L12 Effect-based Monitoring PDF

6/8/2021 L12 Effect-based monitoring Timo Hamers Set-up  Biomarker Definition, types, advantages, shortcomings  Biomarker examples (in vivo) Biotransformation enzymes, reproductive and endocrine parameters, neuromus...

6/8/2021 L12 Effect-based monitoring Timo Hamers Set-up  Biomarker Definition, types, advantages, shortcomings  Biomarker examples (in vivo) Biotransformation enzymes, reproductive and endocrine parameters, neuromuscular parameters  Toxicity Profiling of complex environmental mixtures with bioassays (in vitro) Hazard profiling Risk assessment (“so what?”) Effect directed analysis (EDA) (see L13) 2 1  6/8/2021 Biomarker definition  Any biological response to an environmental chemical at the individual level or below demonstrating a departure from the normal status  Individual level or below Biochemical, physiological, histological, morphological, behavior  Normal status What is normal? Depends on species, life stage, temperature, salinity, … Walker et al. 2004 3 Application of biomarkers  Environmental monitoring To monitor environmental quality To control effectiveness of policy measures  Ad hoc measurements Potentially contaminated sites 5 2  6/8/2021 Types of biomarkers  Biomarkers of exposure Indicate exposure to chemicals No information on the degree of adverse effect caused by the biomarker response  Biomarkers of (toxic) effect Demonstrate (the onset of) an adverse effect 6 Biomarkers are considered as...  early warning responses, i.e. as predictors for relevant effects at higher exposure levels (dose or time) Canary in a coal mine 7 3  6/8/2021 Position of biomarkers in cause-effect chain Early External Internal warning Adverse exposure exposure effects effects 9 Biomarkers can be measured  In situ Feral or caged organisms exposed in the field  Ex situ Laboratory animals exposed to environmental samples  Invasively Destructive: Liver, brain, gonads,... Non-destructive: blood, fat,...  Non-invasively Hair, urine, saliva, semen,...  In vivo  In vitro 10 4  6/8/2021 Biomarker measurements In situ Ex situ (bioassay) In vivo Feral vs caged animals Laboratory animals Feral vs introduced plants Cultured plants Local algae and bacteria Cultured algae, bacteria Destructive vs non-destructive In vitro Tissue-based bioassays Cell-based bioassays Protein-based bioassays 11 Online monitoring – Mussel monitor Length and frequency of opening and closures of the valves 1. Avoidance Closure for longer time 2. Decreased distance between valves 3. Rinsing Increased opening-closing activity 4. Death Constant gaping 12 5  6/8/2021 Advantages of biomarkers  Integrated measurement of exposure (in space and time)  Provides indication of bioavailability  Provides some indication of potential risk  May provide some indication of route of exposure  Can be applied to organisms exposed in nature (not artificial) 15 Challenges in biomarker use and interpretation  Specificity vs. non-specificity of biomarker response  Effect of confounding factors (e.g. temperature, soil moisture, reproductive cycle, life stage, etc.)  Statistical vs. ecological relevance of measured response (what is normal level of response?)  Meaning of biomarker response for higher levels of biological organization (individual, population, community) 16 6  6/8/2021 General vs specific biomarkers - Pollutants  General response to stress  Indicative for specific mode of action 17 General vs specific biomarkers – Adverse effects  Induction of stress proteins  Inhibition of acetylcholinesterase + ACh + AChE + Inhibitor + AChE 18 7  6/8/2021 General effects 13 stress proteins 12 metallothionein 11 VTG induction 10 porphyrin 9 serum proteins 8 DNA adducts 7 immune response 6 vitamin A 5 CYP induction Specific adverse effect 4 clotting proteins 3 ALAD 2 AChE inhibition 1 eggshell thinning 0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 Specific pollutants Many pollutants 19 Set-up  Biomarker Definition, types, advantages, shortcomings  Biomarker examples (in vivo) Biotransformation enzymes, reproductive and endocrine parameters, neuromuscular parameters  Toxicity Profiling of complex environmental mixtures with bioassays (in vitro) Hazard profiling Risk assessment (“so what?”) Effect directed analysis (EDA) (see L13) 20 8  6/8/2021 Main categories of biomarkers  Biotransformation enzymes  Biotransformation products  Oxidative stress  Stress proteins  Haematological parameters  