Hepatic gene expression profiling using Genechips in zebrafish exposed to 17α-ethynylestradiol

Aquatic Toxicology 79 (2006) 233–246

Hepatic gene expression profiling using Genechips in zebrafish exposed to 17␣-ethynylestradiol J.L. Hoffmann, S.P. Torontali, R.G. Thomason, D.M. Lee, J.L. Brill, B.B. Price, G.J. Carr, D.J. Versteeg ∗ Miami Valley Innovation Center, The Procter and Gamble Company, P.O. Box 538707, Cincinnati, OH 45253-8707, United States Received 22 March 2006; received in revised form 7 June 2006; accepted 9 June 2006

Abstract Genomic, proteomic, and metabolomic technologies continue to receive increasing interest from environmental toxicologists. This interest is due to the great potential of these technologies to identify detailed modes of action and to provide assistance in the evaluation of a contaminant’s risk to aquatic organisms. Our experimental model is the zebrafish (Danio rerio) exposed to reference endocrine disrupting compounds in order to investigate compound-induced changes in gene transcript profiles. Adult, female zebrafish were exposed to 0, 15, 40, and 100 ng/L of 17␣ethynylestradiol (EE2) and concentration and time-dependent changes in hepatic gene expression were examined using Affymetrix GeneChip® Zebrafish Genome Microarrays. At 24, 48, and 168 h, fish were sacrificed and liver mRNA was extracted for gene expression analysis (24 and 168 h only). In an effort to link gene expression changes to effects on higher levels of biological organization, body and ovary weights were measured and blood was collected for measurement of plasma steroid hormones (17␤-estradiol (E2), testosterone (T)) and vitellogenin (VTG) using ELISA. EE2 exposure significantly affected gene expression, GSI, E2, T, and VTG. We observed 1622 genes that were significantly affected (p ≤ 0.001) in a concentration-dependent manner by EE2 exposure at either 24 or 168 h. Gene ontology (GO) analysis revealed that EE2 exposure affected genes involved in hormone metabolism, vitamin A metabolism, steroid binding, sterol metabolism, and cell growth. Plasma VTG was significantly increased at 24, 48, and 168 h (p ≤ 0.05) at 40 and 100 ng/L and at 15 ng/L at 168 h. E2 and T were significantly reduced following EE2 exposure at 48 and 168 h. GSI was decreased in a concentration-dependent manner at 168 h. In this study, we identified genes involved in a variety of biological processes that have the potential to be used as markers of exposure to estrogenic substances. Future work will evaluate the use of these genes in zebrafish exposed to weak estrogens to determine if these genes are indicative of exposure to estrogens with varying potencies. © 2006 Elsevier B.V. All rights reserved. Keywords: Zebrafish; 17␣-Ethynlestradiol; Microarray; Liver; 17␤-Estradiol; Testosterone; Vitellogenin; Gonadosomatic index

1. Introduction During the past decade, there has been an increasing awareness that some compounds released into the environment may be affecting the endocrine system of fish and wildlife. These endocrine disrupting compounds (EDCs) consist of natural and synthetic hormones as well as numerous industrial and agricultural compounds (Holland, 2003). Effects attributed to EDCs include altered plasma VTG and steroid hormone levels, altered histology, and decreased fecundity (Ankley et al., 2002; Jobling et al., 2002; Lavado et al., 2004; Versonnen and Janssen, 2004; Vethaak et al., 2005).

∗

Corresponding author. Tel.: +1 513 627 1196; fax: +1 513 627 1208. E-mail address: [email protected] (D.J. Versteeg).

0166-445X/$ – see front matter © 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.aquatox.2006.06.009

Ecotoxicogenomics is a relatively young field that focuses on using genomic techniques (e.g. polymerase chain reaction (PCR), microarrays) to understand the molecular and cellular effects of chemicals via changes in gene expression in aquatic organisms (Snape et al., 2004). The use of genomic techniques in ecotoxicology has increased greatly in recent years, largely due to the fairly recent sequencing efforts and gene annotation for several fish species, including zebrafish and medaka. Chemically induced changes in gene expression have the potential to be used in the evaluation and hazard identification of EDCs with various modes of action (e.g. estrogens, androgens, aromatase inhibitors). Using a variety of genomic techniques (e.g. Northern blots, RNA protection assays, and PCR), measurement of vitellogenin (VTG) mRNA in male or juvenile fish has been one of the most commonly used biomarkers for exposure to estrogenic

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EDCs (Mellanen et al., 1999; Bowman et al., 2000; Korte et al., 2000). While the expression of specific genes such as VTG has been routinely measured in juvenile and male fish, we are not aware of any studies that have examined global hepatic gene expression changes in female fish exposed to estrogenic compounds. Kato et al. (2004) measured changes in hepatic gene expression in both male and female rats administered 17␣ethynylestradiol (EE2) in the diet. The authors found that significantly more genes were affected in female rats as compared to males following exposure. These results provide some evidence that the use of female fish in studies designed to measure the effect of estrogenic compounds on gene expression is a valid approach. While the liver is not traditionally considered a highly estrogen-responsive tissue, we chose to use it for several reasons: (1) it is fairly homogeneous relative to traditionally estrogenresponsive tissues such as ovaries; (2) it plays a critical role in the hypothalamus–pituitary–gonadal axis by producing VTG under the stimulation of E2 from the ovaries; (3) it contains critical monooxygenase enzymes that are involved in the biotransformation of steroid hormones to maintain appropriate levels of plasma hormones; (4) it maintains metabolic homeostasis and is primarily responsible for biotransformation and detoxification of xenobiotics and will thus have broad applicability when compounds with non-EDC modes of action are evaluated. The overall goal of our research program is to develop a screening assay that uses transcriptomics to identify compounds with varying modes of action (estrogen, androgen, aromatase inhibitor). Therefore, we have chosen to use the livers of female zebrafish as our model system. In the present study, our primary objectives were to use Affymetrix GeneChip® Zebrafish Genome Microarrays to characterize hepatic gene expression profiles in gravid, female zebrafish exposed to a model estrogen, EE2, to gain a better understanding of the mechanisms of estrogenic compounds in fish and to identify potential biomarkers of exposure to estrogenic compounds. Plasma vitellogenin (VTG), 17␤-estradiol (E2), testosterone (T) and gonadosomatic index (GSI) were also measured to determine effects of EE2 at higher levels of organization. 2. Materials and methods 2.1. Experimental animals Adult male and female zebrafish (>121 days) were obtained from Aquatic Research Organisms (Hampton, NH) and maintained together (1 male:2 female) for at least 2 weeks prior to experimentation, according to Procter and Gamble’s animal care-approved protocols. Fish were kept together in 75 L tanks that received a constant flow of well water under a 16:8 h, light:dark photoperiod. Temperature and dissolved oxygen were measured daily in each aquaria during the experiment while pH, hardness, conductivity, alkalinity, and ammonia were measured on the first and last day of the experiment. Fish were fed a combination of newly hatched brine shrimp and Tetramin® (Tetra, Germany) flakes twice a day, ad libitum.

