scholarly journals Quasi-species evolution maximizes genotypic reproductive value (not fitness or flatness)

2021 ◽  
Author(s):  
Matteo Smerlak
Keyword(s):  
Fitness Landscape ◽  
Reproductive Value ◽  
Mutational Robustness ◽  
Rate Dependent ◽  
Markovian Processes ◽  
Genotype Space ◽  
Evolutionary Trajectories ◽  
Species Dynamics ◽  
Species Evolution ◽  
Microbial Systems

AbstractGrowing efforts to measure fitness landscapes in molecular and microbial systems are motivated by a longstanding goal to predict future evolutionary trajectories. Sometimes under-appreciated, however, is that the fitness landscape and its topography do not by themselves determine the direction of evolution: under sufficiently high mutation rates, populations can climb the closest fitness peak (survival of the fittest), settle in lower regions with higher mutational robustness (survival of the flattest), or even fail to adapt altogether (error catastrophes). I show that another measure of reproductive success, Fisher’s reproductive value, resolves the trade-off between fitness and robustness in the quasi-species regime of evolution: to forecast the motion of a population in genotype space, one should look for peaks in the (mutation-rate dependent) landscape of genotypic reproductive values—whether or not these peaks correspond to local fitness maxima or flat fitness plateaus. This new landscape picture turns quasi-species dynamics into an instance of non-equilibrium dynamics, in the physical sense of Markovian processes, potential landscapes, entropy production, etc.

scholarly journals On the deformability of an empirical fitness landscape by microbial evolution

2018 ◽  
Vol 115 (44) ◽  
pp. 11286-11291 ◽  
Author(s):  
Djordje Bajić ◽  
Jean C. C. Vila ◽  
Zachary D. Blount ◽  
Alvaro Sánchez
Keyword(s):  
Environmental Effects ◽  
Evolutionary Dynamics ◽  
Fitness Landscape ◽  
Adaptive Dynamics ◽  
Microbial Evolution ◽  
Fitness Landscapes ◽  
Complex Genetics ◽  
Evolutionary Innovation ◽  
Genotype Space ◽  
Evolutionary Trajectories

A fitness landscape is a map between the genotype and its reproductive success in a given environment. The topography of fitness landscapes largely governs adaptive dynamics, constraining evolutionary trajectories and the predictability of evolution. Theory suggests that this topography can be deformed by mutations that produce substantial changes to the environment. Despite its importance, the deformability of fitness landscapes has not been systematically studied beyond abstract models, and little is known about its reach and consequences in empirical systems. Here we have systematically characterized the deformability of the genome-wide metabolic fitness landscape of the bacterium Escherichia coli. Deformability is quantified by the noncommutativity of epistatic interactions, which we experimentally demonstrate in mutant strains on the path to an evolutionary innovation. Our analysis shows that the deformation of fitness landscapes by metabolic mutations rarely affects evolutionary trajectories in the short range. However, mutations with large environmental effects produce long-range landscape deformations in distant regions of the genotype space that affect the fitness of later descendants. Our results therefore suggest that, even in situations in which mutations have strong environmental effects, fitness landscapes may retain their power to forecast evolution over small mutational distances despite the potential attenuation of that power over longer evolutionary trajectories. Our methods and results provide an avenue for integrating adaptive and eco-evolutionary dynamics with complex genetics and genomics.

scholarly journals A systematic survey of an intragenic epistatic landscape

2014 ◽  
Author(s):  
Claudia Bank ◽  
Ryan T. Hietpas ◽  
Jeffrey D. Jensen ◽  
Daniel N.A. Bolon
Keyword(s):  
Fitness Landscape ◽  
Mutational Robustness ◽  
Epistatic Effects ◽  
Fitness Effects ◽  
Amino Acid Region ◽  
Local Sequence ◽  
Evolutionary Variation ◽  
Evolutionary Trajectories ◽  
One Step ◽  
Negative Epistasis

