Eigen Model Research Articles

Variability in mutational fitness effects prevents full lethal transitions in large quasispecies populations

The distribution of mutational fitness effects (DMFE) is crucial to the evolutionary fate of quasispecies. In this article we analyze the effect of the DMFE on the dynamics of a large quasispecies by means of a phenotypic version of the classic Eigen's model that incorporates beneficial, neutral, deleterious, and lethal mutations. By parameterizing the model with available experimental data on the DMFE of Vesicular stomatitis virus (VSV) and Tobacco etch virus (TEV), we found that increasing mutation does not totally push the entire viral quasispecies towards deleterious or lethal regions of the phenotypic sequence space. The probability of finding regions in the parameter space of the general model that results in a quasispecies only composed by lethal phenotypes is extremely small at equilibrium and in transient times. The implications of our findings can be extended to other scenarios, such as lethal mutagenesis or genomically unstable cancer, where increased mutagenesis has been suggested as a potential therapy.

Eigen model of randomness in species evolution

We modify the deterministic Eigen model of species evolution into a randomized model in order to render the Eigen model more realistic for the description of species evolution. In the framework of the Eigen model, we regard the locus mutation rate of a genetic sequence as a Gaussian distributed random variable. Thus the Eigen model turns into a random model. In this randomized model, we can see that when the fluctuation strength of the mutation rate is small, the error threshold of the quasispecies changes slightly and still serves as a phase transition point. However, when the fluctuation strength becomes large, the error threshold shifts from a phase transition point into a crossover region. Since the error threshold in the real species evolution is a crossover region, we should consider the upper limit of the crossover region when dealing with practical problems.

Prediction of Folding Defect in Transitional Region during Local Loading Forming of Titanium Alloy Large-scale Rib-web Component

A prediction model for the folding defect in transitional region during local loading forming of titanium alloy large-scale rib-web component was developed by the combination of finite element simulation, space-filling Maximin Latin hypercube designs method and back-propagation neural network. The FE model of local eigen model of transitional region during local loading forming of large-scale rib-web component was established based on DEFORM-2D and validated by physical experiment. The Maximin Latin hypercube designs method was applied to design uniform experimental schemes with geometrical conditions and reduction amounts as experimental variables. After simulations of the designed experiments, the back-propagation neural network was used to synthesize the data sets (results of folding defect). Finally, a prediction model was established for folding defect judgment in transitional region under various geometrical conditions and reduction amounts during local loading forming of large-scale rib-web components. The predicted results are quite consistent with the results obtained from FE simulation and experiment.

Eigen Model with Correlated Multiple Mutations and Solution of Error Catastrophe Paradox in the Origin of Life

We consider the Eigen model with non-Poisson distribution of mutation number. We apply the Hamilton–Jacobi equation method to solve the model and calculate the mean fitness. We find that the error threshold depends on the correlation, and the suggested mechanism may give a simple solution to the error catastrophe paradox in the origin of life.

On the Relation Between the Eigen Model and the Asexual Wright–Fisher Model

We show that the Eigen model and the asexual Wright-Fisher model can be obtained as two different limit cases of a single stochastic model. This result is used to enlighten the mathematical similarities and differences among these two models.The two key concepts introduced with the Eigen model, the error threshold and the quasispecies, are not invalidated by these differences, so that they are naturally present also in population genetics models. According to this fact, we use the classical diploid mutation-selection equation and the single peak fitness approximation to obtain the error threshold for sexual diploids. Finally, we perform the same analysis in the asexual case and compare the results.

SOME RIGOROUS RESULTS ON THE EIGEN QUASISPECIES MODEL WITH A PERIODICALLY MOVING SHARP-PEAK LANDSCAPE

In this paper we prove some results and detail some calculations published in a previous paper by us on the Eigen model with a periodically moving sharp-peak landscape. The model is concerned with evolution of a virus population in a time-dependent environment mimicking interaction of the viruses with the immune system of a host.

Optimal mutation rates in dynamic environments: The Eigen model

We consider the Eigen quasispecies model with a dynamic environment. For an environment with sharp-peak fitness in which the most-fit sequence moves by k spin-flips each period T we find an asymptotic stationary state in which the quasispecies population changes regularly according to the regular environmental change. From this stationary state we estimate the maximum and the minimum mutation rates for a quasispecies to survive under the changing environment and calculate the optimum mutation rate that maximizes the population growth. Interestingly we find that the optimum mutation rate in the Eigen model is lower than that in the Crow-Kimura model, and at their optimum mutation rates the corresponding mean fitness in the eigenmodel is lower than that in the Crow-Kimura model, suggesting that the mutation process which occurs in parallel to the replication process as in the Crow-Kimura model gives an adaptive advantage under changing environment.

