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Ecotoxicology and Human Environmental Health

A cross-species quantitative adverse outcome pathway for activation of the aryl hydrocarbon receptor leading to early life stage mortality in birds and fishes Jon A Doering, Steve B. Wiseman, John P. Giesy, and Markus Hecker Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b01438 • Publication Date (Web): 04 Jun 2018 Downloaded from http://pubs.acs.org on June 4, 2018

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Environmental Science & Technology

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A cross-species quantitative adverse outcome pathway for activation of the aryl

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hydrocarbon receptor leading to early life stage mortality in birds and fishes

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Jon A. Doering,*,† Steve Wiseman, †,‡ John P. Giesy, †,§ Markus Hecker †,||

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†

Toxicology Centre, University of Saskatchewan, Saskatoon, SK, S7N 5B3, Canada

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‡

Department of Biological Sciences, University of Lethbridge, Lethbridge, AB, T1K 3M4,

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Canada

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§

Department of Veterinary Biomedical Sciences, University of Saskatchewan, Saskatoon, SK,

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S7N 5B4, Canada

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||

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S7N 5C8, Canada

School of the Environment and Sustainability, University of Saskatchewan, Saskatoon, SK,

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Keywords: TCDD, PCB, Risk Assessment, Luciferase Reporter Gene Assay, Species Sensitivity

ACS Paragon Plus Environment


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Abstract

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Dioxin-like compounds (DLCs) elicit adverse effects through activation of the aryl hydrocarbon

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receptor (AHR). Prior investigations demonstrated that sensitivity to activation of AHR1 in an in

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vitro AHR transactivation assay is predictive of early life stage mortality among birds. The

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present study investigated the link between sensitivity to activation of AHR1s and AHR2s and

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early life stage mortality among fishes. A significant, linear relationship was demonstrated

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between sensitivity to activation of AHR2 and early life stage mortality among nine fishes, while

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no relationship was found for AHR1. The slope and y-intercept for the linear relationship

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between sensitivity to activation of AHR1 and early life stage mortality in birds was not

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statistically different from the same relationship for AHR2 in fishes. Data for fishes and birds

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across DLCs were expanded into four significant, linear regression models describing the

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relationship between sensitivity to activation of AHR and the dose to cause early life stage

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mortality of 0, 10, 50, or 100%. These four relationships were combined to form a quantitative

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adverse outcome pathway which can predict dose-response curves of early life stage mortality

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for DLCs to any bird or fish from species- and chemical-specific responses in an in vitro AHR

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transactivation assay.

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TOC

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Introduction Along with habitat loss and overexploitation, pollution is a primary cause for decreases in

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populations of wildlife. Currently, ecological risk assessments are hampered by dramatic

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differences in sensitivity to chemicals among a vast diversity of different species and the reality

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that all species of regulatory concern cannot be pragmatically evaluated. This is particularly true

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for ecological risk assessments of legacy contamination by a class of industrial chemicals known

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as dioxin-like compounds (DLCs). DLCs, which include polychlorinated dibenzo-p-dioxins

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(PCDDs), polychlorinated dibenzofurans (PCDFs), and coplanar polychlorinated biphenyls

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(PCBs), are ubiquitous, persistent, and bioaccumulative pollutants of environmental concern

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globally. DLCs share similarities in structure and bind with relatively great affinity to the aryl

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hydrocarbon receptor (AHR). The AHR is a ligand-activated transcription factor that is thought

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to mediate most, if not all, adverse effects associated with exposure to DLCs in vertebrates

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through direct or indirect pleiotropic dysregulation of genes.1 The most severe adverse effects

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occur in embryos of oviparous vertebrates and include craniofacial and cardiovascular

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malformations, pericardial and yolk sac edema, and early life stage mortality.2 Despite all DLCs

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exerting toxicity via a single, specific, and highly conserved mechanism, differences in relative

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sensitivity of embryos as great as 200-fold to the most studied DLC, 2,3,7,8-tetrachlorodibenzo-

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p-dioxin (TCDD), exist both among and within vertebrate taxa.3-5

