Distribution of fitness effects caused by single-nucleotide substitutions in bacteriophage f1

Fit-Seq2.0: An Improved Software for High-Throughput Fitness Measurements Using Pooled Competition Assays

The fitness of a genotype is defined as its lifetime reproductive success, with fitness itself being a composite trait likely dependent on many underlying phenotypes. Measuring fitness is important for understanding how alteration of different cellular components affects a cell's ability to reproduce. Here, we describe an improved approach, implemented in Python, for estimating fitness in high throughput via pooled competition assays.

COVID-19: A state of art on immunological responses, mutations, and treatment modalities in riposte

Over the last few years, the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) unleashed a global public health catastrophe that had a substantial influence on human physical and mental health, the global economy, and socio-political dynamics. SARS-CoV-2 is a respiratory pathogen and the cause of ongoing COVID-19 pandemic, which testified how unprepared humans are for pandemics. Scientists and policymakers continue to face challenges in developing ideal therapeutic agents and vaccines, while at the same time deciphering the pathology and immunology of SARS-CoV-2. Challenges in the early part of the pandemic included the rapid development of diagnostic assays, vaccines, and therapeutic agents. The ongoing transmission of COVID-19 is coupled with the emergence of viral variants that differ in their transmission efficiency, virulence, and vaccine susceptibility, thus complicating the spread of the pandemic. Our understanding of how the human immune system responds to these viruses as well as the patient groups (such as the elderly and immunocompromised individuals) who are often more susceptible to serious illness have both been aided by this epidemic. COVID-19 causes different symptoms to occur at different stages of infection, making it difficult to determine distinct treatment regimens employed for the various clinical phases of the disease. Unsurprisingly, determining the efficacy of currently available medications and developing novel therapeutic strategies have been a process of trial and error. The global scientific community collaborated to research and develop vaccines at a neck-breaking speed. This review summarises the overall picture of the COVID-19 pandemic, different mutations in SARS-CoV-2, immune response, and the treatment modalities against SARS-CoV-2.

Viral Fitness, Population Complexity, Host Interactions, and Resistance to Antiviral Agents

Fitness of viruses has become a standard parameter to quantify their adaptation to a biological environment. Fitness determinations for RNA viruses (and some highly variable DNA viruses) meet with several uncertainties. Of particular interest are those that arise from mutant spectrum complexity, absence of population equilibrium, and internal interactions among components of a mutant spectrum. Here, concepts, fitness measurements, limitations, and current views on experimental viral fitness landscapes are discussed. The effect of viral fitness on resistance to antiviral agents is covered in some detail since it constitutes a widespread problem in antiviral pharmacology, and a challenge for the design of effective antiviral treatments. Recent evidence with hepatitis C virus suggests the operation of mechanisms of antiviral resistance additional to the standard selection of drug-escape mutants. The possibility that high replicative fitness may be the driver of such alternative mechanisms is considered. New broad-spectrum antiviral designs that target viral fitness may curtail the impact of drug-escape mutants in treatment failures. We consider to what extent fitness-related concepts apply to coronaviruses and how they may affect strategies for COVID-19 prevention and treatment.

The High Mutational Sensitivity of ccdA Antitoxin Is Linked to Codon Optimality

Deep mutational scanning studies suggest that synonymous mutations are typically silent and that most exposed, nonactive-site residues are tolerant to mutations. Here, we show that the ccdA antitoxin component of the Escherichia coli ccdAB toxin-antitoxin system is unusually sensitive to mutations when studied in the operonic context. A large fraction (∼80%) of single-codon mutations, including many synonymous mutations in the ccdA gene shows inactive phenotype, but they retain native-like binding affinity towards cognate toxin, CcdB. Therefore, the observed phenotypic effects are largely not due to alterations in protein structure/stability, consistent with a large region of CcdA being intrinsically disordered. E. coli codon preference and strength of ribosome-binding associated with translation of downstream ccdB gene are found to be major contributors of the observed ccdA mutant phenotypes. In select cases, proteomics studies reveal altered ratios of CcdA:CcdB protein levels in vivo, suggesting that the ccdA mutations likely alter relative translation efficiencies of the two genes in the operon. We extend these results by studying single-site synonymous mutations that lead to loss of function phenotypes in the relBE operon upon introduction of rarer codons. Thus, in their operonic context, genes are likely to be more sensitive to both synonymous and nonsynonymous point mutations than inferred previously.

A White Plaque, Associated with Genomic Deletion, Derived from M13KE-Based Peptide Library Is Enriched in a Target-Unrelated Manner during Phage Display Biopanning Due to Propagation Advantage

The nonspecific enrichment of target-unrelated peptides during biopanning remains a major drawback for phage display technology. The commercial Ph.D.^TM-7 phage display library is used extensively for peptide discovery. This library is based on the M13KE vector, which carries the lacZα sequence, leading to the formation of blue plaques on IPTG-X-gal agar plates. In the current study, we report the isolation of a fast-propagating white clone (displaying WSLGYTG peptide) identified through screening against a recombinant protein. Sanger sequencing demonstrated that white plaques are not contamination from environmental M13-like phages, but derive from the library itself. Whole genome sequencing revealed that the white color of the plaques results from a large 827-nucleotide genomic deletion. The phenotypic characterization of propagation capacity through plaque count- and NGS-based competitive propagation assay supported the higher propagation rate of Ph-WSLGYTG clone compared with the library. According to our data, white plaques are likely to arise endogenously in Ph.D. libraries due to mutations in the M13KE genome and should not always be viewed as exogenous contamination. Our findings also led to the conclusion that the deletion observed here might be an ancestral mutation already present in the naïve library, which causes target-unrelated nonspecific enrichment of white clone during biopanning due to propagation advantage.

Haplotype-based inference of the distribution of fitness effects

Recent genome sequencing studies with large sample sizes in humans have discovered a vast quantity of low-frequency variants, providing an important source of information to analyze how selection is acting on human genetic variation. In order to estimate the strength of natural selection acting on low-frequency variants, we have developed a likelihood-based method that uses the lengths of pairwise identity-by-state between haplotypes carrying low-frequency variants. We show that in some non-equilibrium populations (such as those that have had recent population expansions) it is possible to distinguish between positive or negative selection acting on a set of variants. With our new framework, one can infer a fixed selection intensity acting on a set of variants at a particular frequency, or a distribution of selection coefficients for standing variants and new mutations. We show an application of our method to the UK10K phased haplotype dataset of individuals.

A Two-Level, Intramutant Spectrum Haplotype Profile of Hepatitis C Virus Revealed by Self-Organized Maps

RNA viruses replicate as complex mutant spectra termed viral quasispecies. The frequency of each individual genome in a mutant spectrum depends on its rate of generation and its relative fitness in the replicating population ensemble. The advent of deep sequencing methodologies allows for the first-time quantification of haplotype abundances within mutant spectra. There is no information on the haplotype profile of the resident genomes and how the landscape evolves when a virus replicates in a controlled cell culture environment. Here, we report the construction of intramutant spectrum haplotype landscapes of three amplicons of the NS5A-NS5B coding region of hepatitis C virus (HCV). Two-dimensional (2D) neural networks were constructed for 44 related HCV populations derived from a common clonal ancestor that was passaged up to 210 times in human hepatoma Huh-7.5 cells in the absence of external selective pressures. The haplotype profiles consisted of an extended dense basal platform, from which a lower number of protruding higher peaks emerged. As HCV increased its adaptation to the cells, the number of haplotype peaks within each mutant spectrum expanded, and their distribution shifted in the 2D network. The results show that extensive HCV replication in a monotonous cell culture environment does not limit HCV exploration of sequence space through haplotype peak movements. The landscapes reflect dynamic variation in the intramutant spectrum haplotype profile and may serve as a reference to interpret the modifications produced by external selective pressures or to compare with the landscapes of mutant spectra in complex in vivo environments. IMPORTANCE The study provides for the first time the haplotype profile and its variation in the course of virus adaptation to a cell culture environment in the absence of external selective constraints. The deep sequencing-based self-organized maps document a two-layer haplotype distribution with an ample basal platform and a lower number of protruding peaks. The results suggest an inferred intramutant spectrum fitness landscape structure that offers potential benefits for virus resilience to mutational inputs.

