Anna-Liisa Laine

Rapid genetic change underpins antagonistic coevolution in a natural host‐pathogen metapopulation

Antagonistic coevolution is a critical force driving the evolution of diversity, yet the selective processes underpinning reciprocal adaptive changes in nature are not well understood. Local adaptation studies demonstrate partner impacts on fitness and adaptive change, but do not directly expose genetic processes predicted by theory. Specifically, we have little knowledge of the relative importance of fluctuating selection vs. arms-race dynamics in maintaining polymorphism in natural systems where metapopulation processes predominate. We conducted cross-year epidemiological, infection and genetic studies of multiple wild host and pathogen populations in the Linum-Melampsora association. We observed asynchronous phenotypic fluctuations in resistance and infectivity among demes. Importantly, changes in allelic frequencies at pathogen infectivity loci, and in host recognition of these genetic variants, correlated with disease prevalence during natural epidemics. These data strongly support reciprocal coevolution maintaining balanced resistance and infectivity polymorphisms, and highlight the importance of characterising spatial and temporal dynamics in antagonistic interactions.

Spatial scale of local adaptation in a plant‐pathogen metapopulation

The rate and scale of gene flow can strongly affect patterns of local adaptation in host–parasite interactions. I used data on regional pathogen occurrence to infer the scale of pathogen dispersal and to identify pathogen metapopulations in the interaction between Plantago lanceolata and its specialist phytopathogen, Podosphaera plantaginis. Frequent extinctions and colonizations were recorded in the metapopulations, suggesting substantial gene flow at this spatial scale. The level of pathogen local adaptation was assessed in a laboratory inoculation experiment at three different scales: in sympatric host populations, in sympatric host metapopulations and in allopatric host metapopulations. I found evidence for adaptation to sympatric host populations, as well as evidence indicating that local adaptation may extend to the scale of the sympatric host metapopulation. There was also variation among the metapopulations in the degree of pathogen local adaptation. This may be explained by regional differences in the rate of migration.

Temperature‐mediated patterns of local adaptation in a natural plant–pathogen metapopulation

There have been numerous investigations of parasite local adaptation, a phenomenon important from the perspectives of both basic and applied evolutionary ecology. Recent work has demonstrated that temperature has striking effects on parasite performance by mediating trade-offs in parasite life history and through genotype x environment interactions. To test whether parasite local adaptation is mediated by temperature, I measured the performance of sympatric populations against allopatric populations of a fungal pathogen, Podosphaera plantaginis, on its host Plantago lanceolata, across a temperature gradient. I used data on parasite life history and epidemiology to derive fitness estimates to measure local adaptation. The results demonstrate unambiguously that trajectories of host-parasite co-evolution are tightly coupled with parasite adaptation to the abiotic habitat, as the strength, and even direction, of local adaptation varied with temperature. Patterns of local adaptation further depended on how parasite fitness was estimated, highlighting the importance of choosing relevant fitness measures in studies of local adaptation.

Role of coevolution in generating biological diversity: spatially divergent selection trajectories

The Geographic Mosaic Theory of Coevolution predicts that divergent coevolutionary selection produces genetic differentiation across populations. The 29 studies reviewed here support this hypothesis as they all report spatially diverged selection trajectories which have generated variable outcomes in the interaction traits among populations. This holds for both mutualistic interactions such as those between host plants and their root symbionts, or plants and their pollinators, as well as for antagonistic interactions such as plants and their pathogens or herbivores. Most often, it is the strength of selection that varies across landscapes. Variation may be generated by both the physical environment (namely temperature), and the local community--competitors, parasites, and alternative hosts--that intensify or dilute selection locally for a wide range of species interactions. At its extreme, selection trajectories may be reversed with an antagonistic interaction being commensalistic in some populations and mutualistic in yet others, depending on the local community context. Selection trajectories were found to diverge among continents, but also more locally among neighbouring populations and even within a single population. This result highlights the importance of coevolutionary selection generating biological diversity with far-reaching implications for both biodiversity conservation as well as applied biology.

Evolution of host resistance: looking for coevolutionary hotspots at small spatial scales.

Natural plant populations are often found to be extremely diverse in their resistance to pathogens. While the potential of pathogens in driving the evolution of resistance in hosts has been widely recognized, empirical evidence linking disease dynamics to host population genetic structure has remained scarce. Here I show that current coevolutionary selection for resistance can be divergent even on a very fine spatial scale. In a natural plant–pathogen metapopulation, disease occurrence patterns were highly aggregated over space and time within host populations. A laboratory inoculation experiment showed higher resistance within areas of the host populations where encounter rates with the pathogen have been high. Higher resistance to sympatric than to allopatric strains of the pathogen suggests that this change has taken place as a response to local selection. These results constitute evidence of adaptive microevolution of resistance resulting from disease epidemics in natural plant–pathogen associations, and highlight the importance of finding the relevant scale at which to address questions of current coevolutionary selection.

Variation in infectivity and aggressiveness in space and time in wild host–pathogen systems: causes and consequences

Variation in host resistance and in the ability of pathogens to infect and grow (i.e. pathogenicity) is important as it provides the raw material for antagonistic (co)evolution and therefore underlies risks of disease spread, disease evolution and host shifts. Moreover, the distribution of this variation in space and time may inform us about the mode of coevolutionary selection (arms race vs. fluctuating selection dynamics) and the relative roles of G × G interactions, gene flow, selection and genetic drift in shaping coevolutionary processes. Although variation in host resistance has recently been reviewed, little is known about overall patterns in the frequency and scale of variation in pathogenicity, particularly in natural systems. Using 48 studies from 30 distinct host–pathogen systems, this review demonstrates that variation in pathogenicity is ubiquitous across multiple spatial and temporal scales. Quantitative analysis of a subset of extensively studied plant–pathogen systems shows that the magnitude of within‐population variation in pathogenicity is large relative to among‐population variation and that the distribution of pathogenicity partly mirrors the distribution of host resistance. At least part of the variation in pathogenicity found at a given spatial scale is adaptive, as evidenced by studies that have examined local adaptation at scales ranging from single hosts through metapopulations to entire continents and – to a lesser extent – by comparisons of pathogenicity with neutral genetic variation. Together, these results support coevolutionary selection through fluctuating selection dynamics. We end by outlining several promising directions for future research.

