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The trade‐off between within‐host infection rate and transmission to new hosts is predicted to constrain pathogen evolution, and to maintain polymorphism in pathogen populations. Pathogen life‐history stages and their correlations that underpin infection development may change under coinfection with other parasites as they compete for the same limited host resources. Cross‐kingdom interactions are common among pathogens in both natural and cultivated systems, yet their impacts on disease ecology and evolution are rarely studied. The host plant Plantago lanceolata is naturally infected by both Phomopsis subordinaria, a seed killing fungus, as well as Plantago lanceolata latent virus (PlLV) in the Åland Islands, SW Finland. We performed an inoculation assay to test whether coinfection with PlLV affects performance of two P. subordinaria strains, and the correlation between within‐host infection rate and transmission potential. The strains differed in the measured life‐history traits and their correlations. Moreover, we found that under virus coinfection, within‐host infection rate of P. subordinaria was smaller but transmission potential was higher compared to strains under single infection. The negative correlation between within‐host infection rate and transmission potential detected under single infection became positive under coinfection with PlLV. To understand whether within‐host and between‐host dynamics are correlated in wild populations, we surveyed 260 natural populations of P. lanceolata for P. subordinaria infection occurrence. When infections were found, we estimated between‐hosts dynamics by determining pathogen population size as the proportion of infected individuals, and within‐host dynamics by counting the proportion of infected flower stalks in 10 infected plants. In wild populations, the proportion of infected flower stalks was positively associated with pathogen population size. Jointly, our results suggest that the trade‐off between within‐host infection load and transmission may be strain specific, and that the pathogen life‐history that underpin epidemics may change depending on the diversity of infection, generating variation in disease dynamics. [ABSTRACT FROM AUTHOR]

Summary: Human alteration of natural habitats may change the processes governing species interactions in wild communities. Wild populations are increasingly impacted by agricultural intensification, yet it is unknown whether this alters biodiversity mediation of disease dynamics.We investigated the association between plant diversity (species richness, diversity) and infection risk (virus richness, prevalence) in populations of Plantago lanceolata in natural landscapes as well as those occurring at the edges of cultivated fields. Altogether, 27 P. lanceolata populations were surveyed for population characteristics and sampled for PCR detection of five recently characterized viruses.We find that plant species richness and diversity correlated negatively with virus infection prevalence. Virus species richness declined with increasing plant diversity and richness in natural populations while in agricultural edge populations species richness was moderately higher, and not associated with plant richness. This difference was not explained by changes in host richness between these two habitats, suggesting potential pathogen spill‐over and increased transmission of viruses across the agro‐ecological interface. Host population connectivity significantly decreased virus infection prevalence.We conclude that human use of landscapes may change the ecological laws by which natural communities are formed with far reaching implications for ecosystem functioning and disease. See also the Commentary on this article by Lacroix, 230: 2094–2096. [ABSTRACT FROM AUTHOR]

Wild plant populations may harbour a myriad of unknown viruses. As the majority of research efforts have targeted economically important plant species, the diversity and prevalence of viruses in the wild has remained largely unknown. However, the recent shift towards metagenomics-based sequencing methodologies, especially those targeting small RNAs, is finally enabling virus discovery from wild hosts. Understanding this diversity of potentially pathogenic microbes in the wild can offer insights into the components of natural biodiversity that promotes long-term coexistence between hosts and parasites in nature, and help predict when and where risks of disease emergence are highest. Here, we used small RNA deep sequencing to identify viruses in Plantago lanceolata populations, and to understand the variation in their prevalence and distribution across the Åland Islands, South-West Finland. By subsequent design of PCR primers, we screened the five most common viruses from two sets of P. lanceolata plants: 164 plants collected from 12 populations irrespective of symptoms, and 90 plants collected from five populations showing conspicuous viral symptoms. In addition to the previously reported species Plantago lanceolata latent virus (PlLV), we found four potentially novel virus species belonging to Caulimovirus, Betapartitivirus, Enamovirus, and Closterovirus genera. Our results show that virus prevalence and diversity varied among the sampled host populations. In six of the virus infected populations only a single virus species was detected, while five of the populations supported between two to five of the studied virus species. In 20% of the infected plants, viruses occurred as coinfections. When the relationship between conspicuous viral symptoms and virus infection was investigated, we found that plants showing symptoms were usually infected (84%), but virus infections were also detected from asymptomatic plants (44%). Jointly, these results reveal a diverse virus community with newly developed tools and protocols that offer exciting opportunities for future studies on the ecoevolutionary dynamics of viruses infecting plants in the wild. [ABSTRACT FROM AUTHOR]

