Reservoir host immunology and life history shape virulence evolution in zoonotic viruses.

The management of future pandemic risk requires a better understanding of the mechanisms that determine the virulence of emerging zoonotic viruses. Meta-analyses suggest that the virulence of emerging zoonoses is correlated with but not completely predictable from reservoir host phylogeny, indicating that specific characteristics of reservoir host immunology and life history may drive the evolution of viral traits responsible for cross-species virulence. In particular, bats host viruses that cause higher case fatality rates upon spillover to humans than those derived from any other mammal, a phenomenon that cannot be explained by phylogenetic distance alone. In order to disentangle the fundamental drivers of these patterns, we develop a nested modeling framework that highlights mechanisms that underpin the evolution of viral traits in reservoir hosts that cause virulence following cross-species emergence. We apply this framework to generate virulence predictions for viral zoonoses derived from diverse mammalian reservoirs, recapturing trends in virus-induced human mortality rates reported in the literature. Notably, our work offers a mechanistic hypothesis to explain the extreme virulence of bat-borne zoonoses and, more generally, demonstrates how key differences in reservoir host longevity, viral tolerance, and constitutive immunity impact the evolution of viral traits that cause virulence following spillover to humans. Our theoretical framework offers a series of testable questions and predictions designed to stimulate future work comparing cross-species virulence evolution in zoonotic viruses derived from diverse mammalian hosts.

Bats host the most virulent-but not the most dangerous-zoonotic viruses.

SignificanceThe clear need to mitigate zoonotic risk has fueled increased viral discovery in specific reservoir host taxa. We show that a combination of viral and reservoir traits can predict zoonotic virus virulence and transmissibility in humans, supporting the hypothesis that bats harbor exceptionally virulent zoonoses. However, pandemic prevention requires thinking beyond zoonotic capacity, virulence, and transmissibility to consider collective "burden" on human health. For this, viral discovery targeting specific reservoirs may be inefficient as death burden correlates with viral, not reservoir, traits, and depends on context-specific epidemiological dynamics across and beyond the human-animal interface. These findings suggest that longitudinal studies of viral dynamics in reservoir and spillover host populations may offer the most effective strategy for mitigating zoonotic risk.

The evolutionary dynamics of hyperparasites.

Evolutionary theory has typically focused on pairwise interactions, such as those between hosts and parasites, with relatively little work having been carried out on more complex interactions including hyperparasites: parasites of parasites. Hyperparasites are common in nature, with the chestnut blight fungus virus CHV-1 a well-known natural example, but also notably include the phages of important human bacterial diseases. We build a general modeling framework for the evolution of hyperparasites that highlights the central role that the ability of a hyperparasite to be transmitted with its parasite plays in their evolution. A key result is that hyperparasites which transmit with their parasite hosts (hitchhike) will be selected for lower virulence, trending towards hypermutualism or hypercommensalism. We examine the impact on the evolution of hyperparasite systems of a wide range of host and parasite traits showing, for example, that high parasite virulence selects for higher hyperparasite virulence resulting in reductions in parasite virulence when hyperparasitized. Furthermore, we show that acute parasite infection will also select for increased hyperparasite virulence. Our results have implications for hyperparasite research, both as biocontrol agents and for their role in shaping community ecology and evolution and moreover emphasize the importance of understanding evolution in the context of multitrophic interactions.

Boosting can explain patterns of fluctuations of ratios of inapparent to symptomatic dengue virus infections.

Dengue is the most prevalent arboviral disease worldwide, and the four dengue virus (DENV) serotypes circulate endemically in many tropical and subtropical regions. Numerous studies have shown that the majority of DENV infections are inapparent, and that the ratio of inapparent to symptomatic infections (I/S) fluctuates substantially year-to-year. For example, in the ongoing Pediatric Dengue Cohort Study (PDCS) in Nicaragua, which was established in 2004, the I/S ratio has varied from 16.5:1 in 2006-2007 to 1.2:1 in 2009-2010. However, the mechanisms explaining these large fluctuations are not well understood. We hypothesized that in dengue-endemic areas, frequent boosting (i.e., exposures to DENV that do not lead to extensive viremia and result in a less than fourfold rise in antibody titers) of the immune response can be protective against symptomatic disease, and this can explain fluctuating I/S ratios. We formulate mechanistic epidemiologic models to examine the epidemiologic effects of protective homologous and heterologous boosting of the antibody response in preventing subsequent symptomatic DENV infection. We show that models that include frequent boosts that protect against symptomatic disease can recover the fluctuations in the I/S ratio that we observe, whereas a classic model without boosting cannot. Furthermore, we show that a boosting model can recover the inverse relationship between the number of symptomatic cases and the I/S ratio observed in the PDCS. These results highlight the importance of robust dengue control efforts, as intermediate dengue control may have the potential to decrease the protective effects of boosting.