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In 2007, the National Research Council (NRC) outlined a vision and strategy for toxicity

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testing in the 21st Century.6 The NRC envisioned a shift from whole-animal toxicity testing of

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apical effects to a focus on interactions of chemicals with specific molecular targets leading to

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perturbation of a physiological pathway.6 This vision of predictive toxicology led to the


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development of a conceptual framework known as the adverse outcome pathway (AOP).7 AOPs

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describe existing knowledge and weight of evidence supporting a defensible link between

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adverse apical effects of regulatory relevance, termed the adverse outcome, and the interaction of

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a chemical with a specific molecular target, termed the molecular initiating event.7 The most

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advanced developments in AOPs, known as quantitative AOPs (qAOPs), have potential utility to

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quantitative ecological risk assessments.8-10 A qAOP describes quantitative response-response

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relationships linking the molecular initiating event and adverse outcome to enable quantitative

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prediction of the probability of occurrence or severity of an adverse outcome for a given

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magnitude of chemical interaction with a molecular initiating event.8-10 Depending upon the

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extent of mechanistic understanding and the needs in terms of regulatory application, a qAOP

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could be as simple as a linear regression that quantitatively links the molecular initiating event to

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the adverse outcome, or as complex as a consecutive series of nonlinear models which describe

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responses at several levels of biological organization and simulate associated internal and

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external modifying factors.8,9 However, because of the time and resources required to describe

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even the simplest qAOPs, few have been developed and none have been validated beyond a

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small subset of laboratory model species, which might not be representative of the diversity of

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native species of regulatory concern.8,10-12

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Activation of the AHR is believed to cause early life stage mortality in birds and fishes

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through circulatory failure as a result of cardiovascular teratogenesis.13,14 Several plausible

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mechanisms by which activation of the AHR might cause cardiovascular teratogenesis have been

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investigated, including through dysregulation of vascular endothelial growth factor (VEGF),

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members of the transforming growth factor β (TGF-β) superfamily, cyclooxygenase-2 (COX-2),



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or through production of AHR-dependent reactive oxygen species (ROS).13, 15,16 However, the

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precise series of events which link activation of the AHR to early life stage mortality are

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currently unknown because the AHR directly or indirectly regulates thousands of genes in

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numerous physiological pathways (Figure 1).17-19 This uncertainty in key events and the fact that

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comparable quantitative data is unavailable for most endpoints makes it impossible to describe a

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complete qAOP for activation of the AHR leading to early life stage mortality at present.

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However, results of prior investigations suggest an indirect, quantitative link between sensitivity

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to activation of the AHR and sensitivity to early life stage mortality among birds (Figure 1).20-23

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Specifically, in vitro AHR transactivation assays using COS-7 cells transfected with the AHR1

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isoform of different species of birds has been used to explain the more than 40-fold difference in

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sensitivity to TCDD, and other DLCs, observed within this taxonomic group.20-23 However,

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whether differences in transactivation of AHR isoforms (AHR1 or AHR2) explain differences in

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sensitivity to DLCs among other vertebrates was unknown.5 Therefore, this study identified the

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specific mechanism for the almost 200-fold difference in sensitivity observed within the largest

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group of vertebrates, the fishes.3,5 Specifically, this study investigated sensitivity to activation by

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TCDD in an in vitro AHR transactivation assay for seven AHR1s and twelve AHR2s among

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nine species of fish for which sensitivities of embryos to TCDD were known. The nine species

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were lake trout (Salvelinus namaycush), brook trout (Salvelinus fontinalis), red seabream

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(Pagrus major), fathead minnow (Pimephales promelas), lake sturgeon (Acipenser fulvescens),

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Japanese medaka (Oryzias latipes), white sucker (Catostomus commersonii), northern pike (Esox

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lucius), and zebrafish (Danio rerio). These nine species span an almost 40-fold difference in

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sensitivity to TCDD (Figure S1), comprise six orders and seven families, and include both

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freshwater and marine and both teleost and non-teleost species. Mechanistic understanding


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among chicken (Gallus gallus), pheasant (Phasianus colchicus), and quail (Coturnix japonica)

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described by previous studies21,23 and the nine fishes described here was then used to construct a

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qAOP describing activation of the AHR indirectly leading to early life stage mortality among

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birds and fishes (Figure 1). This qAOP can be used to guide more objective ecological risk

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assessments of native species to exposure to DLCs and demonstrates the potential of 21st Century

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approaches in predictive toxicology proposed by the NRC.

