Effect of unequal vaccination coverage and migration on long-term pathogen evolution in a metapopulation

Worldwide inequalities in vaccine availability are expected to affect the spread and spatial distribution of infectious diseases. It is unclear, however, how spatial variation in vaccination coverage can affect the long-term evolution of pathogens. Here we use an analytical model and numerical simulations to analyse the influence of different imperfect vaccines on the potential evolution of pathogen virulence in a two-population model where vaccination coverage varies between populations. We focus on four vaccines, with different modes of action on the life cycle of a pathogen infecting two host populations coupled by migration. We show that, for vaccines that reduce infection risk or transmissibility, spatial heterogeneity has little effect on pathogen prevalence and host mortality, and no effect on the evolution of pathogen virulence. In contrast, vaccines that reduce pathogen virulence can select for more virulent pathogens and may lead to the coexistence of different pathogen strains, depending on the degree of spatial heterogeneity in the metapopulation. This heterogeneity is driven by two parameters: pathogen migration and the difference in the vaccination rate between the two populations. We show that vaccines that only reduce pathogen virulence select mainly for a single pathogen strategy in the long term, while vaccines that reduce both transmission and virulence can favor the coexistence of two pathogen genotypes. We discuss the implications and potential extensions of our analysis.

Phenotypic evolution of SARS-CoV-2: a statistical inference approach

Since its emergence in late 2019, the SARS-CoV-2 virus has spread globally, causing the ongoing COVID-19 pandemic. In the fall of 2020, the Alpha variant (lineage B.1.1.7) was detected in England and spread rapidly, outcompeting the previous lineage. Yet, very little is known about the underlying modifications of the infection process that can explain this selective advantage. Here, we try to quantify how the Alpha variant differed from its predecessor on two phenotypic traits: The transmission rate and the duration of infectiousness. To this end, we analyzed the joint epidemiological and evolutionary dynamics as a function of the Stringency Index, a measure of the amount of Non-Pharmaceutical Interventions. Assuming that these control measures reduce contact rates and transmission, we developed a two-step approach based on ${{SEIR}}$ models and the analysis of a combination of epidemiological and evolutionary information. First, we quantify the link between the Stringency Index and the reduction in viral transmission. Second, based on a novel theoretical derivation of the selection gradient in an ${{SEIR}}$ model, we infer the phenotype of the Alpha variant from its frequency changes. We show that its selective advantage is more likely to result from a higher transmission than from a longer infectious period. Our work illustrates how the analysis of the joint epidemiological and evolutionary dynamics of infectious diseases can help understand the phenotypic evolution driving pathogen adaptation.

Extending eco-evolutionary theory with oligomorphic dynamics

Understanding the interplay between ecological processes and the evolutionary dynamics of quantitative traits in natural systems remains a major challenge. Two main theoretical frameworks are used to address this question, adaptive dynamics and quantitative genetics, both of which have strengths and limitations and are often used by distinct research communities to address different questions. In order to make progress, new theoretical developments are needed that integrate these approaches and strengthen the link to empirical data. Here, we discuss a novel theoretical framework that bridges the gap between quantitative genetics and adaptive dynamics approaches. 'Oligomorphic dynamics' can be used to analyse eco-evolutionary dynamics across different time scales and extends quantitative genetics theory to account for multimodal trait distributions, the dynamical nature of genetic variance, the potential for disruptive selection due to ecological feedbacks, and the non-normal or skewed trait distributions encountered in nature. Oligomorphic dynamics explicitly takes into account the effect of environmental feedback, such as frequency- and density-dependent selection, on the dynamics of multi-modal trait distributions and we argue it has the potential to facilitate a much tighter integration between eco-evolutionary theory and empirical data.

FLAIR Vascular Hyperintensities as a Surrogate of Collaterals in Acute Stroke: DWI Matters

BACKGROUND AND PURPOSE

FLAIR vascular hyperintensities are thought to represent leptomeningeal collaterals in acute ischemic stroke. However, whether all-FLAIR vascular hyperintensities or FLAIR vascular hyperintensities-DWI mismatch, ie, FLAIR vascular hyperintensities beyond the DWI lesion, best reflects collaterals remains debated. We aimed to compare the value of FLAIR vascular hyperintensities-DWI mismatch versus all-FLAIR vascular hyperintensities for collateral assessment using PWI-derived collateral flow maps as a reference.

