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Application of preparative capillary gas chromatography (pcGC), automated structure generation and mutagenicity prediction to improve effect-directed analysis of genotoxicants in a contaminated groundwater

  • Cornelia Meinert
  • Emma Schymanski
  • Eberhard Küster
  • Ralph Kühne
  • Gerrit Schüürmann
  • Werner Brack
Research Article

Abstract

Background, aim and scope

The importance of groundwater for human life cannot be overemphasised. Besides fulfilling essential ecological functions, it is a major source of drinking water. However, in the industrial area of Bitterfeld, it is contaminated with a multitude of harmful chemicals, including genotoxicants. Therefore, recently developed methodologies including preparative capillary gas chromatography (pcGC), MOLGEN-MS structure generation and mutagenicity prediction were applied within effect-directed analysis (EDA) to reduce sample complexity and to identify candidate mutagens in the samples. A major focus was put on the added value of these tools compared to conventional EDA combining reversed-phase liquid chromatography (RP-LC) followed by GC/MS analysis and MS library search.

Materials and methods

We combined genotoxicity testing with umuC and RP-LC with pcGC fractionation to isolate genotoxic compounds from a contaminated groundwater sample. Spectral library information from the NIST05 database was combined with a computer-based structure generation tool called MOLGEN-MS for structure elucidation of unknowns. Finally, we applied a computer model for mutagenicity prediction (ChemProp) to identify candidate mutagens and genotoxicants.

Results and discussion

A total of 62 components were tentatively identified in genotoxic fractions. Ten of these components were predicted to be potentially mutagenic, whilst 2,4,6-trichlorophenol, 2,4-dichloro-6-methylphenol and 4-chlorobenzoic acid were confirmed as genotoxicants.

Conclusions and perspectives

The results suggest pcGC as a high-resolution fractionation tool and MOLGEN-MS to improve structure elucidation, whilst mutagenicity prediction failed in our study to predict identified genotoxicants. Genotoxicity, mutagenicity and carcinogenicity caused by chemicals are complex processes, and prediction from chemical structure still appears to be quite difficult. Progress in this field would significantly support EDA and risk assessment of environmental mixtures.

Keywords

EDA MODELKEY Identification of unknowns QSAR UmuC 

Notes

Acknowledgements

This study was supported by the EU funded projects MODELKEY (contract no. 511237-GOCE) and OSIRIS (contract no. 037017). We thank Ms. Aulhorn for technical assistance.

Supplementary material

11356_2009_286_MOESM1_ESM.doc (348 kb)
ESMdoc (DOC 347 kb)