2.2. Test solutions A stock solution of 5.88 mg/L EE2 (17␣-ethynylestradiol CAS #: 57-63-6; purity ≥ 98% high-performance liquid chromatography; Sigma–Aldrich, St. Louis, MO) was prepared in ethanol (Aaper Alcohol and Chemical Co., Shelbyville, KY). Aquaria delivery solutions were prepared by diluting the stock solution in deionized water with ethanol as the solvent carrier. 2.3. Exposure To synchronize the reproductive status of female fish, males and females were separated 5 days prior to the initiation of exposure. Gravid females were exposed to EE2 at nominal concentrations of 0, 15, 40, or 100 ng/L under flow-through conditions in 33 L aquaria for 24, 48 or 168 h. Each aquaria contained 15 female zebrafish. Flow rate of dilution water to the exposure aquaria was maintained at 100 mL/min using flow controllers (Alicat Scientific, Tucson, AZ) yielding 4.4 aquaria renewals per day. To achieve the desired concentrations, EE2 and the solvent control (ethanol) were delivered to the exposure aquaria using programmable glass syringe pumps (Harvard Apparatus PHD2000, Holliston, MA) at a flow-rate of 40 mL/h. Prior to delivery to the exposure aquaria, EE2 and the solvent control were combined with the dilution water at a “T” fitting. During the exposure, fish were fed twice daily, once with newly hatched brine shrimp and once with Tetramin® (Tetra, Germany) to reduce the effect of a change in diet on gene expression. Debris was siphoned from each tank daily. 2.4. EE2 analysis Aqueous concentrations of EE2 were determined daily (two replicates/concentration) using solid phase extraction followed by HPLC–MS for quantitation. Briefly, 500–1000 mL samples of water were passed through a 6 cm3 /0.2 gm waters OASISTM HLB extraction cartridge (Waters Corporation Milford MA USA) at approximately 5 mL/min flow. Cartridges were rinsed with purified water and excess water was removed by gentle vacuum. EE2 was eluted with 1 mL methanol followed by 6 mL of 1:1 dichloromethane:methanol, evaporated to dryness under nitrogen and reconstituted in 1:1 methanol:water with E2 internal standard. The resulting sample was analyzed by HPLC–MS using a Waters 2795 Alliance-HT HPLC system coupled to a Micromass ZMD mass spectrometer equipped with a negative ion electrospray source. HPLC conditions used a 2.0 × 150 mm × 3 ␮m Phenomenex Phenylhexyl column (Phenomenex, Torrance, CA, USA) and an acetonitrile:water:0.005% ammonium acetate linear gradient of acetonitrile from 60% to 80% over 8 min. Selected ion recording of the EE2 (m/z = 295) and E2 internal standard (m/z = 271) was used to provide optimum sensitivity. Replicate samples agreed within 10% of each other and the method detection limit was 2 ng/L.

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2.5. Sample collection Five fish per concentration were anesthetized using 300 mg/L MS-222 (Tricane methane sulfonate (Argent Chemical Laboratories, Redmond, WA)) at 24, 48, and 168 h. Fish were weighed and blood was collected from the caudal vein using heparinized hematocrit microcapillary tubes and centrifuged at 11,500 rpm for 2 min. Plasma was separated and frozen at −80 ◦ C until measurement of steroid hormone and VTG levels. After collection of the blood, ovaries were collected and weighed for determination of gonadosomatic index (GSI = (ovary weight (g)/body weight (g)) × 100). The livers were removed, placed in RNAlater (Ambion, Austin, TX, USA) and then stored at 4 ◦ C. After 24 h at 4 ◦ C, RNAlater was aspirated from liver tissue and livers were placed at −80 ◦ C for later processing and gene expression analysis using custom Affymetrix GeneChip arrays (24 and 168 h only). 2.6. VTG, T and E2 analyses Enzyme linked immunosorbent assays (ELISA) were used to quantitate VTG and hormone levels in plasma using commercial kits (Cayman Chemical Ann Arbor, MI). Plasma for VTG analysis was quantitated using a sandwich enzyme immunoassay as described by the manufacturer. Two dilutions of plasma were tested to verify that the appropriate dilution chosen was within the linear range of the standard curve generated using purified zebrafish VTG. A dilution of 1:1,440,000 was found to be acceptable for measurement of VTG. Plasma E2 and T were analyzed using competitive enzyme immunoassays as described by the manufacturer with the following exception: reagent and sample volumes used in the competitive assays were reduced by half due to small sample volume. Prior to E2 and T analysis, plasma samples were purified by ether extraction according to (Drevnick and Sandheinrich, 2003) with minor modifications. Briefly, plasma samples were diluted to 1 mL with reagent-grade water then 3 mL of diethyl ether was added to each sample in a glass tube. Each sample was vortexed for 60 s, and the ether layer was transferred to a clean glass tube. This process was repeated twice before the ether was evaporated off using a gentle stream of dry nitrogen. Extracts were reconstituted in an appropriate amount of dilution buffer for analysis. All samples were analyzed in duplicate and re-assayed if the coefficient of variation exceeded 20%. Data were analyzed using the enzyme immunoassay (EIA) analysis tools available from Cayman Chemicals. 2.7. Expression profiling Total RNA was isolated from livers using 1 mL Trizol (Invitrogen, Carlsbad, CA) and purified using the RNeasy Mini Kit (Qiagen, Valencia, CA). A 10 ␮g total RNA was converted to double-stranded cDNA using SuperScript II Reverse Transcriptase (Invitrogen) with T7-(dT)24 primers (Affymetrix Inc., Santa Clara, CA, USA). Double-stranded cDNA was purified using phenol/chloroform extraction. Synthesis of biotin-labeled cRNA was carried out using the ENZO BioArray High Yield