Immunological parameters  Reproductive and endocrine parameters  Neuromuscular parameters  Genotoxic parameters  Physiological and morphological parameters Van der Oost et al. 2003 21 Biotransformation enzymes  Many xenobiotics induce their own biotransformation cell nucleus UGT-gene Ah-receptor CYP450-gene UGT-mRNA PHAHs CYP450-mRNA dioxins PAHs CYP450 UGT OH O-Gluc OH OH O-Gluc OH O-Gluc OH 23 9  6/8/2021 EROD and PROD activity as biomarker for CYP induction Non-dioxinlike PCBs PBDEs CAR-receptor CYP2B-gene Ah-receptor CYP1A-gene CYP2B-mRNA Dioxinlike CYP1A-mRNA compounds PAHs CYP1A CYP2B N N N O O O HO O O O O O Ethoxyresorufin-O-deethylase Pentoxyresorufin-O-deethylase (EROD) (PROD) 24 Flooding effects on small mammals in Biesbosch area LH PO Hamers et al.2006 25 10  6/8/2021 EROD activity in small mammals from Biesbosch area 400 LH Hamers et al.2006 350 PO 300 * pmol RR/mg /min 250 200 150 100 50 0 S. araneus C. glareolus 26 Main categories of biomarkers  Biotransformation enzymes  Biotransformation products  Oxidative stress  Stress proteins  Haematological parameters  Immunological parameters  Reproductive and endocrine parameters  Neuromuscular parameters  Genotoxic parameters  Physiological and morphological parameters Van der Oost et al. 2003 27 11  6/8/2021 Intersex in Roach oc sd po t po t 28 Sexual disruption (intersex) in wild fish populations (UK) A BC D E F GH I J F G H I J KLM Jobling et al. 1998 29 12  6/8/2021 Signal transduction pathway for steroid hormones OH Steroids, e.g. estrogens 17ß-estradiol CELL OH HO NUCLEUS 17ß-ethynyl-estradiol ERE gene Binding to HO Receptors mRNA bisphenol-A HO OH 4-nonylphenol OH Protein O O di(2-ethylhexyl)phthalate O O Feminizing effects 30 Vitellogenin production 31 13  6/8/2021 Vitellogenin (VTG)  Glyco-lipo-protein  Egg-yolk precursor protein  Expressed in female fish, but dormant in male fish 32 Relationship between VTG biomarker and intersex Jobling et al. 1998 33 14  6/8/2021 Main categories of biomarkers  Biotransformation enzymes  Biotransformation products  Oxidative stress  Stress proteins  Haematological parameters  Immunological parameters  Reproductive and endocrine parameters  Neuromuscular parameters  Genotoxic parameters  Physiological and morphological parameters Van der Oost et al. 2003 38 Organophosphorus insecticides 39 15  6/8/2021 Principle of acetylcholinesterase inhibitors neurotransmission acetylcholine acetylcholinesterase (ACh) (AChE) neuron 1 neuron 2 + ACh + AChE + Inhibitor + AChE 40 Measuring AChE activity as a biomarker + +DTNB ATCh + AChE A + TCh + AChE disulfide + TNB O O + N + AChE N + + AChE S OH + HS acetylthiocholine acetate thiocholine HOOC COOH + O2N S S NO2 HOOC DTNB O2N S COOH S + + N HS NO2 disulfide TNB Ellman et al. 1961 41 16  6/8/2021 Example: field monitoring in brown trout reference urban urban urban urban reference AChE EROD Payne et al. 1996 42 Example: swimming behavior of rainbow trout diazinon malathion 24h exposure 96h esposure Beauvais et al. 2000 96h exposure + 48h recovery 43 17  6/8/2021 Set-up  Biomarker Definition, types, advantages, shortcomings  Biomarker examples (in vivo) Biotransformation enzymes, reproductive and endocrine parameters, neuromuscular parameters  Toxicity Profiling of complex environmental mixtures with bioassays (in vitro) Hazard profiling Risk assessment (“so what?”) Effect directed analysis (EDA) (see L13) 52 Biomarker measurements In situ Ex situ (bioassay) In vivo Feral vs caged animals Laboratory animals Feral vs introduced plants Cultured plants Local algae and bacteria Cultured algae, bacteria Destructive vs non-destructive In vitro Tissue-based bioassays Cell-based bioassays Protein-based bioassays 53 18  6/8/2021 In vitro bioassays  Potency to affect many described biomarkers can be determined in vitro as well  Test (extract from) environmental sample for: EROD inducing potency in primary hepatocytes or liver cell line PROD inducing potency in primary hepatocytes VTG inducing potency in primary hepatocytes AChE-inhibting potency with isolated AChE Etc,… 54 For example: In vitro EROD activity Ah-receptor CYP1A-gene Dioxinlike CYP1A-mRNA compounds PAHs CYP1A N N O O O HO O O Ethoxyresorufin-O-deethylase (EROD) 55 19  6/8/2021 Alternative in vitro bioassay: DR LUC reporter gene assay luciferase-gene Ah-receptor CYP1A-gene luciferase-mRNA Dioxinlike CYP1A-mRNA compounds CYP1A luciferase Luciferin 56 Biosensors Cells or tissues (often