ToxSci Advance Access originally published online on May 21, 2007
Toxicological Sciences 2007 98(2):395-407; doi:10.1093/toxsci/kfm124
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Published by Oxford University Press 2007.
Transcription of Key Genes Regulating Gonadal Steroidogenesis in Control and Ketoconazole- or Vinclozolin-Exposed Fathead Minnows
* U.S. Environmental Protection Agency, ORD, NHEERL, Mid-Continent Ecology Division, Duluth, Minnesota 55804
U.S. Environmental Protection Agency, ORD, NERL, Ecological Exposure Research Division, Cincinnati, Ohio 45268
Pacific Northwest National Laboratory, Richland, Washington 99352
1 To whom correspondence should be addressed at U.S. Environmental Protection Agency, ORD, NHEERL, Mid-Continent Ecology Division, 6201 Congdon Blvd, Duluth, MN 55804. Fax: (218) 529-5003. E-mail: villeneuve.dan{at}epa.gov.
Received April 12, 2007; accepted May 4, 2007
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONSUPPLEMENTARY DATAFUNDINGREFERENCES |
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This study evaluated changes in the expression of steroidogenesis-related genes in male fathead minnows exposed to ketoconazole (KTC) or vinclozolin (VZ) for 21 days. The aim was to evaluate links between molecular changes and higher level outcomes after exposure to endocrine-active chemicals (EACs) with different modes of action. To aid our analysis and interpretation of EAC-related effects, we first examined variation in the relative abundance of steroidogenesis-related gene transcripts in the gonads of male and female fathead minnows as a function of age, gonad development, and spawning status, independent of EAC exposure. Gonadal expression of several genes varied with age and/or gonadal somatic index in either males or females. However, with the exception of aromatase, steroidogenesis-related gene expression did not vary with spawning status. Following the baseline experiments, expression of the selected genes in male fathead minnows exposed to KTC or VZ was evaluated in the context of effects observed at higher levels of organization. Exposure to KTC elicited changes in gene transcription that were consistent with an apparent compensatory response to the chemical's anticipated direct inhibition of steroidogenic enzyme activity. Exposure to VZ, an antiandrogen expected to indirectly impact steroidogenesis, increased pituitary expression of follicle-stimulating hormone ß-subunit as well as testis expression of 20ß-hydroxysteroid dehydrogenase and luteinizing hormone receptor transcripts. Results of this study contribute to ongoing research aimed at understanding responses of the teleost hypothalamic-pituitary-gonadal axis to different types of EACs and how changes in molecular endpoints translate into apical outcomes reflective of either adverse effect or compensation.
Key Words: steroidogenesis inhibitor; antiandrogen; reproduction; gonad development; real-time PCR; testis.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONSUPPLEMENTARY DATAFUNDINGREFERENCES |
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Over the last 10–15 years, considerable effort has been directed toward identifying endocrine-active compounds (EACs) and characterizing their effects. However, to date, relatively few studies have established linkages between molecular changes and apical outcomes that are needed to support scientifically credible use of biomarkers, species, and dose extrapolations, and/or application of predictive models in ecological risk assessments related to EACs. This study is part of an ongoing research effort aimed at providing more comprehensive and integrated characterization of the effects of EACs at multiple levels of biological organization ranging from molecular responses to whole-animal outcomes (e.g., reproductive impairment) using small fish models, particularly the fathead minnow (Pimephales promelas). The fathead minnow is a well established and widely used model for regulatory ecotoxicology testing, including legislatively mandated screening for substances that could adversely affect reproduction through interactions with the hypothalamic-pituitary-gonadal (HPG) axis (Ankley and Villeneuve, 2006
; U.S. EPA, 1998). Recently, Villeneuve et al. (2007a) developed a graphical systems model that summarizes our current understanding of the molecular and biochemical interactions that regulate reproductive functions of the HPG-axis in asynchronous-spawning teleost fish, like the fathead minnow. Through systematic perturbation of the HPG-axis using EACs specifically selected to target different components, we are developing a greater understanding of system-wide responses to chemical stressors and how molecular and biochemical changes translate into apical outcomes reflective of adverse effects or compensation. This type of information will help address ecotoxicological needs related to use of biomarkers, extrapolation, and predictive models in evaluating risks associated with EAC exposure.
The work described herein focused on fathead minnow genes that regulate gonadal steroidogenesis (Fig. 1). Gonadal steroids play critical roles in regulating reproduction as well as growth and development (Norris, 2007). Steroid synthesis is facilitated by steroidogenic acute regulatory protein (StAR) which plays a rate-limiting role in supplying cholesterol, the precursor for steroid synthesis, to the inner mitochondrial membrane (Fig. 1; Miller, 1988; Stocco, 2001; Stocco and Clark, 1996). Steroids are synthesized from cholesterol through a series of reactions catalyzed primarily by several cytochrome P450s, including CYP11A (cholesterol side-chain cleavage; P450scc), CYP17 (cytochrome P450 c17
-hydroxylase, 17, 20-lyase), and CYP19A (cytochrome P450 aromatase, A-isoform); and hydroxysteroid dehydrogenases (HSDs), including 3ß-HSD, 20ß-HSD, and 11ß-HSD (Fig. 1; Agarwal and Auchus, 2005; Miller, 1988, 2005; Norris, 2007). Through interactions with membrane-bound gonadotropin receptors (e.g., luteinizing hormone receptor [LHR] and follicle-stimulating hormone receptor [FSHR]) on the surface of gonad cells, pituitary gonadotropins including LH and FSH play a key role in regulating steroidogenic gene expression and steroid-dependent feedback mechanisms (Chyb et al., 1999; Kumar and Trant, 2001; Mateos et al., 2002; Montserrat et al., 2004; Payne and Youngblood, 1995; Schulz et al., 2001; Yaron et al., 2003). Futhermore, redox partners of steroidogenic enzymes may also play key roles in regulating steroidogenesis (Miller, 2005). For example, allosteric interaction between cytochrome b5 (cyt b5) and CYP17 has been reported to favor the 17,20 lyase activity of CYP17 over its hydroxylase activity (Akhtar et al., 2005; Miller, 2005). Given the potential for EACs to influence steroidogenesis through direct or indirect mechanisms (Sanderson, 2006), and the important role of steroids in regulating the HPG-axis, these genes were considered important targets to study. Consequently, we developed quantitative real-time polymerase chain reaction (QPCR) assays to measure their transcripts in fathead minnows.
