Cheating does not explain selective differences at high and low relatedness in a social amoeba

<p>Abstract</p> <p>Background</p> <p>Altruism can be favored by high relatedness among interactants. We tested the effect of relatedness in experimental populations of the social amoeba <it>Dictyostelium discoideum</it>, where altruism occurs in a starvation-induced social stage when some amoebae die to form a stalk that lifts the fertile spores above the soil facilitating dispersal. The single cells that aggregate during the social stage can be genetically diverse, which can lead to conflict over spore and stalk allocation. We mixed eight genetically distinct wild isolates and maintained twelve replicated populations at a high and a low relatedness treatment. After one and ten social generations we assessed the strain composition of the populations. We expected that some strains would be out-competed in both treatments. In addition, we expected that low relatedness might allow the persistence of social cheaters as it provides opportunity to exploit other strains.</p> <p>Results</p> <p>We found that at high relatedness a single clone prevailed in all twelve populations. At low relatedness three clones predominated in all twelve populations. Interestingly, exploitation of some clones by others in the social stage did not explain the results. When we mixed each winner against the pool of five losers, the winner did not prevail in the spores because all contributed fairly to the stalk and spores. Furthermore, the dominant clone at high-relatedness was not cheated by the other two that persisted at low relatedness. A combination of high spore production and short unicellular stage most successfully explained the three successful clones at low relatedness, but not why one of them fared better at high relatedness. Differences in density did not account for the results, as the clones did not differ in vegetative growth rates nor did they change the growth rates over relevant densities.</p> <p>Conclusions</p> <p>These results suggest that social competition and something beyond solitary growth differences occurs during the vegetative stage when amoebae eat bacteria and divide by binary fission. The high degree of repeatability of our results indicates that these effects are strong and points to the importance of new approaches to studying interactions in <it>D. discoideum</it>.</p

Small changes in enzyme function can lead to surprisingly large fitness effects during adaptive evolution of antibiotic resistance

In principle, evolutionary outcomes could be largely predicted if all of the relevant physicochemical variants of a particular protein function under selection were known and integrated into an appropriate physiological model. We have tested this principle by generating a family of variants of the tetracycline resistance protein TetX2 and identified the physicochemical properties most correlated with organismal fitness. Surprisingly, small changes in the Km(MCN), less than twofold, were sufficient to produce highly successful adaptive mutants over clinically relevant drug concentrations. We then built a quantitative model directly relating the in vitro physicochemical properties of the mutant enzymes to the growth rates of bacteria carrying a single chromosomal copy of the tet(X2) variants over a wide range of minocycline (MCN) concentrations. Importantly, this model allows the prediction of enzymatic properties directly from cellular growth rates as well as the physicochemical-fitness landscape of TetX2. Using experimental evolution and deep sequencing to monitor the allelic frequencies of the seven most biochemically efficient TetX2 mutants in 10 independently evolving populations, we showed that the model correctly predicted the success of the two most beneficial variants tet(X2)T280A and tet(X2)N371I. The structure of the most efficient variant, TetX2T280A, in complex with MCN at 2.7 Å resolution suggests an indirect effect on enzyme kinetics. Taken together, these findings support an important role for readily accessible small steps in protein evolution that can, in turn, greatly increase the fitness of an organism during natural selection

Whole Genome Sequencing of Mutation Accumulation Lines Reveals a Low Mutation Rate in the Social Amoeba Dictyostelium discoideum

Spontaneous mutations play a central role in evolution. Despite their importance, mutation rates are some of the most elusive parameters to measure in evolutionary biology. The combination of mutation accumulation (MA) experiments and whole-genome sequencing now makes it possible to estimate mutation rates by directly observing new mutations at the molecular level across the whole genome. We performed an MA experiment with the social amoeba Dictyostelium discoideum and sequenced the genomes of three randomly chosen lines using high-throughput sequencing to estimate the spontaneous mutation rate in this model organism. The mitochondrial mutation rate of 6.76×10(-9), with a Poisson confidence interval of 4.1×10(-9) - 9.5×10(-9), per nucleotide per generation is slightly lower than estimates for other taxa. The mutation rate estimate for the nuclear DNA of 2.9×10(-11), with a Poisson confidence interval ranging from 7.4×10(-13) to 1.6×10(-10), is the lowest reported for any eukaryote. These results are consistent with low microsatellite mutation rates previously observed in D. discoideum and low levels of genetic variation observed in wild D. discoideum populations. In addition, D. discoideum has been shown to be quite resistant to DNA damage, which suggests an efficient DNA-repair mechanism that could be an adaptation to life in soil and frequent exposure to intracellular and extracellular mutagenic compounds. The social aspect of the life cycle of D. discoideum and a large portion of the genome under relaxed selection during vegetative growth could also select for a low mutation rate. This hypothesis is supported by a significantly lower mutation rate per cell division in multicellular eukaryotes compared with unicellular eukaryotes

Variation, Sex, and Social Cooperation: Molecular Population Genetics of the Social Amoeba Dictyostelium discoideum

