Evolution of Biological Complexity

In order to make a case for or against a trend in the evolution of complexity in biological evolution, complexity needs to be both rigorously defined and measurable. A recent information-theoretic (but intuitively evident) definition identifies genomic complexity with the amount of information a sequence stores about its environment. We investigate the evolution of genomic complexity in populations of digital organisms and monitor in detail the evolutionary transitions that increase complexity. We show that because natural selection forces genomes to behave as a natural ``Maxwell Demon'', within a fixed environment genomic complexity is forced to increase.Comment: LaTeX 19 pages, incl. 4 fig

The Genetic coding style of digital organisms

Recently, all the human genes were identified. But understanding the functions coded in the genes is of course a much harder problem. We are used to view DNA as some sort of a computer code, but there are striking differences. For example, by using entropy, it has been shown that the DNA code is much closer to random code than written text, which in turn is less ordered than ordinary computer code. Instead of saying that the DNA is badly written, using common programming standards, we might say that it is written in a different style − an evolutionary style. In this paper the coding style of creatures from the artificial life platform Avida has been studied. Avida creatures that have evolved under different size merit methods and mutation rates have been analysed using the notion of stylistic measures. The analysis has shown that the evolutionary coding style depends on the environment in which the code evolved, and that the choice of size merit method and mutation probabilities affect different stylistic properties of the genome. A better understanding of Avida’s coding style, might eventually lead to insights of evolutionary codes in general

Increased susceptibility to repeated freeze-thaw cycles in Escherichia coli following long-term evolution in a benign environment

BACKGROUND: In order to study the dynamics of evolutionary change, 12 populations of E. coli B were serially propagated for 20,000 generations in minimal glucose medium at constant 37°C. Correlated changes in various other traits have been previously associated with the improvement in competitive fitness in the selective environment. This study examines whether these evolved lines changed in their ability to tolerate the stresses of prolonged freezing and repeated freeze-thaw cycles during adaptation to a benign environment. RESULTS: All 12 lines that evolved in the benign environment for 20,000 generations are more sensitive to freeze-thaw cycles than their ancestor. The evolved lines have an average mortality rate of 54% per daily cycle, compared to the ancestral rate of 34%. By contrast, there was no significant difference between the evolved lines and their ancestor in mortality during prolonged freezing. There was also some variability among the evolved lines in susceptibility to repeated freeze-thaw cycles. Those lines that had evolved higher competitive fitness in the minimal glucose medium at 37°C also had higher mortality during freeze-thaw cycles. This variability was not associated, however, with differences among lines in DNA repair functionality and mutability. CONCLUSION: The consistency of the evolutionary declines in freeze-thaw tolerance, the correlation between fitness in glucose medium at 37°C and mortality during freeze-thaw cycles, and the absence of greater declines in freeze-thaw survival among the hypermutable lines all indicate a trade-off between performance in minimal glucose medium at 37°C and the capacity to tolerate this stress. Analyses of the mutations that enhance fitness at 37°C may shed light on the physiological basis of this trade-off

Does the Red Queen reign in the kingdom of digital organisms?

In competition experiments between two RNA viruses of equal or almost equal fitness, often both strains gain in fitness before one eventually excludes the other. This observation has been linked to the Red Queen effect, which describes a situation in which organisms have to constantly adapt just to keep their status quo. I carried out experiments with digital organisms (self-replicating computer programs) in order to clarify how the competing strains' location in fitness space influences the Red-Queen effect. I found that gains in fitness during competition were prevalent for organisms that were taken from the base of a fitness peak, but absent or rare for organisms that were taken from the top of a peak or from a considerable distance away from the nearest peak. In the latter two cases, either neutral drift and loss of the fittest mutants or the waiting time to the first beneficial mutation were more important factors. Moreover, I found that the Red-Queen dynamic in general led to faster exclusion than the other two mechanisms.Comment: 10 pages, 5 eps figure

Metabolic modelling in a dynamic evolutionary framework predicts adaptive diversification of bacteria in a long-term evolution experiment