MATERIALS AND METHODS

We retrospectively reviewed the registries of 6 large stroke centers and included all patients with acute stroke with anterior circulation large-vessel occlusion who underwent MR imaging with PWI before thrombectomy. Collateral status was graded from 1 to 4 on PWI-derived collateral flow maps and dichotomized into good (grades 3-4) and poor (grades 1-2). The extent of all-FLAIR vascular hyperintensities and FLAIR vascular hyperintensities-DWI mismatch was assessed on the 7 cortical ASPECTS regions, ranging from 0 (absence) to 7 (extensive), and associations with good collaterals were compared using receiver operating characteristic curves.

RESULTS

Of the 209 included patients, 133 (64%) and 76 (36%) had good and poor collaterals, respectively. All-FLAIR vascular hyperintensity extent was similar between collateral groups (P = .76). Conversely, FLAIR vascular hyperintensities-DWI mismatch extent was significantly higher in patients with good compared with poor collaterals (P < .001). The area under the curve was 0.80 (95% CI, 0.74-0.87) for FLAIR vascular hyperintensities-DWI mismatch and 0.52 (95% CI, 0.44-0.60) for all-FLAIR vascular hyperintensities (P < .001 for the comparison), to predict good collaterals. Variables independently associated with good collaterals were smaller DWI lesion volume (P < .001) and larger FLAIR vascular hyperintensities-DWI mismatch (P = .02).

CONCLUSIONS

In acute ischemic stroke with large-vessel occlusion, the extent of FLAIR vascular hyperintensities does not reliably reflect collateral status unless one accounts for DWI.

Evolution of class-structured populations in periodic environments

What is the influence of periodic environmental fluctuations on life-history evolution? We present a general theoretical framework to understand and predict the long-term evolution of life-history traits under a broad range of ecological scenarios. Specifically, we investigate how periodic fluctuations affect selection when the population is also structured in distinct classes. This analysis yields time-varying selection gradients that clarify the influence of the fluctuations of the environment on the competitive ability of a specific life-history mutation. We use this framework to analyse the evolution of key life-history traits of pathogens. We examine three different epidemiological scenarios and we show how periodic fluctuations of the environment can affect the evolution of virulence and transmission as well as the preference for different hosts. These examples yield new and testable predictions on pathogen evolution, and illustrate how our approach can provide a better understanding of the evolutionary consequences of time-varying environmental fluctuations in a broad range of scenarios.

Targeted vaccination and the speed of SARS-CoV-2 adaptation

The limited supply of vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) raises the question of targeted vaccination. Many countries have opted to vaccinate older and more sensitive hosts first to minimize the disease burden. However, what are the evolutionary consequences of targeted vaccination? We clarify the consequences of different vaccination strategies through the analysis of the speed of viral adaptation measured as the rate of change of the frequency of a vaccine-adapted variant. We show that such a variant is expected to spread faster if vaccination targets individuals who are likely to be involved in a higher number of contacts. We also discuss the pros and cons of dose-sparing strategies. Because delaying the second dose increases the proportion of the population vaccinated with a single dose, this strategy can both speed up the spread of the vaccine-adapted variant and reduce the cumulative number of deaths. Hence, strategies that are most effective at slowing viral adaptation may not always be epidemiologically optimal. A careful assessment of both the epidemiological and evolutionary consequences of alternative vaccination strategies is required to determine which individuals should be vaccinated first.

An epi-evolutionary model for predicting the adaptation of spore-producing pathogens to quantitative resistance in heterogeneous environments

We have modeled the evolutionary epidemiology of spore-producing plant pathogens in heterogeneous environments sown with several cultivars carrying quantitative resistances. The model explicitly tracks the infection-age structure and genetic composition of the pathogen population. Each strain is characterized by pathogenicity traits determining its infection efficiency and a time-varying sporulation curve taking into account lesion aging. We first derived a general expression of the basic reproduction number R 0 for fungal pathogens in heterogeneous environments. We show that the evolutionary attractors of the model coincide with local maxima of R 0 only if the infection efficiency is the same on all host types. We then studied the contribution of three basic resistance characteristics (the pathogenicity trait targeted, resistance effectiveness, and adaptation cost), in interaction with the deployment strategy (proportion of fields sown with a resistant cultivar), to (i) pathogen diversification at equilibrium and (ii) the shaping of transient dynamics from evolutionary and epidemiological perspectives. We show that quantitative resistance affecting only the sporulation curve will always lead to a monomorphic population, whereas dimorphism (i.e., pathogen diversification) can occur if resistance alters infection efficiency, notably with high adaptation costs and proportions of the resistant cultivar. Accordingly, the choice of the quantitative resistance genes operated by plant breeders is a driver of pathogen diversification. From an evolutionary perspective, the time to emergence of the evolutionary attractor best adapted to the resistant cultivar tends to be shorter when resistance affects infection efficiency than when it affects sporulation. Conversely, from an epidemiological perspective, epidemiological control is always greater when the resistance affects infection efficiency. This highlights the difficulty of defining deployment strategies for quantitative resistance simultaneously maximizing epidemiological and evolutionary outcomes.