Mutations are the source of evolutionary variation. The interactions of multiple mutations can have important effects on fitness and evolutionary trajectories. We have recently described the distribution of fitness effects of all single mutations for a nine amino acid region of yeast Hsp90 (Hsp82) implicated in substrate binding. Here, we report and discuss the distribution of intragenic epistatic effects within this region in seven Hsp90 point mutant backgrounds of neutral to slightly deleterious effect, resulting in an analysis of more than 1000 double-mutants. We find negative epistasis between substitutions to be common, and positive epistasis to be rare – resulting in a pattern that indicates a drastic change in the distribution of fitness effects one step away from the wild type. This can be well explained by a concave relationship between phenotype and genotype (i.e., a concave shape of the local fitness landscape), suggesting mutational robustness intrinsic to the local sequence space. Structural analyses indicate that, in this region, epistatic effects are most pronounced when a solvent-inaccessible position is involved in the interaction. In contrast, all 18 observations of positive epistasis involved at least one mutation at a solvent-exposed position. By combining the analysis of evolutionary and biophysical properties of an epistatic landscape, these results contribute to a more detailed understanding of the complexity of protein evolution.

scholarly journals In vitro selected GUAA tetraloop-binding receptors with structural plasticity and evolvability towards natural RNA structural modules

2021 ◽  
Author(s):  
Paul Zakrevsky ◽  
Erin Calkins ◽  
Yi-Ling Kao ◽  
Gurkeerat Singh ◽  
Vasken L Keleshian ◽  
...  
Keyword(s):  
Self Assembly ◽  
High Throughput Sequencing ◽  
In Vitro Selection ◽  
Fitness Landscape ◽  
Sequencing Analysis ◽  
Mutational Robustness ◽  
Rna Molecules ◽  
Receptor Interactions ◽  
Evolutionary Trajectories

Abstract GNRA tetraloop-binding receptor interactions are key components in the macromolecular assembly of a variety of functional RNAs. In nature, there is an apparent bias for GAAA/11nt receptor and GYRA/helix interactions, with the former interaction being thermodynamically more stable than the latter. While past in vitro selections allowed isolation of novel GGAA and GUGA receptors, we report herein an in vitro selection that revealed several novel classes of specific GUAA receptors with binding affinities comparable to those from natural GAAA/11nt interactions. These GUAA receptors have structural homology with double-locked bulge RNA modules naturally occurring in ribosomal RNAs. They display mutational robustness that enables exploration of the sequence/phenotypic space associated to GNRA/receptor interactions through epistasis. Their thermodynamic self-assembly fitness landscape is characterized by a rugged neutral network with possible evolutionary trajectories toward natural GNRA/receptor interactions. High throughput sequencing analysis revealed synergetic mutations located away from the tertiary interactions that positively contribute to assembly fitness. Our study suggests that the repertoire of GNRA/receptor interactions is much larger than initially thought from the analysis of natural stable RNA molecules and also provides clues for their evolution towards natural GNRA/receptors.

scholarly journals Effective potential reveals evolutionary trajectories in complex fitness landscapes

2019 ◽  
Author(s):  
Matteo Smerlak
Keyword(s):  
Effective Potential ◽  
Evolutionary Dynamics ◽  
Fitness Landscape ◽  
Coarse Graining ◽  
Fitness Landscapes ◽  
Coarse Grained ◽  
Mutational Robustness ◽  
Sequencing Technologies ◽  
Wide Range ◽  
Evolutionary Trajectories

AbstractGrowing efforts to measure fitness landscapes in molecular and microbial systems are premised on a tight relationship between landscape topography and evolutionary trajectories. This relationship, however, is far from being straightforward: depending on their mutation rate, Darwinian populations can climb the closest fitness peak (survival of the fittest), settle in lower regions with higher mutational robustness (survival of the flattest), or fail to adapt altogether (error catastrophes). These bifurcations highlight that evolution does not necessarily drive populations “from lower peak to higher peak”, as Wright imagined. The problem therefore remains: how exactly does a complex landscape topography constrain evolution, and can we predict where it will go next? Here I introduce a generalization of quasispecies theory which identifies metastable evolutionary states as minima of an effective potential. From this representation I derive a coarse-grained, Markov state model of evolution, which in turn forms a basis for evolutionary predictions across a wide range of mutation rates. Because the effective potential is related to the ground state of a quantum Hamiltonian, my approach could stimulate fruitful interactions between evolutionary dynamics and quantum many-body theory.SIGNIFICANCE STATEMENTThe course of evolution is determined by the relationship between heritable types and their adaptive values, the fitness landscape. Thanks to the explosive development of sequencing technologies, fitness landscapes have now been measured in a diversity of systems from molecules to micro-organisms. How can we turn these data into evolutionary predictions? I show that preferred evolutionary trajectories are revealed when the effects of selection and mutations are blended in a single effective evolutionary force. With this reformulation, the dynamics of selection and mutation becomes Markovian, bringing a wealth of classical visualization and analysis tools to bear on evolutionary dynamics. Among these is a coarse-graining of evolutionary dynamics along its metastable states which greatly reduces the complexity of the prediction problem.

