ToxSci Advance Access originally published online on March 14, 2008
Toxicological Sciences 2008 103(2):285-297; doi:10.1093/toxsci/kfn053
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Comparative Temporal Toxicogenomic Analysis of TCDD- and TCDF-Mediated Hepatic Effects in Immature Female C57BL/6 Mice
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* Department of Biochemistry & Molecular Biology
Center for Integrative Toxicology & National Food Safety & Toxicology Center, Michigan State University, East Lansing, Michigan 48824
The Dow Chemical Company, Midland, Michigan 48674
1 To whom correspondence should be addressed at Michigan State University, Biochemistry & Molecular Biology, 501 Biochemistry Building, Wilson Road, East Lansing, MI 48824-1319. Fax: (517) 353-9334. E-mail: tzachare{at}msu.edu.
Received January 8, 2008; accepted March 4, 2008
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONSUPPLEMENTARY DATAREFERENCES |
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Temporal analyses were performed on hepatic tissue from immature female C57BL/6 mice in order to compare the gene expression profiles for 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and 2,3,7,8-tetrachlorodibzofuran (TCDF). Time course studies conducted with a single oral dose of 300 µg/kg TCDF or 30 µg/kg TCDD were used to compare differential gene expression on complementary DNA microarrays containing 13,361 features, representing 8194 genes at 2, 4, 8, 12, 24, 72, 120, and 168 h. One hundred and ninety-five genes were identified as differentially regulated by TCDF, of which 116 genes were in common with TCDD, with 109 exhibiting comparable expression profiles (correlation coefficients > 0.3). In general, TCDF was less effective in eliciting hepatic vacuolization, and differential gene expression compared with TCDD when given at an equipotent dose based on a toxic equivalence factor (TEF) of 0.1 for TCDF, especially 72-h postadministration. For example, the induction of Cyp1a1 messenger RNA by TCDF was less when compared TCDD. Moreover, TCDF induced less severe hepatocyte cytoplasmic vacuolization consistent with lower lipid accumulations which significantly subsided by 120 and 168 h when compared with TCDD. TCDF-elicited responses correlated with their hepatic tissue levels which gradually decreased between 18 and 168 h. Although both compounds elicited comparable gene expression profiles, especially at early time points, the TCDF responses were generally weaker. Collectively, these results suggest that the weaker TCDF responses could be attributed to differences in pharmacokinetics. However, more comprehensive dose–response studies are required at optimal times for each end point of interest in order to investigate the effect of pharmacokinetic differences on relative potencies that are important in establishing TEFs.
Key Words: TCDD; TCDF; microarray; liver; mouse; temporal.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONSUPPLEMENTARY DATAREFERENCES |
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2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) and related compounds, including 2,3,7,8-tetrachlorodibenzofuran (TCDF), are ubiquitous environmental contaminants that are inadvertent by-products of various processes including municipal waste combustion and phenoxy acid herbicides production (Mason and Safe, 1986
; Poland and Glover, 1973; Safe et al., 1982). TCDD and related compounds, including TCDF, elicit a broad range of species-specific biochemical and toxic effects in animals such as xenobiotic enzyme induction, wasting syndrome, tumor promotion, teratogenicity, immunotoxicity, hepatotoxicity, and endocrine system modulation (Abbott et al., 1987; Birnbaum, 1995; Birnbaum et al., 1987; Davis and Safe, 1989; Viluksela et al., 2000). Many, if not all of these effects are due to the inappropriate regulation of gene expression mediated by the aryl hydrocarbon receptor (AhR) (Denison and Heath-Pagliuso, 1998; Denison et al., 2002; Poland and Knutson, 1982; Safe, 2001). The proposed mechanism involves ligand binding, activation, and translocation of the cytoplasmic AhR to the nucleus where it heterodimerizes with the AhR nuclear translocator. This complex induces changes in the expression of genes possessing dioxin response elements (DREs) within their regulatory region.
The ability of a large number of structurally diverse chemicals to bind to the AhR and their existence as complex mixtures presents significant challenges in assessing their potential risk to human and ecological health (Ahlborg, 1994; Birnbaum and DeVito, 1995; DeVito et al., 1994; Safe, 1990; Santosfefano et al., 1994). Assessment approaches have focused on their dioxin-like properties and the use of toxic equivalency factors (TEFs) based on end point–specific relative potencies (Ahlborg, 1994; Barnes et al., 1991; Birnbaum and DeVito, 1995; Haws et al., 2006; Safe, 1990; Van den Berg et al., 1998, 2006). The TEF approach assumes that at submaximal doses, the contributions of individual congeners are essentially additive (Harris et al., 1993; Safe, 1997), and that TEFs are independent of dose, time point, and tissue (Poland and Knutson, 1982; Safe, 1990). However, pharmacokinetic and dispositional differences between congeners may affect their relative potencies (Budinsky et al., 2006; DeVito et al., 1997, 1998; Diliberto et al., 2001; Safe, 1995).