Engineering gene overlaps to sustain genetic constructs in vivo

Evolution is often an obstacle to the engineering of stable biological systems due to the selection of mutations inactivating costly gene circuits. Gene overlaps induce important constraints on sequences and their evolution. We show that these constraints can be harnessed to increase the stability of costly genes by purging loss-of-function mutations. We combine computational and synthetic biology approaches to rationally design an overlapping reading frame expressing an essential gene within an existing gene to protect. Our algorithm succeeded in creating overlapping reading frames in 80% of E. coli genes. Experimentally, scoring mutations in both genes of such overlapping construct, we found that a significant fraction of mutations impacting the gene to protect have a deleterious effect on the essential gene. Such an overlap thus protects a costly gene from removal by natural selection by associating the benefit of this removal with a larger or even lethal cost. In our synthetic constructs, the overlap converts many of the possible mutants into evolutionary dead-ends, reducing the evolutionary potential of the system and thus increasing its stability over time.

Genomes are translated by triplets of nucleotides on two different strands, allowing for six different reading frames. This permits the existence of gene overlaps, often observed in microbial genomes, where two different proteins are encoded on the same piece of DNA, but in different reading frames. Gene overlaps are classically considered an obstacle for both evolution and genetic engineering, as mutations in overlapping regions likely have pleitrotropic effects on several genes. In 2013, we identified specific evolutionary scenarios where the decrease in evolutionary potential caused by gene overlaps could instead be advantageous and selected for. In this work, we demonstrate the use of gene overlaps in another context where reducing evolutionary potential can be useful: preventing evolution from inactivating synthetic circuits. We show that gene overlaps can be engineered to increase the evolutionary stability of genes that are costly to their hosts, by entangling these costly genes with essential genes.

Variability in Codon Usage in Coronaviruses Is Mainly Driven by Mutational Bias and Selective Constraints on CpG Dinucleotide

The Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the third human-emerged virus of the 21st century from the Coronaviridae family, causing the ongoing coronavirus disease 2019 (COVID-19) pandemic. Due to the high zoonotic potential of coronaviruses, it is critical to unravel their evolutionary history of host species breadth, host-switch potential, adaptation and emergence, to identify viruses posing a pandemic risk in humans. We present here a comprehensive analysis of the composition and codon usage bias of the 82 Orthocoronavirinae members, infecting 47 different avian and mammalian hosts. Our results clearly establish that synonymous codon usage varies widely among viruses, is only weakly dependent on their primary host, and is dominated by mutational bias towards AU-enrichment and by CpG avoidance. Indeed, variation in GC3 explains around 34%, while variation in CpG frequency explains around 14% of total variation in codon usage bias. Further insight on the mutational equilibrium within Orthocoronavirinae revealed that most coronavirus genomes are close to their neutral equilibrium, the exception being the three recently infecting human coronaviruses, which lie further away from the mutational equilibrium than their endemic human coronavirus counterparts. Finally, our results suggest that, while replicating in humans, SARS-CoV-2 is slowly becoming AU-richer, likely until attaining a new mutational equilibrium.

Mistranslation reduces mutation load in evolving proteins through negative epistasis with DNA mutations

Translational errors during protein synthesis cause phenotypic mutations that are several orders of magnitude more frequent than DNA mutations. Such phenotypic mutations may affect adaptive evolution through their interactions with DNA mutations. To study how mistranslation may affect the adaptive evolution of evolving proteins, we evolved populations of green fluorescent protein (GFP) in either high-mistranslation or low-mistranslation Escherichia coli hosts. In both hosts, we first evolved GFP under purifying selection for the ancestral phenotype green fluorescence, and then under directional selection toward the new phenotype yellow fluorescence. High-mistranslation populations evolved modestly higher yellow fluorescence during each generation of evolution than low-mistranslation populations. We demonstrate by high-throughput sequencing that elevated mistranslation reduced the accumulation of deleterious DNA mutations under both purifying and directional selection. It did so by amplifying the fitness effects of deleterious DNA mutations through negative epistasis with phenotypic mutations. In contrast, mistranslation did not affect the incidence of beneficial mutations. Our findings show that phenotypic mutations interact epistatically with DNA mutations. By reducing a population’s mutation load, mistranslation can affect an important determinant of evolvability.

Effects of synonymous mutations beyond codon bias: The evidence for adaptive synonymous substitutions from microbial evolution experiments

Synonymous mutations are often assumed to be neutral with respect to fitness because they do not alter the encoded amino acid and so cannot be 'seen' by natural selection. Yet a growing body of evidence suggests that synonymous mutations can have fitness effects that drive adaptive evolution through their impacts on gene expression and protein folding. Here, we review what microbial experiments have taught us about the contribution of synonymous mutations to adaptation. A survey of site-directed mutagenesis experiments reveals the distributions of fitness effects for nonsynonymous and synonymous mutations are more similar, especially for beneficial mutations, than expected if all synonymous mutations were neutral, suggesting they should drive adaptive evolution more often than is typically observed. A review of experimental evolution studies where synonymous mutations have contributed to adaptation shows they can impact fitness through a range of mechanisms including the creation of illicit RNA polymerase binding sites impacting transcription and changes to mRNA folding stability that modulate translation. We suggest that clonal interference in evolving microbial populations may be the reason synonymous mutations play a smaller role in adaptive evolution than expected based on their observed fitness effects. We finish by discussing the impacts of falsely assuming synonymous mutations are neutral and discuss directions for future work exploring the role of synonymous mutations in adaptive evolution.

Quantifying the Evolutionary Constraints and Potential of Hepatitis C Virus NS5A Protein

RNA viruses, such as hepatitis C virus (HCV), influenza virus, and SARS-CoV-2, are notorious for their ability to evolve rapidly under selection in novel environments. It is known that the high mutation rate of RNA viruses can generate huge genetic diversity to facilitate viral adaptation. However, less attention has been paid to the underlying fitness landscape that represents the selection forces on viral genomes, especially under different selection conditions. Here, we systematically quantified the distribution of fitness effects of about 1,600 single amino acid substitutions in the drug-targeted region of NS5A protein of HCV. We found that the majority of nonsynonymous substitutions incur large fitness costs, suggesting that NS5A protein is highly optimized. The replication fitness of viruses is correlated with the pattern of sequence conservation in nature, and viral evolution is constrained by the need to maintain protein stability. We characterized the adaptive potential of HCV by subjecting the mutant viruses to selection by the antiviral drug daclatasvir at multiple concentrations. Both the relative fitness values and the number of beneficial mutations were found to increase with the increasing concentrations of daclatasvir. The changes in the spectrum of beneficial mutations in NS5A protein can be explained by a pharmacodynamics model describing viral fitness as a function of drug concentration. Overall, our results show that the distribution of fitness effects of mutations is modulated by both the constraints on the biophysical properties of proteins (i.e., selection pressure for protein stability) and the level of environmental stress (i.e., selection pressure for drug resistance).

IMPORTANCE Many viruses adapt rapidly to novel selection pressures, such as antiviral drugs. Understanding how pathogens evolve under drug selection is critical for the success of antiviral therapy against human pathogens. By combining deep sequencing with selection experiments in cell culture, we have quantified the distribution of fitness effects of mutations in hepatitis C virus (HCV) NS5A protein. Our results indicate that the majority of single amino acid substitutions in NS5A protein incur large fitness costs. Simulation of protein stability suggests viral evolution is constrained by the need to maintain protein stability. By subjecting the mutant viruses to selection under an antiviral drug, we find that the adaptive potential of viral proteins in a novel environment is modulated by the level of environmental stress, which can be explained by a pharmacodynamics model. Our comprehensive characterization of the fitness landscapes of NS5A can potentially guide the design of effective strategies to limit viral evolution.

