecting gene expression aberrantly. To determine if gene expression profiles could be used to detect and distinguish estrogenic EDCs, an estrogen receptor positive human breast cancer cell line (MCF-7) was exposed to known estrogenic compounds, suspected EDCs, and extracts from three effluent samples. A set of specifically estrogenregulated genes was identified by microarray analysis. Nine estrogen up-regulated genes (IGFBP4, HSPA8, B4GALT1, XBP1, KRT8, GTPBP4, HNRPAB, SLC2A1, and CALM1) and two estrogen down-regulated genes (ID2 and ZNF217) were consistently detectable in response to estrogen and other estrogenic compounds. Gene expression patterns in cells that were exposed to effluent sample extracts were compared to gene expression patterns in cells that were exposed to known endocrines. Using this technique, two of the effluent samples were shown to have estrogenic activity. This approach could easily be extended to screen for other types of receptor-mediated endocrine disruption. For example, cells expressing androgen or aryl hydrocarbon receptors could be used in gene expression profiling assays to detect androgenic effects or for the presence of bioactive aromatic hydrocarbons. Gene expression profiling is emerging as a sensitive and specific method to screen complex samples for endocrine disrupting activity.

Introduction Endocrine compounds, which include the female hormone estrogen and the male hormone testosterone, are key regulators of normal development. They typically act through cellular receptors that, upon binding the endocrine, recruit other molecules and interact with specific regions in the DNA to modulate the expression of key genes. The primary role * Corresponding author telephone: (416)946-3506; fax: (416)9788605; e-mail: [email protected]. † University of Toronto. ‡ Ryerson University. 6396

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of endocrines such as estrogen is to change gene expression in the cell. Endocrine-disrupting compounds (EDCs), which are often chemical analogues of normal endocrines, exert their effects by affecting the regulation of these genes aberrantly. A number of xenobiotic compounds (PCBs, pesticides) and other compounds in widespread use (e.g., phthalates found in food packaging) are suspected of having estrogen-like properties (1-3). More recently, phytosterols and their transformation products found in pulp mill effluents have been linked to reproductive effects in fish (4). However, there is much debate over the true concentrations, sources, identity, and effects of potential EDCs. This debate in part stems from the lack of appropriate technologies to accurately detect the presence of such chemicals in the environment. Chemical analysis of concentrations of known compounds can be tedious, does not detect unknown compounds, and does not address synergistic biological effects. While many biological tests have been proposed (5, 6), they frequently have only one limited end point (e.g., they can detect only one of many potential hormonal responses) and often do not provide any mechanistic information (7). In addition, results from rapid screening tests are difficult to correlate with whole organism response, while larger whole organism bioassays are very costly and time-consuming, and thus not useful for screening many samples. In this study, we explore the possibility of using global gene expression patterns generated by DNA microarray analysis to detect potential EDCs in environmental samples. DNA microarray technology, first reported in 1996 (8), is revolutionizing basic and applied molecular biology and medical research and diagnosis. Global gene expression profiles represent a snapshot of all mRNA levels in a cell at a given time. As such, they can provide insight into multiple processes simultaneously and into cascades of processes that are interrelated (9). Expression profiles are now being used to type diseases such as cancer to customize patient treatment and to screen new drugs. Applications to environmental monitoring and toxicogenomics are emerging (10-15). This kind of assay has the potential to be as easy as a simple in vitro assay and thus applicable to large-scale screening but to provide more meaningful information on the nature and source of activity in a given sample. For example, it should be possible to screen for estrogenic, androgenic, and other effects simultaneously. As a first step toward developing gene expression profiling as a screening tool, we established gene expression profiles in the estrogen-receptor positive, immortalized breast cancer cell line MCF-7, in response to estrogens and known and suspected estrogenic compounds. Previous microarray studies have begun to define global gene expression profiles in response to estrogen and to pinpoint novel estrogenresponsive genes of potential clinical relevance (16, 17) and to monitor possible environmental EDCs (18). In this study, our goal was to first identify genes in MCF-7 cells whose expression was regulated early in response to 17β-estradiol (E2) treatment. Next we identified genes expressed in response to chemicals known to have estrogenic or suspected estrogenic activity. In particular, we analyzed gene expression following exposure to two phytosterols and their oxidation products. Finally, we analyzed three effluent samples to test the methodology on real environmental samples.

Materials and Methods Chemicals. All endocrine compounds and chemicals were obtained from Sigma-Aldrich Corp. (St. Louis, MO), except 10.1021/es049235r CCC: $27.50

 2004 American Chemical Society Published on Web 11/02/2004

TABLE 1. Compounds Tested in This Study group natural estrogens

compound

17β-estradiol estriol synthetic estrogens 17β-ethinylestradiol diethylstilbestrol xeno-estrogens 4-nonylphenol 4-octylphenol phyto-estrogens β-sitosterol stigmasterol genistein pesticides 1,1,1-trichloro-2(o-chlorophenyl)-2(p-chlorophenyl)ethane alachlor antiestrogens 4-OH-tamoxifen ICI 182780 androgens testosterone dihydrotestosterone others progesterone cholesterol

