Improving water and sediment quality assessment using adaptive stress response assays and implementing more efficient methodologies

Abstract

In vitro cell based bioassays are commonly used in water and sediment quality assessment. Bioassays are often cell-based methods in which the cellular response to chemical exposure is measured in fluorescence, luminescence or absorbance after conversion of a substrate. The general toxicity endpoints measured with in vitro bioassay include cell viability, production of reactive oxygen species (ROS) and genotoxic potency. Such assays can be a valuable tool in assessing general toxicity endpoints including cell viability and genotoxicity as well as specific endpoints including adaptive stress response activation. Adaptive stress responses include the cellular reactions that occur to protect the cell, tissue or organism following among others genotoxic damage, oxidative stress and inflammation. Measuring these endpoints can be useful in screening chemicals and environmental samples because such effects occur prior to general toxicity endpoints. This review is focused on describing possible improvements to the current bioassay based water and sediment quality assessment. To improve the water and sediment quality assessment developing, validating and implementing headspace-free setups in bioassays is suggested. Measuring several adaptive stress response endpoints for samples is recommended for screening purposes, either in a test battery or multiplex setup (a multiplex assay is method used to measure multiple targets simultaneously). The development of a high-throughput screening multiplex method for adaptive stress responses would provide valuable data whilst saving time and valuable samples. Targets of interest for screening purposes include p53, NF-κB , Nrf2, XBP-1 and GSH , which should be measured simultaneously with general markers of cell viability and mitochondrial activity. Although many specific single assays measuring adaptive stress response endpoints exist, improvements can be made by improving efficiency of the methods and the quality of the acquired data.