Evolvability of an RNA virus is determined by its mutational neighbourhood

Escherichia coli adaptation under prolonged resource exhaustion is characterized by extreme parallelism and frequent historical contingency

Like many other non-sporulating bacterial species, Escherichia coli is able to survive prolonged periods of resource exhaustion, by entering a state of growth called long-term stationary phase (LTSP). In July 2015, we initiated a set of evolutionary experiments aimed at characterizing the dynamics of E. coli adaptation under LTSP. In these experiments populations of E. coli were allowed to initially grow on fresh rich media, but where not provided with any new external growth resources since their establishment. Utilizing whole genome sequencing data obtained for hundreds of clones sampled at 12 time points spanning the first six years of these experiments, we reveal several novel aspects of the dynamics of adaptation. First, we show that E. coli continuously adapts genetically, up to six years under resource exhaustion, through the highly convergent accumulation of mutations. We further show that upon entry into LTSP, long-lasting lineages are established. This lineage structure is in itself convergent, with similar lineages arising across independently evolving populations. The high parallelism with which adaptations occur under LTSP, combined with the LTSP populations' lineage structure, enable us to screen for pairs of loci displaying a significant association in the occurrence of mutations, suggestive of a historical contingency. We find that such associations are highly frequent and that a third of convergently mutated loci are involved in at least one such association. Combined our results demonstrate that LTSP adaptation is characterized by remarkably high parallelism and frequent historical contingency.

Signatures of adaptive decreased virulence of deformed wing virus in an isolated population of wild honeybees (Apis mellifera)

Understanding the ecological and evolutionary processes that drive host-pathogen interactions is critical for combating epidemics and conserving species. The Varroa destructor mite and deformed wing virus (DWV) are two synergistic threats to Western honeybee (Apis mellifera) populations across the globe. Distinct honeybee populations have been found to self-sustain despite Varroa infestations, including colonies within the Arnot Forest outside Ithaca, NY, USA. We hypothesized that in these bee populations, DWV has been selected to produce an avirulent infection phenotype, allowing for the persistence of both host and disease-causing agents. To investigate this, we assessed the titre of viruses in bees from the Arnot Forest and managed apiaries, and assessed genomic variation and virulence differences between DWV isolates. Across groups, we found viral abundance was similar, but DWV genotypes were distinct. We also found that infections with isolates from the Arnot Forest resulted in higher survival and lower rates of symptomatic deformed wings, compared to analogous isolates from managed colonies, providing preliminary evidence to support the hypothesis of adaptive decreased viral virulence. Overall, this multi-level investigation of virus genotype and phenotype indicates that host ecological context can be a significant driver of viral evolution and host-pathogen interactions in honeybees.

The Surprising Ease of Finding Optimal Solutions for Controlling Nonlinear Phenomena in Quantum and Classical Complex Systems

This Perspective addresses the often observed surprising ease of achieving optimal control of nonlinear phenomena in quantum and classical complex systems. The circumstances involved are wide-ranging, with scenarios including manipulation of atomic scale processes, maximization of chemical and material properties or synthesis yields, Nature's optimization of species' populations by natural selection, and directed evolution. Natural evolution will mainly be discussed in terms of laboratory experiments with microorganisms, and the field is also distinct from the other domains where a scientist specifies the goal(s) and oversees the control process. We use the word "control" in reference to all of the available variables, regardless of the circumstance. The empirical observations on the ease of achieving at least good, if not excellent, control in diverse domains of science raise the question of why this occurs despite the generally inherent complexity of the systems in each scenario. The key to addressing the question lies in examining the associated control landscape, which is defined as the optimization objective as a function of the control variables that can be as diverse as the phenomena under consideration. Controls may range from laser pulses, chemical reagents, chemical processing conditions, out to nucleic acids in the genome and more. This Perspective presents a conjecture, based on present findings, that the systematics of readily finding good outcomes from controlled phenomena may be unified through consideration of control landscapes with the same common set of three underlying assumptions─the existence of an optimal solution, the ability for local movement on the landscape, and the availability of sufficient control resources─whose validity needs assessment in each scenario. In practice, many cases permit using myopic gradient-like algorithms while other circumstances utilize algorithms having some elements of stochasticity or introduced noise, depending on whether the landscape is locally smooth or rough. The overarching observation is that only relatively short searches are required despite the common high dimensionality of the available controls in typical scenarios.

Roles of p53-Mediated Host–Virus Interaction in Coronavirus Infection

The emergence of the SARS-CoV-2 coronavirus has garnered global attention due to its highly pathogenic nature and the resulting health crisis and economic burden. Although drugs such as Remdesivir have been considered a potential cure by targeting the virus on its RNA polymerase, the high mutation rate and unique 3’ to 5’ exonuclease with proofreading function make it challenging to develop effective anti-coronavirus drugs. As a result, there is an increasing focus on host–virus interactions because coronaviruses trigger stress responses, cell cycle changes, apoptosis, autophagy, and the dysregulation of immune function and inflammation in host cells. The p53 tumor suppressor molecule is a critical regulator of cell signaling pathways, cellular stress responses, DNA repair, and apoptosis. However, viruses can activate or inhibit p53 during viral infections to enhance viral replication and spread. Given its pivotal role in cell physiology, p53 represents a potential target for anti-coronavirus drugs. This review aims to summarize the relationship between p53 and coronaviruses from various perspectives, to shed light on potential targets for antiviral drug development and vaccine design.

Attenuation of Avian Flavivirus by Rewiring the Leucine and Serine Codons of Its E-NS1 Protein toward Stop Mutation To Redirect Virus Evolution

Recently, a new strategy for attenuating RNA viruses by redirecting their evolution in sequence space was confirmed for Enterovirus and Influenza viruses. Using avian flavivirus as a model, the 69 serine and 53 leucine codons on the E-NS1 genes were modified to change evolutionary direction of the viral sequence space. This means that all codons encoding serine or leucine residues were substituted with codons that are only one base different from the three stop codons, resulting in the initial position of the virus genome in sequence space being closer to the detrimental areas to achieve attenuation by reducing viral adaptability. The growth curve and plaque size of CQW1-one-to-stop (CQW1-OTS) were similar to those of CQW1-wild type (CQW1-WT) in vitro, but attenuated proliferation was detected when treated with a mutagenic reagent (ribavirin). However, comparably high CQW1-OTS and CQW1-WT lethality rates were detected in 9-day-old duck embryos and 5-day-old ducklings, suggesting that this strategy works but with limitations. With that in mind, homologous hosts in nonsensitive age (25-day-old ducks) and heterologous hosts (3-week-old Kunming mice) were employed to investigate if CQW1-OTS was attenuated under host selection pressure. Minimal attenuation of CQW1-OTS in elder ducks and apparent attenuation in mice were reported, providing reduced viral titers, mild clinical signs, and lower specific infectivity. Collectively, we experimentally demonstrate that the attenuation strategy of redirecting virus evolution in sequence space works for flavivirus. Redirection of the virus is attenuated only under some outside pressure, such as heterologous hosts or antiviral drugs treatment, limiting its usage in flaviviruses. IMPORTANCE Flaviviruses are medically important arboviruses that threaten public health, but no approved treatments are currently available. Vaccines prevent flavivirus infection. We employed duck Tembusu virus (TMUV), a mosquito-borne flavivirus, to evaluate virus redirection. TMUV is native to birds and could infect mice by intracerebral injection, making it an experimental animal model to study flavivirus characteristics in vivo. The 69 serine and 53 leucine codons on the E-NS1 proteins of CQW1 were synonymously substituted to change evolutionary direction of the virus in sequence space. In vitro mutagen reagent treatment suppressed CQW1-OTS viral multiplication, but in vivo attenuation depended on host selective pressure. CQW1-OTS viral attenuation was observed in older ducks but not sensitive ducklings; considerable attenuation was also observed in heterogenous host (mice), which provides more selective pressure on viruses. Collectively, these data indicated that there are very important preconditions for application of evaluating whether this strategy shows application prospects in novel flavivirus vaccine development.