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RNA Transcription Labeling Kit (Affymetrix) and then purified using the RNeasy Mini Kit (Qiagen). A 20 ␮g of cRNA was fragmented into approximately 200 bp fragments using a fragmentation buffer (200 mM Tris–acetate, pH 8.1; 500 mM KOAc, 150 mM MgOAc) (Affymetrix). Quantity of RNA was determined by measuring UV absorbance at 260 nm on a UV Spectrophotometer (Nanodrop Technologies; Wilmington, DE, USA). Sample quality was assessed using the Agilent 2100 Bioanalyzer Total RNA Nano Assay (Agilent Technologies, Palo Alto, CA, USA) prior to hybridization to the microarrays. Samples were hybridized to the Affymetrix GeneChip® Zebrafish Genome Microarray that contains 14,900 transcripts of which approximately 6000 are annotated and 8946 are ESTs (expressed sequence tags). Fragmented biotin-labeled cRNA was hybridized to the chip at 45 ◦ C for 16 h using a hybridization cocktail (control oligonucleotide, 50 pM (Affymetrix); four eukaryotic hybridization controls at 1.5, 5.0, 25, and 100 pM (Affymetrix); herring sperm DNA, 0.1 mg/mL (Promega Corp.); bovine serum albumin, 0.5 mg/mL (Invitrogen); hybridization buffer, 1×; and DMSO, 10% (Sigma)). Hybridized genome arrays were then stained with streptavidin–phycoerythrin solution (SAPE) (Invitrogen). Fluorescent signal intensities were then measured using a GeneChip® Scanner 3000 (Affymetrix). A scaling factor of 1500 was applied to each array to bring the average signal intensity to the same level to enable comparisons between arrays. 2.8. Quantitative real-time PCR (qRT-PCR) Changes in the expression of selected genes identified as being significantly different following microarray analysis were validated using qRT-PCR. From each RNA sample, 10 ␮g of total RNA was treated with DNA-free® (Ambion, Austin, TX) to eliminate contamination of genomic DNA. A 1 ␮g of DNasetreated total RNA was then reverse transcribed into cDNA using the iScript cDNA Synthesis Kit (BioRad, Hercules, CA) as described by the manufacturer. qRT-PCR was carried out in clear semi-skirted 96-well plates using the iCycler iQ Detection System (Bio-Rad, Hercules, CA). After diluting the cDNA 1:5 in nuclease-free water, 5 ␮l was used in each real-time PCR reaction. Each PCR reaction consisted of 12.5 ␮l Platinum SYBR Green PCR SuperMix-UDG (Invitrogen, Carlsbad, CA), 6.3 ␮l nuclease-free water and a final concentration of 0.3 ␮M of each the forward and reverse primer, and 10 mM fluorescein. Primers for each gene were designed using Primer3 primer design software (Rozen and Skaletsky, 2000) using criteria for real-time PCR primer design described by (Bustin, 2000). Briefly, the 3 end of each primer was A/T rich, PCR products were between 50 and 150 bp, and runs of identical nucleotides were less than or equal to three. No template controls and negative reverse-transcriptase (-RT) controls were included on each plate. To determine reaction efficiency for each primer, five-fold dilutions of cDNA were carried out. Reaction efficiency was then calculated by the iCycler iQ software using Eq. (1): reaction efficiency = 10−(1/slope) .

(1)

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Table 1 GenBank accession number, real-time primer sequences and product size of the target genes Target

Accession #

Forward primer

Reverse primer

Size (bp)

Ptma Igf2 Igfbp1 Cyp1a gapdh Dio2 Vtg

AF372502 BC085623 NM173283 AF210727 BG306045 CA975553 AY034146

CGCAAAGGACCTCAAAGAAA ACGGAGGAAACACGAACAAC GTCATCCTGGAATGGGAAGA AATCCCAGACGGGCTACA TGGCTCCTCTGGCTAAAGTT GGATGAGTCGGAAAGGTGAA AGCTGCTGAGAGGCTTGTTA

GCCACATCATCGTCTTCCTC GTTCTCCGCCACAGAGAGTC TGTGTGACGGATCAGTGGTT CCGGGCCATAGCACTTAC GATGCAGGGATGATGTTCTG CCACACTAAGCAAGCCCATT GTCCAGGATTTCCCTCAGT

135 106 93 122 160 89 94

Abbreviations—ptma: prothymosin alpha like-1; igf2: insulin-like growth factor 2 precursor; igfbp1: insulin-like growth factor binding protein 1; cyp1a: cytochrome P450 1A1; GAPDH: glyceraldehyde-2-phosphate dehydrogenase; dio2: deiodinase, iodothyronine, type II; vtg: vitellogenin.