Understanding how variation in hosts, parasites, and the environment shapes patterns of disease is key to predicting ecological and evolutionary outcomes of epidemics. Yet in spatially structured populations, variation in host resistance may be spatially confounded with variation in parasite dispersal and environmental factors that affect disease processes. To tease apart these disease drivers, we paired surveys of natural epidemics with experiments manipulating spatial variation in host susceptibility to infection. We mapped epidemics of the wind‐dispersed powdery mildew pathogen Podosphaera plantaginis in five populations of its plant host, Plantago lanceolata. At 15 replicate sites within each population, we deployed groups of healthy potted 'sentinel' plants from five allopatric host lines. By tracking which sentinels became infected in the field and measuring pathogen connectivity and microclimate at those sites, we could test how variation in these factors affected disease when spatial variation in host resistance and soil conditions was minimized. We found that the prevalence and severity of sentinel infection varied over small spatial scales in the field populations, largely due to heterogeneity in pathogen prevalence on wild plants and unmeasured environmental factors. Microclimate was critical for disease spread only at the onset of epidemics, where humidity increased infection risk. Sentinels were more likely to become infected than initially healthy wild plants at a given field site. However, in a follow‐up laboratory inoculation study we detected no significant differences between wild and sentinel plant lines in their qualitative susceptibility to pathogen isolates from the field populations, suggesting that primarily non‐genetic differences between sentinel and wild hosts drove their differential infection rates in the field. Our study leverages a multi‐faceted experimental approach to disentangle important biotic and abiotic drivers of disease patterns within wild populations. [ABSTRACT FROM AUTHOR]

Abstract: Both theory and experimental evolution studies predict migration to influence the outcome of antagonistic coevolution between hosts and their parasites, with higher migration rates leading to increased diversity and evolutionary potential. Migration rates are expected to vary in spatially structured natural pathosystems, yet how spatial structure generates variation in coevolutionary trajectories across populations occupying the same landscape has not been tested. Here, we studied the effect of spatial connectivity on host evolutionary potential in a natural pathosystem characterized by a stable Plantago lanceolata host network and a highly dynamic Podosphaera plantaginis parasite metapopulation. We designed a large inoculation experiment to test resistance of five isolated and five well‐connected host populations against sympatric and allopatric pathogen strains, over 4 years. Contrary to our expectations, we did not find consistently higher resistance against sympatric pathogen strains in the well‐connected populations. Instead, host local adaptation varied considerably among populations and through time with greater fluctuations observed in the well‐connected populations. Jointly, our results suggest that in populations where pathogens have successfully established, they have the upper hand in the coevolutionary arms race, but hosts may be better able to respond to pathogen‐imposed selection in the well‐connected than in the isolated populations. Hence, the ongoing and extensive fragmentation of natural habitats may increase vulnerability to diseases. [ABSTRACT FROM AUTHOR]

Predicting and controlling infectious disease epidemics is a major challenge facing the management of agriculture, human and wildlife health. Co-evolutionarily derived patterns of local adaptation among pathogen populations have the potential to generate variation in disease epidemiology; however, studies of local adaptation in disease systems have mostly focused on interactions between competing pathogens or pathogens and their hosts. In nature, parasites and pathogens are also subject to attack by hyperparasitic natural enemies that can severely impact upon their infection dynamics. However, few studies have investigated whether this interaction varies across combinations of pathogen-hyperparasite strains, and whether this influences hyperparasite incidence in natural pathogen populations. Here, we test whether the association between a hyperparasitic fungus, Ampelomyces, and a single powdery mildew host, Podosphaera plantaginis, varies among genotype combinations, and whether this drives hyperparasite incidence in nature. Laboratory inoculation studies reveal that genotype, genotype × genotype interactions and local adaptation affect hyperparasite infection. However, observations of a natural pathogen metapopulation reveal that spatial rather than genetic factors predict the risk of hyperparasite presence. Our results highlight how sensitive the outcome of biocontrol using hyperparasites is to selection of hyperparasite strains. [ABSTRACT FROM AUTHOR]