Small-Sample Estimation of the Mutational Support and Distribution of SARS-CoV-2

We consider the problem of determining the mutational support and distribution of the SARS-CoV-2 viral genome in the small-sample regime. The mutational support refers to the unknown number of sites that may eventually mutate in the SARS-CoV-2 genome while mutational distribution refers to the distribution of point mutations in the viral genome across a population. The mutational support may be used to assess the virulence of the virus and guide primer selection for real-time RT-PCR testing. Estimating the distribution of mutations in the genome of different subpopulations while accounting for the unseen may also aid in discovering new variants. To estimate the mutational support in the small-sample regime, we use GISAID sequencing data and our state-of-the-art polynomial estimation techniques based on new weighted and regularized Chebyshev approximation methods. For distribution estimation, we adapt the well-known Good-Turing estimator. Our analysis reveals several findings: First, the mutational supports exhibit significant differences in the ORF6 and ORF7a regions (older versus younger patients), ORF1b and ORF10 regions (females versus males) and in almost all ORFs (Asia/Europe/North America). Second, even though the N region of SARS-CoV-2 has a predicted 10% mutational support, mutations fall outside of the primer regions recommended by the CDC.

Fitness of evolving bacterial populations is contingent on deep and shallow history but only shallow history creates predictable patterns

Long-term evolution experiments have tested the importance of genetic and environmental factors in influencing evolutionary outcomes. Differences in phylogenetic history, recent adaptation to distinct environments and chance events, all influence the fitness of a population. However, the interplay of these factors on a population's evolutionary potential remains relatively unexplored. We tracked the outcome of 2000 generations of evolution of four natural isolates of Escherichia coli bacteria that were engineered to also create differences in shallow history by adding previously identified mutations selected in a separate long-term experiment. Replicate populations started from each progenitor evolved in four environments. We found that deep and shallow phylogenetic histories both contributed significantly to differences in evolved fitness, though by different amounts in different selection environments. With one exception, chance effects were not significant. Whereas the effect of deep history did not follow any detectable pattern, effects of shallow history followed a pattern of diminishing returns whereby fitter ancestors had smaller fitness increases. These results are consistent with adaptive evolution being contingent on the interaction of several evolutionary forces but demonstrate that the nature of these interactions is not fixed and may not be predictable even when the role of chance is small.

Changes in the growth rate of Chlamydomonas reinhardtii under long-term selection by temperature and salinity: Acclimation vs. evolution

We investigated the roles of acclimation and different components involved in evolution (adaptation, chance and history) on the changes in the growth rate of the model freshwater microalga Chlamydomonas reinhardtii P. A. Dang. exposed to selective temperature and salinity. Three C. reinhardtii strains previously grown during one year in freshwater medium and 20 °C were exposed to 5 °C temperature increase and a salinity of 5 g L^-1 NaCl. Cultures under each selective scenario and in combination (increase of salinity and temperature), were propagated until growth rate achieved an invariant mean value for 6 months (100-350 generations, varying as a function of scenario and strain). The changes of the growth rate under increased temperature were due to both adaptation and acclimation, as well as history. However, acclimation was the only mechanism detected under salinity increase as well as in the selective scenario of both temperature and salinity, suggesting that genetic variability would not allow survival at salinity higher than that to which experimental populations were exposed. Therefore, it could be hypothesized that under a global change scenario an increase in salinity would be a greater challenge than warming for some freshwater phytoplankton.

Mitonuclear Mismatch is Associated With Increased Male Frequency, Outcrossing, and Male Sperm Size in Experimentally-Evolved C. elegans

We provide a partial test of the mitonuclear sex hypothesis with the first controlled study of how male frequencies and rates of outcrossing evolve in response to mitonuclear mismatch by allowing replicate lineages of C. elegans nematodes containing either mitochondrial or nuclear mutations of electron transport chain (ETC) genes to evolve under three sexual systems: facultatively outcrossing (wildtype), obligately selfing, and obligately outcrossing. Among facultatively outcrossing lines, we found evolution of increased male frequency in at least one replicate line of all four ETC mutant backgrounds tested—nuclear isp-1, mitochondrial cox-1 and ctb-1, and an isp-1 IV; ctb-1M mitonuclear double mutant—and confirmed for a single line set (cox-1) that increased male frequency also resulted in successful outcrossing. We previously found the same result for lines evolved from another nuclear ETC mutant, gas-1. For several lines in the current experiment, however, male frequency declined to wildtype levels (near 0%) in later generations. Male frequency did not change in lines evolved from a wildtype control strain. Additional phenotypic assays of lines evolved from the mitochondrial cox-1 mutant indicated that evolution of high male frequency was accompanied by evolution of increased male sperm size and mating success with tester females, but that it did not translate into increased mating success with coevolved hermaphrodites. Rather, hermaphrodites’ self-crossed reproductive fitness increased, consistent with sexually antagonistic coevolution. In accordance with evolutionary theory, males and sexual outcrossing may be most beneficial to populations evolving from a state of low ancestral fitness (gas-1, as previously reported) and less beneficial or deleterious to those evolving from a state of higher ancestral fitness (cox-1). In support of this idea, the obligately outcrossing fog-2 V; cox-1 M lines exhibited no fitness evolution compared to their ancestor, while facultatively outcrossing lines showed slight upward evolution of fitness, and all but one of the obligately selfing xol-1 X; cox-1 M lines evolved substantially increased fitness—even beyond wildtype levels. This work provides a foundation to directly test the effect of reproductive mode on the evolutionary dynamics of mitonuclear genomes, as well as whether compensatory mutations (nuclear or mitochondrial) can rescue populations from mitochondrial dysfunction.

Why are viral genomes so fragile? The bottleneck hypothesis

If they undergo new mutations at each replication cycle, why are RNA viral genomes so fragile, with most mutations being either strongly deleterious or lethal? Here we provide theoretical and numerical evidence for the hypothesis that genetic fragility is partly an evolutionary response to the multiple population bottlenecks experienced by viral populations at various stages of their life cycles. Modelling within-host viral populations as multi-type branching processes, we show that mutational fragility lowers the rate at which Muller’s ratchet clicks and increases the survival probability through multiple bottlenecks. In the context of a susceptible-exposed-infectious-recovered epidemiological model, we find that the attack rate of fragile viral strains can exceed that of more robust strains, particularly at low infectivities and high mutation rates. Our findings highlight the importance of demographic events such as transmission bottlenecks in shaping the genetic architecture of viral pathogens.

Given that most mutations are deleterious, high mutation rates carry a significant evolutionary cost. To reduce this burden, an obvious evolutionary solution would be to reduce the fitness cost of mutations by becoming more robust; this solution is indeed selected in populations of constantly large size. Here, we show that when populations regularly experience bottlenecks, as viruses do upon transmission to a new host, a less obvious solution becomes more viable: namely, to increase the fitness cost of mutations so that unfit mutants are less likely to fix at each passage. This could explain why viruses—especially RNA viruses—do in fact have very fragile genomes.

The evolutionary impact of population size, mutation rate and virulence on pathogen niche width

Understanding the evolution of pathogen niche width is important for predicting disease spread and the probability that pathogens can emerge in novel hosts. Findings from previous theoretical studies often suggest that pathogens will evolve to be specialists in specific host environments. However, several of these studies make unrealistic assumptions regarding demographic stochasticity and the ability of pathogens to select their hosts. Here, an individual-based model was used to predict how population size, virulence and pathogen mutation rate affects the evolution niche specialism in pathogens. Pathogen specialism evolved regardless of virulence or populations size; thus, the findings of this study are somewhat consistent with those of previous work. However, because specialist pathogens had only a weak selective advantage over generalist pathogens, high mutation rates caused random trait variation to accumulate, preventing the evolution of specialism. Mutation rate varies greatly across different species and strains of pathogen. By showing that high mutation rates may prevent pathogen specialism evolving, this study highlights an intrinsic pathogen trait that may influence the evolution of pathogen niche width.