An optimal value of 2 indicates that the product is doubling with each cycle. Reaction efficiencies of <0.85 were considered unacceptable. To determine if non-specific products were being amplified, a melt curve analysis was performed for each primer and the product was run on a 2% agarose gel to verify amplicon size. Primer sequences, GenBank accession numbers and product sizes for all genes are provided in Table 1. The cycling profile used consisted of 50 ◦ C for 2 min, 95 ◦ C for 2 min and 45 cycles at 95 ◦ C for 15 s and 58 ◦ C for 30 s and 72 ◦ C for 30 s followed by ramping from 41 to 95 ◦ C rising by 0.5 ◦ C each 15 s step for the melt curve analysis. GAPDH, ␤-actin, and 18S were evaluated for use as internal controls for qRT-PCR. Based on results from the microarrays, GAPDH was significantly upregulated in a concentrationdependent manner at 168 h (p < 0.0001) and although not statistically significant, ␤-actin was also increased following EE2 exposure. 18S was significantly upregulated in a concentrationdependent manner at 24 h (measured using qRT-PCR) (data not shown). Therefore, the use of GAPDH, ␤-actin, and 18S as internal controls was deemed inappropriate. Because the expression of three commonly used internal controls (GAPDH, ␤-actin, and 18S) were altered by EE2 exposure, qRT-PCR results are presented without normalization to an internal control. mRNA expression values for each sample were calculated according to the equation described by (Pfaffl, 2001) with minor modifications (Eq. (2)): x=

1 ECt

(2)

E corresponds to the reaction efficiency that was determined (Eq. (1)) for each specific gene of interest. The raw fluorescence data was normalized to background fluorescence and converted to a log scale using the iCycler iQ software. The cycle threshold value (Ct ) was then determined as the cycle number where the threshold line (manually set at a point during the exponential phase of the curve) intersected the amplification curve. The expression ratios were standardized to the mean of control ratios and reported as a fold change relative to controls. 2.9. Data analysis Each gene on a zebrafish genome array is represented by sixteen pairs of oligonucleotide probes (25-mer) that are selected to span approximately 600 bp toward the 3 end. The length of

the probes and the presence of multiple probes for each transcript increase the sensitivity and specificity to the target. One member of the oligonucleotide probe pair is a mismatch probe (MM) which is identical to the perfect match probe (PM) except that it contains a base change at the 13th position. The MM probes control for non-specific hybridization. The Affymetrix Microarray Suite software (Version 1.3) uses probe pair signal intensities to make present, absent, and marginal calls for each gene based on detection algorithms outlined in the GeneChip® Expression Analysis Overview Manual (Affymetrix). Genes that were identified as absent in all samples across treatment groups were eliminated from further comparative analysis. Expression measures were analyzed in S-plus software (Insightful, Seattle, WA). The effects of dose and time were investigated using various linear models (Venables and Ripley, 2006) and non-parametric analyses (Gibbons and Chakraborti, 2003). Linear models were fit that accounted for the effects of dose, duration of follow-up, and their interactions. In these models, dose was treated as both a nominal factor, and as a regressor for the purpose of detecting dose–response. In the non-parametric analyses, trends in gene expression response to dose and time were evaluated by using a stratified test for trend. Stratification is used to control for effects of nuisance variables on responses. Pairwise comparisons of treated groups to their time-matched controls were also used to further understand the dominant patterns of dose effects. Fold changes were determined for each gene by calculating the ratio of the mean expression values of the control and treated samples. Differences in GSI, Vtg, T, and E2 among treatment groups were identified using one-way analysis of variance (ANOVA) followed by Tukey’s honestly significant difference test (JMP IN Version 5.1.2, SAS Institute, USA). 2.10. Gene ontology analysis Genes whose expression was significantly affected (p ≤ 0.01) by EE2 in a concentration-dependent manner were clustered using gene ontology (GO) annotation to identify specific processes or functions that were over-represented in the list of significantly affected genes. Genes (p ≤ 0.01) were then separated into two groups, up-regulated and down-regulated genes and mapped separately to the biological process and molecular

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Table 2 Nominal and measured (mean ± S.D.) EE2 concentrations (ng/L) from each treatment Nominal

Measured

0 15 40 100

0.5 13.8 36.9 97.7

± ± ± ±

% Nominal

1.1 1.4 5.8 15.5

– 92.0 92.3 97.7

Values are mean (n = 8) ± S.D.

function branches of the GO using the integrated informatics platform (IIP) developed at The Procter and Gamble Company, Cincinnati, OH, USA. The IIP uses the Fishers exact test to score the mapping of genes from an experiment to their annotations in the GO. High scoring GO terms are summarized using a heat map (see Tables 5 and 6).

Fig. 1. Plasma vitellogenin levels in zebrafish exposed to EE2 for 24, 48, or 168 h. Data are expressed as mean (n = 5) ± S.E. Asterisk denotes significance difference as determined by one-way ANOVA (p < 0.05).

3.3. VTG, T and E2 analyses 2.11. Online supplemental materials Microarray data discussed in this manuscript have been deposited with ArrayExpress (http://www.ebi.ac.uk/ arrayexpress/). 3. Results 3.1. Exposure conditions Measured EE2 concentrations averaged more than 90% of nominal for all concentrations during the 168 h exposure (Table 2). No mortality occurred at any of the concentrations tested. Water quality parameters were not significantly different between exposure aquaria; therefore, values for all tanks were combined (mean ± S.E.: temperature (◦ C): 26 ± 0.06; dissolved oxygen (mg/L): 6.29 ± 0.11; pH: 7.8 ± 0.06; hardness (mg CaCo3 /L): 171 ± 2.3; alkalinity (mg/L): 132 ± 2.85; ammonia (mg/L): 0.01 ± 0.005).

A significant increase in plasma VTG occurred as early as 24 h at 40 and 100 ng/L and persisted throughout the duration of the study (Fig. 1). At 168 h, plasma VTG was increased at the lowest EE2 concentration (15 ng/L). Plasma E2 was significantly decreased at all EE2 concentrations (15, 40, and 100 ng/L) at 48 and 168 h (Fig. 2A). Due to limited sample (blood volume) obtained from a sufficient number of fish at 24 h, testosterone was not measured at this timepoint. At 48 h, testosterone was reduced at 40 ng/L and at both 48 and 168 h testosterone was reduced at 100 ng/L (Fig. 2B).

3.2. Gonadosomatic index No significant differences were detected in GSI at 24 or 48 h at any concentration tested relative to control. At 168 h, a concentration-dependent decrease in GSI was observed with a significant reduction at the highest concentration of EE2 tested (100 ng/L) (Table 3). A time-dependent decrease (24 versus 168 h) occurred in fish exposed to 100 ng EE2/L. Table 3 Gonadosomatic index in female zebrafish exposed to EE2 for 24, 48, or 168 h EE2 (ng/L)a

24 48 168 a * §

0

15

40

100

16.5 ± 3.1 14.0 ± 2.4 15.1 ± 3.0

12.2 ± 2.3 11.7 ± 1.8 12.0 ± 3.1

11.9 ± 2.1 13.5 ± 2.5 6.5 ± 2.2*

13.5 ± 3.1 10.5 ± 0.5 5.2 ± 0.3*,§

Values are mean (n = 5) ± S.E. Significantly different from 0 ng EE2/L (p < 0.05). Significantly different from 24 h timepoint (p < 0.05).