Dictyostelium discoideum is a eukaryotic microbial model system for multicellular development, cell–cell signaling, and social behavior. Key models of social evolution require an understanding of genetic relationships between individuals across the genome or possibly at specific genes, but the nature of variation within D. discoideum is largely unknown. We re-sequenced 137 gene fragments in wild North American strains of D. discoideum and examined the levels and patterns of nucleotide variation in this social microbial species. We observe surprisingly low levels of nucleotide variation in D. discoideum across these strains, with a mean nucleotide diversity (π) of 0.08%, and no strong population stratification among North American strains. We also do not find any clear relationship between nucleotide divergence between strains and levels of social dominance and kin discrimination. Kin discrimination experiments, however, show that strains collected from the same location show greater ability to distinguish self from non-self than do strains from different geographic areas. This suggests that a greater ability to recognize self versus non-self may arise among strains that are more likely to encounter each other in nature, which would lead to preferential formation of fruiting bodies with clonemates and may prevent the evolution of cheating behaviors within D. discoideum populations. Finally, despite the fact that sex has rarely been observed in this species, we document a rapid decay of linkage disequilibrium between SNPs, the presence of recombinant genotypes among natural strains, and high estimates of the population recombination parameter ρ. The SNP data indicate that recombination is widespread within D. discoideum and that sex as a form of social interaction is likely to be an important aspect of the life cycle

Amino Acid Repeats Cause Extraordinary Coding Sequence Variation in the Social Amoeba Dictyostelium discoideum

Protein sequences are normally the most conserved elements of genomes owing to purifying selection to maintain their functions. We document an extraordinary amount of within-species protein sequence variation in the model eukaryote Dictyostelium discoideum stemming from triplet DNA repeats coding for long strings of single amino acids. D. discoideum has a very large number of such strings, many of which are polyglutamine repeats, the same sequence that causes various human neurological disorders in humans, like Huntington's disease. We show here that D. discoideum coding repeat loci are highly variable among individuals, making D. discoideum a candidate for the most variable proteome. The coding repeat loci are not significantly less variable than similar non-coding triplet repeats. This pattern is consistent with these amino-acid repeats being largely non-functional sequences evolving primarily by mutation and drift

The Repeatability of Adaptive Radiation During Long-Term Experimental Evolution of Escherichia coli in a Multiple Nutrient Environment

Adaptive radiations occur when a species diversifies into different ecological specialists due to competition for resources and trade-offs associated with the specialization. The evolutionary outcome of an instance of adaptive radiation cannot generally be predicted because chance (stochastic events) and necessity (deterministic events) contribute to the evolution of diversity. With increasing contributions of chance, the degree of parallelism among different instances of adaptive radiations and the predictability of an outcome will decrease. To assess the relative contributions of chance and necessity during adaptive radiation, we performed a selection experiment by evolving twelve independent microcosms of Escherichia coli for 1000 generations in an environment that contained two distinct resources. Specialization to either of these resources involves strong trade-offs in the ability to use the other resource. After selection, we measured three phenotypic traits: 1) fitness, 2) mean colony size, and 3) colony size diversity. We used fitness relative to the ancestor as a measure of adaptation to the selective environment; changes in colony size as a measure of the evolution of new resource specialists because colony size has been shown to correlate with resource specialization; and colony size diversity as a measure of the evolved ecological diversity. Resource competition led to the rapid evolution of phenotypic diversity within microcosms. Measurements of fitness, colony size, and colony size diversity within and among microcosms showed that the repeatability of adaptive radiation was high, despite the evolution of genetic variation within microcosms. Consistent with the observation of parallel evolution, we show that the relative contributions of chance are far smaller and less important than effects due to adaptation for the traits investigated. The two-resource environment imposed similar selection pressures in independent populations and promoted parallel phenotypic adaptive radiations in all independently evolved microcosms

Density_and_colony(H)

This file contains the colony counts over the course of the selection experiment. This data was used to calculate the population density and the population diversity, calculated as Shannon-Wiener index H

Diversity_and_Fitness

This file contains the relative fitness data and diversity data calculated as CV* for generations 500 and 100

Relative contributions of adaptation were larger than chance.

<p>Relative contributions of adaptation and chance to (A) fitness, (B) mean colony size and (C) colony size diversity. Error bars represent 95% confidence intervals. The effect of adaptation was measured as the difference between the mean trait value of the derived populations and the trait value of the ancestor. The effect of chance was calculated as the square root of the genetic variation among microcosms.</p

Diverse colony morphologies evolved in all twelve microcosms.

<p>(A) Colony size diversity after 1000 generations of selection. Populations are grouped by arabinose marker (ara+ and ara−), with the ancestors 606 (ara−) and 607 (ara+) to the left and the derived populations on the right. (B) Colony size diversification of the 12 microcosms. Colony size diversity (H') was calculated for every population using the Shannon-Wiener index. Each point represents the mean of colony size diversity (H') of all 12 microcosms. Error bars represent 95% confidence intervals.</p