Effect of population patchiness and migration rates on the adaptation and divergence of vesicular stomatitis virus quasispecies populations

Compost spatial heterogeneity promotes evolutionary diversification of a bacterium

Spatial resource heterogeneity is expected to be a key driver for the evolution of diversity. However, direct empirical support for this prediction is limited to studies carried out in simplified laboratory environments. Here, we investigate how altering spatial heterogeneity of potting compost-by the addition of water and mixing-affects the evolutionary diversification of a bacterial species, Pseudomonas fluorescens, that is naturally found in the environment. There was a greater propensity of resource specialists to evolve in the unmanipulated compost, while more generalist phenotypes dominated the compost-water mix. Genomic data were consistent with these phenotypic findings. Competition experiments strongly suggest these results are due to diversifying selection as a result of resource heterogeneity, as opposed to other covariables. Overall, our findings corroborate theoretical and in vitro findings, but in semi-natural, more realistic conditions.

Sequence polymorphism in an insect RNA virus field population: A snapshot from a single point in space and time reveals stochastic differences among and within individual hosts

Population structure of Homalodisca coagulata Virus-1 (HoCV-1) among and within field-collected insects sampled from a single point in space and time was examined. Polymorphism in complete consensus sequences among single-insect isolates was dominated by synonymous substitutions. The mutant spectrum of the C2 helicase region within each single-insect isolate was unique and dominated by nonsynonymous singletons. Bootstrapping was used to correct the within-isolate nonsynonymous:synonymous arithmetic ratio (N:S) for RT-PCR error, yielding an N:S value ~one log-unit greater than that of consensus sequences. Probability of all possible single-base substitutions for the C2 region predicted N:S values within 95% confidence limits of the corrected within-isolate N:S when the only constraint imposed was viral polymerase error bias for transitions over transversions. These results indicate that bottlenecks coupled with strong negative/purifying selection drive consensus sequences toward neutral sequence space, and that most polymorphism within single-insect isolates is composed of newly-minted mutations sampled prior to selection.

Understanding the dengue viruses and progress towards their control

Traditionally, the four dengue virus serotypes have been associated with fever, rash, and the more severe forms, haemorrhagic fever and shock syndrome. As our knowledge as well as understanding of these viruses increases, we now recognise not only that they are causing increasing numbers of human infections but also that they may cause neurological and other clinical complications, with sequelae or fatal consequences. In this review we attempt to highlight some of these features in the context of dengue virus pathogenesis. We also examine some of the efforts currently underway to control this "scourge" of the tropical and subtropical world.

Evolution of increased survival in RNA viruses specialized on cancer-derived cells

Viruses and other pathogens can diverge in their evolved host-use strategies because of exposure to different host types and conflicts between within-host reproduction and between-host survival. Most host-pathogen studies have emphasized the role of intrahost reproduction in the evolution of pathogen virulence, whereas the role of extra-host survival has received less attention. Here, we examine the evolution of free-living virion survival in RNA virus populations differing in their histories of host use. To do so, we used lineages of vesicular stomatitis virus (VSV) that were experimentally evolved in laboratory tissue culture for 100 generations on cancer-derived cells, noncancerous cells, or alternating passages of the two host types. We observed that free-living survival improved when VSV populations specialized on human epithelial carcinoma (HeLa) cells, whereas this trait was not associated with selection on noncancer cells or combinations of the cell types. We attributed this finding to shorter-lived HeLa monolayers and/or rapid cell-to-cell spread of viruses on HeLa cells in tissue culture, both of which could select for enhanced virus stability between host-cell replenishment. We also showed evidence that increases in virion survival were associated with decreases in virulence, which suggests a trade-off between survival and virulence for the VSV populations on one cell type. Our results shed new light on the causes and consequences of "sit and wait" infection strategies in RNA viruses.