Fig. 2. Plasma hormone levels in zebrafish exposed to EE2 for 24, 48, or 168 h. (A) 17␤-Estradiol and (B) testosterone. Data are expressed as mean (n = 5) ± S.E. Asterisk denotes significance difference as determined by oneway ANOVA (p < 0.05).

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Table 4 Number of genes significantly affected in a concentration-dependent manner vs. what would be expected based on chance alone at either 24 or 168 h (includes only genes that were not eliminated based on absent calls by the Affymetrix Microarray Suite Software) Significance level

Observed

Expected

1 0.1 0.01 0.001 0.0001 1e−005 1e−006

11331 4759 2543 1622 1039 688 448

11331 1133 113 11 1.1 0.1 0

The numbers for the observed column were determined by conducting a test for dose–response that was averaged across the 24 and 168 h timepoints. The expected number was calculated by multiplying the p-value and the total number of genes not eliminated based on absent calls.

sure (Table 5). Certain biological processes such as nitrogen compound metabolism, sterol biosynthesis, protein biosynthesis, tRNA metabolism, and a variety of processes involved in transport were up-regulated at 24 h. While some processes related to nitrogen compound metabolism, biosynthesis, and tRNA metabolism remained elevated 168 h, genes involved in processes related to metabolism, organic acid metabolism, hormone metabolism, and lipid metabolism were down-regulated. Analysis of the molecular function branch of the GO revealed that genes with monooxygenase, steroid dehydrogenase, steroid binding, cyclin-dependent kinase, and ligase activities were also impacted by EE2 exposure (Table 6). Table 7 provides examples of genes significantly affected in a concentration-dependent manner according to one specific biological process or molecular function to which they belong. It is important to note that due to the hierarchical nature of the GO, most genes are represented by more than one GO term so they likely belong to more GO terms than is indicated in Table 7.

3.4. Gene expression profiles Four thousand one hundred and seventy-one genes received absent calls provided by the Affymetrix Suite Software and thus were eliminated from comparative analysis. Of the remaining 11,331 genes, the number of genes that were significantly affected by EE2 exposure in a concentration-dependent manner ranged from 448 to 1622 (1e−006 ≤ p ≤ 0.001) (Table 8). Gene expression changes were evaluated primarily at a significance level of ≤0.001 because at this level, only 1 out of 1000 genes are expected to be due to chance rather than due to EE2 treatment, thus limiting the number of false positives. Trend analysis revealed 1622 genes that were significantly affected (p ≤ 0.001) at either 24 or 168 h in a concentrationdependent manner. Of these 1622 genes, approximately 48% are annotated. At 24 h, 215, 671, and 1084 genes were affected at 15, 40, and 100 ng/L, respectively (p ≤ 0.001) (Fig. 3). At 168 h, 26, 144, 631 genes were affected at 15, 40, and 100 ng/L, respectively (p ≤ 0.001) (Fig. 3). One hundred and seventy two genes were affected at all concentrations at 24 h whereas only six genes were affected at all concentrations at 168 h (Fig. 3). GO analysis identified 107 and 53 biological processes and molecular functions significantly affected by EE2 exposure in at least one timepoint or one concentration, respectively (Tables 5 and 6). Genes involved in processes related to lipid metabolism, sterol metabolism, vitamin metabolism, regulation of growth, and hormone metabolism were affected by EE2 expo-

3.5. qRT-PCR analysis To validate gene expression changes measured using the microarrays, seven genes including prothymosin, alpha (ptma), insulin-like growth factor precursor 2 (igf2), insulin-like growth factor binding protein 1 (igfbp1), cytochrome P450, family 1, subfamily A (cyp1a), glyceraldehyde-2-phosphate dehydrogenase (gapdh), deiodinase, iodothyronine, type II (dio2), and VTG were also quantitated using qRT-PCR. These genes were chosen to be a representative sample of genes that exhibited a variety of expression profiles including genes that were upregulated, downregulated, or were unchanged. Gene expression changes as measured using qRT-PCR exhibited good concordance with results obtained using the microarray. The magnitude of the changes was similar between qRT-PCR and microarray results and the direction of the change was identical at all concentrations and timepoints (Table 8). 4. Discussion In this study, we evaluated hepatic gene expression profiles, plasma levels of VTG, E2 and T, and GSI in gravid, female zebrafish exposed to EE2. Exposure to EE2 resulted in a significant decrease in GSI which is consistent with previously published reports (Van den Belt et al., 2001, 2002; Versonnen

Fig. 3. Venn diagrams illustrating number of significant genes (p < 0.001) that are in common between EE2 treatments.

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and Janssen, 2004). In the current study, we only observed effects on GSI at 40 and 100 ng/L after 168 h of exposure. However, in previous studies a reduction in GSI has been demonstrated in female zebrafish after exposure to concentrations of EE2 as low

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as 10 ng/L after 12–21 days of exposure (Van den Belt et al., 2001, 2002; Versonnen and Janssen, 2004). Reproduction in teleost fish as well as most vertebrates is regulated by the hypothalamic–pituitary–gonadal axis. In response

Table 5 Term survey heat map of the biological process branch of the GO created using genes that were down regulated (−) and up-regulated (+) in a concentration-dependent manner by EE2 exposure (p ≤ 0.01)

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Table 5 (Continued )

Indented GO terms are children of the branch listed in bold. The level of indentation indicates the specificity of the process (e.g. the greater the indentation, the more specific the functional description). The color represents the level of significance determined with the IIP using the Fishers exact test (p-values > 10−3 are coded as gray; between 10−4 and 10−3 as gold; between 10−5 and 10−4 as light orange; between 10−6 and 10−5 as orange; and <10−6 as red) The value in each square indicates the number of genes for that particular molecular function affected at the corresponding EE2 concentration.

