A Systems Toxicology Approach to Elucidate the Mechanisms

Article pubs.acs.org/est

A Systems Toxicology Approach to Elucidate the Mechanisms Involved in RDX Species-Specific Sensitivity Christopher M. Warner,†,‡ Kurt A. Gust,†,* Jacob K. Stanley,† Tanwir Habib,§ Mitchell S. Wilbanks,† Natàlia Garcia-Reyero,∥ and Edward J. Perkins† †

Environmental Laboratory, U.S. Army Engineer Research and Development Center, Vicksburg, Mississippi, United States Keck Graduate Institute, Claremont, California, United States § Badger Technical Services, San Antonio, Texas, United States ∥ Mississippi State University, Starkville, Mississippi, United States ‡

S Supporting Information *

ABSTRACT: Interspecies uncertainty factors in ecological risk assessment provide conservative estimates of risk where limited or no toxicity data is available. We quantitatively examined the validity of interspecies uncertainty factors by comparing the responses of zebrafish (Danio rerio) and fathead minnow (Pimephales promelas) to the energetic compound 1,3,5-trinitroperhydro-1,3,5-triazine (RDX), a known neurotoxicant. Relative toxicity was measured through transcriptional, morphological, and behavioral end points in zebrafish and fathead minnow fry exposed for 96 h to RDX concentrations ranging from 0.9 to 27.7 mg/L. Spinal deformities and lethality occurred at 1.8 and 3.5 mg/L RDX respectively for fathead minnow and at 13.8 and 27.7 mg/L for zebrafish, indicating that zebrafish have an 8-fold greater tolerance for RDX than fathead minnow fry. The number and magnitude of differentially expressed transcripts increased with increasing RDX concentration for both species. Differentially expressed genes were enriched in functions related to neurological disease, oxidative-stress, acute-phase response, vitamin/ mineral metabolism and skeletal/muscular disorders. Decreased expression of collagen-coding transcripts were associated with spinal deformity and likely involved in sensitivity to RDX. Our work provides a mechanistic explanation for species-specific sensitivity to RDX where zebrafish responded at lower concentrations with greater numbers of functions related to RDX tolerance than fathead minnow. While the 10-fold interspecies uncertainty factor does provide a reasonable cross-species estimate of toxicity in the present study, the observation that the responses between ZF and FHM are markedly different does initiate a call for concern regarding establishment of broad ecotoxicological conclusions based on model species such as zebrafish.

■

INTRODUCTION

to compare the relative sensitivity to chemical toxicity among species.3 This study sought to develop a robust empirical cross-species comparison for consideration in ERA and to assess if a typical 10-fold uncertainty factor of is overly conservative. To attain this goal, we analyzed the relationships among multiple levels of biological organization to provide a mechanistic description of differential sensitivity among species. We utilized the Adverse Outcome Pathway (AOP) framework to contextualize our species comparisons.4 The AOP characterizes connections from the molecular initiating event, to impacts on metabolic pathways, to impacts within a cell, through impacts on tissues, organs and so on and ultimately to the adverse outcome at the

New chemical testing programs, including the High Production Volume (HPV) challenge in the United States and Registration, Evaluation, Authorization and Restriction of Chemicals (REACH) in Europe are significantly increasing the number of chemicals for which toxicity data is needed.1 In addition, human and veterinary pharmaceuticals, nanocomposites and other engineered materials promise to increase demands for regulatory testing for ecological effects.2 Ecological testing and screening programs must become more thorough, less costly, and more rapid to make testing of thousands of chemicals feasible. A critical and often overlooked component of transitioning test data to ecological risk assessment (ERA) are the uncertainty factors associated with toxicological effects observed in model versus nonmodel species. Current methods employed for ERA rely on arbitrary uncertainty factors (typically a factor of 10) when quantitative data is not available © 2012 American Chemical Society

Received: Revised: Accepted: Published: 7790

February 6, 2012 May 31, 2012 June 14, 2012 June 14, 2012 dx.doi.org/10.1021/es300495c | Environ. Sci. Technol. 2012, 46, 7790−7798

Environmental Science & Technology

Article

population level.4 Although, a number of studies have adopted the AOP framework to robustly describe systemic toxicological impacts,5−9 our study represents the first to investigate the conservation of AOPs across multiple species and if threshold concentrations for adverse outcomes vary among species. RDX is an energetic compound found as a contaminant at manufacturing sites, loading and storage facilities, firing ranges, and demilitarization areas.10 RDX has the potential to affect many species, as it can accumulate in multiple environmental compartments including soil, surface water, and groundwater, and is a contaminant of concern at over 28 sites in the United States.11 The molecular initiating event for RDX toxicity is the binding to the GABAA receptor.12 The neurological impacts of RDX have been observed in many species, including human, rat, quail, earthworm, fathead minnows, and zebrafish.13−17 In this work, we used a systems toxicology approach to compare the mechanistic responses to RDX toxicity in two cyprinid fish species, the zebrafish and the fathead minnow. We tested a hypothesis of null difference in sensitivity and response profiles among these species.

