Advertisement

Predicting the Ecotoxicological Effects of Transformation Products

  • Beate I. Escher
  • Rebekka Baumgartner
  • Judit Lienert
  • Kathrin Fenner
Chapter
Part of the The Handbook of Environmental Chemistry book series (HEC, volume 2P)

Abstract

Persistent environmental transformation products are increasingly being detected in surface waters and previous parts of this volume have discussed methods for prediction and quantification. However, there is not sufficient experimental data on their ecotoxicological potential to assess the risk associated with transformation products, even if their occurrence and abundance is known. Herein, we review computational methods for the identification and prioritization of transformation products according to their ecotoxicological potential and specifically focus on the assessment of mixtures of organic environmental pollutants and their transformation products. These transformation products can be produced through abiotic or microbial degradation or from metabolism in higher organisms. The proposed model assumes concentration addition between the components of the mixture and uses Quantitative Structure Activity Relationships (QSARs) to fill data gaps. The model is illustrated for five pesticides and their environmental transformation products. Their overall toxic potential is derived by scaling predicted relative aquatic concentrations (RAC, see Fenner et al., 2008, in this volume) with the relative potencies of each transformation product followed by summing up the toxic potentials of all mixture components. The model is versatile and can also be used to assess the cocktail of metabolites that is excreted by humans and animals after consumption/ingestion of pharmaceuticals. The metabolites of pharmaceuticals and hormones that are excreted are often more hydrophilic and consequently presumably less toxic than the ingested parent compound. However, they may be more abundant and therefore may be relevant for overall risk assessment. The weak point of our method, as of any QSAR application, is the correct assignment of the mode of toxic action (moa) of transformation products because they do not necessarily exhibit the same moa as the parent compound. In the future, more emphasis must therefore be placed on this issue, e.g., by identifying toxicophores or other structural alerts that are indicative of a certain mode of toxic action. An improved mode of action assignment would make the model more robust. Nevertheless, the prediction method is valuable for screening purposes and for setting priorities for further experimental testing.

Baseline toxicity Ecotoxicology Environmental transformation products Metabolites Mode of toxic action Pharmaceuticals Pesticides Herbicides QSAR 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Boxall ABA, Sinclair CJ, Fenner K, Kolpin D, Maud SJ (2004) When synthetic chemicals degrade in the environment. Environ Sci Technol 38:368A–375A CrossRefGoogle Scholar
  2. 2.
    Dewez D, Marchand M, Eullaffroy P, Popovic R (2002) Evaluation of the effects of diuron and its derivatives on Lemna gibba using a fluorescence toxicity index. Environ Toxicol 17:493–501 CrossRefGoogle Scholar
  3. 3.
    Liu WP, Gan JJ, Lee SJ, Werner I (2004) Isomer selectivity in aquatic toxicity and biodegradation of cypermethrin. J Agricultur Food Chem 52:6233–6238 CrossRefGoogle Scholar
  4. 4.
    Tixier C, Sancelme M, Bonnemoy F, Cuer A, Veschambre H (2001) Degradation products of a phenylurea herbicide, diuron: Synthesis, ecotoxicity, and biotransformation. Environ Toxicol Chem 20:1381–1389 CrossRefGoogle Scholar
  5. 5.
    Weyandt RG, Pressel J (2003) Strategies for detection of the ecotoxicological risks of degradation metabolites. Anal Bioanal Chem 375:188–189 Google Scholar
  6. 6.
    Belfroid AC, van Drunen M, Beek MA, Schrap SM, van Gestel CAM, van Hattum B (1998) Relative risks of transformation products of pesticides for aquatic ecosystems. Sci Total Environ 222:167–183 CrossRefGoogle Scholar
  7. 7.
    Sinclair CJ, Boxall ABA (2003) Assessing the ecotoxicity of pesticide transformation products. Environ Sci Technol 37:4617–4625 CrossRefGoogle Scholar
  8. 8.
    Lee JH, Landrum PF (2006) Development of a multi-component damage assessment model (MDAM) for time-dependent mixture toxicity with toxicokinetic interactions. Environ Sci Technol 40:1341–1349 CrossRefGoogle Scholar
  9. 9.