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to changes in photoperiod and temperature, gonadotropin releasing hormone from the hypothalamus stimulates the release of gonadotropins from the pituitary. The primary function of gonadotropins is to mediate steroidogenesis in the ovaries that

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results in an increase in the secretion of E2 during gonadal recrudescence. In this study, both plasma T and E2 were decreased following exposure to EE2 at 48 and 168 h. EE2 functions as an oral contraceptive by suppressing the release of the

Table 6 Term survey heat map of the molecular function branch of the GO created using genes that were down regulated (−) and up-regulated (+) in a concentration-dependent manner by EE2 exposure (p ≤ 0.01)

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Table 6 (Continued )

Indented GO terms are children of the branch listed in bold. The level of indentation indicates the specificity of the process (e.g. the greater the indentation, the more specific the functional description). The color represents the level of significance determined with the IIP using the Fishers exact test (p-values > 10−3 are coded as gray; between 10−4 and 10−3 as gold; between 10−5 and 10−4 as light orange; between 10−6 and 10−5 as orange; and <10−6 as red) The value in each square indicates the number of genes for that molecular function process affected at the corresponding EE2 concentration.

gonadotropin, luteinizing hormone, from the pituitary (Van den Belt et al., 2002). Therefore, exposure to EE2 may have resulted in a reduction in gonadotropin release from the pituitary providing one possible mechanism that led to the decrease in plasma T and E2. Exposure to EE2 resulted in a significant increase in plasma VTG at 40 and 100 ng/L at 24, 48, and 168 h of exposure. These results are in concordance with previous studies that also demonstrated an increase in plasma VTG in female zebrafish exposed to concentrations of EE2 as low as 10 ng/L (Versonnen and Janssen, 2004; Van den Belt et al., 2003). Measurement of VTG mRNA and protein in male or juvenile fish is one of the most commonly used biomarkers for exposure to estrogenic EDCs (Fawell et al., 2001; Jobling et al., 2002; Kirby et al., 2004; Robinson et al., 2003). In this study, VTG mRNA was not increased in EE2-exposed fish, whereas VTG protein levels increased in plasma. One potential explanation for this observation is the high constitutive expression level of VTG mRNA in gravid, female zebrafish. Although the liver is not traditionally considered a highly estrogen-responsive tissue, results from this study confirmed that the liver is responsive to estrogens as evidenced by the number of highly significant changes in gene expression (Table 4). These results are consistent with previous studies that demonstrated a significant number of gene expression changes in the livers of both male plaice (Pleuronectes platessa) and ovariectomized mice exposed to estrogens (Brown et al., 2004; Boverhof et al., 2004). GO analysis revealed many biological processes and molecular functions that were impacted by EE2 exposure and, in many cases, can be related to an estrogen mode of action. Genes involved in processes related to transport, sterol biosynthesis, translation, regulation of growth, and hormone metabolism were affected by EE2 exposure (Table 5). Genes with monooxygenase, steroid dehydrogenase, steroid binding, cyclin-dependent kinase, and ligase activities were also impacted by EE2 exposure (Table 6). While GO analysis can be useful in providing information about mode of action, many GO terms affected by EE2 exposure are general descriptions that, based on the results from this experiment alone, make it difficult to link to an estro-

gen mode of action. Further, while a greater proportion of the zebrafish genome is annotated relative to other teleost species (e.g. rainbow trout), there is still a significant proportion that is not annotated at this time. Several genes identified using GO analysis and/or the literature which can be related to an estrogen mode of action and responded to EE2 in a concentration-dependent manner will be discussed. Sex hormone binding globulin (shbg), a plasma binding protein that binds estrogens and androgens, helps regulate the clearance of circulating steroids as well as delivery of these hormones to target tissues (Miguel-Queralt et al., 2004). The expression of shbg was significantly reduced in this study possibly due to reduced concentrations of plasma steroid hormones (E2 and T). Several genes involved in the clearance of plasma hormones were affected by EE2 exposure. Sulfotransferases are responsible for the inactivation of both natural and synthetic (e.g. EE2) steroid hormones via conjugation with a sulfate group (Kotov et al., 1999; Fisher, 2004; Schrag et al., 2004). Although plasma E2 concentrations decreased in a concentration and time-dependent manner, sulfotransferase mRNA was upregulated approximately six-fold after exposure to 100 ng/L for 168 h possibly to facilitate elimination of EE2. In contrast, cyp1a was significantly down-regulated as much as 9.80-fold (100 ng/L at 24 h). This is consistent with other studies that demonstrate that exposure to estrogens results in a decrease in cyp1a gene expression and inhibited enzyme activity (Forlin and Haux, 1990; Navas and Segner, 2001; Elskus, 2004; Vaccaro et al., 2005). Navas and Segner (2001) suggest that the estrogen receptor is involved in estrogen-induced inhibition of cyp1a mRNA. Using human endometrial cells, Ricci et al. (1999) provided evidence that the inhibition of cyp1a expression is associated with the transcription factor, nuclear factor-1 (NF-1), which interacts with both the estrogen receptor and the receptor involved in transcription of cyp1a mRNA, the aryl hydrocarbon receptor (AhR). Specifically, recruitment of NF-1 by AhR to the promoter region of the cyp1a gene is decreased, and the factor is directed to E2responsive genes, resulting in reduction of cyp1a induction. It has been widely demonstrated in mammals that estrogens affect cholesterol homeostasis through a variety of mechanisms

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243

Table 7 Fold-changes of selected genes that involved in biological processes (bp) or molecular functions (mf) whose expression was significantly altered in female zebrafish livers in a concentration-dependent manner following exposure to EE2 at 24 and 168 h Accession no.