using SigmaStat (version 3.5, Systat Software, Chicago, IL) statistical software. Analytical Chemistry. Two water samples were collected from each control and RDX-treatment group upon initiation of bioassays and after exposure-water renewal at 48 h. RDX water concentrations were quantified using high performance liquid chromatography (HPLC) following EPA 8830 protocol.21 Analyses were conducted with an Agilent 1100 Series HPLC (Palo Alto, CA) equipped with a Supelco RP-Amide C-16 column (Sigma, St Louis, MO) and a photodiode array detector. Sample injection volume was 100 μL with a flow rate of 1 mL per minute at a column temperature of 45 °C. An isocratic mobile phase consisting of 55% methanol and 45% water was utilized. Absorbance intensity was measured at 230 and 254 nM, corresponding to peaks identified from confirmation of retention time and spectral analysis. Analytical data were averaged across sampling times resulting in measured exposure concentrations of 0.88, 1.75, 3.46, 6.96, 13.79, or 27.71 mg/L. Our previous work has indicated that RDX concentrations remain stable in static renewal exposures.22 The laboratory reporting limit for all analytes was 0.1 mg/L. Tissue Fixation and RNA Extraction. After 96 h of exposure, five individual FHM or ZF were collected from each experimental unit (EU) for genomics investigations. The remaining five were flash frozen and stored for archival purposes. The five individuals designated for genomics analysis were pooled within each EU providing four biological replicates each for controls and all six RDX treatments. These fish were immediately placed into cryovials containing RNAlater (Ambion, Austin, TX) following manufacturer’s instructions. Due to mortality, only four individual FHM contributed to each of four biological replicates within the 13.79 mg/L RDX exposure concentration. Fathead minnows from the 3.46 mg/L treatment and both ZF and FHM from the 27.71 mg/L treatment were excluded from the design due to high mortality in the bioassay. RNA extraction from tissues and assessment of RNA quality were conducted as described previously15and are briefly described in the SI. Microarrays. Microarray analysis for FHM was conducted using a FHM-specific 15,000 (60mer oligonuleotide probe) feature microarray (GEO: http://www.ncbi.nlm.nih.gov/geo/; Accession platform number GPL9248) designed by Dr. Nancy Denslow (University of Florida, Gainesville, FL) and manufactured by Agilent Technologies. Expression in ZF was determined using a ZF-specific 44 000 (60mer oligonucleotide probe) feature microarray (GEO: http://www.ncbi.nlm.nih. gov/geo/; Accession platform number GPL7301) manufactured by Agilent Technologies. The Agilent One-Color Microarray Hybridization protocol (Agilent Technologies) was utilized for microarray hybridizations following manufacturer’s recommendations using 400 ng of total RNA extracted from each composite sample containing four to five whole fry representing one of four biological replicates per treatment. Randomized block designs were utilized to eliminate the potential for batch effects among two temporally separated microarray hybridization events. Two of the four total biological replicates for each treatment were randomly assigned to one of two blocks (consisting of multiple microarray slides) using a random number generator. Both FHM and ZF exposures included solvent control, 0.88, 1.75, 6.96, and 13.79 mg/L treatments. Due to high observed variance in the initial FHM hybridization (high relative to the ZF hybrid-

■

MATERIALS AND METHODS Three-day-old fathead minnow (FHM) and zebrafish (ZF) fry (Aquatic BioSystems, Fort Collins, CO) were exposed to either solvent control or one of six measured exposure concentrations of RDX (0.88, 1.75, 3.46, 6.96, 13.79, or 27.71 mg/L) for 96 h. A static renewal exposure design (exposure water renewed after 48 h) was used for both species and was based on the U.S. EPA acute testing method for Pimephales promelas, test method 2000.0.18 Tap water (Vicksburg, MS) dechlorinated via activated charcoal filtration was used for all exposures. Exposures were conducted in an environmental chamber at 25 °C and a light:dark cycle of 16 h:8 h. Four replicate experimental units were used per treatment with 10 fish per unit. Each unit was housed in individual beakers where dissolved oxygen concentrations were ensured via slight aeration (approximately one bubble per second) into each beaker with a single glass pipet connected to a constant airflow. Fish were fed three hours before the 48 h water renewal. FHM were fed brine shrimp (Artemia nauplii, San Francisco Bay Brand, Newark, CA) and ZF were fed ARTEMAC-0 fish food (20−80 μM diameter, Aquafauna Bio-Marine, Inc., Hawthorne, CA). Measured end points included survival, swimming behavior, transcript expression, and incidence of vertebral deformity at the end of the 96 h. Swimming behavioral analyses were performed on each surviving fish after 96 h of exposure using a video tracking system with Noldus EthoVision (Wageningen, Netherlands) as described in the Supporting Information (SI). Incidence of vertebral deformity was selected as an end point because Mukhi et al.19 found that RDX caused vertebral column deformity in developing larvae in 96 h acute bioassays. All surviving larvae were observed under a stereomicroscope at the end of the 96 h exposure to determine the proportion of individuals exhibiting vertebral deformities. Statistical Analysis of Toxicology Data. Fifty percent lethal concentrations (LC50) were determined using the Trimmed Spearman-Karber method.20 Analyses of FHM and ZF survival and vertebral deformity data were performed using a parametric one-way analysis of variance (ANOVA) along with a Dunnett’s multiple range test. Analysis of response between species in a treatment was performed using a parametric twoway ANOVA and a Tukey’s test. All ANOVAs were performed 7791

dx.doi.org/10.1021/es300495c | Environ. Sci. Technol. 2012, 46, 7790−7798


Article

ization), a second set of technical replicate hybridizations were conducted for FHM. Microarray Analysis. An Axon GenePix 4000B Microarray Scanner (Molecular Devices, Inc., Sunnyvale, CA) was used to scan microarray images at 5 μm resolution. Data were extracted using Agilent Feature Extraction software, version 9.5.1 (Agilent Technologies). Internal control spots were analyzed to confirm that signal data was within the linear range of detection. Raw data was deposited at the Gene Expression Omnibus Web site (GEO: http://www.ncbi.nlm.nih.gov/geo/; accession series record number GSE27067). GeneSpring version GX 11.0.2 (Agilent Technologies) was used to normalize data using quantile normalization followed by baseline transformation to the median of all samples. Statistical analysis was performed in GeneSpring where one-way ANOVA (p ≤ 0.05) with Benjamini-Hochberg multiple-testing correction was conducted including a 1.5 fold-change cutoff. In FHM, duplicate sets of technical replicates were averaged and then analyzed as described above. Finally, a total of four outlier hybridizations were removed from the FHM analysis. To avoid biases due different numbers of gene probes on each array, ZF and FHM expression was compared using a gene set including genes only present on both arrays. Where multiple probes were found to target a GenBank accession number, a single probe was randomly selected to represent that gene. A gene set totaling 6098 nonredundant, unique transcript identities was found to be common on both FHM and ZF arrays (SI Table S1). All comparative analyses were conducted using this common probe set. Functional Enrichment. Functional analyses of differentially expressed transcripts (DETs) for both ZF and FHM were conducted using Ingenuity Pathway Analysis (IPA, Ingenuity Systems, www.ingenuity.com) and the common gene set. Enrichment analysis for biological function and canonical pathways was conducted using DETs for each RDXexposure concentration. A right-tailed Fisher’s exact test was used to test for significant enrichment (p = 0.05). Real-Time Quantitative Polymerase Chain Reaction. FHM and ZF microarray results were validated using real-time quantitative polymerase chain reaction (RT-qPCR) (SI Table S2). DNase (Qiagen, Valencia, CA) treated total RNA from all biological replicates previously used in microarray hybridizations (four replicates per treatment) were examined by RTqPCR (see SI for molecular methods). Briefly, 400 ng of total RNA was reverse transcribed into cDNA in a 6.3 μL reaction containing 250 ng of random primers and SuperScript III reverse transcriptase, following the manufacturer’s protocol. Cycling parameters for cDNA amplification were 95 °C for 15 min, 40 cycles of 95 °C for 15 s, and 60 °C for 1 min. Results were normalized to 18S rRNA and analyzed using the ΔΔCt method (Applied Biosystems, Foster City, CA).