scholarly journals On the deformability of an empirical fitness landscape by microbial evolution

2018 ◽  
Author(s):  
Djordje Bajić ◽  
Jean C.C. Vila ◽  
Zachary D. Blount ◽  
Alvaro Sánchez
Keyword(s):  
Evolutionary Dynamics ◽  
Fitness Landscape ◽  
Adaptive Dynamics ◽  
Microbial Evolution ◽  
Fitness Landscapes ◽  
Complex Genetics ◽  
Evolutionary Innovation ◽  
Genome Wide ◽  
Genotype Space ◽  
Evolutionary Trajectories

AbstractA fitness landscape is a map between the genotype and its reproductive success in a given environment. The topography of fitness landscapes largely governs adaptive dynamics, constraining evolutionary trajectories and the predictability of evolution. Theory suggests that this topography can be “deformed” by mutations that produce substantial changes to the environment. In spite of its importance, the deformability of fitness landscapes has not been systematically studied beyond abstract models, and little is known about its reach and consequences in empirical systems. Here we have systematically characterized the deformability of the genome-wide metabolic fitness landscape of the bacterium E. coli. Deformability is quantified by the non-commutativity of epistatic interactions, which we experimentally demonstrate in mutant strains on the path to an evolutionary innovation. Our analysis shows that the deformation of fitness landscapes by metabolic mutations rarely affects evolutionary trajectories in the short-range. However, mutations with large environmental effects leave these as a “legacy”, producing long-range landscape deformations in distant regions of the genotype space that affect the fitness of later descendants. Our methods and results provide the basis for an integration between adaptive and eco-evolutionary dynamics with complex genetics and genomics.

scholarly journals Criticality in tumor evolution and clinical outcome

2018 ◽  
Vol 115 (47) ◽  
pp. E11101-E11110 ◽  
Author(s):  
Erez Persi ◽  
Yuri I. Wolf ◽  
Mark D. M. Leiserson ◽  
Eugene V. Koonin ◽  
Eytan Ruppin
Keyword(s):  
Clinical Outcome ◽  
Cancer Biology ◽  
Patient Survival ◽  
Fitness Landscape ◽  
Purifying Selection ◽  
Nonlinear Effects ◽  
Tumor Evolution ◽  
Evolutionary Trajectories ◽  
Cancer Types ◽  
Selection Phase

How mutation and selection determine the fitness landscape of tumors and hence clinical outcome is an open fundamental question in cancer biology, crucial for the assessment of therapeutic strategies and resistance to treatment. Here we explore the mutation-selection phase diagram of 6,721 tumors representing 23 cancer types by quantifying the overall somatic point mutation load (ML) and selection (dN/dS) in the entire proteome of each tumor. We show that ML strongly correlates with patient survival, revealing two opposing regimes around a critical point. In low-ML cancers, a high number of mutations indicates poor prognosis, whereas high-ML cancers show the opposite trend, presumably due to mutational meltdown. Although the majority of cancers evolve near neutrality, deviations are observed at extreme MLs. Melanoma, with the highest ML, evolves under purifying selection, whereas in low-ML cancers, signatures of positive selection are observed, demonstrating how selection affects tumor fitness. Moreover, different cancers occupy specific positions on the ML–dN/dS plane, revealing a diversity of evolutionary trajectories. These results support and expand the theory of tumor evolution and its nonlinear effects on survival.

scholarly journals Higher-fitness yeast genotypes are less robust to deleterious mutations

