## 6.4.4. Effect Based water quality assessment

Effect-based water quality assessment

Authors: Milo de Baat, Michiel Kraak

Reviewers: Ad Ragas, Ron van der Oost, Beate Escher

Learning objectives:

You should be able to

- list the advantages and drawbacks of an effect-based monitoring approach in comparison to a compound-based approach for water quality assessment.
- motivate the necessity of employing a bioassay battery in effect-based monitoring approaches.
- explain the expression of bioassay responses in terms of toxic/bioanalytical equivalents of reference compounds.
- translate the outcome of a bioassay battery into a ranking of contaminated sites based on ecotoxicological risk.

Keywords: Effect-based monitoring, water quality assessment, bioassay battery, effect-based trigger values, ecotoxicological risk assessment

Introduction

Traditional chemical water quality assessment is based on the analysis of a list of a varying, but limited number of priority substances. Nowadays, the use of many of these compounds is restricted or banned, and concentrations of priority substances in surface waters are therefore decreasing. At the same time, industries have switched to a plethora of alternative compounds, which may enter the aquatic environment, seriously impacting water quality. Hence, priority substances lists are outdated, as the selected compounds are frequently absent, while many compounds with higher relevance are not listed as priority substances. Consequently, a large portion of toxic effects observed in surface waters cannot be attributed to compounds measured by water authorities, and toxic risks to freshwater ecosystems are thus caused by mixtures of a myriad of (un)known, unregulated compounds. Understanding of these risks requires a paradigm shift towards new monitoring methods that do not depend on chemical analysis of priority substances solely, but consider the biological effects of the entire micropollutant mixture first. Therefore, there is a need for effect-based monitoring strategies that employ bioassays to identify environmental risk. Responses in bioassays are caused by all bioavailable (un)known compounds and their metabolites, whether or not they are listed as priority substances.

Table 1. Example of the bioassay battery employed by the SIMONI approach of Van der Oost et al. (2017) that can be applied to assess surface water toxicity. Effect-based trigger values (EBT) were previously defined by Escher et al. (2018) (PAH, anti-AR and ER CALUX) and Van der Oost et al. (2017).

| Bioassay | Endpoint | Reference compound | EBT | Unit
in situ | Daphnia in situ | Mortality | n/a | 20 | % mortality
in vivo | Daphniatox | Mortality | n/a | 0.05 | TU
Algatox | Algal growth inhibition | n/a | 0.05 | TU
Microtox | Luminescence inhibition | n/a | 0.05 | TU
in vitro CALUX | cytotox | Cytotoxicity | n/a | 0.05 | TU
DR | Dioxin (-like) activity | 2,3,7,8-TCDD | 50 | pg TEQ/L
PAH | PAH activity | benzo(a)pyrene | 6.21 | ng BapEQ/L
PPARγ | Lipid metabolism inhibition | rosiglitazone | 10 | ng RosEQ/L
Nrf2 | Oxidative stress | curcumin | 10 | µg CurEQ/L
PXR | Toxic compound metabolism | nicardipine | 3 | µg NicEQ/L
p53 -S9 | Genotoxicity | n/a | 0.005 | TU
p53 +S9 | Genotoxicity (after metabolism) | n/a | 0.005 | TU
ER | Estrogenic activity | 17ß-estradiol | 0.1 | ng EEQ/L
anti-AR | Antiandrogenic activity | flutamide | 14.4 | µg FluEQ/L
GR | Glucocorticoid activity | dexamethasone | 100 | ng DexEQ/L
in vitro antibiotics | T | Bacterial growth inhibition (Tetracyclines) | oxytetracycline | 250 | ng OxyEQ/L
Q | Bacterial growth inhibition (Quinolones) | flumequine | 100 | ng FlqEQ/L
B+M | Bacterial growth inhibition (β-lactams and Macrolides) | penicillin G | 50 | ng PenEQ/L
S | Bacterial growth inhibition (Sulfonamides) | sulfamethoxazole | 100 | ng SulEQ/L
A | Bacterial growth inhibition (Aminoglycosides) | neomycin | 500 | ng NeoEQ/L

B ioassay battery

The regular application of effect-based monitoring largely relies on the ease of use, endpoint specificity, costs and size of the used bioassays, as well as on the ability to interpret the measured responses. To ensure sensitivity to a wide range of potential stressors, while still providing specific endpoint sensitivity, a successful bioassay battery like the example given in Table 1 can include in situ whole organism assays (see section on Biomonitoring and in situ bioassays), and should include laboratory-based whole-organism in vivo (see section on In vivo bioassays) and mechanism-specific in vitro assays (see section on In vitro bioassays). Adverse effects in the whole-organism bioassays point to general toxic pressure and represent a high ecological relevance. In vitro or small-scale in vivo assays with specific drivers of adverse effects allow for focused identification and subsequent confirmation of (groups of) toxic compounds with specific modes of action. Bioassay selection can also be based on the Adverse Outcome Pathways (AOP) (see section on Adverse Outcome Pathways) concept that describes relationships between molecular initiating events and adverse outcomes. Combining different types of bioassays ranging from whole organism tests to in vitro assays targeting specific modes of action can thus greatly aid in narrowing down the number of candidate compound(s) that cause environmental risks. For example, if bioanalytical responses at a higher organisational level are observed (the orange and black pathways in Figure 1), responses in specific molecular pathways (blue, green, grey and red in Figure 1) can help to identify certain (groups of) compounds responsible for the observed effects.