    Lee JH, Landrum PF (2006) Application of multi-component damage assessment model (MDAM) for the toxicity of metabolized PAH in Hyalella azteca. Environ Sci Technol 40:1350–1357 CrossRefGoogle Scholar
  10. 10.
    Legierse KCHM, Verhaar HJM, Vaes WHJ, De Bruijn JHM, Hermens JLM (1999) Analysis of the time-dependent acute aquatic toxicity of organophosphorus pesticides: The critical target occupation model. Environ Sci Technol 33:917–925 CrossRefGoogle Scholar
  11. 11.
    Escher BI, Bramaz N, Richter M, Lienert J (2006) Comparative ecotoxicological hazard assessment of beta-blockers and their human metabolites using a mode-of-action based test battery and a QSAR approach. Environ Sci Technol 40:7402–7408 CrossRefGoogle Scholar
  12. 12.
    Lienert J, Güdel K, Escher BI (2007) Screening method for ecotoxicological hazard assessment of 42 pharmaceuticals considering human metabolism and excretory routes. Environ Sci Technol 41:4471–4478 CrossRefGoogle Scholar
  13. 13.
    Fenner K, Kooijman C, Scheringer M, Hungerbuhler K (2002) Including transformation products into the risk assessment for chemicals: The case of nonylphenol ethoxylate usage in Switzerland. Environ Sci Technol 36:1147–1154 CrossRefGoogle Scholar
  14. 14.
    Villeneuve D, Blankenship A, Giesy J (2000) Derivation and application of relative potency estimates based on in-vitro bioassays. Environ Sci Toxicol 19:2835–2843 CrossRefGoogle Scholar
  15. 15.
    Altenburger R, Backhaus T, Boedeker W, Faust M, Scholze M, Grimme LH (2000) Predictability of the toxicity of multiple chemical mixtures to Vibrio Fischeri: mixtures composed of similarly acting chemicals. Environ Toxicol Chem 19:2341–2347 CrossRefGoogle Scholar
  16. 16.
    Backhaus T, Altenburger R, Boedeker W, Faust M, Scholze M, Grimme LH (2000) Predictability of the toxicity of multiple mixtures of dissimilarly acting chemicals to Vibrio Fischeri. Environ Toxicol Chem 19:2348–2356 CrossRefGoogle Scholar
  17. 17.
    Escher BI, Bramaz N, Eggen RIL, Richter M (2005) In-vitro assessment of modes of toxic action of pharmaceuticals in aquatic life. Environ Sci Technol 39:3090–3100 CrossRefGoogle Scholar
  18. 18.
    Altenburger R, Walter H, Grote M (2004) What contributes to the combined effect of a complex mixture? Environ Sci Technol 38:6353–6362 CrossRefGoogle Scholar
  19. 19.
    Junghans M, Backhaus T, Faust M, Scholze M, Grimme LH (2006) Application and validation of approaches for the predictive hazard assessment of realistic pesticide mixtures. Aqua Toxicol 76:93–110 CrossRefGoogle Scholar
  20. 20.
    McCarty LS, Hodson PV, Craig GR, Kaiser KLE (1985) The use of quantitative structure-activity relationships to predict the acute and chronic toxicities of organic chemicals to fish. Environ Tox Chem 4:595–606 CrossRefGoogle Scholar
  21. 21.
    Hermens JLM (1989) Quantitative structure-activity relationships of environmental pollutants. In The Handbook of Environmental Chemistry, Reaction and Processes; Hutzinger J (ed) Springer, Berlin, Germany, vol 2E, pp 111–162 Google Scholar
  22. 22.
    Hansch C, Leo A (1995) Exploring QSAR Fundamentals and Applications in Chemistry and Biology. Am Chem Soc, Washington, DC Google Scholar
  23. 23.
    van Wezel AP, Opperhuizen A (1995) Narcosis due to environmental pollutants in aquatic organisms: residue-based toxicity, mechanisms, and membrane burdens. Crit Rev Toxicol 25:255–279 CrossRefGoogle Scholar
  24. 24.
    Lipnick RL, Watson K, Strausz A (1987) A QSAR study of the acute toxicity of some industrial organic chemicals to goldfish. Narcosis, electrophile and proelectrophile mechanism. Xenobiotica 17:1011–1025 CrossRefGoogle Scholar
  25. 25.