TEFs for 29 polychlorinated dibenzo-p-dioxins, dibenzofurans, and biphenyls (PCBs), have been established relative to TCDD, the reference chemical which is assigned a TEF of 1 (Van den Berg et al., 2006). For example, 36 separate in vivo relative effect potencies, from 13 different peer-reviewed publications and one thesis were available to the expert panel convened by the World Health Organization (WHO) to establish a TEF for TCDF. Assuming in vitro data was only used in the absence of sufficient in vivo data, and the panel adopted the criteria developed for REP 2004, 17 of 36 in vivo studies were considered when the TEF of 0.1 for TCDF was set, with the understanding that it could vary by a half-log unit (Van den Berg et al., 2006). Of these studies, three were in the Wistar rat, one was in the Hartley guinea pig, and 13 used C57BL/6J and C57BL/6N mice. The end points examined included enzyme assays (ethoxyresorufin-O-deethylase [EROD], acetanilide 4-hydroxylation, benzo[a]pyrene hydroxylase), body weight (BW) gain, kidney damage, cleft palate, relative liver weight (RLW), and immunosuppression measured by the plaque forming cell assay. Consequently, the potential toxicity of a mixture containing these 29 TCDDs, TCDFs, and PCBs could be estimated relative to TCDD by calculating the sum of the concentrations of each individual congener multiplied by their corresponding TEF.
Comparative toxicogenomics is a powerful approach to further elucidate the mechanisms of toxicity of TCDD and related compounds across species. Temporal analyses using these technologies facilitates the identification of linkages between differential gene expression and injury, and can also distinguish adaptive differential gene expression from responses associated with adverse effects by correlation to other concurrently assessed apical end points (i.e., phenotypic anchoring) (Afshari et al., 1999; Hamadeh et al., 2002; Nuwaysir et al., 1999). Published studies examining the hepatotoxicity of TCDD using the same model, dosing regimen, complementary DNA (cDNA) microarrays and data analysis methods have linked some differentially expressed genes to TCDD elicited histopathology (Boverhof et al., 2005). Furthermore, using the same models and approaches facilitates the identification of ligand-specific responses that may be important when evaluating potency. In this study, comparable comprehensive differential gene expression time course cDNA microarrays with complementary histopathology and tissue level analyses were conducted to compare the effects elicited by TCDD and TCDF at equipotent-based TEF doses. Collectively, 300 µg/kg TCDF elicited a weaker subset of the responses induced by 30 µg/kg TCDD, especially at later time points, consistent with the decreasing hepatic tissue levels of TCDF. Consequently, pharmacokinetics is an important factor when establishing TEF values. However, more comprehensive time optimized dose–response studies are required to provide additional REP data for reconsideration of the TCDF TEF, in context with all other TCDF REP data.
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MATERIALS AND METHODS |
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Animal husbandry.
Female C57BL/6 mice, all having BWs within 10% of the average BW, were obtained from Charles River Laboratories (Raleigh, NC) on postnatal day (PND) 25. The mice were housed in polycarbonate cages containing cellulose fiber chips (Aspen Chip Laboratory Bedding, Northeastern Products, Warrensberg, NY) in a 23°C Hepa-filtered environment with 30–40% humidity and 12-h light/dark cycle (7:00 A.M.–7:00 P.M.). Animals were allowed free access to deionized water and fed ad libitum Harlan Tekad 22/5 Rodent Diet 8640 (Madison, WI), and acclimatized for 4 days prior to dosing. On the fourth day, animals were weighed and stock solutions of TCDD and TCDF (provided by The DOW Chemical Company, Midland, MI) were diluted in sesame oil (Sigma, St Louis, MO) to achieve the desired dose based on the average weight. All procedures were performed with the approval of the Michigan State University All-University Committee on Animal Use and Care.
In-life study design.