Could a New COVID-19 Mutant Strain Undermine Vaccination Efforts? A Mathematical Modelling Approach for Estimating the Spread of B.1.1.7 Using Ontario, Canada, as a Case Study

Infections represent highly dynamic processes, characterized by evolutionary changes and events that involve both the pathogen and the host. Among infectious agents, viruses, such as Severe Acute Respiratory Syndrome-related Coronavirus type 2 (SARS-CoV-2), the infectious agent responsible for the currently ongoing Coronavirus disease 2019 (COVID-2019) pandemic, have a particularly high mutation rate. Taking into account the mutational landscape of an infectious agent, it is important to shed light on its evolution capability over time. As new, more infectious strains of COVID-19 emerge around the world, it is imperative to estimate when these new strains may overtake the wild-type strain in different populations. Therefore, we developed a general-purpose framework to estimate the time at which a mutant variant is able to take over a wild-type strain during an emerging infectious disease outbreak. In this study, we used COVID-19 as a case-study; however, the model is adaptable to any emerging pathogen. We devised a two-strain mathematical framework to model a wild- and a mutant-type viral population and fit cumulative case data to parameterize the model, using Ontario as a case study. We found that, in the context of under-reporting and the current case levels, a variant strain was unlikely to dominate until March/April 2021. The current non-pharmaceutical interventions in Ontario need to be kept in place longer even with vaccination in order to prevent another outbreak. The spread of a variant strain in Ontario will likely be observed by a widened peak of the daily reported cases. If vaccine efficacy is maintained across strains, then it is still possible to achieve high levels of immunity in the population by the end of 2021. Our findings have important practical implications in terms of public health as policy- and decision-makers are equipped with a mathematical tool that can enable the estimation of the take-over of a mutant strain of an emerging infectious disease.

Genetic diversity through social heterosis can increase virulence in RNA viral infections and cancer progression

In viral infections and cancer tumours, negative health outcomes often correlate with increasing genetic diversity. Possible evolutionary processes for such relationships include mutant lineages escaping host control or diversity, per se, creating too many immune system targets. Another possibility is social heterosis where mutations and replicative errors create clonal lineages varying in intrinsic capability for successful dispersal; improved environmental buffering; resource extraction or effective defence against immune systems. Rather than these capabilities existing in one genome, social heterosis proposes complementary synergies occur across lineages in close proximity. Diverse groups overcome host defences as interacting 'social genomes' with group genetic tool kits exceeding limited individual plasticity. To assess the possibility of social heterosis in viral infections and cancer progression, we conducted extensive literature searches for examples consistent with general and specific predictions from the social heterosis hypothesis. Numerous studies found supportive patterns in cancers across multiple tissues and in several families of RNA viruses. In viruses, social heterosis mechanisms probably result from long coevolutionary histories of competition between pathogen and host. Conversely, in cancers, social heterosis is a by-product of recent mutations. Investigating how social genomes arise and function in viral quasi-species swarms and cancer tumours may lead to new therapeutic approaches.

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.

Experimental evolution of cowpea mild mottle virus reveals recombination-driven reduction in virulence accompanied by increases in diversity and viral fitness

Major themes in pathogen evolution are emergence, evolution of virulence, host adaptation and the processes that underlie them. RNA viruses are of particular interest due to their rapid evolution. The in vivo molecular evolution of an RNA plant virus was demonstrated here using a necrotic isolate of cowpea mild mottle virus (CPMMV) and a susceptible soybean genotype submitted to serial inoculations. We show that the virus lost the capacity to cause necrosis after six passages through the host plant. When a severe bottleneck was imposed, virulence reduction occurred in the second passage. The change to milder symptoms had fitness benefits for the virus (higher RNA accumulation) and for its vector, the whitefly Bemisia tabaci. Genetic polymorphisms were highest in ORF1 (viral replicase) and were independent of the symptom pattern. Recombination was a major contributor to this diversity - even with the strong genetic bottleneck, recombination events and hot spots were detected within ORF1. Virulence reduction was associated with different sites in ORF1 associated to recombination events in both experiments. Overall, the results demonstrate that the reduction in virulence was a consequence of the emergence of new variants, driven by recombination. Besides providing details of the evolutionary mechanisms behind a reduction in virulence and its effect under viral and vector fitness, we propose that this recombination-driven switch in virulence allows the pathogen to rapidly adapt to a new host and, potentially, switch back.

Extension of "Interfacial Adsorption Denaturation" Behavior Interpretation Based on Gibbs Monolayer Formation by Biomolecules

Using glucose oxidase and salmon testis-derived DNA molecules, we sought to extend the recently proposed idea of interfacial adsorption denaturation. The surface pressure-time (π-t) isotherm of the glucose oxidase Gibbs monolayer exhibited a rapid increase in surface pressure and a relatively prompt transition to a liquid condensed film. The appearance of this rapid liquid expansion phase occurred much earlier than that previously identified for lysozyme, trypsin, cytochrome C, and luciferase. This experimental finding was linked to the number of hydrophobic residues in the constituent unit, and the number of hydrophobic residues in glucose oxidase was the highest among these biomolecules. On the other hand, DNA molecules do not have such hydrophobic groups, or present a positive surface on the π-t curve. However, interfacial adsorption occurred, and the existence of molecules at the air/water interface was confirmed, even in the two-dimensional gas phase state. Furthermore, it was confirmed that an increase in surface pressure was detected during the formation of a mixed film of DNA molecules and biomolecules, forming a stable Gibbs monolayer. This mimic the behavior of mixed monolayer formation with matrix molecules in Langmuir monolayers. Moreover, it was clarified that the interfacial adsorption denaturation behavior changed when pH dependence was evaluated considering the isoelectric point of the biomolecular group.

Host diversity slows bacteriophage adaptation by selecting generalists over specialists

Most viruses can infect multiple hosts, yet the selective mechanisms that maintain multi-host generalists over single-host specialists remain an open question. Here we propagate populations of the newly identified bacteriophage øJB01 in coculture with many host genotypes and find that while phage can adapt to infect any of the new hosts, increasing the number of hosts slows the rate of adaptation. We quantify trade-offs in the capacity for individual phage to infect different hosts and find that phage from evolved populations with more hosts are more likely to be generalists. Sequencing of evolved phage reveals strong selection and the genetic basis of adaptation, supporting a model that shows how the addition of more potential hosts to a community can select for low-fitness generalists over high-fitness specialists. Our results show how evolution with multiple hosts alters the rate of viral adaptation and provides empirical support for an evolutionary mechanism that promotes generalists over specialists.

Addressing Non-linear System Dynamics of Single-Strand RNA Virus-Host Interaction

Positive single-strand ribonucleic acid [(+)ssRNA] viruses can cause multiple outbreaks, for which comprehensive tailored therapeutic strategies are still missing. Virus and host cell dynamics are tightly connected, generating a complex dynamics that conveys in virion assembly to ensure virus spread in the body. Starting from the knowledge of relevant processes in (+ss)RNA virus replication, transcription, translation, virions budding and shedding, and their respective energy costs, we built up a systems thinking (ST)-based diagram of the virus-host interaction, comprehensive of stocks, flows, and processes as well-described in literature. In ST approach, stocks and flows are expressed by a proxy of the energy embedded and transmitted, respectively, whereas processes are referred to the energy required for the system functioning. In this perspective, healthiness is just a particular configuration, in which stocks relevant for the system (equivalent but not limited to proteins, RNA, DNA, and all metabolites required for the survival) are constant, and the system behavior is stationary. At time of infection, the presence of additional stocks (e.g., viral protein and RNA and all metabolites required for virion assembly and spread) confers a complex network of feedbacks leading to new configurations, which can evolve to maximize the virions stock, thus changing the system structure, output, and purpose. The dynamic trajectories will evolve to achieve a new stationary status, a phenomenon described in microbiology as integration and symbiosis when the system is resilient enough to the changes, or the system may stop functioning and die. Application of external driving forces, acting on processes, can affect the dynamic trajectories adding a further degree of complexity, which can be captured by ST approach, used to address these new configurations. Investigation of system configurations in response to external driving forces acting is developed by computational analysis based on ST diagrams, with the aim at designing novel therapeutic approaches.