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Materials and Methods

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Identification, Sequencing, and Phylogeny of AHRs. Sequences of AHRs had not yet been

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identified for lake trout, brook trout, fathead minnow, white sucker, or northern pike. AHRs were

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isolated from samples obtained from each species (Table S1). Total RNA was extracted from

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approximately 30 mg of liver by use of the RNeasy Lipid Tissue Mini Kit (Qiagen, Mississauga,

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ON). First-strand cDNA was synthesized from 1 µg total RNA by use of the QuantiTect Reverse

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Transcription Kit (Qiagen). Full-length products were amplified by use of the LongRange PCR

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Kit (Qiagen) with gene-specific primers (Table S2) that were designed from partial sequences

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obtained from a combination of degenerate primers, rapid amplification of cDNA ends (RACE)

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PCR, transcriptome sequencing,24,25 and published sequences in the National Center for

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Biotechnology Information (NCBI) database. Purified full-length products were cloned into

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pGEM-T easy vectors by use of a DNA ligation kit (Invitrogen, Burlington, ON) and

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transformed into competent JM109 Escherichia coli cells (Promega, Madison, WI). Plasmids

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were isolated by use of the QIAprep Spin Miniprep Kit (Qiagen) and sequenced by the

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University of Calgary’s University Core DNA Services (Calgary, AB). A consensus nucleotide

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sequence was determined by aligning three or more replicated sequences and has been made



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publicly available in the National Center for Biotechnology Information (NCBI) database (Table

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S2).

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Development of Expression Constructs for AHRs. Expression constructs for AHR1s and

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AHR2s were generated by use of the pENTR Directional TOPO entry vector kit (Invitrogen) and

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pcDNA 3.2/V5-DEST gateway vector kit (Invitrogen) according to methods described

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previously21,26 using gene-specific primers (Table S3).

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Luciferase Reporter Gene (LRG) Assay. Culture of COS-7 cells, transfection of constructs,

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and the luciferase reporter gene (LRG) assay were performed in 96-well plates according to

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methods described previously,21 with minor modifications.26 Amounts of expression constructs

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transfected into cells were 8 ng of AHR, 1.5 ng of white sturgeon ARNT2,26 20 ng of rat

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CYP1A1 reporter construct (pGudLuc 6.1),27,28 and 0.75 ng of Renilla luciferase vector

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(Promega). The total amount of DNA that was transfected into cells was kept constant at 50 ng

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by addition of salmon sperm DNA (Invitrogen). Transfected COS-7 cells were dosed with serial

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concentrations of TCDD ranging from 0.003 to 300 nM. TCDD (purity >98%) was acquired

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from Wellington Laboratories (Guelph, ON) and stock solutions were prepared in dimethyl

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sulfoxide (DMSO). Concentrations of TCDD were confirmed by high-resolution gas

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chromatography and mass spectrometry (GC-MS) according to Agilent methods 7890A and

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5975C, respectively. Luciferase was measured by use of a POLARstar OPTIMA microplate

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reader (BMG Labtech, New Orleans, LA). The LRG assay had previously been performed for

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AHRs from birds,21-23 red seabream,29 lake sturgeon,30 and zebrafish.31,32

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Concentration-response Curves and Statistical Analysis. All concentration-response curves

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for each AHR were obtained from three independent experiments, each with a different passage

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of cells, and each with four technical replicates per concentration of TCDD. Response curves,

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effect concentrations (ECs), and linear regressions were developed by use of GraphPad Prism 6

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software (San Diego, CA). Response curves were fit by use of a four-parameter logistic model.