TCDD and TCDF doses were based on (1) a published comprehensive TCDD time course and dose–response study (Boverhof et al., 2005), and (2) the TEF for TCDF (0.1) as determined by an expert panel of the WHO (Van den Berg et al., 2006). Thirty micrograms per kilogram TCDD was initially selected for use in the Boverhof et al. study because it elicited maximum induction of Cyp1a1 and 1a2 messenger RNA (mRNA) levels while not inducing significant changes in BW gain (Boverhof et al., 2005). It was used again in the present study, to facilitate comparisons between studies that employed the same species, experimental design, cDNA microarray platform, and analysis methods. However, note that this study used intact immature female C57BL/6 mice, whereas previous studies in this lab have used ovariectomized immature female C57BL/6 mice (Boverhof et al., 2005). Three hundred micrograms per kilogram TCDF was used to examine the hypothesis that it would elicit hepatic effects comparable to 30 µg/kg TCDD, based on the TCDF TEF of 0.1. The vehicle groups were not the same between the current TCDF study and the Boverhof et al. study, but the same vehicle controls were used for the internal TCDD treated mice in the current TCDF study.
Mice were orally gavaged with 0.1 ml of sesame oil for a nominal dose of 0 (vehicle control), 300 µg/kg BW of TCDF, or 30 µg/kg BW of TCDD. Five animals were treated per dose group and time point, and housed in separate cages (Fig. 1). TCDF-treated and time-matched vehicle control animals were sacrificed at 2-, 4-, 8-, 12-, 18-, 24-, 72-, 120-, or 168-h postdosing. Mice that were treated with 30 µg/kg BW TCDD were sacrificed at 4-, 12-, 72-, 120-, or 168-h postdose. This limited number of time points was meant to serve as a few internal controls to facilitate comparisons with a more comprehensive TCDD time course study (Boverhof et al., 2005). TCDD and TCDF doses were chosen to elicit moderate hepatic effects while avoiding overt toxicity in longer-term studies. Animals were sacrificed by cervical dislocation and tissue samples were excised, weighed, flash frozen in liquid nitrogen, and stored at –80°C until further use. The right lobe of the liver was fixed in 10% neutral buffered formalin (Sigma) for histological analysis.
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Histological analysis.
Sections taken through the center of the right middle lobes were processed sequentially in formalin, alcohol, butanol, xylene, and paraffin in a Tissue Tek VIP 5 vacuum infiltration processor (Torrance, CA). Tissues were then embedded in paraffin with a Miles Tissue Tek embedding center, after which paraffin blocks were sectioned at 6 µm with a rotary microtome. Sections were placed on glass microscope slides, dried, and stained with hematoxylin and eosin. Histological evaluations were performed by a board certified veterinary pathologist.
Quantification of TCDF and TCDD in liver tissues.
Liver samples were processed in parallel with lab blanks and a reference or background sample at The Dow Chemical Company. The samples were weighed, spiked with 13C12-labeled TCDD or TCDF surrogate, digested and extracted by shaking overnight in a solution containing concentrated hydrochloric acid and a 5% benzene:hexane solution. The organic phase was processed through a series of three clean-up columns. The first column consisted from bottom to top: silica gel, caustic silica gel (33% NaOH/Silica Gel), silica gel, acid silica gel (44% H2SO4/Silica Gel), and silica gel. The second and third clean-up columns contained silver nitrate (10% silver nitrate/silica gel) and basic alumina, respectively. The final cleaned-up extract was concentrated and spiked with an injection standard. The analysis was performed on a high-resolution gas chromatography/high-resolution mass spectrometer (HRGC/HRMS) using a Hewlett Packard 5890 series II GC (Palo Alto, CA) interfaced to a VG 70SE HRMS (VG Analytical, Manchester, UK). The HRMS was operated in the electron impact/selected ion recording mode at 10,000 resolution. A 60-m DB5 column (J & W Scientific, Folsom, CA) with an internal diameter of 0.25 mm and film thickness of 0.25 µm was employed. The injection method was splitless with an injection volume of 2 µl. All calculations were performed via the isotope-dilution mass spectrometric procedure. When appropriate, the system and laboratory performance was monitored using the guidelines specified in environmental protection agency method 1613b.
RNA isolation.
Frozen liver samples (approximately 70–100 mg) were transferred to 1.3 ml of Trizol (Invitrogen, Carlsbad, CA) and homogenized in a Mixer Mill 300 tissue homogenizer (Retsch, Germany). Total RNA was isolated according to the manufacturer's protocol with an additional phenol:chloroform extraction. RNA was resuspended in RNA storage solution (Ambion, Inc., Austin, TX), quantified (A260) for concentration, and the purity determined by A260/A280 ratio and by visual inspection of 1.0 µg on a denaturing gel electrophoresis.
Microarray assay.
