A deterministic approach for the estimation of mutation rates in cultured mammalian cells

Unequal growth rates between mutant and wild-type cells in a large population constitute a problem for the estimation of mutation rate. Over a period of cell growth, a selective advantage of one cell type over the other might lead to considerable error in the estimation of mutation rate if equal growth rates are assumed. In this study, we propose a formula and apply it to the estimation of spontaneous mutation rate in a growing population of Chinese hamster V79 cells in which ouabain-resistant mutant cells exhibit a slower growth rate than the wild-type cells. The formula is a generalization of that previously presented by Armitage (1953), and this is the first attempt to apply the deterministic approach for mutation rate estimation to cultured mammalian cells. The value of the estimated rate is compared with that derived from a parallel experiment using the fluctuation test of Luria and Delbrück (1943). The limitations and advantages of taking the deterministic approach to mutation rate estimation in mammalian cell systems are discussed.

Estimation of mutation rates in cultured mammalian cells

The factors that affect reliable estimations of mutation rates (mu) in cultured mammalian somatic cell populations by fluctuation analysis are studied experimentally and statistically. We analyze the differential effect of the final cell population size in each culture (Nt) and the number of parallel cultures (C) on the variation in the rate estimates (mu) inferred from the P0 method. The analysis can be made after the derivation of the variance of mu, which is a measure of variation of mu for a given combination of Nt and C in a number of repeat experiments. The variance of mu is inversely proportional to C and to the square of Nt . Nt determines the probability of occurrence of mutations in a cell culture. By influencing the size of P0, Nt also determines whether a rate estimate is obtainable from the experiment. Since Po is estimated from the fraction of cultures containing no mutation in a set of C cultures, C becomes a determining factor for the accuracy of mu. The rate estimated from P0 is biased, but the bias is in general 2 orders of magnitude smaller than mu. By the selection of an appropriate combination of Nt and C for the experiment, this bias can be reduced even further. Based on the notion of comparing two proportions, we propose a test statistic and have applied it to experimental results for a test of equality of mutation rates in different cell lines. This development places the comparison of mutation rates on a statistical basis.