Death and Progress: How Evolvability is Influenced by Intrinsic Mortality

2020 ◽  
Vol 26 (1) ◽  
pp. 90-111 ◽  
Author(s):  
Frank Veenstra ◽  
Pablo González de Prado Salas ◽  
Kasper Stoy ◽  
Josh Bongard ◽  
Sebastian Risi
Keyword(s):  
Mortality Rate ◽  
Mutation Rate ◽  
Spatial Model ◽  
Fitness Landscape ◽  
State Of The Art ◽  
Global Maximum ◽  
Random Genetic Drift ◽  
Internal Factors ◽  
Programmed Death ◽  
Intrinsic Mortality

Many factors influence the evolvability of populations, and this article illustrates how intrinsic mortality (death induced through internal factors) in an evolving population contributes favorably to evolvability on a fixed deceptive fitness landscape. We test for evolvability using the hierarchical if-and-only-if (h-iff) function as a deceptive fitness landscape together with a steady state genetic algorithm (SSGA) with a variable mutation rate and indiscriminate intrinsic mortality rate. The mutation rate and the intrinsic mortality rate display a relationship for finding the global maximum. This relationship was also found when implementing the same deceptive fitness landscape in a spatial model consisting of an evolving population. We also compared the performance of the optimal mutation and mortality rate with a state-of-the-art evolutionary algorithm called age-fitness Pareto optimization (AFPO) and show how the two approaches traverse the h-iff landscape differently. Our results indicate that the intrinsic mortality rate and mutation rate induce random genetic drift that allows a population to efficiently traverse a deceptive fitness landscape. This article gives an overview of how intrinsic mortality influences the evolvability of a population. It thereby supports the premise that programmed death of individuals could have a beneficial effect on the evolvability of the entire population.

scholarly journals The Rotavirus Vaccine Landscape, an Update

Pathogens ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 520
Author(s):  
Roberto Cárcamo-Calvo ◽  
Carlos Muñoz ◽  
Javier Buesa ◽  
Jesús Rodríguez-Díaz ◽  
Roberto Gozalbo-Rovira
Keyword(s):  
Developing Countries ◽  
Mortality Rate ◽  
Low Income ◽  
State Of The Art ◽  
The State ◽  
Cold Chain ◽  
Low Income Countries ◽  
Rotavirus Vaccine ◽  
Oral Vaccines

Rotavirus is the leading cause of severe acute childhood gastroenteritis, responsible for more than 128,500 deaths per year, mainly in low-income countries. Although the mortality rate has dropped significantly since the introduction of the first vaccines around 2006, an estimated 83,158 deaths are still preventable. The two main vaccines currently deployed, Rotarix and RotaTeq, both live oral vaccines, have been shown to be less effective in developing countries. In addition, they have been associated with a slight risk of intussusception, and the need for cold chain maintenance limits the accessibility of these vaccines to certain areas, leaving 65% of children worldwide unvaccinated and therefore unprotected. Against this backdrop, here we review the main vaccines under development and the state of the art on potential alternatives.

scholarly journals GENETIC VARIABILITY MAINTAINED BY MUTATION AND OVERDOMINANT SELECTION IN FINITE POPULATIONS

Genetics ◽  
1981 ◽  
Vol 98 (2) ◽  
pp. 441-459 ◽  
Author(s):  
Takeo Maruyama ◽  
Masatoshi Nei
Keyword(s):  
Mutation Rate ◽  
Allozyme Polymorphism ◽  
Random Genetic Drift ◽  
Effective Population ◽  
Mathematical Properties ◽  
Overdominant Selection ◽  
Mean And Variance ◽  
The Mean ◽  
Neutral Mutations ◽  
The Relationship

ABSTRACT Mathematical properties of the overdominance model with mutation and random genetic drift are studied by using the method of stochastic differential equations (Itô and McKean 1974). It is shown that overdominant selection is very powerful in increasing the mean heterozygosity as compared with neutral mutations, and if 2Ns (N = effective population size; s = selective disadvantage for homozygotes) is larger than 10, a very low mutation rate is sufficient to explain the observed level of allozyme polymorphism. The distribution of heterozygosity for overdominant genes is considerably different from that of neutral mutations, and if the ratio of selection coefficient (s) to mutation rate (ν) is large and the mean heterozygosity (h) is lower than 0.2, single-locus heterozygosity is either approximately 0 or 0.5. If h increases further, however, heterozygosity shows a multiple-peak distribution. Reflecting this type of distribution, the relationship between the mean and variance of heterozygosity is considerably different from that for neutral genes. When s/v is large, the proportion of polymorphic loci increases approximately linearly with mean heterozygosity. The distribution of allele frequencies is also drastically different from that of neutral genes, and generally shows a peak at the intermediate gene frequency. Implications of these results on the maintenance of allozyme polymorphism are discussed.