Gene ontology annotation (ID)

24 h

168 h

15 ng/L

40 ng/L

100 ng/L

15 ng/L

40 ng/L

100 ng/L

Negative regulation of cell growth (GO: 0008285 (bp)) NM131458.1 Insulin-like growth factor binding protein 2 (igfbp2) NM131405 Prospero-related homeobox gene 1 (prox1) NM201297 EST—strong similarity to human prohibitin NM212732 Mdm4, transformed 3T3 cell double minute 4, p53 binding protein NM200772 Tryptophanyl-tRNA synthetase NM212792 Cyclin-dependent kinase inhibitor 1b (p27, kip1) NM173283.1 Insulin-like growth factor binding protein 1 (igfbp1)

−1.72 −2.27 1.24 2.05 2.87 4.60 2.63

−2.17 −3.16 1.57 2.52 4.70 5.84 8.52

−4.35 −3.88 1.58 3.92 5.80 8.84 11.41

−1.18 −2.37 −1.35 1.54 −1.16 1.96 1.33

−2.63 −2.51 1.16 3.09 2.25 2.09 8.24

−3.27 −3.24 2.20 2.39 3.31 2.11 8.37

Cell division (GO: 0051301 (bp)) NM213172 Cyclin G2 NM001002183 CDC42 effector protein BC049021.1 Cyclin-dependent kinase inhibitor 3

−2.94 −1.39 2.14

−3.81 −1.52 2.64

−6.17 −2.55 3.21

−1.05 −1.14 −1.09

−1.19 −1.19 1.15

−4.05 −1.61 1.25

Cell death (GO: 0008219 (bp)) BG739102 EST—weak similarity to growth arrest and DNA damage inducible, ␤ NM205741 Mcl1b NM213310 egl homolog 3

8.98 −1.67 3.14

8.54 −2.88 3.74

15.51 −3.93 4.63

1.37 1.17 2.37

2.15 −1.97 3.86

3.04 −3.26 2.88

Lipid metabolism (GO: 0006629 (bp)) NM213634 Lipocalin-type prostaglandin D synthase-like protein NM131818 Angiopoietin-like 3 NM131849.1 Alcohol dehydrogenase 5 (adh5), mRNA. NM213404 Lipase A NM199731 Tocopherol (alpha) transfer protein NM131128 Apolipoprotein A-I NM001004529 Enoyl coenzyme A hydratase, short chain, 1, mitochondrial

−2.71 −2.78 −1.52 −1.27 −1.58 1.22 −1.13

−3.72 −3.75 −3.05 −1.47 −1.87 −1.97 −1.46

−5.48 −3.58 −3.34 −2.34 −2.19 −2.01 −1.60

−1.05 −2.04 −1.33 1.13 −1.19 −3.03 −1.14

−2.45 −3.40 −4.59 −1.80 −1.31 −6.48 −1.64

−3.67 −4.58 −10.24 −2.02 −2.15 −2.85 −2.57

Vitamin metabolism (GO: 0006766 (bp)) NM201331 Retinol dehydrogenase 10 NM198069 Retinol dehydrogenase 1 NM199609 Retinol dehydrogenase 1-like NM131217 Retinoid × receptor, alpha NM131799 Beta-carotene 15, 15-dioxygenase 2 NM201471 Aldehyde dehydrogenase 9

1.64 −1.19 −2.05 −1.72 −2.21 −1.86

2.45 −1.88 −3.23 −1.46 −2.27 −4.21

4.57 −2.44 −5.59 −1.92 −3.70 −6.20

2.33 −1.11 1.11 1.18 −1.10 1.15

1.78 −2.64 −2.14 −1.24 −1.20 −2.82

3.61 −5.22 −2.88 −1.72 −2.24 −3.91

5.16 2.99 5.75 3.47

7.55 5.80 8.69 5.65

10.72 7.27 8.73 5.23

1.52 1.22 1.50 2.04

3.84 3.85 7.18 5.11

2.29 2.82 6.61 3.19

Hormone metabolism (GO: 0042445 (bp)) NM212720 Hydroxysteroid 11-beta Dehydrogenase 2 NM199809 Hydroxy-
-5-steroid dehydrogenase, 3␤- and steroid
-isomerse NM001007283 Deiodinase, iodothyronine, type I NM212789 Deiodinase, iodothyronine, type II

1.86 −1.49 −1.95 −1.03

−4.67 −2.21 −3.09 −1.76

−4.23 −3.38 −5.16 −2.80

−2.14 −1.84 −2.18 −1.15

−9.63 −2.16 −4.54 −2.32

−16.15 −4.31 −6.83 −4.14

Steroid binding (GO: 0005496) (mf)) NM001007151 Sex hormone binding globulin NM194368 Hepatocyte nuclear factor 4 alpha

−1.74 −1.68

−2.54 −1.70

−6.32 −2.82

1.01 −1.30

−2.11 −2.22

−5.46 −3.07

Sterol biosynthesis (GO: 0016126 (bp)) NM001001730 Cytochrome P450, family 51 NM201330 7-dehydrocholesterol reductase NM201085 3-hydroxy-3-methylglutaryl-coenzyme A synthase 1 (soluble) NM213353 Sterol-C4-methyl oxidase-like

Fold-changes were determined by calculating the ratio of the mean expression values from the control and treated samples.

that generally result in a decrease of plasma levels of cholesterol (Bravo et al., 1999; Koopen et al., 1999; Bravo et al., 2001; Parini et al., 2000). This effect is, in part, due to an increase in low-density lipoprotein receptor (ldlr) which has been shown to facilitate the uptake of cholesterol from plasma into cells via endocytosis in response to estrogenic compounds (Parini et al., 2000; Smith et al., 2004). Consistent with previous reports, we observed a significant increase in ldlr mRNA in zebrafish exposed to EE2 providing some evidence that plasma levels of

cholesterol may have been reduced. The expression of genes involved in cholesterol biosynthesis is known to be regulated via negative cholesterol feedback (Fink et al., 2005). Under sterollimiting conditions in estrogen-exposed animals, the expression of genes involved in cholesterol biosynthesis is upregulated. This was corroborated by observations in this study in which the expression of several genes involved in the synthesis of cholesterol were increased in a concentration-dependent manner by exposure to EE2, including cytochrome P45051 (cyp51) which

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Table 8 Comparison of fold-change values of selected genes analyzed using microarray and qRT-PCR Gene name