Science ◽  
2019 ◽  
Vol 366 (6464) ◽  
pp. 490-493 ◽  
Author(s):  
Milo S. Johnson ◽  
Alena Martsul ◽  
Sergey Kryazhimskiy ◽  
Michael M. Desai
Keyword(s):  
Second Order ◽  
Order Selection ◽  
Deleterious Mutations ◽  
Mutational Robustness ◽  
First Order ◽  
Fitness Effects ◽  
Yeast Strains ◽  
Selection For ◽  
Microbial Systems ◽  
Insertion Mutations

Natural selection drives populations toward higher fitness, but second-order selection for adaptability and mutational robustness can also influence evolution. In many microbial systems, diminishing-returns epistasis contributes to a tendency for more-fit genotypes to be less adaptable, but no analogous patterns for robustness are known. To understand how robustness varies across genotypes, we measure the fitness effects of hundreds of individual insertion mutations in a panel of yeast strains. We find that more-fit strains are less robust: They have distributions of fitness effects with lower mean and higher variance. These differences arise because many mutations have more strongly deleterious effects in faster-growing strains. This negative correlation between fitness and robustness implies that second-order selection for robustness will tend to conflict with first-order selection for fitness.

Biophysical determinants of mutational robustness in a viral molecular fitness landscape

2017 ◽  
Author(s):  
Manasi A. Pethe ◽  
Aliza B. Rubenstein ◽  
Dmitri Zorine ◽  
Sagar D. Khare
Keyword(s):  
Fitness Landscape ◽  
Rna Virus ◽  
Fitness Landscapes ◽  
Viral Fitness ◽  
Mutational Robustness ◽  
Hcv Protease ◽  
Viral Polyprotein ◽  
Biophysical Interactions ◽  
Proteins And Peptides

Biophysical interactions between proteins and peptides are key determinants of genotype-fitness landscapes, but an understanding of how molecular structure and residue-level energetics at protein-peptide interfaces shape functional landscapes remains elusive. Combining information from yeast-based library screening, next-generation sequencing and structure-based modeling, we report comprehensive sequence-energetics-function mapping of the specificity landscape of the Hepatitis C Virus (HCV) NS3/4A protease, whose function — site-specific cleavages of the viral polyprotein — is a key determinant of viral fitness. We elucidate the cleavability of 3.2 million substrate variants by the HCV protease and find extensive clustering of cleavable and uncleavable motifs in sequence space indicating mutational robustness, and thereby providing a plausible molecular mechanism to buffer the effects of low replicative fidelity of this RNA virus. Specificity landscapes of known drug-resistant variants are similarly clustered. Our results highlight the key and constraining role of molecular-level energetics in shaping plateau-like fitness landscapes from quasispecies theory.

Multidimensional epistasis and fitness landscapes in enzyme evolution

2012 ◽  
Vol 445 (1) ◽  
pp. 39-46 ◽  
Author(s):  
Wei Zhang ◽  
Daniel F. A. R. Dourado ◽  
Pedro Alexandrino Fernandes ◽  
Maria João Ramos ◽  
Bengt Mannervik
Keyword(s):  
Glutathione Transferase ◽  
Fitness Landscape ◽  
Evolutionary Process ◽  
Salient Feature ◽  
Selective Advantage ◽  
Enzyme Evolution ◽  
Conventional Analysis ◽  
Evolutionary Response ◽  
Single Protein ◽  
Evolutionary Trajectories

The conventional analysis of enzyme evolution is to regard one single salient feature as a measure of fitness, expressed in a milieu exposing the possible selective advantage at a given time and location. Given that a single protein may serve more than one function, fitness should be assessed in several dimensions. In the present study we have explored individual mutational steps leading to a triple-point-mutated human GST (glutathione transferase) A2-2 displaying enhanced activity with azathioprine. A total of eight alternative substrates were used to monitor the diverse evolutionary trajectories. The epistatic effects of the mutations on catalytic activity were variable in sign and magnitude and depended on the substrate used, showing that epistasis is a multidimensional quality. Evidently, the multidimensional fitness landscape can lead to alternative trajectories resulting in enzymes optimized for features other than the selectable markers relevant at the origin of the evolutionary process. In this manner the evolutionary response is robust and can adapt to changing environmental conditions.

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