Figure 1. (A) Survival in separate 96-h fathead minnow and zebrafish bioassays. Error bars are ± one standard deviation. Stars directly over bars indicate significant differences (p < 0.05) in survival as compared to each species’ respective control group. Stars over a bracket indicate a significant difference between survival in fathead minnow and zebrafish within a single RDX treatment. (B) Proportion of surviving fathead minnows and zebrafish exhibiting vertebral deformity at the end of separate 96 h bioassays. Error bars are ± one standard deviation. Stars directly over bars indicate significant differences in the incidence of spinal deformity as compared to each species’ respective control group. Stars over a bracket indicate a significant difference between incidence of vertebral deformity in surviving fathead minnow and zebrafish within a single RDX treatment.

for FHM is shallow (and as a consequence shows more irregularities) compared to ZF indicating differential functional responses to RDX among species. Significant differences in survival between FHM and ZF at the same treatment level were observed at the 0.88, 1.75, 3.46, 6.96, and 13.79 mg/L RDX treatments (Figure 1A). Vertebral Deformity Assay. FHM exhibited a greater incidence of vertebral deformity than ZF (Figure 1B). The LOEC for vertebral deformity was 1.75 mg/L for FHM and 13.79 mg/L for ZF, a 7.88 fold difference. Significant differences in incidence of vertebral deformity between FHM and ZF at the same treatment level were observed at the 1.75, 6.96, and 13.79 mg/L RDX treatments (Figure 1B). Incidences of vertebral deformities in ZF were observed at similar frequencies to corresponding treatment levels in ZF previously observed by Mukhi et al.19 Swimming Behavior. Analysis of FHM swimming behavior showed potential, but nonsignificant, trends (see SI

■

RESULTS Survival. Survival in controls at the conclusion of the 96 h exposures was above the required minimum of 90% for both species.18 FHM were more sensitive to RDX exposure for lethal effects than ZF (Figure 1A). The lowest observed effect concentration (LOEC) for FHM was 3.46 mg/L RDX, whereas the LOEC for ZF was the highest treatment level tested, 27.71 mg/L, an 8-fold difference. A nonmonotonic response was observed for FHM as significant reductions in survival were observed at the 3.46 and 13.79 mg/L treatments but not the 6.96 treatment level. The concentration-lethality relationship 7792



Article

for details) in the end points assessed. No concentrationdependent trends in any of the swimming behavioral end points assessed were observed for ZF. Gene-Transcript Expression. Results of ANOVA with multiple-test corrections identified 687 and 2,154 differentially expressed transcripts (DETs) for FHM and ZF, respectively. When only the common targets in both arrays were examined, 187 and 496 DETs were differentially expressed in FHM and ZF, respectively (SI Table S3). There were 30 overlapping DETs between the two species. A positive relationship between RDX-exposure concentration and the number of DETs was observed in both species. FHM had 1, 25, 66, and 109 DETs, whereas ZF had 17, 32, 181, and 459 DETs in 0.88, 1.75, 6.96, and 13.79 mg/L treatments, respectively (SI Table S3). Finally, comparison of microarray and RT-qPCR results indicated that there was 71.3% and 77.1% concordance among expression results for ZF and FHM, respectively (SI Table S4). Functional Enrichment. A total of 134 and 369 DETs had meaningful associated functional annotations. There were 86 biological functions (SI Table S5) and 66 canonical pathways (SI Table S6) statistically enriched as a result of RDX exposure. A total of 82 biological functions and 6 canonical pathways were observed in common among species. Enrichment of biological functions and canonical pathways tended to increase in overall number and degree of enrichment in a concentrationdependent manner for both species. The number of DET pathway/function members in enriched functions and canonical pathways potentially related to RDX sensitivity and/or RDXinduced spinal deformity such as glutamate metabolism, neurological disease, drug metabolism, Nrf2 mediated pathway, Vitamin and mineral metabolism, acute phase response, connective tissue disorders, and skeletal and muscular disorders generally increased with increasing RDX concentration (Figure 2, SI Tables S5 and S6). However, ZF tended to have a greater response to RDX than FHM both in magnitude of response (numbers of pathway/function members and expression values) and sensitivity to RDX. (SI Tables S7 and S8). ZF had a pathway-based LOEC of 0.88 mg/L RDX where significant effects were observed on canonical signaling pathways including IL-22 Signaling, Role of JAK family kinases in IL-6-type Cytokine Signaling, IL-9 Signaling, Role of JAK2 in Hormone-like Cytokine Signaling, CNTF Signaling, Eicosanoid Signaling, Role of JAK1 and JAK3 in Cytokine Signaling, Erythropoietin Signaling, Growth Hormone Signaling, IL-10 Signaling, JAK/Stat Signaling, Starch and Sucrose Metabolism, and Prolactin Signaling (SI Table S6). FHM had a higher pathway-based LOEC with significant effects initiated at 1.75 mg/L RDX on the canonical pathways DNA methylation and transcriptional repression signaling, antiproliferative role of TOB in T cell signaling, pentose phosphate pathway, aminoacyl-tRNA Biosynthesis, galactose metabolism, and TNFR1 signaling (SI Table S6).

