The induction of adaptive stress response pathways is an early and sensitive indicator of the presence of chemical and non-chemical stressors in cells. An important stress response is the Nrf-2 mediated oxidative stress response pathway where electrophilic chemicals or chemicals that cause the formation of reactive oxygen species initiate the production of antioxidants and metabolic detoxification enzymes. The AREc32 cell line is sensitive to chemicals inducing oxidative stress and has been previously applied for water quality monitoring of organic micropollutants and disinfection byproducts. Here we propose an algorithm for the derivation of effect-based water quality trigger values for this end point that is based on the combined effects of mixtures of regulated chemicals. Mixture experiments agreed with predictions by the mixture toxicity concept of concentration addition. The responses in the AREc32 and the concentrations of 269 individual chemicals were quantified in nine environmental samples, ranging from treated effluent, recycled water, stormwater to drinking water. The effects of the detected chemicals could explain less than 0.1% of the observed induction of the oxidative stress response in the sample, affirming the need to use effect-based trigger values that account for all chemicals present.

The reporter gene assay AREc32 is based on the induction of the Nrf2 mediated oxidative stress response pathway in the human breast cancer cell line MCF7, where eight copies of the antioxidant response element (ARE) are linked to a reporter gene encoding for luciferase. The Nrf2-ARE pathway is responsive to many chemicals that cause oxidative stress, among them a large number of pesticides and skin irritants. We adopted and validated the AREc32 bioassay for water quality testing. tert-Butylhydroquinone served as the positive control, phenol as the negative control and other reactive chemicals were assessed for their specificity. An environmentally relevant reference chemical, benzo(a)pyrene was the most potent inducer of all tested chemicals. The concentration causing an induction ratio (IR) of 1.5 (EC(IR1.5)) was chosen as the effect benchmark value. The assay was applied to 21 water samples ranging from sewage to drinking water, including secondary treatment and various tertiary treatment options (ozonation, biologically activated carbon filtration, membrane filtration, reverse osmosis, advanced oxidation, chlorination, chloramination). The samples were enriched by solid phase extraction. In most samples the oxidative stress response was far more sensitive than cytotoxicity. The primary and secondary treated effluent exceeded the effect threshold IR 1.5 at a relative enrichment factor (REF) of 1, i.e., the native samples were active. All tertiary treated samples were less potent and their EC(IR1.5) lay between REF 1 and 10. The Nrf2 pathway was induced at a REF of approximately 10 for surface waters and drinking water, and above this enrichment cytotoxicity took over in most samples and quenched the induction. The blank (ultrapure water run through the sample enrichment process) was cytotoxic at an REF of 100, which is the limit of concentrations range that can be evaluated. Treatment typically decreased both the cytotoxicity and oxidative stress response apart from drinking water treatment where chlorination caused an increase in oxidative stress response, presumably due to the formation of disinfection by-products. This study demonstrates the relevance and applicability of the oxidative stress response pathway for water quality monitoring.

Individual variation in animal venom has been linked to geographical location, feeding habit, season, size, and gender. Uniquely, cone snails possess the remarkable ability to change venom composition in response to predatory or defensive stimuli. To date, correlations between the venom gland transcriptome and proteome within and between individual cone snails have not been reported. In this study, we use 454 pyrosequencing and mass spectrometry to decipher the transcriptomes and proteomes of the venom gland and corresponding predation-evoked venom of two specimens of Conus imperialis. Transcriptomic analyses revealed 17 conotoxin gene superfamilies common to both animals, including 5 novel superfamilies and two novel cysteine frameworks. While highly expressed transcripts were common to both specimens, variation of moderately and weakly expressed precursor sequences was surprisingly diverse, with one specimen expressing two unique gene superfamilies and consistently producing more paralogs within each conotoxin gene superfamily. Using a quantitative labelling method, conotoxin variability was compared quantitatively, with highly expressed peptides showing a strong correlation between transcription and translation, whereas peptides expressed at lower levels showed a poor correlation. These results suggest that major transcripts are subject to stabilizing selection, while minor transcripts are subject to diversifying selection.

The conventional setup of in vitro bioassays in microplates does not prevent the loss of volatile compounds, which hampers the toxicological characterization of waterborne volatile disinfection by-products (DBPs). To minimize the loss of volatile test chemicals, we adapted four in vitro bioassays to a headspace-free setup using eight volatile organic compounds (four trihalomethanes, 1,1-dichloroethene, bromoethane, and two haloacetonitriles) that cover a wide range of air-water partition coefficients. The nominal effect concentrations of the test chemicals decreased by up to three orders of magnitude when the conventional setup was changed to a headspace-free setup for the bacterial cytotoxicity assay using bioluminescence inhibition of Vibrio fischeri. The increase of apparent sensitivity correlated significantly with the air-water partition coefficient. Purge and trap GC/MS analysis revealed a reduced loss of dosed volatile compounds in the headspace free setup (78-130% of nominal concentration) compared to a substantial loss in the conventional set up (2-13% of the nominal concentration). The experimental effect concentrations converged with the headspace-free setup to the effect concentrations predicted by a QSAR model, confirming the suitability of the headspace-free approach to minimize the loss of volatile test chemicals. The analogue headspace-free design of the bacterial bioassays for genotoxicity (umuC assay) and mutagenicity (Ames fluctuation assay) increased the number of compounds detected as genotoxic or mutagenic from one to four and zero to two, respectively. In a bioassay with a mammalian cell line applied for detecting the induction of the Nrf-2-mediated oxidative stress response (AREc32 assay), the headspace-free setup improved the apparent sensitivity by less than one order of magnitude, presumably due to the retaining effect of the serum components in the medium, which is also reflected in the reduced aqueous concentrations of compounds. This study highlights the importance of adapting bioanalytical test setups when volatile/semivolatile compounds are present in the sample to avoid the loss of chemicals and thus to avoid underestimating the toxicity of mixtures and complex environmental samples.

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