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Adaptive stress response pathways induced by environmental mixtures of bioaccumulative chemicals in dugongs Ling Jin, Caroline Gaus, and Beate I. Escher Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.5b00947 • Publication Date (Web): 29 Apr 2015 Downloaded from http://pubs.acs.org on May 17, 2015
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Adaptive stress response pathways induced by
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environmental mixtures of bioaccumulative
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chemicals in dugongs
4 Ling Jin,† Caroline Gaus,† and Beate I. Escher†,‡,ǁ,*
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†
The University of Queensland, National Research Centre for Environmental Toxicology (Entox),
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Brisbane, QLD, Australia ‡
UFZ - Helmholtz Centre for Environmental Research, Cell Toxicology, Leipzig, Germany ǁ
Eberhard Karls University Tübingen, Environmental Toxicology, Center for Applied
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Geosciences, Germany
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Key words: bioanalytical equivalent, metabolic activation, mixture toxicity, passive sampling,
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polydimethylsiloxane
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ABSTRACT
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To address the poorly understood mixture effects of chemicals in the marine mammal dugong,
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we coupled equilibrium-based passive sampling in blubber to a range of in vitro bioassays for
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screening mixtures of bioaccumulative chemicals. The modes of action included early effect
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indicators along important toxicity pathways, such as induction of xenobiotic metabolism, and
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some integrative indicators downstream of the molecular initiating event, such as adaptive stress
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responses. Activation of aryl hydrocarbon receptor (AhR) and Nrf2-mediated oxidative stress
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response were found to be the most prominent effects, while the p53-mediated DNA damage
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response and NF-κB-mediated response to inflammation were not significantly affected. While
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polychlorinated dibenzo-p-dioxins (PCDDs) quantified in the samples accounted for the majority
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of AhR-mediated activity, PCDDs explained less than 5% of the total oxidative stress response,
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despite their known ability to activate this pathway. Altered oxidative stress response was
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observed with both individual chemicals and blubber extracts subject to metabolic activation by
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rat liver S9 fraction. Metabolic activation resulted in both enhanced and reduced toxicity,
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suggesting the relevance and utility of incorporating metabolic enzymes into in vitro bioassays.
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Our approach provides a first insight into the burden of toxicologically relevant bioaccumulative
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chemical mixtures in dugongs and can be applied to lipid tissue of other wildlife species.
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INTRODUCTION
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The (sub)tropical coastal zone of Queensland, Australia sustains diverse and unique ecosystems
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where, for instance, extensive seagrass habitats nearshore provide food sources for the strictly
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herbivorous marine mammal dugong (Dugong dugon). The nearshore environment is receiving
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land-based chemical contaminants, including persistent bioaccumulative toxic (PBT) chemicals,
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via agricultural, industrial sources and urban runoff.1 The unique feeding habit of dugongs
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determines their inevitable uptake of contaminants associated with the sediment-seagrass system.
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Long life spans and high lipid content render dugongs prone to accumulation of hydrophobic
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organic chemicals such as dioxin-like chemicals to levels that may lead to adverse health
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effects.2-4 In reality, however, dugongs are exposed to a much broader spectrum of known and
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unknown chemicals, in addition to those chemicals targeted in previous investigations.5-7 A
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quantitative, mechanistic understanding of the toxicological implications of these chemical
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mixtures is required to fully establish the role of PBT chemical burdens in the health of dugong
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populations; however, little is known about the combined effects of these complex and
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unresolved mixtures.
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While an archive of dugong blubber samples provided an opportunity to understand PBT
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chemical exposure and mixture effect, our attempts to investigate such mixture effects using
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bioanalytical tools have been hindered by conventional exhaustive solvent extraction methods.
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These traditional methods often require select extraction solvents and extensive clean-up efforts
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to minimize (bio)analytical interferences caused by biological matrices (e.g., lipid),8, 9 thus
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limiting the sample throughput as well as the spectrum of chemicals captured in the extracts.
