734 research outputs found
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
Diversity in CRISPR-based immunity protects susceptible genotypes by restricting phage spread and evolution.
This is the final version. Available from the publisher via the DOI in this record.Data deposited at dryad: https://doi.org/10.5061/dryad.66t1g1k00.Diversity in host resistance often associates with reduced pathogen spread. This may result from ecological and evolutionary processes, likely with feedback between them. Theory and experiments on bacteria-phage interactions have shown that genetic diversity of the bacterial adaptive immune system can limit phage evolution to overcome resistance. Using the CRISPR-Cas bacterial immune system and lytic phage, we engineered a host-pathogen system where each bacterial host genotype could be infected by only one phage genotype. With this model system, we explored how CRISPR diversity impacts the spread of phage when they can overcome a resistance allele, how immune diversity affects the evolution of the phage to increase its host range, and if there was feedback between these processes. We show that increasing CRISPR diversity benefits susceptible bacteria via a dilution effect, which limits the spread of the phage. We suggest that this ecological effect impacts the evolution of novel phage genotypes, which then feeds back into phage population dynamics
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Coevolution Drives the Emergence of Complex Traits and Promotes Evolvability
The evolution of complex organismal traits is obvious as a historical fact, but the underlying causes—including the role of natural selection—are contested. Gould argued that a random walk from a necessarily simple beginning would produce the appearance of increasing complexity over time. Others contend that selection, including coevolutionary arms races, can systematically push organisms toward more complex traits. Methodological challenges have largely precluded experimental tests of these hypotheses. Using the Avida platform for digital evolution, we show that coevolution of hosts and parasites greatly increases organismal complexity relative to that otherwise achieved. As parasites evolve to counter the rise of resistant hosts, parasite populations retain a genetic record of past coevolutionary states. As a consequence, hosts differentially escape by performing progressively more complex functions. We show that coevolution's unique feedback between host and parasite frequencies is a key process in the evolution of complexity. Strikingly, the hosts evolve genomes that are also more phenotypically evolvable, similar to the phenomenon of contingency loci observed in bacterial pathogens. Because coevolution is ubiquitous in nature, our results support a general model whereby antagonistic interactions and natural selection together favor both increased complexity and evolvability
Evolution Equation of Phenotype Distribution: General Formulation and Application to Error Catastrophe
An equation describing the evolution of phenotypic distribution is derived
using methods developed in statistical physics. The equation is solved by using
the singular perturbation method, and assuming that the number of bases in the
genetic sequence is large. Applying the equation to the mutation-selection
model by Eigen provides the critical mutation rate for the error catastrophe.
Phenotypic fluctuation of clones (individuals sharing the same gene) is
introduced into this evolution equation. With this formalism, it is found that
the critical mutation rate is sometimes increased by the phenotypic
fluctuations, i.e., noise can enhance robustness of a fitted state to mutation.
Our formalism is systematic and general, while approximations to derive more
tractable evolution equations are also discussed.Comment: 22 pages, 2 figure
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
Evolutionary trajectories in rugged fitness landscapes
We consider the evolutionary trajectories traced out by an infinite
population undergoing mutation-selection dynamics in static, uncorrelated
random fitness landscapes. Starting from the population that consists of a
single genotype, the most populated genotype \textit{jumps} from a local
fitness maximum to another and eventually reaches the global maximum. We use a
strong selection limit, which reduces the dynamics beyond the first time step
to the competition between independent mutant subpopulations, to study the
dynamics of this model and of a simpler one-dimensional model which ignores the
geometry of the sequence space. We find that the fit genotypes that appear
along a trajectory are a subset of suitably defined fitness \textit{records},
and exploit several results from the record theory for non-identically
distributed random variables. The genotypes that contribute to the trajectory
are those records that are not \textit{bypassed} by superior records arising
further away from the initial population. Several conjectures concerning the
statistics of bypassing are extracted from numerical simulations. In
particular, for the one-dimensional model, we propose a simple relation between
the bypassing probability and the dynamic exponent which describes the scaling
of the typical evolution time with genome size. The latter can be determined
exactly in terms of the extremal properties of the fitness distribution.Comment: Figures in color; minor revisions in tex
Live to cheat another day: bacterial dormancy facilitates the social exploitation of beta-lactamases
The breakdown of antibiotics by β-lactamases may be cooperative, since resistant cells can detoxify their environment and facilitate the growth of susceptible neighbours. However, previous studies of this phenomenon have used artificial bacterial vectors or engineered bacteria to increase the secretion of β-lactamases from cells. Here, we investigated whether a broad-spectrum β-lactamase gene carried by a naturally occurring plasmid (pCT) is cooperative under a range of conditions. In ordinary batch culture on solid media, there was little or no evidence that resistant bacteria could protect susceptible cells from ampicillin, although resistant colonies could locally detoxify this growth medium. However, when susceptible cells were inoculated at high densities, late-appearing phenotypically susceptible bacteria grew in the vicinity of resistant colonies. We infer that persisters, cells that have survived antibiotics by undergoing a period of dormancy, founded these satellite colonies. The number of persister colonies was positively correlated with the density of resistant colonies and increased as antibiotic concentrations decreased. We argue that detoxification can be cooperative under a limited range of conditions: if the toxins are bacteriostatic rather than bacteridical; or if susceptible cells invade communities after resistant bacteria; or if dormancy allows susceptible cells to avoid bactericides. Resistance and tolerance were previously thought to be independent solutions for surviving antibiotics. Here, we show that these are interacting strategies: the presence of bacteria adopting one solution can have substantial effects on the fitness of their neighbours
Knowledge politics and new converging technologies: a social epistemological perspective
The “new converging technologies” refers to the prospect of advancing the human condition by the integrated study and application of nanotechnology, biotechnology, information technology and the cognitive sciences - or “NBIC”. In recent years, it has loomed large, albeit with somewhat different emphases, in national science policy agendas throughout the world. This article considers the political and intellectual sources - both historical and contemporary - of the converging technologies agenda. Underlying it is a fluid conception of humanity that is captured by the ethically challenging notion of “enhancing evolution”
Signatures of arithmetic simplicity in metabolic network architecture
Metabolic networks perform some of the most fundamental functions in living
cells, including energy transduction and building block biosynthesis. While
these are the best characterized networks in living systems, understanding
their evolutionary history and complex wiring constitutes one of the most
fascinating open questions in biology, intimately related to the enigma of
life's origin itself. Is the evolution of metabolism subject to general
principles, beyond the unpredictable accumulation of multiple historical
accidents? Here we search for such principles by applying to an artificial
chemical universe some of the methodologies developed for the study of genome
scale models of cellular metabolism. In particular, we use metabolic flux
constraint-based models to exhaustively search for artificial chemistry
pathways that can optimally perform an array of elementary metabolic functions.
Despite the simplicity of the model employed, we find that the ensuing pathways
display a surprisingly rich set of properties, including the existence of
autocatalytic cycles and hierarchical modules, the appearance of universally
preferable metabolites and reactions, and a logarithmic trend of pathway length
as a function of input/output molecule size. Some of these properties can be
derived analytically, borrowing methods previously used in cryptography. In
addition, by mapping biochemical networks onto a simplified carbon atom
reaction backbone, we find that several of the properties predicted by the
artificial chemistry model hold for real metabolic networks. These findings
suggest that optimality principles and arithmetic simplicity might lie beneath
some aspects of biochemical complexity
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