Modulation of Ras signaling alters the toxicity of hydroquinone, a benzene metabolite and component of cigarette smoke

BackgroundBenzene is an established human leukemogen, with a ubiquitous environmental presence leading to significant population exposure. In a genome-wide functional screen in the yeast Saccharomyces cerevisiae, inactivation of IRA2, a yeast ortholog of the human tumor suppressor gene NF1 (Neurofibromin), enhanced sensitivity to hydroquinone, an important benzene metabolite. Increased Ras signaling is implicated as a causal factor in the increased pre-disposition to leukemia of individuals with mutations in NF1.MethodsGrowth inhibition of yeast by hydroquinone was assessed in mutant strains exhibiting varying levels of Ras activity. Subsequently, effects of hydroquinone on both genotoxicity (measured by micronucleus formation) and proliferation of WT and Nf1 null murine hematopoietic precursors were assessed.ResultsHere we show that the Ras status of both yeast and mammalian cells modulates hydroquinone toxicity, indicating potential synergy between Ras signaling and benzene toxicity. Specifically, enhanced Ras signaling increases both hydroquinone-mediated growth inhibition in yeast and genotoxicity in mammalian hematopoetic precursors as measured by an in vitro erythroid micronucleus assay. Hydroquinone also increases proliferation of CFU-GM progenitor cells in mice with Nf1 null bone marrow relative to WT, the same cell type associated with benzene-associated leukemia.ConclusionsTogether our findings show that hydroquinone toxicity is modulated by Ras signaling. Individuals with abnormal Ras signaling could be more vulnerable to developing myeloid diseases after exposure to benzene. We note that hydroquinone is used cosmetically as a skin-bleaching agent, including by individuals with cafe-au-lait spots (which may be present in individuals with neurofibromatosis who have a mutation in NF1), which could be unadvisable given our findings

Modulation of Ras signaling alters the toxicity of hydroquinone, a benzene metabolite and component of cigarette smoke

BACKGROUND: Benzene is an established human leukemogen, with a ubiquitous environmental presence leading to significant population exposure. In a genome-wide functional screen in the yeast Saccharomyces cerevisiae, inactivation of IRA2, a yeast ortholog of the human tumor suppressor gene NF1 (Neurofibromin), enhanced sensitivity to hydroquinone, an important benzene metabolite. Increased Ras signaling is implicated as a causal factor in the increased pre-disposition to leukemia of individuals with mutations in NF1. METHODS: Growth inhibition of yeast by hydroquinone was assessed in mutant strains exhibiting varying levels of Ras activity. Subsequently, effects of hydroquinone on both genotoxicity (measured by micronucleus formation) and proliferation of WT and Nf1 null murine hematopoietic precursors were assessed. RESULTS: Here we show that the Ras status of both yeast and mammalian cells modulates hydroquinone toxicity, indicating potential synergy between Ras signaling and benzene toxicity. Specifically, enhanced Ras signaling increases both hydroquinone-mediated growth inhibition in yeast and genotoxicity in mammalian hematopoetic precursors as measured by an in vitro erythroid micronucleus assay. Hydroquinone also increases proliferation of CFU-GM progenitor cells in mice with Nf1 null bone marrow relative to WT, the same cell type associated with benzene-associated leukemia. CONCLUSIONS: Together our findings show that hydroquinone toxicity is modulated by Ras signaling. Individuals with abnormal Ras signaling could be more vulnerable to developing myeloid diseases after exposure to benzene. We note that hydroquinone is used cosmetically as a skin-bleaching agent, including by individuals with cafe-au-lait spots (which may be present in individuals with neurofibromatosis who have a mutation in NF1), which could be unadvisable given our findings

Gene Expression Profiling in <i>Daphnia magna</i>, Part II: Validation of a Copper Specific Gene Expression Signature with Effluent from Two Copper Mines in California