TCDF-treated samples were cohybridized with time-matched vehicles controls using an independent reference design (Yang and Speed, 2002). cDNA microarrays were also performed for the "internal" TCDD-treated group of mice, which used the same vehicle controls as in the TCDF microarray design. In the Boverhof et al. study, independent groups of the TCDD-treated and vehicle control mice were used. All experiments were performed with three biological replicates with two independent labelings of each sample (dye swap) for each time point or dose group, using custom mouse cDNA microarrays containing 13,361 features representing 8516 unique genes (UniGene build 144).
Detailed protocols for microarray preparation, labeling of the cDNA probe, sample hybridization, and washing can be found at http://dbzach.fst.msu.edu/interfaces/microarray.html. Briefly, PCR amplified DNA was robotically arrayed onto epoxy-coated glass slides (Schott-Nexterion, Duryea, PA) using an Omnigrid arrayer (GeneMachines, San Carlos, CA) equipped with chipmaker 2 pins (Telechem, Atlanta, GA) at the Research Technology Support Facility (http://www.genomics.msu.edu). Total RNA (30 µg) was reverse transcribed in the presence of cy3-or cy5-deoxyuridine triphosphate to create fluor-labeled cDNA, which was purified using a Qiagen PCR purification kit (Qiagen, Valencia, CA). After cDNA labeling, cy3 and cy5 samples were mixed, vacuum dried, and resuspended in 48 µl of hybridization buffer (40% formamide, 4x sodium chloride-sodium citrate, 1% sodium dodecyl sulfate with 20 µg polydA and 20 µg of mouse COT-1 DNA (Invitrogen) as competitor. The hybridization mixture was heated at 95°C for 3 min and hybridized on the array under a 22 x 40 mm lifterslip (Erie Scientific Company, Portsmouth, NH) in a light-protected and humidified hybridization chamber (Corning, Inc., Corning, NY) for 18–24 h in a 42°C water bath. Slides were then washed, dried by centrifugation, and scanned at 635 nm (cy5) and 532 nm (cy3) on a GenePix Personal 4100A microarray scanner (Molecular Devices, Union City, CA). Scanned Images were analyzed for feature and background intensities using GenePix Pro 6.0 (Molecular Devices).
cDNA microarray data analysis.
All microarray data used within this study passed the laboratory quality assurance protocol (Burgoon et al., 2005), although there was more variability relative to previous studies (Boverhof et al., 2005, 2006), possibly due to the use of intact immature 28–35 day old C57BL/6 mice. Microarray data were normalized using a semiparametric approach (Eckel et al., 2004, 2005), and the posterior probabilities were calculated using an empirical Bayes analysis on a per gene and time point or dose basis (Eckel et al., 2004). Normalization and empirical Bayes analysis were performed using SAS version 9.1 (SAS Institute, Inc., Cary, NC) and R version 2.3.1. Gene expression data were ranked and prioritized using a P1(t) cut-off of 0.999 and ± 1.4-fold change to identify an initial subset of differentially expressed genes for further investigation and data interpretation. Relaxed filtering criteria (from P1(t) = 0.999; > 1.4-fold absolute fold change to P1(t) = 0.9; > 1.4 absolute fold change) were also used to examine overlapping differentially regulated genes to minimize classifying genes as TCDF or TCDD specific as a result of using stringent cut-offs. Hierarchical clustering of differentially expressed genes was performed using GeneSpring GX 7.3.1 software (Agilent Technologies, Santa Clara, CA) and standard correlation tool as the similarity metric. Trajectory analysis was performed in R using singular value decomposition. Regression analysis was also performed in R using the nonlinear, robust loess with 1000 iterations. The slope was estimated empirically using the loess model.
Multiple features spotted on our cDNA microarray represent the same gene (e.g., Cyp1a1). To obtain the number of unique genes, the features were first screened by their corresponding Entrez Gene IDs. If several features had the same Entrez Gene ID, they were all considered to be representative of the same genes and counted as one gene. Due to this redundancy, and because of missing annotation and changes to annotation in the mouse genome, the 13,361 features spotted on our cDNA microarray correspond to 8516 unique genes based on the annotation provided by UniGene build 144.
Quantitative real-time PCR.
Quantitative real-time PCR verification of microarray responses was performed as described previously (Boverhof et al., 2005). Briefly, 1.0 µg of total RNA was reverse transcribed by Superscript II using an anchored oligo-dT primer as described by the manufacturer (Invitrogen). The cDNA (1.0 µl) was used as a template in a 30 µl of PCR reaction containing 0.1µM of forward and reverse gene-specific primers, 3mM MgCl2, 1.0mM deoxy-nucleotidyl triphosphatases, 0.025 IU AmpliTaq Gold, and 1x SYBR Green PCR buffer (Applied Biosystems). Gene names, accession numbers, forward and reverse primer sequences and amplicon sizes are listed in Supplementary Table 1. PCR amplification was conducted on an Applied Biosystems PRISM 7000 Sequence Detection System. cDNAs were quantified using a standard curve approach and the copy number of each sample was standardized to three housekeeping genes (Actb, Gapdh, Hprt) to control for differences in RNA loading, quality and cDNA synthesis.