References

  1. ACD (2007) ACD/pk a DB, version 11.0. Advanced Chemistry Development, Toronto, CanadaGoogle Scholar
  2. Benecke C, Grüner T, Kerber A, Laue R, Wieland T (1997) Molecular structure generation with MOLGEN, new features and future developments. Fresenius’ J Anal Chem 359:23–32CrossRefGoogle Scholar
  3. Bobeldijk I, Brandt A, Wullings B, Noij ThHM (2001) High-performance liquid chromatography-ToxPrint: chromatographic analysis with a novel (geno)toxicity detection. J Chromatogr A 918:277–291CrossRefGoogle Scholar
  4. Brack W (2003) Effect-directed analysis: a promising tool for the identification of organic toxicants in complex mixtures. Anal Bioanal Chem 377:397–407CrossRefGoogle Scholar
  5. Brack W, Schmitt-Jansen M, Machala M, Brix R, Barceló D, Schymanski E, Streck G, Schulze T (2008) How to confirm identified toxicants in effect-directed analysis. Anal Bioanal Chem 390:1959–1973CrossRefGoogle Scholar
  6. Braga RS, Barone PMVB, Galvao DS (1999) Identifying carcinogenic activity of methylated polycyclic aromatic hydrocarbons (PAHs). J Mol Struc-Theochem 464:257–266CrossRefGoogle Scholar
  7. Castillo M, Barceló D (1999) Identification of polar toxicants in industrial wastewaters using toxicity-based fractionation with liquid chromatography/mass spectrometry. Anal Chem 71:3769–3776CrossRefGoogle Scholar
  8. Chemie AG B-W (1993) Bitterfelder Chronik. 100 Jahre Chemiestandort Bitterfeld-Wolfen. Vorstand der Chemie AG Bitterfeld-Wolfen, Bitterfeld-WolfenGoogle Scholar
  9. Coutois YA, Pesle ML, Festy B (1992) Activation of pro-mutagens in complex mixtures by rat liver S9 systems. Mutat Res 276:133–137Google Scholar
  10. Degirmenci E, Ono Y, Kawara O, Utsumi H (2000) Genotoxicity analysis and hazardousness priorization of a group of chemicals. Water Sci Technol 42:125–131Google Scholar
  11. De Maagd PGJ, Tonkes M (2000) Selection of genotoxicity tests for risk assessment of effluents. Environ Toxicol 15:81–90CrossRefGoogle Scholar
  12. Eglinton TI, Aluwihare LI, Bauer JE, Druffel ERM, McNichol AP (1996) Gas chromatographic isolation of individual compounds from complex matrices for radiocarbon dating. Anal Chem 68:904–912CrossRefGoogle Scholar
  13. Galassi S, Benfenati E (2000) Fractionation and toxicity evaluation of waste waters. J Chromatogr A 889:149–154CrossRefGoogle Scholar
  14. Hilal SH, Karickhoff SW, Carreira LA (1995) A rigorous test for SPARCs chemical reactivity models: estimations of more than 4300 ionisation pK a s. Quant Struc Act Rel 14:348–355CrossRefGoogle Scholar
  15. Hilal SH, Karickhoff SW, Carreira LA (2004) Prediction of the solubility, activity coefficient and liquid/liquid partition coefficient of organic compounds. QSAR Comb Sci 23:709–720CrossRefGoogle Scholar
  16. Holmstrand H, Mandalakis M, Zencak Z, Gustafsson O, Andersson P (2006) Chlorine isotope fractionation of a semi-volatile organochlorine compound during preparative megabore-column capillary gas chromatography. J Chromatogr A 1103:133–138CrossRefGoogle Scholar
  17. Imamura T, Talcott R (1985) Mutagenic and alkylating properties of organophosphorus impurities of commercial malathion. Mut Res 155:1–6CrossRefGoogle Scholar
  18. ISO/TC 147/SC5 (1999) Water quality-determination of genotoxicity of water and wastewater using the umu-test. International Organization for Standardization, GenevaGoogle Scholar
  19. Kazius J, McGuire R, Bursi R (2005) Derivation and validation of toxicophores for mutagenicity prediction. J Med Chem 48:312–320CrossRefGoogle Scholar
  20. Kerber A, Laue R, Meringer M, Varmuza K (2001) MOLGEN-MS: evaluation of low resolution electron impact mass spectra with MS classification and exhaustive structure generation. Adv Mass Spectrom 15:939–940Google Scholar
  21. Kerber A, Meringer M, Rucker C (2006) CASE via MS: ranking structure candidates by mass spectra. Croat Chem Acta 79:449–464Google Scholar
  22. Mandalakis M, Holmstrand H, Andersson P, Gustafsson Ö (2008) Compound-specific chlorine isotope analysis of polychlorinated biphenyls isolated from Aroclor and Clophen technical mixtures. Chemosphere 71:299–305CrossRefGoogle Scholar
