Effect of Host Species on Topography of the Fitness Landscape for a Plant RNA Virus

ABSTRACTAdaptive fitness landscapes are a fundamental concept in evolutionary biology that relate the genotypes of individuals to their fitness. In the end, the evolutionary fate of evolving populations depends on the topography of the landscape, that is, the numbers of accessible mutational pathways and possible fitness peaks (i.e., adaptive solutions). For a long time, fitness landscapes were only theoretical constructions due to a lack of precise information on the mapping between genotypes and phenotypes. In recent years, however, efforts have been devoted to characterizing the properties of empirical fitness landscapes for individual proteins or for microbes adapting to artificial environments. In a previous study, we characterized the properties of the empirical fitness landscape defined by the first five mutations fixed during adaptation of tobacco etch potyvirus (TEV) to a new experimental host,Arabidopsis thaliana. Here we evaluate the topography of this landscape in the ancestral hostNicotiana tabacum. By comparing the topographies of the landscapes for the two hosts, we found that some features remained similar, such as the existence of fitness holes and the prevalence of epistasis, including cases of sign and reciprocal sign epistasis that created rugged, uncorrelated, and highly random topographies. However, we also observed significant differences in the fine-grained details between the two landscapes due to changes in the fitness and epistatic interactions of some genotypes. Our results support the idea that not only fitness tradeoffs between hosts but also topographical incongruences among fitness landscapes in alternative hosts may contribute to virus specialization.IMPORTANCEDespite its importance for understanding virus evolutionary dynamics, very little is known about the topography of virus adaptive fitness landscapes, and even less is known about the effects that different host species and environmental conditions may have on this topography. To bridge this gap, we evaluated the topography of a small fitness landscape formed by all genotypes that result from every possible combination of the first five mutations fixed during adaptation of TEV to the novel hostA. thaliana. To assess the effect that host species may have on this topography, we evaluated the fitness of every genotype in both the ancestral and novel hosts. We found that both landscapes share some macroscopic properties, such as the existence of holes and being highly rugged and uncorrelated, yet they differ in microscopic details due to changes in the magnitude and sign of fitness and epistatic effects.

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The distribution of epistasis on simple fitness landscapes

10.1101/490573 ◽

2018 ◽

Author(s):

Christelle Fraïsse ◽

John J. Welch

Keyword(s):

Evolutionary Dynamics ◽

Fitness Landscape ◽

Null Model ◽

Large Data ◽

Fitness Landscapes ◽

Mutational Bias ◽

Data Set ◽

Epistatic Interactions ◽

Standing Variation ◽

Mean And Variance

AbstractFitness interactions between mutations can influence a population’s evolution in many different ways. While epistatic effects are difficult to measure precisely, important information about the overall distribution is captured by the mean and variance of log fitnesses for individuals carrying different numbers of mutations. We derive predictions for these quantities from simple fitness landscapes, based on models of optimizing selection on quantitative traits. We also explore extensions to the models, including modular pleiotropy, variable effects sizes, mutational bias, and maladaptation of the wild-type. We illustrate our approach by reanalysing a large data set of mutant effects in a yeast snoRNA. Though characterized by some strong epistatic interactions, these data give a good overall fit to the non-epistatic null model, suggesting that epistasis might have little effect on the evolutionary dynamics in this system. We also show how the amount of epistasis depends on both the underlying fitness landscape, and the distribution of mutations, and so it is expected to vary in consistent ways between new mutations, standing variation, and fixed mutations.

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The distribution of epistasis on simple fitness landscapes

Biology Letters ◽

10.1098/rsbl.2018.0881 ◽

2019 ◽

Vol 15 (4) ◽

pp. 20180881 ◽

Cited By ~ 5

Author(s):

Christelle Fraïsse ◽

John J. Welch

Keyword(s):

