MacLean and Buckling 29 also characterized the DFE of beneficial mutations in environments where wild-type fitness is low, and in those cases they rejected the exponential distribution.
Kassen and Bataillon 27 and MacLean and Buckling 29 characterized the DFE of beneficial mutations in environments where wild-type fitness is high (i.e., close to the fitness optimum) and showed that the observed DFE is not significantly different from an exponential distribution.
Whether similar paths are followed in nature is likely to depend on the strength and unidirectionality of selection and the extent of antagonistic pleiotropy: the contrast between the benefits of a mutation in one environment and its costs in others.
We examined the line of descent to identify the mutations that led to the loss of a particular function, and we determined the fitness effect of each of these mutations in the environment in which they arose as well as other environments.
31 used a modified version of the fluctuation assay procedure involving a reporter construct to characterize the DFE of beneficial mutations in an environment where wild-type fitness is low, and found that a normal distribution provided the best fit to their data.
This compares to no reduction in content owing to the SSII deficiency, and an increase in the starch content conditioned by SSIII mutation in the growth environment used in this study.
Such models make explicit assumptions about initial population size, threshold population size (below which the population is at high extinction risk) population growth, and fitness changes across time as a result of the initial change in environment, mutation rates, and subsequent selection.
After this procedure, 560 single-nucleotide mutations (in all environments) remain for further analysis.
It is likely that most populations will experience both beneficial and detrimental mutations in most environments.
Directly measuring the effect of mutations that occur in laboratory populations can be a powerful approach for examining the fitness consequences of individual mutations in specific environments.
By gauging the fitness consequences of these mutations in other environments and in other bacterial strains, the authors show that the beneficial effects of these mutations are highly specific and highlight two factors that are crucial for the evolution of antibiotic resistance: pleiotropy and epistasis.
