January 17, 2010 0

Gary AnkleyUSEPA, Duluth, MN

Emerging Contaminants and Protection of Aquatic Life: Prioritization and Identification

1/17/2010 1

There are known knowns. These are things we know that we know. There are known unknowns. That is to say, there are things that we know we don't know. But there are also unknown unknowns. There are things we don't know we don't know.

Donald Rumsfeld

1/17/2010 2

Assessing Risks of Contaminants of Concern

• Known knowns: “Conventional” pollutants, e.g., pesticides, PCBs, PAHs, metals, etc.– Know how to measure them and have the data to assess risk– Require effective exposure monitoring

• Known unknowns: PBDEs, PPCPs (including some EDCs), nanomaterials– Suspect or know (increasingly) they are present, but don’t have data to

assess risk– Require prospective assessments

• Unknown unknowns: ???– Chemicals we either can’t or don’t know to measure—could include

mixtures—but may be causing effects– Require retrospective (or diagnostic) assessments

1/17/2010 3

Contaminants of Emerging Concern• Known unknowns (prospective)

– Daunting “laundry lists” of chemicals for which little/no data exist– Need to identify those substances of most concern and acquire data

required to assess risk– Reliance only on fate/exposure (production volume, persistence,

residues) to identify these chemicals problematic– Requires ability to estimate possible effects without extensive testing

• Unknown unknowns (retrospective)– Adverse effects inferred either from field observations or controlled

testing of field samples (including in situ studies)– Effects generally associated with complex mixture of stressors– Requires ability to associate (chemical) stressors with observed

response(s)

Conventional toxicology approaches alone not well suited to meeting these challenges

1/17/2010 4

Conventional Approach to Toxicology

• Empirical emphasis focused on whole animal testing• “Apical” endpoints

– Survival, development/growth, reproduction, cancer• Dose Observe

– Adverse effects assessed without necessarily understanding how or why they occur

• Test all possible outcomes to determine which are relevant

http://images.google.com/imgres?imgurl=http://www.all-creatures.org/saen/rat-01a.jpg&imgrefurl=http://www.all-creatures.org/wlalw/fact-product.html&usg=__qp9Q22PdWOZNEbVjk7Vw0l1SgwE=&h=492&w=520&sz=20&hl=en&start=1&tbnid=Ho6MDoOsj6OfjM:&tbnh=124&tbnw=131&prev=/images%3Fq%3DToxicity%2Btesting%26gbv%3D2%26hl%3Denhttp://images.google.com/imgres?imgurl=http://www.nrcan-rncan.gc.ca/mms/canmet-mtb/mmsl-lmsm/enviro/metals/images/gallery/images/composite.jpg&imgrefurl=http://www.nrcan-rncan.gc.ca/mms/canmet-mtb/mmsl-lmsm/enviro/metals/images/gallery/pages/composite-e.htm&usg=__H1yJwuQFVNW7Ro7vx5FxD5sA_bs=&h=363&w=359&sz=15&hl=en&start=10&tbnid=Co760veVIlQknM:&tbnh=121&tbnw=120&prev=/images%3Fq%3DToxicity%2Btesting%26gbv%3D2%26hl%3Den

1/17/2010 5

Traditional Approach to Toxicology

Problems:

1. Costs of testing (money, time, animals)

• Example: pesticide registration – total costs around $50 M

• Example: EDSP – Tier 1 $200-400K, Tier 2 $1.25 M, 600-1200 animals

2. Tens of thousands of chemicals to evaluate

3. Species extrapolation challenges (25,000-30,000 species of fish alone)

4. Difficult to address environmental mixtures

1/17/2010 6

http://search.barnesandnoble.com/booksearch/imageviewer.asp?ean=9780309109925&z=y

1/17/2010 7

Predictive Toxicology

• Transparent

• Reasonable and quantifiable uncertainty• Optimal use of available resources and data

• Grounded in established and verifiable theory

• The science of making predictions of toxicity outcomes based on previously untested relationships (Ramos et al. 2007)