abbrev

concn

E2 E3 EE2 DES 4NP 4OP Sit Sti Gen DDT

10 nM 100 nM 8 nM 4 nM 10 µM 10 µM 100 µM 100 µM 100 µM 1 µM

Ala OHT ICI Tes DHT Pro Cho

10 µM 100 nM 50 nM 10 nM 10 nM 10 nM 10 nM

where noted. The compounds used in this study and their abbreviations (Table 1) included natural estrogens: 17β-estradiol (E2) and estriol (E3); synthetic estrogens: 17β-ethinylestradiol (EE2) and diethylstilbestrol (DES); xeno-estrogens: 4-nonylphenol (4NP) and 4-octylphenol (4OP); phytoestrogens: β-sitosterol (Sit), stigmasterol (Sti), and genistein (Gen); pesticides: 1,1,1-trichloro-2-(o-chlorophenyl)-2-(pchlorophenyl)ethane (DDT), alachlor (Ala), and antiestrogens: 4-OH-tamoxifen (OHT) and ICI 182,780 (ICI, Tocris Cookson Inc. Ellisville, MO); androgens: testosterone (Tes) and dihydrotestosterone (DHT); and progesterone (Pro) and cholesterol (Cho). Ethanol (EtOH) was the solvent for the endocrine compounds and was also used as control. Methanol (MeOH) and methyl tert-butyl ether (MtBE) were used to extract effluent samples. Cell culture media and supplements and microarray hybridization and RT-PCR reagents were products of Invitrogen Corp. (Carlsbad, CA) except where noted. Synthesis of Chlorine Dioxide Oxidation Products from β-Sitosterol and Stigmasterol. β-Sitosterol and stigmasterol used for synthesizing oxidation products were obtained from Steraloids (Newport, RI). The β-sitosterol contained 80% β-sitosterol, 14% sitostanol, and 6% campesterol. The stigmasterol was >99% pure. Oxidations were carried out by adding the sterols (2 mM) to solutions of chlorine dioxide (0.41 g, 6 mM) in water (45 mL) at room temperature with stirring. The mixtures were heated to 70 °C and stirred for 30 min protected from light. After cooling, the products were extracted with ethyl acetate, and the extracts washed with water and dried. The extracts from each oxidation were split into two equal portions and evaporated separately. One portion of each oxidation product was stirred with 10% NaOH (20 mL) at 60 °C for 20 min. After being cooled, these samples were acidified with 10% HCl and extracted with ethyl acetate. The extracts were washed with water, dried, and evaporated. Thus, for each parent phytosterol, two different oxidized samples were prepared, one without NaOH treatment (ClO2Ox: ClO2‚Sit or ClO2‚Sti) and one with NaOH treatment (NaOH-Ox: NaOH‚Sit or NaOH‚Sti). Cell Culture. Cells from the human breast cancer cell line MCF-7 were obtained from American Type Culture Collection (Manassas, VA) and maintained in RPMI 1640 medium supplemented by 10% fetal bovine serum, penicillin, and streptomycin and incubated at 37 °C in 5% CO2. Before exposure to potentially estrogenic compounds or effluent sample extracts, the cells were transferred into phenol redfree RPMI 1640 medium supplemented with 10% charcoal/ dextran treated (hormone-free) fetal bovine serum (Hyclone Laboratories, Inc., Logan, UT), and subsequently grown for