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Lowest observed effect concentrations (LOECs) were defined as the least dose of TCDD that

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caused an effect that was statistically significant (p ≤ 0.05) from response of the DMSO control.

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Comparison of slopes and y-intercepts for linear regressions were performed by use of analysis

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of covariance (ANCOVA).

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Quantitative Adverse Outcome Pathway Development. Relationships between LD0, LD10,

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LD50, or LD100 and EC50 were developed based on data from birds and fishes for one PCDD, two

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PCDFs, and two coplanar PCBs from the published literature.4,33-38 All values used in

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development of the qAOP are provided (Table S4; Table S5). The LD0, LD10, LD50, and LD100

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were chosen because sufficient information for these points could be extracted from the

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published literature enabling robust linear regressions. Data was only used if the study reported

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exposure measurements and % mortality, performed statistical analysis, and had matching LRG

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data not involving mutant constructs. Data for LD0, LD10, and LD100 were only used for studies

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with greater than five doses. LD0 was defined as the greatest concentration where mortality is not

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statistically different from controls. LD10 was used if reported, otherwise was defined as the least

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dose where mortality was statistically different from controls. LD50 was only used if reported.

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LD100 was defined as the least dose where mortality was not statistically different from 100%.

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Predicted dose-response curves for early life stage mortality were validated against experimental



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dose-response curves from the published literature that reported exposure concentrations and %

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mortality.4,33-35,37,39-44 Control mortality in the experimental dose-response curves were

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normalized to 0% by use of GraphPad Prism 6 software. Predictions were evaluated against

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experimental results based on fold-difference (FD), mean absolute error (MAE), root mean

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square error (RMSE), and mean absolute percent error (MAPE).

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Results

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Identification of AHR1s and AHR2s of Fishes. Sequences of AHRs had not yet been identified

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for most fishes of known sensitivity of embryos to TCDD. A single AHR1 was identified in

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fathead minnow and two AHR1s (AHR1a and AHR1b) were identified in northern pike. Two

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AHR2s (AHR2a and AHR2b) were identified in lake trout, brook trout, and northern pike, while

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a single AHR2 was identified in fathead minnow and white sucker. Putative amino acid

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sequences for AHR2a of lake trout, brook trout, and northern pike clustered most closely with

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sequences for AHR2α and AHR2β of previously investigated salmonids, while sequences for

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AHR2b of lake trout, brook trout, and northern pike clustered most closely with sequences for

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AHR2δ and AHR2γ (Figure S2; Table S6).

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Activation of AHR1 and AHR2 of Fishes In Vitro. All AHR1s and AHR2s that were

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investigated here were activated in a concentration-dependent manner by exposure to TCDD

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(Figure S3; Figure S4; Table S7). There was no significant, linear relationship (R2 = 0.30; p =

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0.26) between EC50s for activation of AHR1 and the dose to cause 50% mortality (LD50) in early

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life stages of fishes (Figure 2A). A significant, linear relationship (R2 = 0.97; p = < 0.0001) was

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observed between EC50s for activation of AHR2s and LD50s in fishes (Figure 2B). AHR2b of


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lake trout, brook trout, and northern pike fit the linear relationship, while AHR2a did not (Figure

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2B).

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Development and Validation of a Quantitative Adverse Outcome Pathway. The slope and y-

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intercept for the linear relationship for AHR2s of fishes (Figure 2B; slope = 0.72; y-intercept = -

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2.8) is not statistically different (p = 0.99 and p = 0.82, respectively) from the slope and y-

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intercept for the linear relationship for AHR1s of birds (Figure 2C; slope = 0.71; y-intercept = -

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2.8). Since the slopes and y-intercepts were not different, cross-chemical, -species, and -taxa data

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were combined for four points on the dose-response curve. Statistically significant, linear

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relationships were observed between EC50s for activation of AHR1 of birds or AHR2 of fishes

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and LD0 (R2 = 0.85; p = < 0.0001), LD10 (R2 = 0.91; p = < 0.0001), LD50 (R2 = 0.85; p =

A cross-species quantitative adverse outcome ... - ACS Publications

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