    Verhaar HJM, Ramos EU, Hermens JLM (1996) Classifying environmental pollutants. 2: Separation of class 1 (baseline toxicity) and class 2 (polar narcosis) type compounds based on chemical descriptors. J Chemometrics 10:149–162 CrossRefGoogle Scholar
  26. 26.
    Maeder V, Escher BI, Scheringer M, Hungerbühler K (2004) Toxic ratio as an indicator of the intrinsic toxicity in the assessment of persistent, bioaccumulative, and toxic chemicals. Environ Sci Technol 38:3659–3666 CrossRefGoogle Scholar
  27. 27.
    Bradbury SP (1994) Predicting modes of toxic action from chemical structure. An overview. SAR and QSAR in Environ Res 2:89–104 CrossRefGoogle Scholar
  28. 28.
    Hermens JLM, Balaz S, Damborsky J, Karcher W, Müller M, Sabljic A, Sjöström M (1995) Assessment of QSARs for predicting fate and effects of chemicals in the environment: an international European project. SAR and QSAR Environ Res 3:223–236 CrossRefGoogle Scholar
  29. 29.
    Spycher S, Nendza M, Gasteiger J (2004) Comparison of different classification methods applied to a mode of toxic action data set. QSAR Comb Sci 23:779–791 CrossRefGoogle Scholar
  30. 30.
    von der Ohe PC, Kühne R, Ebert R-U, Altenburger R, Liess M, Schüürmann G (2005) Structural alerts- a new classification model to discriminate excess toxicity from narcotic effect levels of organic compounds in the acute daphnid assay. Chem Res Toxicol 18:536–555 CrossRefGoogle Scholar
  31. 31.
    European Commission Technical Guidance Document in Support of Commission Directive 93/67/EEC on Risk Assessment for New Notified Substances, Commission Regulation (EC) No 1488/94 on Risk Assessment for Existing Substances, and Directive 98/8/EC of the European Parliament and of the Council Concerning the Placing of Biocidal Products on the Market, Office for Official Publications of the European Communities, 2003. http://ecb.jrc.it/
  32. 32.
    Vaes WHM, Urrestarazu-Ramos E, Verhaar H, Hermens JLM (1998) Acute toxicity of nonpolar versus polar narcosis: is there a difference? Environ Toxicol Chem 17:1380–1384 CrossRefGoogle Scholar
  33. 33.
    Vaes WHJ, Urrestarazu-Ramos E, Hamwick C, van Holstein I, Blaauboer BJ, Seinen W, Verhaar HJM, Hermens JLM (1997) Solid phase microextraction as a tool to determine membrane/water partition coefficients and bioavailable concentrations in in-vitro systems. Chem Res Toxicol 10:1067–1072 CrossRefGoogle Scholar
  34. 34.
    Vaes WHJ, Urrestarazu-Ramos E, Verhaar HJM, Cramer CJ, Hermens JLM (1998) Understanding and estimating membrane/water partition coefficients: Approaches to derive quantitative structure property relationships. Chem Res Toxicol 11:847–854 CrossRefGoogle Scholar
  35. 35.
    Escher BI, Sigg L (2004) Chemical Speciation of Organics and of Metals at Biological Interfaces. In: Van Leeuwen HP, Köster W (eds) Physicochemical Kinetics and Transport at Biointerfaces. Wiley, Chichester, vol 9, pp 205–271 Google Scholar
  36. 36.
    Verhaar HJM, Mulder W, Hermens JLM (1995) QSARs for ecotoxicity, Report prepared within the framework of the project QSAR for Prediction of Fate and Effects of Chemicals in the Environment, an international project of the Environmental Technologies RTD Programme (DGXII/D-1) of the European Commission under Contract number EV5V-CT92_0211 Google Scholar
  37. 37.
    Van Leeuwen CJ, van der Zandt PTJ, Aldenberg T, Verhaar HJM, Hermens JLM (1992) Application of QSARs, extrapolation and equilibrium partitioning in aquatic effect assessment. 1. Narcotic industrial pollutants. Environmental Toxicology and Chemistry 11:267–282 CrossRefGoogle Scholar
  38. 38.
    Hilal SH, Karickhoff SW, Carreira LA (2005) University of Georgia, Athens, GA Google Scholar
  39. 39.
    USEPA Exposure Assessment Tools and Models, United States Environmental Protection Agency, 2005. http://www.epa.gov/oppt/exposure/docs/episuite.htm
  40. 40.