• Identify organizing principles that underlie biological response to chemicals

•Use that knowledge in a systematic fashion to predict, based on physical/chemical properties, a priori knowledge, and/or simplified bioassays, the likelihood that a given chemical will elicit an adverse effect or that an observed response might be associated with a given chemical

http://images.google.com/imgres?imgurl=http://static.twoday.net/bmworacleracing/images/crystal_ball2_bmwPreview.jpg&imgrefurl=http://openeuropeblog.blogspot.com/2008_07_01_archive.html&usg=__SnNCbPTRFAAMjZ5GI167TX8AsMc=&h=263&w=400&sz=22&hl=en&start=2&tbnid=uEWQyKoCpJUnGM:&tbnh=82&tbnw=124&prev=/images%3Fq%3DCrystal%2Bball%26gbv%3D2%26hl%3Den

1/17/2010 8

Predictive/Mechanistic Toxicology inEcological Risk Assessments

• Prioritization (P)– Depending on degree of allowable uncertainty, could be used to

eliminate chemicals from testing

• Focus testing (P)– Species, endpoints, experimental design

• Cross-species/chemical extrapolations (P,R)

• Exposure analysis/reconstruction (R)– Critical for non-persistent chemicals

• Support diagnostic approaches to ascertain chemicals (or chemical classes) responsible for observed effects (R)

1/17/2010 9

Challenges in the Application of MechanisticToxicology to Ecological Risk Assessment

• Many of the “tools” require specialized training/facilities– Histological analyses– In vitro (tissue, cell) assays– Alterations in gene/protein/metabolite expression or abundance

• Complex data analysis– Bioinformatic challenges can be substantial (e.g., “omics”)– Confusing or contradictory information (e.g., due to lack of

baseline knowledge)

• Translation of information into endpoints meaningful to risk assessment not always apparent– Both a science and communication issue

1/17/2010 10

10

In Press:Environmental Toxicology and Chemistry

Adverse Outcome Pathways: A Conceptual Framework to Support

Ecotoxicology Research and Risk Assessment.

Gerald T. Ankley, Richard S. Bennett, Russell J. Erickson, Dale J. Hoff, Michael W. Hornung, Rodney D. Johnson, David R. Mount,

John W. Nichols, Christine L. Russom, Patricia K. Schmieder, Jose A. Serrano, Joseph E. Tietge, Daniel L. Villeneuve

http:// www3.interscience.wiley.com / journal / 122596462 / issue

1/17/2010 11

Adverse Outcome Pathway

11

Definition:

Adverse Outcome Pathway (AOP):

a conceptual framework that portrays existing knowledge

concerning the linkage between a direct molecular initiating event

and an adverse outcome, at a level of biological organization

relevant to risk assessment

Builds on the “toxicity pathway” concept described by NRC (2007)

Designed for the translation of mechanistic information into endpoints meaningful to ecological risk

1/17/2010 12

12

ChemicalProperties

Receptor/LigandInteraction

DNA BindingProtein Oxidation

Gene Activation

Protein Production

Altered SignalingProtein

Depletion

Altered PhysiologyDisrupted

HomeostasisAltered Tissue Developmentor Function

LethalityImpaired

DevelopmentImpaired

ReproductionCancer

Toxicant

Macro-Molecular

InteractionsCellular

ResponsesOrgan

ResponsesOrganism

Responses

Structure

Recruitment

Extinction

PopulationResponses

Toxicity Pathway

Adverse Outcome Pathway

“Cellular response pathways that when sufficiently perturbed are expected to result in adverse health effects”Toxicity Testing in 21st Century, NRC 2007.