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Before investigating the impact of EACs on the expression of steroidogenesis-related genes, we wanted to develop an understanding of the baseline variability in the abundance of the target messenger RNA (mRNA) transcripts under conditions similar to those used for EAC testing (Ankley et al., 2001
). In particular, we hypothesized that expression of these genes could vary as a function of fish age, relative gonad development, spawning activity, and sex. Those hypotheses were tested in two experiments conducted with nonexposed male and female fathead minnows. Data from the baseline experiments were used to determine whether these variables should be controlled through experimental design and/or considered in statistical analyses in order to discriminate the direct effects of the EACs from indirect effects or confounding factors associated with these variables.
Knowledge gained from the baseline studies was then applied to the primary study goal of examining the effects of two endocrine-active fungicides, ketoconazole (KTC) and vinclozolin (VZ), on the expression of steroidogenesis-regulating genes in the testis of male fathead minnows at the same time point other in vivo and ex vivo endpoints had been examined (e.g., 21 days; see Ankley et al., 2007; Martinovic et al., submitted for publication). KTC has been shown to inhibit steroidogenic CYPs (Albertson et al., 1988; Feldman, 1986; Morita et al., 1990) and would be expected to directly impact the steroidogenic pathway. In contrast, the active metabolites of VZ act as androgen receptor (AR) antagonists (Gray et al., 1994; Kelce et al., 1994) and would be expected to indirectly impact steroidogenesis. We hypothesized that both EACs would elicit changes in the expression of steroidogenesis-related genes and that the nature of those changes would reflect differences in their modes of action and associated apical effects. The overall aim of these studies was to enhance our understanding of the continuum of biological response to these chemical stressors over multiple levels of biological organization.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONSUPPLEMENTARY DATAFUNDINGREFERENCES |
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Animals and test chemicals.
Fathead minnows (Pimephales promelas) were obtained from an on-site culture facility at the Environment Protection Agency (EPA) laboratory in Duluth, MN. Laboratory procedures involving animals were reviewed and approved by the local Animal Care and Use Committee in compliance with Animal Welfare Act regulations and Interagency Research Animal Committee guidelines. KTC (99% pure) was obtained from Sigma-Aldrich (St Louis, MO). VZ (99% pure) was purchased from Crescent Chemical Company (Hauppauge, NY).
Complementary DNA sequences for fathead minnow genes.
Complementary DNA (cDNA) sequences used to design the primers and dual-labeled probes for the QPCR assays were derived from three sources. Partial cDNA sequences for fathead minnow CYP17, CYP19A, LHß, and FSHß were previously described (Halm et al., 2003; Villeneuve et al., 2006, 2007b) and are available in GenBank (National Center for Biotechnology Information; NCBI; Table 1). Partial cDNA sequences for fathead minnow StAR, CYP11A, and FSHR were determined specifically for this study. Finally, partial cDNA sequences for fathead minnow 3ß-HSD, 11ß-HSD, 20ß-HSD, LHR, and cytochrome b5 were identified from a large library of fathead minnow expressed sequence tags (ESTs) submitted to the NCBI nucleotide database by the Joint Genome Institute.
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To derive partial cDNA sequences for StAR, CYP11A, and FSHR, total RNA was extracted from the gonads of six male and six female fathead minnows using Tri-Reagent (Sigma, St Louis, MO) and pooled by sex. cDNA was prepared using Superscript II reverse transcriptase (Invitrogen, Carlsbad, CA). The target cDNAs were amplified using degenerate primers designed using the CODEHOP strategy and web-based software (Table S.1; Rose et al., 1998
). For FSHR, care was taken to select degenerate primers derived from portions of the amino acid sequence distinct from those of LHR and thyroid stimulating hormone receptor, which are highly homologous (Kumar and Trant, 2001). PCR products were obtained using a touchdown PCR protocol described previously (Villeneuve et al., 2007b). Products excised from a 1.5% agarose gel (Nusieve GTG agarose, Fischer Scientific, Pittsburgh, PA) and extracted using a Nucleotrap gel extraction kit (BD Biosciences, Clontech, Palo Alto, CA) were sequenced by fluorescence dye termination reaction (DYEnamic ET dye terminator cycle sequencing kit, Amersham Biosciences, Cleveland, OH) with a MegaBACE 1000 DNA analysis system (Amersham, Piscataway, NJ). For StAR and CYP11A, additional sequence information was generated by random amplification of cDNA ends (RACE) using a BD SMART RACE cDNA amplification kit (BD Biosciences; see Table S.2 for RACE primer sequences). The identity of the partial cDNA sequences obtained was verified by BLASTx search and sequence alignment (Table 2; Altschul et al., 1997) and submitted to GenBank.