Variability in the durability of CRISPR-Cas immunity

The durability of host resistance is challenged by the ability of pathogens to escape the defence of their hosts. Understanding the variability in the durability of host resistance is of paramount importance for designing more effective control strategies against infectious diseases. Here, we study the durability of various clustered regularly interspaced short palindromic repeats-Cas (CRISPR-Cas) alleles of the bacteria Streptococcus thermophilus against lytic phages. We found substantial variability in durability among different resistant bacteria. Since the escape of the phage is driven by a mutation in the phage sequence targeted by CRISPR-Cas, we explored the fitness costs associated with these escape mutations. We found that, on average, escape mutations decrease the fitness of the phage. Yet, the magnitude of this fitness cost does not predict the durability of CRISPR-Cas immunity. We contend that this variability in the durability of resistance may be because of variations in phage mutation rate or in the proportion of lethal mutations across the phage genome. These results have important implications on the coevolutionary dynamics between bacteria and phages and for the optimal deployment of resistance strategies against pathogens and pests. Understanding the durability of CRISPR-Cas immunity may also help develop more effective gene-drive strategies based on CRISPR-Cas9 technology. This article is part of a discussion meeting issue 'The ecology and evolution of prokaryotic CRISPR-Cas adaptive immune systems'.

Recent insights into the genotype-phenotype relationship from massively parallel genetic assays

With the molecular revolution in Biology, a mechanistic understanding of the genotype-phenotype relationship became possible. Recently, advances in DNA synthesis and sequencing have enabled the development of deep mutational scanning assays, capable of scoring comprehensive libraries of genotypes for fitness and a variety of phenotypes in massively parallel fashion. The resulting empirical genotype-fitness maps pave the way to predictive models, potentially accelerating our ability to anticipate the behaviour of pathogen and cancerous cell populations from sequencing data. Besides from cellular fitness, phenotypes of direct application in industry (e.g. enzyme activity) and medicine (e.g. antibody binding) can be quantified and even selected directly by these assays. This review discusses the technological basis of and recent developments in massively parallel genetics, along with the trends it is uncovering in the genotype-phenotype relationship (distribution of mutation effects, epistasis), their possible mechanistic bases and future directions for advancing towards the goal of predictive genetics.

Simulations reveal challenges to artificial community selection and possible strategies for success

Multispecies microbial communities often display "community functions" arising from interactions of member species. Interactions are often difficult to decipher, making it challenging to design communities with desired functions. Alternatively, similar to artificial selection for individuals in agriculture and industry, one could repeatedly choose communities with the highest community functions to reproduce by randomly partitioning each into multiple "Newborn" communities for the next cycle. However, previous efforts in selecting complex communities have generated mixed outcomes that are difficult to interpret. To understand how to effectively enact community selection, we simulated community selection to improve a community function that requires 2 species and imposes a fitness cost on one or both species. Our simulations predict that improvement could be easily stalled unless various aspects of selection are carefully considered. These aspects include promoting species coexistence, suppressing noncontributors, choosing additional communities besides the highest functioning ones to reproduce, and reducing stochastic fluctuations in the biomass of each member species in Newborn communities. These considerations can be addressed experimentally. When executed effectively, community selection is predicted to improve costly community function, and may even force species to evolve slow growth to achieve species coexistence. Our conclusions hold under various alternative model assumptions and are therefore applicable to a variety of communities.

Rates of Mutation and Recombination in Siphoviridae Phage Genome Evolution over Three Decades

The evolution of asexual organisms is driven not only by the inheritance of genetic modification but also by the acquisition of foreign DNA. The contribution of vertical and horizontal processes to genome evolution depends on their rates per year and is quantified by the ratio of recombination to mutation. These rates have been estimated for bacteria; however, no estimates have been reported for phages. Here, we delineate the contribution of mutation and recombination to dsDNA phage genome evolution. We analyzed 34 isolates of the 936 group of Siphoviridae phages using a Lactococcus lactis strain from a single dairy over 29 years. We estimate a constant substitution rate of 1.9 × 10⁻⁴ substitutions per site per year due to mutation that is within the range of estimates for eukaryotic RNA and DNA viruses. The reconstruction of recombination events reveals a constant rate of five recombination events per year and 4.5 × 10⁻³ nucleotide alterations due to recombination per site per year. Thus, the recombination rate exceeds the substitution rate, resulting in a relative effect of recombination to mutation (r/m) of ∼24 that is homogenous over time. Especially in the early transcriptional region, we detect frequent gene loss and regain due to recombination with phages of the 936 group, demonstrating the role of the 936 group pangenome as a reservoir of genetic variation. The observed substitution rate homogeneity conforms to the neutral theory of evolution; hence, the neutral theory can be applied to phage genome evolution and also to genetic variation brought about by recombination.

Stochastic Modeling and Simulation of Viral Evolution

RNA viruses comprise vast populations of closely related, but highly genetically diverse, entities known as quasispecies. Understanding the mechanisms by which this extreme diversity is generated and maintained is fundamental when approaching viral persistence and pathobiology in infected hosts. In this paper, we access quasispecies theory through a mathematical model based on the theory of multitype branching processes, to better understand the roles of mechanisms resulting in viral diversity, persistence and extinction. We accomplish this understanding by a combination of computational simulations and the theoretical analysis of the model. In order to perform the simulations, we have implemented the mathematical model into a computational platform capable of running simulations and presenting the results in a graphical format in real time. Among other things, we show that the establishment of virus populations may display four distinct regimes from its introduction into new hosts until achieving equilibrium or undergoing extinction. Also, we were able to simulate different fitness distributions representing distinct environments within a host which could either be favorable or hostile to the viral success. We addressed the most used mechanisms for explaining the extinction of RNA virus populations called lethal mutagenesis and mutational meltdown. We were able to demonstrate a correspondence between these two mechanisms implying the existence of a unifying principle leading to the extinction of RNA viruses.

Mutation and Epistasis in Influenza Virus Evolution

Influenza remains a persistent public health challenge, because the rapid evolution of influenza viruses has led to marginal vaccine efficacy, antiviral resistance, and the annual emergence of novel strains. This evolvability is driven, in part, by the virus's capacity to generate diversity through mutation and reassortment. Because many new traits require multiple mutations and mutations are frequently combined by reassortment, epistatic interactions between mutations play an important role in influenza virus evolution. While mutation and epistasis are fundamental to the adaptability of influenza viruses, they also constrain the evolutionary process in important ways. Here, we review recent work on mutational effects and epistasis in influenza viruses.

Evidence for the Selective Basis of Transition-to-Transversion Substitution Bias in Two RNA Viruses

The substitution rates of transitions are higher than expected by chance relative to those of transversions. Many have argued that selection disfavors transversions, as nonsynonymous transversions are less likely to conserve biochemical properties of the original amino acid. Only recently has it become feasible to directly test this selective hypothesis by comparing the fitness effects of a large number of transition and transversion mutations. For example, a recent study of six viruses and one beta-lactamase gene did not find evidence supporting the selective hypothesis. Here, we analyze the relative fitness effects of transition and transversion mutations from our recently published genome-wide study of mutational fitness effects in influenza virus. In contrast to prior work, we find that transversions are significantly more detrimental than transitions. Using what we believe to be an improved statistical framework, we also identify a similar trend in two HIV data sets. We further demonstrate a fitness difference in transition and transversion mutations using four deep mutational scanning data sets of influenza virus and HIV, which provided adequate statistical power. We find that three of the most commonly cited radical/conservative amino acid categories are predictive of fitness, supporting their utility in studies of positive selection and codon usage bias. We conclude that selection is a major contributor to the transition:transversion substitution bias in viruses and that this effect is only partially explained by the greater likelihood of transversion mutations to cause radical as opposed to conservative amino acid changes.