Identification of DREs.
The regulatory regions (–10,000 relative to the transcription start site through the 5'-untranslated region) for all genes with a mature Refseq accession were obtained from the University of California, Santa Cruz, Genome Browser for the mouse (build 34). All sequences were deposited into dbZach, an in-house data management solution (Burgoon et al., 2006). Core DRE sequences (5'-GCGTG-3') were identified using a response element application developed in Java (Sun et al., 2004).
Statistical analysis.
Statistical analysis, unless otherwise defined, was performed using SAS version 9.1. Data were analyzed using analysis of variance followed by Dunnett's or Tukey's post hoc tests. Differences between treatment groups were considered significant when p < 0.05. Half-life estimates were derived using WinNonlin (Pharsight, Mountain View, CA).
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RESULTS |
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Organ and Body Weights
Changes in BW, liver weight and cell morphology are characteristic rodent responses following exposure to TCDD and related compounds (Poland and Knutson, 1982
). Mice treated with 30 µg/kg of TCDD showed significant (p < 0.05) increases in RLW at 72, 120, and 168 h (Table 1), as previously reported (Boverhof et al., 2005). Similar treatment with the TEQ dose of TCDF (300 µg/kg) also elicited significant (p < 0.05) increases in RLWs at 24, 72, 120, and 168 h (Table 1). Despite reports of wasting in TCDD treated rodents, mice in this study did not exhibit significant treatment-related alterations in BW at the doses used, consistent with published studies (Boverhof et al., 2005; Fletcher et al., 2001).
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Hepatic TCDD/TCDF Concentrations
Hepatic TCDD and TCDF levels per wet weight (n = 3) were quantified to assess the temporal relationship and relative potency between TCDD and TCDF in relation to RLW, histopathology and gene expression responses. Hepatic levels of TCDD reached maximal levels at 12 h which were sustained through 72 h, followed by gradual decreases at 120 and 168 h (Fig. 2). Similarly, TCDF hepatic levels increased between 2 and 12 h, followed by a more rapid decrease between 18 and 168 h compared with TCDD (Fig. 2). These findings are consistent with published reports on the disposition of TCDF and TCDD in rats and mice (DeVito and Birnbaum, 1995
; DeVito et al., 1997; Hamm et al., 2003) and the capacity of Cyp1a1 induction to metabolically clear TCDF (McKinley et al., 1993; Olson et al., 1994; Tai et al., 1993). Fitting of the liver concentration versus time data yielded estimated hepatic clearance half-lives of 40 and 177 h (1.7 and 7.4 days) for TCDF and TCDD, respectively. Comparison of hepatic levels of TCDD and TCDF, when expressed as TEQ, revealed no significant differences in hepatic tissue levels at 12 h, however, TCDD levels were significantly greater than TCDF levels at 72 h and 168 h (Fig. 2), consistent with the longer half-life (10 days) of TCDD compared with 2 days for TCDF (DeVito and Birnbaum, 1995). These data suggest that ligand-specific pharmacokinetic and disposition factors may contribute to differences in relative potencies across end points. Consequently, hepatic TCDD and TCDF levels are important factors in phenotypically anchoring gene expression to RLW and histopathology.
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Histopathology
The principal treatment-related alteration in response to TCDF or TCDD was very slight to moderate cytoplasmic vacuolization of hepatocytes, consistent with lipid accumulation, primarily observed in the periportal and midzonal regions of the liver. In the time course study, TCDD induced cytoplasmic vacuolization at 72 h, which peaked at 120 h with all animals exhibiting moderate vacuolization, and then decreased in severity by 168 h (Table 2). In comparison, TCDF induced cytoplasmic vacuolization at 24 h, which became more severe by 72 h, but lessened at 120 h, and significantly subsided to very slight effects by 168 h (Table 2). In addition, at 120 and 168 h TCDD and TCDF increased numbers of inflammatory cell aggregates consisting of lymphocytes, neutrophils, and macrophages that were frequently associated with multiple degenerative and necrotic hepatocytes. Treatment-related centrilobular hypertrophy of hepatocytes was noted in at least two out of five animals treated with TCDD or TCDF at 168 h.