Evolution models with lethal mutations on symmetric or random fitness landscapes

We calculate the mean fitness for evolution models, when the fitness is a function of the Hamming distance from a reference sequence, and there is a probability that this fitness is nullified (Eigen model case) or tends to the negative infinity (Crow-Kimura model case). We calculate the mean fitness of these models. The mean fitness is calculated also for the random fitnesses with logarithmic-normal distribution, reasonably describing sometimes the situation with RNA viruses.

A Stochastic Version of the Eigen Model

We exhibit a stochastic discrete time model that produces the Eigen model (Naturwissenschaften 58:465-523, 1971) in the deterministic and continuous time limits. The model is based on the competition among individuals differing in terms of fecundity but with the same viability. We explicitly write down the Markov matrix of the discrete time stochastic model in the two species case and compute the master sequence concentration numerically for various values of the total population. We also obtain the master equation of the model and perform a Van Kampen expansion. The results obtained in the two species case are compared with those coming from the Eigen model. Finally, we comment on the range of applicability of the various approaches described, when the number of species is larger than two.

Uniqueness of the fixed point for the quasi-species model under changing environments

We investigate the uniqueness of the stable fixed point of the quasi-species models: the Eigen model and the Parallel Mutation-Selection model. Under changing environments with a sharp-peak fitness function where the fitness peak oscillates periodically, we use the Perron-Frobenius theorem to show that the stable fixed point must be unique in those models. By using the symmetry, we also show that the stationary values for the maximum and the minimum population probabilities of the two peak sequences must be equal, respectively.

Relaxation Property and Stability Analysis of the Quasispecies Models

The relaxation property of both Eigen model and Crow–Kimura model with a single peak fitness landscape is studied from phase transition point of view. We first analyze the eigenvalue spectra of the replication mutation matrices. For sufficiently long sequences, the almost crossing point between the largest and second-largest eigenvalues locates the error threshold at which critical slowing down behavior appears. We calculate the critical exponent in the limit of infinite sequence lengths and compare it with the result from numerical curve fittings at sufficiently long sequences. We find that for both models the relaxation time diverges with exponent 1 at the error (mutation) threshold point. Results obtained from both methods agree quite well. From the unlimited correlation length feature, the first order phase transition is further confirmed. Finally with linear stability theory, we show that the two model systems are stable for all ranges of mutation rate. The Eigen model is asymptotically stable in terms of mutant classes, and the Crow–Kimura model is completely stable.

Phase Diagram of the Eigen Model under Changing Environments with a Sharp-Peak Fitness Function

Phase Diagram of the Eigen Model under Changing Environments with a Sharp-Peak Fitness Function

Solution of the Crow-Kimura and Eigen Models for Alphabets of Arbitrary Size by Schwinger Spin Coherent States

To represent the evolution of nucleic acid and protein sequence, we express the parallel and Eigen models for molecular evolution in terms of a functional integral representation with an $h$-letter alphabet, lifting the two-state, purine/pyrimidine assumption often made in quasi-species theory. For arbitrary $h$ and a general mutation scheme, we obtain the solution of this model in terms of a maximum principle. Euler's theorem for homogeneous functions is used to derive this `thermodynamic' formulation of evolution. The general result for the parallel model reduces to known results for the purine/pyrimidine $h=2$ alphabet and the nucleic acid $h=4$ alphabet for the Kimura 3 ST mutation scheme. Examples are presented for the $h=4$ and $h=20$ cases. We derive the maximum principle for the Eigen model for general $h$. The general result for the Eigen model reduces to a known result for $h=2$. Examples are presented for the nucleic acid $h=4$ and the amino acid $h=20$ alphabet. An error catastrophe phase transition occurs in these models, and the order of the phase transition changes from second to first order for smooth fitness functions when the alphabet size is increased beyond two letters to the generic case. As examples, we analyze the general analytic solution for sharp peak, linear, quadratic, and quartic fitness functions.