Combining mathematics and empirical data to predict emergence of RNA viruses that differ in reservoir use

RNA viruses may be particularly capable of contributing to the increasing biomedical problem of infectious disease emergence. Empirical studies and epidemiological models are informative for the understanding of evolutionary processes that promote pathogen emergence, but rarely are these approaches combined in the same study. Here, we used an epidemiology model containing observations of pathogen productivity in reservoirs, as a means to predict which pathogens should be most prone to emerge in a primary host such as humans. We employed as a model system a collection of vesicular stomatitis virus populations that had previously diverged in host-use strategy: specialists, directly selected generalists and indirectly selected (fortuitous) generalists. Using data from experiments where these viral strategists were challenged to grow on unencountered novel hosts in vitro, logistic growth models determined that the directly selected generalist viruses tended to grow best on model reservoirs. Furthermore, when we used the growth data to estimate average reproductive rate across secondary reservoirs, we showed that the combined approach could be used to estimate relative success of the differing virus strategists when encountering a primary host. Our study suggests that synergistic approaches combining epidemiological modelling with empirical data from experimental evolution may be useful for developing efforts to predict which types of pathogens pose the greatest probability of emerging in the future.

Experimental evidence that source genetic variation drives pathogen emergence

A pathogen can readily mutate to infect new host types, but this does not guarantee successful establishment in the new habitat. What factors, then, dictate emergence success? One possibility is that the pathogen population cannot sustain itself on the new host type (i.e. host is a sink), but migration from a source population allows adaptive sustainability and eventual emergence by delivering beneficial mutations sampled from the source's standing genetic variation. This idea is relevant regardless of whether the sink host is truly novel (host shift) or whether the sink is an existing or related, similar host population thriving under conditions unfavourable to pathogen persistence (range expansion). We predicted that sink adaptation should occur faster under range expansion than during a host shift owing to the effects of source genetic variation on pathogen adaptability in the sink. Under range expansion, source migration should benefit emergence in the sink because selection acting on source and sink populations is likely to be congruent. By contrast, during host shifts, source migration is likely to disrupt emergence in the sink owing to uncorrelated selection or performance tradeoffs across host types. We tested this hypothesis by evolving bacteriophage populations on novel host bacteria under sink conditions, while manipulating emergence via host shift versus range expansion. Controls examined sink adaptation when unevolved founding genotypes served as migrants. As predicted, adaptability was fastest under range expansion, and controls did not adapt. Large, similar and similarly timed increases in fitness were observed in the host-shift populations, despite declines in mean fitness of immigrants through time. These results suggest that source populations are the origin of mutations that drive adaptive emergence at the edge of a pathogen's ecological or geographical range.

Understanding the molecular epidemiology of foot-and-mouth-disease virus

The use of molecular epidemiology is an important tool in understanding and consequently controlling FMDV. In this review I will present basic information about the disease, needed to perform molecular epidemiology. I will give a short introduction to the history and impact of foot-and-mouth disease, clinical picture, infection route, subclinical and persistent infections, general aspects of the transmission of FMDV, serotype-specific epidemiological characteristics, field epidemiology of FMDV, evolution and molecular epidemiology of FMDV. This is followed by two chapters describing the molecular epidemiology of foot-and-mouth disease in global surveillance and molecular epidemiology of foot-and-mouth disease in outbreak investigation.

The effect of spatial structure on adaptation in Escherichia coli

Populations of organisms are generally organized in a given spatial structure. However, the vast majority of population genetic studies are based on populations in which every individual competes globally. Here we use experimental evolution in Escherichia coli to directly test a recently made prediction that spatial structure slows down adaptation and that this cost increases with the mutation rate. This was studied by comparing populations of different mutation rates adapting to a liquid (unstructured) medium with populations that evolved in a Petri dish on solid (structured) medium. We find that mutators adapt faster to both environments and that adaptation is slower if there is spatial structure. We observed no significant difference in the cost of structure between mutator and wild-type populations, which suggests that clonal interference is intense in both genetic backgrounds.