1/17/2010 13

AOP Examples (Ankley et al. in press)

13

Narcosis

Photo-Activated Toxicity

AhR Mediated Toxicity

Estrogen Receptor Activation

Impaired Vitellogenesis

1/17/2010 14

ChemicalPropertyProfile

Receptor/LigandInteraction

DNA BindingProtein

Oxidation

Gene ActivationProtein

ProductionAltered SignalingProtein Depletion

Altered PhysiologyDisrupted

HomeostasisAltered Tissue Developmentor Function

LethalityImpaired

DevelopmentImpaired

ReproductionCancer

Toxicant Macro-MolecularInteractionsCellular

ResponsesOrgan

ResponsesIndividual

Responses

Structure

Recruitment

Extinction

PopulationResponses

Adverse Outcome Pathway

CN

NN

Aromataseinhibition

8

0

2

4

6

E2 (n

g/m

l)

*

*

0

10

20

Vtg

(mg/

ml)

*

* *Control 2 10 50

Fadrozole (µg/l)

8

0

2

4

6

E2 (n

g/m

l)

*

*

0

10

20

Vtg

(mg/

ml)

*

* *Control 2 10 50

Fadrozole (µg/l)

-20 -18 -16-14-12 -10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16 18 20Exposure (d)

0

2

4

6

8

10

(Tho

usan

ds)

Cum

ulat

ive

Num

ber o

f Egg

s

Control21050

Fadrozole (ug/L)

***

-20 -18 -16-14-12 -10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16 18 20Exposure (d)

0

2

4

6

8

10

(Tho

usan

ds)

Cum

ulat

ive

Num

ber o

f Egg

s

Control21050

Fadrozole (ug/L)

***

Reduced E2, Vtg synthesis

Impaired vitellogenesis Reduced fecundity

Example of an AOP in fathead minnows exposed to an aromatase inhibitor

1/17/2010 15

e.g. FadrozoleProchloraz Inhibition

Substrate

Antagonism

Agonism

EstrogenReceptor

Reduced Vtgproduction

Hepatocyte

Impaired oocytedevelopment

Ovary

Impairedovulation

& spawning

Female

Decliningtrajectory

Population

AromataseEnzyme

Agonism

AndrogenReceptor

Reduced LH/FSHsynthesis/release

GnRH neurons/ Gonadotrophs

( E2)

ReducedE2 synthesis

GranulosaCell

ReducedT synthesis

e.g.

* Fenarimol

ERantagonist

( T)

Aromataseinhibitor

e.g.17ß-Trenbolone

AR agonist

Predictive Model Linkage Based on Vtg Down-Regulation

(A)

(B)

(C)

Toxicant Macro-MolecularInteractionsCellular

ResponsesOrgan

ResponsesIndividual

ResponsesPopulationResponses

Adverse Outcome Pathway

Multiple AOPs converging at common insult of impaired vitellogenesis

1/17/2010 16

Insights from the Impaired Vitellogenesis AOP

• Prospective Assessments (prioritizing)– Support endpoint selection for short-term in vivo screens (VTG in

females)– Focus in vitro assay and QSAR model development (inhibition of

aromatase, ER antagonism, AR activation)

• Retrospective Assessments (diagnosing)– Identification of classes of causative chemical stressors (e.g.,

inhibitors of steroidogenesis)– Interpretation of biomarker data (sex steroids, VTG) relative to

possible population responses

1/17/2010 17

Mechanistic Toxicology Approaches in Prospective Ecological Assessments

• Prioritization/extrapolation based on existing knowledge– Use of high-quality, searchable sources of ecotoxicology data– Consideration of data from human health-oriented studies

• Evaluation of biological targets, pathway conservation and potency (e.g., pharmaceuticals)

• Pathway-specific computational models to predict effects

• Prioritization/extrapolation based on pathway identification for untested chemicals– Short-term in vivo and in vitro assays– Responses reflective of specific pathways

1/17/2010 18

ECOTOX: A Freely Available Data Resourcehttp://cfpub.epa.gov/ecotox/

1/17/2010 19

In ECOTOX’s Advanced Database Query one can access independently compiled data sets

ECOTOX has been addingdata fields quarterly (12/09)

1/17/2010 20

Pharmaceuticals in the Environment (PiE)

• PiEs considered CECs for several reasons– Increasingly detected in drinking and surface waters– Potentially 1000s of parent compounds and metabolites– High public visibility (human health)– Potential risk to fish/wildlife populations (EE2, diclofenac)

• May not be highly persistent in conventional sense– Pseudo-persistence significant issue

• Often target conserved pathways

• Tend not to be acutely toxic but can be extremely potent – Fish ACRs (acute-to-chronic ratio) >1000