scholarly journals Evolution of gene regulatory networks by means of selection and random genetic drift

2018 ◽  
Author(s):  
Antonios Kioukis ◽  
Pavlos Pavlidis
Keyword(s):  
Natural Selection ◽  
Positive Selection ◽  
Genetic Drift ◽  
Regulatory Networks ◽  
Fitness Landscape ◽  
Random Genetic Drift ◽  
Maturation Period ◽  
Evolutionary Forces ◽  
Gene Regulatory

The evolution of a population by means of genetic drift and natural selection operating on a gene regulatory network (GRN) of an individual has not been scrutinized in depth. Thus, the relative importance of various evolutionary forces and processes on shaping genetic variability in GRNs is understudied. Furthermore, it is not known if existing tools that identify recent and strong positive selection from genomic sequences, in simple models of evolution, can detect recent positive selection when it operates on GRNs. Here, we propose a simulation framework, called EvoNET, that simulates forward-in-time the evolution of GRNs in a population. Since the population size is finite, random genetic drift is explicitly applied. The fitness of a mutation is not constant, but we evaluate the fitness of each individual by measuring its genetic distance from an optimal genotype. Mutations and recombination may take place from generation to generation, modifying the genotypic composition of the population. Each individual goes through a maturation period, where its GRN reaches equilibrium. At the next step, individuals compete to produce the next generation. As time progresses, the beneficial genotypes push the population higher in the fitness landscape. We examine properties of the GRN evolution such as robustness against the deleterious effect of mutations and the role of genetic drift. We confirm classical results from Andreas Wagner’s work that GRNs show robustness against mutations and we provide new results regarding the interplay between random genetic drift and natural selection.

DIFFUSION OF A POPULATION OF INTERACTING REPLICATORS IN SEQUENCE SPACE

2002 ◽  
Vol 05 (04) ◽  
pp. 457-461 ◽  
Author(s):  
BÄRBEL M. R. STADLER
Keyword(s):  
Simple Model ◽  
Population Size ◽  
Computer Simulations ◽  
Mutation Rate ◽  
Sequence Space ◽  
Finite Population ◽  
Fitness Landscape ◽  
Diffusion Constant ◽  
Sequence Length

We consider a simple model for catalyzed replication. Computer simulations show that a finite population moves in sequence space by diffusion analogous to the behavior of a quasispecies on a flat fitness landscape. The diffusion constant depends linearly on the per position mutation rate and the ratio of sequence length and population size.

scholarly journals The state-of-the art in gelotophobia research: A review and some theoretical extensions

2014 ◽  
Vol 27 (1) ◽  
Author(s):  
Willibald Ruch ◽  
Jennifer Hofmann ◽  
Tracey Platt ◽  
René Proyer
Keyword(s):  
State Of The Art ◽  
Empirical Studies ◽  
Dynamic Nature ◽  
Internal Factors ◽  
Research And Practice ◽  
Life Trajectories ◽  
Humor Theory ◽  
Shame Proneness ◽  
Theory Research

AbstractResearch on gelotophobia (the fear of being laughed at) has come a long way since the first empirical studies published in 2008. Based on a review of the findings on gelotophobia, its structure, causes and consequences, updates to the model are introduced emphasizing the context of the fear and its dynamic nature. More precisely, external and internal factors are seen to moderate the effects of initial events on gelotophobia, and a spiral nature in the development of the fear is assumed. It is highlighted that gelotophobia needs to be studied in the context of related variables (such as timidity, shame-proneness and social anxiety), and research should focus on the time span in which this fear is most prevalent. The relevance of gelotophobia for humor theory, research and practice is highlighted and new areas of research are introduced. Among the latter the role of gelotophobia at work and in relation to life trajectories is discussed.

scholarly journals Machine Learning-Assisted Directed Evolution Navigates a Combinatorial Epistatic Fitness Landscape with Minimal Screening Burden

2020 ◽  
Author(s):  
Bruce J. Wittmann ◽  
Yisong Yue ◽  
Frances H. Arnold
Keyword(s):  
Machine Learning ◽  
Directed Evolution ◽  
Path Dependence ◽  
Fitness Landscape ◽  
Combinatorial Libraries ◽  
Single Step ◽  
Saturation Mutagenesis ◽  
Global Maximum ◽  
Training Procedure ◽  
Greedy Optimization