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To address these limitations, we previously established a simple passive sampling technique
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based on polydimethylsiloxane (PDMS) polymer for unbiased, quantitative sampling of a range
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of bioaccumulative chemicals enriched in the dugong blubber.10 While PDMS can only extract
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neutral organic chemicals, the spectrum of chemicals covered reflects those accumulated in
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typical fatty tissue, such as dugong blubber. Governed by a generally constant lipid-PDMS
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partition coefficient (Klip-PDMS) of 30 for chemicals across a range of physicochemical properties,
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chemical mixture compositions in the sample are thereby proportionally transferred into in
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PDMS.10 In our previous study,10 we demonstrated that the passive sampling technique can be
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linked to in vitro bioassay based screening without the need for clean-up steps to remove lipid
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matrices. The application was validated with a receptor-mediated endpoint, the activation of the
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reporter gene by the aryl hydrocarbon receptor (AhR), which specifically responds to dioxin-like
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chemicals.10 Although the chemical mass transfer from lipid to PDMS is typically low (e.g., 2-3%
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under a mass ratio of 0.5 g blubber to 0.235 g PDMS (one PDMS disk)), PDMS-based passive
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sampling meets the detection limit of the AhR-based bioassay, and up-scaling of the PDMS
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amount can increase the mass of chemicals extracted from blubber in order for a detectable
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response in other less sensitive bioassays.10 Note that unlike for passive sampling of the freely
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dissolved phase, the PBT chemical mass in the blubber sample can be depleted without
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compromising the mass-balance calculations.11
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In addition to the AhR, previous efforts exploring exposure and effect in marine wildlife species
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mainly focused on specific hormone receptor-mediated effects related to endocrine disruption,
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specifically that of estrogen,9, 12-14 androgen,8, 9 and thyroid hormone receptors.15-17 Beyond these
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specific receptor-mediated modes of action, non-specific and reactive modes of action are,
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however, equally important in toxicological screening. Among them, adaptive stress response
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pathway systems offer a set of cellular defense mechanisms protecting cells from damaging
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processes, such as oxidative stress, DNA damage and inflammation, which can be caused by a
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more diverse range of environmental chemicals than those specifically targeting nuclear
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receptors.18 Together with specific modes of action, adaptive stress response mechanisms form
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vital early effect indicators, thus serving as a sentinel ensemble in toxicological screening of both
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individual chemicals and environmental mixtures.18
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In vitro bioassays based on activation of Nrf2-mediated oxidative stress response, for example,
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have been used to screen a myriad of environmental chemicals.19-22 These bioassays have also
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been extensively applied to benchmark organic micropollutants for water quality assessment21, 23-
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28
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mediated DNA damage response and NF-κB-mediated inflammation responses have also been
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applied for these purposes.27, 28 However, the toxicological relevance of these pathways with
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regards to bioaccumulative chemicals in wildlife samples has been scarcely explored.
and in few cases for sediment sample screening.29 In vitro bioassays indicative of p53-
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The present study thus extended the application of PDMS-based passive sampling beyond AhR
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signaling to in vitro bioassays indicative of key stress response pathways (oxidative stress, DNA
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damage and inflammation). Using this toxicologically relevant test battery, we conducted an
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initial hazard screening for dugongs by investigating which modes of action are relevant to
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chemicals present in dugong blubber and evaluating the dynamic range of the biologically active
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chemical burdens across individual samples. According to the results of individual chemical
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profiling in the bioassays, selected potent chemicals were instrumentally analyzed for dugong
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samples, and mixed at the ratio found in each sample to form a defined mixture. The mixture
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experiments were performed with each of these defined mixtures to understand the extent to
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which it may contribute to the combined effect of the corresponding blubber extract.
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EXPERIMENTAL SECTION
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Materials and chemicals. PDMS disks (thickness of 1 mm, diameter of 16 mm, density of 1.17
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g cm-3) were prepared from medical grade PDMS sheet (Specialty Silicone Products, Inc.
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Ballston, Spa, NY, USA). The chemical standards purchased from Sigma Aldrich (purity >97%)
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included polychlorinated dibenzodioxins (PCDDs) and biphenyls (PCBs), polybrominated
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diphenyl ethers (PBDEs), polyaromatic hydrocarbons (PAHs), organochlorine (OC) and
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pyrethroid pesticides (Table 1). Solvents included acetone (analytical grade; Merck, Darmstadt,
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Germany), hexane (analytical grade; Sigma Aldrich, St Louis, MO USA), toluene (analytical
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grade; Merck, Darmstadt, Germany), methanol (analytical grade; Merck, Darmstadt, Germany)
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and dimethyl sulfoxide (DMSO) (Sigma Aldrich; St Louis, MO USA).