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For 3ß-HSD, 11ß-HSD, 20ß-HSD, LHR, and cyt b5, zebrafish (Danio rerio) nucleotide sequences were used as query sequences (Table 1) for a nucleotide–nucleotide BLAST (BLASTn) search of the Pimephales promelas EST database. Putative, partial, fathead minnow cDNA sequences for each gene were identified (Table 1). Identity of the putative fathead minnow sequences relative to the zebrafish query sequence was greater than 84% for all genes, and Expect values (E-values) were very close to zero (Table 1) indicating good confidence in the sequence match.
Quantitative real-time PCR.
The various cDNA sequences were used to design gene-specific oligonucleotide primers and dual-labeled DNA probes for QPCR assays and development of gene-specific mRNA standards (Table S.2). To prepare standards, gene-specific cDNA was amplified from a pool of mixed male and female gonad cDNA using W-FW and W-RV primer pairs (Table S.2). That product was then used for a second round of PCR amplification using T7-FW and W-RV primers (Table S.2) to generate an amplicon containing a phage T7 RNA polymerase promoter. mRNA was prepared from the T7 products using high-yield in vitro transcription (MEGAscript, Ambion, Austin, TX). The size and purity of each mRNA standard was confirmed using an Agilent 2100 Bioanalyzer and an RNA 6000 Nano Labchip kit (Agilent, Palo Alto, CA) and an RNA 6000 Ladder (Ambion). Concentrations of mRNA standards and total RNA from experimental samples were quantified using a Nanodrop ND-1000 spectrophotometer (Nanodrop Technologies, Wilmington, DE). Prior to analyzing the samples from a given experiment, samples were diluted to a uniform concentration. Appropriate dilutions of samples and standards were prepared in RNAse-free water. All QPCR assays were performed in duplicate using a Taqman EZ RT-PCR kit (Applied Biosystems, Foster City, CA). Each 25-µl reaction contained 50 ng total RNA (except female age-series ovary samples and pituitary samples where 25 and 10 ng, respectively, were used), 150nM of the appropriate probe (except for FSHß, 300nM), 200nM forward primer, and 200nM reverse primer (Table S.2). Samples were reverse-transcribed (50°C for 2 min, 60°C for 30 min, 95°C for 5 min) followed immediately by 40 cycles of PCR amplification (melt 94°C for 20 s, anneal and extend 58°C for 60 s) using a 7500 Real-Time PCR System (Applied Biosystems). A standard curve of known molar quantities of the appropriate gene-specific mRNA (10-fold dilution series, generally 50–5 x 107 copies) was used to calibrate the QPCR data and values interpolated from the standard curve were normalized to the mass of total RNA in the reaction and expressed as copies mRNA/ng total RNA for each sample. Intrassay CVs were typically less than 10% for duplicate measurements of the same sample and statistical comparisons were restricted to samples run in the same assay, thus eliminating interassay variability as a factor in the analyses.
The nature of real-time PCR data needs to be considered when interpreting the study results. Due to potential differences in amplification and probe-binding efficiencies between total RNA samples and purified mRNA standards, copies mRNA/ng total RNA should be regarded as an approximate and relative estimate of the number of transcripts, as opposed to an absolute quantification of transcript abundance. Furthermore, because we normalized to total RNA extracted from tissues composed of multiple cell types, changes in transcription of the gene of interest within one or more given cell types cannot be discriminated from changes in the proportions of the various cell types (e.g., proliferation of a specific type of cells) that express that gene at different basal levels. Normalization to house-keeping or reference genes would have similar limitations unless similar basal expression in all cell types within the tissue of interest was validated. Unlike normalization to house-keeping genes, normalization to total RNA does not control for variations or errors in the reverse transcription or PCR (Huggett et al., 2005). However, in these experiments use of a single-step real-time PCR method in which the reverse transcription and PCR are conducted in the same well of a 96-well plate, using the same master-mix for all samples run on that plate, provides an effective methodological control that should minimize any variation during those steps. Questions have been raised about the utility of house-keeping or reference genes for real-time PCR normalization with authors concluding that reference genes need to be validated for each set of experimental conditions to assure they are not influenced by those conditions (e.g., Arukwe, 2006; Dheda et al., 2005; Huggett et al., 2005). However, as Huggett et al. (2005) point out, reference gene validation experiments themselves are subject to the same problems of normalization and often simply rely on normalization to total RNA. Given that all normalization strategies are subject to some degree of error, we felt that normalization to total RNA and calibration to a gene-specific mRNA standard curve was a reliable and reproducible approach well suited to the single-step methodology employed.
Baseline experiments (age series, pre-/postspawn).
Details regarding the experiments used to generate the age-series and pre-/postspawn samples were described by Villeneuve et al. (2007b). Briefly, for the age-series study we examined samples collected from 12 males and 12 females from each of three different age classes (3, 4, and 5 months old) in an effort to survey fish with a wide range of gonad development, from relatively immature animals with recently differentiated gonads to fish with mature gonads. Fish examined in the age-series experiment were held under conditions not considered ideal for spawning (i.e., mass culture with large numbers mature of males and females). In contrast, for the pre-/postspawn experiment, pairs of fish (one male, one female per tank) were held under breeding conditions. Pairs were sampled either within 24 h of spawning (postspawn) or within 24 h of their next expected spawning date (prespawn) as determined based on spawning frequency observed during a monitoring period of 11–24 days. Samples from seven or eight prespawn and postspawn pairs were examined in this study. For both experiments, one gonad from each fish was preserved for histological staging while the other was preserved in RNAlater (Sigma) for extraction of the RNA samples used in the QPCR assays. Details regarding various morphometric endpoints, plasma vitellogenin and steroid concentrations, fecundity of the pre-/postspawn fish, and pituitary LHß and FSHß expression for these baseline studies are reported elsewhere (Villeneuve et al., 2007b).