Fitness effects of mutation in natural populations of Arabidopsis thaliana reveal a complex influence of local adaptation

Little is empirically known about the contribution of mutations to fitness in natural environments. However, Fisher's Geometric Model (FGM) provides a conceptual foundation to consider the influence of the environment on mutational effects. To quantify mutational properties in the field, we established eight sets of MA lines (7-10 generations) derived from eight founders collected from natural populations of Arabidopsis thaliana from French and Swedish sites, representing the range margins of the species in Europe. We reciprocally planted the MA lines and their founders at French and Swedish sites, allowing us to test predictions of FGM under naturally occurring environmental conditions. The performance of the MA lines relative to each other and to their respective founders confirmed some and contradicted other predictions of the FGM: the contribution of mutation to fitness variance increased when the genotype was in an environment where its fitness was low, that is, in the away environment, but mutations were more likely to be beneficial when the genotype was in its home environment. Consequently, environmental context plays a large role in the contribution of mutations to the evolutionary process and local adaptation does not guarantee that a genotype is at or close to its optimum.

Tell Me Where You've Been and I'll Tell You How You'll Evolve

The reproducibility of adaptive evolution is a long-standing debate in evolutionary biology. Kempher et al. (M. L. Kempher, X. Tao, R. Song, B. Wu, et al., mBio 11:e00569-20, 2020, https://doi.org/10.1128/mBio.00569-20) used experimental evolution to investigate the effect of previous evolutionary trajectories on the ability of microbial populations to adapt to high temperatures. Despite the divergence caused by adaptation to previous environments, all populations reproducibly converged on similar final levels of fitness.

The reproducibility of adaptive evolution is a long-standing debate in evolutionary biology. Kempher et al. (M. L. Kempher, X. Tao, R. Song, B. Wu, et al., mBio 11:e00569-20, 2020, https://doi.org/10.1128/mBio.00569-20) used experimental evolution to investigate the effect of previous evolutionary trajectories on the ability of microbial populations to adapt to high temperatures. Despite the divergence caused by adaptation to previous environments, all populations reproducibly converged on similar final levels of fitness. Nevertheless, the genetic basis of adaptation depended on past selection experiments, reinforcing the idea that previous adaptation can dictate the trajectories of later evolutionary processes.

Single-Point Mutations within the Coxsackie B Virus Receptor-Binding Site Promote Resistance against Soluble Virus Receptor Traps

Coxsackie B viruses (CVB) cause a wide spectrum of diseases, ranging from mild respiratory syndromes and hand, foot, and mouth disease to life-threatening conditions, such as pancreatitis, myocarditis, and encephalitis. Previously, we and others found that the soluble virus receptor trap sCAR-Fc strongly attenuates CVB3 infection in mice. In this study, we investigated whether treatment with sCAR-Fc results in development of resistance by CVB3. Two CVB3 strains (CVB3-H3 and CVB3 Nancy) were passaged in HeLa cells in the presence of sCAR-Fc. The CVB3-H3 strain did not develop resistance, whereas two populations of CVB3 Nancy mutants emerged, one with complete (CVB3_M) and one with partial (CVB3_K) resistance. DNA sequence alignment of the resistant virus variant CVB3_M with CVB3 Nancy revealed an amino acid exchange from Asn(N) to Ser(S) at position 139 of the CVB3 capsid protein VP2 (N2139S), an amino acid predicted to be involved in the virus's interaction with its cognate receptor CAR. Insertion of the N2139S mutation into CVB3-H3 by site-directed mutagenesis promoted resistance of the engineered CVB3-H3_N2139S to sCAR-Fc. Interestingly, development of resistance by CVB3-H3_N2139S and the exemplarily investigated CVB3_M-clone 2 (CVB3_M2) against soluble CAR did not compromise the use of cellular CAR for viral infection. Infection of HeLa cells showed that sCAR-Fc resistance, however, negatively affected both virus stability and viral replication compared to that of the parental strains. These data demonstrate that during sCAR-Fc exposure, CVB3 can develop resistance against sCAR-Fc by single-amino-acid exchanges within the virus-receptor binding site, which, however, come at the expense of viral fitness.IMPORTANCE The emergence of resistant viruses is one of the most frequent obstacles preventing successful therapy of viral infections, representing a significant threat to human health. We investigated the emergence of resistant viruses during treatment with sCAR-Fc, a well-studied, highly effective antiviral molecule against CVB infections. Our data show the molecular aspects of resistant CVB3 mutants that arise during repetitive sCAR-Fc usage. However, drug resistance comes at the price of lower viral fitness. These results extend our knowledge of the development of resistance by coxsackieviruses and indicate potential limitations of antiviral therapy using soluble receptor molecules.

The problem of mediocre generalists: population genetics and eco-evolutionary perspectives on host breadth evolution in pathogens

Many of our theories for the generation and maintenance of diversity in nature depend on the existence of specialist biotic interactions which, in host-pathogen systems, also shape cross-species disease emergence. As such, niche breadth evolution, especially in host-parasite systems, remains a central focus in ecology and evolution. The predominant explanation for the existence of specialization in the literature is that niche breadth is constrained by trade-offs, such that a generalist is less fit on any particular environment than a given specialist. This trade-off theory has been used to predict niche breadth (co)evolution in both population genetics and eco-evolutionary models, with the different modelling methods providing separate, complementary insights. However, trade-offs may be far from universal, so population genetics theory has also proposed alternate mechanisms for costly generalism, including mutation accumulation. However, these mechanisms have yet to be integrated into eco-evolutionary models in order to understand how the mechanism of costly generalism alters the biological and ecological circumstances predicted to maintain specialism. In this review, we outline how population genetics and eco-evolutionary models based on trade-offs have provided insights for parasite niche breadth evolution and argue that the population genetics-derived mutation accumulation theory needs to be better integrated into eco-evolutionary theory.

Effects of Genetic and Physiological Divergence on the Evolution of a Sulfate-Reducing Bacterium under Conditions of Elevated Temperature

Improving our understanding of how previous adaptation influences evolution has been a long-standing goal in evolutionary biology. Natural selection tends to drive populations to find similar adaptive solutions for the same selective conditions. However, variations in historical environments can lead to both physiological and genetic divergence that can make evolution unpredictable. Here, we assessed the influence of divergence on the evolution of a model sulfate-reducing bacterium, Desulfovibrio vulgaris Hildenborough, in response to elevated temperature and found a significant effect at the genetic but not the phenotypic level. Understanding how these influences drive evolution will allow us to better predict how bacteria will adapt to various ecological constraints.

Adaptation via natural selection is an important driver of evolution, and repeatable adaptations of replicate populations, under conditions of a constant environment, have been extensively reported. However, isolated groups of populations in nature tend to harbor both genetic and physiological divergence due to multiple selective pressures that they have encountered. How this divergence affects adaptation of these populations to a new common environment remains unclear. To determine the impact of prior genetic and physiological divergence in shaping adaptive evolution to accommodate a new common environment, an experimental evolution study with the sulfate-reducing bacterium Desulfovibrio vulgaris Hildenborough (DvH) was conducted. Two groups of replicate populations with genetic and physiological divergence, derived from a previous evolution study, were propagated in an elevated-temperature environment for 1,000 generations. Ancestor populations without prior experimental evolution were also propagated in the same environment as a control. After 1,000 generations, all the populations had increased growth rates and all but one had greater fitness in the new environment than the ancestor population. Moreover, improvements in growth rate were moderately affected by the divergence in the starting populations, while changes in fitness were not significantly affected. The mutations acquired at the gene level in each group of populations were quite different, indicating that the observed phenotypic changes were achieved by evolutionary responses that differed between the groups. Overall, our work demonstrated that the initial differences in fitness between the starting populations were eliminated by adaptation and that phenotypic convergence was achieved by acquisition of mutations in different genes.

Ecological fitting is the forerunner to diversification in a plant virus with broad host range

The evolution and diversification of ssRNA plant viruses are often examined under reductionist conditions that ignore potentially much wider biotic interactions. The host range of a plant virus is central to interactions at higher levels that are organized by both fitness and ecological criteria. Here we employ a strategy to minimize sampling biases across distinct plant communities and combine it with a high-throughput sequencing approach to examine the influence of four habitats on the evolution of Watermelon mosaic virus (WMV). Local, regional and global levels of genetic diversity that correspond to spatial and temporal extents are used to infer haplotype relationships using network and phylogenetic approaches. We find that the incidence and genetic diversity of WMV were structured significantly by host species and habitat type. A single haplotype that infected 11 host species of a total of 24 showed that few constraints on host species use exist in the crop communities. When the evolution of WMV was examined at broader levels of organization, we found variation in genetic diversity and contrasting host use footprints that broadly corresponded to habitat effects. The findings demonstrated that nondeterministic ecological factors structured the genetic diversity of WMV. Habitat-driven constraints underlie host use preferences.