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Dugong blubber samples. All the blubber samples (from the ventral line beneath the
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hypodermis) were collected from dugongs stranded along the Queensland coast from 1998-2012
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(more information in SI, Table SI-1). The samples were archived at -20°C at Entox, The
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University of Queensland. The lipid content of each dugong blubber sample ranged from 21-92%
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(median: 73%; SI, Section SI-1, Table SI-2, Figure SI-1).
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PDMS-based passive sampling of bioaccumulative chemicals from blubber. Chemical
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sampling from dugong blubber followed our previously established procedure.10 Briefly, a
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PDMS disk (thickness of 1 mm, diameter of 16 mm, ~235 mg) was sandwiched between a
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blubber slice pair (~0.25 g per slice). The high lipid content of the tested blubber samples
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ensured rapid equilibration of chemicals between PDMS and dugong blubber during passive
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sampling ( dioxin-like PCBs > PAHs measured in the CAFLUX assay
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was consistent with findings in similar in vitro systems measuring AhR activity.42, 43
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Eleven out of 21 chemicals tested were positive for Nrf2-mediated oxidative stress response
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without S9 treatment with ECIR1.5 values spanning approximately five orders of magnitude
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(Figure 2A; Table 2; SI, Table SI-6). For the ten chemicals tested negative for Nrf2 activation,
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no cytotoxicity was observed across the dosed concentration range indicating that a response was
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not prevented by cytotoxicity, but the chemicals did not activate the Nrf2 pathway. Pyrene, OC
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pesticides (p,p’-DDT and p,p’-DDD) and BDE 47 are of similar potency ranking to previously
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reported compounds, including less hydrophobic pesticides, pharmaceuticals and disinfection
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byproducts.21 Except for OCDD, which did not reach IR of 1.5 albeit showing an upward trend,
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it is interesting to note that PCDDs, dioxin-like PCBs and BaP, which are primarily AhR ligands,
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were among the most potent in activating the Nrf2-mediated oxidative stress response pathway.
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A closer examination of the AhR-active compounds (PCDDs, PCBs and PAHs) revealed that the
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rank order of ECIR1.5 for Nrf2 induction in the AREc32 assay followed that of their EC50 for AhR
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activation in the CAFLUX assay (Figure 2B). While PCDDs, PCBs and B[k]F align along the
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1:10 line, B[b]F at the 1:1 line and BaP at the 10:1 line between the two EC values, these
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apparent ratios do not imply the exact quantitative relationship between the two pathways, as the
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AREc32 and CAFLUX assays differ in sensitivity and mechanisms. However, the 10- or100-fold
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differences in the two ratios should be noted, which distinguishes more persistent dioxin-like
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chemicals from more labile PAH compounds. This means degradation of B[b]F and BaP
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rendered them less effective in AhR activation and more effective in Nrf2-mediated oxidative
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stress response than if they would persist in parent forms.
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The mechanism by which AhR ligands activate Nrf2 is not fully understood, because these
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chemicals are by definition not electrophiles directly causing oxidative and/or electrophilic stress
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on the Nrf2-mediated signaling pathway.44 However, crosstalk mechanisms between AhR and
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Nrf2 signaling have been suggested for production of reactive oxygen species following AhR
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binding,45, 46 and thus may explain the activation of Nrf2-mediated pathway. Metabolically active
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AhR ligands such as PAHs can be transformed by cytochrome (CYP) P450 metabolic enzymes
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(e.g., CYP1A1) into more reactive metabolites, such as epoxide, which trigger the Nrf2-mediated
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pathway. While the MCF7 cell, on which the AREc32 assay is based, is generally low in
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metabolic activity due to the low expression of various metabolic enzymes, it, however, contains
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a significant amount of endogenous AhR and CYP1A1.47
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None of the 21 chemicals tested showed any significant effect in the p53 and NF-kB assays, and
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no cytotoxicity was observed across the tested concentration range (Table 2; SI, Table SI-6). In a
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recent study28 on profiling disinfection byproducts on the p53 pathway, a narrow concentration-
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response window was observed between p53 induction and cytotoxicity, that is, the endpoint
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induction cannot be specifically distinguished from cytoxicity. This agrees with the biochemical
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understanding that the p53 activation in the final steps leading to cell fate selection, such as
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apoptosis, when cellular stress response mechanisms are overwhelmed by external stimuli.18 As
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the highest concentration of each test chemical reached or exceeded their estimated medium
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solubility limits, no higher concentration can be used to observe endpoint induction or a decline
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in cell viability.