Evolutionary Dynamics ◽

Fitness Landscape ◽

Null Model ◽

Fitness Landscapes ◽

Mutational Bias ◽

Variable Effect ◽

Epistatic Effects ◽

Standing Variation ◽

Mean And Variance ◽

Nucleolar Rna

Fitness interactions between mutations can influence a population’s evolution in many different ways. While epistatic effects are difficult to measure precisely, important information is captured by the mean and variance of log fitnesses for individuals carrying different numbers of mutations. We derive predictions for these quantities from a class of simple fitness landscapes, based on models of optimizing selection on quantitative traits. We also explore extensions to the models, including modular pleiotropy, variable effect sizes, mutational bias and maladaptation of the wild type. We illustrate our approach by reanalysing a large dataset of mutant effects in a yeast snoRNA (small nucleolar RNA). Though characterized by some large epistatic effects, these data give a good overall fit to the non-epistatic null model, suggesting that epistasis might have limited influence on the evolutionary dynamics in this system. We also show how the amount of epistasis depends on both the underlying fitness landscape and the distribution of mutations, and so is expected to vary in consistent ways between new mutations, standing variation and fixed mutations.

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Biophysical determinants of mutational robustness in a viral molecular fitness landscape

10.1101/172197 ◽

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.

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Lexical landscapes as largein silicodata for examining advanced properties of fitness landscapes

10.1101/640151 ◽

2019 ◽

Author(s):

Victor A. Meszaros ◽

Miles D. Miller-Dickson ◽

C. Brandon Ogbunugafor

Keyword(s):

Evolutionary Theory ◽

Empirical Data ◽

In Silico ◽

Evolutionary Biology ◽

Fitness Landscape ◽

Evolutionary Genetics ◽

Higher Order ◽

Fitness Landscapes ◽

Adaptive Landscape ◽

Data Sets

In silicoapproaches have served a central role in the development of evolutionary theory for generations. This especially applies to the concept of the fitness landscape, one of the most important abstractions in evolutionary genetics, and one which has benefited from the presence of large empirical data sets only in the last decade or so. In this study, we propose a method that allows us to generate enormous data sets that walk the line betweenin silicoand empirical: word usage frequencies as catalogued by the Google ngram corpora. These data can be codified or analogized in terms of a multidimensional empirical fitness landscape towards the examination of advanced concepts—adaptive landscape by environment interactions, clonal competition, higher-order epistasis and countless others. We argue that the greaterLexical Landscapesapproach can serve as a platform that offers an astronomical number of fitness landscapes for exploration (at least) or theoretical formalism (potentially) in evolutionary biology.

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Adaptive walks on high-dimensional fitness landscapes and seascapes with distance-dependent statistics

10.1101/435669 ◽

2018 ◽

Cited By ~ 1

Author(s):

Atish Agarwala ◽

Daniel S. Fisher

Keyword(s):

Evolutionary Dynamics ◽

Fitness Landscape ◽

Broad Class ◽

Fitness Landscapes ◽

High Dimensional ◽

General Function ◽

Long Distance ◽

Future Evolution ◽

Adaptive Mutations ◽

Adaptive Walks

AbstractThe dynamics of evolution is intimately shaped by epistasis — interactions between genetic elements which cause the fitness-effect of combinations of mutations to be non-additive. Analyzing evolutionary dynamics that involves large numbers of epistatic mutations is intrinsically difficult. A crucial feature is that the fitness landscape in the vicinity of the current genome depends on the evolutionary history. A key step is thus developing models that enable study of the effects of past evolution on future evolution. In this work, we introduce a broad class of high-dimensional random fitness landscapes for which the correlations between fitnesses of genomes are a general function of genetic distance. Their Gaussian character allows for tractable computational as well as analytic understanding. We study the properties of these landscapes focusing on the simplest evolutionary process: random adaptive (uphill) walks. Conventional measures of “ruggedness” are shown to not much affect such adaptive walks. Instead, the long-distance statistics of epistasis cause all properties to be highly conditional on past evolution, determining the statistics of the local landscape (the distribution of fitness-effects of available mutations and combinations of these), as well as the global geometry of evolutionary trajectories. In order to further explore the effects of conditioning on past evolution, we model the effects of slowly changing environments. At long times, such fitness “seascapes” cause a statistical steady state with highly intermittent evolutionary dynamics: populations undergo bursts of rapid adaptation, interspersed with periods in which adaptive mutations are rare and the population waits for more new directions to be opened up by changes in the environment. Finally, we discuss prospects for studying more complex evolutionary dynamics and on broader classes of high-dimensional landscapes and seascapes.