The legacy of the use and misuse of antibiotics in recent decades has left us with a global public health crisis: antibiotic-resistant bacteria are on the rise, making it harder to treat infections. At the same time, evolution of antibiotic resistance is probably the best-documented case of contemporary evolution. To date, research on antibiotic resistance has largely ignored the complexity of interactions that bacteria engage in. However, in natural populations, bacteria interact with other species; for example, competition and grazing are import interactions influencing bacterial population dynamics. Furthermore, antibiotic leakage to natural environments can radically alter bacterial communities. Overall, we argue that eco-evolutionary feedback loops in microbial communities can be modified by residual antibiotics and evolution of antibiotic resistance. The aim of this review is to connect some of the well-established key concepts in evolutionary biology and recent advances in the study of eco-evolutionary dynamics to research on antibiotic resistance. We also identify some key knowledge gaps related to eco-evolutionary dynamics of antibiotic resistance, and review some of the recent technical advantages in molecular microbiology that offer new opportunities for tackling these questions. Finally, we argue that using the full potential of evolutionary theory and active communication across the different fields is needed for solving this global crisis more efficiently. This article is part of the themed issue 'Human influences on evolution, and the ecological and societal consequences'. [ABSTRACT FROM AUTHOR]

Infectious diseases dynamics are affected by both spatial and temporal heterogeneity in their environments. Our ability to quantify and predict how this heterogeneity impacts risks of infection and disease emergence is the key to successful disease prevention efforts. Here, we review the literature on infectious diseases from human, agricultural, and wildlife ecosystems to describe the rapid ecological and evolutionary responses in pathogens to environmental heterogeneity, with expected impacts on their epidemiology. To date, the underlying network structures through which disease transmission proceeds have been notoriously difficult to quantify because of this variation. We show that with recent advances in statistical methods and genomic approaches, it is now more feasible than ever to trace disease transmission networks, the molecular underpinning of infection, and the environmental variation relevant to disease dynamics. We end by identifying major new opportunities and challenges in understanding disease dynamics in an ever-changing world. [ABSTRACT FROM AUTHOR]

Plants have evolved different strategies to resist pathogens, but little is known about how effective, stable and costly these mechanisms are in perennial plants across multiple growing seasons., We conducted a laboratory experiment to assess resistance variation in Plantago lanceolata against the powdery mildew-causing fungus Podosphaera plantaginis and to measure possible trade-offs between the different resistance strategies. To test stability and costs of resistance, we established common garden populations of plants possessing three different resistance strategies: qualitative resistance that is the ability to block pathogen infection, quantitative resistance that is the ability to mitigate pathogen development and susceptibility. We measured their performance with and without disease for 3 years., There were no trade-offs between qualitative and quantitative resistance, and the components of quantitative resistance were positively correlated., Throughout the 3-year common garden study, pathogen loads were significantly affected by host resistance in the study populations. Qualitative resistance efficiently blocked infections but contrary to laboratory obtained results; quantitative resistance did not hinder epidemic growth., We detected costs in plant performance for qualitative and quantitative resistance compared to susceptible plants in absence of the pathogen. The costs of infection varied according to resistance strategy, pathogen load and plant age., Synthesis. In perennial plants, the costs and benefits of resistance need to be evaluated over multiple years as they may change with plant age. Our results give new insights into how polymorphism in resistance can be maintained through costs of resistance in plant performance and through shifts in resource allocation between vegetative growth and reproduction under infection. [ABSTRACT FROM AUTHOR]

Pathogens are considered to drive ecological and evolutionary dynamics of plant populations, but we lack data measuring the population-level consequences of infection in wild plant-pathogen interactions. Moreover, while it is often assumed that offseason environmental conditions drive seasonal declines in pathogen population size, little is known about how offseason environmental conditions impact the survival of pathogen resting stages, and how critical the offseason is for the next season's epidemic., The fungal pathogen Podosphaera plantaginis persists as a dynamic metapopulation in the large network of Plantago lanceolata host populations. Here, we analyze long-term data to measure the spatial synchrony of epidemics and consequences of infection for over 4000 host populations. Using a theoretical model, we study whether large-scale environmental change could synchronize disease occurrence across the metapopulation., During 2001-2013 exposure to freezing decreased, while pathogen extinction-colonization-persistence rates became more synchronized. Simulations of a theoretical model suggest that increasingly favorable winter conditions for pathogen survival could drive such synchronization. Our data also show that infection decreases host population growth., These results confirm that mild winter conditions increase pathogen overwintering success and thus increase disease prevalence across the metapopulation. Further, we conclude that the pathogen can drive host population growth in the Plantago- Podosphaera system. [ABSTRACT FROM AUTHOR]