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Relevance of modes of action to chemical mixtures in blubber samples. The response of the
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four biological endpoints tested with extracts of dugong blubber samples mirrored that of the
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tested individual chemicals. Generally, AhR-mediated activity and Nrf2-mediated oxidative
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stress response were more prominent effects triggered by samples, while none of the 34 dugong
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blubber extracts resulted in a p53-mediated DNA damage response or NF-κB-mediated response
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to inflammation.
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One third (12 out of 34) of the blubber samples induced AhR activation and two thirds (22 out of
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34) triggered an oxidative stress response. The effect elicited by these samples via both modes of
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action span a little more than one order of magnitude, ranging from 10-8
>10-8
-S9 -11
NFκB (ECIR1.5, M)
2,3,7,8-tetrachlorodibenzo-p-dioxin
TCDD
1746-01-6
6.67
2.39(±0.29)×10
3.99(±0.44)×10
1,2,3,7,8-pentachlorodibenzo-p-dioxin
PeCDD
40321-76-4
7.08
1.94(±0.35)×10-11
5.07(±0.57)×10-10
7.82(±0.61)×10-10
>10-8
>10-8
-11
-9
-9
-8
>10-8
1,2,3,4,7,8-hexachlorodibenzo-p-dioxin 1,2,3,4,5,7,8-heptachlorodibenzo-pdioxin 1,2,3,4,6,7,8,9-octachlorodibenzo-pdioxin 2,2’,5,5’-tetrachlorobiphenyl 2,2',4,5,5’-pentachlorobiphenyl
HxCDD
39227-28-6
7.56
5.63(±0.70)×10
2.08(±0.21)×10
2.78(±0.33)×10
>10
HpCDD
35822-46-9
8.17
1.88(±0.52)×10-10
4.11(±0.24)×10-9
6.33(±0.47)×10-9
>10-8
>10-8
OCDD
3268-87-9
8.64
5.68(±0.81)×10-9
>10-8
>10-8
>10-8
>10-8
PCB 52
35693-99-3
6.34
>10-4
>10-4
>10-4
>10-5
>10-5
PCB 101
37680-73-2
6.80
>8×10-5
>5×10-6
>5×10-6
>8×10-5 -9
>8×10-5 -8
-8
-5
>10-5
3,3',4,4',5-pentachlorobiphenyl
PCB 126
57465-28-8
6.98
1.82(±0.39)×10
2.28(±0.12)×10
3.60(±0.28)×10
>10
3,3',4,4',5,5'-hexachlorobiphenyl
PCB 169
56-25-7
7.41
1.05(±0.12)×10-8
1.71(±0.11)×10-7
3.12(±0.37)×10-7
>10-6
>10-6
BaP
50-32-8
6.44
3.45(±0.61)×10-5
3.42(±0.56)×10-6
5.98(±0.24)×10-7
>5×10-6
>5×10-6
5.78
-7
n.a.
n.a.
n.a.
Benzo[a]pyrene #
Benzo[b]fluoranthene
#
Benzo[k]fluoranthene
B[b]F
205-99-2
8.98(±0.46)×10
-8
9.05×10
-7 -7
B[k]F
207-08-9
6.11
5.66(±0.37)×10
8.32×10
n.a.
n.a.
n.a.
