Dynamic fitness landscapes: Expansions for small mutation rates

We study the evolution of asexual microorganisms with small mutation rate in fluctuating environments, and develop techniques that allow us to expand the formal solution of the evolution equations to first order in the mutation rate. Our method can be applied to both discrete time and continuous time systems. While the behavior of continuous time systems is dominated by the average fitness landscape for small mutation rates, in discrete time systems it is instead the geometric mean fitness that determines the system's properties. In both cases, we find that in situations in which the arithmetic (resp. geometric) mean of the fitness landscape is degenerate, regions in which the fitness fluctuates around the mean value present a selective advantage over regions in which the fitness stays at the mean. This effect is caused by the vanishing genetic diffusion at low mutation rates. In the absence of strong diffusion, a population can stay close to a fluctuating peak when the peak's height is below average, and take advantage of the peak when its height is above average.Comment: 19 pages Latex, elsart style, 4 eps figure

Field theory for a reaction-diffusion model of quasispecies dynamics

RNA viruses are known to replicate with extremely high mutation rates. These rates are actually close to the so-called error threshold. This threshold is in fact a critical point beyond which genetic information is lost through a second-order phase transition, which has been dubbed the ``error catastrophe.'' Here we explore this phenomenon using a field theory approximation to the spatially extended Swetina-Schuster quasispecies model [J. Swetina and P. Schuster, Biophys. Chem. {\bf 16}, 329 (1982)], a single-sharp-peak landscape. In analogy with standard absorbing-state phase transitions, we develop a reaction-diffusion model whose discrete rules mimic the Swetina-Schuster model. The field theory representation of the reaction-diffusion system is constructed. The proposed field theory belongs to the same universality class than a conserved reaction-diffusion model previously proposed [F. van Wijland {\em et al.}, Physica A {\bf 251}, 179 (1998)]. From the field theory, we obtain the full set of exponents that characterize the critical behavior at the error threshold. Our results present the error catastrophe from a new point of view and suggest that spatial degrees of freedom can modify several mean field predictions previously considered, leading to the definition of characteristic exponents that could be experimentally measurable.Comment: 13 page

Optimal timing of contrast-enhanced three-dimensional magnetic resonance left atrial angiography before pulmonary vein ablation

Background: To achieve high image quality of cardiovascular magnetic resonance (CMR) pulmonary vein (PV) angiography prior catheter ablation in patients with atrial fibrillation, optimal timing of the angiographic sequence during contrast agent passage is important. The present study identified influential cardiovascular parameters for prediction of contrast agent travel time.Methods: One hundred six consecutive patients underwent a CMR examination including three-dimensional (3D) contrast-enhanced PV angiography with real-time bolus tracking prior to catheter ablation. Correct scan timing was characterized by relative signal enhancement measurements in the pulmonary artery, left atrium (LA), and ascending aorta. Furthermore, left- and right-ventricular function, left- and right-atrial dimensions, presence of mitral or tricuspid insufficiencies, and main pulmonary artery diameter were determined.Results: The highest relative signal enhancement in LA demonstrated optimal scan timing. Contrast agent travel time showed wide variability (range: 12–42 s; mean: 18 ± 4 s). On univariate analysis, most cardiovascular parameters correlated with contrast agent travel time while on multivariate analysis left- and right-ventricular function remained the only independent predictors, but overall a poor fit to the data (adjusted R2, 27.5%) was found.Conclusions: Contrast agent travel time was mainly influenced by left- and right-ventricular function but prediction models poorly fitted the data. Thus, 3D PV angiography prior to PV ablation procedures necessitates real-time assessment, with visual determination of individual contrast agent passage time to ensure consistently high CMR image quality

Error Thresholds on Dynamic Fittness-Landscapes

In this paper we investigate error-thresholds on dynamics fitness-landscapes. We show that there exists both lower and an upper threshold, representing limits to the copying fidelity of simple replicators. The lower bound can be expressed as a correction term to the error-threshold present on a static landscape. The upper error-threshold is a new limit that only exists on dynamic fitness-landscapes. We also show that for long genomes on highly dynamic fitness-landscapes there exists a lower bound on the selection pressure needed to enable effective selection of genomes with superior fitness independent of mutation rates, i.e., there are distinct limits to the evolutionary parameters in dynamic environments.Comment: 5 page

Error thresholds for self- and cross-specific enzymatic replication

The information content of a non-enzymatic self-replicator is limited by Eigen's error threshold. Presumably, enzymatic replication can maintain higher complexity, but in a competitive environment such a replicator is faced with two problems related to its twofold role as enzyme and substrate: as enzyme, it should replicate itself rather than wastefully copy non-functional substrates, and as substrate it should preferably be replicated by superior enzymes instead of less-efficient mutants. Because specific recognition can enforce these propensities, we thoroughly analyze an idealized quasispecies model for enzymatic replication, with replication rates that are either a decreasing (self-specific) or increasing (cross-specific) function of the Hamming distance between the recognition or "tag" sequences of enzyme and substrate. We find that very weak self-specificity suffices to localize a population about a master sequence and thus to preserve its information, while simultaneous localization about complementary sequences in the cross-specific case is more challenging. A surprising result is that stronger specificity constraints allow longer recognition sequences, because the populations are better localized. Extrapolating from experimental data, we obtain rough quantitative estimates for the maximal length of the recognition or tag sequence that can be used to reliably discriminate appropriate and infeasible enzymes and substrates, respectively.Comment: 23 pages, 7 figures; final version as publishe

Quasispecies Spatial Models for RNA Viruses with Different Replication Modes and Infection Strategies

Empirical observations and theoretical studies suggest that viruses may use different replication strategies to amplify their genomes, which impact the dynamics of mutation accumulation in viral populations and therefore, their fitness and virulence. Similarly, during natural infections, viruses replicate and infect cells that are rarely in suspension but spatially organized. Surprisingly, most quasispecies models of virus replication have ignored these two phenomena. In order to study these two viral characteristics, we have developed stochastic cellular automata models that simulate two different modes of replication (geometric vs stamping machine) for quasispecies replicating and spreading on a two-dimensional space. Furthermore, we explored these two replication models considering epistatic fitness landscapes (antagonistic vs synergistic) and different scenarios for cell-to-cell spread, one with free superinfection and another with superinfection inhibition. We found that the master sequences for populations replicating geometrically and with antagonistic fitness effects vanished at low critical mutation rates. By contrast, the highest critical mutation rate was observed for populations replicating geometrically but with a synergistic fitness landscape. Our simulations also showed that for stamping machine replication and antagonistic epistasis, a combination that appears to be common among plant viruses, populations further increased their robustness by inhibiting superinfection. We have also shown that the mode of replication strongly influenced the linkage between viral loci, which rapidly reached linkage equilibrium at increasing mutations for geometric replication. We also found that the strategy that minimized the time required to spread over the whole space was the stamping machine with antagonistic epistasis among mutations. Finally, our simulations revealed that the multiplicity of infection fluctuated but generically increased along time