KTC experiment.
Groups of four female and two male fathead minnows were held in test tanks (four replicate tanks per treatment), supplied with spawning substrates to encourage reproduction, and exposed to nominal KTC concentrations of 0, 6, 25, 100, or 400 µg/l delivered in a continuous flow of Lake Superior water for 21 days. Pituitary and gonad samples were collected and preserved in RNAlater for RNA extraction and QPCR analysis. Samples from both males and two females from each replicate tank were extracted to provide a sample size of n = 8 per sex per treatment for most analyses. For this study we focused on analysis of the relative abundance of steroidogenesis-regulating gene transcripts in pituitary and testis RNA samples from males. Full details regarding the KTC experiment including apical and molecular responses of the test animals to the pesticide are provided by Ankley et al. (2007). Data for two of the steroidogenesis-related genes considered in this study, CYP11A and CYP17, were also reported in that paper.
VZ experiment.
For the VZ experiment, test tanks were divided into two equal-sized sections with a screen and one male and one female fathead minnow were placed, together with a spawning substrate, on each side of the divider. Fish were exposed to nominal water concentrations of 100, 400, and 700 µg VZ/l delivered in a continuous flow of Lake Superior water for 21 days and there were five replicate tanks per treatment (Martinovic et al., submitted for publication). Pituitary and gonad samples were collected and preserved in RNAlater for subsequent RNA extraction and QPCR analysis. For this study we focused on analysis of steroidogenesis-regulating gene transcripts in male pituitary and testis. Full details regarding the VZ study, including description of the apical and molecular responses of the fish to VZ exposure, are described elsewhere (Martinovic et al., submitted for publication). Data for one of the steroidogenesis-related genes considered in this study, 11ß-HSD, were reported in that paper.
Data analysis.
Normality of the QPCR data was tested using a Kolmogorov–Smirnov test. Levene's test was used to test for homogeneity of variance. In cases where the QPCR data or transformed data met parametric assumptions, one-way analysis of variance (ANOVA) was used to test for differences across groups, while differences between groups were determined using Duncan's multiple range test. General linear model ANOVA was used to test for interactions between chemical treatments and quantitative factors like gonadal somatic index (GSI). For the few cases in which the data (or transformed data) did not conform to parametric assumptions, a nonparametric Kruskall–Wallis test was used to test for differences across groups, and Dunn's test was used to determine which groups differed significantly from one another. Differences were considered significant at p < 0.05, unless otherwise noted. Correlation analysis was based on Pearson correlation coefficients which were also considered significant at p < 0.05, unless otherwise noted. All statistical analyses were conducted using SAS 9.0 (SAS Institute, Cary, NC), except Dunn's test which was conducted using GraphPad Instat v. 3.01 (GraphPad Software, San Diego, CA).
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONSUPPLEMENTARY DATAFUNDINGREFERENCES |
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Age-Series Experiment
For the age-series experiments, variability of steroidgenesis-related gonadal gene transcripts was analyzed as a function of age (Table 3), histologically determined gonad stage (Fig. S.1), and GSI (Table 3). Among males, four of the 10 gonad transcripts examined, 11ß-HSD, 3ß-HSD, CYP11A, and StAR varied significantly as a function of age class (Table 3). All four genes were most highly expressed in the 5-month-old males (Table 3). In the case of females, 20ß-HSD, 3ß-HSD, CYP17, CYP11A, CYP19A, and FSHR expression varied significantly as a function of age (Table 3). For 20ß-HSD, 3ß-HSD, and CYP11A, the mean transcript abundance for the 4-month-old females was different from that of 3- and 5-month-old females (Table. 3). For CYP17 and CYP19A, all age classes differed significantly, with 4-month-old fish having the lowest abundance of these gene transcripts (Table 3). Expression of FSHR was significantly greater in the 3-month-old females than in either other age class (Table 3). Overall, CYP11A and 3ß-HSD were the only genes whose transcript abundance varied as a function of age in both male and female gonads.
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Transcript abundance of six of the 10 genes examined was significantly correlated with GSI for either males or females (Table 3). In the case of females, all the statistically significant correlations with GSI were negative (Table 3). The negative correlations were particularly pronounced for 20ß-HSD, 3ß-HSD, and LHR (Table 3). For males, CYP11A and StAR expression in testis was significantly, and positively, correlated with GSI (Table 3). FSHR expression in testis was negatively correlated with GSI, but statistical significance was marginal (Table 3).
Statistical evaluation of gonad transcript abundance as a function of stage was somewhat limited due to imbalances in the sample size in each class (n = 1–14 for females; n = 1–11 for males). Overall, the distribution of gonad stages in the three age classes resulted in a sample population biased toward stage 2–3 testes and 3–3.5 ovaries (Villeneuve et al., 2007b). Only CYP11A transcript abundance in testis was found to vary significantly as a function of gonad stage (Figs. 2 and S.1). Expression of 3ß-HSD in gonad was significantly, and positively, correlated with testis stage but negatively correlated with ovary stage (Fig. 2). Several transcripts seemed to show stage-dependent trends or differences in their relative abundance (e.g., LHR in males and females; CYP17 in females; 11ß-HSD in males) but the observed differences were not significant (Fig. S.1).
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Pre-/Postspawn Experiment
The pre-/postspawn experiment was designed to evaluate whether expression of steroidogenesis-related genes would be influenced by discrete spawning events. In general, mean transcript abundance in the gonads of fish that had spawned in the previous 24 h (postspawn) was not significantly different from that of fish that had not spawned for 2–4 days, but were expected to spawn within the next 24 h (prespawn; Table 3). The only exceptions were CYP19A expression in ovary tissue and a statistically marginal difference in LHR expression in testis tissue (p = 0.0553; Table 3).