    Hansch C, Leo A, Hoekman D (1995) Exploring QSAR Hydrophobic, Electronic and Steric Constants; American Chemical Society: Washington, DC Google Scholar
  41. 41.
    Gasser L, Fenner K, Scheringer M (2007) Indicators for the exposure assessment of transformation products of organic micropollutants. Environ Sci Technol 41:2445–2451 CrossRefGoogle Scholar
  42. 42.
    Escher B, Schwarzenbach RP (2002) Mechanistic studies on baseline toxicity and uncoupling as a basis for modeling internal lethal concentrations in aquatic organisms. Aquat Sci 64:20–35 CrossRefGoogle Scholar
  43. 43.
    USEPA Reregistration Eligibility Decision for Diuron List A Case 0046, United States Environmental Protection Agency, Office of Prevention, Pesticides and Toxic Substances, 2003. http://www.epa.gov/REDs/diuron_red.pdf
  44. 44.
    USEPA ECOTOX Database, United States Environmental Protection Agency, 2006. http://www.epa.gov/ecotox/ecotox_home.htm
  45. 45.
    Fernández-Alba AR, Hernando MD, Piedra L, Chisti Y (2002) Toxicity evaluation of single and mixed antifouling biocides measured with acute toxicity bioassays. Analytica Chimica Acta 456:303–312 CrossRefGoogle Scholar
  46. 46.
    Urrestarazu-Ramos E, Vaal MA, Hermens JLM (2002) Interspecies sensitivity in the aquatic toxicity of aromatic amines. Environ Toxicol Pharmacol 11:149–158 CrossRefGoogle Scholar
  47. 47.
    Solomon KR, Baker DB, Richards RP, Dixon DR, Klaine SJ, LaPoint TW, Kendall RJ, Weisskopf CP, Giddings JM, Giesy JP, Hall LW, Williams WM (1996) Ecological risk assessment of atrazine in North American surface waters. Environ Toxicol Chem 15:31–74 CrossRefGoogle Scholar
  48. 48.
    Stratton GW (1984) Effects of the Herbicide Atrazine and its Degradation Products, Alone and in Combination, on Phototrophic Microorganisms. Arch Environ Contam Toxicol 13:35–42 CrossRefGoogle Scholar
  49. 49.
    Fairchild JF, Ruessler DS, Haverland PS, Carlson AR (1997) Comparative Sensitivity of Selenastrum capricornutum and Lemna minor to Sixteen Herbicides. Arch Environ Contam Toxicol 32:353–357 CrossRefGoogle Scholar
  50. 50.
    EuropeanCommission Bromoxynil SANCO/4347/2000 – final, 2004. http://europa.eu.int/comm/food/plant/protection/evaluation/existactive/list_bromoxynil.pdf
  51. 51.
    Escher BI, Hunziker RW, Schwarzenbach RP (2001) Interaction of phenolic uncouplers in binary mixtures: concentration-additive and synergistic effects. Environ Sci Technol 35:3905–3914 CrossRefGoogle Scholar
  52. 52.
    Peterson HG, Boutin C, Martin PA, Freemark KE, Ruecker NJ, Moody MJ (1994) Aquatic phyto-toxicity of 23 pesticides applied at Expected Environmental Concentrations. Aquatic Toxicol 28:275–292 CrossRefGoogle Scholar
  53. 53.
    EMEA Guideline on the Environmental Risk Assessment of Medicinal Products for Human Use CHMP/SWP/4447/00, The European Agency for the Evaluation of Medicinal Products, 2006. http://www.emea.eu.int/pdfs/human/swp/444700en.pdf
  54. 54.
    Crane M, Watts C, Boucard T (2006) Chronic aquatic environmental risks from exposure to human pharmaceuticals. Sci Tot Environ 367:23–41 CrossRefGoogle Scholar
  55. 55.
    Huschek G, Hansen PD (2006) Ecotoxicological classification of the Berlin river system using bioassays in respect to the European Water Framework Directive. Environmental Monitoring and Assessment 121:15–31 CrossRefGoogle Scholar
  56. 56.