Environmental heterogeneity enhances clonal interference

Clonal interference (CI) is a phenomenon that may be important in several asexual microbes. It occurs when population sizes are large and mutation rates to new beneficial alleles are of significant magnitude. Here we explore the role of gene flow and spatial heterogeneity in selection strength in the adaptation of asexuals. We consider a subdivided population of individuals that are adapting, through new beneficial mutations, and that migrate between different patches. The fitness effect of each mutation depends on the patch and all mutations considered are assumed to be unconditionally beneficial. We find that spatial variation in selection pressure affects the rate of adaptive evolution and its qualitative effects depend on the level of gene flow. In particular, we find that both low migration and high levels of heterogeneity lead to enhanced CI. In contrast, for high levels of migration the rate of fixation of adaptive mutations is higher when environmental heterogeneity is present. In addition, we observe that the level of fitness variation is higher and simultaneous fixation of multiple mutations tends to occur in the regime of low migration rates and high heterogeneity.

Quasi-species evolution in subdivided populations favours maximally deleterious mutations

Most models of quasi-species evolution predict that populations will evolve to occupy areas of sequence space with the greatest concentration of neutral sequences, thus minimizing the deleterious mutation rate and creating mutationally 'robust' genomes. In contrast, empirical studies of the principal model of quasi-species evolution, RNA viruses, suggest that the effects of deleterious mutations are more severe than in similar DNA-based microbes. We demonstrate that populations divided into discrete patches connected by dispersal may favour genotypes where the deleterious effect of non-neutral mutations is maximized. This effect is especially strong in the absence of back mutation and when the amount of time spent in hosts prior to dispersal is intermediate. Our results indicate that RNA viruses that produce acute infections initiated by a small number of virions are expected to evolve fragile genetic architectures when compared with other RNA viruses.

Virus fitness: concept, quantification, and application to HIV population dynamics

Viral fitness has been broadly studied during the past three decades, mainly to test evolutionary models and population theories difficult to analyze and interpret with more complex organisms. More recent studies, however, are focused in the role of fitness on viral transmission, pathogenesis, and drug resistance. Here, we used human immunodeficiency virus (HIV) as one of the most relevant models to evaluate the importance of viral quasispecies and fitness in HIV evolution, population dynamics, disease progression, and potential clinical implications.

The effect of migration on local adaptation in a coevolving host-parasite system

Antagonistic coevolution between hosts and parasites in spatially structured populations can result in local adaptation of parasites; that is, the greater infectivity of local parasites than foreign parasites on local hosts. Such parasite specialization on local hosts has implications for human health and agriculture. By contrast with classic single-species population-genetic models, theory indicates that parasite migration between subpopulations might increase parasite local adaptation, as long as migration does not completely homogenize populations. To test this hypothesis we developed a system-specific mathematical model and then coevolved replicate populations of the bacterium Pseudomonas fluorescens and a parasitic bacteriophage with parasite only, with host only or with no migration. Here we show that patterns of local adaptation have considerable temporal and spatial variation and that, in the absence of migration, parasites tend to be locally maladapted. However, in accord with our model, parasite migration results in parasite local adaptation, but host migration alone has no significant effect.

The population genetics and evolutionary epidemiology of RNA viruses

The authors discuss the main mechanisms of RNA virus evolution — mutation, recombination, natural selection, genetic drift and migration, and how these interact to shape the genetic structure of populations. The quasispecies model of RNA virus evolution is explained and the question of whether this model provides an accurate description of RNA virus evolution is discussed. Experiments that can be carried out to test the basic principles of evolutionary theory are briefly described. The authors review what such experiments have told us about virus evolution and, more widely, what these experiments have revealed in terms of general evolutionary principles. RNA viruses evolve quickly, so a detailed reconstruction of their epidemiological history can be undertaken. The authors show how epidemiological patterns of viruses result from their evolution at two different levels: within individual hosts (and vectors) and among hosts at the population level. Using several examples, including HIV and SARS, the authors describe how studying RNA virus evolution could be used to understand virus emergence. Finally, the important topics of the evolution of virulence and resistance to drugs are discussed.