Figure 1. From toxicokinetics via molecular responses to population responses. Redrawn from Escher et al. (2018) by Wilma IJzerman.

Toxic and bioanalytical equivalent concentrations

The severity of the adverse effect of an environmental sample in a bioassay is expressed as toxic equivalent (TEQ) concentrations for toxicity in in vivo assays or as bioanalytical equivalent (BEQ) concentrations for responses in in vitro bioassays. The toxic equivalent concentrations and bioanalytical equivalent concentrations represent the joint toxic potency of all unknown chemicals present in the sample that have the same mode of action (see section on Toxicodynamics and molecular interactions) as the reference compound and act concentration-additively (see section on Mixture toxicity). The toxic equivalent concentrations and bioanalytical equivalent concentrations are expressed as the concentration of a reference compound that causes an effect equal to the entire mixture of compounds present in an environmental sample. Figure 2 depicts a typical dose-response curve for a molecular in vitro assay that is indicative of the presence of compounds with a specific mode of action targeted by this in vitro assay. A specific water sample induced an effect of 38% in this assay, equivalent to the effect of approximately 0.02 nM bioanalytical equivalents.

Effect-based trigger values

The identification of ecological risks from bioassay battery responses follows from the comparison of bioanalytical signals to previously determined thresholds, defined as effect-based trigger values (EBT), that should differentiate between acceptable and poor water quality. Since bioassays potentially respond to the mixture of all compounds present in a sample, effect-based trigger values are expressed as toxic or bioanalytical equivalents of concentrations of model compounds for the respective bioassay (Table 1).

Figure 2. Dose response relationship for a reference compound in an in vitro bioassay. The blue lines show that a specific water sample induced an effect of 38%, representing approximately 0.02 nM bioanalytical equivalents.

Ranking of contaminated sites based on effect-based risk assessment

Once the toxic potency of a sample in a bioassay is expressed as toxic equivalent concentrations or bioanalytical equivalent concentrations, this response can be compared to the effect-based trigger value for that assay, thus determining whether or not there is a potential ecological risk from contaminants in the investigated water sample. The ecotoxicity profiles of the surface water samples generated by a bioassay battery allow for calculation and ranking of a cumulative ecological risk for the selected locations. In the example given in Figure 3, water samples of six locations were subjected to the SIMONI bioassay battery of Van der Oost et al. (2017), consisting of 17 in situ, in vivo and in vitro bioassays. Per site and per bioassay the response is compared to the corresponding effect-based trigger value and classified as ‘no response’ (green), ‘response below the effect-based trigger value’ (yellow) or ‘response above the effect-based trigger value’ (orange). Next, the cumulative ecological risk per location is calculated.

The resulting integrated ecological risk score allows ranking of the selected sites based on the presence of ecotoxicological risks rather than on the presence of a limited number of target compounds. This in turn permits water authorities to invest money where it matters most: identification of compounds causing adverse effects at locations with indicated ecotoxicological risks. Initially, the compounds causing the observed effect-based trigger value exceedance will not be known, however, this can subsequently be elucidated with targeted or non-target chemical analysis, which will only be necessary at locations with indicated ecological risks. A potential follow-up step could be to investigate the drivers of the observed effects by means of effect-directed analysis (see section on Effect-directed analysis).

Figure 3. Heat map showing the response of 17 in situ, in vivo and in vitro bioassays to six surface water samples. The integrated risk score (SIMONI Risk Indication; Van der Oost et al., 2017) is classified as ‘low risk’ (green), ‘potential risk’ (orange) or ‘risk’ (red).

References

Escher, B. I., Aїt-Aїssa, S., Behnisch, P. A., Brack, W., Brion, F., Brouwer, A., et al. (2018). Effect-based trigger values for in vitro and in vivo bioassays performed on surface water extracts supporting the environmental quality standards (EQS) of the European Water Framework Directive. Science of the Total Environment 628-629, 748-765.

Van der Oost, R., Sileno, G., Suarez-Munoz, M., Nguyen, M.T., Besselink, H., Brouwer, A. (2017). SIMONI (Smart Integrated Monitoring) as a novel bioanalytical strategy for water quality assessment: part I – Model design and effect-based trigger values. Environmental Toxicology and Chemistry 36, 2385-2399.

Additional reading

Altenburger, R., Ait-Aissa, S., Antczak, P., Backhaus, T., Barceló, D., Seiler, T.-B., et al. (2015). Future water quality monitoring — Adapting tools to deal with mixtures of pollutants in water resource management. Science of the Total Environment 512-513, 540–551.

Escher, B.I., Leusch, F.D.L. (2012). Bioanalytical Tools in Water Quality Assessment. IWA publishing, London (UK).

Hamers, T., Legradi, J., Zwart, N., Smedes, F., De Weert, J., Van den Brandhof, E-J., Van de Meent, D., De Zwart, D. (2018). Time-Integrative Passive sampling combined with TOxicity Profiling (TIPTOP): an effect-based strategy for cost-effective chemical water quality assessment. Environmental Toxicology and Pharmacology 64, 48-59.