6 d (Figure 1). The cells were then challenged with estrogen, putative estrogenic compounds, and effluent sample extracts at specific concentrations and exposure times as described below. Experiments with 17β-Estradiol. To study the temporal response to estrogen stimulation, MCF-7 cells were first grown in hormone-free medium for 6 d, after which the medium was amended with 10 nM E2. A parallel set of MCF-7 cells amended with an equal volume of EtOH without E2 was used as a control. Cells from both the estrogentreated samples and the control samples were harvested at 0, 2, 4, 8, 12, 24, 48, 72, or 96 h after exposure (Figure 1). In a separate experiment, cells were exposed to different concentrations of E2 ranging from 10-7 to 103 nM for 4 h. Experiments with Known and Putative Estrogenic Compounds. To study the effects of different endocrine compounds and possible EDCs, MCF-7 cells, pre-grown in hormone-free medium for 6 d, were amended with either 10 nM E2; 100 nM E3; 8 nM EE2; 4 nM DES; 10 µM 4NP; 10 µM 4OP; 100 µM Gen, Sit, and Sti; 1µM DDT, 10 µM Ala or 10 nM of Tes, DHT, Pro, and Cho (Table 1). Oxidized phytosterol samples were tested at 100 µM, the same concentration as the parent compounds Sit and Sti. Concentrations with putative environmental EDCs were chosen based on their relative potencies in cell proliferation or ERR binding in MCF-7 cells as compared to E2 (19) and concentrations used in other studies (20-22). The phyto-estrogens Sit and Sti were also tested at a variety of different concentrations ranging from 10-3 to 105 nM. Cells were harvested after 4 h exposure. MCF-7 cells amended with ethanol only were used as controls in these experiments (Figure 1). Experiments with Effluent Samples. Two pulp and paper mill effluent samples (A and B) and one municipal effluent sample (C) were used to test the methodology on real environmental samples. The samples were collected between March and May 2001 and were stored frozen at -20 °C. The effluent samples were either filtered or treated by solid-phase extraction (SPE) before addition to cell cultures (Figure 1). To test if putative EDCs were present in the dissolved phase of the samples, the samples were filtered through syringe filters (PALL 0.2 µM, Ann Arbor, MI), and the filtrates were applied to cell cultures at two dilutions: 1 volume filtrate to 3 volumes hormone-free medium (25%); and 9 volumes filtrate to one volume of 10 times concentrated hormonefree medium (90%). Distilled water only and distilled water plus E2 (10 nM) were also filtered as negative and positive control samples, respectively. SPE of effluents was performed using Oasis HLB cartridges (Water Corp., Milford, MA) according to the manufacturer’s instructions with slight modifications. The cartridges were conditioned using 10 mL of 10% MeOH in MtBE and then equilibrated with 3 mL of water. Effluent samples (200 mL) were loaded onto and drawn through the conditioned cartridges. The cartridges were washed with 3 mL of 5% MeOH in water and eluted using 1 mL of 10% MeOH in MtBE by spinning at 500 rpm. The 200× concentrated extracts were stored at -20 °C until use. Control samples including distilled water only, distilled water containing 10 nM E2, and distilled water containing 100 µM Sit were also similarly extracted by SPE. The 200× concentrated SPE extracts were added to the MCF-7 cells pregrown in hormone-free medium for 6 d (Figure 1) at a ratio of 1:1000 (v:v) resulting in an overall 1/5 (20%) dilution relative to the concentration in the original whole effluent samples. In all cases, cell cultures amended with filtrates or SPE extracts were harvested after 4 h exposure. Experiments with Antiestrogens. To determine the effects of estrogen-receptor antagonists ICI and OHT on gene expression patterns, MCF-7 cells were exposed to putative EDCs and control samples as described above, but in addition, VOL. 38, NO. 23, 2004 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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FIGURE 1. Schematic diagram of experimental procedures. Gene expression in cells exposed to test compounds was always compared relative to control (reference) samples containing only the solvent, ethanol (EtOH). Effluent samples were compared to extracted or filtered water control samples containing estrogen (E2) and β-sitosterol (Sit). mRNA samples for each experiment were first analyzed by RT-PCR to ensure gene expression in the positive control samples, prior to using the mRNA in microarray hybridizations. 50 nM ICI or 100 nM OHT were added to the cells prior to the 4 h incubation. RNA Preparation. All cell pellets were immediately frozen in liquid nitrogen and stored at -70 °C. Spin columns (QIAshredder, Qiagen, Valencia, CA) were used to homogenize the samples. Total RNA was extracted from cell pellets using the Qiagen RNeasy kit according to the manufacturer’s instructions and then frozen at -70 °C until used. RT-PCR. Semiquantitative reverse-transcriptase polymerase chain reaction (RT-PCR) was used to ensure that the treated cells were responding to estrogen. PDZK1 is a multiple PDZ domain containing protein expressed in response to estrogen (20). PDZK1 expression in response to E2 has been confirmed both by microarray (22-24) and RT-PCR (23, 25) experiments. Therefore, PDZK1 expression, measured by RTPCR, was used as an estrogenic activity biomarker. A reference housekeeping gene (β-actin) was used to confirm the success of the RT reaction and to normalize cDNA template concentrations in each reaction. RT-PCR was conducted according to Invitrogen’s protocol with slight modifications. Briefly, total RNA (5 µg) was reverse transcribed with the oligo(dT)20 primer in a total reaction volume of 20 µL, and PCR was carried out using 1 µL of reverse transcription product for amplification of target genes in a total reaction volume of 25 µL and was performed using a GeneAmp PCR System 2400 (Perkin-Elmer Corp. Norwalk, CT). PDZK1 and β-actin were amplified from the same sample in individual reactions. The sequences of the primers for amplifying PDZK1 were forward primer 5′-AAGGTGAAGAAGTCAGGAAGCCGTG3′ and reverse primer 5′-TGGCAGACCCCGAATCGCATT6398

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TAAG-3′, yielding a PCR fragment of 603 bp. The sequences of the primers for amplifying β-actin were forward primer 5′-TGACGGGGTCACCCACACTGTGCCCATCTA-3′ and reverse primer 5′-CTAGAAGCATTTGCGGTGGACGATGGAGGG3′, yielding a PCR fragment of 661 bp. The PCR conditions were as follows: 94 °C for 30 s, 57 °C for 30 s, and 72 °C for 1 min repeated over 25 cycles. PCR products were visualized by electrophoresis on 1.2% agarose gels. The image analyses were performed using NIH Image ver.1.63 (http://rsb.info.nih.gov/nih-image/). All RT-PCR reactions were performed in duplicate. Microarray Hybridization. Human cDNA microarray slides were obtained from The UHN Microarray Centre (Toronto, ON; www.microarray.ca). Two types of slides were used: double-spot Human 19k cDNA microarray slides (H19k, version 3 or 4) and single spot Human 19k cDNA microarray slides (ss-H19k, version 6). These microarrays contained 19 008 characterized and unknown human expressed sequence tags (ESTs) with slight modifications to the gene list between the different slide versions. For comparative microarray hybridization, cDNAs synthesized from paired samples of test RNA and reference (control) RNA (the same samples used for RT-PCR for PDZK1 expression, see Figure 1) were labeled according to protocols provided by the UHN Microarray Centre (http://www.microarray.ca/ ). Briefly, 10 µg of total RNA was reverse transcribed with Superscript II reverse transcriptase, AncT primer (5′-T20VN3′), and aminoallyl-dUTP (Sigma) at 42 °C for 2 h. cDNA from test and reference samples were labeled with Cy5 and Cy3 dyes (Amersham Biosciences Corp., Piscataway, NJ),

