Pathogen Population Dynamics Research Articles

Breeding Progress in Seedling Resistance against Various Races of Stripe and Leaf Rust in European Bread Wheat

Background: Stripe and leaf rust are major constraints of wheat production with substantial impacts on grain yield. Population dynamics of both pathogens and the emergence of new virulent races have resulted in relentless efforts related to wheat breeding to improve resistance during the last decades. Methods: To evaluate the breeding progress achieved with respect to race-specific resistance, a set of nine isolates of the two rust pathogens have been tested in seedling assays on a panel of 191 elite winter wheat cultivars representing wheat breeding in Europe between 1966 and 2013. Results: Significant differences in the resistance of wheat cultivars concerning both pathogens have been detected by means of two-way ANOVA. Isolates as well as genotype × isolate interaction had a significant effect for both pathogens. Breeding progress, resulting in an increased seedling resistance, has been achieved against all nine isolates over the past five decades. The slope of progress was steeper for leaf rust than for stripe rust isolates. Progress against the highly common leaf rust isolate “4171” and” the stripe rust isolate “Warrior(-)” was strongest. Conclusions: The study reveals that a steady increase in seedling resistance was achieved during the past five decades. An additive contribution of these isolate specific R genes after breakdown has been hypothesised.

Epistatic control of intrinsic resistance by virulence genes in Listeria.

Elucidating the relationships between antimicrobial resistance and virulence is key to understanding the evolution and population dynamics of resistant pathogens. Here, we show that the susceptibility of the gram-positive bacterium Listeria monocytogenes to the antibiotic fosfomycin is a complex trait involving interactions between resistance and virulence genes and the environment. We found that a FosX enzyme encoded in the listerial core genome confers intrinsic fosfomycin resistance to both pathogenic and non-pathogenic Listeria spp. However, in the genomic context of the pathogenic L. monocytogenes, FosX-mediated resistance is epistatically suppressed by two members of the PrfA virulence regulon, hpt and prfA, which upon activation by host signals induce increased fosfomycin influx into the bacterial cell. Consequently, in infection conditions, most L. monocytogenes isolates become susceptible to fosfomycin despite possessing a gene that confers high-level resistance to the drug. Our study establishes the molecular basis of an epistatic interaction between virulence and resistance genes controlling bacterial susceptibility to an antibiotic. The reported findings provide the rationale for the introduction of fosfomycin in the treatment of Listeria infections even though these bacteria are intrinsically resistant to the antibiotic in vitro.

Disentangling the drivers of invasion spread in a vector-borne tree disease.

Pine wilt disease (PWD) invaded southern Japan in the early 1900s and has gradually expanded its range to northern Honshu (Japanese mainland). The disease is caused by a pathogenic North American nematode, which is transmitted by native pine sawyer beetles. Recently, the disease has invaded other portions of East Asia and Europe where extensive mortality of host pines is anticipated to resemble historical patterns seen in Japan. There is a critical need to identify the main drivers of PWD invasion spread so as to predict the future spread and evaluate containment strategies in newly invaded world regions. But the coupling of pathogen and vector population dynamics introduces considerable complexity that is important for understanding this and other plant disease invasions. In this study, we analysed historical (1980-2011) records of PWD infection and vector abundance, which were spatially extensive but recorded at coarse categorical levels (none, low and high) across 403 municipalities in northern Honshu. We employed a multistate occupancy model that accounted both for demographic stochasticity and observation errors in categorical data. Analysis revealed that sparse sawyer populations had lower probabilities of transition to high abundance than did more abundant populations even when regional abundance stayed the same, suggesting the existence of positive density dependence, that is an Allee effect, in sawyer dynamics. Climatic conditions (average accumulated degree days) substantially limited invasion spread in northern regions, but this climatic influence on sawyer dynamics was generally weaker than the Allee effect. Our results suggest that tactics (eg sanitation logging of infected pines) which strengthen Allee effects in sawyer dynamics may be effective strategies for slowing the spread of PWD.

Pathogen population structure can explain hospital outbreaks.

Hospitalized patients are at risk for increased length of stay, illness, or death due to hospital acquired infections. The majority of hospital transmission models describe dynamics on the level of the host rather than on the level of the pathogens themselves. Accordingly, epidemiologists often cannot complete transmission chains without direct evidence of either host-host contact or a large reservoir population. Here, we propose an ecology-based model to explain the transmission of pathogens in hospitals. The model is based upon metapopulation biology, which describes a group of interacting localized populations and island biogeography, which provides a basis for how pathogens may be moving between locales. Computational simulation trials are used to assess the applicability of the model. Results indicate that pathogens survive for extended periods without the need for large reservoirs by living in localized ephemeral populations while continuously transmitting pathogens to new seed populations. Computational simulations show small populations spending significant portions of time at sizes too small to be detected by most surveillance protocols and that the number and type of these ephemeral populations enable the overall pathogen population to be sustained. By modeling hospital pathogens as a metapopulation, many observations characteristic of hospital acquired infection outbreaks for which there has previously been no sufficient biological explanation, including how and why empirically successful interventions work, can now be accounted for using population dynamic hypotheses. Epidemiological links between temporally isolated outbreaks are explained via pathogen population dynamics and potential outbreak intervention targets are identified.