The Critical Role of Codon Composition on the Translation Efficiency Robustness of the Hepatitis A Virus Capsid

Hepatoviruses show an intriguing deviated codon usage, suggesting an evolutionary signature. Abundant and rare codons in the cellular genome are scarce in the human hepatitis A virus (HAV) genome, while intermediately abundant host codons are abundant in the virus. Genotype–phenotype maps, or fitness landscapes, are a means of representing a genotype position in sequence space and uncovering how genotype relates to phenotype and fitness. Using genotype–phenotype maps of the translation efficiency, we have shown the critical role of the HAV capsid codon composition in regulating translation and determining its robustness. Adaptation to an environmental perturbation such as the artificial induction of cellular shutoff—not naturally occurring in HAV infection—involved movements in the sequence space and dramatic changes of the translation efficiency. Capsid rare codons, including abundant and rare codons of the cellular genome, slowed down the translation efficiency in conditions of no cellular shutoff. In contrast, rare capsid codons that are abundant in the cellular genome were efficiently translated in conditions of shutoff. Capsid regions very rich in slowly translated codons adapt to shutoff through sequence space movements from positions with highly robust translation to others with diminished translation robustness. These movements paralleled decreases of the capsid physical and biological robustness, and resulted in the diversification of capsid phenotypes. The deviated codon usage of extant hepatoviruses compared with that of their hosts may suggest the occurrence of a virus ancestor with an optimized codon usage with respect to an unknown ancient host.

Influenza Viruses in Mice: Deep Sequencing Analysis of Serial Passage and Effects of Sialic Acid Structural Variation

Influenza A viruses have regularly jumped to new host species to cause epidemics or pandemics, an evolutionary process that involves variation in the viral traits necessary to overcome host barriers and facilitate transmission. Mice are not a natural host for influenza virus but are frequently used as models in studies of pathogenesis, often after multiple passages to achieve higher viral titers that result in clinical disease such as weight loss or death. Here, we examine the processes of influenza A virus infection and evolution in mice by comparing single nucleotide variations of a human H1N1 pandemic virus, a seasonal H3N2 virus, and an H3N2 canine influenza virus during experimental passage. We also compared replication and sequence variation in wild-type mice expressing N-glycolylneuraminic acid (Neu5Gc) with those seen in mice expressing only N-acetylneuraminic acid (Neu5Ac). Viruses derived from plasmids were propagated in MDCK cells and then passaged in mice up to four times. Full-genome deep sequencing of the plasmids, cultured viruses, and viruses from mice at various passages revealed only small numbers of mutational changes. The H3N2 canine influenza virus showed increases in frequency of sporadic mutations in the PB2, PA, and NA segments. The H1N1 pandemic virus grew well in mice, and while it exhibited the maintenance of some minority mutations, there was no clear evidence for adaptive evolution. The H3N2 seasonal virus did not establish in the mice. Finally, there were no clear sequence differences associated with the presence or absence of Neu5Gc.IMPORTANCE Mice are commonly used as a model to study the growth and virulence of influenza A viruses in mammals but are not a natural host and have distinct sialic acid receptor profiles compared to humans. Using experimental infections with different subtypes of influenza A virus derived from different hosts, we found that evolution of influenza A virus in mice did not necessarily proceed through the linear accumulation of host-adaptive mutations, that there was variation in the patterns of mutations detected in each repetition, and that the mutation dynamics depended on the virus examined. In addition, variation in the viral receptor, sialic acid, did not affect influenza virus evolution in this model. Overall, our results show that while mice provide a useful animal model for influenza virus pathology, host passage evolution will vary depending on the specific virus tested.

Evolvability Costs of Niche Expansion

What prevents generalists from displacing specialists, despite obvious competitive advantages of utilizing a broad niche? The classic genetic explanation is antagonistic pleiotropy: genes underlying the generalism produce 'jacks-of-all-trades' that are masters of none. However, experiments challenge this assumption that mutations enabling niche expansion must reduce fitness in other environments. Theory suggests an alternative cost of generalism: decreased evolvability, or the reduced capacity to adapt. Generalists using multiple environments experience relaxed selection in any one environment, producing greater relative lag load. Additionally, mutations fixed by generalist lineages early during their evolution that avoid or compensate for antagonistic pleiotropy may limit access to certain future evolutionary trajectories. Hypothesized evolvability costs of generalism warrant further exploration, and we suggest outstanding questions meriting attention.

Effects of Arbovirus Multi-Host Life Cycles on Dinucleotide and Codon Usage Patterns

Arthropod-borne viruses (arboviruses) of vertebrates including dengue, zika, chikungunya, Rift Valley fever, and blue tongue viruses cause extensive morbidity and mortality in humans, agricultural animals, and wildlife across the globe. As obligate intercellular pathogens, arboviruses must be well adapted to the cellular and molecular environment of both their arthropod (invertebrate) and vertebrate hosts, which are vastly different due to hundreds of millions of years of separate evolution. Here we discuss the comparative pressures on arbovirus RNA genomes as a result of a dual host life cycle, focusing on pressures that do not alter amino acids. We summarize what is currently known about arboviral genetic composition, such as dinucleotide and codon usage, and how cyclical infection of vertebrate and invertebrate hosts results in different genetic profiles compared with single-host viruses. To serve as a comparison, we compile what is known about arthropod tRNA, dinucleotide, and codon usages and compare this with vertebrates. Additionally, we discuss the potential roles of genetic robustness in arboviral evolution and how it may vary from other viruses. Overall, both arthropod and vertebrate hosts influence the resulting genetic composition of arboviruses, but a great deal remains to be investigated.

Existing Host Range Mutations Constrain Further Emergence of RNA Viruses

RNA viruses are capable of rapid host shifting, typically due to a point mutation that confers expanded host range. As additional point mutations are necessary for further expansions, epistasis among host range mutations can potentially affect the mutational neighborhood and frequency of niche expansion. We mapped the mutational neighborhood of host range expansion using three genotypes of the double-stranded RNA (dsRNA) bacteriophage φ6 (wild type and two isogenic host range mutants) on the novel host Pseudomonas syringae pv. atrofaciens. Both Sanger sequencing of 50 P. syringae pv. atrofaciens mutant clones for each genotype and population Illumina sequencing revealed the same high-frequency mutations allowing infection of P. syringae pv. atrofaciens. Wild-type φ6 had at least nine different ways of mutating to enter the novel host, eight of which are in p3 (host attachment protein gene), and 13/50 clones had unchanged p3 genes. However, the two isogenic mutants had dramatically restricted neighborhoods: only one or two mutations, all in p3. Deep sequencing revealed that wild-type clones without mutations in p3 likely had changes in p12 (morphogenic protein), a region that was not polymorphic for the two isogenic host range mutants. Sanger sequencing confirmed that 10/13 of the wild-type φ6 clones had nonsynonymous mutations in p12, and 2 others had point mutations in p9 and p5. None of these genes had previously been associated with host range expansion in φ6. We demonstrate, for the first time, epistatic constraint in an RNA virus due to host range mutations themselves, which has implications for models of serial host range expansion.IMPORTANCE RNA viruses mutate rapidly and frequently expand their host ranges to infect novel hosts, leading to serial host shifts. Using an RNA bacteriophage model system (Pseudomonas phage φ6), we studied the impact of preexisting host range mutations on another host range expansion. Results from both clonal Sanger and Illumina sequencing show that extant host range mutations dramatically narrow the neighborhood of potential host range mutations compared to that of wild-type φ6. This research suggests that serial host-shifting viruses may follow a small number of molecular paths to enter additional novel hosts. We also identified new genes involved in φ6 host range expansion, expanding our knowledge of this important model system in experimental evolution.