FIGURE 2. RT-PCR detection of PDZK1 expression in response to 17β-estradiol (E2), β-sitosterol (Sit), and stigmasterol (Sti) in MCF-7 cells. PDZK1 response to E2 exposed for 0-96 h (A); PDZK1 response as a function of concentration after 4 h exposure to E2 (B), Sit (C), and Sti (D). PDZK1 levels were quantified by normalizing the intensity of the signal for PDZK1 to that of the internal control gene, β-actin. Error bars are standard error. respectively, at room temperature for 1 h. The two separately labeled cDNAs from test and reference samples were purified, combined, and then hybridized to microarray slides. Hybridization was conducted at 37 °C overnight in DIG Easy Hyb solution (Roche Diagnostics Corp., Indianapolis, IN). The slides were washed in 0.1× SSC and 0.1% SDS at 50 °C and then scanned using a GenePix 4000 scanner (Axon Instruments Inc., Union City, CA). Microarray Data Analysis. Image analysis was performed using Axon’s GenePix Pro 3.0. The microarray data was further analyzed by GeneTraffic 2.7 (Iobion Informatics, La Jolla, CA) to normalize Cy5 and Cy3 signal intensities (I) using the LOWESS algorithm, to calculate Cy5 and Cy3 intensity ratios (I/Io; where I is the intensity of the test sample, and Io is the control or reference sample) for each EST on the microarray, and to compare and combine replicate data sets. To minimize false-positive results in DNA microarray experiments, replicate microarray hybridizations were performed. For each experimental condition, a minimum of two biological replicates were tested. The cDNA from each biological replicate was hybridized to either one double-spot slide or to two single-spot slides. This provided at least two biological replicates and two microarray replicates per condition. Reference (control) samples without the putative EDC were analyzed in an identical fashion in parallel and simultaneously hybridized to the array. Only those genes that had similar expression levels in at least three cDNA spots relative to control samples and in at least two independent experiments and that showed at least a 2-fold increase (log2 (I/Io) g 1) or 2-fold decrease (log2 (I/Io) e -1) in expression relative to the control (reference) were selected as estrogen-regulated candidate genes for further analysis. Hierarchical clustering was performed using Cluster and TreeView software (http://rana.lbl.gov/EisenSoftware.htm). Principal component analysis (PCA) was carried out using S-plus statistical software (24).

Results and Discussion PDZK1 Expression in Response to Estrogen. We determined previously that expression of estrogen-responsive gene PDZK1 occurred rapidly (in less than 2 h) following exposure of cultured immortalized breast cancer cells (MCF-7 cells)

to 17β-estradiol (E2) and was induced by concentrations of E2 as low as 10-3 nM (25). Several known estrogenic compounds, including natural and synthetic estrogens also stimulated PDZK1 expression. Furthermore, expression of PDZK1 was specific to estrogenic chemicals. Nonestrogenic compounds such as cholesterol (a biochemical precursor to steroid hormones; 26), testosterone (an androgen) or progesterone (a female sex hormone) did not cause expression of this gene (25). Moreover, the expression of PDZK1 could be prevented by treating cells simultaneously with 4-OHtamoxifen (OHT)sa competitive antagonist of estrogen (27). Thus, PDZK1 appears to be a sensitive and specific biomarker to monitor estrogenic activity in MCF-7 cells (25). PDZK1 expression in response to E2 could be detected as early as 2 h after exposure and always significantly after 4 h exposure (Figure 2A). Therefore 4 h was selected in this study as the standard exposure time for other compounds or samples. The highest levels of PDZK1 expression were detected using 10 nM E2 (Figure 2B), which was the working concentration used in this study. PDZK1 Expression in Response to a Variety of Estrogenic and Putative Estrogenic Compounds. Appropriate test concentrations for the various compounds surveyed in this study were generally obtained from the literature and are listed in Table 1. Given the importance of phytosterols as a waste stream of the pulp and paper industry, we examined the effect of concentration more closely for two phytosterols Sit and Sti. Significant induction of PDZK1 was observed in MCF-7 cells exposed to the highest concentration tested, 100 µM (Figure 2C,D). Next, we examined PDZK1 expression in response to E2, Sit, Sit, and their chemical oxidation products as there is some concern that phytosterols may become more active upon oxidation. In the positive control reactions, PDZK1 expression was clearly stimulated by E2 and inhibited by antiestrogens ICI and OHT (Figure 3A). OHT also inhibited PDZK1 expression in response to Sit and Sti, indicating that PDZK1 expression was mediated through the ER. However, the two oxidation products did not stimulate PDZK1 expression in MCF-7 cells as did their parent chemicals (Figure 3A). MCF-7 cells were also exposed to two natural estrogens, two synthetic estrogens, two xenoestrogens, three phyto-estrogens, and two pesticides at the VOL. 38, NO. 23, 2004 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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FIGURE 3. RT-PCR detection of PDZK1 expression in response to a variety of compounds. PDZK1 expression in response Sit and Sti and four oxidation products ClO2‚Sit, NaOH‚Sit, ClO2‚Sti, and NaOH‚Sti (see Methods and Materials for details) as compared to E2 (A). MCF-7 cells were exposed for 4 h, and the response was compared with and without the addition of two estrogen inhibitors: OHT and ICI. PDZK1 expression in response to selected putative estrogenic compounds (see Table 1 for details) as well as some non-estrogenic control chemicals (Cho, Pro, Tes, and DHT) (B). MCF-7 cells were expose to each compound for 4 h. Error bars are standard error. concentrations provided in Table 1. Two androgens, Tes and DHT, as well as Pro and Cho were used as controls. A 4 h cell exposure time was selected based on the time-course results with E2. PDZK1 expression was clearly induced when cells were exposed to natural estrogen E3; synthetic estrogens EE2 and DES; and xeno-estrogens 4NP and 4OP. PZDK1 expression was lower with Sit, Sti, and DDT as compared to E2 and was absent with Gen and Ala (Figure 3B). Moreover, the two androgens as well as Pro and Cho did not stimulate PDZK1 expression in MCF-7 cells (Figure 3B). Most of the selected putative EDCs in this experiment stimulated PDZK1 expression, although the strength of the response varied with each compound, especially if the differences in concentrations are considered. Further studies will be required to establish accurate dose-response data for each compound or group of compounds. Because phyto-estrogens and their derivatives may be important estrogenic chemicals in pulp mill effluent samples, Sit and E2 were selected as controls for effluent samples in subsequent experiments. Gene Expression Profiles in Response to E2. While PDZK1 is a useful biomarker, a more powerful approach to distinguish the effects of potential EDCs on a living cell is to monitor the expression levels of all the genes in the cell upon exposure. This kind of analysis is now possible with DNA microarray technology. To this end, DNA microarrays comprised of 19 000 fragments of human genes (ESTs) were used to identify many E2-responsive genes. The cDNA samples from replicate sets of MCF-7 cells exposed to E2 for 0-48 h were labeled and hybridized to the microarrays. Prior to labeling, the mRNA from E2-exposed cells was first tested for PDZK1 expression using RT-PCR to ensure that the cells had been properly treated (Figure 4, bottom histogram, left). Hierarchical clustering revealed 20 up-regulated and four downregulated cDNA fragments (ESTs) after exposure to E2 for 2-8 h (Figure 4, left column). The responsive ESTs were grouped into four categories (A-D) according to how quickly the expression of a particular gene was induced (Figure 4, bars A-C) or repressed (Figure 4, bar D). The 20 estrogen6400

