Headspace-Free Setup of <i>in Vitro</i> Bioassays for the Evaluation of Volatile Disinfection By-Products

The conventional setup of <i>in vitro</i> 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 <i>in vitro</i> 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 <i>Vibrio fischeri</i>. 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

Analyzed contaminants.

<p>Analyzed contaminants.</p

Multiple linear regression models testing the effect of environmental parameters and contaminants on biotic response variables: the total number of individuals and taxa, Simpson and Shannon diversity, number of EPT taxa and the saprobic index.

<p>Given are df-, R²-, F- and p-values for full models after stepwise deletion of non-significant terms (n.s.) and of significant model parameters.</p>★<p>, p<0.05;</p>★★<p>, p<0.01;</p>★★★<p>, p<0.001; n.a., not available.</p

NMDS biplot of taxa and environmental variables.

<p>Displayed are variables with a significant impact (p<0.05) for sampling campaign in spring (A) and autumn (B). HM, components of the principal component analysis (PCA) with heavy metals; OC, components of the PCA with organic contaminants; structure, structural degradation. Spring: two convergent solutions, two dimensions, stress = 0.17; autumn: two convergent solutions, two dimensions, stress = 0.21).</p

River systems with respective streams, abbreviations (abbr.), and number of sampling sites (no.).

<p>River systems with respective streams, abbreviations (abbr.), and number of sampling sites (no.).</p

Number of EPT taxa (Ephemeroptera, Plecoptera, Trichoptera) correlating with the first component of the PCA with organic contaminants (OC1).

<p>Displayed are results for sampling campaign in spring (A) and autumn (B). Please note different scaling of y-axes in A and B.</p