    Joss A, Zabczynski S, Göbel A, Hoffmann B, Löffler D, McArdell CS, Ternes TA, Thomson A, Siegrist H (2006) Biological degradation of pharmaceuticals in municipal wastewater treatment: proposing a classification scheme. Water Research 40:1686–1696 CrossRefGoogle Scholar
  57. 57.
    Kolpin DW, Furlong ET, Meyer MT, Thurman EM, Zaugg SD (2002) Pharmaceuticals, hormones and other organic contaminants in U.S. streams, 1999–2000: a national reconnaissance. Environ Sci Technol 36:1201–1211 Google Scholar
  58. 58.
    Davies MN (1998) Clinical pharmacokinetics of ibuprofen. Clinical Pharmacokinetics 34:101–154 CrossRefGoogle Scholar
  59. 59.
    Dollery C, Boobis AR, Burley D, Davies DM, Davies DS, Harrison PI, Orme MLE, Park BK, Goldberg LI (eds) (1991) Therapeutic drugs; Churchill Livingstone, New York, NY Google Scholar
  60. 60.
    Baselt RC, Cravey RH (2000) Disposition of Toxic Drugs and Chemicals in Man; fourth edition ed, Chemical Toxicology Institute: Foster City, CA, USA Google Scholar
  61. 61.
    Avdeef A, Box KJ, Comer JEA, Hibbert C, Yam KY (1998) PH-metric log P10. Determination of liposomal membrane-water partition coefficients of ionizable drugs. Pharm Res 15:209–215 CrossRefGoogle Scholar
  62. 62.
    Cleuvers M (2003) Aquatic ecotoxicity of pharmaceuticals including the assessment of combination effects. Toxicol Lett 142:185–194 CrossRefGoogle Scholar
  63. 63.
    Hanisch B, Abbas B, Kratz W (2002) Ökotoxikologische Bewertung von Humanarzneimitteln in aquatischen Ökosystemen, Landesumweltamt Brandenburg Google Scholar
  64. 64.
    Ferrari B, Mons R, Vollat B, Fraysse B, Paxeus N, Lo Giudice R, Pollio A, Garric J (2004) Environmental risk assessment of six human pharmaceuticals: Are the current environmental risk assessment procedures sufficient for the protection of the aquatic environment? Environ Toxicol Chem 23:1344–1354 CrossRefGoogle Scholar
  65. 65.
    Saller R (1983) Praktische Pharmakologie. Eigenschaften gebräuchlicher Medikamente; Schattauer: Stuttgart, Germany Google Scholar
  66. 66.
    Brooks BW, Foran CM, Richards SM, Weston J, Turner PK, Stanley JK, Solomon KR, Slattery JK, LaPoint TW (2003) Aquatic Ecotoxicology of fluoxetine. Toxicol Lett 142:169–183 CrossRefGoogle Scholar
  67. 67.
    Christensen AM, Faaborg-Andersen S, Ingerslev F, Baun A (2007) Mixture and single-substance toxicity of selective serotonin reuptake inhibitors toward algae and crustaceans. Environ Toxicol Chem 26:85–91 CrossRefGoogle Scholar
  68. 68.
    Berzas Nevado JJ, Villasenor Llenera MJ, Guiberteau Cabanillas C, Rodriguez Robledo V (2006) Screening of citalopram, fluoxetine and their metabolites in human urine samples by gas-chromatography-mass spectrometry. A global robustness/ruggedness study. J Chromatogr A 1123:130–133 CrossRefGoogle Scholar
  69. 69.
    Traboulsie A, Chemin J, Kupfer E, Nargeot J, Lory P (2006) T-Type calcium channels are inhibited by fluoxetine and its metabolite norfluoxetine. Mol Pharmacol 69:1963–1968 CrossRefGoogle Scholar
  70. 70.
    de Vane CL (1999) Metabolism and pharmacokinetics of selective serotonin reuptake inhibitors. Cell Mol Neurobiol 19:443–466 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Beate I. Escher
    • 1
  • Rebekka Baumgartner
    • 1
    • 2
  • Judit Lienert
    • 1
  • Kathrin Fenner
    • 1
    • 2
  1. 1.Swiss Federal Institute of Aquatic Science and Technology (Eawag)DübendorfSwitzerland
  2. 2.Institute for Biogeochemistry and Pollutant DynamicsSwiss Federal Institute of Technology (ETH), ETH ZürichZürichSwitzerland

Personalised recommendations