Figure 2. Functional enrichment of differentially expressed transcripts corresponding to biological functions (blue bars) and canonical pathways (orange bars) calculated by ingenuity pathway analysis software (SI Tables S5 and S6). Right-tailed Fisher’s exact tests were used to test for significant enrichment [(*) p < 0.05, (**) p < 0.01] within each RDX-exposure concentration. Colored boxes represent groupings of related biological functions and/or canonical pathways. Plot titles (in black) represent official biological function or canonical pathway nomenclature. The x-axis represents RDX exposure concentration (mg/L). The Y-axis represents the number of differentially expressed genes present in the function or pathway.

well as providing potential mechanisms underlying differential tolerance to RDX. Potential Mechanisms for Differential Species Sensitivity. ZF fry were approximately 8-fold less sensitive than FHM fry to RDX when the apical end points of spinal deformity and lethality are considered. However, ZF larvae were also 2-fold more sensitive than FHM when LOECs of pathway-level impacts are considered. Several biological functions and canonical pathways were enriched in both ZF and FHM that we hypothesize to underscore differential species sensitivity (SI Tables S5 and S6). The most probable mechanisms include the summary categories of neurological impacts, RDX metabolism, response to oxidative stress and

■

DISCUSSION Herein, we (1) describe the hypothetical molecular mechanisms and metabolic strategies underlying the difference in tolerance observed among FHM and ZF in response to RDX, (2) describe a plausible mechanisms underlying RDX-induced spinal deformity and (3) contextualize differential tolerance observations within ERA and ecotoxicology. All observations have been combined into an AOP context (Figure 3) yielding an integration of the observed responses to RDX exposure as 7793



Article

Figure 3. An adverse outcome pathway-based conceptualization of hypothetical responses to RDX exposure in fathead minnow (FHM) and zebrafish (ZF) based on transcript-expression data. Multiple adverse outcomes are integrated in this conceptualization where the various end-states are influenced by the relative tolerance and/or effectiveness of RDX-detoxification strategies of each species. A key for module colors: RDX green = improved state, orange = molecular initiating event, red = adverse event, blue = biological processes indicated to be in operation based on transcript expression. Square boxes represent final states for the organism, whereas rounded boxes represent intermediate states. Finally, solid lines indicate relationships previously observed, where as dashed lines represent relationships hypothesized in this study.

chlonic-tonic seizures.15,27 The molecular initiating event for this response is RDX binding to GABAA receptors which causes unconstrained excitation in neurons and subsequent seizures.12 Many of the molecular impacts of RDX exposure are conserved across a broad range of phyla with consistent enrichment of neurological pathways and functions.17 In the present study, the canonical pathway “glutamate metabolism” and the biological functions “neurological disease” and “nervous system development and function” were significantly enriched in RDX exposures for ZF at all concentrations and in FHM at the 1.75, 6.96, and 13.79 mg/L concentrations (Figure 2, SI Tables S5 and S6). In both species, the number of DETs increased with increasing RDX-exposure concentrations. Overall, ZF and FHM had a similar response to RDX regarding the specific functions and pathways contributing to neurological impacts (Figure 2, SI Table S5 and S6). However, different genes within a biological function and pathway were affected in each species and pathways were enriched at difference concentrations of RDX (SI Tables S7 and S8). For example, a concentration-dependent increase in three key transcripts involved in glutamate metabolism was observed in

tissue preservation. Indicators of neurological impacts included enrichment of glutamate metabolism pathways as well as enrichment of the biological function neurological disease (Figure 2). Characteristic responses for RDX metabolism were observed in the biological function, drug metabolism and subsequent responses in the category of response to oxidative stress that included enrichment of the Nrf2-mediated oxidative stress response pathway and the biological function vitamin and mineral metabolism (Figure 2). The pathway acute-phase response signaling was considered a mechanism of tissue preservation. Finally, there was overlap among observed responses to oxidative stress and the mechanism likely involved in spinal deformity, specifically related to enrichment of vitamin and mineral metabolism (Figure 2). Taken in total, the differential responses and occurrence of these biological functions and canonical pathways at lower concentrations of RDX when ZF is compared to FHM implicates their involvement in conferring greater RDX tolerance to ZF. Neurological Impacts. Although RDX is known to cause a range of effects on endocrine, hematopoietic, and reproductive systems,23−26 the principle clinical symptom induced by RDX is 7794