Data from the pre-/postspawn experiment were also used to compare relative gene expression in reproductively active males and females. This data set was well suited for comparison between sexes because the sample sizes made it feasible to analyze both male and female samples on the same 96-well plate, thus eliminating interassay variability as a potential confounding factor. There were significant differences in transcript abundance (normalized to total RNA) between sexes for seven of the 10 genes examined in gonad tissue (Table 3). In the case of 11ß-HSD, CYP17, CYP11A, StAR, and FSHR, transcript abundance was significantly greater in males than in females (Table 3). Expression of 20ß-HSD and CYP19A was greater in females than in males (Table 3). The gonadal abundance of 3ß-HSD, cyt b5, and LHR transcripts in gonad tissue did not differ between sexes (Table 3).
KTC Experiment
Twenty one days of exposure to KTC significantly impacted the expression of a number of genes in the pituitary and gonad tissue of male fathead minnows. Effects on FSHß and LHß expression in pituitary tissue, and CYP11A and CYP17 expression in testis tissue were reported elsewhere (Ankley et al., 2007; Villeneuve et al., 2007b). Here we also report significant effects on the expression of StAR, 20ß-HSD, and cyt b5 in testis (Fig. 3). In all cases, fish exposed to 400 µg KTC/l had significantly greater abundance of these transcripts than those of control males or males exposed to lesser concentrations (Fig. 3). StAR, was the only gene whose expression was significantly elevated at lesser concentrations, although the apparent effect was only significant at 6 µg KTC/l (Fig. 3). Overall, observation of significant effects in the 400 µg/l treatment was consistent with the concentration–response data for CYP11A, CYP17, and FSHß expression (Ankley et al., 2007; Villeneuve et al., 2007b). KTC did not significantly affect expression of LHR, FSHR, 3ß-HSD, or 11ß-HSD in testis (Fig. S.2).
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VZ Experiment
Exposure to VZ for 21 days had a significant impact on the expression of four of the 11 genes examined in males (Fig. S.3, Martinovic et al., submitted for publication). In pituitary tissue, mean FSHß expression was significantly elevated in fish exposed to 700 µg VZ/l (Fig. 4), but there was no effect on LHß expression (Fig. S.3). The FSHß expression in pituitary showed a concentration-dependent increase (Fig. 4). Similar concentration-dependent increases were observed for 20ß-HSD (Fig. 4) and 11ß-HSD (Martinovic et al., submitted for publication) expression in testis tissue. The most sensitive of the 11 transcripts examined in the testis was LHR which was significantly elevated in all three VZ treatments (Fig. 4). Overall, expression of steroidogenesis-regulating genes in pituitary and testis tissue was universally either upregulated or unaffected by VZ exposure (Fig. S.3). There was no evidence of downregulation in response to the fungicide.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONSUPPLEMENTARY DATAFUNDINGREFERENCES |
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Utility of the Fathead Minnow in Molecular Investigations
Real-time PCR methods for measuring expression of fathead minnow CYP11A, StAR, 3ß-HSD, 20ß-HSD, LHR, FSHR, and cyt b5 transcripts were developed to support the objectives of this study. Obtaining cDNA sequences for the genes of interest was the critical step in the method development. Direct sequencing of amplicons isolated and amplified using degenerate primers provided the necessary sequence information for CYP11A, StAR, and FSHR. Furthermore, although the fathead minnow genome has not been completely sequenced, the increasingly well annotated zebrafish (D. rerio) genome provides a robust library of teleost sequence information that can be used to query over 250,000 fathead minnow ESTs made available in the NCBI database through the efforts of the Joint Genome Institute (U.S. Department of Energy, Walnut Creek, CA). This approach was successfully used in this and another recent study (e.g., Martinovic et al., submitted for publication) to identify putative cDNA sequences for fathead minnow genes. Another recent study reported that clustering of the 250,000 fathead minnow ESTs has yielded approximately 36,000 unique gene sequences (Larkin et al.
, in press). Thus, although the fathead minnow initially lagged behind some other small fish models such as zebrafish with respect to its utility for systems-oriented and genomic-level ecotoxicology research, there is now ample information to support the routine use of the species for such investigations (Ankley and Villeneuve, 2006). This has facilitated a much greater capacity to establish links between molecular changes and toxicological outcomes using this important ecotoxicology test species.
Age-Series Experiment
The primary goal of the age-series experiment was to determine the degree to which variation in age, GSI, and/or gonad stage influenced the expression of the target genes. Such information was needed to help interpret the results of chemical exposure experiment. There were significant differences in relative transcript abundance between age classes for four and six of the genes examined in males and females, respectively (Table 3). Differences in the distribution of fish with different GSI and gonad stage within each age class likely accounted for some of the age-related variation. For example, the gonad stage and GSI of females in the 4-month class was less variable than that in the other classes (Villeneuve et al., 2007b). Correspondingly, the 4-month-old females differed from the other ages the most frequently (Table 3). However, age-related differences were detected for a number of genes for which no significant differences among stages and no significant correlation to GSI was observed (e.g., 11ß-HSD in males, CYP17 and CYP19A in females). This suggests that, at least for certain genes, age-related differences in expression were not solely attributed to differences in gonad status. Other unidentified age-related factors seem to be involved. Overall, the results highlight the importance of using well-defined age classes for experiments that consider steroidogenesis-related gene expression endpoints.