Cryptic genetic variation shapes the adaptive evolutionary potential of enzymes

Genetic variation among orthologous proteins can cause cryptic phenotypic properties that only manifest in changing environments. Such variation may impact the evolvability of proteins, but the underlying molecular basis remains unclear. Here, we performed comparative directed evolution of four orthologous metallo-β-lactamases toward a new function and found that different starting genotypes evolved to distinct evolutionary outcomes. Despite a low initial fitness, one ortholog reached a significantly higher fitness plateau than its counterparts, via increasing catalytic activity. By contrast, the ortholog with the highest initial activity evolved to a less-optimal and phenotypically distinct outcome through changes in expression, oligomerization and activity. We show how cryptic molecular properties and conformational variation of active site residues in the initial genotypes cause epistasis, that could lead to distinct evolutionary outcomes. Our work highlights the importance of understanding the molecular details that connect genetic variation to protein function to improve the prediction of protein evolution.

Evolutionary Virology at 40

RNA viruses are diverse, abundant, and rapidly evolving. Genetic data have been generated from virus populations since the late 1970s and used to understand their evolution, emergence, and spread, culminating in the generation and analysis of many thousands of viral genome sequences. Despite this wealth of data, evolutionary genetics has played a surprisingly small role in our understanding of virus evolution. Instead, studies of RNA virus evolution have been dominated by two very different perspectives, the experimental and the comparative, that have largely been conducted independently and sometimes antagonistically. Here, we review the insights that these two approaches have provided over the last 40 years. We show that experimental approaches using in vitro and in vivo laboratory models are largely focused on short-term intrahost evolutionary mechanisms, and may not always be relevant to natural systems. In contrast, the comparative approach relies on the phylogenetic analysis of natural virus populations, usually considering data collected over multiple cycles of virus-host transmission, but is divorced from the causative evolutionary processes. To truly understand RNA virus evolution it is necessary to meld experimental and comparative approaches within a single evolutionary genetic framework, and to link viral evolution at the intrahost scale with that which occurs over both epidemiological and geological timescales. We suggest that the impetus for this new synthesis may come from methodological advances in next-generation sequencing and metagenomics.

Contingency and determinism in evolution: Replaying life’s tape

Historical processes display some degree of “contingency,” meaning their outcomes are sensitive to seemingly inconsequential events that can fundamentally change the future. Contingency is what makes historical outcomes unpredictable. Unlike many other natural phenomena, evolution is a historical process. Evolutionary change is often driven by the deterministic force of natural selection, but natural selection works upon variation that arises unpredictably through time by random mutation, and even beneficial mutations can be lost by chance through genetic drift. Moreover, evolution has taken place within a planetary environment with a particular history of its own. This tension between determinism and contingency makes evolutionary biology a kind of hybrid between science and history. While philosophers of science examine the nuances of contingency, biologists have performed many empirical studies of evolutionary repeatability and contingency. Here, we review the experimental and comparative evidence from these studies. Replicate populations in evolutionary “replay” experiments often show parallel changes, especially in overall performance, although idiosyncratic outcomes show that the particulars of a lineage’s history can affect which of several evolutionary paths is taken. Comparative biologists have found many notable examples of convergent adaptation to similar conditions, but quantification of how frequently such convergence occurs is difficult. On balance, the evidence indicates that evolution tends to be surprisingly repeatable among closely related lineages, but disparate outcomes become more likely as the footprint of history grows deeper. Ongoing research on the structure of adaptive landscapes is providing additional insight into the interplay of fate and chance in the evolutionary process.

(Non)Parallel Evolution

Parallel evolution across replicate populations has provided evolutionary biologists with iconic examples of adaptation. When multiple populations colonize seemingly similar habitats, they may evolve similar genes, traits, or functions. Yet, replicated evolution in nature or in the laboratory often yields inconsistent outcomes: Some replicate populations evolve along highly similar trajectories, whereas other replicate populations evolve to different extents or in distinct directions. To understand these heterogeneous outcomes, biologists are increasingly treating parallel evolution not as a binary phenomenon but rather as a quantitative continuum ranging from parallel to nonparallel. By measuring replicate populations’ positions along this (non)parallel continuum, we can test hypotheses about evolutionary and ecological factors that influence the extent of repeatable evolution. We review evidence regarding the manifestation of (non)parallel evolution in the laboratory, in natural populations, and in applied contexts such as cancer. We enumerate the many genetic, ecological, and evolutionary processes that contribute to variation in the extent of parallel evolution.

The mobility of packaged phage genome controls ejection dynamics

The cell decision between lytic and lysogenic infection is strongly influenced by dynamics of DNA injection into a cell from a phage population, as phages compete for limited resources and progeny. However, what controls the timing of viral DNA ejection events was not understood. This in vitro study reveals that DNA ejection dynamics for phages can be synchronized (occurring within seconds) or desynchronized (displaying minutes-long delays in initiation) based on mobility of encapsidated DNA, which in turn is regulated by environmental factors, such as temperature and extra-cellular ionic conditions. This mechano-regulation of ejection dynamics is suggested to influence viral replication where the cell’s decision between lytic and latent infection is associated with synchronized or desynchronized delayed ejection events from phage population adsorbed to a cell. Our findings are of significant importance for understanding regulatory mechanisms of latency in phage and Herpesviruses, where encapsidated DNA undergoes a similar mechanical transition.

Viruses are tiny ‘parasites’ that smuggle their genetic material inside a cell and then hijack its resources for their own benefit. A viral infection can either be lytic or latent. In a lytic cycle, viruses make their host produce many copies of themselves, ultimately killing the cell. In contrast, during a latent infection, the viruses go ‘dormant’: for instance, some of them can insert their genetic material into the DNA of their host, which then gets passed on as the cell divides.

Certain viruses are capable of both lytic and latent infections. One example is the lambda phage, which targets Escherichia coli bacteria. In the first stage of infection, the genetic material ‘shoots out’ of the virus and gets injected inside the bacterium. The dynamics of the ejection process determine the type of infection that will follow. If multiple phages release their genomes quickly and within seconds of each other into the same cell, the bacterium tends to incorporate the viral DNA into its own genome, leading to a latent cycle. If the infections take place more slowly and not all at the same time, the cell is more likely to go through a lytic phase. However, the mechanism behind the different injection behaviors is still unknown; in particular, it is unclear which factors control the specificities of the ejection process in the first place.

Here, Alex Evilevitch demonstrates that the mechanical state of the phage DNA just before ejection dictates how the genetic material will then be injected in the bacteria. The experiments measured the stiffness of the DNA and the amount of heat given off during infection. Like fluid toothpaste, if the DNA is more liquid and flexible, it gets ejected quickly and simultaneously from several phages. Then, the genetic information of these viruses can be incorporated in the genome of the bacteria. On the other hand, if the DNA is more solid, it is likely to ‘stick’ and take time before it can be squeezed out: the injections become unsynchronised, which leads to a lytic phase.

Evilevitch then shows that the environment can influence the properties of the phages’ genome. A little more heat, or certain chemicals, can make the DNA more fluid inside the viruses, and change the way it can be injected inside the bacteria.

Many viruses that cause diseases in humans – from cold sores to glandular fever – can switch between the lytic and latent cycles. For the first time, these results show that the mechanical properties of the DNA inside a virus influence the ‘decision’ between the two types of infection. This knowledge could help us prevent infections from becoming lytic and ultimately allow us to control the spread of disease.

Experimental Design, Population Dynamics, and Diversity in Microbial Experimental Evolution

In experimental evolution, laboratory-controlled conditions select for the adaptation of species, which can be monitored in real time. Despite the current popularity of such experiments, nature's most pervasive biological force was long believed to be observable only on time scales that transcend a researcher's life-span, and studying evolution by natural selection was therefore carried out solely by comparative means. Eventually, microorganisms' propensity for fast evolutionary changes proved us wrong, displaying strong evolutionary adaptations over a limited time, nowadays massively exploited in laboratory evolution experiments. Here, we formulate a guide to experimental evolution with microorganisms, explaining experimental design and discussing evolutionary dynamics and outcomes and how it is used to assess ecoevolutionary theories, improve industrially important traits, and untangle complex phenotypes. Specifically, we give a comprehensive overview of the setups used in experimental evolution. Additionally, we address population dynamics and genetic or phenotypic diversity during evolution experiments and expand upon contributing factors, such as epistasis and the consequences of (a)sexual reproduction. Dynamics and outcomes of evolution are most profoundly affected by the spatiotemporal nature of the selective environment, where changing environments might lead to generalists and structured environments could foster diversity, aided by, for example, clonal interference and negative frequency-dependent selection. We conclude with future perspectives, with an emphasis on possibilities offered by fast-paced technological progress. This work is meant to serve as an introduction to those new to the field of experimental evolution, as a guide to the budding experimentalist, and as a reference work to the seasoned expert.

