A comparison of the generation and detoxification of reactive aflatoxin B1 metabolites in different species may elucidate why animal species vary widely in sensitivity to aflatoxin B1 carcinogenicity, in addition to offering some perspective on how sensitive man may be to the carcinogenic effects of this mycotoxin. Scientific literature comparing the ability of cellular fractions from different species to metabolize aflatoxin B1 is reviewed. However, in vitro studies exclude components for multiple metabolic pathways, eliminating the possibility of competition between metabolic activation and detoxification. Quantification of metabolic activation by different species from these studies is therefore limited. The species-specific carcinogenic potency of aflatoxin B1 may be reflected in levels of aflatoxin B1-DNA adducts generated in vivo. The current paucity of quantitative information on human DNA adduct levels does not permit comparisons between different species on this basis.
Transgenic mice carrying the bacterial lacl gene in a lambda shuttle vector were used to isolate and characterize background and 7,12-dimethylbenz[a]anthracene (DMBA)-induced mutations in skin. Adult male mice were treated once topically with either DMBA or acetone or were left untreated. Seven days later, DMBA treatment had significantly increased the mutant frequency in the skin (mean +/- SEM, 36 +/- 3 x 10(-5)) versus in vehicle-treated (6.4 +/- 1.2 x 10(-5)) and untreated mice (7.1 x 1.0 x 10(-5)). At least 10 mutants from each of three DMBA-treated and three untreated mice were selected for DNA sequence analysis. In each case, the entire 1080-bp target gene was sequenced. Base-pair substitutions predominated (86 of 96 mutations), although frameshift and deletion mutations were also detected. Twelve percent of the mutants carried more than one mutation. In controls, the mutations were predominantly GC-->AT transitions (26 of 42), and no AT-->TA transversions were recovered. In contrast, in the DMBA-treated mice, AT-->TA transversions represented 42% of the mutations (23 of 54) and GC-->AT transitions accounted for only 11%. The AT-->TA transversions occurred mostly at 5'-CA sites. This class of mutation has been recovered frequently in ras genes from DMBA-treated mice and probably represents an early event in carcinogenesis (Nelson MA et al., Proc Natl Acad Sci USA 89:6398-6402, 1992). Our present results are consistent with the types of DNA damage induced by DMBA. The observation of different mutant frequencies and spectra in treated and control mice demonstrates the utility of this approach in the study of mutagenesis in vivo.
We have been working on identifying sources of variability in data from transgenic mouse mutation assays in order to develop appropriate statistical methods and designs for routine studies. Data from our lab and elsewhere point to the presence of significant animal-to-animal variability, which must be taken into account in statistical hypothesis tests. Here, the usual Cochran-Armitage (CA) test for trend in mutant frequencies, which takes the transgene as the experimental unit, and a generalized Cochran-Armitage test (GCA), which takes the animal as the experimental unit, are contrasted in computer simulations that help to quantify the differences between these statistical tests. The simulations report the statistical power of each test to detect treatment group differences, and their type I error rates. We find in general that the GCA test performs poorly compared to the CA test when it is appropriate to take the transgene as the experimental unit, and the study also uses a small number of animals. However, the CA test performs poorly in small group-size studies when the animal is the appropriate experimental unit. Extensions of the computer simulations allow for identification of cost-effective experimental designs. The results emphasize that the benefits of using additional animals in these mutation studies can be realized without substantial increases in costs. Here we illustrate the methods for liver studies in our lab. These methods can be used to derive optimal experimental designs for any combination of spontaneous mutant frequency and animal-to-animal variability.
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