Changes in gonadal steroid production help regulate germ cell development in fish gonads (Arukwe and Goksøyr, 2003; Cavaco et al., 2001; Patiño et al., 2001; Weltzien et al., 2004; Yaron, 1995). Regulation of these changes is thought to be mediated by the binding of gonadotropins to their receptors on the surface of gonadal cells (Kusakabe et al., 2006; Patiño et al., 2001; Weltzien et al., 2004; Yaron, 1995). In synchronous-spawning species like rainbow trout (Oncorhynchus mykiss), expression of steroidogenesis-related genes, and gonadotropin receptors has been shown to vary over the course of gonad development (Kusakabe et al., 2006). The fathead minnow is an asynchronous-spawning species that has germ cells at multiple stages of development present in its gonads. Nonetheless, variation in the expression of steroidogenesis-related genes in the gonad as a function of GSI or gonad stage might also be expected. Consequently, we hypothesized that GSI and/or gonad stage might need to be considered in analyses aimed at evaluating links between molecular and apical effects.
With the exception of CYP11A and 3ß-HSD transcripts in testis, we did not find gonad stage to be a robust predictor of differences in the transcript abundance of steroidogenesis-related genes. However, expression of a number of the genes was significantly correlated with GSI. Given that GSI is a comparatively easy measurement to collect, the results suggest that routine examination of the significance of GSI as a variable in statistical analyses designed to test for chemical effects on steroidogenesis-related gene expression would be useful. In some cases (e.g., examination of 20ß-HSD, 3ß-HSD, or LHR in females or CYP11A and StAR in males) consideration of GSI should aid the detection of chemical impacts over background heterogeneity in gonad status among the fish sampled. Additionally, consideration of GSI could help discriminate the direct effects of EACs from indirect effects on gene expression associated with proliferation or degeneration of gonad tissue relative to body mass, which would be valuable in understanding the relationships between molecular-level changes and whole organism outcomes.
Pre-/Postspawn Experiment
EAC testing with fathead minnows has routinely been conducted using reproductively active adults. At the time of test-termination, there can be considerable variation in how recently the various individuals sampled have spawned. The pre-/postspawn experiment was designed to test whether discrete spawning events could cause changes in steroidogenesis-related gene expression. We hypothesized that acute shifts in gene expression could occur either as a direct part of signaling processes involved in ovulation and/or spermiation, or as an indirect effect associated with changes in the proportions of germ cells at each stage toward less developed stages (i.e., upon spawning), particularly in females (Villeneuve et al., 2007b). For example, expression of 20ß-HSD, which codes for the enzyme involved in synthesis of 17,20 ß-dihydroxy-4-pregnen-3-one (17,20ß-P; Fig. 1), a hormone involved in triggering final oocyte or spermatocyte maturation, might be greater in animals nearly ready to spawn than in those that have spawned within the previous 24 h (Patiño et al., 2001; Weltzien et al., 2004; Yaron, 1995). One might also expect greater expression of CYP19A and 11ß-HSD in the ovaries and testis, respectively, as the overall population of asynchronously developing germ cells shifts toward greater proportions of less mature oocytes and spermatocytes (e.g., Villeneuve et al., 2007b). Therefore, we hypothesized that spawning status could significantly impact the gene expression results and wanted to determine whether or not some measure of spawning interval (days since last spawn) should be incorporated in the analysis.
Overall, data from the pre-/postspawn experiment generally did not support the hypothesis that discrete spawning events in this asynchronous-spawning species would significantly alter the expression of steroidogenesis-related genes. CYP19A expression in females was the only response that showed a difference between pre- and postspawn fish, with significantly greater expression in postspawn fish (Table 3). Thus, it appears that in most cases it is not necessary to consider the spawning interval of individual fathead minnows in analyzing for effects of EACs on transcription of steroidogenesis-related genes.
Sex-related differences in the transcript abundance of steroidogenesis-related genes were commonly observed and a number of them were consistent with current understanding of the relative importance of specific steroids in males versus females. For example, in teleosts, 11-ketotestosterone (11-KT) is considered the dominant androgen in supporting development of male secondary sex characteristics and reproductive behaviors, as well as spermatogenesis (Borg, 1994). It is typically found at greater plasma concentrations in males than in females (Borg, 1994; Jensen et al., 2001). Correspondingly, transcripts coding for 11ß-HSD, a key enzymatic regulator of 11-KT synthesis (Fig. 1), were approximately 10-fold more abundant (normalized to total RNA) in males than females. Conversely, CYP19A, which is involved in the synthesis of estradiol (Fig. 1), a hormone whose levels are greater in females (Jensen et al., 2001; Watanabe et al., 2007), had greater transcript abundance in ovary than in testis.
Some of the sex-related differences were unexpected. For example, one would not necessarily anticipate major sex-related differences in StAR, CYP11A, or CYP17 expression since they mediate processes that are common to the synthesis of estrogens, androgens, and progestins (Fig. 1). However, transcripts for all three genes were on the order of 15- to 50-fold less abundant in ovary than in testis (Table 3). In contrast, 20ß-HSD transcripts were seven- to eightfold less abundant in testis than in ovary, despite the fact that 17,20ß-P plays a similar role in the final maturation of both sperm and oocytes (Yaron, 1995). Based on data from this study alone, it is not clear whether these sex-related differences in expression reflect real differences in the importance or role of those genes in ovary versus testis tissue, or whether differences in factors like transcript or protein stability, enzyme activities, or ratios of specific mRNAs to ribosomal or total RNA might account for differences observed. Regardless, it is clear that sex is an important factor that should be considered in designing and analyzing experiments aimed at linking the effects of EACs on expression of steroidogenesis-related genes to apical outcomes.