Genomic technologies show great potential for classifying disease states and toxicological impacts from exposure to chemicals into functional categories. In environmental monitoring, the ability to classify field samples and predict the pollutants present in these samples could contribute to monitoring efforts and the diagnosis of contaminated sites. Using gene expression analysis, we challenged our custom <i>Daphnia magna</i> cDNA microarray to determine the presence of a specific metal toxicant in blinded field samples collected from two copper mines in California. We compared the gene expression profiles from our field samples to previously established expression profiles for Cu, Cd, and Zn. The expression profiles from the Cu-containing field samples clustered with the laboratory-exposed Cu-specific gene expression profiles and included genes previously identified as copper biomarkers, verifying that gene expression analysis can predict environmental exposure to a specific pollutant. In addition, our study revealed that upstream field samples containing undetectable levels of Cu caused the differential expression of only a few genes, lending support for the concept of a no observed transcriptional effect level (NOTEL). If confirmed by further studies, the NOTEL may play an important role in discriminating polluted and nonpolluted sites in future monitoring efforts

Reverse Engineering Adverse Outcome Pathways

The toxicological effects of many stressors are mediated through unknown, or incompletely characterized, mechanisms of action. The application of reverse engineering complex interaction networks from high dimensional omics data (gene, protein, metabolic, signaling) can be used to overcome these limitations. This approach was used to characterize adverse outcome pathways (AOPs) for chemicals that disrupt the hypothalamus‐pituitary‐gonadal endocrine axis in fathead minnows (FHM, Pimephales promelas). Gene expression changes in FHM ovaries in response to seven different chemicals, over different times, doses, and in vivo versus in vitro conditions, were captured in a large data set of 868 arrays. Potential AOPs of the antiandrogen flutamide were examined using two mutual information‐based methods to infer gene regulatory networks and potential AOPs. Representative networks from these studies were used to predict network paths from stressor to adverse outcome as candidate AOPs. The relationship of individual chemicals to an adverse outcome can be determined by following perturbations through the network in response to chemical treatment, thus leading to the nodes associated with the adverse outcome. Identification of candidate pathways allows for formation of testable hypotheses about key biological processes, biomarkers, or alternative endpoints that can be used to monitor an AOP. Finally, the unique challenges facing the application of this approach in ecotoxicology were identified and a road map for the utilization of these tools presented. Environ. Toxicol. Chem. 2011;30:22–38. © 2010 SETA

Reverse Engineering Adverse Outcome Pathways

The toxicological effects of many stressors are mediated through unknown, or incompletely characterized, mechanisms of action. The application of reverse engineering complex interaction networks from high dimensional omics data (gene, protein, metabolic, signaling) can be used to overcome these limitations. This approach was used to characterize adverse outcome pathways (AOPs) for chemicals that disrupt the hypothalamus‐pituitary‐gonadal endocrine axis in fathead minnows (FHM, Pimephales promelas). Gene expression changes in FHM ovaries in response to seven different chemicals, over different times, doses, and in vivo versus in vitro conditions, were captured in a large data set of 868 arrays. Potential AOPs of the antiandrogen flutamide were examined using two mutual information‐based methods to infer gene regulatory networks and potential AOPs. Representative networks from these studies were used to predict network paths from stressor to adverse outcome as candidate AOPs. The relationship of individual chemicals to an adverse outcome can be determined by following perturbations through the network in response to chemical treatment, thus leading to the nodes associated with the adverse outcome. Identification of candidate pathways allows for formation of testable hypotheses about key biological processes, biomarkers, or alternative endpoints that can be used to monitor an AOP. Finally, the unique challenges facing the application of this approach in ecotoxicology were identified and a road map for the utilization of these tools presented. Environ. Toxicol. Chem. 2011;30:22–38. © 2010 SETA

Transcriptomic and Network Analyses Reveal Mechanistic-Based Biomarkers of Endocrine Disruption in the Marine Mussel, <i>Mytilus edulis</i>