Viral Fitness Correlates with the Magnitude and Direction of the Perturbation Induced in the Host's Transcriptome: The Tobacco Etch Potyvirus-Tobacco Case Study

Determining the fitness of viral genotypes has become a standard practice in virology as it is essential to evaluate their evolutionary potential. Darwinian fitness, defined as the advantage of a given genotype with respect to a reference one, is a complex property that captures, in a single figure, differences in performance at every stage of viral infection. To what extent does viral fitness result from specific molecular interactions with host factors and regulatory networks during infection? Can we identify host genes in functional classes whose expression depends on viral fitness? Here, we compared the transcriptomes of tobacco plants infected with seven genotypes of tobacco etch potyvirus that differ in fitness. We found that the larger the fitness differences among genotypes, the more dissimilar the transcriptomic profiles are. Consistently, two different mutations, one in the viral RNA polymerase and another in the viral suppressor of RNA silencing, resulted in significantly similar gene expression profiles. Moreover, we identified host genes whose expression showed a significant correlation, positive or negative, with the virus' fitness. Differentially expressed genes which were positively correlated with viral fitness activate hormone- and RNA silencing-mediated pathways of plant defense. In contrast, those that were negatively correlated with fitness affect metabolism, reducing growth, and development. Overall, these results reveal the high information content of viral fitness and suggest its potential use to predict differences in genomic profiles of infected hosts.

Experimental Determination and Prediction of the Fitness Effects of Random Point Mutations in the Biosynthetic Enzyme HisA

The distribution of fitness effects of mutations is a factor of fundamental importance in evolutionary biology. We determined the distribution of fitness effects of 510 mutants that each carried between 1 and 10 mutations (synonymous and nonsynonymous) in the hisA gene, encoding an essential enzyme in the l-histidine biosynthesis pathway of Salmonella enterica. For the full set of mutants, the distribution was bimodal with many apparently neutral mutations and many lethal mutations. For a subset of 81 single, nonsynonymous mutants most mutations appeared neutral at high expression levels, whereas at low expression levels only a few mutations were neutral. Furthermore, we examined how the magnitude of the observed fitness effects was correlated to several measures of biophysical properties and phylogenetic conservation.We conclude that for HisA: (i) The effect of mutations can be masked by high expression levels, such that mutations that are deleterious to the function of the protein can still be neutral with regard to organism fitness if the protein is expressed at a sufficiently high level; (ii) the shape of the fitness distribution is dependent on the extent to which the protein is rate-limiting for growth; (iii) negative epistatic interactions, on an average, amplified the combined effect of nonsynonymous mutations; and (iv) no single sequence-based predictor could confidently predict the fitness effects of mutations in HisA, but a combination of multiple predictors could predict the effect with a SD of 0.04 resulting in 80% of the mutations predicted within 12% of their observed selection coefficients.

Proofreading-Deficient Coronaviruses Adapt for Increased Fitness over Long-Term Passage without Reversion of Exoribonuclease-Inactivating Mutations

The coronavirus (CoV) RNA genome is the largest among the single-stranded positive-sense RNA viruses. CoVs encode a proofreading 3'-to-5' exoribonuclease within nonstructural protein 14 (nsp14-ExoN) that is responsible for CoV high-fidelity replication. Alanine substitution of ExoN catalytic residues [ExoN(-)] in severe acute respiratory syndrome-associated coronavirus (SARS-CoV) and murine hepatitis virus (MHV) disrupts ExoN activity, yielding viable mutant viruses with defective replication, up to 20-fold-decreased fidelity, and increased susceptibility to nucleoside analogues. To test the stability of the ExoN(-) genotype and phenotype, we passaged MHV-ExoN(-) 250 times in cultured cells (P250), in parallel with wild-type MHV (WT-MHV). Compared to MHV-ExoN(-) P3, MHV-ExoN(-) P250 demonstrated enhanced replication and increased competitive fitness without reversion at the ExoN(-) active site. Furthermore, MHV-ExoN(-) P250 was less susceptible than MHV-ExoN(-) P3 to multiple nucleoside analogues, suggesting that MHV-ExoN(-) was under selection for increased replication fidelity. We subsequently identified novel amino acid changes within the RNA-dependent RNA polymerase and nsp14 of MHV-ExoN(-) P250 that partially accounted for the reduced susceptibility to nucleoside analogues. Our results suggest that increased replication fidelity is selected in ExoN(-) CoVs and that there may be a significant barrier to ExoN(-) reversion. These results also support the hypothesis that high-fidelity replication is linked to CoV fitness and indicate that multiple replicase proteins could compensate for ExoN functions during replication.IMPORTANCE Uniquely among RNA viruses, CoVs encode a proofreading exoribonuclease (ExoN) in nsp14 that mediates high-fidelity RNA genome replication. Proofreading-deficient CoVs with disrupted ExoN activity [ExoN(-)] either are nonviable or have significant defects in replication, RNA synthesis, fidelity, fitness, and virulence. In this study, we showed that ExoN(-) murine hepatitis virus can adapt during long-term passage for increased replication and fitness without reverting the ExoN-inactivating mutations. Passage-adapted ExoN(-) mutants also demonstrate increasing resistance to nucleoside analogues that is explained only partially by secondary mutations in nsp12 and nsp14. These data suggest that enhanced resistance to nucleoside analogues is mediated by the interplay of multiple replicase proteins and support the proposed link between CoV fidelity and fitness.

Various mutations compensate for a deleterious lacZα insert in the replication enhancer of M13 bacteriophage

M13 and other members of the Ff class of filamentous bacteriophages have been extensively employed in myriad applications. The Ph.D. series of phage-displayed peptide libraries were constructed from the M13-based vector M13KE. As a direct descendent of M13mp19, M13KE contains the lacZα insert in the intergenic region between genes IV and II, where it interrupts the replication enhancer of the (+) strand origin. Phage carrying this 816-nucleotide insert are viable, but propagate in E. coli at a reduced rate compared to wild-type M13 phage, presumably due to a replication defect caused by the insert. We have previously reported thirteen compensatory mutations in the 5'-untranslated region of gene II, which encodes the replication initiator protein gIIp. Here we report several additional mutations in M13KE that restore a wild-type propagation rate. Several clones from constrained-loop variable peptide libraries were found to have ejected the majority of lacZα gene in order to reconstruct the replication enhancer, albeit with a small scar. In addition, new point mutations in the gene II 5'-untranslated region or the gene IV coding sequence have been spontaneously observed or synthetically engineered. Through phage propagation assays, we demonstrate that all these genetic modifications compensate for the replication defect in M13KE and restore the wild-type propagation rate. We discuss the mechanisms by which the insertion and ejection of the lacZα gene, as well as the mutations in the regulatory region of gene II, influence the efficiency of replication initiation at the (+) strand origin. We also examine the presence and relevance of fast-propagating mutants in phage-displayed peptide libraries.

Strain-dependent mutational effects for Pepino mosaic virus in a natural host

Background

Pepino mosaic virus (PepMV) is an emerging plant pathogen that infects tomatoes worldwide. Understanding the factors that influence its evolutionary success is essential for developing new control strategies that may be more robust against the evolution of new viral strains. One of these evolutionary factors is the distribution of mutational fitness effect (DMFE), that is, the fraction of mutations that are lethal, deleterious, neutral, and beneficial on a given viral strain and host species. The goal of this study was to characterize the DMFE of introduced nonsynonymous mutations on a mild isolate of PepMV from the Chilean 2 strain (PepMV-P22). Additionally, we also explored whether the fitness effect of a given mutation depends on the gene where it appears or on epistatic interactions with the genetic background. To address this latter possibility, a subset of mutations were also introduced in a mild isolate of the European strain (PepMV-P11) and the fitness of the resulting clones measured.