Ketoconazole
KTC is a fungicide used as a human therapeutic that also inhibits activity of vertebrate steroidogenic CYPs (Albertson et al., 1988; Feldman, 1986; Morita et al., 1990). Exposure to KTC for 21 days caused significant reductions in fathead minnow fecundity as well as testosterone production by gonad tissue cultured for 14.5 h following the in vivo exposure (Ankley et al., 2007). However, concomitant reductions in plasma testosterone were not observed, apparently due to compensatory responses. For example, in exposed males, there was notable proliferation of Leydig cells in the testes and significant increases in transcripts coding for steroidogenic CYPs including CYP11A and CYP17 (Ankley et al., 2007). The relative abundance of gonadotropin ß-subunit transcripts detected in the pituitary tissue of males was also affected by 21 days of exposure to KTC but could not be as readily linked to the apparent compensatory response (Villeneuve et al., 2007b). Results from the current study indicate that StAR, 20ß-HSD, and cyt b5 transcripts were also increased in the testis of males exposed to 400 µg KTC/l (Fig. 3). Given the proliferation of Leydig cells (the primary steroidogenic cells in testis) observed in KTC-exposed animals it may seem that the observed increase in CYP11A, CYP17, StAR, cyt b5, and 20ß-HSD expression was due to proportionally greater representation of Leydig cell transcripts in the pool of total testis RNA. However, if that were true, one would also expect significant increases in 3ß-HSD and 11ß-HSD transcripts, as these are also more highly expressed in Leydig cells than in other gonad cell types. That was not the case (Fig. S.2). Increased expression of StAR could be viewed as part of a compensatory response to the effects of KTC. If carried through to translation of the protein, increased transcription of StAR would serve to increase the rate of cholesterol transfer to the inner mitochondrial membrane, a step considered to be rate-limiting for acute steroidogenesis (Stocco, 2001; Stocco and Clark, 1996). Since cyt b5 is thought to enhance the lyase activity of CYP17, increased expression of cyt b5 could also be viewed as offsetting the direct effects of KTC on androgen synthesis (Fig. 1; Akhtar et al., 2005; Miller, 2005; Pandy and Miller, 2005). Increased 20ß-HSD expression would be consistent with a compensatory feedback mechanism as well, since progestin synthesis would be impacted by potential direct effects of KTC on CYP11A and/or CYP17 activity (Fig. 1, Albertson et al., 1988; Kan et al., 1985). Due to potential time-lag and other disconnects between transcript abundance and associated protein levels and/or activity, it is difficult to fully interpret the biological significance of the changes in gene expression observed relative to the apical effects. However, it was clear that exposure to KTC altered expression of multiple genes involved in regulation of a biosynthetic pathway critical to reproductive and developmental functions. Furthermore, the overall concentration–response profile was highly consistent among the multiple molecular endpoints surveyed (as well as effects at higher levels or organization; Ankley et al., 2007). At a minimum, the molecular and apical data collected support a consistent narrative pertaining to a putative compensatory response to the direct effects of KTC.
Data provided by the baseline studies directly aided the analysis and interpretation of the KTC experiment results. For example, when the QPCR data were analyzed using treatment alone as an independent variable, the effect of 400 µg KTC/l on testis CYP11A expression could not be discriminated statistically (p = 0.120), even though the mean was fourfold greater than that of controls. However, based on the observation that CYP11A expression in males was correlated with GSI, we conducted a factorial analysis using GSI as an additional quantitative variable. That analysis revealed a statistically significant effect of KTC (p = 0.005), GSI (p = 0.0273), and a significant interaction between the two (KTC*GSI p = 0.0133). Similarly, although a significant effect of KTC on StAR expression was statistically discriminated without considering GSI in the analysis (p = 0.0308), statistical resolution of the effect of the chemical was further improved by considering GSI. The effect of KTC was highly significant (p = 0.0002) and a significant effect of GSI (p = 0.0016) and significant interaction between KTC and GSI (p = 0.0015) were detected. It was notable that the influence of GSI on the StAR and CYP11A expression was statistically apparent despite the fact that a correlation between GSI and StAR (R2 = –0.055; p = 0.737) or CYP11A (R2 = 0.065; p = 0.696) was not detected in the KTC experiment, presumably due to the added influence of KTC. These examples highlight the utility of the baseline data for aiding interpretation of the results from chemical exposure experiments.
Vinclozolin
VZ is a dicarboximide fungicide used to control fungal growth on plants (U.S. EPA, 2000). Active metabolites of VZ act as AR antagonists (Gray et al., 1994; Kelce et al., 1994). Exposure to VZ for 21 days caused a concentration-dependent decrease in fathead minnow egg production (Martinovic et al., submitted for publication). In males, exposure to 400 or 700 µg VZ/l (nominal) increased GSI and testicular AR and 11ß-HSD expression (Martinovic et al., submitted for publication). Additionally, testosterone and 11KT production by testis tissue cultured for 14.5 h following the in vivo exposure was significantly increased (Martinovic et al., submitted for publication). The increased androgen production ex vivo, together with a corresponding increase in 11ß-HSD expression, was suggestive of a compensatory upregulation in androgen production in response to VZ treatment (Martinovic et al., submitted for publication). However, unlike in the KTC experiment, no corresponding upregulation of steroidogenic CYPs was observed. Expression of 20ß-HSD and LHR was elevated in the testis of VZ treated males, but overall there was relatively little evidence for compensatory upregulation of steroidogenesis-related genes after 21 days of VZ treatment. Thus, at least in the case of VZ, the gene expression changes elicited by an EAC that indirectly impacts steroidogenesis were not as readily linked to apical responses as when the EAC acted directly on steroidogenic enzyme activities (e.g., KTC).