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.

Epidemiological impacts of post-infection mortality.

Infectious diseases may cause some long-term damage to their host, leading to elevated mortality even after recovery. Mortality due to complications from so-called 'long COVID' is a stark illustration of this potential, but the impacts of such post-infection mortality (PIM) on epidemic dynamics are not known. Using an epidemiological model that incorporates PIM, we examine the importance of this effect. We find that in contrast to mortality during infection, PIM can induce epidemic cycling. The effect is due to interference between elevated mortality and reinfection through the previously infected susceptible pool. In particular, robust immunity (via decreased susceptibility to reinfection) reduces the likelihood of cycling; on the other hand, disease-induced mortality can interact with weak PIM to generate periodicity. In the absence of PIM, we prove that the unique endemic equilibrium is stable and therefore our key result is that PIM is an overlooked phenomenon that is likely to be destabilizing. Overall, given potentially widespread effects, our findings highlight the importance of characterizing heterogeneity in susceptibility (via both PIM and robustness of host immunity) for accurate epidemiological predictions. In particular, for diseases without robust immunity, such as SARS-CoV-2, PIM may underlie complex epidemiological dynamics especially in the context of seasonal forcing.

Multimorph Eco-Evolutionary Dynamics in Structured Populations.

AbstractOur understanding of the evolution of quantitative traits in nature is still limited by the challenge of including realistic trait distributions in the context of frequency-dependent selection and ecological feedbacks. We extend to class-structured populations a recently introduced "oligomorphic approximation," which bridges the gap between adaptive dynamics and quantitative genetics approaches and allows for the joint description of the dynamics of ecological variables and of the moments of multimodal trait distributions. Our theoretical framework allows us to analyze the dynamics of populations composed of several morphs and structured into distinct classes (e.g., age, size, habitats, infection status, and species). We also introduce a new approximation to simplify the eco-evolutionary dynamics using reproductive values. We illustrate the effectiveness of this approach by applying it to the important conceptual case of two-habitat migration-selection models. In particular, we show that our approach allows us to predict both the long-term evolutionary end points and the short-term transient dynamics of the eco-evolutionary process, including fast evolution regimes. We discuss the theoretical and practical implications of our results and sketch perspectives for future work.

The diversity-generating benefits of a prokaryotic adaptive immune system.

Prokaryotic CRISPR-Cas adaptive immune systems insert spacers derived from viruses and other parasitic DNA elements into CRISPR loci to provide sequence-specific immunity. This frequently results in high within-population spacer diversity, but it is unclear if and why this is important. Here we show that, as a result of this spacer diversity, viruses can no longer evolve to overcome CRISPR-Cas by point mutation, which results in rapid virus extinction. This effect arises from synergy between spacer diversity and the high specificity of infection, which greatly increases overall population resistance. We propose that the resulting short-lived nature of CRISPR-dependent bacteria-virus coevolution has provided strong selection for the evolution of sophisticated virus-encoded anti-CRISPR mechanisms.

Experimental evidence that local interactions select against selfish behaviour.

How social behaviours evolve remains one of the most debated questions in evolutionary biology. An important theoretical prediction is that when organisms interact locally due to limited dispersal or strong social ties, the population structure that emerges may favour cooperation over antagonism. We carry out an experimental test of this theory by directly manipulating population spatial structure in an insect laboratory model system and measuring the impact on the evolution of the extreme selfish behaviour of cannibalism. We show that, as predicted by the theory, Indian meal moth larvae that evolved in environments with more limited dispersal are selected for lower rates of cannibalism. This is important because it demonstrates that local interactions select against selfish behaviour. Therefore, the ubiquitous variation in population structure that we see in nature is a simple mechanism that can help to explain the variation in selfish and cooperative behaviours that we see in nature.

The central role of host reproduction in determining the evolution of virulence in spatially structured populations.

A substantial body of work has shown that local transmission selects for less acute, 'prudent' parasites that have lower virulence and transmission rates. This is because parasite strains with higher transmission rates 'self-shade' due to a combination of genetic correlations (self: clustered related parasite strains compete for susceptible individuals) and ecological correlations (shade: infected individuals clustering and blocking transmission). However, the interaction of ecological and genetic correlations alongside higher order ecological effects such as patch extinctions means that spatial evolutionary effects can be nuanced; theory has predicted that a relatively small proportion of local infection can select for highest virulence, such that there is a humped relationship between the degree of local infection and the harm that parasites are selected to cause. Here, we examine the separate roles of the interaction scales of reproduction and infection in the context of different degrees of pathogenic castration in determining virulence evolution outcomes. Our key result is that, as long as there is significant reproduction from infected individuals, local infection always selects for lower virulence, and that the prediction that a small proportion of local infection can select for higher virulence only occurs for highly castrating pathogens. The results emphasize the importance of demography for evolutionary outcomes in spatially structured populations, but also show that the core prediction that parasites are prudent in space is reasonable for the vast majority of host-parasite interactions and mixing patterns in nature.