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The fitness landscape of the codon space across environments

10.1101/252395 ◽

2018 ◽

Author(s):

Inès Fragata ◽

Sebastian Matuszewski ◽

Mark A. Schmitz ◽

Thomas Bataillon ◽

Jeffrey D. Jensen ◽

...

Keyword(s):

Amino Acid ◽

Evolutionary Dynamics ◽

Fitness Landscape ◽

Fitness Landscapes ◽

Synonymous Mutations ◽

Landscape Studies ◽

Fitness Effects ◽

Bayesian Monte Carlo ◽

The Relationship

AbstractFitness landscapes map the relationship between genotypes and fitness. However, most fitness landscape studies ignore the genetic architecture imposed by the codon table and thereby neglect the potential role of synonymous mutations. To quantify the fitness effects of synonymous mutations and their potential impact on adaptation on a fitness landscape, we use a new software based on Bayesian Monte Carlo Markov Chain methods and reestimate selection coefficients of all possible codon mutations across 9 amino-acid positions in Saccharomyces cerevisiae Hsp90 across 6 environments. We quantify the distribution of fitness effects of synonymous mutations and show that it is dominated by many mutations of small or no effect and few mutations of larger effect. We then compare the shape of the codon fitness landscape across amino-acid positions and environments, and quantify how the consideration of synonymous fitness effects changes the evolutionary dynamics on these fitness landscapes. Together these results highlight a possible role of synonymous mutations in adaptation and indicate the potential mis-inference when they are neglected in fitness landscape studies.

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Fitness landscape analysis reveals that the wild type allele is sub-optimal and mutationally robust

10.1101/2021.09.27.461914 ◽

2021 ◽

Author(s):

Tzahi Gabzi ◽

Yitzhak Tzachi Pilpel ◽

Tamar Friedlander

Keyword(s):

Mutation Rate ◽

Evolutionary Biology ◽

Evolutionary Dynamics ◽

Fitness Landscape ◽

Mutation Rates ◽

Wild Type Allele ◽

Wild Type ◽

Type Allele ◽

Landscape Mapping ◽

Evolutionary Trajectories

Fitness landscape mapping and the prediction of evolutionary trajectories on these landscapes are major tasks in evolutionary biology research. Evolutionary dynamics is tightly linked to the landscape topography, but this relation is not straightforward. Models predict different evolutionary outcomes depending on mutation rates: high-fitness genotypes should dominate the population under low mutation rates and lower-fitness, mutationally robust (also called 'flat') genotypes - at higher mutation rates. Yet, so far, flat genotypes have been demonstrated in very few cases, particularly in viruses. The quantitative conditions for their emergence were studied only in simplified single-locus, two-peak landscapes. In particular, it is unclear whether within the same genome some genes can be flat while the remaining ones are fit. Here, we analyze a previously measured fitness landscape of a yeast tRNA gene. We found that the wild type allele is sub-optimal, but is mutationally robust ('flat'). Using computer simulations, we estimated the critical mutation rate in which transition from fit to flat allele should occur for a gene with such characteristics. We then used a scaling argument to extrapolate this critical mutation rate for a full genome, assuming the same mutation rate for all genes. Finally, we propose that while the majority of genes are still selected to be fittest, there are a few mutation hot-spots like the tRNA, for which the mutationally robust flat allele is favored by selection.

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Susceptibility across host species is independent of dietary protein to carbohydrate ratios

10.1101/2020.10.21.348987 ◽

2020 ◽

Author(s):

Katherine E Roberts ◽

Ben Longdon

Keyword(s):

