Assessing Modes of Toxic Action of Organic Cations in In Vitro Cell-Based Bioassays: the Critical Role of Partitioning to Cells and Medium Components.

High-throughput cell-based bioassays can fulfill the growing need to assess the hazards and modes of toxic action (MOA) of ionic liquids (ILs). Although nominal concentrations (C_nom) are typically used in an in vitro bioassay, freely dissolved concentrations (C_free) are considered a more accurate dose metric because they account for chemical partitioning processes and are informative about MOA. We determined the C_free of IL cations in AREc32 and AhR-CALUX assays using both mass balance model (MBM) prediction and experimental quantification. Partition coefficients between membrane lipid-water (K_mw), serum albumin-water (K_albumin/w), and cell-water (K_cell/w) as well as potential confounding factors (binding to a test plate and micelle formation) were determined to improve the MBM prediction. IL cations showed a higher affinity for both cell lines than that predicted by the MBM based on K_mw and K_albumin/w. Their affinity for the AhR-CALUX cells was more than 1 order of magnitude higher than for the AREc32, signifying cell line-specific affinity. The MBM with an experimental K_cell/w accurately predicted C_free. Evaluating cytotoxicity based on C_free eliminated the leveling off of toxicity observed for hydrophobic IL cations (side chain cutoff), suggesting that C_nom underestimates the effects of compounds with high affinity for the assay medium. Cell membrane concentrations calculated from C_free using K_mw were compared to the critical membrane burden to identify whether IL cations act as baseline toxicants. The IL cations carrying 16 carbons in the chain in the AREc32 assay and most of the IL cations in the AhR-CALUX assay were classified as excess toxicants. However, since the reasons for the deviation of experimental K_cell/w from MBM prediction remain unexplained, it is uncertain whether the cell membrane concentrations can be well predicted from K_mw used in this study. Therefore, future studies should aim to uncover the underlying causes of differing cell affinities observed across cell lines and model predictions.