Article

ability to sense and recruit antioxidant responses to both mitigate the activity of oxidizing agents and repair cellular damage induced by oxidative stress represent plausible mechanisms of tolerance for oxidative toxicants such as RDX. Both FHM and ZF displayed increased expression of transcripts involved in the Nrf2 mediated oxidative stress response (SI Table S8), and similar to the response observed regarding neurological impacts, ZF and FHM employed induction of completely disparate genes within the Nrf2 pathway. Again, we hypothesize that there may be inherent differences in effectiveness of each species-specific metabolic strategy. Tissue Preservation. In addition to activation of mechanisms to reduce oxidative stress, significant enrichment of the “acute phase response” pathway was observed in both ZF and FHM representing another suite of compensatory mechanisms that likely influenced RDX tolerance (Figure 2, SI Table S8). The acute phase response in fish employs a variety of defenserelated activities such as repair of tissue damage, inactivation of proteases, and restoration of the healthy cellular state.43 The number of significant DETs in the pathway increased with increasing RDX exposure concentration for both fish species, however 4-fold more DETs were differentially expressed in ZF when compared to FHM (Figure 2) including greater relative fold change in transcript expression in ZF (SI Table S8). NFKB1A, a master regulator for induction of inflammatory responses44 was increased in expression in both ZF and FHM, while expression of many components of the coagulation cascade was decreased, including the SERPINF family (in ZF and FHM), ITIH3 (in ZF), as well as three genes composing fibrinogen (F2, FGB, FGG), in ZF only (SI Table S8). Reactive oxygen species (ROS) have been shown to induce platelet activation in humans through oxidative stress, especially lipid peroxidation and oxidation of thiol groups.45 Oxidative-stress induced disregulation of the coagulation system could lead to circulatory system failure through excessive thrombosis.46,47 Given these observations, decreased expression of the coagulation system and increased expression of inflammatory responses represent plausible mechanisms that could confer increased tolerance through integrative mitigation of oxidative stress. ZF exhibited a much stronger acute phase response, with more than 3 times as many transcripts differentially expressed potentially reflecting a more robust and effective acute-phase response against RDX exposure. Mechanisms Underlying RDX-Induced Spinal Deformity. The oxidative stress resulting from RDX exposure has the potential to contribute to spinal deformities observed in ZF and FHM. Further, additional potential mechanisms including antioxidant vitamin depletion and resultant impacts on the expression of pathways involved in bone development were also affected in RDX exposures (Figures 2 and 3). Oxidative Stress Taxing Vitamin Metabolism. In order to mitigate the oxidative stress resulting from RDX exposure, vitamin and minerals pools (particularly antioxidants) could become depleted and affect critical physiological processes. For example, vitamin C (ascorbate) deficiency has been shown to cause spinal deformities through a decrease in the collagen content of bone in channel catfish (Ictalurus punctatus).48 Additionally, Vitamin A deficiency has been observed to alter collagen fiber organization through inflammation pathways in rats.49 Vitamin and mineral metabolism was statistically enriched in RDX exposures of FHM and ZF with the number of DETs increasing with increasing RDX concentrations in ZF (Figure 2). A general decrease in the expression level of

ZF. These transcripts code for glutamate-ammonia-ligase (GLUL), a member of the glutamine-synthetase family that is responsible for catabolism of the excitatory neurotransmitter glutamate to the nonactive glutamine,28 glutamate-cysteine ligase (GCLM), the rate-limiting enzyme of glutathione synthesis,29 and NAD synthase glutamine-hydrolyzing (NADSYN1), involved in the degradation of glutamate (SI Table S8).30 In FHM, only one differentially expressed transcript was involved in glutamate metabolism, which was glutathione reductase (GSR, SI Table S8, the central enzyme of cellular antioxidant defense and the reduction of oxidized glutathione disulfide to the sulfhydryl form GSH.31 In both species, RDX elicited responses consistent with decreasing the stimulatory effects of free glutamate to mitigate hyper-excitation of neurons. Although this metabolic response is likely common among species, the sensitivity and the chain of events to achieve the response appears to be unique for ZF and FHM, and consequently, we hypothesize that there may be inherent differences in effectiveness of each species-specific metabolic strategy perhaps via more sensitive signaling pathways in ZF. RDX Metabolism. Studies with rats indicate that RDX affects metabolic activity of key mitochondrial enzymes involved in xenobiotic catabolism in the liver.32 This catabolic process is thought to be initiated by cytochrome P450 or P450-like enzymes by which nitroso groups are cleaved, releasing nitrite molecules, followed by hydroxylation of the carbon atoms. Subsequently, nitrite and formaldehyde are produced, among other intermediates.33 Significant enrichment of the biological function “drug metabolism” was observed (Figure 2) and was comprised of genes encoding: cytochrome P450-like oxidoreductases, peroxidases, heat shock proteins and other redox enzymes hypothesized to be involved in the biotransformation of energetic nitroamines (SI Table S7). ZF had more than twice as many DETs expressed in this biological function compared to FHM, indicating a greater potential for ZF to metabolize RDX. There was a predominant decreased expression of transcripts coding for redox machinery observed in both species, which may represent an acclimation response given that the products of these metabolic steps may form highly oxidative free radicals that can be more toxic than the parent compound.34 In contrast, transcripts coding for heat shock proteins were observed to have increased expression (SI Table S7) including heat shock 70 kDa protein (HSPA1L), a protein observed to allows fish cells to cope with a variety of stressors.35 Relative to FHM, ZF displayed a broader overall response to RDX metabolism likely influencing effectiveness of the response. Response to Oxidative Stress. RDX, like other energetic compounds, has been shown to induce oxidative stress responses in a variety of tissues.12,15,32,36−41 As described above, both RDX and its breakdown products are highly reactive oxidizing agents, consistent with enrichment of transcripts coding for enzymes involved in sensing and responding to oxidative stress (Figure 2). In particular, the Nrf2 mediated oxidative stress response, an important pathway in the sensing and recruitment of cellular antioxidant defense system especially in neurodegenerative diseases in which oxidative stress is closely implicated,42 was significantly enriched in both ZF and FHM. Furthermore, the number of DETs involved in Nrf2 mediated oxidative stress increased with increasing RDX concentrations (Figure 2, SI Table S8). Interestingly, a similar oxidative stress response pattern to RDX has been observed in the earthworm Eisenia fetida.16 The 7795



Article

indicated the potential for RDX to cause neurological impacts, induce responses to metabolize RDX, mobilize oxidative stress responses, preserve tissue by recruiting acute-phase responses, tax vitamin/mineral metabolism and induce spinal deformities through impairment of bone development in both species (Figure 2). We hypothesize that a differential capacity to respond to RDX exposure underlies the observed difference in tolerance among ZF and FHM. ZF mobilized a larger-scale response to oxidative stress and mechanisms to preserve healthier states of cells and tissues at lower exposure concentrations relative to FHM (Figure 2). Further, although ZF and FHM largely had similar responses at the functional and pathway levels of organization, ZF and FHM induced disparate components of functions and pathways in response to RDX (SI Tables S7 and S8) likely resulting in inherent differences in effectiveness. In total, FHM displayed reduced potential to mitigate the impacts of RDX leading to increased incidence of mortality and spinal deformity relative to ZF. While the 10-fold interspecies uncertainty factor prescribed in ERA does provide a reasonable cross-species estimate of toxicity in the present case study, the observation that the responses between ZF and FHM are markedly different does initiate a call for concern regarding establishment of broad ecotoxicological conclusions based on model species such as zebrafish.

