Epistatic interactions between mutations play a prominent role in evolutionary theories. Many studies have found that epistasis is widespread, but they have rarely considered beneficial mutations. We analyzed the effects of epistasis on fitness for the first five mutations to fix in an experimental population of Escherichia coli. Epistasis depended on the effects of the combined mutations--the larger the expected benefit, the more negative the epistatic effect. Epistasis thus tended to produce diminishing returns with genotype fitness, although interactions involving one particular mutation had the opposite effect. These data support models in which negative epistasis contributes to declining rates of adaptation over time. Sign epistasis was rare in this genome-wide study, in contrast to its prevalence in an earlier study of mutations in a single gene.

Twelve populations of Escherichia coli, derived from a common ancestor, evolved in a glucose-limited medium for 20,000 generations. Here we use DNA expression arrays to examine whether gene-expression profiles in two populations evolved in parallel, which would indicate adaptation, and to gain insight into the mechanisms underlying their adaptation. We compared the expression profile of the ancestor to that of clones sampled from both populations after 20,000 generations. The expression of 59 genes had changed significantly in both populations. Remarkably, all 59 were changed in the same direction relative to the ancestor. Many of these genes were members of the cAMP-cAMP receptor protein (CRP) and guanosine tetraphosphate (ppGpp) regulons. Sequencing of several genes controlling the effectors of these regulons found a nonsynonymous mutation in spoT in one population. Moving this mutation into the ancestral background showed that it increased fitness and produced many of the expression changes manifest after 20,000 generations. The same mutation had no effect on fitness when introduced into the other evolved population, indicating that a mutation of similar effect was present already. Our study demonstrates the utility of expression arrays for addressing evolutionary issues including the quantitative measurement of parallel evolution in independent lineages and the identification of beneficial mutations.

In theory, competition between asexual lineages can lead to second-order selection for greater evolutionary potential. To test this hypothesis, we revived a frozen population of Escherichia coli from a long-term evolution experiment and compared the fitness and ultimate fates of four genetically distinct clones. Surprisingly, two clones with beneficial mutations that would eventually take over the population had significantly lower competitive fitness than two clones with mutations that later went extinct. By replaying evolution many times from these clones, we showed that the eventual winners likely prevailed because they had greater potential for further adaptation. Genetic interactions that reduce the benefit of certain regulatory mutations in the eventual losers appear to explain, at least in part, why they were outcompeted.

Since Bateson's discovery that genes can suppress the phenotypic effects of other genes, gene interactions-called epistasis-have been the topic of a vast research effort. Systems and developmental biologists study epistasis to understand the genotype -phenotype map, whereas evolutionary biologists recognize the fundamental importance of epistasis for evolution. Depending on its form, epistasis may lead to divergence and speciation, provide evolutionary benefits to sex and affect the robustness and evolvability of organisms. That epistasis can itself be shaped by evolution has only recently been realized. Here, we review the empirical pattern of epistasis, and some of the factors that may affect the form and extent of epistasis. Based on their divergent consequences, we distinguish between interactions with or without mean effect, and those affecting the magnitude of fitness effects or their sign. Empirical work has begun to quantify epistasis in multiple dimensions in the context of metabolic and fitness landscape models. We discuss possible proximate causes (such as protein function and metabolic networks) and ultimate factors (including mutation, recombination, and the importance of natural selection and genetic drift). We conclude that, in general, pleiotropy is an important prerequisite for epistasis, and that epistasis may evolve as an adaptive or intrinsic consequence of changes in genetic robustness and evolvability.

The hyperneuronal activity of the occipital cortex is consistent with general cortical hyperexcitability in migraine.

Identification of the selective forces contributing to the origin and maintenance of sex is a fundamental problem in biology. The Fisher–Muller model proposes that sex is advantageous because it allows beneficial mutations that arise in different lineages to recombine, thereby reducing clonal interference and speeding adaptation. I used the F plasmid to mediate recombination in the bacterium Escherichia coli and measured its effect on adaptation at high and low mutation rates. Recombination increased the rate of adaptation ∼3-fold more in the high mutation rate treatment, where beneficial mutations had to compete for fixation. Sequencing of candidate loci revealed the presence of a beneficial mutation in six high mutation rate lines. In the absence of recombination, this mutation took longer to fix and, over the course of its substitution, conferred a reduced competitive advantage, indicating interference between competing beneficial mutations. Together, these results provide experimental support for the Fisher–Muller model and demonstrate that plasmid-mediated gene transfer can accelerate bacterial adaptation.

BackgroundEnvironmental conditions affect the topology of the adaptive landscape and thus the trajectories followed by evolving populations. For example, a heterogeneous environment might lead to a more rugged adaptive landscape, making it more likely that replicate populations would evolve toward distinct adaptive peaks, relative to a uniform environment. To date, the influence of environmental variability on evolutionary dynamics has received relatively little experimental study.ResultsWe report findings from an experiment designed to test the effects of environmental variability on the adaptation and divergence of replicate populations of E. coli. A total of 42 populations evolved for 2000 generations in 7 environmental regimes that differed in the number, identity, and presentation of the limiting resource. Regimes were organized in two sets, having the sugars glucose and maltose singly and in combination, or glucose and lactose singly and in combination. Combinations of sugars were presented either simultaneously or as temporally fluctuating resource regimes. This design allowed us to compare the effects of resource identity and presentation on the evolutionary trajectories followed by replicate populations. After 2000 generations, the fitness of all populations had increased relative to the common ancestor, but to different extents. Populations evolved in glucose improved the least, whereas populations evolving in maltose or lactose increased the most in their respective sets. Among-population divergence also differed across regimes, with variation higher in those groups that evolved in fluctuating environments than in those that faced constant resource regimens. This divergence under the fluctuating conditions increased between 1000 and 2000 generations, consistent with replicate populations evolving toward distinct adaptive peaks.ConclusionsThese results support the hypothesis that environmental heterogeneity can give rise to more rugged adaptive landscapes, which in turn promote evolutionary diversification. These results also demonstrate that this effect depends on the form of environmental heterogeneity, with greater divergence when the pairs of resources fluctuated temporally rather than being presented simultaneously.

Determining the fitness of specific microbial genotypes has extensive application in microbial genetics, evolution, and biotechnology. While estimates from growth curves are simple and allow high throughput, they are inaccurate and do not account for interactions between costs and benefits accruing over different parts of a growth cycle. For this reason, pairwise competition experiments are the current “gold standard” for accurate estimation of fitness. However, competition experiments require distinct markers, making them difficult to perform between isolates derived from a common ancestor or between isolates of nonmodel organisms. In addition, competition experiments require that competing strains be grown in the same environment, so they cannot be used to infer the fitness consequence of different environmental perturbations on the same genotype. Finally, competition experiments typically consider only the end-points of a period of competition so that they do not readily provide information on the growth differences that underlie competitive ability. Here, we describe a computational approach for predicting density-dependent microbial growth in a mixed culture utilizing data from monoculture and mixed-culture growth curves. We validate this approach using 2 different experiments with Escherichia coli and demonstrate its application for estimating relative fitness. Our approach provides an effective way to predict growth and infer relative fitness in mixed cultures.