Reservoir population ecology, viral evolution and the risk of emerging infectious disease

The ecology and life history of wild animals influences their potential to harbour infectious disease. This observation has motivated studies identifying empirical relationships between traits of wild animals and historical patterns of spillover and emergence into humans. Although these studies have identified compelling broad-scale patterns, they are generally agnostic with respect to underlying mechanisms. Here, we develop mathematical models that couple reservoir population ecology with viral epidemiology and evolution to clarify existing verbal arguments and pinpoint the conditions that favour spillover and emergence. Our results support the idea that average lifespan influences the likelihood of an animal serving as a reservoir for human infectious disease. At the same time, however, our results show that the magnitude of this effect is sensitive to the rate of viral mutation. Our results also demonstrate that viral pathogens causing persistent infections or a transient immune response within the reservoir are more likely to fuel emergence. Genetically explicit stochastic simulations enrich these mathematical results by identifying relationships between the genetic basis of transmission and the risk of spillover and emergence. Together, our results clarify the scope of applicability for existing hypotheses and refine our understanding of emergence risk.

Phenotypic and functional variation in venom and venom resistance of two sympatric rattlesnakes and their prey

Predator-prey interactions often lead to the coevolution of adaptations associated with avoiding predation and, for predators, overcoming those defences. Antagonistic coevolutionary relationships are often not simple interactions between a single predator and prey but rather a complex web of interactions between multiple coexisting species. Coevolution between venomous rattlesnakes and small mammals has led to physiological venom resistance in several mammalian taxa. In general, viperid venoms contain large quantities of snake venom metalloproteinase toxins (SVMPs), which are inactivated by SVMP inhibitors expressed in resistant mammals. We explored variation in venom chemistry, SVMP expression, and SVMP resistance across four co-distributed species (California Ground Squirrels, Bryant's Woodrats, Southern Pacific Rattlesnakes, and Red Diamond Rattlesnakes) collected from four different populations in Southern California. Our aim was to understand phenotypic and functional variation in venom and venom resistance in order to compare coevolutionary dynamics of a system involving two sympatric predator-prey pairs to past studies that have focused on single pairs. Proteomic analysis of venoms indicated that these rattlesnakes express different phenotypes when in sympatry, with Red Diamonds expressing more typical viperid venom (with a diversity of SVMPs) and Southern Pacifics expressing a more atypical venom with a broader range of non-enzymatic toxins. We also found that although blood sera from both mammals were generally able to inhibit SVMPs from both rattlesnake species, inhibition depended strongly on the snake population, with snakes from one geographic site expressing SVMPs to which few mammals were resistant. Additionally, we found that Red Diamond venom, rather than woodrat resistance, was locally adapted. Our findings highlight the complexity of coevolutionary relationships between multiple predators and prey that exhibit similar offensive and defensive strategies in sympatry.

Population genetics and host specificity of Varroa destructor mites infesting eastern and western honeybees

In a globalized world, parasites are often brought in contact with new potential hosts. When parasites successfully shift host, severe diseases can emerge at a large cost to society. However, the evolutionary processes leading to successful shifts are rarely understood, hindering risk assessment, prevention, or mitigation of their effects. Here, we screened populations of Varroa destructor, an ectoparasitic mite of the honeybee genus Apis, to investigate their genetic structure and reproductive potential on new and original hosts. From the patterns identified, we deduce the factors that influenced the macro- and microevolutionary processes that led to the structure observed. Among the mite variants identified, we found two genetically similar populations that differed in their reproductive abilities and thus in their host specificity. These lineages could interbreed, which represents a threat due to the possible increased virulence of the parasite on its original host. However, interbreeding was unidirectional from the host-shifted to the nonshifted native mites and could thus lead to speciation of the former. The results improve our understanding of the processes affecting the population structure and evolution of this economically important mite genus and suggest that introgression between shifted and nonshifted lineages may endanger the original host.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10340-020-01322-7.