Detection of interactions between the pea root rot pathogens Aphanomyces euteiches and Fusarium spp. using a multiplex qPCR assay

Pea root rot complex (PRRC) describes a group of closely associated soilborne pathogens that cause root rot disease in field pea. Aphanomyces euteiches and several Fusarium spp. are the most prevalent and damaging microorganisms within this complex, although the impact of interspecific interactions on disease progression remains largely unexplored. Furthermore, a fast and reliable method of detecting and quantifying these pathogens is not currently available. The objectives of this experiment were to: (i) investigate the effect of microbial interactions on root rot severity in pea under greenhouse conditions; and (ii) characterize changes in colonization rates when multiple pathogens are present using qPCR. Seeds were exposed to three species of Fusarium and were planted into A. euteiches‐infested soil in varying combinations. For each experimental treatment, an index of disease severity was used to visually rate disease symptoms. Additionally, two triplex quantitative PCR (qPCR) assays were designed to detect and quantify changes in pathogen population dynamics on the roots. Both assays demonstrated a high degree of sensitivity and efficiency. Results from two independent greenhouse trials indicated an increase in disease severity in the presence of multiple pathogen species compared to single inoculations. Specifically, roots infected with A. euteiches were more susceptible to fusarium root rot than those exposed only to Fusarium spp. These observations were confirmed by qPCR results, which revealed significant changes in colonization rates when multiple species were present. These findings suggest an increased risk of yield loss in regions where A. euteiches and Fusarium spp. co‐occur.

Bayesian reconstruction of transmission within outbreaks using genomic variants.

Pathogen genome sequencing can reveal details of transmission histories and is a powerful tool in the fight against infectious disease. In particular, within-host pathogen genomic variants identified through heterozygous nucleotide base calls are a potential source of information to identify linked cases and infer direction and time of transmission. However, using such data effectively to model disease transmission presents a number of challenges, including differentiating genuine variants from those observed due to sequencing error, as well as the specification of a realistic model for within-host pathogen population dynamics. Here we propose a new Bayesian approach to transmission inference, BadTrIP (BAyesian epiDemiological TRansmission Inference from Polymorphisms), that explicitly models evolution of pathogen populations in an outbreak, transmission (including transmission bottlenecks), and sequencing error. BadTrIP enables the inference of host-to-host transmission from pathogen sequencing data and epidemiological data. By assuming that genomic variants are unlinked, our method does not require the computationally intensive and unreliable reconstruction of individual haplotypes. Using simulations we show that BadTrIP is robust in most scenarios and can accurately infer transmission events by efficiently combining information from genetic and epidemiological sources; thanks to its realistic model of pathogen evolution and the inclusion of epidemiological data, BadTrIP is also more accurate than existing approaches. BadTrIP is distributed as an open source package (https://bitbucket.org/nicofmay/badtrip) for the phylogenetic software BEAST2. We apply our method to reconstruct transmission history at the early stages of the 2014 Ebola outbreak, showcasing the power of within-host genomic variants to reconstruct transmission events.

Evidence for selection pressure from resistant potato genotypes but not from fungicide application within a clonal Phytophthora infestans population

Insight into pathogen population dynamics provides a key input for effective disease management of the potato late blight pathogen Phytophthora infestans. Phytophthora infestans populations vary from genetically complex to more simple with a few clonal lineages. The presence or absence of certain strains of P. infestans may impact the efficacy of fungicides or host resistance. Current evidence indicates that genetically, the Irish populations of P. infestans are relatively simple with a few clonal lineages. In this study, P. infestans populations were genetically characterized based on samples collected at the national centre for potato breeding during the period 2012–16. The dominance of clonal lineages within this P. infestans population was confirmed and the potential selection pressure of fungicide treatment (2013–15) and host resistance (2016) on this clonal P. infestans population was then investigated. It was found that fungicide products did not notably affect the genetic structure of sampled populations relative to samples from untreated control plants. In contrast, samples taken from several resistant potato genotypes were found to be more often of the EU_13_A2 lineage than those taken from control King Edward plants or potato genotypes with low resistance ratings. Resistant potato varieties Sarpo Mira and Bionica, containing characterized R genes, were found to strongly select for EU_13_A2 strains.

