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The ΦX174 transgenic mouse was first developed as an in vivo Ames test, detecting base pair substitution (bps) at a single bp in a reversion assay. A forward mutational assay was also developed, which is a gain of function assay that also detects bps exclusively. Later work with both assays focused on establishing that a mutation was fixed in vivo using single-burst analysis: determining the number of mutant progeny virus from an electroporated cell by dividing the culture into aliquots before scoring mutants. We review results obtained from single-burst analysis, including testing the hypothesis that high mutant frequencies (MFs) of G:C to A:T mutation recovered by transgenic targets include significant numbers of unrepaired G:T mismatches. Comparison between the ΦX174 and lacI transgenes in mouse spleen indicates that the spontaneous bps mutation frequency per nucleotide (mf(n)) is not significantly lower for ΦX174 than for lacI; the response to ENU is also comparable. For the lacI transgene, the spontaneous bps mf(n) is highly age-dependent up to 12 weeks of age and the linear trend extrapolates at conception to a frequency close to the human bps mf(n) per generation of 1.7 × 10(-8). Unexpectedly, we found that the lacI somatic (spleen) bps mf(n) per cell division at early ages was estimated to be the same as for the human germ-line. The bps mf(n) in bone marrow for the gpt transgene is comparable to spleen for the lacI and ΦX174 transgenes. We conclude that the G:C to A:T transition is characteristic of spontaneous in vivo mutation and that the MFs measured in these transgenes at early ages reflect the expected accumulation of in vivo mutation typical of endogenous mammalian mutation rates. However, spontaneous and induced mf(n)s per nucleotide for the cII gene in spleen are 5-10 times higher than for these other transgenes., (Published by Elsevier B.V.)

Daily, rhythmic variation in various biochemical, physiological, and behavioral events is a fundamental property of biological organization. Here, we report analysis of relative levels of gene expression in the liver of 16 Fischer 344 rats as a function of time of day. Expression levels were determined for 3906 genes using high-density oligonucleotide microarrays. Of the 3906 genes, 1171 (30%) were clearly expressed while 2735 (70%) were not expressed or the expression was too low to distinguish from background levels. The maximum estimated changes observed for most genes (1029, 88%) were less than 1.5-fold. Analysis of variance and the Kruskal-Wallis tests were used to identify 67 genes whose expression was significantly altered as a function of time of day. These significantly altered genes were classified according to their functions and fall into key cellular pathways including drug metabolism, ion transport, signal transduction, DNA binding and regulation of transcription, and immune response.

Genotypic selection methods detect rare sequence changes in populations of DNA molecules. These methods have been used to investigate the chemical induction of mutation and for the detection and diagnosis of cancer. The possible use of genotypic selection for improving current risk assessment practices is based on the premise that the frequency of somatic mutation is of critical importance in understanding and modeling carcinogenesis. If genotypic selection can measure the induction of specific mutations that disrupt normal cell/tissue homeostasis, then it could provide key mechanistic information for cancer risk assessment. For example, genotypic selection data might support a particular low-dose extrapolation method or characterize the relationship between rodent and human cancer risk. Strategies for evaluating the use of genotypic selection in cancer risk assessment include the concept of developing a battery of targets that detect a range of agent-specific effects. Ideal targets to examine by genotypic selection are the oncogene and tumor suppressor gene mutations frequently detected in human tumors because these are thought to represent tumor-initiating events. The most commonly occurring basepair (bp) substitutions within the ras and p53 genes are identified. Also, the battery of genotypic selection methods is defined in terms of the most important mutational specificities to include. In theory, the major basepair substitution mutations induced by 29 of 31 chemical carcinogens could be detected by analyzing three different mutations: G:C-->T:A, G:C-->A:T, and A:T-->T:A. Genotypic selection will have the greatest impact on risk assessment if measurement of spontaneous mutation is possible. Data from phenotypic selection assays suggest this corresponds to detection of mutant fractions of approximately 10(-7), and this would necessitate examining DNA samples containing >10(7) target molecules. Despite its apparent potential, considerable development and validation is needed before genotypic selection data can be applied to cancer risk assessment.

The Poisson distribution is a fundamental probability model for count data, and is a natural model for the observed plaque counts in mutation assays using animals with lambda or PhiX174 transgenes. The Poisson likelihood for observed counts is a function of the mutant fraction, and it is straightforward to derive the associated maximum likelihood estimate of the mutant fraction and its variance. The estimate is easy to calculate, and if not the same, very similar to ad hoc estimates in current use. The model indicates the proper way to combine data from a number of plates, possibly prepared with different sample dilutions. The estimator of the mutant fraction is biased as a consequence of dividing by a random variable, the plaque count used to calculate the total recovered plaque-forming units. Fortunately, the bias becomes negligible as this count becomes large. On the other hand, increasing this count can increase the variance by decreasing the amount of sample assayed for mutant phages. Concurrent heed to the bias and the variance provides some guidance as to the optimum allocation of a sample into portions assayed for mutant phages and total recovered phages. The distribution of the estimate of the mutant fraction is related to the binomial distribution. This relationship implies a binomial distribution for the mutant count conditional on an overall count (either the sum of mutant and counted total plaques or the sum of counted mutant and non-mutant plaques). A special but important case occurs when each plate can be evaluated for mutant plaques and non-mutant plaques. Then, the observed proportion of mutants estimates the mutant fraction. More generally, the relationship to a binomial distribution provides a procedure for calculating a confidence interval., (Copyright 1999 Elsevier Science B.V.)

A test procedure is described for detecting germ cell mutations which alter activity of enzymes in in vivo mammalian tissues. The objective is to identify those individuals, among a population of F1 animals from treated parents, that are heterozygous for a mutation at an unspecified locus which results in an altered activity of one or more of the enzymes monitored. Animals are evaluated through three analysis screens with emphasis on identification of mutant individuals. In the first screen, activity values of a battery of enzymes are compared to their respective normal ranges to identify those which are aberrant. The mean activities and coefficients of variation useful in defining the normal ranges for 19 enzymes in C57BL/6J Nctr mice are presented along with a set of theoretical normal animal misclassification probabilities for each of these enzymes. The second screen is a Michaelis-Menten kinetic analysis of aberrant enzymes, the goal of which is to correct misclassifications of normal animals made in the first screen. A third screen of aberrant enzyme activities in a subsequent generation is used to demonstrate inheritance and confirm the mutation. The advantages and the limitations, as well as possible variations of the basic procedure are discussed.