While recent studies have elucidated many of the factors driving parasite dynamics during the growing season, the ecological and evolutionary dynamics during the off-season (i.e. the period between growing seasons) remain largely unexplored., We combined large-scale surveys and detailed experiments to investigate the overwintering success of the specialist plant pathogen Podosphaera plantaginis on its patchily distributed host plant Plantago lanceolata in the Åland Islands., Twelve years of epidemiological data establish the off-season as a crucial stage in pathogen metapopulation dynamics, with c. 40% of the populations going extinct during the off-season. At the end of the growing season, we observed environmentally mediated variation in the production of resting structures, with major consequences for spring infection at spatial scales ranging from single individuals to populations within a metapopulation. Reciprocal transplant experiments further demonstrated that pathogen population of origin and overwintering site jointly shaped infection intensity in spring, with a weak signal of parasite adaptation to the local off-season environment., We conclude that environmentally mediated changes in the distribution and evolution of parasites during the off-season are crucial for our understanding of host-parasite dynamics, with applied implications for combating parasites and diseases in agriculture, wildlife and human disease systems. [ABSTRACT FROM AUTHOR]

Theory indicates that spatial scale and habitat configuration are fundamental for coevolutionary dynamics and how diversity is maintained in host-pathogen interactions. Yet, we lack empirical data to translate the theory to natural host-parasite systems. In this study, we conduct a multiscale cross-inoculation study using the specialist wild plant pathogen Podosphaera plantaginis on its host plant Plantago lanceolata. We apply the same sampling scheme to a region with highly fragmented (Åland) and continuous (Saaremaa) host populations. Although theory predicts higher parasite virulence in continuous regions, we did not detect differences in traits conferring virulence among the regions. Patterns of adaptation were highly scale dependent. We detected parasite maladaptation among regions, and among populations separated by intermediate distances (6.0-40.0 km) within the fragmented region. In contrast, parasite performance did not vary significantly according to host origin in the continuous landscape. For both regions, differentiation among populations was much larger for genetic variation than for phenotypic variation, indicating balancing selection maintaining phenotypic variation within populations. Our findings illustrate the critical role of spatial scale and habitat configuration in driving host-parasite coevolution. The absence of more aggressive strains in the continuous landscape, in contrast to theoretical predictions, has major implications for long-term decision making in conservation, agriculture, and public health. [ABSTRACT FROM AUTHOR]

Genetic variation in pathogen populations may be an important factor driving heterogeneity in disease dynamics within their host populations. However, to date, we understand poorly how genetic diversity in diseases impact on epidemiological dynamics because data and tools required to answer this questions are lacking. Here, we combine pathogen genetic data with epidemiological monitoring of disease progression, and introduce a statistical exploratory method to investigate differences among pathogen strains in their performance in the field. The method exploits epidemiological data providing a measure of disease progress in time and space, and genetic data indicating the relative spatial patterns of the sampled pathogen strains. Applying this method allows to assign ranks to the pathogen strains with respect to their contributions to natural epidemics and to assess the significance of the ranking. This method was first tested on simulated data, including data obtained from an original, stochastic, multi-strain epidemic model. It was then applied to epidemiological and genetic data collected during one natural epidemic of powdery mildew occurring in its wild host population. Based on the simulation study, we conclude that the method can achieve its aim of ranking pathogen strains if the sampling effort is sufficient. For powdery mildew data, the method indicated that one of the sampled strains tends to have a higher fitness than the four other sampled strains, highlighting the importance of strain diversity for disease dynamics. Our approach allowing the comparison of pathogen strains in natural epidemic is complementary to the classical practice of using experimental infections in controlled conditions to estimate fitness of different pathogen strains. Our statistical tool, implemented in the R package StrainRanking, is mainly based on regression and does not rely on mechanistic assumptions on the pathogen dynamics. Thus, the method can be applied to a wide range of pathogens. [ABSTRACT FROM AUTHOR]