24 h

168 h

15 ng/L

ptma igf2 igfbp1 CYP1A1 GAPDH Dio2 Vtg

40 ng/L

100 ng/L

15 ng/L

40 ng/L

100 ng/L

Chip

qPCR

Chip

qPCR

Chip

qPCR

Chip

qPCR

Chip

qPCR

Chip

qPCR

−1.87 −1.98 4.54 −1.72 −1.02 −1.03 1.10

−2.43 −2.54 4.42 −3.07 −1.65 −2.20 1.09

−2.51 −3.92 13.12 −3.42 1.29 −1.76 1.28

−3.20 −3.14 14.16 −3.89 −1.01 −3.25 1.36

−3.35 −8.55 21.37 −9.80 −1.11 −2.80 1.09

−3.89 −5.10 22.04 −14.12 −1.30 −4.29 1.56

−1.15 −1.06 1.03 1.12 1.20 −1.15 1.19

−1.87 −1.12 −1.72 −1.15 1.04 −1.15 1.06

−2.50 −4.05 7.66 −1.84 2.62 −2.32 1.01

−3.05 −4.76 4.17 −1.95 2.29 −3.01 1.27

−3.96 −7.94 6.55 −4.57 4.11 −4.14 −1.11

−3.12 −6.32 4.47 −7.57 2.43 −5.24 1.03

Fold-changes were determined by calculating the ratio of the mean expression values from the control and treated samples. Abbreviations—ptma: prothymosin alpha like-1; igf2: insulin-like growth factor 2 precursor; igfbp1: insulin-like growth factor binding protein 1; cyp1a: cytochrome P450 1A1; GAPDH: glyceraldehyde-2phosphate dehydrogenase; dio2: deiodinase, iodothyronine, type II; vtg: vitellogenin.

encodes sterol 14␣-demethylase, 7-dehydrocholesterol reductase (dhcr7), and sterol-C4-methyl oxidase-like (sc4mol). The catabolism of cholesterol to bile acids is a primary route for the elimination of cholesterol from the body and, thus, is a critical pathway in the maintenance of cholesterol homeostasis. It has been widely shown that estrogens induce cholestasis, a condition that leads to a reduction in bile flow and therefore leads to hepatic accumulation of bile acids (Stieger et al., 2000; Sanchez Pozzi et al., 2003). Bile acids exert negative feedback inhibition on their own synthesis via both transcriptional and translational mechanisms (Rao et al., 1999; St. Pierre et al., 2001; Castillo-Olivares et al., 2004). In concordance, two genes involved in bile acid synthesis, sterol 27-hydroxylase (cyp27) and sterol 12-alpha hydroxylase (cyp8b), were significantly reduced in a concentration-dependent manner in response to EE2 exposure. Genes involved in vitamin A biosynthesis, metabolism and transport were affected by exposure to EE2, including retinoic acid receptor alpha 2a (rara2a), several retinol dehydrogenases (rdh), and retinol binding protein (rbp2a). Consistent with results from this study, previous studies have demonstrated that exposure of ovariectomized mice and murine embryos to estrogenic compounds E2 or Bisphenol A, respectively, upregulated expression of retinoic acid receptor (Celli et al., 1996; Nishizawa et al., 2005). The expression of retinol binding protein (rbp) has been proposed as a possible biomarker for exposure to a wide variety of endocrine disrupting compounds based on results in Xenopus laevis hepatocytes (Levy et al., 2004). However, these authors observed a significant increase in rbp expression in Xenopus laevis hepatocytes in response to E2 while we observed a decrease. This suggests the model system used in these two studies responds differently to estrogen. Our results were consistent to those obtained in rainbow trout in which rbp mRNA was significantly reduced in livers of E2-exposed fish (Sammar et al., 2001). EE2 is known to induce hepatocarcinogenesis in female rats (Yager et al., 1994). While exposure to EE2 initially results in liver hyperplasia, it is followed by a reduction in hepatocyte proliferation and an increase in apoptosis (Mayol et al., 1992; Yager et al., 1994; Koroxenidou et al., 2005). In the

present study, genes involved in apoptosis including cyclindependent kinase inhibitor 1b (cdkn1b) and growth arrest and DNA-damage inducible gene 45b (gadd45b) were significantly upregulated following EE2 exposure. Consistent with an increase in the pro-apoptotic genes, cdkn1b and gadd45b, genes involved in regulating growth and proliferation including insulin-like growth factor precursor (ilgf2), insulin like growth factor binding protein I (igfbp1), and insulin-like growth factor 1(ilgf1) were altered in a concentration-dependent manner following exposure to EE2. Our observations corroborate results from previous studies with mice, rats, and teleost fish that demonstrated that exposure to estrogens alters the expression of insulin-like growth factor genes within hours or a few days after initiation of exposure (Naciff et al., 2003; Boverhof et al., 2004; Carnevali et al., 2005). In this study, exposure of zebrafish to EE2 altered the expression of genes involved in growth and proliferation as early as 24 h. This suggests that EE2 exposure initially alters transcription of genes involved in growth and proliferation that ultimately leads to the growth-inhibitory effect that has been reported after prolonged exposure to estrogens (Yager et al., 1994). Using zebrafish microarrays, we have identified over 1600 genes in the liver of zebrafish affected by EE2 in a concentrationdependent manner (p ≤ 0.001). In addition to changes in gene expression, we have confirmed that EE2 exposure resulted in effects at higher levels of biological organization as evidenced by alterations in GSI, E2, T, and VTG. Although it is beyond the scope of this manuscript to fully characterize the mode of action of EE2 in zebrafish, we used GO analysis to identify a variety of biological functions and molecular functions affected by EE2 exposure. Further, we were able to relate some of the affected genes to an estrogen mode of action. However, in some cases, the identity of genes that were highly affected by EE2 exposure (−5 ≤ fold change ≥ 5) is unknown. As the zebrafish genome becomes better annotated, it is expected that more relevant genes will be identified. Many of the genes that we have discussed responded in a concentration-dependent manner and have the potential to be used as biomarkers of exposure to strong estrogens. To further validate the use of any genes identified in this study as biomarkers of exposure to a wide range of estro-

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