transcripts associated with vitamin and mineral metabolism was observed (SI Table S7) indicating a potential decrease in activity in support of basal metabolism and, more specifically, bone development. RDX Affected Expression of Transcripts Involved in Bone Development. Significant enrichment of biological functions including “skeletal and muscular disorders”, “skeletal and muscular system development and function”, “connective tissue disorders”, and “connective tissue development and function” were observed in both ZF and FHM (Figure 2 and SI Table S5). As described above, oxidative stress and impairment of vitamin metabolism likely contributed to these effects. Decreased expression of transcripts coding for collagen including col10a1, col15a1, col1a1a, col1a2, and col4a5 was observed in ZF and decreased expression of col10a1, col1a1 and col1a2 was observed in FHM (Figure 4 and SI Tables S3

■

ASSOCIATED CONTENT

S Supporting Information *

Common probe list used for comparative transcript expression analysis for ZF and FHM (ST1), a copy of the primers used for RT-QPCR (ST2), all DETs from each species (ST3), enriched biological functions (ST4), enriched canonical pathways (ST5), RT-QPCR results (ST6), expression values for canonical pathways (ST7), expression values for biological functions (ST8). Supplementary figures detail results from the swimming behavior assay (SF1), and correlation information matching microarray and RT-QPCR analysis (SF2). Additional details explaining our methods. This material is available free of charge via the Internet at http://pubs.acs.org.

■

AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Notes

Figure 4. Effect of RDX exposure on expression of collagen-coding transcripts in zebrafish and fathead minnow. Symbols represent mean values from RT-qPCR analysis. Symbols that are circled and marked with “*” represent expression values that are significantly different from controls. See SI Table S4 for corresponding microarray expression values.

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS This work was funded by the U.S. Army Environmental Quality Research Program (including BAA 08-4379). Permission for publishing this information has been granted by the Chief of Engineers.

■

and S5). Type I collagen plays a critical role in early bone development with a specific role in calcium deposition.50 Disorders in collagen synthesis have been observed to cause a number of deleterious effects including spinal deformity,51 therefore the decreased expression of the various collagen transcripts in ZF and FHM likely plays a key mechanistic role in observed spinal deformities. Implication for Risk Assessment. This study demonstrates the potential for RDX to elicit mortality and spinal deformities in larval FHM and ZF at relatively high concentrations (Figure 1). Interestingly, FHM was observed to be as much as eight times more sensitive than ZF for each of these responses. The effects of RDX on transcript expression

REFERENCES

(1) Ankley, G. T.; Daston, G. P.; Degitz, S. J.; Denslow, N. D.; Hoke, R. A.; Kennedy, S. W.; Miracle, A. L.; Perkins, E. J.; Snape, J.; Tillitt, D. E.; Tyler, C. R.; Versteeg, D. Toxicogenomics in regulatory ecotoxicology. Environ. Sci. Technol. 2006, 40 (13), 4055−65. (2) Sanderson, H.; Solomon, K. Contaminants of emerging concern challenge ecotoxicology. Environ. Toxicol. Chem. 2009, 28 (7), 1359− 60. (3) Klassen, C. D. 2001, Ed. Casarett and Doull’s Toxicology: The Basic Science of Poisons, 6th, ed.; McGraw-Hill: New York, 2001. (4) Ankley, G. T.; Bennett, R. S.; Erickson, R. J.; Hoff, D. J.; Hornung, M. W.; Johnson, R. D.; Mount, D. R.; Nichols, J. W.; 7796