• Little useful exposure/effects data for directly assessing ecological risk

1/17/2010 21

Prioritizing PiEs for Assessment and Monitoring

• Valuable data exist for many drugs collected as part of development/ human health safety testing (e.g., www.drugbank.ca)– Basic physico-chemical properties– Major degradates and metabolites– Biological targets/pathways (primary & side effects)– Potency

• Considered in a systematic manner, this information can provide an basis for a screening-level assessment of risk

SETAC Pellston reports on human and veterinary drugs (2005; 2008)

Draft CENR report “Pharmaceuticals in the Environment: An Interagency Research Strategy” (2009)

1/17/2010 22

Prioritizing PiEs for Potential Ecological Risk

• Which occur (or likely could occur) in the environment?– Empirical data (e.g., Benotti et al.; Wu et al.; Ramirez et al.) or

estimates from stability, Kow, etc.

• Is there knowledge of stable and/or biologically-active degradates/metabolites?

• Are the known biological targets/pathways directly relevant to processes controlling populations?– Survival, growth/development, reproduction

• What is the degree of conservation of pathways across species?

• How potent are the chemicals?

1/17/2010Published in: Lina Gunnarsson; Alexandra Jauhiainen; Erik Kristiansson; Olle Nerman; D. G. Joakim Larsson; Environ. Sci. Technol. 2008, 42, 5807-5813.DOI: 10.1021/es8005173Copyright © 2008 American Chemical Society

Conservation of Drug Targets Across Species

1/17/2010 24

Computational Models for PredictingEffects: Narcosis Example

24

Narcosis is “non-specific toxicity resulting from weak and reversible hydrophobic interactions” (Overton, 1901)

Baseline toxicity: if a chemical does not produce toxicity by some more specific mechanism it will act by narcosis, providing it issufficiently soluble in water at high enough concentrations to achieve required chemical activity

Narcosis is theorized to result from hydrophobic interactions between chemicals and cellular membranes.

Estimated that 60% of industrial chemicals act via this pathway

1/17/2010 25

Narcosis – Baseline Toxicity

25

CellularMembranes

Changes in fluidity

/ transport

Non-polarNarcotics

NumerousChemicals

Neurons(Multiple)

? Respiration,Metabolic rate

CNS/ MultipleOrgan types

Equilibriumloss,

Mortality

Organism

Decliningtrajectory

Population? ?

Not all linkages are known with absolute certainty in this AOP

… but the relationship between chemical property and adverse outcome is well established

1/17/2010 26

26

Data from Russom et al. 1997. ET&C, 16, 948-967

-1

0

1

2

3

4

5

6

-2 -1 0 1 2 3 4 5 6 7

Log Kow

96-h

Log

LC5

0 (m

g/L)

Fathead Minnow 96-h Toxicity

1/17/2010 27

27

Log Kow 96 h LC50

CellularMembranes

Changes in fluidity

/ transport

Non-polarNarcotics

NumerousChemicals

Neurons(Multiple)

? Respiration,Metabolic rate

CNS/ MultipleOrgan types

Equilibriumloss,

Mortality

Organism

Decliningtrajectory

Population

? ?

Robust Predictive QSAR

1/17/2010 28

Identifying Pathways of Concernfor Untested Chemicals

• No empirical data for majority of chemicals in commerce

• Computational models helpful for predicting baseline toxicity, but not available for many “reactive” pathways

• Collection of focused biological data for previously untested chemicals and comparison to responses for tested chemicals one viable option – Suites of in vitro assays for well-defined pathways– Short-term in vivo assays for pathway “discovery” and/or

simultaneously monitoring multiple pathways (toxicogenomics)

1/17/2010 2929

ToxCast Background

• Coordinated through EPA/ORD National Center for Computational Toxicology• Phase 1 data publically available; Phase 2 ongoing

• Addresses chemical screening and prioritization needs for pesticidalinerts, anti-microbials, drinking water contaminants, HPVs, etc.