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Hepatic Gene Expression Response to TCDF and TCDD
Analysis of temporal hepatic gene expression responses to TCDD and TCDF was performed using custom mouse cDNA microarrays containing 13,361 features representing 8194 unique genes. For TCDD, empirical Bayes analysis identified 242 features, representing 208 unique genes, which were differentially expressed (P1(t) > 0.999 and |fold change| > 1.4) relative to time-match vehicle controls at one or more time points. For TCDF, 233 features representing 195 unique genes were differentially expressed at one or more time points in the time course study (Figs. 3A and 3B) (complete listing of all gene expression data is available in Supplementary Table 2).
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As was seen with effects on RLW, hepatic concentrations and liver histopathology, TCDF elicited fewer differential gene expression responses over time. TCDD displayed a time-dependent increase in number of genes induced between 2 and 4 h, which remained stable through 18 h, and increased further between 24 and 168 h (Boverhof et al., 2005
). In contrast, TCDF elicited differential gene expression was highest at early time points, with maximal induction at 12 h, followed by dramatic decreases in number of differently expressed genes after 24 h (Fig. 3A), consistent with decreasing hepatic TCDF levels. Comparison of the differentially expressed gene lists identified 116 genes regulated by both TCDD and TCDF (Fig. 3B) (complete listing of all genes used in the comparison are available in Supplementary Table 3). There was significant overlap in gene expression TCDD-responsive genes at all time points. TCDF-specific differential gene expression typically included marginal responses that were selected due to the use of a stringent statistical cut-off. When the selection criteria in the TCDD datase were relaxed (P1(t) > 0.9; fold change > 1.4), almost all of the apparent TCDF-specific responses also exhibited differential gene expression with TCDD (data not shown). Consequently, TCDF elicited differential gene expression was comparable to gene expression changes elicited by TCDD. This is consistent with TCDF eliciting comparable hepatic effects, although the induction of RLW (Table 1) and vacuolization (Table 2) was weaker at later time points.
Comparison of TCDD and TCDF Elicited Differential Gene Expression Responses
Hierarchical clustering of the microarray data by experimental time point illustrates the induction and repression of early and late differential gene expression responses. Moreover, early (4–72 h) TCDD and TCDF elicited responses clustered together based on time point, whereas later time points (120–168 h) clustered according to treatment (Fig. 4A). Overall, differential gene expression responses elicited by TCDF were similar in magnitude to TCDD responses at the early time points, but were lower from 120 to 168 h relative to TCDD consistent with the decreasing hepatic TCDF tissue levels.
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Pearson's correlation analysis of the temporal gene expression (fold change) and significance (P1(t)) profiles of the 116 commonly regulated genes exhibited similar differential expression patterns (Fig. 4B). For this analysis, TCDD and TCDF paired data were plotted on a coordinate axis with the x-axis as the gene expression correlation and the y-axis as the significance correlation. A majority of the gene relationships fell into the upper right hand quadrant representing TCDD and TCDF responsive genes that exhibit highly correlated differential gene expression and significance patterns. Overall, 107 of the 116 genes regulated by TCDD and TCDF exhibited a gene expression correlation greater than 0.3, indicating similarity in gene expression patterns. Correlations less than 0.3 tended to occur with genes exhibiting differential gene expression after 24 h.
Functional Analysis of the Common Gene Responses
Functional annotation of TCDD and TCDF elicited differential gene expression was associated with phase 1 and 2 enzymes, development and differentiation, fatty acid uptake and metabolism, gluconeogenesis, immune signaling, transcription regulation, apoptosis, transport, and endocrine disruption (Table 3). Many AhR battery genes were induced by both compounds, including cytochrome P450s and glutathione transferases (Boverhof et al., 2006; Fletcher et al., 2005; Nebert et al., 2000; Puga et al., 1992; Stahl, 1995; Stahl et al., 1993; Tian et al., 1999; Viluksela et al., 1999; Weber et al., 1991). A more thorough discussion of the association between differential gene expression, functional annotation, and elicited hepatic effects has been previously published (Boverhof et al., 2005, 2006).