Background: Predicting adaptive trajectories is a major goal of evolutionary biology and useful for practical applications. Systems biology has enabled the development of genome-scale metabolic models. However, analysing these models via flux balance analysis (FBA) cannot predict many evolutionary outcomes including adaptive diversification, whereby an ancestral lineage diverges to fill multiple niches. Here we combine in silico evolution with FBA and apply this modelling framework, evoFBA, to a long-term evolution experiment with Escherichia coli. Results: Simulations predicted the adaptive diversification that occurred in one experimental population and generated hypotheses about the mechanisms that promoted coexistence of the diverged lineages. We experimentally tested and, on balance, verified these mechanisms, showing that diversification involved niche construction and character displacement through differential nutrient uptake and altered metabolic regulation. Conclusion: The evoFBA framework represents a promising new way to model biochemical evolution, one that can generate testable predictions about evolutionary and ecosystem-level outcomes

Surface state engineering of molecule-molecule interactions

Engineering the electronic structure of organics through interface manipulation, particularly the interface dipole and the barriers to charge carrier injection, is of essential importance to improved organic devices. This requires the meticulous fabrication of desired organic structures by precisely controlling the interactions between molecules. The well-known principles of organic coordination chemistry cannot be applied without proper consideration of extra molecular hybridization, charge transer and dipole formation at the interfaces. Here we identify the interplay between energy level alignment, charge transfer, surface dipole and charge pillow effect and show how these effects collectively determine the net force between adsorbed porphyrin 2H-TPP on Cu(111). We show that the forces between supported porphyrins can be altered by controlling the amount of charge transferred across the interface accurately through the relative alignment of molecular electronic levels with respect to the Shockley surface state of the metal substrate, and hence govern the self-assembly of the molecules

Selective pressures on genomes in molecular evolution

We describe the evolution of macromolecules as an information transmission process and apply tools from Shannon information theory to it. This allows us to isolate three independent, competing selective pressures that we term compression, transmission, and neutrality selection. The first two affect genome length: the pressure to conserve resources by compressing the code, and the pressure to acquire additional information that improves the channel, increasing the rate of information transmission into each offspring. Noisy transmission channels (replication with mutations) gives rise to a third pressure that acts on the actual encoding of information; it maximizes the fraction of mutations that are neutral with respect to the phenotype. This neutrality selection has important implications for the evolution of evolvability. We demonstrate each selective pressure in experiments with digital organisms.Comment: 16 pages, 3 figures, to be published in J. theor. Biolog

Evolutionary instability of Zero Determinant strategies demonstrates that winning isn't everything

Zero Determinant (ZD) strategies are a new class of probabilistic and conditional strategies that are able to unilaterally set the expected payoff of an opponent in iterated plays of the Prisoner's Dilemma irrespective of the opponent's strategy, or else to set the ratio between a ZD player's and their opponent's expected payoff. Here we show that while ZD strategies are weakly dominant, they are not evolutionarily stable and will instead evolve into less coercive strategies. We show that ZD strategies with an informational advantage over other players that allows them to recognize other ZD strategies can be evolutionarily stable (and able to exploit other players). However, such an advantage is bound to be short-lived as opposing strategies evolve to counteract the recognition.Comment: 14 pages, 4 figures. Change in title (again!) to comply with Nature Communications requirements. To appear in Nature Communication

Mutator Dynamics on a Smooth Evolutionary Landscape

We investigate a model of evolutionary dynamics on a smooth landscape which features a ``mutator'' allele whose effect is to increase the mutation rate. We show that the expected proportion of mutators far from equilibrium, when the fitness is steadily increasing in time, is governed solely by the transition rates into and out of the mutator state. This results is a much faster rate of fitness increase than would be the case without the mutator allele. Near the fitness equilibrium, however, the mutators are severely suppressed, due to the detrimental effects of a large mutation rate near the fitness maximum. We discuss the results of a recent experiment on natural selection of E. coli in the light of our model.Comment: 4 pages, 3 figure