Regulation of prophage induction and lysogenization by phage communication systems

Many viruses cause both lytic infections, where they release viral particles, and dormant infections, where they await future opportunities to reactivate.1 The benefits of each transmission mode depend on the density of susceptible hosts in the environment.2-4 Some viruses infecting bacteria use molecular signaling to respond plastically to changes in host availability.5 These viruses produce a signal during lytic infection and regulate, based on the signal concentration in the environment, the probability with which they switch to causing dormant infections.5,6 We present an analytical framework to examine the adaptive significance of plasticity in viral life-history traits in fluctuating environments. Our model generalizes and extends previous theory7 and predicts that host density fluctuations should select for plasticity in entering lysogeny as well as virus reactivation once signal concentrations decline. Using Bacillus subtilis and its phage phi3T, we experimentally confirm the prediction that phages use signal to make informed decisions over prophage induction. We also demonstrate that lysogens produce signaling molecules and that signal is degraded by hosts in a density-dependent manner. Declining signal concentrations therefore potentially indicate the presence of uninfected hosts and trigger prophage induction. Finally, we find that conflict over the responses of lysogenization and reactivation to signal is resolved through the evolution of different response thresholds for each trait. Collectively, these findings deepen our understanding of the ways viruses use molecular communication to regulate their infection strategies, which can be leveraged to manipulate host and phage population dynamics in natural environments.

Design of a prospective, longitudinal cohort of people living with type 1 diabetes exploring factors associated with the residual cardiovascular risk and other diabetes-related complications: The SFDT1 study

Type 1 diabetes mellitus (T1DM) is associated with a high risk of cardiovascular (CV) complications, even after controlling for traditional CV risk factors. Therefore, determinants of the residual increased CV morbidity and mortality remain to be discovered. This prospective cohort of people living with T1DM in France (SFDT1) will include adults and children aged over six years living with T1DM, recruited throughout metropolitan France and overseas French departments and territories. The primary objective is to better understand the parameters associated with CV complications in T1DM. Clinical data and biobank samples will be collected during routine visits every three years. Data from connected tools, including continuous glucose monitoring, will be available during the 10-year active follow-up. Patient-reported outcomes, psychological and socioeconomic information will also be collected either at visits or through web questionnaires accessible via the internet. Additionally, access to the national health data system (Health Data Hub) will provide information on healthcare and a passive 20-year medico-administrative follow-up. Using Health Data Hub, SFDT1 participants will be compared to non-diabetic individuals matched on age, gender, and residency area. The cohort is sponsored by the French-speaking Foundation for Diabetes Research (FFRD) and aims to include 15,000 participants.

Epidemiological and evolutionary consequences of periodicity in treatment coverage

Host heterogeneity is a key driver of host-pathogen dynamics. In particular, the use of treatments against infectious diseases creates variation in quality among hosts, which can have both epidemiological and evolutionary consequences. We present a general theoretical model to highlight the consequences of different imperfect treatments on pathogen prevalence and evolution. These treatments differ in their action on host and pathogen traits. In contrast with previous studies, we assume that treatment coverage can vary in time, as in seasonal or pulsed treatment strategies. We show that periodic treatment strategies can limit both disease spread and virulence evolution, depending on the type of treatment. We also introduce a new method to analytically calculate the selection gradient in periodic environments, which allows our predictions to be interpreted using the concept of reproductive value, and can be applied more generally to analyse eco-evolutionary dynamics in class-structured populations and fluctuating environments.