Results

A collection of 25 PepMV clones each containing a single nucleotide nonsynonymous substitution was created by site-directed mutagenesis and the fitness of each mutant was determined. PepMV-P22 genome showed a high degree of robustness against point mutations, with 80% of mutations being either neutral or even beneficial and only 20% being deleterious or lethal. We found that the effect of mutations strongly depended on the gene in which they were introduced. Mutations with the largest average beneficial effects were those affecting the RdRp gene, in contrast to mutations affecting TGB1 and CP genes, for which the average effects were deleterious. Moreover, significant epistatic interactions were observed between nonsynonymous mutations and the genetic background, meaning that the effect of a given nucleotide substitution on a particular genomic context cannot be predicted by knowing its effect in a different one.

Conclusions

Our results indicated that PepMV genome has a surprisingly high robustness against mutations. We also found that fitness consequences of a given mutation differ between the two strains analyzed. This discovery suggests that the strength of selection, and thus the rates of evolution, vary among PepMV strains.

The Mutational Robustness of Influenza A Virus

A virus’ mutational robustness is described in terms of the strength and distribution of the mutational fitness effects, or MFE. The distribution of MFE is central to many questions in evolutionary theory and is a key parameter in models of molecular evolution. Here we define the mutational fitness effects in influenza A virus by generating 128 viruses, each with a single nucleotide mutation. In contrast to mutational scanning approaches, this strategy allowed us to unambiguously assign fitness values to individual mutations. The presence of each desired mutation and the absence of additional mutations were verified by next generation sequencing of each stock. A mutation was considered lethal only after we failed to rescue virus in three independent transfections. We measured the fitness of each viable mutant relative to the wild type by quantitative RT-PCR following direct competition on A549 cells. We found that 31.6% of the mutations in the genome-wide dataset were lethal and that the lethal fraction did not differ appreciably between the HA- and NA-encoding segments and the rest of the genome. Of the viable mutants, the fitness mean and standard deviation were 0.80 and 0.22 in the genome-wide dataset and best modeled as a beta distribution. The fitness impact of mutation was marginally lower in the segments coding for HA and NA (0.88 ± 0.16) than in the other 6 segments (0.78 ± 0.24), and their respective beta distributions had slightly different shape parameters. The results for influenza A virus are remarkably similar to our own analysis of CirSeq-derived fitness values from poliovirus and previously published data from other small, single stranded DNA and RNA viruses. These data suggest that genome size, and not nucleic acid type or mode of replication, is the main determinant of viral mutational fitness effects.

Like other RNA viruses, influenza virus has a very high mutation rate. While high mutation rates may increase the rate at which influenza virus will adapt to a new host, acquire a new route of transmission, or escape from host immune surveillance, data from model systems suggest that most new viral mutations are either lethal or highly detrimental. Mutational robustness refers to the ability of a virus to tolerate, or buffer, these mutations. The mutational robustness of a virus will determine which mutations are maintained in a population and may have a greater impact on viral evolution than mutation rate. We defined the mutational robustness of influenza A virus by measuring the fitness of a large number of viruses, each with a single point mutation. We found that the overall robustness of influenza was similar to that of poliovirus and other viruses of similar size. Interestingly, mutations appeared to be more easily accommodated in hemagglutinin and neuraminidase than elsewhere in the genome. This work will inform models of influenza evolution at the global and molecular scale.

Distribution of mutational fitness effects and of epistasis in the 5' untranslated region of a plant RNA virus

BACKGROUND

Understanding the causes and consequences of phenotypic variability is a central topic of evolutionary biology. Mutations within non-coding cis-regulatory regions are thought to be of major effect since they affect the expression of downstream genes. To address the evolutionary potential of mutations affecting such regions in RNA viruses, we explored the fitness properties of mutations affecting the 5'-untranslated region (UTR) of a prototypical member of the picorna-like superfamily, Tobacco etch virus (TEV). This 5' UTR acts as an internal ribosomal entry site (IRES) and is essential for expression of all viral genes.

RESULTS

We determined in vitro the folding of 5' UTR using the selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) technique. Then, we created a collection of single-nucleotide substitutions on this region and evaluated the statistical properties of their fitness effects in vivo. We found that, compared to random mutations affecting coding sequences, mutations at the 5' UTR were of weaker effect. We also created double mutants by combining pairs of these single mutations and found variation in the magnitude and sign of epistatic interactions, with an enrichment of cases of positive epistasis. A correlation exists between the magnitude of fitness effects and the size of the perturbation made in the RNA folding structure, suggesting that the larger the departure from the predicted fold, the more negative impact in viral fitness.

CONCLUSIONS

Evidence that mutational fitness effects on the short 5' UTR regulatory sequence of TEV are weaker than those affecting its coding sequences have been found. Epistasis among pairs of mutations on the 5' UTR ranged between the extreme cases of synthetic lethal and compensatory. A plausible hypothesis to explain all these observations is that the interaction between the 5' UTR and the host translational machinery was shaped by natural selection to be robust to mutations, thus ensuring the homeostatic expression of viral genes even at high mutation rates.

On the Causes of Evolutionary Transition:Transversion Bias

A pattern in which nucleotide transitions are favored several fold over transversions is common in molecular evolution. When this pattern occurs among amino acid replacements, explanations often invoke an effect of selection, on the grounds that transitions are more conservative in their effects on proteins. However, the underlying hypothesis of conservative transitions has never been tested directly. Here we assess support for this hypothesis using direct evidence: the fitness effects of mutations in actual proteins measured via individual or paired growth experiments. We assembled data from 8 published studies, ranging in size from 24 to 757 single-nucleotide mutations that change an amino acid. Every study has the statistical power to reveal significant effects of amino acid exchangeability, and most studies have the power to discern a binary conservative-vs-radical distinction. However, only one study suggests that transitions are significantly more conservative than transversions. In the combined set of 1,239 replacements (544 transitions, 695 transversions), the chance that a transition is more conservative than a transversion is 53 % (95 % confidence interval 50 to 56) compared with the null expectation of 50 %. We show that this effect is not large compared with that of most biochemical factors, and is not large enough to explain the several-fold bias observed in evolution. In short, the available data have the power to verify the “conservative transitions” hypothesis if true, but suggest instead that selection on proteins plays at best a minor role in the observed bias.

Effects of new mutations on fitness: insights from models and data

The rates and properties of new mutations affecting fitness have implications for a number of outstanding questions in evolutionary biology. Obtaining estimates of mutation rates and effects has historically been challenging, and little theory has been available for predicting the distribution of fitness effects (DFE); however, there have been recent advances on both fronts. Extreme-value theory predicts the DFE of beneficial mutations in well-adapted populations, while phenotypic fitness landscape models make predictions for the DFE of all mutations as a function of the initial level of adaptation and the strength of stabilizing selection on traits underlying fitness. Direct experimental evidence confirms predictions on the DFE of beneficial mutations and favors distributions that are roughly exponential but bounded on the right. A growing number of studies infer the DFE using genomic patterns of polymorphism and divergence, recovering a wide range of DFE. Future work should be aimed at identifying factors driving the observed variation in the DFE. We emphasize the need for further theory explicitly incorporating the effects of partial pleiotropy and heterogeneity in the environment on the expected DFE.

A comprehensive, high-resolution map of a gene's fitness landscape

Mutations are central to evolution, providing the genetic variation upon which selection acts. A mutation’s effect on the suitability of a gene to perform a particular function (gene fitness) can be positive, negative, or neutral. Knowledge of the distribution of fitness effects (DFE) of mutations is fundamental for understanding evolutionary dynamics, molecular-level genetic variation, complex genetic disease, the accumulation of deleterious mutations, and the molecular clock. We present comprehensive DFEs for point and codon mutants of the Escherichia coli TEM-1 β-lactamase gene and missense mutations in the TEM-1 protein. These DFEs provide insight into the inherent benefits of the genetic code’s architecture, support for the hypothesis that mRNA stability dictates codon usage at the beginning of genes, an extensive framework for understanding protein mutational tolerance, and evidence that mutational effects on protein thermodynamic stability shape the DFE. Contrary to prevailing expectations, we find that deleterious effects of mutation primarily arise from a decrease in specific protein activity and not cellular protein levels.