RNA viruses are ubiquitous intracellular parasites that are responsible for many emerging diseases, including AIDS and SARS. Here, we discuss the principal mechanisms of RNA virus evolution and highlight areas where future research is required. The rapidity of sequence change in RNA viruses means that they are useful experimental models for the study of evolution in general and it enables us to watch them change in 'real time', and retrace the spread through populations with molecular phylogenies. An understanding of the mechanisms of RNA virus sequence change is also crucial to predicting important aspects of their emergence and long-term evolution.

Genetic variability: the key problem in the prevention and therapy of RNA-based virus infections

Despite extraordinary progress that has recently been made in biomedical sciences, viral infectious diseases still remain one of the most serious world health problems. Among the different types of viruses, those using RNA as their genetic material (RNA viruses and retroviruses) are especially dangerous. At present there is no medicine allowing an effective treatment of RNA-based virus infections. Many RNA viruses and retroviruses need only a few weeks to escape immune response or to produce drug-resistant mutants. This seems to be the obvious consequence of the unusual genetic variability of RNA-based viruses. An individual virus does not form a homogenous population but rather a set of similar but not identical variants. In consequence, RNA-based viruses can easily adapt to environmental changes, also those resulting from immune system response or therapy. The modifications identified within viral genes can be divided into two groups: point mutations and complex genome rearrangements. The former arises mainly during error-prone replication, whereas RNA recombination and generic reassortment are responsible for the latter. This article shortly describes major strategies used to control virus infections. Then, it presents the various mechanisms generating the genetic diversity of RNA-based viruses, which are most probably the main cause of clinical problems.

Evolution of RNA virus in spatially structured heterogeneous environments

A hallmark of the infectious cycle for many RNA viruses parasitizing multicellular hosts is the need to invade and successfully replicate in tissues that comprise a variety of cell types. Thus, multicellular hosts represent a heterogeneous environment to evolving viral populations. To understand viral adaptation to multicellular hosts, we took a double approach. First, we developed a mathematical model that served to make predictions concerning the dynamics of viral populations evolving in heterogeneous environments. Second, the predictions were tested by evolving vesicular stomatitis virus in vitro on a spatially structured environment formed by three different cell types. In the absence of gene flow, adaptation was tissue-specific, but fitness in all tissues decreased with migration rate. The performance in a given tissue was negatively correlated with its distance to the tissue hosting the population. This correlation decreased with migration rate.

r- and K-selection in experimental populations of vesicular stomatitis virus

Here we explore the adaptation of vesicular stomatitis RNA virus to different population densities and the existence of a trade-off between r- and K-selection. Increasing population density represents a challenging special situation for viruses, since different selective pressures arise depending upon the number of available host cells per virus. Adaptation to low density represents a prototypical case of r-selection, where the optimal evolutionary solution should be a high replication rate. Adaptation to high density represents a case of K-selection. In this case, genotypes optimally exploiting the resources, instead of faster replicating ones, should be selected. Five independent populations were maintained in two environments, called r and K, for 100 generations. In the r environment, effective population size was small. In contrast, the effective population size in the K environment was large. Our results support the existence of the expected trade-offs between these two types of selections. Viral populations evolved at low density performed worse as population density increased. Similarly, viral populations evolved at high density showed reduced fitness at low density. Finally, we compare our results with those obtained for other RNA viruses.

Evolutionary history conditions the timing of transmission in vesicular stomatitis virus

It has been postulated that early transmitted viruses would evolve to be more virulent than late transmitted ones. The reason for this prediction is that early transmission selects for rapid viral replication and, consequently, rapid host death, whereas late transmission would select for slow-replicating viruses that permit longer survival to the host. To test this prediction, experimental lineages of vesicular stomatitis virus (VSV) had been adapted to three different transmission dynamics during more than 100 generations. Transmission dynamic differed in the stage of infection at which transmission took place: early, intermediate or late. Regardless the timing of transmission imposed during the competition experiments done for estimating fitness, lineages adapted to an intermediate time of transmission reached higher fitness than viruses adapted to either early or late transmission. Viruses adapted to early and late transmission schedules showed a trade-off in their performance at other transmission times, with higher fitness at their own transmission time than at any other. The basis of fitness differences, in terms of growth parameters, have also been explored. Fitness correlated with the rate of growth and with the moment of maximum population density but not with the maximum density itself. In addition, a positive correlation between virus performance at late transmission and stability outside the cellular host has been detected.