Variability in the durability of CRISPR-Cas immunity

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

Evolutionary emergence of infectious diseases in heterogeneous host populations

The emergence and re-emergence of pathogens remains a major public health concern. Unfortunately, when and where pathogens will (re-)emerge is notoriously difficult to predict, as the erratic nature of those events is reinforced by the stochastic nature of pathogen evolution during the early phase of an epidemic. For instance, mutations allowing pathogens to escape host resistance may boost pathogen spread and promote emergence. Yet, the ecological factors that govern such evolutionary emergence remain elusive because of the lack of ecological realism of current theoretical frameworks and the difficulty of experimentally testing their predictions. Here, we develop a theoretical model to explore the effects of the heterogeneity of the host population on the probability of pathogen emergence, with or without pathogen evolution. We show that evolutionary emergence and the spread of escape mutations in the pathogen population is more likely to occur when the host population contains an intermediate proportion of resistant hosts. We also show that the probability of pathogen emergence rapidly declines with the diversity of resistance in the host population. Experimental tests using lytic bacteriophages infecting their bacterial hosts containing Clustered Regularly Interspaced Short Palindromic Repeat and CRISPR-associated (CRISPR-Cas) immune defenses confirm these theoretical predictions. These results suggest effective strategies for cross-species spillover and for the management of emerging infectious diseases.

The probability that an epidemic will break out is highly dependent on the ability of the pathogen to acquire new adaptive mutations and to induce evolutionary emergence. Forecasting pathogen emergence thus requires a good understanding of the interplay between the epidemiology and evolution taking place at the onset of an outbreak. Here, we provide a comprehensive theoretical framework to analyze the impact of host population heterogeneity on the probability of pathogen evolutionary emergence. We use this model to predict the impact of the fraction of susceptible hosts, the inoculum size of the pathogen, and the diversity of host resistance on pathogen emergence. Our experiments using lytic bacteriophages and CRISPR-resistant bacteria support our theoretical predictions and demonstrate that manipulating the diversity of resistance alleles in a host population may be an effective way to limit the emergence of new pathogens.

From the Price equation to the selection gradient in class-structured populations: a quasi-equilibrium route

Recent studies in theoretical evolutionary ecology have emphasised two approaches to modelling evolution. On the one hand, models based on a separation of time scales rely on the concept of invasion fitness. On the other hand, models based on the Price equation track the dynamics of a trait average, coupled with a description of ecological dynamics. The aim of this article is to show that, in class-structured populations, both approaches yield the same expression for the selection gradient under weak selection. Although the result is not new, I propose an alternative route to its derivation using the dynamics of scaled measures of between-class phenotypic differentiation. Under weak selection, these measures of phenotypic differentiation can be treated as fast variables compared to the trait mean, which allows for a quasi-equilibrium approximation. This suggests a different approach to calculating weak selection approximations of evolutionary dynamics, and clarifies the links between short- and long-term perspectives on evolution in structured populations.

Class Structure, Demography, and Selection: Reproductive-Value Weighting in Nonequilibrium, Polymorphic Populations

In natural populations, individuals of a given genotype may belong to different classes. Such classes can represent different age groups, developmental stages, or habitats. Class structure has important evolutionary consequences because the fitness of individuals with the same genetic background may vary depending on their class. As a result, demographic transitions between classes can cause fluctuations in the trait mean that need to be removed when estimating selection on a trait. Intrinsic differences between classes are classically taken into account by weighting individuals by class-specific reproductive values, defined as the relative contribution of individuals in a given class to the future of the population. These reproductive values are generally constant weights calculated from a constant projection matrix. Here, I show for large populations and clonal reproduction that reproductive values can be defined as time-dependent weights satisfying dynamical demographic equations that depend only on the average between-class transition rates over all genotypes. Using these time-dependent demographic reproductive values yields a simple Price equation where the nonselective effects of between-class transitions are removed from the dynamics of the trait. This generalizes previous theory to a large class of ecological scenarios, taking into account density dependence, ecological feedbacks, arbitrary strength of selection, and arbitrary trait distributions. I discuss the role of reproductive values for prospective and retrospective analyses of the dynamics of phenotypic traits.

Theoretical Approaches in Evolutionary Ecology: Environmental Feedback as a Unifying Perspective

Evolutionary biology and ecology have a strong theoretical underpinning, and this has fostered a variety of modeling approaches. A major challenge of this theoretical work has been to unravel the tangled feedback loop between ecology and evolution. This has prompted the development of two main classes of models. While quantitative genetics models jointly consider the ecological and evolutionary dynamics of a focal population, a separation of timescales between ecology and evolution is assumed by evolutionary game theory, adaptive dynamics, and inclusive fitness theory. As a result, theoretical evolutionary ecology tends to be divided among different schools of thought, with different toolboxes and motivations. My aim in this synthesis is to highlight the connections between these different approaches and clarify the current state of theory in evolutionary ecology. Central to this approach is to make explicit the dependence on environmental dynamics of the population and evolutionary dynamics, thereby materializing the eco-evolutionary feedback loop. This perspective sheds light on the interplay between environmental feedback and the timescales of ecological and evolutionary processes. I conclude by discussing some potential extensions and challenges to our current theoretical understanding of eco-evolutionary dynamics.

