Phase variation is a mechanism of ON–OFF switching that is widely utilized by bacterial pathogens. There is currently no standardization to how the rate of phase variation is determined experimentally, and traditional methods of mutation rate estimation may not be appropriate to this process. Here, the history of mutation rate estimation is reviewed, describing the existing methods available. A new mathematical model that can be applied to this problem is also presented. This model specifically includes the confounding factors of back-mutation and the influence of fitness differences between the alternate phenotypes. These are central features of phase variation but are rarely addressed, with the result that some previously estimated phase variation rates may have been significantly overestimated. It is shown that, conversely, the model can also be used to investigate fitness differences if mutation rates are approximately known. In addition, stochastic simulations of the model are used to explore the impact of ‘jackpot cultures' on the mutation rate estimation. Using the model, the impact of realistic rates and selection on population structure is investigated. In the absence of fitness differences it is predicted that there will be phenotypic stability over many generations. The rate of phenotypic change within a population is likely, therefore, to be principally determined by selection. A greater insight into the population dynamics of mutation rate processes can be gained if populations are monitored over successive time points.
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