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.

Contrasting impacts of a novel specialist vector on multihost viral pathogen epidemiology in wild and managed bees.

Typically, pathogens infect multiple host species. Such multihost pathogens can show considerable variation in their degree of infection and transmission specificity, which has important implications for potential disease emergence. Transmission of multihost pathogens can be driven by key host species and changes in such transmission networks can lead to disease emergence. We study two viruses that show contrasting patterns of prevalence and specificity in managed honeybees and wild bumblebees, black queen cell virus (BQCV) and slow bee paralysis virus (SBPV), in the context of the novel transmission route provided by the virus-vectoring Varroa destructor. Our key result is that viral communities and RNA virus genetic variation are structured by location, not host species or V. destructor presence. Interspecific transmission is pervasive with the same viral variants circulating between pollinator hosts in each location; yet, we found virus-specific host differences in prevalence and viral load. Importantly, V. destructor presence increases the prevalence in honeybees and, indirectly, in wild bumblebees, but in contrast to its impact on deformed wing virus (DWV), BQCV and SBPV viral loads are not increased by Varroa presence, and do not show genetic evidence of recent emergence. Effective control of Varroa in managed honeybee colonies is necessary to mitigate further disease emergence, and alleviate disease pressure on our vital wild bee populations. More generally, our results highlight the over-riding importance of geographical location to the epidemiological outcome despite the complexity of multihost-parasite interactions.

Resource quality determines the evolution of resistance and its genetic basis.

Parasites impose strong selection on their hosts, but the level of any evolved resistance may be constrained by the availability of resources. However, studies identifying the genomic basis of such resource-mediated selection are rare, particularly in nonmodel organisms. Here, we investigated the role of nutrition in the evolution of resistance to a DNA virus (PiGV), and any associated trade-offs in a lepidopteran pest species (Plodia interpunctella). Through selection experiments and whole-genome resequencing, we identify genetic markers of resistance that vary between the nutritional environments during selection. We do not find consistent evolution of resistance in the presence of virus but rather see substantial variation among replicate populations. Resistance in a low-nutrition environment is negatively correlated with growth rate, consistent with an established trade-off between immunity and development, but this relationship is highly context dependent. Whole-genome resequencing of the host shows that resistance mechanisms are likely to be highly polygenic and although the underlying genetic architecture may differ between high and low-nutrition environments, similar mechanisms are commonly used. As a whole, our results emphasize the importance of the resource environment on influencing the evolution of resistance.

The target of selection matters: An established resistance-development-time negative genetic trade-off is not found when selecting on development time.

Trade-offs are fundamental to evolutionary outcomes and play a central role in eco-evolutionary theory. They are often examined by experimentally selecting on one life-history trait and looking for negative correlations in other traits. For example, populations of the moth Plodia interpunctella selected to resist viral infection show a life-history cost with longer development times. However, we rarely examine whether the detection of such negative genetic correlations depends on the trait on which we select. Here, we examine a well-characterized negative genotypic trade-off between development time and resistance to viral infection in the moth Plodia interpunctella and test whether selection on a phenotype known to be a cost of resistance (longer development time) leads to the predicted correlated increase in resistance. If there is tight pleiotropic relationship between genes that determine development time and resistance underpinning this trade-off, we might expect increased resistance when we select on longer development time. However, we show that selecting for longer development time in this system selects for reduced resistance when compared to selection for shorter development time. This shows how phenotypes typically characterized by a trade-off can deviate from that trade-off relationship, and suggests little genetic linkage between the genes governing viral resistance and those that determine response to selection on the key life-history trait. Our results are important for both selection strategies in applied biological systems and for evolutionary modelling of host-parasite interactions.

A mathematical model shows macrophages delay Staphylococcus aureus replication, but limitations in microbicidal capacity restrict bacterial clearance.

S. aureus is a leading cause of bacterial infection. Macrophages, the first line of defence in the human immune response, phagocytose and kill S. aureus but the pathogen can evade these responses. Therefore, the exact role of macrophages is incompletely defined. We develop a mathematical model of macrophage - S. aureus dynamics, built on recent experimental data. We demonstrate that, while macrophages may not clear infection, they significantly delay its growth and potentially buy time for recruitment of further cells. We find that macrophage killing is a major obstacle to controlling infection and ingestion capacity also limits the response. We find bistability such that the infection can be limited at low doses. Our combination of experimental data, mathematical analysis and model fitting provide important insights in to the early stages of S. aureus infections, showing macrophages play an important role limiting bacterial replication but can be overwhelmed with large inocula.