Spatial evolutionary epidemiology of spreading epidemics

Most spatial models of host-parasite interactions either neglect the possibility of pathogen evolution or consider that this process is slow enough for epidemiological dynamics to reach an equilibrium on a fast timescale. Here, we propose a novel approach to jointly model the epidemiological and evolutionary dynamics of spatially structured host and pathogen populations. Starting from a multi-strain epidemiological model, we use a combination of spatial moment equations and quantitative genetics to analyse the dynamics of mean transmission and virulence in the population. A key insight of our approach is that, even in the absence of long-term evolutionary consequences, spatial structure can affect the short-term evolution of pathogens because of the build-up of spatial differentiation in mean virulence. We show that spatial differentiation is driven by a balance between epidemiological and genetic effects, and this quantity is related to the effect of kin competition discussed in previous studies of parasite evolution in spatially structured host populations. Our analysis can be used to understand and predict the transient evolutionary dynamics of pathogens and the emergence of spatial patterns of phenotypic variation.

Beyond Mortality: Sterility As a Neglected Component of Parasite Virulence

Virulence is generally defined as the reduction in host fitness following infection by a parasite (see Box 1 for glossary) [1]. In general, parasite exploitation of host resources may reduce host survival (mortality virulence), decrease host fecundity (sterility virulence), or even have sub-lethal effects that disturb the way individuals interact within a community (morbidity) [2,3]. In fact, the virulence of many parasites involves a combination of these various effects (Box 2). In practice, however, virulence is most often defined as disease-induced mortality [1, 4–6]. This is especially true in the theoretical literature, where the evolution of sterility virulence, morbidity, and mixed strategies of host exploitation have received relatively little attention. While the focus on mortality effects has allowed for easy comparison between models and, thus, rapid advancement of the field, we ask whether these theoretical simplifications have led us to inadvertently minimize the evolutionary importance of host sterilization and secondary virulence effects. As explicit theoretical work on morbidity is currently lacking (but see [7]), our aim in this Opinion piece is to discuss what is understood about sterility virulence evolution, its adaptive potential, and the implications for parasites that utilize a combination of host survival and reproductive resources.

Superinfection and the coevolution of parasite virulence and host recovery

Parasite strategies of host exploitation may be affected by host defence strategies and multiple infections. In particular, within-host competition between multiple parasite strains has been shown to select for higher virulence. However, little is known on how multiple infections could affect the coevolution between host recovery and parasite virulence. Here, we extend a coevolutionary model introduced by van Baalen (Proc. R. Soc. B, 265, 1998, 317) to account for superinfection. When the susceptibility to superinfection is low, we recover van Baalen's results and show that there are two potential evolutionary endpoints: one with avirulent parasites and poorly defended hosts, and another one with high virulence and high recovery. However, when the susceptibility to superinfection is above a threshold, the only possible evolutionary outcome is one with high virulence and high investment into defence. We also show that within-host competition may select for lower host recovery, as a consequence of selection for more virulent strains. We discuss how different parasite and host strategies (superinfection facilitation, competitive exclusion) as well as demographic and environmental parameters, such as host fecundity or various costs of defence, may affect the interplay between multiple infections and host-parasite coevolution. Our model shows the interplay between coevolutionary dynamics and multiple infections may be affected by crucial mechanistic or ecological details.

Quantifying the epidemic spread of Ebola virus (EBOV) in Sierra Leone using phylodynamics

Measuring epidemic parameters early in an outbreak is essential to inform control efforts. Using the viral genome sequence and collection date from 78 infections in the 2014 Ebola virus outbreak in Sierra Leone, we estimate key epidemiological parameters such as infectious period duration (approximately 71 hours) and date of the first case in Sierra Leone (approximately April 25th). We also estimate the effective reproduction number, Re, (approximately 1.26), which is the number of secondary infections effectively caused by an infected individual and accounts for public health control measures. This study illustrates that phylodynamics methods, applied during the initial phase of an outbreak on fewer and more easily attainable data, can yield similar estimates to count-based epidemiological studies.