Olive anthracnose: a yield- and oil quality-degrading disease caused by several species of Colletotrichum that differ in virulence, host preference and geographical distribution.

The disease is caused by diverse species of Colletotrichum, mostly clustering in the C.acutatum species complex. Colletotrichum nymphaeae and C.godetiae are the prevalent species in the Northern Hemisphere, whereas C.acutatum sensu stricto is the most frequent species in the Southern Hemisphere, although it is recently and quickly emerging in the Northern Hemisphere. The disease has been reported from all continents, but it attains higher incidence and severity in the west of the Mediterranean Basin, where it is endemic in traditional orchards of susceptible cultivars. The pathogens are able to survive on vegetative organs. On the fruit surface, infections remain quiescent until fruit maturity, when typical anthracnose symptoms develop. Under severe epidemics, defoliation and death of branches can also occur. Pathogen species differ in virulence, although this depends on the cultivar. The selection of resistant cultivars depends strongly on pathogen diversity and environmental conditions, posing added difficulties to breeding efforts. Chemical disease control is normally achieved with copper-based fungicides, although this may be insufficient under highly favourable disease conditions and causes concern because of the presence of fungicide residues in the oil. In areas in which the incidence is high, farmers tend to anticipate harvest, with consequences in yield and oil characteristics. Olive production systems, harvest and post-harvest processing have experienced profound changes in recent years, namely new training systems using specific cultivars, new harvest and processing techniques and new organoleptic market requests. Changes are also occurring in both the geographical distribution of pathogen populations and the taxonomic framework. In addition, stricter rules concerning pesticide use are likely to have a strong impact on control strategies. A detailed knowledge of pathogen diversity, population dynamics and host-pathogen interactions is basal for the deployment of durable and effective disease control strategies, whether based on resistance breeding, agronomic practices or biological or chemical control.

Effects of multiple sources of genetic drift on pathogen variation within hosts.

Changes in pathogen genetic variation within hosts alter the severity and spread of infectious diseases, with important implications for clinical disease and public health. Genetic drift may play a strong role in shaping pathogen variation, but analyses of drift in pathogens have oversimplified pathogen population dynamics, either by considering dynamics only at a single scale—such as within hosts or between hosts—or by making drastic simplifying assumptions, for example, that host immune systems can be ignored or that transmission bottlenecks are complete. Moreover, previous studies have used genetic data to infer the strength of genetic drift, whereas we test whether the genetic drift imposed by pathogen population processes can be used to explain genetic data. We first constructed and parameterized a mathematical model of gypsy moth baculovirus dynamics that allows genetic drift to act within and between hosts. We then quantified the genome-wide diversity of baculovirus populations within each of 143 field-collected gypsy moth larvae using Illumina sequencing. Finally, we determined whether the genetic drift imposed by host–pathogen population dynamics in our model explains the levels of pathogen diversity in our data. We found that when the model allows drift to act at multiple scales—including within hosts, between hosts, and between years—it can accurately reproduce the data, but when the effects of drift are simplified by neglecting transmission bottlenecks and stochastic variation in virus replication within hosts, the model fails. A de novo mutation model and a purifying selection model similarly fail to explain the data. Our results show that genetic drift can play a strong role in determining pathogen variation and that mathematical models that account for pathogen population growth at multiple scales of biological organization can be used to explain this variation.

Rethinking the role of aquatic ecology in hydroponic cultivation

Hydroponic production systems are challenged by root diseases, but can be made less susceptible to infection. While the systems are mostly unchallenged by nematodes, pathogens that can live and spread though water still cause loss of yield. Common diseases would be Phytophthora, Pythium, Fusarium and bacteria such as Erwinias and Pseudomonads. Since horticulture cannot be performed in a sterile environment on a commercial scale, insight in population dynamics of pathogens in aquatic systems as well as plants' resilience need to be understood to lower the risk of infection. This paper addresses a number of biological principles in aquatic ecology that could be used in improving system design processes as well as providing the first data on the population dynamics in chrysanthemum production on deep flow systems in The Netherlands using next generation sequencing (NGS). It was observed that free colonisation of the water leads to highly diverse bacterial populations, while inoculation with water from an established deep flow pond leads to more uniform populations in the long run. Temperature can strongly influence bacterial populations. Addition of benefical micro-organisms leads to increase plant resilience against diseases. It is yet unclear whether such reduced infection is due to direct antagonistic effect, through a plant-endophyte symbiotic relationship or through competition for nutrients (sugars) or physical space. Fungal populations could not be studied since the similarity of DNA-database was too low to draw conclusions.

Interactions between host immune response and antigenic variation that control Borrelia burgdorferi population dynamics.