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induced and four estrogen-repressed ESTs included 16 known human genes. Eleven of these genes have previously been reported to be estrogen-responsive or to be related to estrogen receptor status, and another 5 genes were reported as estrogen-induced and validated by RT-PCR in our earlier study (25). A quantitative summary of known E2-responsive genes found by this microarray analysis is provided in Table 2. Gene Expression Profiles in Response to Putative EDCs. Microarray hybridizations were performed to detect expression profiles in cells treated with putative EDCs. Many of the same genes that responded to E2 also responded to putative EDCs (Figure 4). In the E2-regulated gene cluster A (earlyinduced genes), the expression of six estrogen-induced genes including E2IG4, XBP1, AFG3LT1, B4GALT1, SLC2A1, and IGFBP4 (up-regulated with E2 as early 2 h post-exposure) were also up-regulated when the cells were exposed to natural and synthetic estrogens and to the alkylphenols at 4 h (Figure 4, bar A). Induction of these genes was also observed with Sit and to some extent with DDT, although the fold induction was lower as compared to E2 at the same exposure time. For example, the average fold induction (exposed vs control) for the genes in cluster A for E2 at 4 h was 2.9 as compared to 1.5 and 1.3 for Sit and DDT, respectively. Expression was less evident with phyto-estrogen Gen or pesticide Ala (Figure 4, bar A). In the E2-regulated gene cluster B (induced by E2 after 4 h), HSPA8, KRT8, GTPBP4, and HNRPAB were upregulated in the cells exposed to natural and synthetic estrogens and Sit (Figure 4, bar B). The three genes CYCS, NME1, and NSEP1 were mainly responsive to natural and synthetic estrogens only (Figure 4, bar B). The two genes HSPD1 and AAK1 in cluster C that responded to E2 at 8 h were responsive only to the natural estrogen E3 after 4 h (Figure 3, bar C). TFF1 is a classical estrogen-induced gene (28) but in these experiments was not induced, perhaps owing to the short exposure time (Figure 4, bar B). Of the four clearly down-regulated genes found in these microarray experiments (Figure 4, bar D), only ID2 was recently reported as estrogen

FIGURE 4. Gene expression patterns in response to 17β-estradiol (E2) in MCF-7 cells exposed for 0-48 h and in response to various endocrine-disrupting chemicals in MCF-7 cells exposed for 4 h. Microarray hierarchical clustering is represented as a pseudo-color visualization matrix. Gene clusters denoted by the bars and letters A-C group genes that responded to E2 after 2, 4, and 8 h treatment, respectively. Cluster D is a group of E2 down-regulated genes. The expression patterns with gene names are shown on the right. The known estrogen-responsive genes are listed in Table 2. The color scale used to represent the expression ratios is shown on the top right. The bottom histogram provides PDZK1 expression levels detected by RT-PCR for comparison (an EST for the PDZK1 gene was not printed on the UHN microarrays). suppressing in MCF-7 cells (29) (Table 2). The expression of GATA binding protein 3 (GATA3) was shown to be strongly correlated with the presence of estrogen receptors (30-32) and also clustered with other estrogen-regulated genes such as XBP1 (32). However, GATA3 is not directly estrogeninduced (30, 31) but is a transcription factor that may regulate the expression of genes involved in estrogen receptor status (30, 32). In this study, GATA3 was consistently down-regulated when the MCF-7 cells were exposed to EDCs. None of the estrogen-regulated genes responded to any significant extent to the two androgens, testosterone and dihydrotestosterone (except for weak signals for one of the three ESTs corresponding to XBP1 and one of the two ESTs for CYCS). Moreover, PDZK1 expression measured by RTPCR (Figure 4, bottom histogram, right) was in general agreement with the microarray data. To visualize differences in the gene expression profiles, a PCA (24) of the data was performed using the 20 upregulated ESTs and the 4 down-regulated ESTs. PCA evaluation of the expression profiles indicated that the natural and synthetic estrogens were separable from both putative estrogenic compounds and androgens (Figure 8A). The results demonstrated that different gene expression profiles vary consistently in response to different chemicals. These dif-