Article

Russom, C. L.; Schmieder, P. K.; Serrrano, J. A.; Tietge, J. E.; Villeneuve, D. L. Adverse outcome pathways: A conceptual framework to support ecotoxicology research and risk assessment. Environ. Toxicol. Chem. 2010, 29 (3), 730−41. (5) Fedorenkova, A.; Vonk, J. A.; Lenders, H. J.; Ouborg, N. J.; Breure, A. M.; Hendriks, A. J. Ecotoxicogenomics: Bridging the gap between genes and populations. Environ. Sci. Technol. 2010, 44 (23), 9239−40. (6) Watanabe, K. H.; Andersen, M. E.; Basu, N.; Carvan, M. J., 3rd; Crofton, K. M.; King, K. A.; Suñol, C.; Tiffany-Castiglioni, E.; Schultz, I. R. Defining and modeling known adverse outcome pathways: Domoic acid and neuronal signaling as a case study. Environ. Toxicol. Chem. 2011, 30 (1), 9−21. (7) Miller, D. H.; Jensen, K. M.; Villeneuve, D. L.; Kahl, M. D.; Makynen, E. A.; Durhan, E. J.; Ankley, G. T. Linkage of biochemical responses to population-level effects: A case study with vitellogenin in the fathead minnow (Pimephales promelas). Environ. Toxicol. Chem. 2007, 26 (3), 521−7. (8) Murphy, C. A.; Rose, K. A.; Rahman, M. S.; Thomas, P. Testing and applying a fish vitellogenesis model to evaluate laboratory and field biomarkers of endocrine disruption in Atlantic croaker (Micropogonias undulatus) exposed to hypoxia. Environ. Toxicol. Chem. 2009, 28 (6), 1288−303. (9) Villeneuve D. L.; Garcia-Reyero N, Escalon B. L.; Jensen K. M.; Cavallin J. E.; Makynen E. A.; Durhan E. J.; Kahl M. D.; Thomas L. M.; Perkins E. J.; Ankley G. T. Ecotoxicogenomics to support ecological risk assessment: A case study with bisphenol A in fish. Environ. Sci. Technol. 2012, 46, 51−59 (10) Jenkins, T. F.; Pennington, J. C.; Ranney, T. A.; Berry, T. E., Jr.; Miyares, P. H. Characterization of Explosives Contamination at Military Firing Ranges, Technical Report TR-01-5; US Army Cold Regions Research and Engineering Laboratory, Hanover, New Hampshire, 2001. (11) Card, R. E.; Autenrieth, R. Treatment of HMX and RDX Contamination; Amarillo National Resource Center for Plutonium: Amarillo, TX, 1998. (12) Williams, L. R.; Aroniadou-Anderjaska, V.; Qashu, F.; Finne, H.; Pidoplichko, V.; Bannon, D. I.; Braga, M. F. RDX binds to the GABAA receptor-convulsant site and blocks GABAA receptor-mediated currents in the amygdala: A mechanism for RDX-induced seizures. Environ. Health. Perspect. 2011, 119 (3), 357−63. (13) Kaplan, A. S.; Berghout, C. F.; Peczenik, A. Human intoxication from RDX. Arch. Environ. Health 1965, 10, 877−83. (14) Krishnan, K.; Crouse, L. C.; Bazar, M. A.; Majo, M. A.; Reddy, G. Physiologically based pharmacokinetic modeling of cyclotrimethylenetrinitramine in male rats. J Appl Toxicol 2009, 29 (7), 629−37. (15) Gust, K. A.; Pirooznia, M.; Michael, J.; Quinn, M. J., Jr.; Johnson, M. S.; Escalon, B. L.; Indest, K. J.; Guan, X.; Clarke, J.; Deng, Y.; Gong, P.; Perkins, E. J. Neurotoxicogenomic investigations to assess mechanisms of action of the munitions constituents RDX and 2,6-DNT in northern bobwhite (Colinus virginianus). Toxicol. Sci. 2009, 110 (1), 168−80. (16) Gong, P.; Guan, X.; Inouye, L. S.; Deng, Y.; Pirooznia, M.; Perkins, E. J. Transcriptomic analysis of RDX and TNT interactive sublethal effects in the earthworm Eisenia fetida. BMC Genomics 2008, 9 (Suppl I), S15. (17) Garcia-Reyero, N.; Habib, T.; Pirooznia, M.; Gust, K. A.; Gong, P.; Warner, C. M.; Wilbanks, M. S.; Perkins, E. J. Conserved toxic responses across divergent phylogenetic lineages: A Meta-analysis of the neurotoxic effects of RDX among multiple species using toxicogenomics. Ecotoxicology 2011, 20 (3), 580−94. (18) United States Environmental Protection Agency. Method 1003.0 in Short-Term Methods for Estimating the Chronic Toxicity of Effluents and Receiving Waters to Freshwater Organisms, 4th ed.; U.S. EPA: Washington DC, 2002. (19) Mukhi, S.; Pan, X.; Cobb, G. P.; Patino, R. Toxicity of hexahydro-1,3,5-trinitro-1,3,5-triazine to larval zebrafish (Danio rerio). Chemosphere 2005, 61 (2), 178−85.

(20) Hamilton, M. A.; Russo, R. C.; Thurston, R. V. Trimmed Spearman-Karber method for estimating median lethal concentrations in toxicity bioassays. Environ. Sci. Technol. 1977, 11 (7), 714−719 correction 12(4):417 (1978). (21) United States Environmental Protection Agency. Method 8330A. Nitroaromatics and Nitramines by High Performance Liquid Chromatography, EPA SW-486; U.S. EPA: Washington DC, 2007. (22) Gust, K. A.; Brasfield, S. M.; Stanley, J. K.; Wilbanks, M. S.; Chappell, P.; Perkins, E. J.; Lotufo, G. R.; Lance, R. F. Genomic investigation of year long and multi-generational exposures of fathead minnow to the munitions compound RDX. Environ. Toxicol. Chem. 2011B, 30 (8), 1852−64. (23) Reddy, G.; Erexson, G. L.; Cifone, M. A.; Major, M. A.; Leach, G. J. Genotoxicity assessment of hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX). Int. J. Toxicol. 2005, 24 (6), 427−434. (24) Health Effects. In Toxicological profile for RDX.Agency for Toxic Substances and Disease Registry (ATSDR); Public Health Service, U.S. Department of Health and Human Services: Atlanta, GA and National Technical Information Service: Springfield, VA, 1995; www. atsdr.cdc.gov/toxprofiles/tp78.pdf. (25) Small, M. J.; Rosenblatt, D. H. Technical Report 7404 Munitions Production Products of Potential Concern as Waterborne Pollutants− Phase II; US Army Medical Bioengineering Research and Development Laboratory: Aberdeen Proving Ground, MD, 1974. (26) Gust, K. A.; Wilbanks, M. S.; Guan, X.; Pirooznia, M.; Habib, T.; Yoo, L.; Wintz, H.; Vulpe, C. D.; Perkins, E. J.Investigations of transcript expression in fathead minnow (Pimephales promelas) brain tissue reveal toxicological impacts of RDX exposure. Aquat. Toxicol. 2011A, 101 (1), 135−45. (27) Quinn, M. J., Jr.; Bazar, M. A.; McFarland, C. A.; Perkins, E. J.; Gust, K. A.; Johnson, M. S. Sublethal effects of subacute exposure to RDX (1,3,5-trinitro-1,3,5-triazine) in the northern bobwhite Colinus virginianus. Environ. Toxicol. Chem. 2009, 28 (6), 1266−70. (28) Meldrum, B. Glutamate as a neurotransmitter in the brain: Review of physiology and pathology. J. Nutr. 2000, 130 (4S), 1007S− 15S. (29) Chen, Y.; Shertzer, H. G.; Schneider, S. N.; Nebert, D. W.; Dalton, T. P. Glutamate cysteine ligase catalysis: Dependence on ATPand modifier subunit for regulation of tissue glutathione levels. J. Biol. Chem. 2005, 33766−74. (30) Hara, N.; Yamada, K.; Terashima, M.; Osago, H.; Shimoyama, M.; Tsuchiya, M. Molecular identification of human glutamine- and ammonia-dependent NAD synthetases carbon-nitrogen hydrolase domain confers glutamine dependency. J. Biol. Chem. 2003, 278 (13), 10914−21. (31) Green, D. E.; Leloir, L. F.; Nocito, W. Transaminases. J. Biol. Chem. 1945, 161, 559−82. (32) Bannon, D. I.; Dillman, J. F.; Hable, M. A.; Phillips, C. S.; Perkins, E. J. Global gene expression in rat brain and liver after oral exposure to the explosive Hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX). Chem. Res. Toxicol. 2009, 22 (4), 620−25. (33) Bhushan, B.; Trott, S.; Spain, J. C.; Halasz, A.; Paquet, L.; Hawari, J. Biotransformation of hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) by a rabbit liver cytochrome P450: Insight into the mechanism of RDX biodegradation by Rhodococcus sp. Strain DN22. Appl. Environ. Microbiol. 2003, 69 (3), 1347−51. (34) Rao, M. R.; Halfhill, M. D.; Abercrombie, L. G.; Ranjan, P.; Abercrombie, J. M.; Gouffon, J. S.; Saxton, A. M.; Stewart, C. N., Jr. Phytoremediation and phytosensing of chemical contaminants, RDX and TNT: Identification of the required target genes. Funct. Integr. Genomics 2009, 9, 537−47. (35) Iwama, G. K.; Thomas, P. T.; Forsyth, R. B.; Vijanyan, M. M. Heat shock protein expression in fish. Rev. Fish Biol. Fish. 1998, 8, 35− 56. (36) Perkins, E. J.; Bao, W.; Guan, X.; Ang, C. Y.; Wolfinger, R. D.; Chu, T. M.; Meyer, S. A.; Inouye, L. S. Comparison of transcriptional responses in liver tissue and primary hepatocyte cell cultures after exposure to hexahydro-1, 3, 5-trinitro-1, 3, 5-triazine. BMC Bioinf. 2006, 7 (Suppl. 4), 22. 7797