  23. Meinert C, Brack W (2010) Optimisation of trapping parameters in preparative capillary gas chromatography for the application in effect-directed analysis. Chemosphere 78:416–422, http://dx.doi.org/10.1016/j.chemosphere.2009.10.061 CrossRefGoogle Scholar
  24. Meinert C, Moeder M, Brack W (2007) Fractionation of technical p-nonylphenol with preparative capillary gas chromatography. Chemosphere 70:215–223CrossRefGoogle Scholar
  25. NIST (2007) Automated Mass Spectral Deconvolution and Identification System (AMDIS). National Institute of Standards and Technology, US Department of Defence, Washington DC, USA. http://chemdata.nist.gov/mass-spc/amdis/
  26. NIST/EPA/NIH (2005) NIST mass spectral library, version 2.0. National Institute of Standards and Technology, US Department of Commerce, WashingtonGoogle Scholar
  27. OpenBabel (2007) OpenBabel, version 2.0.1. http//openbabel.sourceforge.net
  28. Reifferscheid G, Heil J (1996) Validation of the SOS/umu test using test results of 486 chemicals and comparison with the Ames test and carcinogenicity data. Mut Res Toxicol 369:129–145Google Scholar
  29. Reifferscheid G, Heil J, Oda Y, Zahn RK (1991) A microplate version of the SOS/umu-test for rapid detection of genotoxins and genotoxic potentials of environmental samples. Mut Res 253:215–222Google Scholar
  30. Schüürmann G, Kuehne R, Kleint F, Ebert RU, Rothenbacher C, Herth P (1997) A software system for automatic chemical property estimation from molecular structure. In: Chen F, Schüürmann G (eds) Quantitative structure–activity relationships in environmental sciences. VII SETAC Press, Pensacola, pp 93–114Google Scholar
  31. Schüürmann G, Ebert RU, Nendza M, Dearden JC, Paschke A, Kuehne R (2007) Prediction of fate-related compound properties. In: van Leeuwen K, Vermeire T (eds) Risk assessment of chemicals. An introduction. Springer Science, Dordrecht, pp 375–426CrossRefGoogle Scholar
  32. Schymanski EL, Meinert C, Meringer M, Brack W (2008) The use of MS classifiers and structure generation to assist in the identification of unknowns in effect-directed analysis. Anal Chim Acta 615:136–147CrossRefGoogle Scholar
  33. Schymanski EL, Bataineh M, Brack W, Bataineh M, Goss KU (2009) Integrated analytical and computer tools for structure elucidation in effect-directed analysis. TrAC Trends in Anal Chem 28:550–561CrossRefGoogle Scholar
  34. SPARC. Sparc performs automated reasoning in chemistry, version 4.2. http://ibmlc2.chem.uga.edu/sparc/
  35. The MathWorks (2006) MATLAB, version 7.2.0.232. The MathWorks Inc, USAGoogle Scholar
  36. US EPA (2007) Estimation Program Interface (EPI) Suite (TM), version 3.20. United States Environmental Protection Agency, WashingtonGoogle Scholar
  37. Varmuza K, Werther W (1996) Mass spectral classifiers for supporting systematic structure elucidation. J Chem Inf Comput Sci 36:323–333Google Scholar
  38. Weiß H, Teutsch G, Fritz P, Daus B, Dahmke A, Grathwohl P, Trabitzsch R, Feist B, Ruske R, Böhme O, Schirmer M (2001) Sanierungsforschung in regional kontaminierten Aquiferen (SAFIRA)—1. Information zum Forschungsschwerpunkt am Standort Bitterfeld. Grundwasser 6:113–122CrossRefGoogle Scholar
  39. Whong WZ, Wen Y, Steward J, Ong T (1986) Validation of the SOS/Umu-test with mutagenic complex mixtures. Mut Res 175:139–144CrossRefGoogle Scholar
  40. Wycisk P, Weiss H, Kaschl A, Heidrich S, Sommerwerk K (2003) Groundwater pollution and remediation options for multi-source contaminated aquifers (Bitterfeld/Wolfen, Germany). Toxicol Lett 140–141:343–351CrossRefGoogle Scholar
  41. Zvinavashe E, Murk AJ, Rietjens IMCM (2008) Promises and pitfalls of quantitative structure–activity relationship approaches for predicting metabolism and toxicity. Chem Res Toxicol 21:2229–2236CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Cornelia Meinert
    • 1
  • Emma Schymanski
    • 1
  • Eberhard Küster
    • 2
  • Ralph Kühne
    • 3
  • Gerrit Schüürmann
    • 3
  • Werner Brack
    • 1
  1. 1.Department of Effect-Directed AnalysisUFZ, Helmholtz Centre for Environmental ResearchLeipzigGermany
  2. 2.Department of Bioanalytical EcotoxicologyUFZ, Helmholtz Centre for Environmental ResearchLeipzigGermany
  3. 3.Department of Ecological ChemistryUFZ, Helmholtz Centre for Environmental ResearchLeipzigGermany

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