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Despite TCDD and TCDF eliciting comparable hepatic effects, there were differences in temporal differential gene regulation and efficacy as illustrated by their divergent paths in the trajectory plots (Fig. 5A). Regression analysis was conducted on 2–24 and 72–120 h grouped temporal data based on the hierarchical clustering and Pearson's correlation analyses in order to further investigate differences in ligand efficacy and temporal regulation, relative to tissue levels. Tissue levels of both compounds were comparable from 2 to 24 h, and the slope of the nonlinear regression function for gene expression efficacy approaches 1.00, indicating that TCDD and TCDF exhibit equal efficacy at these earlier time points (Fig. 5B). However, the slope of the nonlinear regression function is approximately 0.52 suggesting significantly lower TCDF efficacy between 72–168 h (Fig. 5C). This is consistent with decreasing TCDF tissue levels, and the lower RLWs and vacuolization effects (Tables 1 and 2). In general, it is also consistent with the lower induction of secondary and tertiary responses associated with inflammatory cell accumulation and fatty acid transport and metabolism (Table 3).
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Verification of Microarray Response
Quantitative real-time PCR (QRT-PCR) was used to verify the differential expression for a selected subset of differentially expressed genes from Table 3 representing different response profiles and functions (Fig. 6). In general, there was good agreement in the level of differential expression when comparing microarray and QRT-PCR data. However, microarray data compression was evident for Cyp1a1 due to the limited dynamic fluorescence intensity range (0–65,535), which results in signal saturation for highly induced genes and compression of the true induction. Cross hybridization of homologous probes to a given target sequence on the microarray may also be a contributing factor, especially in comparison to other, more gene-specific measurement techniques (Yuen et al., 2002
).
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONSUPPLEMENTARY DATAREFERENCES |
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The WHO assigned TEF of 0.1 for TCDF is based on expert judgment considering all toxicity data, under the assumption that in vitro data is only used in the absence of sufficient in vivo data (Barnes, 1991
; Birnbaum and DeVito, 1995; Haws et al., 2006; Safe, 1993; Toyoshiba et al., 2004; van Birgelen et al., 1996; Van den Berg et al., 2006). The present in vivo study used a comprehensive toxicogenomic study design with complementary histopathology and hepatic tissue concentration analysis to compare the hepatic effects elicited by equipotent doses of TCDF and TCDD based on the WHO TEF in order to assess time-dependent differences in differential gene expression. These temporal changes provide essential baseline data for subsequent dose–response studies.
Hepatic clearance estimates for TCDF and TCDD are consistent with previous reports (Birnbaum, 1986; Decad et al., 1981; Gasiewicz et al., 1983). The estimated hepatic half-life for TCDF was approximately 40 h (1.7 days), almost identical to the hepatic half-life reported in C57BL/6 and DBA/2J mice (Decad et al., 1981). The hepatic half-life of 7.4 days for TCDD is less than the 10 to 12 day half-life previously reported (Birnbaum, 1986; Gasiewicz et al., 1983). Reduced adipose tissue in the immature mice used in this study may partially explain the apparent enhanced clearance. The difference may also be a function of examining hepatic clearance versus whole-body clearance, as reported in these other studies. Because adipose tissue concentrations were not obtained it is not possible to calculate whole-body clearance and half-life estimates from this study.
Ligand-specific pharmacokinetic and dispositional characteristics may lead to differences in the relative potencies of dioxin-like congeners across end points (Chen et al., 2001; DeVito and Birnbaum, 1995; DeVito et al., 1997, 1998, 2000). There were significantly lower hepatic TCDF levels at later time points when expressed as TEQs that can be attributed to ligand-specific pharmacokinetic properties consistent with previously published studies (DeVito and Birnbaum, 1995; Diliberto et al., 1995; Diliberto et al., 2001; Hamm et al., 2003). For example, the relative potencies of TCDD and TCDF are dependent on their pharmacokinetics in female B6C3F1 mice (DeVito and Birnbaum, 1995). The TEFs accurately estimated the relative potency of steady state levels of TCDF after 4 weeks based on EROD activity. However, after 13 weeks the TEF overestimates potency as hepatic EROD induced by TCDD and TCDF were 41- and 6-fold, respectively. This is in agreement with the levels of hepatotoxicity observed in this study and the reported half-life of 2 and 15 days for TCDF and TCDD, respectively (Birnbaum, 1986; Diliberto et al., 1995). TCDF is reported to induce its own metabolic clearance via induction of Cyp1a1 (Budinsky et al., in press).
