Elisa Visher

Host heterogeneity and spatial population structure each influence parasite evolution and may interact when space structures contacts between host types. Here, we experimentally evolve granulosis virus in microcosms of its natural Plodia interpunctella (Indian meal moth) host that differ in both spatial structure and host genetic diversity. We control spatial structure by manipulating the viscosity of the food that the larvae live within and host genetic diversity by adding larvae from either one or two non-evolving inbred lines to opposite microcosm ends. We preserve spatial structure across passages and assay virus from different positions within the microcosm on both host genotypes. We find that the lower contact rates between host genotypes resulting from spatial structure can lead to the evolution of locally specialized virus, even when the host population is genetically diverse overall. We also find that spatial structure changes how viruses specialize: viruses evolved in well-mixed environments had lower exploitation rates (proportion infected x virions) on the host they evolved with, while those in spatially structured environments exhibited higher exploitation of familiar hosts. These results demonstrate that spatial structure and host heterogeneity interact to shape pathogen specialization and that the evolutionary consequences of host diversity depend on population structure.

Host heterogeneity and spatial population structure each influence parasite evolution but may also interact because space structures contacts between host types. Here, we experimentally evolve granulosis virus in microcosms of its Plodia interpunctella (Indian meal moth) host that differ in both spatial structure and host genetic diversity. We control spatial structure by manipulating the viscosity of the food that the larvae live within and host genetic diversity by adding larvae from either a single or two inbred lines to opposite ends of the microcosm. We preserve spatial structure across passages and assay virus from different positions within the microcosm on both host genotypes. We find that the lower contact rates between host genotypes resulting from spatial structure can lead to the evolution of locally specialized virus, even when the host population is genetically diverse overall. We also find that spatial structure changes how viruses specialize: viruses evolved in well-mixed environments had lower exploitation of familiar hosts, while those in spatially structured environments exhibited higher exploitation of familiar hosts. These results demonstrate that spatial structure and host heterogeneity interact to shape pathogen specialization and that the evolutionary consequences of host diversity depends on the population structure.

Hosts can often evolve resistance to parasites (and other stressors), but such resistance is generally thought to be constrained by trade-offs with other traits. These trade-offs determine the host’s optimal resistance strategy and whether resistance cycles, diversifies, and/or is maintained in the absence of parasite. However, trade-offs are often inconsistently measured across experiments and can depend on environmental conditions. Here, we extend a selection experiment evolving resistance to viral infection under variable resource quality in the Plodia interpunctella model system to explore the evolutionary conditions leading to an incongruent earlier measurement of costless resistance. We find that environmental resource quality, historical contingency, and the time scale of selection all affect trade-offs in our long-term selection experiment. Specifically, populations selected for resistance with the dual stressor of low resource quality are slowed, but not prevented, from evolving resistance. Second, variation in starting populations or early sampled adaptations led to contingency towards context-dependent resistance. Finally, some costs to resistance observed at early time points were compensated over longer evolutionary time scales. Our work therefore informs perspectives for the predictability of adaptation and how variation in specific evolutionary conditions can alter the evolutionary trajectories of a population towards costly or costless resistance strategies.

Niche breadth coevolution between biotic partners underpins theories of diversity and co-existence and influences patterns of disease emergence and transmission in host-parasite systems. Despite these broad implications, we still do not fully understand how the breadth of parasites' infectivity evolves, the nature of any associated costs, or the genetic basis of specialization. Here, we serially passage a granulosis virus on multiple inbred populations of its Plodia interpunctella host to explore the dynamics and outcomes of specialization. In particular, we collect time series of phenotypic and genetic data to explore the dynamics of host genotype specialization throughout the course of experimental evolution and examine two fitness components. We find that the Plodia interpunctella granulosis virus consistently evolves and increases in overall specialization, but that our two fitness components evolve independently such that lines can specialize in productivity or infectivity. Furthermore, we find that specialization in our experiment is a highly polygenic trait best explained by a combination of evolutionary mechanisms. These results are important for understanding the evolution of specialization in host-parasite interactions and its broader implications for co-existence, diversification, and infectious disease management.

Niche breadth coevolution between biotic partners underpins theories of diversity and co-existence and influences patterns of disease emergence and transmission in host-parasite systems. Despite these broad implications, we still do not fully understand how the breadth of parasites’ infectivity evolves, the nature of any associated costs, or the genetic basis of specialization. Here, we serially passage a granulosis virus on multiple inbred populations of its Plodia interpunctella host to explore the dynamics and outcomes of specialization. In particular, we collect time series of phenotypic and genetic data to explore the dynamics of host genotype specialization throughout the course of experimental evolution and examine two fitness components. We find that the Plodia interpunctella granulosis virus consistently evolves increases in overall specialization, but that our two fitness components evolve independently such that lines specialize in either productivity or infectivity. Furthermore, we find that specialization in our experiment is a highly polygenic trait best explained by a combination of evolutionary mechanisms including conditionally positive fitness asymmetries and mutation accumulation. These results are important for understanding the evolution of specialization in host-parasite interactions and its broader implications for co-existence, diversification, and infectious disease management.

There is increasing interest in the role that evolution may play in current and future pandemics, but there is often also considerable confusion about the actual evolutionary predictions. This may be, in part, due to a historical separation of evolutionary and medical fields, but there is a large, somewhat nuanced body of evidence-supported theory on the evolution of infectious disease. In this review, we synthesize this evolutionary theory in order to provide a framework for clearer understanding of the key principles. Specifically, we discuss the selection acting on zoonotic pathogens' transmission rates and virulence at spillover and during emergence. We explain how the direction and strength of selection during epidemics of emerging zoonotic disease can be understood by a three Ts framework: trade-offs, transmission, and time scales. Virulence and transmission rate may trade-off, but transmission rate is likely to be favoured by selection early in emergence, particularly if maladapted zoonotic pathogens have ‘no-cost’ transmission rate improving mutations available to them. Additionally, the optimal virulence and transmission rates can shift with the time scale of the epidemic. Predicting pathogen evolution, therefore, depends on understanding both the trade-offs of transmission-improving mutations and the time scales of selection.

Identifying virus characteristics associated with the largest public health impacts on human populations is critical to informing zoonotic risk assessments and surveillance strategies. Efforts to assess “zoonotic risk” often use trait-based analyses to identify which viral and reservoir host groups are most likely to source zoonoses but have not fully addressed how and why the impacts of zoonotic viruses vary in terms of disease severity (‘virulence’), capacity to spread within human populations (‘transmissibility’), or total human mortality (‘death burden’). We analyzed trends in human case fatality rates, transmission capacities, and total death burdens across a comprehensive dataset of mammalian and avian zoonotic viruses. Bats harbor the most virulent zoonotic viruses even when compared to birds, which alongside bats, have been hypothesized to be “special” zoonotic reservoirs due to molecular adaptations that support the physiology of flight. Reservoir host groups more closely related to humans—in particular, Primates—harbor less virulent, but more highly transmissible viruses. Importantly, disproportionately high human death burden, arguably the most important metric of zoonotic risk, is not associated with any animal reservoir, including bats. Our data demonstrate that mechanisms driving death burdens are diverse and often contradict trait-based predictions. Ultimately, total human mortality is dependent on context-specific epidemiological dynamics, which are shaped by a combination of viral traits and conditions in the animal host population and across and beyond the human-animal interface. Understanding the conditions that predict high zoonotic burden in humans will require longitudinal studies of epidemiological dynamics in wildlife and human populations. Significance statement The 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.

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.

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.