ferent expression patterns, once fully developed and replicated for many chemicals as a function of concentration and exposure time, present a method of detecting and most importantly distinguishing the nature and source of potentially EDCs in complex samples. PDZK1 Expression in Response to Effluent Samples. To demonstrate the applicability of this approach to complex environmental samples, three effluent samples were analyzed, first by RT-PCR for PDZK1 expression and second by microarray analysis (next section). PDZK1 expression in MCF-7 cells was stimulated only in cells exposed to the higher concentration (90%, not 25%) of filtered effluent A (Figure 5). Therefore, this concentration was used for experiments with the two remaining samples. PDZK1 expression in cells exposed to all three effluent samples (filtrates and SPE extracts) revealed that the two pulp mill samples induced considerable PDZK1 expression, while the response using municipal effluent (C) was minimal (Figure 5). Moreover, the SPE extracts for sample A demonstrated significantly higher activity than the corresponding filtrate at similar dilution (20% vs 25%), indicating that the majority of the activity arose from compounds in the suspended solids in the whole effluent samples (Figure 5). On the basis of these results, subsequent analyses were restricted to SPE extracts. VOL. 38, NO. 23, 2004 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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TABLE 2. Microarray Data (log2) for MCF-7 Cells Exposed to E2 and OHTa differentially expressed genes

0h

2h

Up-Regulated genes E2IG4, estrogen-induced gene 4 -0.06 1.25 XBP1, X-box binding protein 1 0.01 1.45 AFG3L1, AFG3 ATPase family gene 3-like 1 0.00 1.12 B4GALT1, β1,4-galactosyltransferase, polypeptide 1 -0.07 1.27 SLC2A1, solute carrier family 2 member 1 0.07 1.26 IGFBP4, insulin-like growth factor binding protein 4 -0.03 0.73 CALM1, calmodulin 1 nd nd CYCS, cytochrome c, somatic -0.03 0.24 HSPA8, heat shock 70-kDa protein 8 -0.01 0.33 TFF1, trefoil factor 1 -0.02 0.37 KRT8, keratin 8 0.01 0.11 HNRPAB, heterogeneous nuclear ribonucleoprotein A/B 0.02 0.21 NME1, non-metastatic cells 1 -0.02 0.04 NSEP1, nuclease sensitive element binding protein 1 0.02 0.11 HSPD1, heat shock 60-kDa protein 1 0.02 0.06 GTPBP4, GTP binding protein 4 0.01 0.11 ID2, inhibitor of DNA binding 2 ZNF217, zinc finger protein 217

Down-Regulated Genes -0.04 -1.1 nd nd

E2 4h

8h

24 h

0.90 1.25 1.82 1.58 1.03 1.71 1.23 0.53 0.61 0.56 0.70 0.60 0.41 0.41 0.19 0.63

0.29 1.04 1.27 1.18 1.27 1.32 nd 1.21 0.90 0.56 0.45 0.91 0.58 0.72 0.90 0.76

0.35 1.20 1.10 0.28 1.23 1.15 nd 1.71 1.74 1.03 1.00 1.18 1.30 1.58 1.65 0.86

-1.0 -1.3

-0.9 nd

-1.1 nd

E2 + OHT 4h nd 0.56 nd 0.89 0.71 0.59 0.37 nd 0.32 nd 0.58 0.16 ndndnd0.19 0.03 -0.1

also reported by (ref no.) 21 16,17 25 22,25 34,35 17 21 25 21 21 36 25 21,37 25 21 25 29 29

a The data in boldface type |log (I/I )| g 1 corresponding to 2-fold or greater induction or repression. Using this transformation, genes that are 2 o up-regulated as compared to the control have a log2 (I/Io) greater than +1, and those that are down-regulated have a value less than -1. nd, no data.

