project

Effect-based water-quality measurements with bioassays

Expert(s):
Astrid Reus, Milou Dingemans PhD

  • Start date
    01 May 2020
  • End date
    31 Dec 2025

The number of chemicals encountered in water is increasing worldwide. Effect-based chemical measurements add value because they provide direct information about chemical mixtures in water, when it is not yet clear whether these might be harmful to human health. Effect-based measurement with bioassays answers this concern.

Water-quality monitoring often requires the conduct of more than a single bioassay. This is because the chemicals present in the water might have different harmful effects; for example, on the DNA, the nervous system and/or the endocrine system.

In its general and project-based research, KWR conducts different bioassays in its own laboratory. With regard to research on the effects on the DNA, this involves:

This set of tests makes it possible to determine the different mechanisms through which compounds cause damage to the DNA. KWR can also conduct bioassays for oxidative stress (AREc32 reporter gen assay) and cytotoxicity (cell toxicity). And we can give advice on which tests are best suited to the research question at hand.

In the case of bioassays to determine the harmful effects on the nervous system (i.e., neurotoxicity bioassays), we explore whether such tests are available and appropriate.

Bioassays to determine the effects on the endocrine system are, in the case of reporter gen assays, specific to a particular process, so that it is advisable to conduct more than one reporter gen assay. KWR looks after the outsourcing and the interpretation of the measurement data of such tests.

A staged strategy can be used to determine both the water quality of a drinking water source as well as the effectiveness of a water treatment process. By using bioassays for the purpose of screening,  water samples can be prioritised for further research using more advanced bioassays, whether or not in combination with chemical analysis and in silico tools. For many years now, KWR has worked on the interpretation of measurement data using effect-based trigger values.