Analytical and Bioanalytical Chemistry

, Volume 390, Issue 8, pp 1959–1973

How to confirm identified toxicants in effect-directed analysis

Authors

    • Department Effect-Directed AnalysisUFZ Helmholtz Centre for Environmental Research
  • Mechthild Schmitt-Jansen
    • Department Bioanalytical EcotoxicologyUFZ Helmholtz Centre for Environmental Research
  • Miroslav Machala
    • Veterinary Research Institute
  • Rikke Brix
    • Department of Environmental ChemistryIIQAB-CSIC
  • Damià Barceló
    • Department of Environmental ChemistryIIQAB-CSIC
  • Emma Schymanski
    • Department Effect-Directed AnalysisUFZ Helmholtz Centre for Environmental Research
  • Georg Streck
    • Department Effect-Directed AnalysisUFZ Helmholtz Centre for Environmental Research
  • Tobias Schulze
    • Department Effect-Directed AnalysisUFZ Helmholtz Centre for Environmental Research
Review

DOI: 10.1007/s00216-007-1808-8

Cite this article as:
Brack, W., Schmitt-Jansen, M., Machala, M. et al. Anal Bioanal Chem (2008) 390: 1959. doi:10.1007/s00216-007-1808-8

Abstract

Due to the production and use of a multitude of chemicals in modern society, waters, sediments, soils and biota may be contaminated with numerous known and unknown chemicals that may cause adverse effects on ecosystems and human health. Effect-directed analysis (EDA), combining biotesting, fractionation and chemical analysis, helps to identify hazardous compounds in complex environmental mixtures. Confirmation of tentatively identified toxicants will help to avoid artefacts and to establish reliable cause–effect relationships. A tiered approach to confirmation is suggested in the present paper. The first tier focuses on the analytical confirmation of tentatively identified structures. If straightforward confirmation with neat standards for GC–MS or LC–MS is not available, it is suggested that a lines-of-evidence approach is used that combines spectral library information with computer-based structure generation and prediction of retention behaviour in different chromatographic systems using quantitative structure–retention relationships (QSRR). In the second tier, the identified toxicants need to be confirmed as being the cause of the measured effects. Candidate components of toxic fractions may be selected based, for example, on structural alerts. Quantitative effect confirmation is based on joint effect models. Joint effect prediction on the basis of full concentration–response plots and careful selection of the appropriate model are suggested as a means to improve confirmation quality. Confirmation according to the Toxicity Identification Evaluation (TIE) concept of the US EPA and novel tools of hazard identification help to confirm the relevance of identified compounds to populations and communities under realistic exposure conditions. Promising tools include bioavailability-directed extraction and dosing techniques, biomarker approaches and the concept of pollution-induced community tolerance (PICT).

https://static-content.springer.com/image/art%3A10.1007%2Fs00216-007-1808-8/MediaObjects/216_2007_1808_Figa_HTML.gif
Figure

Toxicity confirmation in EDA as a tiered approach

Keywords

Effect-directed analysis Toxicity identification evaluation Toxicity confirmation Structural analysis Mixture toxicity Hazard

Abbreviations

AhR

arylhydrocarbon receptor

AMDIS

Automated Mass Spectral Deconvolution and Identification System

BEQ

benzo[a]pyrene equivalent quantity

BP

boiling point

CA

concentration addition

CALUX

chemical-activated luciferase expression

ECX

effect concentration required to achieve X% effect

EDA

effect-directed analysis

EROD

ethoxyresorufin-O-deethylase

DNA

deoxyribonucleic acid

GC/MS

gas chromatography with mass-selective detection

IA

independent action

ICQ

index of confirmation quality

IEQ

induction equivalent quantities

IP

identification points

LC-Q-TOF-MS

liquid chromatography with a hybrid quadrupole–time-of-flight mass spectrometer

LSER

linear solvation free-energy relationships

NIST

National Institute of Standards and Technology

NMR

nuclear magnetic resonance

PAH

polycyclic aromatic hydrocarbon

PCB

polychlorinated biphenyl

PCDD/F

polychlorinated dibenzo-p-dioxin and furan

PDMS

polydimethylsiloxane

PICT

pollution-induced community tolerance

QSAR

quantitative structure–activity relationship

QSRR

quantitative structure–retention relationship

REP

relative potency

RI

retention index

RTL-W1

rainbow trout liver cell line W1

SPMD

semipermeable membrane device

TEQ

toxicity equivalent quantity

TIE

toxicity identification evaluation

TU

toxic units

US EPA

United States Environmental Protection Agency

Copyright information

© Springer-Verlag 2007