Nonetheless, two aspects of the KTC and VZ results were similar. First, while VZ did not cause a notable proliferation of Leydig cells relative to other testis cell types, both chemicals caused an increase in male GSI (Ankley et al., 2007; Martinovic et al., submitted for publication). Second, both KTC and VZ caused a significant increase in the abundance of FSHß transcripts in male pituitary tissue (Villeneuve et al., 2007b, Fig. 3). In mammals, FSH is thought to be responsible for regulation of Sertoli cell proliferation (Allan et al., 2004), but a combination of FSH-induced Sertoli cell factors and LH-stimulated androgen production is needed for proper germ cell development in the testis (Meachem et al., 2005; Walker and Cheng, 2005). Assuming similar function in teleosts, one could hypothesize that increased FSHß expression in the pituitary could be a common feedback-related response to EACs that interfere with sperm development. In the KTC and VZ studies, two mechanisms for such interference were examined, and both resulted in increased FSHß expression. If this pattern of response holds for additional EACs that inhibit fathead minnow reproduction, FSHß transcript measurements may have use as a marker of potential impairment of male fertility.
The effects of VZ and flutamide, another antiandrogen, on steroidogenesis-related gene expression in rat testis and pituitary (Kubota et al., 2003; Ohsako et al., 2003) were not directly comparable to the effects observed in this study. Treatment with antiandrogens caused increased expression of LHß and FSHß in rat pituitary tissue (Kubota et al., 2003; Ohsako et al., 2003). However, in the fathead minnow, only FSHß transcripts were elevated. Both VZ and flutamide increased the expression of mRNAs coding for CYP11A, CYP17, and 3ß-HSD in rat testis (Kubota et al., 2003; Ohsako et al., 2003), but similar effects were not observed in fathead minnows exposed to VZ for 21 days. While differences in exposure design preclude discrimination of species differences from the influence of experimental design, the lack of increased LHß expression in the pituitary of male minnows may partially explain why CYP11A, CYP17, and/or 3ß-HSD expression was not increased in their testes following VZ exposure as it was in rats, since LH is thought to be the primary regulator of Leydig cell steroidogenesis (Schulz et al., 2001).
Conclusions
This study for the first time evaluated the effects of KTC and VZ on a series of steroidogenesis-related molecular endpoints using a small teleost model. Real-time PCR methods for quantifying the relative abundance of fathead minnow steroidogenesis-related mRNA transcripts including StAR, CYP11A, 3ß-HSD, 11ß-HSD, 20ß-HSD, cyt b5, FSHR, and LHR were established. Examination of the variability in the abundance of those and related transcripts in the baseline experiments provided information that guided the design and analysis of the KTC and VZ experiments and will aid the design of future experiments as well. For example, the means and standard deviations generated in the baseline experiments can be used in a power analysis to estimate appropriate sample sizes for future experiments involving these endpoints (e.g., Watanabe et al., 2007). Results from the KTC and VZ experiment highlight the interpretive value of comparing endpoints at multiple levels of biological organization. Reproductive, histological, and other apical endpoints served as phenotypic anchors that enhanced the ability to interpret the significance of transcript results. Conversely, the transcript results provided important insights into the biological changes leading to adverse effect or compensation.
The linkage of gene expression measurements to apical responses and vice versa represents the major long-term aim of our research. By coupling the examination of molecular-level changes with characterization of whole-animal effects (e.g., changes in GSI, histology, steroid production, and reproduction) we can start to establish and explore the plausible functional linkages, direct or indirect, between transcript changes, chemical mode of action, and higher level outcomes with relevance to individual and/or ecosystem health. There are significant challenges to establishing these linkages. For example, the time-course over which transcript changes can translate into phenotypic alterations, and in turn phenotypic changes can feedback to cause transcript changes, is uncertain. In the present study, transcript measurements were restricted to a single time point proximal to that at which apical endpoints were examined (e.g., after 21 days of chemical exposure). However, in future experiments, greater understanding of the functional interplay of transcript changes and apical responses could be gained through more intensive time-course sampling and analysis. Further, as effects of additional chemicals with different modes of action are evaluated across multiple levels of biological organization and time points, a greater understanding of system-wide responses to chemical stressors and how molecular and biochemical changes translate into apical outcomes reflective of both adverse effects and compensation can be established.
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SUPPLEMENTARY DATA |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONSUPPLEMENTARY DATAFUNDINGREFERENCES |
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Supplementary data (i.e., Tables S.1, S.2; Figures S.1, S.2, S.3) are available online at http://toxsci.oxfordjournals.org/.
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FUNDING |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONSUPPLEMENTARY DATAFUNDINGREFERENCES |
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Funding through National Center for Computational Toxicology of the U.S. EPA Office of Research and Development and the U.S. EPA Office of Science Policy by using resources awarded to the Ecological Exposure Research and Ecosystem Research Divisions (National Exposure Research Laboratory) in Cincinnati, OH, and Athens, GA, respectively, and the Mid-Continent Ecology Division (National Health and Environmental Effects Research Laboratory) in Duluth, MN; National Research Council Post-doctoral Research Associateships to D.M. and D.L.V.
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ACKNOWLEDGMENTS |
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Additional technical support and/or guidance for aspects of this work were provided by Michael D. Kahl, Kathleen M. Jensen, Elizabeth A. Makynen, Elizabeth J. Durhan, Ann Linnum, Edward F. Orlando, Sigmund J. Degitz, Joseph J. Korte, and Cathy Richter. We thank Allen Olmstead and Adam Biales for reviewing an earlier draft of this paper. This manuscript has been reviewed in accordance with official U.S. EPA policy. Mention of products or trade names does not indicate endorsement by the federal government. Conclusions drawn in this study neither constitute nor necessarily reflect U.S. EPA policy regarding test chemicals and test methods.
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