Host and Parasite Evolution in a Tangled Bank

Most hosts and parasites exist in diverse communities wherein they interact with other species, spanning the parasite-mutualist continuum. These additional interactions have the potential to impose selection on hosts and parasites and influence the patterns and processes of their evolution. Yet, host-parasite interactions are almost exclusively studied in species pairs. A wave of new research has incorporated a multispecies community context, showing that additional ecological interactions can alter components of host and parasite fitness, as well as interaction specificity and virulence. Here, we synthesize these findings to assess the effects of increased species diversity on the patterns and processes of host and parasite evolution. We argue that our understanding of host-parasite interactions would benefit from a richer biotic perspective.

Epidemiological and Evolutionary Outcomes in Gene-for-Gene and Matching Allele Models

Gene-for-gene (GFG) and matching-allele (MA) models are qualitatively different paradigms for describing the outcome of genetic interactions between hosts and pathogens. The GFG paradigm was largely built on the foundations of Flor's early work on the flax-flax rust interaction and is based on the concept of genetic recognition leading to incompatible disease outcomes, typical of host immune recognition. In contrast, the MA model is based on the assumption that genetic recognition leads to compatible interactions, which can result when pathogens require specific host factors to cause infection. Results from classical MA and GFG models have led to important predictions regarding various coevolutionary phenomena, including the role of fitness costs associated with resistance and infectivity, the distribution of resistance genes in wild populations, patterns of local adaptation and the evolution and maintenance of sexual reproduction. Empirical evidence (which we review briefly here), particularly from recent molecular advances in understanding of the mechanisms that determine the outcome of host-pathogen encounters, suggests considerable variation in specific details of the functioning of interactions between hosts and pathogens, which may contain elements of both models. In this regard, GFG and MA scenarios likely represent endpoints of a continuum of potentially more complex interactions that occur in nature. Increasingly, this has been recognized in theoretical studies of coevolutionary processes in plant host-pathogen and animal host-parasite associations (e.g., departures from strict GFG/MA assumptions, diploid genetics, multi-step infection processes). However, few studies have explored how different genetic assumptions about host resistance and pathogen infectivity might impact on disease epidemiology or pathogen persistence within and among populations. Here, we use spatially explicit simulations of the basic MA and GFG scenarios to highlight qualitative differences between these scenarios with regard to patterns of disease and impacts on host demography. Given that such impacts drive evolutionary trajectories, future theoretical advances that aim to capture more complex genetic scenarios should explicitly address the interaction between epidemiology and different models of host-pathogen interaction genetics.

Multiple host shifts by the emerging honeybee parasite, Varroa jacobsoni

Host shifts are a key mechanism of parasite evolution and responsible for the emergence of many economically important pathogens. Varroa destructor has been a major factor in global honeybee (Apis mellifera) declines since shifting hosts from the Asian honeybee (Apis cerana) > 50 years ago. Until recently, only two haplotypes of V. destructor (Korea and Japan) had successfully host shifted to A. mellifera. In 2008, the sister species V. jacobsoni was found for the first time parasitizing A. mellifera in Papua New Guinea (PNG). This recent host shift presents a serious threat to world apiculture but also provides the opportunity to examine host shifting in this system. We used 12 microsatellites to compare genetic variation of V. jacobsoni on A. mellifera in PNG with mites on A. cerana in both PNG and surrounding regions. We identified two distinct lineages of V. jacobsoni reproducing on A. mellifera in PNG. Our analysis indicated independent host shift events have occurred through small numbers of mites shifting from local A. cerana populations. Additional lineages were found in the neighbouring Papua and Solomon Islands that had partially host shifted to A. mellifera, that is producing immature offspring on drone brood only. These mites were likely in transition to full colonization of A. mellifera. Significant population structure between mites on the different hosts suggested host shifted V. jacobsoni populations may not still reproduce on A. cerana, although limited gene flow may exist. Our studies provide further insight into parasite host shift evolution and help characterize this new Varroa mite threat to A. mellifera worldwide.