• Comprehensive use of HTS technologies to generate fingerprints and predictive signatures reflective of biological pathways of concern

• Oriented toward human health, but covers many conserved pathways

1/17/2010 30

ToxCast In vitro HTS Assays

• Cell lines– HepG2 human hepatoblastoma– A549 human lung carcinoma– HEK 293 human embryonic kidney

• Primary cells– Human endothelial cells– Human monocytes– Human keratinocytes– Human fibroblasts– Human proximal tubule kidney cells– Human small airway epithelial cells

• Biotransformation competent cells– Primary rat hepatocytes– Primary human hepatocytes

• Assay formats– Cytotoxicity– Reporter gene – Gene expression– Biomarker production– High-content imaging for cellular phenotype

• Protein families– GPCR– NR– Kinase– Phosphatase– Protease– Other enzyme– Ion channel– Transporter

• Assay formats– Radioligand binding– Enzyme activity– Co-activator recruitment

Cellular AssaysBiochemical Assays

467 Endpoints

1/17/2010 31

Phase I ToxCast309 Unique Chemicals

Chemical Class Distribution(≥5/Class)

• 276 Conventional Actives• 16 Antimicrobials• 9 Industrial Chemicals• 8 Metabolites

Organophosphorus (39)Amide (26)Urea (26)Conazole (18)Carbamate (16)Phenoxy (15)Pyrethroid (12)Pyridine (11)Triazine (9)Dicarboximide (8)Phthalate (7)

Dinitroaniline (7)Antibiotic (7)Thiocarbamate (7)Pyrazole (6)Nicotinoid (6)Dithiocarbamate (6)Aromatic Acid (6)Insect Growth Regulators (5)Imidazolinone (5)Unclassified (21)Other (93)

www.epa.gov/ncct/toxcast/

1/17/2010 32

• USEPA (NERL) – Cincinnati, OH• D. Bencic, M. Kostich, D. Lattier, J. Lazorchak, G. Toth, R.-L. Wang,

• USEPA (NHEERL)– Duluth, MN, and Grosse Isle, MI• G. Ankley, E Durhan, M Kahl, K Jensen, E Makynen, D. Martinovic,

D. Miller, D. Villeneuve• USEPA (NERL)– Athens, GA

• T. Collette, D. Ekman, M. Henderson, Q. Teng• USEPA-RTP, NC

• M.&M. Breen, R. Conolly (NCCT)• S. Edwards (NHEERL)

• USEPA (NCER) STAR Program• N. Denslow (Univ. of Florida), E. Orlando, (Florida Atlantic

University), K. Watanabe (Oregon Health Sciences Univ.), M. Sepulveda (Purdue Univ.)

• USACE – Vicksburg, MS• E. Perkins, N. Garcia-Reyero

• Other partners• UC-SB, J. Shoemaker, K. Gayen (Santa Barbara, CA)• Joint Genome Institute, DOE (Walnut Creek, CA)• Sandia, DOE (Albuquerque, NM)• Pacific Northwest National Laboratory (Richland, WA)

Linkage of Exposure and Effects Using Genomics, Linkage of Exposure and Effects Using Genomics, Proteomics, and Metabolomics in Small Fish Models Proteomics, and Metabolomics in Small Fish Models

1/17/2010 33

Zebrafish

1/17/2010 34

Fathead Minnows

1/17/2010 35

11βHSD

P45011β.

GnRHNeuronal System

GABA Dopamine

Brain

Gonadotroph

Pituitary

D1 R

D2 R

?

?

Y2 R

NPY

Y1 R

GnRH R

?

Activin

Inhibin

GABAAR

GABABR

Y2 R

D2 R

GnRH

Circulating Sex Steroids / Steroid Hormone Binding Globlulin

PACAP

Follistatin

Activin PAC1 R

Activin R

FSHβ LHβ

GPα

Circulating LH, FSH

FSH RLH R

Circulating LDL, HDL

LDL R

HDL R

Outer mitochondrial membrane

Inner mitochondrial membrane

StAR

P450scc

pregnenolone 3βHSD

P450c17

androstenedione

testosterone

Cholesterol

estradiol

Gonad(Generalized, gonadal,

steroidogenic cell)