Spatial structure, host heterogeneity and parasite virulence: implications for vaccine-driven evolution

Natural host-parasite interactions exhibit considerable variation in host quality, with profound consequences for disease ecology and evolution. For instance, treatments (such as vaccination) may select for more transmissible or virulent strains. Previous theory has addressed the ecological and evolutionary impact of host heterogeneity under the assumption that hosts and parasites disperse globally. Here, we investigate the joint effects of host heterogeneity and local dispersal on the evolution of parasite life-history traits. We first formalise a general theoretical framework combining variation in host quality and spatial structure. We then apply this model to the specific problem of parasite evolution following vaccination. We show that, depending on the type of vaccine, spatial structure may select for higher or lower virulence compared to the predictions of non-spatial theory. We discuss the implications of our results for disease management, and their broader fundamental relevance for other causes of host heterogeneity in nature.

Multiple infections, kin selection and the evolutionary epidemiology of parasite traits

The coinfection of a host by several parasite strains is known to affect selective pressures on parasite strategies of host exploitation. I present a general model of coinfections that ties together kin selection models of virulence evolution and epidemiological models of multiple infections. I derive an analytical expression for the invasion fitness of a rare mutant in a population with an arbitrary distribution of the multiplicity of infection (MOI) across hosts. When a single mutation affects parasite strategies in all MOI classes, I show that the evolutionarily stable level of virulence depends on a demographic average of within-host relatedness across all host classes. This generalization of previous kin selection results requires that within-host parasite densities do not vary between hosts. When host exploitation strategies are allowed to vary across classes, I show that the strategy of host exploitation in a focal MOI class depends on the relative magnitudes of parasite reproductive values in the focal class and in the next. Thus, in contrast to previous findings, lower within-host relatedness in competitive parasite interactions can potentially correspond to either higher or lower levels of virulence.

Evolution of suicide as a defence strategy against pathogens in a spatially structured environment

Suicide upon infection by lytic phages is known in several bacteria species and represents an effective defence strategy to limit phage spread. However, the ecological conditions favouring the evolution of such a radically altruistic behaviour are unclear. Here, we model the feedback of epidemiology on host evolution in a spatially structured environment and we generate several specific predictions on altruistic suicide evolution. We test these predictions experimentally by competing E. coli cells carrying the suicide gene Lit against non-carrier cells in the presence or in the absence of the lytic phage T6. We show that in accord with our theoretical analysis altruistic suicide is only favoured in the presence of the phage in spatially structured environments at intermediate levels of mixing. Our work provides a general explanation for the evolution of altruistic defence strategies against pathogens. We discuss the implications of these results for oncolytic virus therapy.

Tips and traps in brain MRI: applications to vascular disorders

The French Society of Radiology's guide to good use of medical imaging examinations recommends MRI as the first-line examination for exploring cerebrovascular events or disorders. This paper will discuss the main traps in the images when stroke is suspected and provide the technical tips or knowledge necessary for an optimal radiological report.

Evolution of host life-history traits in a spatially structured host-parasite system

Most models for the evolution of host defense against parasites assume that host populations are not spatially structured. Yet local interactions and limited dispersal can strongly affect the evolutionary outcome, because they significantly alter epidemiological feedbacks and the spatial genetic structuring of the host and pathogen populations. We provide a general framework to study the evolution of a number of host life-history traits in a spatially structured host population infected by a horizontally transmitted parasite. Our analysis teases apart the selective pressures on hosts and helps disentangle the direct fitness effect of mutations and their indirect effects via the influence of spatial structure on the genetic, demographic, and epidemiological structure of the host population. We then illustrate the evolutionary consequences of spatial structure by focusing on the evolution of two host defense strategies against parasitism: suicide upon infection and reduced transmission. Because they bring no direct fitness benefit, these strategies are counterselected or selectively neutral in a nonspatial setting, but we show that they can be selected for in a spatially structured environment. Our study thus sheds light on the evolution of altruistic defense mechanisms that have been observed in various biological systems.