Fold or hold: experimental evolution in vitro

We introduce a system for experimental evolution consisting of populations of short oligonucleotides (Oli populations) evolving in a modified quantitative polymerase chain reaction (qPCR). It is tractable at the genetic, genomic, phenotypic and fitness levels. The Oli system uses DNA hairpins designed to form structures that self-prime under defined conditions. Selection acts on the phenotype of self-priming, after which differences in fitness are amplified and quantified using qPCR. We outline the methodological and bioinformatics tools for the Oli system here and demonstrate that it can be used as a conventional experimental evolution model system by test-driving it in an experiment investigating adaptive evolution under different rates of environmental change.

Microbial evolution in vivo and in silico: methods and applications

Microbial evolution has been extensively studied in the past fifty years, which has lead to seminal discoveries that have shaped our understanding of evolutionary forces and dynamics. It is only recently however, that transformative technologies and computational advances have enabled a larger in-scale and in-depth investigation of the genetic basis and mechanistic underpinnings of evolutionary adaptation. In this review we focus on the strengths and limitations of in vivo and in silico techniques for studying microbial evolution in the laboratory, and we discuss how these complementary approaches can be integrated in a unifying framework for elucidating microbial evolution.

Latent effects of Hsp90 mutants revealed at reduced expression levels

In natural systems, selection acts on both protein sequence and expression level, but it is unclear how selection integrates over these two dimensions. We recently developed the EMPIRIC approach to systematically determine the fitness effects of all possible point mutants for important regions of essential genes in yeast. Here, we systematically investigated the fitness effects of point mutations in a putative substrate binding loop of yeast Hsp90 (Hsp82) over a broad range of expression strengths. Negative epistasis between reduced expression strength and amino acid substitutions was common, and the endogenous expression strength frequently obscured mutant defects. By analyzing fitness effects at varied expression strengths, we were able to uncover all mutant effects on function. The majority of mutants caused partial functional defects, consistent with this region of Hsp90 contributing to a mutation sensitive and critical process. These results demonstrate that important functional regions of proteins can tolerate mutational defects without experimentally observable impacts on fitness.

Extreme genetic fragility of the HIV-1 capsid

Genetic robustness, or fragility, is defined as the ability, or lack thereof, of a biological entity to maintain function in the face of mutations. Viruses that replicate via RNA intermediates exhibit high mutation rates, and robustness should be particularly advantageous to them. The capsid (CA) domain of the HIV-1 Gag protein is under strong pressure to conserve functional roles in viral assembly, maturation, uncoating, and nuclear import. However, CA is also under strong immunological pressure to diversify. Therefore, it would be particularly advantageous for CA to evolve genetic robustness. To measure the genetic robustness of HIV-1 CA, we generated a library of single amino acid substitution mutants, encompassing almost half the residues in CA. Strikingly, we found HIV-1 CA to be the most genetically fragile protein that has been analyzed using such an approach, with 70% of mutations yielding replication-defective viruses. Although CA participates in several steps in HIV-1 replication, analysis of conditionally (temperature sensitive) and constitutively non-viable mutants revealed that the biological basis for its genetic fragility was primarily the need to coordinate the accurate and efficient assembly of mature virions. All mutations that exist in naturally occurring HIV-1 subtype B populations at a frequency >3%, and were also present in the mutant library, had fitness levels that were >40% of WT. However, a substantial fraction of mutations with high fitness did not occur in natural populations, suggesting another form of selection pressure limiting variation in vivo. Additionally, known protective CTL epitopes occurred preferentially in domains of the HIV-1 CA that were even more genetically fragile than HIV-1 CA as a whole. The extreme genetic fragility of HIV-1 CA may be one reason why cell-mediated immune responses to Gag correlate with better prognosis in HIV-1 infection, and suggests that CA is a good target for therapy and vaccination strategies.

The HIV-1 capsid protein (CA) is absolutely essential for viral replication and there is, therefore, intense evolutionary pressure for HIV-1 CA to conserve its functions. However, HIV-1 CA is also a key target of the host immune response, which should provide evolutionary pressure to diversify CA sequence. Genetic robustness, or fragility, is defined as the ability, or lack thereof, of a biological entity to preserve function in the face of sequence changes. Thus, it should be advantageous to HIV-1 CA to evolve genetic robustness. Here, we present the results of extensive, random mutagenesis of single amino acids in CA that reveal an extreme genetic fragility. Although CA participates in several steps in HIV-1 replication, the biological basis for its genetic fragility was primarily the need to participate in the efficient and proper assembly of mature virion particles. The extreme genetic fragility of HIV-1 CA may be one reason why immune responses to it correlate with better prognosis in HIV-1 infection, and suggests that CA is a good target for therapy and vaccination strategies.

Random codon re-encoding induces stable reduction of replicative fitness of Chikungunya virus in primate and mosquito cells

Large-scale codon re-encoding represents a powerful method of attenuating viruses to generate safe and cost-effective vaccines. In contrast to specific approaches of codon re-encoding which modify genome-scale properties, we evaluated the effects of random codon re-encoding on the re-emerging human pathogen Chikungunya virus (CHIKV), and assessed the stability of the resultant viruses during serial in cellulo passage. Using different combinations of three 1.4 kb randomly re-encoded regions located throughout the CHIKV genome six codon re-encoded viruses were obtained. Introducing a large number of slightly deleterious synonymous mutations reduced the replicative fitness of CHIKV in both primate and arthropod cells, demonstrating the impact of synonymous mutations on fitness. Decrease of replicative fitness correlated with the extent of re-encoding, an observation that may assist in the modulation of viral attenuation. The wild-type and two re-encoded viruses were passaged 50 times either in primate or insect cells, or in each cell line alternately. These viruses were analyzed using detailed fitness assays, complete genome sequences and the analysis of intra-population genetic diversity. The response to codon re-encoding and adaptation to culture conditions occurred simultaneously, resulting in significant replicative fitness increases for both re-encoded and wild type viruses. Importantly, however, the most re-encoded virus failed to recover its replicative fitness. Evolution of these viruses in response to codon re-encoding was largely characterized by the emergence of both synonymous and non-synonymous mutations, sometimes located in genomic regions other than those involving re-encoding, and multiple convergent and compensatory mutations. However, there was a striking absence of codon reversion (<0.4%). Finally, multiple mutations were rapidly fixed in primate cells, whereas mosquito cells acted as a brake on evolution. In conclusion, random codon re-encoding provides important information on the evolution and genetic stability of CHIKV viruses and could be exploited to develop a safe, live attenuated CHIKV vaccine.

Emerging arthropod-borne viruses (arboviruses) are a major cause of human and animal morbidity and mortality. Climatic and anthropological activities are responsible for the dispersal of arbovirus transmission vectors into new territories. Chikungunya virus (CHIKV) is an important example of a re-emerging pathogen for which no licensed vaccine exists. One of the vectors of CHIKV, the mosquito Aedes albopictus, has dispersed into new temperate regions resulting in outbreaks where they had not been previously observed. Here, we demonstrate that random codon re-encoding, a method that modifies the nucleic acid composition of large coding regions without modifying the encoded proteins, can significantly decrease the replicative fitness of CHIKV. This powerful method of attenuating viruses has several potential advantages for vaccine development, including the possibility to modulate precisely the degree of replicative fitness loss and to generate safe, live-attenuated vaccines that confer long-term protection, in a cost effective manner. Our studies also demonstrate that these re-encoded viruses exhibit a stable phenotype, and that the response to codon re-encoding was largely compensatory in nature, with little reversion of mutations. Finally, we provide further evidence that many synonymous sites in RNA viruses are not neutral and clearly impact viral fitness.