Accuracies of the empirical theories of the escape probability based on Eigen model and Braun model compared with the exact extension of Onsager theory

This paper deals with the exact extension of the original Onsager theory of the escape probability to the case of finite recombination rate at nonzero reaction radius. The empirical theories based on the Eigen model and the Braun model, which are applicable in the absence and presence of an external electric field, respectively, are based on a wrong assumption that both recombination and separation processes in geminate recombination follow exponential kinetics. The accuracies of the empirical theories are examined against the exact extension of the Onsager theory. The Eigen model gives the escape probability in the absence of an electric field, which is different by a factor of 3 from the exact one. We have shown that this difference can be removed by operationally redefining the volume occupied by the dissociating partner before dissociation, which appears in the Eigen model as a parameter. The Braun model gives the escape probability in the presence of an electric field, which is significantly different from the exact one over the whole range of electric fields. Appropriate modification of the original Braun model removes the discrepancy at zero or low electric fields, but it does not affect the discrepancy at high electric fields. In all the above theories it is assumed that recombination takes place only at the reaction radius. The escape probability in the case when recombination takes place over a range of distances is also calculated and compared with that in the case of recombination only at the reaction radius.

Adaptation dynamics of the quasispecies model

We study the adaptation dynamics of an initially maladapted population evolving via the elementary processes of mutation and selection. The evolution occurs on rugged fitness landscapes which are defined on the multi-dimensional genotypic space and have many local peaks separated by low fitness valleys. We mainly focus on the Eigen's model that describes the deterministic dynamics of an infinite number of self-replicating molecules. In the stationary state, for small mutation rates such a population forms a {\it quasispecies} which consists of the fittest genotype and its closely related mutants. The quasispecies dynamics on rugged fitness landscape follow a punctuated (or step-like) pattern in which a population jumps from a low fitness peak to a higher one, stays there for a considerable time before shifting the peak again and eventually reaches the global maximum of the fitness landscape. We calculate exactly several properties of this dynamical process within a simplified version of the quasispecies model.

Quasispecies distribution of Eigen model

We study sharp peak landscapes (SPL) of Eigen model from a new perspective about how the quasispecies distribute in the sequence space. To analyze the distribution more carefully, we bring forth two tools. One tool is the variance of Hamming distance of the sequences at a given generation. It not only offers us a different avenue for accurately locating the error threshold and illustrates how the configuration of the distribution varies with copying fidelity $q$ in the sequence space, but also divides the copying fidelity into three distinct regimes. The other tool is the similarity network of a certain Hamming distance $d_{0}$, by which we can get a visual and in-depth result about how the sequences distribute. We find that there are several local optima around the center (global optimum) in the distribution of the sequences reproduced near the threshold. Furthermore, it is interesting that the distribution of clustering coefficient $C(k)$ follows lognormal distribution and the curve of clustering coefficient $C$ of the network versus $d_{0}$ appears as linear behavior near the threshold.

A Large Protonated Water Cluster H+(H2O)27 in a 3D Metal−Organic Framework

A large protonated water cluster, H+(H2O)27, has been trapped and stabilized within the well-modulated cavity of a 3D metal-organic framework formed by cobalt(II) and 4,4'-bipyridine-N,N'-dioxide with a globular Keggin structure [PW12O4]3- anion as template. The structurally characterized protonated water cluster might comprise a (H2O)26 shell with Oh symmetry and a monowater core within the center which is suggested to be a hydronium ion with the Eigen model.

Quasispecies theory for multiple-peak fitness landscapes.

We use a path integral representation to solve the Eigen and Crow-Kimura molecular evolution models for the case of multiple fitness peaks with arbitrary fitness and degradation functions. In the general case, we find that the solution to these molecular evolution models can be written as the optimum of a fitness function, with constraints enforced by Lagrange multipliers and with a term accounting for the entropy of the spreading population in sequence space. The results for the Eigen model are applied to consider virus or cancer proliferation under the control of drugs or the immune system.

Exact solution of the Eigen model with general fitness functions and degradation rates

We present an exact solution of Eigen's quasispecies model with a general degradation rate and fitness functions, including a square root decrease of fitness with increasing Hamming distance from the wild type. The found behavior of the model with a degradation rate is analogous to a viral quasispecies under attack by the immune system of the host. Our exact solutions also revise the known results of neutral networks in quasispecies theory. To explain the existence of mutants with large Hamming distances from the wild type, we propose three different modifications of the Eigen model: mutation landscape, multiple adjacent mutations, and frequency-dependent fitness in which the steady-state solution shows a multicenter behavior.

Solvable biological evolution model with a parallel mutation-selection scheme.

Based on the connection between a quantum spin model and an asexual biological evolution model with a single-peak fitness function in parallel mutation-selection scheme, we solve exactly both static and dynamics of the evolution model. We find that relaxation in such a parallel scheme is faster than that in a connected scheme of Eigen model. Our method can also be extended to other fitness functions.