Levels Of S9 Research Articles

Mutagenic interactions of model chemical mixtures

Although current methodology for human health risk assessment assumes additive interactions among the contaminants of a complex mixture, chemical interactions may occur which produce synergistic or antagonistic effects. In this study, the mutagenic response of three model compounds, benzo(a)pyrene (B(a)P), pentachlorophenol (PCP) and 2,4,6-trinitrotoluene (TNT), were tested individually and in binary and tertiary solutions, using the Salmonella/microsome assay with each of three bacterial tester strains (TA97a, TA98, and TA100). For all strains, B(a)P was mutagenic with metabolic activation (Arochlor 1254-induced Sprague-Dawley rat liver S9 fraction), TNT was mutagenic without metabolic activation, and pentachlorophenol was inactive both with and without metabolic activation. In binary and tertiary solutions, pentachlorophenol had no effect on the mutagenicity of B(a)P or TNT, independent of metabolic activation. For strain TA97a, the mutagenicity of B(a)P with metabolic activation was slightly decreased in the presence of TNT; the mutagenicity of TNT without metabolic activation was slightly decreased in the presence of B(a)P and PCP; and the mutagenicity of the tertiary solution (496 revertants/10 ug) with metabolic activation was lower than the mutagenicity of B(a)P alone (729 revertants/10 ug). The mutagenicity of B(a)P in strain TA98 with activation was inhibited by the addition of TNT. Studies conducted using several concentrations of TNT or B(a)P indicate that the inhibition of B(a)P mutagenicity was increased as the concentration of TNT increased. Assays performed using four concentrations of S9 indicated the inhibition of B(a)P mutagenicity was relatively unaffected by the level of S9. The data suggest that an interaction in the presence of TNT limits the concentration of B(a)P that is capable of reaching or binding with bacterial DNA.

A statistical analysis of the third UKEMS collaborative trial

In the third UKEMS collaborative trial, nine laboratories optimized protocols for a variety of mammalian cell mutagenicity assays and used these protocols to test three reference mutagens. Data from the trial have been deposited with Mutagenesis under the scheme of the journal for a database of results of extensive mutagenicity testing programmes. A preliminary examination of the data using procedures advocated by the UKEMS guidelines on statistical evaluation of mutagenicity test data confirms that the assays are capable of giving clear, convincing data, in a form amenable to statistical analysis. The utility of the methods of analysis proposed by both the plate and fluctuation test statistical working groups was confirmed. In almost all cases variation between plates or trays from the same replicate treatment was little greater than Poisson or binomial, whereas variation between replicate treatments was substantially larger, confirming the recommendation of both groups for true independent replicates of each treatment. In six out of nine laboratories part of this variation between replicates was consistent for both viability and mutation, which might cause the guide-lines procedure for fluctuation test data to underestimate significance. In about half the cases examined, variation between experiments was significantly greater than variation between replicates within an experiment, which may create problems of interpretation. Supplementary tests, using the statistical package GLIM, suggested that although factors such as choice of expression time, level of S9, zero dose cloning efficiency or spontaneous mutation frequency might have an effect, they would not have been likely to interfere with detection of a mutagenic effect in the present data set.

An explanation for optimal levels of S9 in Ames and fluctuation tests

An explanation for optimal levels of S9 in Ames and fluctuation tests

Optimal levels of S9 fraction in the Ames and fluctuation tests: apparent importance of diffusion of metabolites from top agar.

For activation of 2-acetylaminofluorene (AAF) there is an optimal level of rat liver S9 fraction which is considerably lower in the fluctuation test than in the Ames test. The optimal level of S9 is not markedly affected by the dose of AAF used, nor by the ratio of S9 to bacteria, nor by the presence of soft agar. The difference between Ames and fluctuation tests appears to be due to diffusion of some substance or substances from the top agar layer in the Ames test. Diffusion of the co-factors NADP and glucose-6-phosphate is not responsible for the difference in S9 optima, nor is diffusion of soluble S9 constituents although this may considerably affect the performance of the S9 mix. We present evidence that diffusion of non-mutagenic metabolites of AAF from the Ames test top agar may be responsible for the difference in S9 optima. Our results are consistent with a model whereby lipophilic non-mutagenic metabolites accumulate in the microsomes and inhibit further activation. When the metabolites are able to diffuse away, a higher level of S9 will be optimal. The model is consistent with some other phenomena of S9 activation.