Viral diversity threshold for adaptive immunity in prokaryotes

Bacteria and archaea face continual onslaughts of rapidly diversifying viruses and plasmids. Many prokaryotes maintain adaptive immune systems known as clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated genes (Cas). CRISPR-Cas systems are genomic sensors that serially acquire viral and plasmid DNA fragments (spacers) that are utilized to target and cleave matching viral and plasmid DNA in subsequent genomic invasions, offering critical immunological memory. Only 50% of sequenced bacteria possess CRISPR-Cas immunity, in contrast to over 90% of sequenced archaea. To probe why half of bacteria lack CRISPR-Cas immunity, we combined comparative genomics and mathematical modeling. Analysis of hundreds of diverse prokaryotic genomes shows that CRISPR-Cas systems are substantially more prevalent in thermophiles than in mesophiles. With sequenced bacteria disproportionately mesophilic and sequenced archaea mostly thermophilic, the presence of CRISPR-Cas appears to depend more on environmental temperature than on bacterial-archaeal taxonomy. Mutation rates are typically severalfold higher in mesophilic prokaryotes than in thermophilic prokaryotes. To quantitatively test whether accelerated viral mutation leads microbes to lose CRISPR-Cas systems, we developed a stochastic model of virus-CRISPR coevolution. The model competes CRISPR-Cas-positive (CRISPR-Cas+) prokaryotes against CRISPR-Cas-negative (CRISPR-Cas−) prokaryotes, continually weighing the antiviral benefits conferred by CRISPR-Cas immunity against its fitness costs. Tracking this cost-benefit analysis across parameter space reveals viral mutation rate thresholds beyond which CRISPR-Cas cannot provide sufficient immunity and is purged from host populations. These results offer a simple, testable viral diversity hypothesis to explain why mesophilic bacteria disproportionately lack CRISPR-Cas immunity. More generally, fundamental limits on the adaptability of biological sensors (Lamarckian evolution) are predicted.

A remarkable recent discovery in microbiology is that bacteria and archaea possess systems conferring immunological memory and adaptive immunity. Clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated genes (CRISPR-Cas) are genomic sensors that allow prokaryotes to acquire DNA fragments from invading viruses and plasmids. Providing immunological memory, these stored fragments destroy matching DNA in future viral and plasmid invasions. CRISPR-Cas systems also provide adaptive immunity, keeping up with mutating viruses and plasmids by continually acquiring new DNA fragments. Surprisingly, less than 50% of mesophilic bacteria, in contrast to almost 90% of thermophilic bacteria and Archaea, maintain CRISPR-Cas immunity. Using mathematical modeling, we probe this dichotomy, showing how increased viral mutation rates can explain the reduced prevalence of CRISPR-Cas systems in mesophiles. Rapidly mutating viruses outrun CRISPR-Cas immune systems, likely decreasing their prevalence in bacterial populations. Thus, viral adaptability may select against, rather than for, immune adaptability in prokaryotes.

Viral fitness: definitions, measurement, and current insights

Viral fitness is an active area of research, with recent work involving an expanded number of human, non-human vertebrate, invertebrate, plant, and bacterial viruses. Many publications deal with RNA viruses associated with major disease emergence events, such as HIV-1, influenza virus, and Dengue virus. Study topics include drug resistance, immune escape, viral emergence, host jumps, mutation effects, quasispecies diversity, and mathematical models of viral fitness. Important recent trends include increasing use of in vivo systems to assess vertebrate virus fitness, and a broadening of research beyond replicative fitness to also investigate transmission fitness and epidemiologic fitness. This is essential for a more integrated understanding of overall viral fitness, with implications for disease management in the future.

Horizontal gene transfer dynamics and distribution of fitness effects during microbial in silico evolution

Background

Horizontal gene transfer (HGT) is a process that facilitates the transfer of genetic material between organisms that are not directly related, and thus can affect both the rate of evolution and emergence of traits. Recent phylogenetic studies reveal HGT events are likely ubiquitous in the Tree of Life. However, our knowledge of HGT's role in evolution and biological organization is very limited, mainly due to the lack of ancestral evolutionary signatures and the difficulty to observe complex evolutionary dynamics in a laboratory setting. Here, we utilize a multi-scale microbial evolution model to comprehensively study the effect of HGT on the evolution of complex traits and organization of gene regulatory networks.

Results

Large-scale simulations reveal a distinct signature of the Distribution of Fitness Effect (DFE) for HGT events: during evolution, while mutation fitness effects become more negative and neutral, HGT events result in a balanced effect distribution. In either case, lethal events are significantly decreased during evolution (33.0% to 3.2%), a clear indication of mutational robustness. Interestingly, evolution was accelerated when populations were exposed to correlated environments of increasing complexity, especially in the presence of HGT, a phenomenon that warrants further investigation. High HGT rates were found to be disruptive, while the average transferred fragment size was linked to functional module size in the underlying biological network. Network analysis reveals that HGT results in larger regulatory networks, but with the same sparsity level as those evolved in its absence. Observed phenotypic variability and co-existing solutions were traced to individual gain/loss of function events, while subsequent re-wiring after fragment integration was necessary for complex traits to emerge.

The phenotype-fitness map in experimental evolution of phages

Evolutionary biologists commonly interpret adaptations of organisms by reference to a phenotype-fitness map, a model of how different states of a phenotype affect fitness. Notwithstanding the popularity of this approach, it remains difficult to directly test these mappings, both because the map often describes only a small subset of phenotypes contributing to total fitness and because direct measures of fitness are difficult to obtain and compare to the map. Both limitations can be overcome for bacterial viruses (phages) grown in the experimental condition of unlimited hosts. A complete accounting of fitness requires 3 easily measured phenotypes, and total fitness is also directly measurable for arbitrary genotypes. Yet despite the presumed transparency of this system, directly estimated fitnesses often differ from fitnesses calculated from the phenotype-fitness map. This study attempts to resolve these discrepancies, both by developing a more exact analytical phenotype-fitness map and by exploring the empirical foundations of direct fitness estimates. We derive an equation (the phenotype-fitness map) for exponential phage growth that allows an arbitrary distribution of lysis times and burst sizes. We also show that direct estimates of fitness are, in many cases, plausibly in error because the population has not attained stable age distribution and thus violates the model underlying the phenotype-fitness map. In conjunction with data provided here, the new understanding appears to resolve a discrepancy between the reported fitness of phage T7 and the substantially lower value calculated from its phenotype-fitness map.

Effect of host species on the distribution of mutational fitness effects for an RNA virus

Knowledge about the distribution of mutational fitness effects (DMFE) is essential for many evolutionary models. In recent years, the properties of the DMFE have been carefully described for some microorganisms. In most cases, however, this information has been obtained only for a single environment, and very few studies have explored the effect that environmental variation may have on the DMFE. Environmental effects are particularly relevant for the evolution of multi-host parasites and thus for the emergence of new pathogens. Here we characterize the DMFE for a collection of twenty single-nucleotide substitution mutants of Tobacco etch potyvirus (TEV) across a set of eight host environments. Five of these host species were naturally infected by TEV, all belonging to family Solanaceae, whereas the other three were partially susceptible hosts belonging to three other plant families. First, we found a significant virus genotype-by-host species interaction, which was sustained by differences in genetic variance for fitness and the pleiotropic effect of mutations among hosts. Second, we found that the DMFEs were markedly different between Solanaceae and non-Solanaceae hosts. Exposure of TEV genotypes to non-Solanaceae hosts led to a large reduction of mean viral fitness, while the variance remained constant and skewness increased towards the right tail. Within the Solanaceae hosts, the distribution contained an excess of deleterious mutations, whereas for the non-Solanaceae the fraction of beneficial mutations was significantly larger. All together, this result suggests that TEV may easily broaden its host range and improve fitness in new hosts, and that knowledge about the DMFE in the natural host does not allow for making predictions about its properties in an alternative host.