genetically modified), which respond specifically to certain toxicant (e.g. to dioxins, estrogens, mutagens) 57 57 20  6/8/2021 Similarly: ER-LUC reporter gene assay (xeno-)estrogen CELL NUCLEUS ERE gene Estrogen Receptors mRNA pERE-tata-Luc Luciferase Protein Legler et al. 1999 58 Set-up  Biomarker Definition, types, advantages, shortcomings  Biomarker examples (in vivo) Biotransformation enzymes, reproductive and endocrine parameters, neuromuscular parameters  Toxicity Profiling of complex environmental mixtures with bioassays (in vitro) Hazard profiling Risk assessment (“so what?”) Effect directed analysis (EDA) (see L13) 62 21  6/8/2021 Toxicity profiling of environmental samples 30 25 Relative Light Units (RLUs) 20 15 11.6 10 5 0 0.1 1 8.310 100 1000 Concentration E2 (pM) 63 Toxicity Profiling in Sediments from Dutch Delta Hamers et al. 2010 based on Houtman et al. 2004 64 22  6/8/2021 Toxicity profiling of complex mixtures Hamers et al. 2010 65 Toxicity Profiling in Sediments from Dutch Delta EDA Hamers et al. 2010 See L13 on Effect-Directed Analysis 66 23  6/8/2021 ER-LUC reporter gene assay: so what? (xeno-)estrogen CELL NUCLEUS ERE gene Estrogen Receptors mRNA pERE-tata-Luc Luciferase Protein Legler et al. 1999 71 Linking biomarkers from in vitro to in vivo Exposure in transgenic zebrafish assay 125 In vitro ER-CALUX a Luciferase Activity ER-CALUX (%) E2 (xeno-)estrogens 100 fate in aquarium E1 75 EE2 BPA bioavailability 50 NP 25 DEHP 0 0.001 0.01 0.1 1 10 100 1000 10000 nominal concentration (nM) toxicokinetics In vivo transgenic zebrafish Luciferase Activity Transgenic Zebrafish (%) 125 b E2 (xeno-)estrogens TARGET CELL 100 E1 NUCLEUS 75 EE2 ERE gene BPA 50 Estrogen Receptors NP Exposure in pERE-tata-Luc mRNA 25 DEHP ER-CALUX assay 0 0.001 0.01 0.1 1 10 100 1000 10000 Luciferase Protein nominal concentration (nM) Legler 72 et al. 2000, 2002, 2005 72 24  6/8/2021 Endocrine parameters: luciferase expression 350 Luciferase induction 300 250 Onset of gonad differentiation 200 150 100 50 0 1 dpf 7 dpf 14 dpf 21 dpf 28 dpf 35 dpf Legler et al. 2000 73 Endocrine parameters: reproductive fitness 120 Copies vtg-1 (x 10 million) Total no. Eggs per clutch Fertilization (%) 80 Luciferase Induction control Exposure clutchs avg (std) avg (std) 40 E2 0.1 1.00 E2 10 0.75 NP 500 Control 13 103 (18) 78 (24) 0.50 E2 0.1 nM 10 121 (24) 85 (6) 0.25 0.00 E2 10 nM 8 80 (24) 46 (26) luciferase vitellogenin NP 500 nM 11 89 (27) 48 (19)  Male fish  3-week exposure during gonad development (3-6 weeks of age)  Luciferase and vitellogenin measured after exposure  Reproductive fitness measured for males further reared to adulthood Legler et al. 2005 74 25  6/8/2021 Effect EE2 on fathead minnow population EE2 5 ng/l (=0.02 nM), during summer season Kidd et al. 2007 75 Linking biomarkers from in vitro to in vivo  Compare in vitro and in vivo estrogenic potencies  Identify critical life-stages  Identify critical tissues  Link biomarkers to effects on reproductive fitness  Derive environmental threshold values (“effect-based trigger values”) 76 26  6/8/2021 Effect-based trigger (EBT) values  EBT: Bioassay response where no adverse effects are to be expected (“safe bioassay response”)  Estrogenicity Best studied example Based on in vitro-in vivo extrapolation  Other modes of action Different strategies required Starting points: > TDI reference compound with worst case kinetic assumptions > EQS reference compound > Field observations 77 Effect-based trigger values for human health Brand et al. 2013 78 27  6/8/2021 Effect-based trigger values for the environment Escher et al. 2018 79 Effect-based trigger values for the environment Van der Oost et al. 2017 80 28  6/8/2021 Toxicity profiling: A screening tool to get GRIP on complex mixtures Group locations with similar hazard profiles Rank locations based on “distance” to effect-based trigger value (EBT) Identify Important modes of action Responsible compounds (EDA) Prioritize Hot Spots Compounds of interest 81 81 Learning goals: After this lecture, you…  Know what a biomarker is Definition, types, advantages, shortcomings  Understand biomarker examples (in vivo/in vitro) Biotransformation enzymes, reproductive and endocrine parameters, neuromuscular parameters, genotoxic parameters  Understand Toxicity Profiling of complex environmental mixtures using bioassays Hazard profiling Risk assessment (“so what?”) Effect directed analysis (EDA) (see L13) 83 29