Androgen / Estrogen Responsive Tissues

(e.g. liver, fatpad, gonads)ARER

3

4

5

6

Blood

Blood

Compartment

17βHSD

P450arom

11-ketotestosterone

progesterone17α-hydroxyprogesterone

17α,20β-P (MIS)

20βHSD

Fipronil (-)

Muscimol (+)

Apomorphine (+)

Haloperidol (-)

Trilostane (-)

Ketoconazole (-)

Fadrozole (-)

Prochloraz (-,-)

Vinclozolin (-)

Flutamide (-)

17β-Trenbolone (+)

17α-Ethynylestradiol(+)

7

8

9

10

11

12

2

1

Chemical ProbesChemical Probes

1/17/2010 36

Endpoints and Analysis

• Global (microarray) and focused (QPCR) gene expression changes

• Protein and metabolite profiles

• Apical effects: steroids, gonad histology, reproduction

• Linked physiological and population models in a systems biology framework to facilitate prediction of effects

1/17/2010 37

Prospective Assessment Application:Screening to detect different classes of EDCs

Small battery of molecular responses measured by real-time PCR array•Established linkage to impaired reproduction in fish & diagnostic utility

•Robust across species

•Short-term exposure duration (e.g., 4 d)

•Analyses amenable to HTS automation

•Design based on robust power analysis for all responses

CN

NN

1/17/2010 38

Mechanistic Toxicology Approachesin Retrospective Assessments

• In vitro assays with complex samples (water, sediment) from the field

• Short-term in vivo assays conducted with field samples in the lab or in situ (caged animals)

• Collection of organisms from extant populations

Molecular/biochemical/histological endpoints reflective of defined biological pathways

1/17/2010 39

Examples of Mechanistic Assays/Endpoints for Retrospective Assessment of EDCs

• Cell lines transfected with estrogen/androgen receptor-reporter (e.g., luciferase) gene constructs

• Measurement of changes in single gene/protein expression (e.g.,vitellogenin [VTG] in fish)

• Evaluation of changes in multiple gene, protein, metabolite expression profiles (i.e., transcriptomics, proteomics, metabolomics)

• Determination of histological abnormalities (e.g., testis-ova) in fish collected from the field

1/17/2010 40

VTG Induction as an Indicatorof Estrogen Exposure in Fish

Hours Post Treatment

1 10 100 5000

10

20

30

40

50

fmol

of V

TG m

RN

A/ug

Tot

al R

NA

mg

of V

TG/m

l Pla

sma

1 10 100 5000

6

12

18

24

30

1 10 100 5000

140

280

420

560

700

ng o

f E2/

ml P

lasm

a

a

b

c

1/17/2010 41

Considerations in Assay/Endpoint Selection:VTG Induction as a Case Example

• Ease/cost of measurement– Commercial PCR (mRNA) or ELISA (protein) kits

• Sensitivity, rapidity and persistence of response– Occurs w/i hours at ng/L estrogen concentrations and can

remain elevated long-term

• Specificity for pathway of concern– No chemicals other than estrogens induce VTG in males

• Linkage to biological impacts– Estrogens well established reproductive toxins in fish– Concentrations of EE2 (ca. 1 ng/L) that cause VTG induction

comparable to those reducing production of fertile eggs

1/17/2010 42

?

Impaired spawning behavior

Reducedfecundity

Altered “X-Y”gamete Ratio

Adult Fish

AOP: Estrogen Receptor Activation

Decliningtrajectory

Skewedsex ratio

Population

Increased VTG production

Hepatocyte

Sex reversalIntersex

Testes

IncreasedVTG in males

Liver-Blood

Impaireddevelopment & ovulation

Ovary

?

Gonadal Cells

Agonism

EstrogenReceptor

EE2,E2

ERAgonist

Feminizedphenotype

MultipleTissues

?

Feminizedphenotype

MultipleCell Types

?Brain

??Neurons

?

?

?