A speed-fidelity trade-off determines the mutation rate and virulence of an RNA virus

Mutation rates can evolve through genetic drift, indirect selection due to genetic hitchhiking, or direct selection on the physicochemical cost of high fidelity. However, for many systems, it has been difficult to disentangle the relative impact of these forces empirically. In RNA viruses, an observed correlation between mutation rate and virulence has led many to argue that their extremely high mutation rates are advantageous because they may allow for increased adaptability. This argument has profound implications because it suggests that pathogenesis in many viral infections depends on rare or de novo mutations. Here, we present data for an alternative model whereby RNA viruses evolve high mutation rates as a byproduct of selection for increased replicative speed. We find that a poliovirus antimutator, 3D^G64S, has a significant replication defect and that wild-type (WT) and 3D^G64S populations have similar adaptability in 2 distinct cellular environments. Experimental evolution of 3D^G64S under selection for replicative speed led to reversion and compensation of the fidelity phenotype. Mice infected with 3D^G64S exhibited delayed morbidity at doses well above the lethal level, consistent with attenuation by slower growth as opposed to reduced mutational supply. Furthermore, compensation of the 3D^G64S growth defect restored virulence, while compensation of the fidelity phenotype did not. Our data are consistent with the kinetic proofreading model for biosynthetic reactions and suggest that speed is more important than accuracy. In contrast with what has been suggested for many RNA viruses, we find that within-host spread is associated with viral replicative speed and not standing genetic diversity.

Why organisms have different mutation rates is a longstanding question in evolutionary biology. The polymerases of RNA viruses generally lack proofreading activity and exhibit extremely high mutation rates. Because most mutations are deleterious and mutation rates are typically tuned by natural selection, we asked why RNA viruses haven’t evolved a polymerase with a lower mutation rate. We used experimental evolution and a murine infection model to show that RNA virus mutation rates may actually be too high and are not necessarily adaptive. Rather, our data indicate that viral mutation rates have evolved to be higher as a result of selection for viruses with faster replication kinetics. We suggest that viruses have high mutation rates, not because they facilitate adaptation but because it is hard to be both fast and accurate and these viruses have prioritized speed over fidelity.

Genetic variation in adaptability and pleiotropy in budding yeast

Evolution can favor organisms that are more adaptable, provided that genetic variation in adaptability exists. Here, we quantify this variation among 230 offspring of a cross between diverged yeast strains. We measure the adaptability of each offspring genotype, defined as its average rate of adaptation in a specific environmental condition, and analyze the heritability, predictability, and genetic basis of this trait. We find that initial genotype strongly affects adaptability and can alter the genetic basis of future evolution. Initial genotype also affects the pleiotropic consequences of adaptation for fitness in a different environment. This genetic variation in adaptability and pleiotropy is largely determined by initial fitness, according to a rule of declining adaptability with increasing initial fitness, but several individual QTLs also have a significant idiosyncratic role. Our results demonstrate that both adaptability and pleiotropy are complex traits, with extensive heritable differences arising from naturally occurring variation.

Synonymous codon usage analysis of hand, foot and mouth disease viruses: A comparative study on coxsackievirus A6, A10, A16, and enterovirus 71 from 2008 to 2015

Enterovirus 71 (EV71) and coxsackievirus A16 (CVA16) have been considered major pathogens of hand, foot and mouth disease (HFMD) throughout the world for decades. In recent years, coxsackievirus A6 (CVA6) and coxsackievirus A10 (CVA10) have raised attention as two other serious pathogens of HFMD. The present study focused on the synonymous codon usage of four viruses isolated from 2008 to 2015, with particular attention on P1 (encoding capsid proteins) and P2-P3 regions (both encoding non-structural proteins) in the genomic RNA. Relative synonymous codon usage, effective number of codons, neutrality and correspondence were analyzed. The results indicated that these viruses prefer A/T at the third position in codons rather than G/C. The most frequent codons of 4 essential and 2 semi-essential amino acids, as well as a key amino acid of metabolic junctions (Glu) used in the four viruses are also the most frequently used in humans. Effective number of codons (ENC) values indicated weak codon usage bias in all the viruses. Relatively, the force of mutation pressure in the P1 region was found to be stronger than that in the P2-P3 region, and this force in the P1 region of CVA6 and EV71 was stronger than that of CVA10 and A16. The neutrality analysis results implied that mutation pressure plays a minor role in shaping codon bias of these viruses. Correspondence analysis indicated that the codon usage of EV71 strains varied much more than that of other viruses. In conclusion, the present study provides novel and comparative insight into the evolution of HFMD pathogens at the codon level.

Attenuation of RNA viruses by redirecting their evolution in sequence space

RNA viruses pose serious threats to human health. Their success relies on their capacity to generate genetic variability and, consequently, on their adaptive potential. We describe a strategy to attenuate RNA viruses by altering their evolutionary potential. We rationally altered the genomes of Coxsackie B3 and influenza A viruses to redirect their evolutionary trajectories towards detrimental regions in sequence space. Specifically, viral genomes were engineered to harbour more serine and leucine codons with nonsense mutation targets: codons that could generate Stop mutations after a single nucleotide substitution. Indeed, these viruses generated more Stop mutations both in vitro and in vivo, accompanied by significant losses in viral fitness. In vivo, the viruses were attenuated, generated high levels of neutralizing antibodies and protected against lethal challenge. Our study demonstrates that cornering viruses in ‘risky’ areas of sequence space may be implemented as a broad-spectrum vaccine strategy against RNA viruses.

Virus attenuation is used to obtain vaccine strains. Here, the rapid evolution of RNA viruses is exploited by engineering their genomes to encode sites that are a mutation away from a stop codon, a clever method to generate attenuated viruses.

Identification of the potentiating mutations and synergistic epistasis that enabled the evolution of inter-species cooperation

Microbes often engage in cooperation through releasing biosynthetic compounds required by other species to grow. Given that production of costly biosynthetic metabolites is generally subjected to multiple layers of negative feedback, single mutations may frequently be insufficient to generate cooperative phenotypes. Synergistic epistatic interactions between multiple coordinated changes may thus often underlie the evolution of cooperation through overproduction of metabolites. To test the importance of synergistic mutations in cooperation we used an engineered bacterial consortium of an Escherichia coli methionine auxotroph and Salmonella enterica. S. enterica relies on carbon by-products from E. coli if lactose is the only carbon source. Directly selecting wild-type S. enterica in an environment that favored cooperation through secretion of methionine only once led to a methionine producer, and this producer both took a long time to emerge and was not very effective at cooperating. On the other hand, when an initial selection for resistance of S. enterica to a toxic methionine analog, ethionine, was used, subsequent selection for cooperation with E. coli was rapid, and the resulting double mutants were much more effective at cooperation. We found that potentiating mutations in metJ increase expression of metA, which encodes the first step of methionine biosynthesis. This increase in expression is required for the previously identified actualizing mutations in metA to generate cooperation. This work highlights that where biosynthesis of metabolites involves multiple layers of regulation, significant secretion of those metabolites may require multiple mutations, thereby constraining the evolution of cooperation.

Diminishing-returns epistasis decreases adaptability along an evolutionary trajectory

Populations evolving in constant environments exhibit declining adaptability. Understanding the basis of this pattern could reveal underlying processes determining the repeatability of evolutionary outcomes. In principle, declining adaptability can be due to a decrease in the effect size of beneficial mutations, a decrease in the rate at which they occur, or some combination of both. By evolving Escherichia coli populations started from different steps along a single evolutionary trajectory, we show that declining adaptability is best explained by a decrease in the size of available beneficial mutations. This pattern reflected the dominant influence of negative genetic interactions that caused new beneficial mutations to confer smaller benefits in fitter genotypes. Genome sequencing revealed that starting genotypes that were more similar to one another did not exhibit greater similarity in terms of new beneficial mutations, supporting the view that epistasis acts globally, having a greater influence on the effect than on the identity of available mutations along an adaptive trajectory. Our findings provide support for a general mechanism that leads to predictable phenotypic evolutionary trajectories.