Transcriptomics, high-throughput assays, and adverse outcome pathways (AOP) are promising approaches applied to toxicity monitoring in the 21st century, but development of these methods is challenging for nonmodel organisms and emerging contaminants. For example, Endocrine Disrupting Compounds (EDCs) may cause reproductive impairments and feminization of male bivalves; however, the mechanism linked to this adverse outcome is unknown. To develop mechanism-based biomarkers that may be linked through an AOP, we exposed <i>Mytilus edulis</i> to 17-alpha-ethinylestradiol (5 and 50 ng/L) and 4-nonylphenol (1 and 100 μg/L) for 32 and 39 days. When mussels were exposed to these EDCs, we found elevated female specific transcripts and significant female-skewed sex ratios using a RT-qPCR assay. We performed gene expression analysis on digestive gland tissue using an <i>M. edulis</i> microarray and through network and targeted analyses identified the nongenomic estrogen signaling pathway and steroidogenesis pathway as the likely mechanisms of action for a putative AOP. We also identified several homologues to genes within the vertebrate steroidogenesis pathway including the cholesterol side chain cleavage complex. From this AOP, we designed the Coastal Biosensor for Endocrine Disruption (C-BED) assay which was confirmed in the laboratory and tested in the field

Gene Expression Profiling in <i>Daphnia magna</i> Part I: Concentration-Dependent Profiles Provide Support for the No Observed Transcriptional Effect Level

Ecotoxicogenomic approaches to environmental monitoring provide holistic information, offer insight into modes of action, and help to assess the causal agents and potential toxicity of effluents beyond the traditional end points of death and reproduction. Recent investigations of toxicant exposure indicate dose-dependent changes are a key issue in interpreting genomic studies. Additionally, there is interest in developing methods to integrate gene expression studies in environmental monitoring and regulation, and the No Observed Transcriptional Effect Level (NOTEL) has been proposed as a means for screening effluents and unknown chemicals for toxicity. However, computational methods to determine the NOTEL have yet to be established. Therefore, we examined effects on gene expression in <i>Daphnia magna</i> following exposure to Cu, Cd, and Zn over a range of concentrations including a tolerated, a sublethal, and a nearly acutely toxic concentration. Each concentration produced a distinct gene expression profile. We observed differential expression of a very few genes at tolerated concentrations that were distinct from the expression profiles observed at concentrations associated with toxicity. These results suggest that gene expression analysis may offer a strategy for distinguishing toxic and nontoxic concentrations of metals in the environment and provide support for a NOTEL for metal exposure in <i>D. magna</i>. Mechanistic insights could be inferred from the concentration-dependent gene expression profiles including metal specific effects on disparate metabolic processes such as digestion, immune response, development and reproduction, and less specific stress responses at higher concentrations

Transcriptomic and Network Analyses Reveal Mechanistic-Based Biomarkers of Endocrine Disruption in the Marine Mussel, <i>Mytilus edulis</i>

Transcriptomics, high-throughput assays, and adverse outcome pathways (AOP) are promising approaches applied to toxicity monitoring in the 21st century, but development of these methods is challenging for nonmodel organisms and emerging contaminants. For example, Endocrine Disrupting Compounds (EDCs) may cause reproductive impairments and feminization of male bivalves; however, the mechanism linked to this adverse outcome is unknown. To develop mechanism-based biomarkers that may be linked through an AOP, we exposed <i>Mytilus edulis</i> to 17-alpha-ethinylestradiol (5 and 50 ng/L) and 4-nonylphenol (1 and 100 μg/L) for 32 and 39 days. When mussels were exposed to these EDCs, we found elevated female specific transcripts and significant female-skewed sex ratios using a RT-qPCR assay. We performed gene expression analysis on digestive gland tissue using an <i>M. edulis</i> microarray and through network and targeted analyses identified the nongenomic estrogen signaling pathway and steroidogenesis pathway as the likely mechanisms of action for a putative AOP. We also identified several homologues to genes within the vertebrate steroidogenesis pathway including the cholesterol side chain cleavage complex. From this AOP, we designed the Coastal Biosensor for Endocrine Disruption (C-BED) assay which was confirmed in the laboratory and tested in the field