AbstractDue to screening limitations, in directed evolution (DE) of proteins it is rarely feasible to fully evaluate combinatorial mutant libraries made by mutagenesis at multiple sites. Instead, DE often involves a single-step greedy optimization in which the mutation in the highest-fitness variant identified in each round of single-site mutagenesis is fixed. However, because the effects of a mutation can depend on the presence or absence of other mutations, the efficiency and effectiveness of a single-step greedy walk is influenced by both the starting variant and the order in which beneficial mutations are identified—the process is path-dependent. We recently demonstrated a path-independent machine learning-assisted approach to directed evolution (MLDE) that allows in silico screening of full combinatorial libraries made by simultaneous saturation mutagenesis, thus explicitly capturing the effects of cooperative mutations and bypassing the path-dependence that can limit greedy optimization. Here, we thoroughly investigate and optimize an MLDE workflow by testing a number of design considerations of the MLDE pipeline. Specifically, we (1) test the effects of different encoding strategies on MLDE efficiency, (2) integrate new models and a training procedure more amenable to protein engineering tasks, and (3) incorporate training set design strategies to avoid information-poor low-fitness protein variants (“holes”) in the training data. When applied to an epistatic, hole-filled, four-site combinatorial fitness landscape of protein G domain B1 (GB1), the resulting focused training MLDE (ftMLDE) protocol achieved the global fitness maximum up to 92% of the time at a total screening burden of 470 variants. In contrast, minimal-screening-burden single-step greedy optimization over the GB1 fitness landscape reached the global maximum just 1.2% of the time; ftMLDE matching this minimal screening burden (80 total variants) achieved the global optimum up to 9.6% of the time with a 49% higher expected maximum fitness achieved. To facilitate further development of MLDE, we present the MLDE software package (https://github.com/fhalab/MLDE), which is designed for use by protein engineers without computational or machine learning expertise.

scholarly journals The effect of weak clonal interference on average fitness trajectories in the presence of macroscopic epistasis

2021 ◽  
Author(s):  
Yipei Guo ◽  
Ariel Amir
Keyword(s):  
Mutation Rate ◽  
Fitness Landscape ◽  
Large Population ◽  
Beneficial Mutation ◽  
Clonal Interference ◽  
Beneficial Mutations ◽  
Speed Up ◽  
Fixation Probabilities ◽  
Population Competition ◽  
Open Question

Adaptation dynamics on fitness landscapes is often studied theoretically in the strong-selection, weak-mutation (SSWM) regime. However, in a large population, multiple beneficial mutants can emerge before any of them fixes in the population. Competition between mutants is known as clonal interference, and how it affects the form of long-term fitness trajectories in the presence of epistasis is an open question. Here, by considering how changes in fixation probabilities arising from weak clonal interference affect the dynamics of adaptation on fitness-parameterized landscapes, we find that the change in the form of fitness trajectory arises only through changes in the supply of beneficial mutations (or equivalently, the beneficial mutation rate). Furthermore, a depletion of beneficial mutations as a population climbs up the fitness landscape can speed up the functional form of the fitness trajectory, while an enhancement of the beneficial mutation rate does the opposite of slowing down the form of the dynamics. Our findings suggest that by carrying out evolution experiments in both regimes (with and without clonal interference), one could potentially distinguish the different sources of macroscopic epistasis (fitness effect of mutations vs. change in fraction of beneficial mutations).

scholarly journals Within-patient mutation frequencies reveal fitness costs of CpG dinucleotides and drastic amino acid changes in HIV

2016 ◽  
Author(s):  
Kristof Theys ◽  
Alison F. Feder ◽  
Maoz Gelbart ◽  
Marion Hartl ◽  
Adi Stern ◽  
...  
Keyword(s):  
Amino Acid ◽  
Mutation Rate ◽  
Fitness Landscape ◽  
Fitness Costs ◽  
Nonsense Mutations ◽  
Cpg Dinucleotides ◽  
Synonymous Mutations ◽  
The Cost ◽  
Patient Mutation

AbstractHIV has a high mutation rate, which contributes to its ability to evolve quickly. However, we know little about the fitness costs of individual HIV mutationsin vivo, their distribution and the different factors shaping the viral fitness landscape. We calculated the mean frequency of transition mutations at 870 sites of thepolgene in 160 patients, allowing us to determine the cost of these mutations. As expected, we found high costs for non-synonymous and nonsense mutations as compared to synonymous mutations. In addition, we found that non-synonymous mutations that lead to drastic amino acid changes are twice as costly as those that do not and mutations that create new CpG dinucleotides are also twice as costly as those that do not. We also found that G→A and C→T mutations are more costly than A→G mutations. We anticipate that our newin vivofrequency-based approach will provide insights into the fitness landscape and evolvability of not only HIV, but a variety of microbes.Author summaryHIV’s high mutation rate allows it to evolve quickly. However, most mutations probably reduce the virus’ ability to replicate – they are costly to the virus. Until now, the actual cost of mutations is not well understood. We used within-patient mutation frequencies to estimate the cost of 870 HIV mutationsin vivo. As expected, we found high costs for non-synonymous and nonsense mutations. In addition, we found surprisingly high costs for mutations that lead to drastic amino acid changes, mutations that create new CpG sites (possibly because they trigger the host’s immune system), and G→A and C→T mutations. Our results demonstrate the power of analyzing mutant frequencies fromin vivoviral populations to study costs of mutations. A better understanding of fitness costs will help to predict the evolution of HIV.