FIGURE 5. PDZK1 expression in response to different extracts from effluent samples. Two concentrations of effluent filtrates and negative control (water) and positive control (water plus E2) samples were applied to MCF-7 cells for 4 h. Solid-phase extracts from those same samples were similarly tested. PDZK1 expression was used to compare sample preparation methods. Error bars are standard error. In the next set of experiments, in addition to the effluent samples (A-C), a water sample, a water sample with17βestradiol, and a water sample with β-sitosterol were also extracted using SPE and analyzed. PDZK1 expression was observed clearly in SPE extracts of control samples containing E2 but not in the negative control (water only). PDZK1 expression was highest with E2 but also significant with Sit, effluents A and B, but not for effluent C (Figure 6, bottom histogram). These results suggested that there was estrogenic activity in effluents A and B and that further testing with these samples was warranted. Gene Expression Profiles in Response to Effluent Samples. To obtain a broader picture of the possible estrogenic activity in the effluent samples, the RNA extracted from treated cells and control cells (and tested using RT-PCR for PDZK1 expression) was differentially labeled and hybridized to microarrays as per the scheme shown in Figure 1. A similar cluster of up-regulated genes was identified as found in the earlier experiments with pure E2 and specific EDCs. In the up-regulated cluster E (Figure 6), eight known estrogen6402

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induced genes (including IGFBP4, HSPA8, B4GALT1, XBP1, KRT8, GTPBP4, HNRPAB, SLC2A1) were up-regulated in MCF-7 cells exposed to E2, Sit, and the two mill effluents A and B but not to effluent C. Moreover, in this same cluster, four other up-regulated ESTs corresponding to two genes: calmodulin 1 (CALM1) and hypothetical protein MGC5370 were also detected. CALM1, represented by two ESTs on these arrays, is also a known estrogen-induced gene (Table 2). MGC5370 is a hypothetical protein also represented by two ESTs on these arrays. There were just 26 amino acids in the short open reading frame of MGC5370 (Accession No. NM_032739) and no functional information is available todate for this EST. In the down-regulated cluster F (Figure 6), a total of seven genes was detected, of which ID2 and ZNF217 have been previously reported as estrogen suppressed genes in MCF-7 cells (Table 2). GATA3 was also found to be repressed in our experiments with EDCs (Figure 4, Bar D). The remaining four down-regulated genes corresponded to two unidentified ESTs: one ORF of unknown function and one

FIGURE 6. Gene expression patterns generated from cDNA microarray hybridizations in response to estrogens and effluent samples. Gene expression patterns in response to 17β-estradiol and β-sitosterol in MCF-7 cells exposed for 4 h as compared to SPE extracts of effluent samples A-C without or with the effects of estrogen inhibitor 4-OH-tamoxifen. Microarray hierarchical clustering is represented as a pseudo-color visualization matrix. Gene clusters denoted by the bars and letters E and F are the estrogen-induced genes and estrogenrepressed genes, respectively. The names of the genes within the two clusters E and F are provided in the magnified panel on the right. The known estrogen-regulated genes reported previously are listed in Table 2. The color scale used to represent the expression ratios is shown on the top right. Cluster G represents a group of down-regulated genes that dose not react with 4-OH-tamoxifen. The bottom histogram provides PDZK1 expression levels detected by RT-PCR for comparison. gene (RPS6KKB2) not previously reported to be estrogenrepressed (Figure 6, Bar F). Another down-regulated cluster G (Figure 6) corresponds to genes observed to be downregulated in all samples but for which this effect was not reversed when the inhibitor tamoxifen was also added to the cells. This effect therefore appeared to be a nonspecific response of the cells and not indicative of estrogenic activity. Effect of Tamoxifen on Gene Expression Profiles. Estrogen receptors are transcription factors that become activated through binding of estrogen. The estrogen/receptor complexes recruit other proteins that in concert regulate the expression of many estrogen-responsive genes. Tamoxifen (4-OH-tamoxifen, OHT) competitively binds to the estrogen receptor, inhibiting estrogen receptor activity (27). It is thus a useful inhibitor to determine if the observed gene expression patterns are mediated through an estrogen receptor or not. In this study, OHT significantly blocked the induction or repression of known E2-responsive genes in cells treated simply with E2 (Table 2). OHT significantly blocked PDZK1 expression induced by SPE extracts of water samples spiked with E2 and Sit, as well as by SPE extracts of effluent samples A and B (Figure 6, bottom histogram). OHT also blocked induction of estrogen-induced genes in cluster E (Figure 6) and blocked repression of estrogen-repressed genes in cluster F (Figure 6). This strongly indicates that the observed gene expression changes are estrogen-receptor mediated and thus specific to compounds that bind to the estrogen receptor.

Comparative Analysis of Gene Expression Profiles. To summarize the microarray data quantitatively for comparative purposes, the average expression ratios (from 2 to 4 microarray experiments) expressed as log2 (I/Io) (see Materials and Methods) were plotted for the 10 most responsive genes for known compounds and effluent samples (Figure 7). These data were also analyzed by PCA (Figure 8B). These data illustrate the potential discriminating power of gene expression profiles. For example, 4NP, which is a well-established EDC based on other testing methods, clearly induced a similar set of genes as did E2 after 4 h exposure; however, the relative intensities of the response were not identical: While XBP1, IGFBP4, ID2, and GATA3 response was equal or stronger than that of E2, HNRPAB, GTPBP4, and HSPA8 response was lower for NP than for E2. The phyto-estrogen Gen showed very little response as compared to E2 for most of the genes, except for GTPBP4 and GATA3. Therefore, depending on which gene is compared, Gen could be classified as estrogenic or not. The patterns for Sit and E2 were similar, although one must recall that the test concentrations differed by 4 orders of magnitude (10 nM vs 100 µM). With more profiles of individual compounds as a function of concentration and exposure time, it should be possible to analyze and cluster data into similar expression profiles. The two mill samples, tested at 20% of full strength, clearly showed estrogenic activity since gene expression profiles were most similar to those for Sit and E2. VOL. 38, NO. 23, 2004 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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FIGURE 7. Histograms of genes expression levels in response to estrogenic chemicals and effluent samples in MCF-7 cells exposed for 4 h. Ten human estrogen-responsive genes including eight up-regulated genes and two down-regulated genes were quantified on the basis of average expression levels converted to log2 (I/Io) from the normalized microarray signal intensities. Error bars are standard error. Abbreviations: E2, β-estradiol; DES, diethylstilbestrol; 4NP, 4-nonylphenol; 4OP, 4-octylphenol; Sit, β-sitosterol; Eff.A, effluent A; Eff.B, effluent B; Eff.C, effluent C; DDT, 1,1,1-trichloro-2-(o-chlorophenyl)-2-(p-chlorophenyl)ethane; Gen, genistein; Ala, alachlor; and Tes, testosterone. A t-test was used to compare the putative estrogenic group (E2, DES, 4NP, 4OP, Eff.A, and Eff.B) to the remaining samples (Eff.C, DDT, Gen, Ala, and Tes). P values are reported on each panel.