Higher resources decrease fluctuating selection during host-parasite coevolution

We still know very little about how the environment influences coevolutionary dynamics. Here, we investigated both theoretically and empirically how nutrient availability affects the relative extent of escalation of resistance and infectivity (arms race dynamic; ARD) and fluctuating selection (fluctuating selection dynamic; FSD) in experimentally coevolving populations of bacteria and viruses. By comparing interactions between clones of bacteria and viruses both within- and between-time points, we show that increasing nutrient availability resulted in coevolution shifting from FSD, with fluctuations in average infectivity and resistance ranges over time, to ARD. Our model shows that range fluctuations with lower nutrient availability can be explained both by elevated costs of resistance (a direct effect of nutrient availability), and reduced benefits of resistance when population sizes of hosts and parasites are lower (an indirect effect). Nutrient availability can therefore predictably and generally affect qualitative coevolutionary dynamics by both direct and indirect (mediated through ecological feedbacks) effects on costs of resistance.

Effects of epistasis on infectivity range during host-parasite coevolution

Understanding how parasites adapt to changes in host resistance is crucial to evolutionary epidemiology. Experimental studies have demonstrated that parasites are more capable of adapting to gradual, rather than sudden changes in host phenotype, as the latter may require multiple mutations that are unlikely to arise simultaneously. A key, but as yet unexplored factor is precisely how interactions between mutations (epistasis) affect parasite evolution. Here, we investigate this phenomenon in the context of infectivity range, where parasites may experience selection to infect broader sets of genotypes. When epistasis is strongly positive, we find that parasites are unlikely to evolve broader infectivity ranges if hosts exhibit sudden, rather than gradual changes in phenotype, in close agreement with empirical observations. This is due to a low probability of fixing multiple mutations that individually confer no immediate advantage. When epistasis is weaker, parasites are more likely to evolve broader infectivity ranges if hosts make sudden changes in phenotype, which can be explained by a balance between mutation supply and selection. Thus, we demonstrate that both the rate of phenotypic change in hosts and the form of epistasis between mutations in parasites are crucial in shaping the evolution of infectivity range.

Connecting functional and statistical definitions of genotype by genotype interactions in coevolutionary studies

Predicting how species interactions evolve requires that we understand the mechanistic basis of coevolution, and thus the functional genotype-by-genotype interactions (G × G) that drive reciprocal natural selection. Theory on host-parasite coevolution provides testable hypotheses for empiricists, but depends upon models of functional G × G that remain loosely tethered to the molecular details of any particular system. In practice, reciprocal cross-infection studies are often used to partition the variation in infection or fitness in a population that is attributable to G × G (statistical G × G). Here we use simulations to demonstrate that within-population statistical G × G likely tells us little about the existence of coevolution, its strength, or the genetic basis of functional G × G. Combined with studies of multiple populations or points in time, mapping and molecular techniques can bridge the gap between natural variation and mechanistic models of coevolution, while model-based statistics can formally confront coevolutionary models with cross-infection data. Together these approaches provide a robust framework for inferring the infection genetics underlying statistical G × G, helping unravel the genetic basis of coevolution.

Do-or-die life cycles and diverse post-infection resistance mechanisms limit the evolution of parasite host ranges

In light of the dynamic nature of parasite host ranges and documented potential for rapid host shifts, the observed high host specificity of most parasites remains an ecological paradox. Different variants of host-use trade-offs have become a mainstay of theoretical explanations of the prevalence of host specialism, but empirical evidence for such trade-offs is rare. We propose an alternative theory based on basic features of the parasite life cycle: host selection and subsequent intrahost replication. We introduce a new concept of effective burst size that accounts for the fact that successful host selection does not guarantee intrahost replication. Our theory makes a general prediction that a parasite will expand its host range if its effective burst size is positive. An in silico model of bacteria-phage coevolution verifies our predictions and demonstrates that the tendency for relatively narrow host ranges in parasites can be explained even in the absence of trade-offs.