Article

(37) Ek, H.; Dave, G.; Sturve, J.; Almroth, B. C.; Stephensen, E.; Förlin, L.; Birgersson, G. Tentative biomarkers for 2,4,6-trinitrotoluene (TNT) in fish (Oncorhynchus mykiss). Aquat. Toxicol. 2005, 72 (3), 221−30. (38) Miliukiene, V.; Cenas, N. Cytotoxicity of nitroaromatic explosives and their biodegradation products in mice splenocytes: Implications for their immunotoxicity. Z. Naturforsch., C: J. Biosci. 2008, 63 (7−8), 519−25. (39) Hebels, D. G.; Briedé, J. J.; Khampang, R.; Kleinjans, J. C.; de Kok, T. M. Radical mechanisms in nitrosamine- and nitrosamideinduced whole-genome gene expression modulations in Caco-2 cells. Toxicol. Sci. 2010, 116 (1), 194−205. (40) Peters, G. T.; Burton, D. T.; Paulson, R. L.; Turlety, S. D. The acute and chronic toxicity of hexahydro-1,3,5-trinitro-1,3,5 triazine (RDX) to three freshwater invertebrates. Environ. Toxicol. Chem. 1991, 10, 1073−81. (41) Faust, R. A. Toxicity Summary for Hexahydro-1,3,5-Trinitro-1,3,5Triazine (RDX); Chemical Hazard Evaluation Group, Biomedical and Environmental Information Analysis Section, Health Sciences Research Division, Oak Ridge Reservation Environmental Restoration Program, Oak Ridge National Laboratory: Oak Ridge, TN, 1994 (42) Lee, J.; Johnson, J. A. An important role of Nrf2-ARE pathway in the cellular defense mechanism. J. Biochem. Mol. Bio. 2004, 37 (2), 139−43. (43) Bayne, C. J.; Gerwick, L. The acute phase response and innate immunity of fish. Dev. Comp. Immunol. 2001, 25 (8−9), 725−43. (44) Chen, F.; Castranova, V.; Shi, X.; Demers, L. M. New insights into the role of nuclear factor-kappa-B, a ubiquitous transcription factor in the initiation of diseases. Clin. Chem. 1999, 45 (1), 7−17. (45) Violi, F.; Pignatelli, P. Platelet oxidative stress and thrombosis. Arterioscler., Thromb., Vasc. Biol. 2008, 28, s11−s16. (46) Sobotková, A.; Másová-Chrastinová, L.; Suttnar, J.; Stikarová, J.; Májek, P.; Reicheltová, Z.; Kotlín, R.; Weisel, J. W.; Malý, M.; Dyr, J. E. Antioxidants change platelet responses to various stimulating events. Free Radic. Biol. Med. 2009, 47 (12), 1707−14. (47) Freedman, J. E. Oxidative Stress and Platelets. Arterioscler., Thromb., Vasc. Biol. 2008, 28, s11−s16. (48) Lim, C.; Lowell, R. T. Pathology of the vitamin C syndrome in channel catfish (Ictalurus punctatus). J. Nutr. 1978, 108 (7), 1137−46. (49) Marín, M. P.; Esteban-Pretel, G.; Alonso, R.; Sado, Y.; Barber, T.; Renau-Piqueras, J.; Timoneda, J. Vitamin A deficiency alters the structure and collagen IV composition of rat renal basement membranes. J. Nutr. 2005, 135 (4), 695−701. (50) Cowles, E. A.; DeRome, M. E.; Pastizzo, G.; Brailey, L. L.; Gronowicz, G. A. Mineralization and the expression of matrix proteins during in vivo bone development. Calcif. Tissue Int. 1998, 62 (1), 74− 82. (51) Widmann, R. F.; Bitan, F. D.; Laplaza, F. J.; Burke, S. W.; DiMaio, M. F.; Schneider, R. Spinal deformity, pulmonary compromise, and quality of life in osteogenesis imperfect. Spine 1999, 24 (16), 1673−8.

7798


A Systems Toxicology Approach to Elucidate the Mechanisms

Recommend Documents