The Critical Role of Infectious Disease in Compensatory Population Growth in Response to Culling.

Despite the ubiquity of disease in nature, the role that disease dynamics play in the compensatory growth response to harvesting has been ignored. We use a mathematical approach to show that harvesting can lead to compensatory growth due to a release from disease-induced mortality. Our findings imply that culling in systems that harbor virulent parasites can reduce disease prevalence and increase population density. Our models predict that this compensation occurs for a broad range of infectious disease characteristics unless the disease induces long-lasting immunity in hosts. Our key insight is that a population can be regulated at a similar density by disease or at reduced prevalence by a combination of culling and disease. We illustrate our predictions with a system-specific model representing wild boar tuberculosis infection, parameterized for central Spain, and find significant compensation to culling. Given that few wildlife diseases are likely to induce long-lived immunity, populations with virulent diseases may often be resilient to harvesting.

Understanding the role of eco-evolutionary feedbacks in host-parasite coevolution.

It is widely recognised that eco-evolutionary feedbacks can have important implications for evolution. However, many models of host-parasite coevolution omit eco-evolutionary feedbacks for the sake of simplicity, typically by assuming the population sizes of both species are constant. It is often difficult to determine whether the results of these models are qualitatively robust if eco-evolutionary feedbacks are included. Here, by allowing interspecific encounter probabilities to depend on population densities without otherwise varying the structure of the models, we provide a simple method that can test whether eco-evolutionary feedbacks per se affect evolutionary outcomes. Applying this approach to explicit genetic and quantitative trait models from the literature, our framework shows that qualitative changes to the outcome can be directly attributable to eco-evolutionary feedbacks. For example, shifting the dynamics between stable monomorphism or polymorphism and cycling, as well as changing the nature of the cycles. Our approach, which can be readily applied to many different models of host-parasite coevolution, offers a straightforward method for testing whether eco-evolutionary feedbacks qualitatively change coevolutionary outcomes.

Contact networks structured by sex underpin sex-specific epidemiology of infection.

Contact networks are fundamental to the transmission of infection and host sex often affects the acquisition and progression of infection. However, the epidemiological impacts of sex-related variation in animal contact networks have rarely been investigated. We test the hypothesis that sex-biases in infection are related to variation in multilayer contact networks structured by sex in a population of European badgers Meles meles naturally infected with Mycobacterium bovis. Our key results are that male-male and between-sex networks are structured at broader spatial scales than female-female networks and that in male-male and between-sex contact networks, but not female-female networks, there is a significant relationship between infection and contacts with individuals in other groups. These sex differences in social behaviour may underpin male-biased acquisition of infection and may result in males being responsible for more between-group transmission. This highlights the importance of sex-related variation in host behaviour when managing animal diseases.

The evolution of constitutive and induced defences to infectious disease.

In response to infectious disease, hosts typically mount both constitutive and induced defences. Constitutive defence prevents infection in the first place, while induced defence typically shortens the infectious period. The two routes to defence, therefore, have very different implications not only to individuals but also to the epidemiology of the disease. Moreover, the costs of constitutive defences are likely to be paid even in the absence of disease, while induced defences are likely to incur the most substantial costs when they are used in response to infection. We examine theoretically the evolutionary implications of these fundamental differences. A key result is that high virulence in the parasite typically selects for higher induced defences even if they result in immunopathology leading to very high disease mortality. Disease impacts on fecundity are critical to the relative investment in constitutive and induced defence with important differences found when parasites castrate their hosts. The trade-off between constitutive and induced defence has been cited as a cause of the diversity in defence, but we show that the trade-off alone is unlikely to lead to diversity. Our models provide a framework to examine relative investment in different defence components both experimentally and in the field.

The Need for Evolutionarily Rational Disease Interventions: Vaccination Can Select for Higher Virulence.

There is little doubt evolution has played a major role in preventing the control of infectious disease through antibiotic and insecticide resistance, but recent theory suggests disease interventions such as vaccination may lead to evolution of more harmful parasites. A new study published in PLOS Biology by Andrew Read and colleagues shows empirically that vaccination against Marek's disease has favored higher virulence; without intervention, the birds die too quickly for any transmission to occur, but vaccinated hosts can both stay alive longer and shed the virus. This is an elegant empirical demonstration of how evolutionary theory can predict potentially dangerous responses of infectious disease to human interventions.