Viral Load ◽

Dietary Protein ◽

Host Species ◽

Rna Virus ◽

Ecological Factors ◽

Host Shift ◽

Host Susceptibility ◽

Novel Host ◽

Host Diet ◽

Host Parasite

AbstractThe likelihood of a successful host shift of a parasite to a novel host species can be influenced by environmental factors that can act on both the host and parasite. Changes in nutritional resource availability have been shown to alter pathogen susceptibility and the outcome of infection in a range of systems. Here we examined how dietary protein to carbohydrate altered susceptibility in a large cross infection experiment. We infected 27 species of Drosophilidae with an RNA virus on three food types of differing protein to carbohydrate ratios. We then measured how viral load and mortality across species was affected by changes in diet. We found that changes in the protein:carbohydrate in the diet did not alter the outcomes of infection, with strong positive inter-species correlations in both viral load and mortality across diets, suggesting no species by diet interaction. Mortality and viral load were strongly positively correlated, and this association was consistent across diets. This suggests changes in diet may give consistent outcomes across host species, and may not be universally important in determining host susceptibility to pathogens.Impact StatementA successful host shift of a parasite from one susceptible species to a novel host can be influenced by many ecological factors. Changes in host diet can alter the immune response and outcomes of host–parasite interactions and could potentially alter the outcome of a virus host shift. To investigate, we infected 27 species of Drosophilidae with an RNA virus (DCV) across three food types with differing protein to carbohydrate ratios. We then looked at pathogen loads and survival of infected hosts compared to uninfected controls. Changes in the ratio of protein to carbohydrate did not alter susceptibility to DCV across host species.

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Host shifts result in parallel genetic changes when viruses evolve in closely related species

10.1101/226175 ◽

2017 ◽

Author(s):

Ben Longdon ◽

Jonathan P Day ◽

Joel M Alves ◽

Sophia CL Smith ◽

Thomas M Houslay ◽

...

Keyword(s):

Host Species ◽

Related Species ◽

Rna Virus ◽

Parallel Evolution ◽

Emerging Infectious Diseases ◽

New Host ◽

Closely Related Species ◽

Genetic Changes ◽

Host Shifts ◽

Novel Host

AbstractHost shifts, where a pathogen invades and establishes in a new host species, are a major source of emerging infectious diseases. They frequently occur between related host species and often rely on the pathogen evolving adaptations that increase their fitness in the novel host species. To investigate genetic changes in novel hosts, we experimentally evolved replicate lineages of an RNA virus (Drosophila C Virus) in 19 different species of Drosophilidae and deep sequenced the viral genomes. We found a strong pattern of parallel evolution, where viral lineages from the same host were genetically more similar to each other than to lineages from other host species. When we compared viruses that had evolved in different host species, we found that parallel genetic changes were more likely to occur if the two host species were closely related. This suggests that when a virus adapts to one host it might also become better adapted to closely related host species. This may explain in part why host shifts tend to occur between related species, and may mean that when a new pathogen appears in a given species, closely related species may become vulnerable to the new disease.

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High-order epistasis in catalytic power of dihydrofolate reductase gives rise to a rugged fitness landscape in the presence of trimethoprim selection

10.1101/398065 ◽

2018 ◽

Cited By ~ 3

Author(s):

Yusuf Talha Tamer ◽

Ilona K. Gaszek ◽

Haleh Abdizadeh ◽

Tugce Altinusak Batur ◽

Kimberly Reynolds ◽

...

Keyword(s):

Dihydrofolate Reductase ◽

Biochemical Parameters ◽

Evolutionary Dynamics ◽

Fitness Landscape ◽

Computational Study ◽

Binding Pocket ◽

Resistance Mechanisms ◽

Fitness Landscapes ◽

High Order ◽

Catalytic Power

ABSTRACTEvolutionary fitness landscapes of certain antibiotic target enzymes have been comprehensively mapped showing strong high order epistasis between mutations, but understanding these effects at the biochemical and molecular levels remained open. Here, we carried out an extensive experimental and computational study to quantitatively understand the evolutionary dynamics of Escherichia coli dihydrofolate reductase (DHFR) enzyme in the presence of trimethoprim induced selection. Biochemical and structural characterization of resistance-conferring mutations targeting a total of ten residues spanning the substrate binding pocket of DHFR revealed distinct resistance mechanisms. Next, we experimentally measured biochemical parameters (Km, Ki, and kcat) for a mutant library carrying all possible combinations of six resistance-conferring DHFR mutations and quantified epistatic interactions between them. We found that the epistasis between DHFR mutations is high-order for catalytic power of DHFR (kcat and Km), but less prevalent for trimethoprim affinity (Ki). Taken together our data provide a concrete illustration of how epistatic coupling at the level of biochemical parameters can give rise to complex fitness landscapes, and suggest new strategies for developing mutant specific inhibitors.

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