Matters of Size: Genetic Bottlenecks in Virus Infection and Their Potential Impact on Evolution

For virus infections of multicellular hosts, narrow genetic bottlenecks during transmission and within-host spread appear to be widespread. These bottlenecks will affect the maintenance of genetic variation in a virus population and the prevalence of mixed-strain infections, thereby ultimately determining the strength with which different random forces act during evolution. Here we consider different approaches for estimating bottleneck sizes and weigh their merits. We then review quantitative estimates of bottleneck size during cellular infection, within-host spread, horizontal transmission, and finally vertical transmission. In most cases we find that bottlenecks do regularly occur, although in many cases they appear to be virion-concentration dependent. Finally, we consider the evolutionary implications of genetic bottlenecks during virus infection. Although on average strong bottlenecks will lead to declines in fitness, we consider a number of scenarios in which bottlenecks could also be advantageous for viruses.

Evolved Populations of Shigella flexneri Phage Sf6 Acquire Large Deletions, Altered Genomic Architecture, and Faster Life Cycles

Genomic architecture is the framework within which genes and regulatory elements evolve and where specific constructs may constrain or potentiate particular adaptations. One such construct is evident in phages that use a headful packaging strategy that results in progeny phage heads packaged with DNA until full rather than encapsidating a simple unit-length genome. Here, we investigate the evolution of the headful packaging phage Sf6 in response to barriers that impede efficient phage adsorption to the host cell. Ten replicate populations evolved faster Sf6 life cycles by parallel mutations found in a phage lysis gene and/or by large, 1.2- to 4.0-kb deletions that remove a mobile genetic IS911 element present in the ancestral phage genome. The fastest life cycles were found in phages that acquired both mutations. No mutations were found in genes encoding phage structural proteins, which were a priori expected from the experimental design that imposed a challenge for phage adsorption by using a Shigella flexneri host lacking receptors preferred by Sf6. We used DNA sequencing, molecular approaches, and physiological experiments on 82 clonal isolates taken from all 10 populations to reveal the genetic basis of the faster Sf6 life cycle. The majority of our isolates acquired deletions in the phage genome. Our results suggest that deletions are adaptive and can influence the duration of the phage life cycle while acting in conjunction with other lysis time-determining point mutations.

A case study in evolutionary contingency

Biological evolution is a fundamentally historical phenomenon in which intertwined stochastic and deterministic processes shape lineages with long, continuous histories that exist in a changing world that has a history of its own. The degree to which these characteristics render evolution historically contingent, and evolutionary outcomes thereby unpredictably sensitive to history has been the subject of considerable debate in recent decades. Microbial evolution experiments have proven among the most fruitful means of empirically investigating the issue of historical contingency in evolution. One such experiment is the Escherichia coli Long-Term Evolution Experiment (LTEE), in which twelve populations founded from the same clone of E. coli have evolved in parallel under identical conditions. Aerobic growth on citrate (Cit(+)), a novel trait for E. coli, evolved in one of these populations after more than 30,000 generations. Experimental replays of this population's evolution from various points in its history showed that the Cit(+) trait was historically contingent upon earlier mutations that potentiated the trait by rendering it mutationally accessible. Here I review this case of evolutionary contingency and discuss what it implies about the importance of historical contingency arising from the core processes of evolution.

Antigenic diversification is correlated with increased thermostability in a mammalian virus

The theory of plastogenetic congruence posits that ultimately, the pressure to maintain function in the face of biomolecular destabilization produces robustness. As temperature goes up so does destabilization. Thus, genetic robustness, defined as phenotypic constancy despite mutation, should correlate with survival during thermal challenge. We tested this hypothesis using vesicular stomatitis virus (VSV). We produced two sets of evolved strains after selection for higher thermostability by either preincubation at 37°C or by incubation at 40°C during infection. These VSV populations became more thermostable and also more fit in the absence of thermal selection, demonstrating an absence of tradeoffs. Eleven out of 12 evolved populations had a fixed, nonsynonymous substitution in the nucleocapsid (N) open reading frame. There was a partial correlation between thermostability and mutational robustness that was observed when the former was measured at 42°C, but not at 37°C. These results are consistent with our earlier work and suggest that the relationship between robustness and thermostability is complex. Surprisingly, many of the thermostable strains also showed increased resistance to monoclonal antibody and polyclonal sera, including sera from natural hosts. These data suggest that evolved thermostability may lead to antigenic diversification and an increased ability to escape immune surveillance in febrile hosts, and potentially to an improved robustness. These relationships have important implications not only in terms of viral pathogenesis, but also for the development of vaccine vectors and oncolytic agents.

Field measurements of genotype by environment interaction for fitness caused by spontaneous mutations in Arabidopsis thaliana

As the ultimate source of genetic diversity, spontaneous mutation is critical to the evolutionary process. The fitness effects of spontaneous mutations are almost always studied under controlled laboratory conditions rather than under the evolutionarily relevant conditions of the field. Of particular interest is the conditionality of new mutations-that is, is a new mutation harmful regardless of the environment in which it is found? In other words, what is the extent of genotype-environment interaction for spontaneous mutations? We studied the fitness effects of 25 generations of accumulated spontaneous mutations in Arabidopsis thaliana in two geographically widely separated field environments, in Michigan and Virginia. At both sites, mean total fitness of mutation accumulation lines exceeded that of the ancestors, contrary to the expected decrease in the mean due to new mutations but in accord with prior work on these MA lines. We observed genotype-environment interactions in the fitness effects of new mutations, such that the effects of mutations in Michigan were a poor predictor of their effects in Virginia and vice versa. In particular, mutational variance for fitness was much larger in Virginia compared to Michigan. This strong genotype-environment interaction would increase the amount of genetic variation maintained by mutation-selection balance.

Contrasting effects of historical contingency on phenotypic and genomic trajectories during a two-step evolution experiment with bacteria

BACKGROUND

The impact of historical contingency, i.e. the past evolutionary history of a population, on further adaptation is mostly unknown at both the phenotypic and genomic levels. We addressed this question using a two-step evolution experiment. First, replicate populations of Escherichia coli were propagated in four different environmental conditions for 1000 generations. Then, all replicate populations were transferred and propagated for further 1000 generations to a single new environment.

RESULTS

Using this two-step experimental evolution strategy, we investigated, at both the phenotypic and genomic levels, whether and how adaptation in the initial historical environments impacted evolutionary trajectories in a new environment. We showed that both the growth rate and fitness of the evolved populations obtained after the second step of evolution were contingent upon past evolutionary history. In contrast however, the genes that were modified during the second step of evolution were independent from the previous history of the populations.

CONCLUSIONS

Our work suggests that historical contingency affects phenotypic adaptation to a new environment. This was however not reflected at the genomic level implying complex relationships between environmental factors and the genotype-to-phenotype map.

Genetic variation in fitness within a clonal population of a plant RNA virus

A long-standing observation in evolutionary virology is that RNA virus populations are highly polymorphic, composed by a mixture of genotypes whose abundances in the population depend on complex interaction between fitness differences, mutational coupling and genetic drift. It was shown long ago, though in cell cultures, that most of these genotypes had lower fitness than the population they belong, an observation that explained why single-virion passages turned on Muller’s ratchet while very large population passages resulted in fitness increases in novel environments. Here we report the results of an experiment specifically designed to evaluate in vivo the fitness differences among the subclonal components of a clonal population of the plant RNA virus tobacco etch potyvirus (TEV). Over 100 individual biological subclones from a TEV clonal population well adapted to the natural tobacco host were obtained by infectivity assays on a local lesion host. The replicative fitness of these subclones was then evaluated during infection of tobacco relative to the fitness of large random samples taken from the starting clonal population. Fitness was evaluated at increasing number of days post-inoculation. We found that at early days, the average fitness of subclones was significantly lower than the fitness of the clonal population, thus confirming previous observations that most subclones contained deleterious mutations. However, as the number of days of viral replication increases, population size expands exponentially, more beneficial and compensatory mutations are produced, and selection becomes more effective in optimizing fitness, the differences between subclones and the population disappeared.