Background: Molecular tools may greatly improve our understanding of pathogen evolution and epidemiology but technical constraints have hindered the development of genetic resources for parasites compared to free-living organisms. This study aims at developing molecular tools for Podosphaera plantaginis, an obligate fungal pathogen of Plantago lanceolata. This interaction has been intensively studied in the Å land archipelago of Finland with epidemiological data collected from over 4,000 host populations annually since year 2001. Principal Findings: A cDNA library of a pooled sample of fungal conidia was sequenced on the 454 GS-FLX platform. Over 549,411 reads were obtained and annotated into 45,245 contigs. Annotation data was acquired for 65.2% of the assembled sequences. The transcriptome assembly was screened for SNP loci, as well as for functionally important genes (mating-type genes and potential effector proteins). A genotyping assay of 27 SNP loci was designed and tested on 380 infected leaf samples from 80 populations within the Åland archipelago. With this panel we identified 85 multilocus genotypes (MLG) with uneven frequencies across the pathogen metapopulation. Approximately half of the sampled populations contain polymorphism. Our genotyping protocol revealed mixed-genotype infection within a single host leaf to be common. Mixed infection has been proposed as one of the main drivers of pathogen evolution, and hence may be an important process in this pathosystem. Significance: The developed SNP panel offers exciting research perspectives for future studies in this well-characterized pathosystem. Also, the transcriptome provides an invaluable novel genomic resource for powdery mildews, which cause significant yield losses on commercially important crops annually. Furthermore, the features that render genetic studies in this system a challenge are shared with the majority of obligate parasitic species, and hence our results provide methodological insights from SNP calling to field sampling protocols for a wide range of biological systems. [ABSTRACT FROM AUTHOR]

Ecology Letters (2012) 15: 425-435 Abstract 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. [ABSTRACT FROM AUTHOR]

Variation in disease resistance is a widespread phenomenon in wild plant-pathogen associations. Here, we review current literature on natural plant-pathogen associations to determine how diversity in disease resistance is distributed at different hierarchical levels - within host individuals, within host populations, amongst host populations at the metapopulation scale and at larger regional scales. We find diversity in resistance across all spatial scales examined. Furthermore, variability seems to be the best counter-defence of plants against their rapidly evolving pathogens. We find that higher diversity of resistance phenotypes also results in higher levels of resistance at the population level. Overall, we find that wild plant populations are more likely to be susceptible than resistant to their pathogens. However, the degree of resistance differs strikingly depending on the origin of the pathogen strains used in experimental inoculation studies. Plant populations are on average 16% more resistant to allopatric pathogen strains than they are to strains that occur within the same population (48% vs. 32% respectively). Pathogen dispersal mode affects levels of resistance in natural plant populations with lowest levels detected for hosts of airborne pathogens and highest for waterborne pathogens. Detailed analysis of two model systems, Linum marginale infected by Melampsora lini, and Plantago lanceolata infected by Podosphaera plantaginis, show that the amount of variation in disease resistance declines towards higher spatial scales as we move from individual hosts to metapopulations, but evaluation of multiple spatial scales is needed to fully capture the structure of disease resistance. Synthesis. Variation in disease resistance is ubiquitous in wild plant-pathogen associations. Whilst the debate over whether the resistance structure of plant populations is determined by pathogen-imposed selection versus non-adaptive processes remains unresolved, we do report examples of pathogen-imposed selection on host resistance. Here we highlight the importance of measuring resistance across multiple spatial scales, and of using sympatric strains when looking for signs of coevolution in wild plant-pathogen interactions. [ABSTRACT FROM AUTHOR]

Recent methodological advances have uncovered tremendous microbial diversity cohabiting in the same host plant, and many of these microbes cause disease. In this review we highlight how the presence of other pathogen species, or other pathogen genotypes, within a plant can affect key components of host–pathogen interactions: (i) within-plant virulence and pathogen accumulation, through direct and host-mediated mechanisms; (ii) evolutionary trajectories of pathogen populations, through virulence evolution, generation of novel genetic combinations, and maintenance of genetic diversity; and (iii) disease dynamics, with multiple infection likely to render epidemics more devastating. The major future challenges are to couple a community ecology approach with a molecular investigation of the mechanisms operating under coinfection and to evaluate the evolution and effectiveness of resistance within a coinfection framework. [ABSTRACT FROM AUTHOR]