Within-host parasite cooperation and the evolution of virulence

Infections by multiple genotypes are common in nature and are known to select for higher levels of virulence for some parasites. When parasites produce public goods (PGs) within the host, such co-infections have been predicted to select for lower levels of virulence. However, this prediction is based on simplifying assumptions regarding epidemiological feedbacks on the multiplicity of infections (MOI). Here, we analyse the case of parasites producing a PG (for example, siderophore-producing bacteria) using a nested model that ties together within-host and epidemiological processes. We find that the prediction that co-infection should select for less virulent strains for PG-producing parasites is only valid if both parasite transmission and virulence are linear functions of parasite density. If there is a trade-off relationship such that virulence increases more rapidly than transmission, or if virulence also depends on the total amount of PGs produced, then more complex relationships between virulence and the MOI are predicted. Our results reveal that explicitly taking into account the distribution of parasite strains among hosts could help better understand the selective pressures faced by parasites at the population level.

Inclusive fitness theory and eusociality

Arising from M. A. Nowak, C. E. Tarnita & E. O. Wilson 466, 1057-1062 (2010); Nowak et al. reply. Nowak et al. argue that inclusive fitness theory has been of little value in explaining the natural world, and that it has led to negligible progress in explaining the evolution of eusociality. However, we believe that their arguments are based upon a misunderstanding of evolutionary theory and a misrepresentation of the empirical literature. We will focus our comments on three general issues.

Are parasites ''prudent'' in space?

There has been a renewed controversy on the processes that determine evolution in spatially structured populations. Recent theoretical and empirical studies have suggested that parasites should be expected to be more “prudent” (less harmful and slower transmitting) when infection occurs locally. Using a novel approach based on spatial moment equations, we show that the evolution of parasites in spatially structured host populations is determined by the interplay of genetic and demographic spatial structuring, which in turn depends on the details of the ecological dynamics. This allows a detailed understanding of the roles of epidemiology, demography and network topology. Demographic turnover is needed for local interactions to select for prudence in the susceptible-infected models that have been the focus of previous studies. In diseases with little demographic turnover (as typical of many human diseases), we show that only parasites causing diseases with long-lived immunity are likely to be prudent in space. We further demonstrate why, at intermediate parasite dispersal, virulence can evolve to higher levels than predicted by non-spatial theory.

Evolution of reproductive effort in viscous populations: the importance of population dynamics

I present two ecological models for the evolution of reproductive effort in viscous populations with empty sites. In contrast with previous studies, I show that limited dispersal needs not have a positive effect on the evolutionarily stable allocation of resources to fecundity versus survival. Rather, depending on the feedback between the trait and the population dynamics, population viscosity may have no effect or even lead to a decrease in the evolutionarily stable reproductive effort when individuals can degrade their environment during their lifetime. I show that the different evolutionary outcomes can be explained by the asymmetry in the level of kin competition resulting from investing into juveniles or into adults.

Life history, habitat saturation and the evolution of fecundity and survival altruism

Hamilton's rule provides a general description of the conditions for the evolution of altruism. But altruism can take different forms depending on which life-history trait is affected by the helping behavior (fecundity vs. survival helping). In particular, these different forms of helping may have very different demographic consequences, which may feed back on evolution. We examine the interplay between various forms of helping and demography in viscous populations with empty sites. A key component of our analysis is the local density of empty sites experienced by a focal individual, which provides a measure of habitat saturation. Habitat saturation is shown to have contrasting effects depending on (1) whether the physiological costs and benefits of helping affect fecundity, survival or both; and (2) whether the costs of helping are paid in a density-dependent or density-independent manner. For a given level of habitat saturation and with density-dependent reproduction, we find that the conditions for the evolution of helping should be more favorable in the survival altruism life cycle with a cost on fecundity, and more stringent in the fecundity altruism life cycle with a cost on survival. More generally, our analysis stresses the importance of taking into account the feedback between population demography, life history, and kin selection when investigating the selective pressures on altruism.

Assessment of asymptomatic liver fibrosis in alcoholic patients using fibroscan: prospective comparison with seven non-invasive laboratory tests

BACKGROUND

Systematic screening for liver fibrosis in heavy-drinking patients is a challenge. Aims To assess Fibroscan for non-invasive diagnosis of asymptomatic liver fibrosis in alcohol abuse patients, to determine diagnostic liver stiffness cut-off values and to compare performance of Fibroscan with seven non-invasive laboratory tests.

METHODS

One hundred and three alcoholic patients were studied. Liver fibrosis was staged by METAVIR system. Fibroscan, Fibrotest, Fibrometer, Hepascore, APRI, PGA, PGAA and hyaluronic acid tests were performed. Liver stiffness cut-offs were determined using receiver-operating characteristic (ROC) curves.