Established mechanistic linkage withquantitative or semi-quantitative data

Potential biomarker associated with exposure/response information

Plausible linkage with limited data Hypothetical linkage

KEY Predictive model linkages based on chemical structure/property and quantitative exposure-response data

Empirical linkage based on quantitativeexposure-response data

AOPs for putting Biomarkers in Context: VTG Induction and

Reproduction

1/17/2010 43

Establishing Causation: The Role of TIE• Retrospective assessments rely on observation of

biological responses to indicate potential impacts• Complex mixtures of chemical stressors are present• Toxicity identification evaluation (TIE) techniques

developed in late 80’s to identify toxicants causing lethality in WWTP effluents (NPDES)

• TIEs with mechanistic endpoints– Estrogenic WWTP effluent in UK (EE2)– Androgenic discharges from pulp/paper mills– Surface water associated with agriculture

1/17/2010 44Buckeye Plant, Fenhalloway River, FL

Mechanism-Based TIEs: A Pulp Mill Case Study

Collaborators: G. Ankley, L. Durhan (EPA, MED); E. Gray, P. Hartig, C. Lambright, L. Parks, V. Wilson (EPA, RTD); L. Guillette (Univ. Florida)

1/17/2010 45

FieldSample

Media made with Field Sample

1 2 3

CV-1 cellshAR

MMTV-luciferase

Cells Exposedto Field Sample

I.

II. Measure Luciferase Activity

CellCell--Based Assays for Based Assays for Detecting Detecting EDCsEDCs in Mixturesin Mixtures

1/17/2010 46

PME Androgenic Activity

Con

PME

1PM

E 2

PME

2Up

Fen

Econ

fina

DHT

0.0

0.5

1.0

1.5

Log1

0 Fo

ld in

duct

ion

over

Med

ia C

on

1/17/2010 47

Application of TIE Analysis to Androgenic PME

C18SPE

25% 75%50% 80% 90% 95% 100%85%

% Methanol / Water Elutions

PME

1/17/2010 48

0

1

2

3

4

5

6

7

DHT 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

HPLC Fraction Number

Andr

ogen

ic A

ctiv

ity

Media

Linking Androgenic Activity in Cellsto Fractionation of PME

Androstenedione

1/17/2010 49

Summary and Conclusions• Predictive/mechanistic toxicology tools have substantial

potential for assessing the ecological risk of CECs

• Prospective assessments– Efficient use of existing knowledge/concepts– Computational (QSAR/SAR) models– Pathway-based in vitro/in vivo bioassays

• Retrospective assessments– Pathway-based bioassays with field samples– Mechanistic endpoints in organisms from the field– Fractionation/TIE to address mixtures

Emerging Contaminants and Protection of Aquatic Life: Prioritization and IdentificationAssessing Risks of Contaminants of ConcernContaminants of Emerging ConcernConventional Approach to ToxicologyTraditional Approach to ToxicologyPredictive/Mechanistic Toxicology in�Ecological Risk Assessments Challenges in the Application of Mechanistic�Toxicology to Ecological Risk AssessmentAdverse Outcome Pathway AOP Examples (Ankley et al. in press) Insights from the Impaired Vitellogenesis AOPMechanistic Toxicology Approaches �in Prospective Ecological AssessmentsECOTOX: A Freely Available Data ResourcePharmaceuticals in the Environment (PiE)Prioritizing PiEs for Assessment and MonitoringPrioritizing PiEs for Potential �Ecological RiskComputational Models for Predicting�Effects: Narcosis ExampleNarcosis – Baseline Toxicity Robust Predictive QSAR�Identifying Pathways of Concern�for Untested Chemicals ToxCast BackgroundToxCast In vitro HTS AssaysZebrafishFathead MinnowsEndpoints and AnalysisMechanistic Toxicology Approaches�in Retrospective AssessmentsExamples of Mechanistic Assays/Endpoints for Retrospective Assessment of EDCsConsiderations in Assay/Endpoint Selection:�VTG Induction as a Case ExampleEstablishing Causation: The Role of TIEMechanism-Based TIEs: A Pulp Mill Case StudyPME Androgenic ActivityApplication of TIE Analysis to �Androgenic PME�Linking Androgenic Activity in Cells�to Fractionation of PMESummary and Conclusions