scholarly journals Escherichia coli with a Tunable Point Mutation Rate for Evolution Experiments

2020 ◽  
Vol 10 (8) ◽  
pp. 2671-2681 ◽  
Author(s):  
Nicholas A. Sherer ◽  
Thomas E. Kuhlman
Keyword(s):  
Escherichia Coli ◽  
Point Mutation ◽  
Mutation Rate ◽  
Fitness Landscape ◽  
Genetically Engineered ◽  
Mutation Rates ◽  
Nucleotide Polymorphisms ◽  
Beneficial Mutations ◽  
Beneficial Effects ◽  
Evolution Experiment

The mutation rate and mutations’ effects on fitness are crucial to evolution. Mutation rates are under selection due to linkage between mutation rate modifiers and mutations’ effects on fitness. The linkage between a higher mutation rate and more beneficial mutations selects for higher mutation rates, while the linkage between a higher mutation rate and more deleterious mutations selects for lower mutation rates. The net direction of selection on mutations rates depends on the fitness landscape, and a great deal of work has elucidated the fitness landscapes of mutations. However, tests of the effect of varying a mutation rate on evolution in a single organism in a single environment have been difficult. This has been studied using strains of antimutators and mutators, but these strains may differ in additional ways and typically do not allow for continuous variation of the mutation rate. To help investigate the effects of the mutation rate on evolution, we have genetically engineered a strain of Escherichia coli with a point mutation rate that can be smoothly varied over two orders of magnitude. We did this by engineering a strain with inducible control of the mismatch repair proteins MutH and MutL. We used this strain in an approximately 350 generation evolution experiment with controlled variation of the mutation rate. We confirmed the construct and the mutation rate were stable over this time. Sequencing evolved strains revealed a higher number of single nucleotide polymorphisms at higher mutations rates, likely due to either the beneficial effects of these mutations or their linkage to beneficial mutations.

scholarly journals Lethal mutagenesis and evolutionary epidemiology

2010 ◽  
Vol 365 (1548) ◽  
pp. 1953-1963 ◽  
Author(s):  
Guillaume Martin ◽  
Sylvain Gandon
Keyword(s):  
Mutation Rate ◽  
Fitness Landscape ◽  
Genetic Load ◽  
Continuous Distribution ◽  
Evolutionary Model ◽  
Simple Expression ◽  
Stochastic Simulations ◽  
Lethal Mutagenesis ◽  
Evolutionary Epidemiology ◽  
Parameter Values

The lethal mutagenesis hypothesis states that within-host populations of pathogens can be driven to extinction when the load of deleterious mutations is artificially increased with a mutagen, and becomes too high for the population to be maintained. Although chemical mutagens have been shown to lead to important reductions in viral titres for a wide variety of RNA viruses, the theoretical underpinnings of this process are still not clearly established. A few recent models sought to describe lethal mutagenesis but they often relied on restrictive assumptions. We extend this earlier work in two novel directions. First, we derive the dynamics of the genetic load in a multivariate Gaussian fitness landscape akin to classical quantitative genetics models. This fitness landscape yields a continuous distribution of mutation effects on fitness, ranging from deleterious to beneficial (i.e. compensatory) mutations. We also include an additional class of lethal mutations. Second, we couple this evolutionary model with an epidemiological model accounting for the within-host dynamics of the pathogen. We derive the epidemiological and evolutionary equilibrium of the system. At this equilibrium, the density of the pathogen is expected to decrease linearly with the genomic mutation rate U . We also provide a simple expression for the critical mutation rate leading to extinction. Stochastic simulations show that these predictions are accurate for a broad range of parameter values. As they depend on a small set of measurable epidemiological and evolutionary parameters, we used available information on several viruses to make quantitative and testable predictions on critical mutation rates. In the light of this model, we discuss the feasibility of lethal mutagenesis as an efficient therapeutic strategy.

Sign in / Sign up

Export Citation Format

Share Document