Mutagenicity testing of organic extracts of diesel exhaust particles after fractionation and recombination.

A new strategy for the evaluation of mixtures is presented. The mixture used was the organic extract of diesel exhaust particles (DEP). After extraction with dichloromethane (DCM), the crude extract was fractionated according to polarity into five fractions: aliphatic hydrocarbons, polycyclic aromatic hydrocarbons (PAHs), nitro-PAHs, dinitro-PAHs, and polar compounds. After dissolving in dimethylsulphoxide (DMSO), the three fractions containing the primary mutagens (fractions 3-5) were recombined in different combinations to create new extracts. The blend matrix was obtained using a mixture design at three dose levels to support an empirical model with linear, interaction, and quadratic terms (Taylor polynome). The recombined extracts were tested in the Ames Salmonella assay using strain TA100. Multivariate data analysis was performed with projections to latent structures (PLS). The best model describing the relation between the mutagenicity (response) and the three fractions (variables) contained two interaction terms. The model showed high correlation (r2) and prediction properties (Q2), the latter obtained after cross validation. Interaction terms are only indications of possible synergism or antagonism and have to be evaluated with respect to dose-additivity and response-additivity. The incorporation of dose in the design reduced the number of samples (recombined extracts) significantly, compared to determining dose-response curves on each sample (i.e. the recombined extracts in different dilutions). Furthermore, instead of running two independent experiments as required in the standard procedure for the Ames test, predictions and verifications of a few new samples were used. The principle of fractionation and recombination, and the use of mixture design may in principle be extended to an unlimited number of variables. An adaptation of mixture design to the isobole method is discussed.