Pyrene
Pyr
129-0-0
4.88
>10-4
5.58(±0.69)×10-5
2.72(±0.16)×10-6
>10-5
>10-5
Phenanthrene
Phe
85-1-8
4.46
>10-4
>8×10-5
9.80(±0.85)×10-6
>5×10-5
>5×10-5
BDE 47
5436-43-1
6.81
>5×10-5
1.27(±0.07)×10-5
>2.5×10-5
>10-5
>10-5
BDE 209
1163-19-5
9.87
>2×10-5
>2×10-5
>2×10-5
>10-6
>10-6
p,p'-DDT
50-29-3
6.91
>5×10-5
1.14(±0.04)×10-5
>2.5×10-5
>10-5
>10-5
-5
-5
-5
>10-5
2,2',4,4'-tetrabromodiphenyl ether 2,2',3,3',4,4',5,5',6,6'decabromodiphenyl ether 4,4'-dichlorodiphenyltrichloroethane 4,4'-dichlorodiphenyldichloroethane
p,p'-DDD
72-55-9
6.02
>5×10
4,4'-dichlorodiphenyldichloroethylene
p,p'-DDE
72-54-8
6.51
HCB
118-74-1
5.31
Hexachlorobenzene γ-hexachlorocyclohexane
772 773 774 775 776
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-5
2.99(±0.15)×10
>5×10
>5×10-5
>5×10-5
>5×10-5
>10-5
>10-5
>5×10-5
>5×10-5
>5×10-5
>5×10-6
>5×10-6
-5
>5×10-5
-4
-4
-4
>10
γ-HCH
58-89-9
3.61
>10
Bifenthrin
-
82657-04-3
6.48
>5×10-5
>5×10-5
>5×10-5
>10-5
>10-5
Permethrin
-
52645-53-1
6.10
>2.5×10-5
>2.5×10-5
>2.5×10-5
>5×10-6
>5×10-6
#
26
>10
>10
>5×10
ECIR1.5 values of B[b]F and B[k]F for Nrf2 from Tang et al. (n=1); the EC50 for AhR were newly measured for 72 h in consistency with other compounds in this study as Tang et al.26 measured them for 24 h; n.a. = not analyzed. * Data from EPI Suite.52
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Table 2. Test battery of bioassays used in this study. Cell line
Mode of action
Targeted chemicals
Measured endpoint
Reference compound
CAFLUX
H4IIE rat hepatoma cells
AhR activation indicative of xenobiotic metabolism
dioxin-like chemicals including PAHs
AhR-dependent green fluorescent protein expression
TCDD
AREc-32
MCF-7 human breast cancer cells
Nrf2 activation indicative of oxidative stress response
electrophiles and ROSinducing compounds
HCT1666 human colon cancer cells
p53 activation indicative of tumor suppressor gene
genotoxic agents
THP1 human monocytic leukemia cells
NFκB activation indicative of response to inflammation
drugs, endotoxins, immune-modulating compounds
Assay
p53-bla
NFκB-bla
778
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Nrf2-dependent luciferase expression p53-dependent βlactamase expression NF-κB-dependent βlactamase expression
TCDD (-S9) BaP (+S9)
mitomycin tumor necrosis factor-alpha (TNF-α)
Ref 10, 53
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Figure 2. (A) Comparisons of EC50 in the CAFLUX assay for AhR-mediated activity (filled triangles) and ECIR1.5 values in the AREc32 assay for Nrf2-mediated oxidative stress (empty triangles) among chemicals tested in this study; (B) Relationship between the ECIR1.5 values of each of the tested AhR-active compounds (ECIR1.5 of B[b]F and B[k]F for Nrf2 from Tang et al.;29 with 24-h exposure, EC50 of B[b]F and B[k]F for AhR re-measured for a 72-h exposure period in consistency with other chemicals tested in the present study. 263x107mm (300 x 300 DPI)
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Figure 3. Bioanalytical equivalent concentrations of dugong blubber sample extracts (BEQbio,sample) for different modes of action determined in the corresponding bioassays (data from Table SI-8 with conversion of molar concentrations into mass-based concentrations using equation 8; derivation of method detection limit (MDL) in SI, Section SI-8, Table SI-5). 99x68mm (300 x 300 DPI)
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Figure 4. Percentage contribution of instrumentally quantified PCDDs to the overall mixture effect in dugong blubber samples (n=5 for AhR; n=10 for Nrf2). 87x71mm (300 x 300 DPI)
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