RESULTS

Liver stiffness was correlated with fibrosis (r = 0.72, P < 0.014), with median at 5.7, 6.3, 8.4, 15 and 47.3 kPa for F0 (n = 8), F1 (n = 18), F2 (n = 24), F3 (n = 20) and F4 (n = 33) stage fibrosis respectively. For Fibroscan, areas under ROC curves (AUROCs) were 0.84 (95% CI: 0.73-0.95) (F > or = 1), 0.91 (0.85-0.98) (F > or = 2), 0.90 (0.82-0.97) (F > or = 3) and 0.92 (0.87-0.98) (F = 4), yielding diagnostic stiffness cut-offs of 5.9 (F > or = 1), 7.8 (F > or = 2), 11 (F > or = 3) and 19.5 (F4) kPa. Sensitivity, specificity, PPV and NPV were 80%, 90.5%, 93% and 70% for F > or = 2, and 85.7%, 84.2%, 68.6% and 87.9% for F = 4. Performance of Fibroscan was higher than seven laboratory tests, for which AUROCs ranged from 0.66 to 0.77 (F > or = 1), from 0.54 to 0.82 (F > or = 2), from 0.43 to 0.88 (F > or = 3) and from 0.56 to 0.89 (F = 4), with significant difference only vs. APRI (P < 0.001) and Hepascore (P = 0.04). Combining Fibroscan with each tests did not improve performance.

CONCLUSIONS

Fibroscan is effective to assess liver fibrosis in alcoholic patients. Instant screening of liver fibrosis in heavy drinkers is feasible without liver biopsy.

Self-structuring in spatial evolutionary ecology

Spatial self-structuring has been a focus of recent interest among evolutionary ecologists. We review recent developments in the study of the interplay between spatial self-structuring and evolution. We first discuss the relative merits of the various theoretical approaches to spatial modelling in ecology. Second, we synthesize the main theoretical studies of the evolution of cooperation in spatially structured populations. We show that population viscosity is generally beneficial to cooperation, because cooperators can reap additional benefits from being clustered. A similar mechanism can explain the evolution of honest communication and of reduced virulence in host-parasite interactions. We also discuss some recent innovative empirical results that test these theories. Third, we show the relevance of these results to the general field of evolutionary ecology. An important conclusion is that kin selection is the main process that drives evolution of cooperation in viscous populations. Many results of kin selection theory can be recovered as emergent properties of spatial ecological dynamics. We discuss the implications of these results for the study of multilevel selection and evolutionary transitions. We conclude by sketching some perspectives for future research, with a particular emphasis on the topics of evolutionary branching, criticality, spatial fluctuations and experimental tests of theoretical predictions. Space is the place - Sun Ra.

The evolution of parasite manipulation of host dispersal

We investigate the evolution of manipulation of host dispersal behaviour by parasites using spatially explicit individual-based simulations. We find that when dispersal is local, parasites always gain from increasing their hosts' dispersal rate, although the evolutionary outcome is determined by the costs-to-benefits ratio. However, when dispersal can be non-local, we show that parasites investing in an intermediate dispersal distance of their hosts are favoured even when the manipulation is not costly, due to the intrinsic spatial dynamics of the host-parasite interaction. Our analysis highlights the crucial importance of ecological spatial dynamics in evolutionary processes and reveals the theoretical possibility that parasites could manipulate their hosts' dispersal.

An extension to the metabolic control theory taking into account correlations between enzyme concentrations

The classical metabolic control theory [Kacser, H. & Burns, J.A. (1973) Symp. Soc. Exp. Biol.27, 65-104; Heinrich, R. & Rapoport, T. (1974) Eur. J. Biochem.42, 89-95.] does not take into account experimental evidence for correlations between enzyme concentrations in the cell. We investigated the implications of two causes of linear correlations: competition between enzymes, which is a mere physical adaptation of the cell to the limitation of resources and space, and regulatory correlations, which result from the existence of regulatory networks. These correlations generate redistribution of enzyme concentrations when the concentration of an enzyme varies; this may dramatically alter the flux and metabolite concentration curves. In particular, negative correlations cause the flux to have a maximum value for a defined distribution of enzyme concentrations. Redistribution coefficients of enzyme concentrations allowed us to calculate the 'combined response coefficient' that quantifies the response of flux or metabolite concentration to a perturbation of enzyme concentration.