TCDD's disposition (% dose/g tissue) and retained dose levels (21–34%) were also greater when compared with TCDF (2.5–6.2%) (DeVito et al., 1998). Binding of dioxin-like chemicals to inducible proteins such as Cyp1a2 may also contribute to differential hepatic sequestration in rats and mice (Chen et al., 2001; DeVito et al., 2000; Diliberto et al., 1995, 1997, 1999). Cyp1a2-null mice exhibited little TCDD and other dioxin-like chemical accumulation, suggesting that Cyp1a2 expression is important in the pharmacokinetics and disposition of these compounds (Diliberto et al., 1997, 1999). Overall, the relative potency, and thus the estimates of a TEF value for a specific dibenzo-p-dioxin or dibenzofuran congener, relative to TCDD, may be dependent on its metabolic clearance (i.e., Cyp1a1 hydroxylation of TCDF) or hepatic sequestration (Cyp1a2 binding of TCDD). The issue of external TEFs based on administered dose and those of internal TEFs based on tissue concentration or body burden metrics was a concern expressed by the 2005 WHO panel charged with updating the TEF values (Van den Berg et al., 2006).
TCDD- and TCDF-induced temporal-dependent increases in RLW and differential gene expression associated with fatty vacuolization are consistent with previously published studies (Boverhof et al., 2005; DeVito et al., 1998; Diliberto et al., 1999; Fletcher et al., 2005; Viluksela et al., 1998). Differences in TCDD and TCDF RLWs can be directly attributed to lower TCDF hepatic levels, which were observed in this study. Histopathology revealed time-dependent differences in cytoplasmic vacuolization consistent with lipid accumulation indicative of alterations in triglyceride metabolisms/and or lipoprotein trafficking, and inflammation with associated hepatocellular degeneration and necrosis. As with the effects on RLW, TCDF induced less hepatocellular cytoplasmic vacuolization, especially at later time points, consistent with its shorter half-life. The linkages between differential gene expression (e.g., lipid metabolism and transport; immune response) and elicited liver histopathology have been previously described (Boverhof et al., 2005, 2006).
In general, responses elicited by TCDF were consistent with the hepatic tissue levels and histopathology effects. There was also substantial overlap in the early differential gene expression responses elicited by TCDD and TCDF. Both compounds induced the well characterized AhR gene battery (i.e., Cyp1a1, Nqo1, Ugdh), as well as other genes involved in gluconeogenesis, fatty acid metabolism, development, and oxidative stress (Nebert et al., 1993; Safe, 1995) (complete listing of all gene expression data is available in Supplementary Table 2). Hierarchical clustering revealed strong concordance between the administered dose and the transcriptional responses at the early time points while clustering was ligand dependent at the later time points. Trajectory analysis further illustrated the similarity in gene expression at early time points with divergence at 24 h and continuing separation at 168 h. The slope (0.52) of the PCA scatter plot nonlinear regression line after 24 h clearly indicates the weaker potency of TCDF, consistent with its shorter half-life and hepatic clearance (Birnbaum, 1986; DeVito and Birnbaum, 1995). Although early differential gene expression responses are similar, they are not sufficient to elicit comparable levels of toxicity which represents a continuum of effects governed by temporal and spatial factors as well as exposure conditions. For example, 300 µg/kg TCDF was generally less potent than 30 µg/kg TCDD in inducing immune response and fatty acid metabolism genes, which are associated with the secondary response leading to hepatotoxicity. Moreover, TCDD toxicity appears to be more sustained over time compared with TCDF, which continuously diminished after 24 h, consistent with its shorter half-life, increased rate of hepatic clearance, and recovering histopathology effects.
Comprehensive gene expression data that can be phenotypically anchored to complementary histopathology can be used to further elucidate the mechanisms involved in the adaptive and toxic responses elicited by TCDD and TCDF. For example, there were fewer lipid transport and metabolism gene expression changes elicited by 300 µg/kg TCDF from 24 to 168 h when compared with 30 µg/kg TCDD, consistent with the recovery in hepatic fatty accumulation. Similar to TCDF, a recent toxicogenomic study of PCB126 hepatic effects using the same model, study design and analysis methods also reported that hepatocellular vacuolization, and lipid transport and metabolism differential gene expression diminished at later time points (Kopec et al., 2008). However, unlike PCB126 which continued to accumulate in the liver throughout the study, decreases in TCDF elicited hepatocellular vacuolization, and lipid transport and metabolism differential gene expression is consistent with the enhanced hepatic clearance of TCDF. Nevertheless, the possibility of specific differential gene expression elicited by TCDF cannot be ruled out because the cDNA microarrays used in this study did not include a feature representative of each gene in the mouse genome. Collectively, these results suggest that the TEF value of 0.1 for TCDF decreases with time after exposure/dose. However, in order to more accurately determine the effects of pharmacokinetic differences on the potency of TCDF relative to TCDD, more comprehensive dose–response studies are required at times that are optimal for each end point of interest.
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Supplementary data are available online at http://toxsci.oxfordjournals.org/.
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONSUPPLEMENTARY DATAREFERENCES |
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