Estimating relative fitness in viral competition experiments

The relative fitness of viral variants has previously been defined as the slope of the logarithmic ratio of the genotype or phenotype frequencies in time plots of pairwise competition experiments. Developing mathematical models for such experiments by employing the conventional coefficient of selection s, we demonstrate that this logarithmic ratio gives the fitness difference, rather than the relative fitness. This fitness difference remains proportional to the actual replication rate realized in the particular experimental setup and hence cannot be extrapolated to other situations. Conversely, the conventional relative fitness (1 + s) should be more generic. We develop an approach to compute the generic relative fitness in conventional competition experiments. This involves an estimation of the total viral replication during the experiment and requires an estimate of the average lifetime of productively infected cells. The novel approach is illustrated by estimating the relative fitness, i.e., the relative replication rate, of a set of zidovudine-resistant human immunodeficiency virus type 1 variants. A tool for calculating the relative fitness from observed changes in viral load and genotype (or phenotype) frequencies is publically available on the website at http://www-binf.bio.uu.nl/( approximately )rdb/fitness.html.

The evolution of RNA viruses: A population genetics view

RNA viruses are excellent experimental models for studying evolution under the theoretical framework of population genetics. For a proper justification of this thesis we have introduced some properties of RNA viruses that are relevant for studying evolution. On the other hand, population genetics is a reductionistic theory of evolution. It does not consider or make simplistic assumptions on the transformation laws within and between genotypic and phenotypic spaces. However, such laws are minimized in the case of RNA viruses because the phenotypic space maps onto the genotypic space in a much more linear way than on higher DNA-based organisms. Under experimental conditions, we have tested the role of deleterious and beneficial mutations in the degree of adaptation of vesicular stomatitis virus (VSV), a nonsegmented virus of negative strand. We also have studied how effective population size, initial genetic variability in populations, and environmental heterogeneity shapes the impact of mutations in the evolution of vesicular stomatitis virus. Finally, in an integrative attempt, we discuss pros and cons of the quasispecies theory compared with classic population genetics models for haploid organisms to explain the evolution of RNA viruses.

Diminishing returns of population size in the rate of RNA virus adaptation

Whenever an asexual viral population evolves by adapting to new environmental conditions, beneficial mutations, the ultimate cause of adaptation, are randomly produced and then fixed in the population. The larger the population size and the higher the mutation rate, the more beneficial mutations can be produced per unit time. With the usually high mutation rate of RNA viruses and in a large enough population, several beneficial mutations could arise at the same time but in different genetic backgrounds, and if the virus is asexual, they will never be brought together through recombination. Thus, the best of these genotypes must outcompete each other on their way to fixation. This competition among beneficial mutations has the effect of slowing the overall rate of adaptation. This phenomenon is known as clonal interference. Clonal interference predicts a speed limit for adaptation as the population size increases. In the present report, by varying the size of evolving vesicular stomatitis virus populations, we found evidence clearly demonstrating this speed limit and thus indicating that clonal interference might be an important factor modulating the rate of adaptation to an in vitro cell system. Several evolutionary and epidemiological implications of the clonal interference model applied to RNA viruses are discussed.

Clonal interference and the evolution of RNA viruses

In asexual populations, beneficial mutations that occur in different lineages compete with one another. This phenomenon, known as clonal interference, ensures that those beneficial mutations that do achieve fixation are of large effect. Clonal interference also increases the time between fixations, thereby slowing the adaptation of asexual populations. The effects of clonal interference were measured in the asexual RNA virus vesicular stomatitis virus; rates and average effects of beneficial mutations were quantified.