FIGURE 8. Principle component analysis (PCA). Microarray expression data reported in Figures 4 and 7 were analyzed by PCA, and the results were projected onto the first two principal components (PC1 and PC2). (A) PCA plot based on the expression levels of 24 ESTs for 12 different EDCs at 4 h shown in Figure 4. Variance of PC1 ) 61.2% and of PC2 ) 18.3%. (B) PCA plot based on the expression levels of the 10 genes shown in Figure 7 for three effluent samples and eight different EDCs. Variance of PC1 ) 65.6% and of PC2 ) 11.3%. Implications and Significance. The use of gene expression profiling (33) for diagnostic purposes is beginning to gain 6404

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acceptance for a wide range of applications. Gene expression profiles are beginning to be used for medical diagnosis in

breast cancer and leukemia (10, 11). Several groups are approaching toxicity screening using microarray technology (12-15). To develop an assay for EDCs based on gene expression profiling, a biological system must be chosen. One could use a whole organism, such as a fish or amphibian, and extract RNA from a specific tissue, such as liver or gonads. This kind of experiment is vital for clearly establishing organismal response but would not be tractable for large numbers of samples. To develop a quick in-vitro assay, a cell culture is a simpler biological system. The advantage of using a well-established cell line is that growth is reproducible and can be carried out in multiple replicate samples inexpensively and generate ample RNA. The primary disadvantages are that the assay will not detect processes such as chemical modification, differential mobility, and hindered transport that may occur in a whole organism. Accepting these shortcomings, a well-established vertebrate cell line is a good choice because it provides both ease of growth and physiological relevance. For this study, a steroid receptor-positive human cell line was selected because human microarrays were readily available and offer a large number of genes for analysis. Another excellent alternative would be to use a cell line from a freshwater animal found in effluent receiving waters, such as a fish hepatocyte cell line, but at present the availability of fish microarrays is limited. The purpose of this study was to demonstrate that gene expression profiles could be used to detect and distinguish potential sources of estrogenic activity in environmental samples. Upon binding a ligand, the ER enters into a variety of different ligand-specific protein-protein interactions. These protein complexes have different affinities for distinct promotor regions on DNA and thus differentially regulate expression of many genes. Therefore, unlike a simple receptor binding assay, gene expression profiles will detect which ligand-ER complexes are physiologically active because they can recruit other proteins to a particular promotor region and alter gene expression patterns. In this study, we used the expression of PDZK1, an early estrogen-induced gene, as a biomarker to verify experimental procedures prior to using mRNA in microarray experiments. PDZK1 proved to be a very reliable biomarker for estrogenic activity, based on our survey of many known and putative EDCs. In particular, PDZK1 expression data suggested that both phytosterols Sit and Sti, but not their oxidation products, have estrogenic activity. In microarray experiments, a list of 12 candidate E2-responsives genes was identified. Different gene expression profiles were observed for different compounds tested, demonstrating the potential for using gene expression profiles for distinguishing the extent and nature of the activity. This technique established that the two whole mill effluents tested exhibited clear estrogenic activity, equivalent to that exerted by roughly 20-100 µM β-sitosterol or 2-10 nM 17β-estradiol. The full power of this technique will be realized with more gene expression profiles for more compounds at different concentrations. Expression profiles for other compounds, such as those interacting with the androgen receptor and aryl-hydrocarbon receptors, are also required. With a database of gene expression profiles for a given cell system for different EDCs, it will be possible to detect synergistic effects in complex mixtures where individual constituent compounds are at concentrations too low to detect separately. To obtain a truly environmentally relevant diagnostic test, gene expression profiles for individual EDCs should be correlated to in-vivo bioassay results to link the type of response observed at a cellular level to the whole organism physiological response.

Acknowledgments We thank Aled M. Edwards (University of Toronto) for advice and financial support. We also thank Ronit Andorn-Broza, Limin Chen, and Jing Sun (University of Toronto) for their technical assistance. This work was supported by grants from the National Science and Engineering Research Council of Canada (Strategic Projects), from the National Cancer Institute of Canada (awarded to Aled M. Edwards), and from industries supporting a research consortium on “Minimizing the Impact of Pulp and Paper Mill Discharges” at the University of Toronto Pulp and Paper Centre.

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Received for review May 24, 2004. Revised manuscript received September 1, 2004. Accepted September 6, 2004. ES049235R