Ecological and evolutionary effects of fragmentation on infectious disease dynamics

Many connections are not always bad for health Contrary to expectations, highly connected populations can experience less impact from infectious disease than isolated groups. What happens to pathogens in natural populations has been poorly studied, because they rarely cause devastating disease outbreaks. Thanks to a long-term study of an inconspicuous fungal-plant disease system, we have now gained some surprising insights. During a 12-year study, Jousimo et al. discovered that clustered and linked host-plant patches showed lower levels of fungal damage and higher fungal extinction rates than more distant patches (see the Perspective by Duffy). This phenomenon is explained by high gene flow and rapid evolution of host resistance within the connected patches. Populations of the modest weed Plantago, growing on the Åland Islands in the Baltic, were less than 10% infected by the Podosphaera mildew fungus in any given year, but infection turnover was high. These findings have broad implications for ecology, disease biology, conservation, and agriculture. Science, this issue p. 1289; see also p. 1229 Better connected plant hosts are better able to resist a fungal pathogen, probably because of higher gene flow. [Also see Perspective by Duffy] Ecological theory predicts that disease incidence increases with increasing density of host networks, yet evolutionary theory suggests that host resistance increases accordingly. To test the combined effects of ecological and evolutionary forces on host-pathogen systems, we analyzed the spatiotemporal dynamics of a plant (Plantago lanceolata)–fungal pathogen (Podosphaera plantaginis)relationship for 12 years in over 4000 host populations. Disease prevalence at the metapopulation level was low, with high annual pathogen extinction rates balanced by frequent (re-)colonizations. Highly connected host populations experienced less pathogen colonization and higher pathogen extinction rates than expected; a laboratory assay confirmed that this phenomenon was caused by higher levels of disease resistance in highly connected host populations.

Pathogen fitness components and genotypes differ in their sensitivity to nutrient and temperature variation in a wild plant–pathogen association

Understanding processes maintaining variation in pathogen life‐history stages affecting infectivity and reproduction is a key challenge in evolutionary ecology. Models of host–parasite coevolution are based on the assumption that genetic variation for host–parasite interactions is a significant cause of variation in infection, and that variation in environmental conditions does not overwhelm the genetic basis. However, surprisingly little is known about the stability of genotype–genotype interactions under variable environmental conditions. Here, using a naturally occurring plant–pathogen interaction, I tested whether the two distinct aspects of the infection process – infectivity and transmission potential – vary over realistic nutrient and temperature gradients. I show that the initial pathogen infectivity and host resistance responses are robust over the environmental gradients. However, for compatible responses there were striking differences in how different pathogen life‐history stages and host and pathogen genotypes responded to environmental variation. For some pathogen genotypes even slight changes in temperature arrested spore production, rendering the developing infection ineffectual. The response of pathogen genotypes to environmental gradients varied in magnitude and even direction, so that their rankings changed across the abiotic gradients. Hence, the variable environment of spatially structured host–parasite interactions may strongly influence the maintenance of polymorphism in pathogen life‐history stages governing transmission, whereas evolutionary trajectories of infectivity may be unaffected by the surrounding environment.

Spatiotemporal Structure of Host‐Pathogen Interactions in a Metapopulation

The ecological and evolutionary dynamics of species are influenced by spatiotemporal variation in population size. Unfortunately, we are usually limited in our ability to investigate the numerical dynamics of natural populations across large spatial scales and over long periods of time. Here we combine mechanistic and statistical approaches to reconstruct continuous‐time infection dynamics of an obligate fungal pathogen on the basis of discrete‐time occurrence data. The pathogen, Podosphaera plantaginis, infects its host plant, Plantago lanceolata, in a metapopulation setting where the presence of the pathogen has been recorded annually for 6 years in ∼4,000 host populations across an area of 50 km × 70 km in Finland. The dynamics are driven by strong seasonality, with a high extinction rate during winter and epidemic expansion in summer for local pathogen populations. We are able to identify with our model the regions in the study area where overwintering has been most successful. These overwintering sites represent foci that initiate local epidemics during the growing season. There is striking heterogeneity at the regional scale in both the overwintering success of the pathogen and the encounter intensity between the host and the pathogen. Such heterogeneity has profound implications for the coevolutionary dynamics of the interaction.

Co-infection alters population dynamics of infectious disease

Co-infections by multiple pathogen strains are common in the wild. Theory predicts co-infections to have major consequences for both within- and between-host disease dynamics, but data are currently scarce. Here, using common garden populations of Plantago lanceolata infected by two strains of the pathogen Podosphaera plantaginis, either singly or under co-infection, we find the highest disease prevalence in co-infected treatments both at the host genotype and population levels. A spore-trapping experiment demonstrates that co-infected hosts shed more transmission propagules than singly infected hosts, thereby explaining the observed change in epidemiological dynamics. Our experimental findings are confirmed in natural pathogen populations—more devastating epidemics were measured in populations with higher levels of co-infection. Jointly, our results confirm the predictions made by theoretical and experimental studies for the potential of co-infection to alter disease dynamics across a large host–pathogen metapopulation.