Measuring selection coefficients below 10(-3): method, questions, and prospects

Measuring fitness with precision is a key issue in evolutionary biology, particularly in studying mutations of small effects. It is usually thought that sampling error and drift prevent precise measurement of very small fitness effects. We circumvented these limits by using a new combined approach to measuring and analyzing fitness. We estimated the mutational fitness effect (MFE) of three independent mini-Tn10 transposon insertion mutations by conducting competition experiments in large populations of Escherichia coli under controlled laboratory conditions. Using flow cytometry to assess genotype frequencies from very large samples alleviated the problem of sampling error, while the effect of drift was controlled by using large populations and massive replication of fitness measures. Furthermore, with a set of four competition experiments between ancestral and mutant genotypes, we were able to decompose fitness measures into four estimated parameters that account for fitness effects of our fluorescent marker (α), the mutation (β), epistasis between the mutation and the marker (γ), and departure from transitivity (τ). Our method allowed us to estimate mean selection coefficients to a precision of 2 × 10(-4). We also found small, but significant, epistatic interactions between the allelic effects of mutations and markers and confirmed that fitness effects were transitive in most cases. Unexpectedly, we also detected variation in measures of s that were significantly bigger than expected due to drift alone, indicating the existence of cryptic variation, even in fully controlled experiments. Overall our results indicate that selection coefficients are best understood as being distributed, representing a limit on the precision with which selection can be measured, even under controlled laboratory conditions.

The fitness effects of synonymous mutations in DNA and RNA viruses

Despite being silent with respect to protein sequence, synonymous nucleotide substitutions can be targeted by natural selection directly at the DNA or RNA level. However, there has been no systematic assessment of how frequent this type of selection is. Here, we have constructed 53 single random synonymous substitution mutants of the bacteriophages Qβ and ΦX174 by site-directed mutagenesis and assayed their fitness. Analysis of this mutant collection and of previous studies undertaken with a variety of single-stranded (ss) viruses demonstrates that selection at synonymous sites is stronger in RNA viruses than in DNA viruses. We estimate that this type of selection contributes approximately 18% of the overall mutational fitness effects in ssRNA viruses under our assay conditions and that random synonymous substitutions have a 5% chance of being lethal to the virus, whereas in ssDNA viruses, these figures drop to 1.4% and 0%, respectively. In contrast, the effects of nonsynonymous substitutions appear to be similar in ssRNA and ssDNA viruses.

Experimental evolution of RNA versus DNA viruses

Based on their extremely high mutation rates, RNA viruses have been traditionally considered as the fastest evolving entities in nature. However, recent work has revealed that, despite their greater replication fidelity, single-stranded (ss) DNA viruses can evolve fast in a similar way. To further investigate this issue, we have compared the rates of adaptation and molecular evolution of ssRNA and ssDNA viruses under highly controlled laboratory conditions using the bacteriophages ΦX174, G4, f1, Qβ, SP, and MS2 as model systems. Our results indicate that ssRNA phages evolve faster than ssDNA phages under strong selective pressure, and that their extremely high mutation rates appear to be optimal for this kind of scenario. However, their performance becomes similar to that of ssDNA phages over the longer term or when the population is moderately well-adapted. Interestingly, the roughly 100-fold difference between the mutation rates of ssRNA and ssDNA phages yields less than a fivefold difference in adaptation and nucleotide substitution rates. The results are therefore consistent with the observation that, despite their lower mutation rates, ssDNA viruses can sometimes match the evolvability of RNA viruses.

A biophysical protein folding model accounts for most mutational fitness effects in viruses

Fitness effects of mutations fall on a continuum ranging from lethal to deleterious to beneficial. The distribution of fitness effects (DFE) among random mutations is an essential component of every evolutionary model and a mathematical portrait of robustness. Recent experiments on five viral species all revealed a characteristic bimodal-shaped DFE featuring peaks at neutrality and lethality. However, the phenotypic causes underlying observed fitness effects are still unknown and presumably, are thought to vary unpredictably from one mutation to another. By combining population genetics simulations with a simple biophysical protein folding model, we show that protein thermodynamic stability accounts for a large fraction of observed mutational effects. We assume that moderately destabilizing mutations inflict a fitness penalty proportional to the reduction in folded protein, which depends continuously on folding free energy (ΔG). Most mutations in our model affect fitness by altering ΔG, whereas based on simple estimates, ~10% abolish activity and are unconditionally lethal. Mutations pushing ΔG > 0 are also considered lethal. Contrary to neutral network theory, we find that, in mutation/selection/drift steady state, high mutation rates (m) lead to less stable proteins and a more dispersed DFE (i.e., less mutational robustness). Small population size (N) also decreases stability and robustness. In our model, a continuum of nonlethal mutations reduces fitness by ~2% on average, whereas ~10-35% of mutations are lethal depending on N and m. Compensatory mutations are common in small populations with high mutation rates. More broadly, we conclude that interplay between biophysical and population genetic forces shapes the DFE.

The effects of low-impact mutations in digital organisms

Background

Avida is a computer program that performs evolution experiments with digital organisms. Previous work has used the program to study the evolutionary origin of complex features, namely logic operations, but has consistently used extremely large mutational fitness effects. The present study uses Avida to better understand the role of low-impact mutations in evolution.

Results

When mutational fitness effects were approximately 0.075 or less, no new logic operations evolved, and those that had previously evolved were lost. When fitness effects were approximately 0.2, only half of the operations evolved, reflecting a threshold for selection breakdown. In contrast, when Avida's default fitness effects were used, all operations routinely evolved to high frequencies and fitness increased by an average of 20 million in only 10,000 generations.

Conclusions

Avidian organisms evolve new logic operations only when mutations producing them are assigned high-impact fitness effects. Furthermore, purifying selection cannot protect operations with low-impact benefits from mutational deterioration. These results suggest that selection breaks down for low-impact mutations below a certain fitness effect, the selection threshold. Experiments using biologically relevant parameter settings show the tendency for increasing genetic load to lead to loss of biological functionality. An understanding of such genetic deterioration is relevant to human disease, and may be applicable to the control of pathogens by use of lethal mutagenesis.

Mutational fitness effects in RNA and single-stranded DNA viruses: common patterns revealed by site-directed mutagenesis studies

The fitness effects of mutations are central to evolution, yet have begun to be characterized in detail only recently. Site-directed mutagenesis is a powerful tool for achieving this goal, which is particularly suited for viruses because of their small genomes. Here, I discuss the evolutionary relevance of mutational fitness effects and critically review previous site-directed mutagenesis studies. The effects of single-nucleotide substitutions are standardized and compared for five RNA or single-stranded DNA viruses infecting bacteria, plants or animals. All viruses examined show very low tolerance to mutation when compared with cellular organisms. Moreover, for non-lethal mutations, the mean fitness reduction caused by single mutations is remarkably constant (0.10-0.13), whereas the fraction of lethals varies only modestly (0.20-0.41). Other summary statistics are provided. These generalizations about the distribution of mutational fitness effects can help us to better understand the evolution of RNA and single-stranded DNA viruses.

Viral mutation rates

Accurate estimates of virus mutation rates are important to understand the evolution of the viruses and to combat them. However, methods of estimation are varied and often complex. Here, we critically review over 40 original studies and establish criteria to facilitate comparative analyses. The mutation rates of 23 viruses are presented as substitutions per nucleotide per cell infection (s/n/c) and corrected for selection bias where necessary, using a new statistical method. The resulting rates range from 10(-8) to 10(-6) s/n/c for DNA viruses and from 10(-6) to 10(-4) s/n/c for RNA viruses. Similar to what has been shown previously for DNA viruses, there appears to be a negative correlation between mutation rate and genome size among RNA viruses, but this result requires further experimental testing. Contrary to some suggestions, the mutation rate of retroviruses is not lower than that of other RNA viruses. We also show that nucleotide substitutions are on average four times more common than insertions/deletions (indels). Finally, we provide estimates of the mutation rate per nucleotide per strand copying, which tends to be lower than that per cell infection because some viruses undergo several rounds of copying per cell, particularly double-stranded DNA viruses. A regularly updated virus mutation rate data set will be available at www.uv.es/rsanjuan/virmut.