The population dynamics of pathogens within hosts result from interactions between host immune responses and mechanisms of the pathogen to evade or resist immune responses. Vertebrate hosts have evolved adaptive immune responses to eliminate the infection, while many pathogens evade immune clearance through altering surface antigens. Such interactions can result in a characteristic pattern of pathogen population dynamics within hosts consisting of population growth after infection, rapid population decline following specific immune responses, followed by persistence at low densities during a chronic infection stage. Despite the medical importance of chronic infections, little is known about the conditions of the interactions between variable antigens and the adaptive immune system that cause the characteristic pathogen population dynamics. Using the vls antigenic variation system of the Lyme disease pathogen, Borrelia burgdorferi, as a model system, we investigated conditions of the interaction between the antigenic variation system and the adaptive immune response that can explain the within-host population dynamics of B. burgdorferi using mathematical modelling. This characteristic population dynamic pattern can be explained by models that assume a variable immune removal rate of antibody-bound B. burgdorferi. However, models with a constant immune removal rate could reproduce the rapid population decline of B. burgdorferi populations but not their long-term persistence within hosts using parameter values determined by fitting empirical data. The model predictions, along with the assumptions about the interactions between B. burgdorferi and the immune response, can be tested experimentally to estimate the likelihood that each mechanism affects B. burgdorferi population dynamics in real infections.

Short Rotations in Forest Plantations Accelerate Virulence Evolution in Root-Rot Pathogenic Fungi

As disease outbreaks in forest plantations are causing concern worldwide, a clear understanding of the influence of silvicultural practices on the development of epidemics is still lacking. Importantly, silvicultural practices are likely to simultaneously affect epidemiological and evolutionary dynamics of pathogen populations. We propose a genetically explicit and individual-based model of virulence evolution in a root-rot pathogenic fungus spreading across forest landscapes, taking the Armillaria ostoyae–Pinus pinaster pathosystem as reference. We used the model to study the effects of rotation length on the evolution of virulence and the propagation of the fungus within a forest landscape composed of even-aged stands regularly altered by clear-cutting and thinning operations. The life cycle of the fungus modeled combines asexual and sexual reproduction modes, and also includes parasitic and saprotrophic phases. Moreover, the tree susceptibility to the pathogen is primarily determined by the age of the stand. Our simulations indicated that the shortest rotation length accelerated both the evolution of virulence and the development of the epidemics, whatever the genetic variability in the initial fungal population and the asexuality rate of the fungal species

Deciphering the landscape of host barriers to Listeria monocytogenes infection

Listeria monocytogenes is a common food-borne pathogen that can disseminate from the intestine and infect multiple organs. Here, we used sequence tag-based analysis of microbial populations (STAMP) to investigate Lmonocytogenes population dynamics during infection. We created a genetically barcoded library of murinized Lmonocytogenes and then used deep sequencing to track the pathogen's dissemination routes and quantify its founding population (Nb) sizes in different organs. We found that the pathogen disseminates from the gastrointestinal tract to distal sites through multiple independent routes and that Nb sizes vary greatly among tissues, indicative of diverse host barriers to infection. Unexpectedly, comparative analyses of sequence tags revealed that fecally excreted organisms are largely derived from the very small number of L. monocytogenes cells that colonize the gallbladder. Immune depletion studies suggest that distinct innate immune cells restrict the pathogen's capacity to establish replicative niches in the spleen and liver. Finally, studies in germ-free mice suggest that the microbiota plays a critical role in the development of the splenic, but not the hepatic, barriers that prevent L. monocytogenes from seeding these organs. Collectively, these observations illustrate the potency of the STAMP approach to decipher the impact of host factors on population dynamics of pathogens during infection.

The abundance of the Lyme disease pathogen Borrelia afzelii declines over time in the tick vector Ixodes ricinus

BackgroundThe population dynamics of vector-borne pathogens inside the arthropod vector can have important consequences for vector-to-host transmission. Tick-borne spirochete bacteria of the Borrelia burgdorferi (sensu lato) species complex cause Lyme borreliosis in humans and spend long periods of time (>12 months) in their Ixodes tick vectors. To date, few studies have investigated the dynamics of Borrelia spirochete populations in unfed Ixodes nymphal ticks.MethodsLarval ticks from our laboratory colony of I. ricinus were experimentally infected with B. afzelii, and killed at 1 month and 4 months after the larva-to-nymph moult. The spirochete load was also compared between engorged larval ticks and unfed nymphs (from the same cohort) and between unfed nymphs and unfed adult ticks (from the same cohort). The spirochete load of B. afzelii in each tick was estimated using qPCR.ResultsThe mean spirochete load in the 1-month-old nymphs (~14,000 spirochetes) was seven times higher than the 4-month-old nymphs (~2000 spirochetes). Thus, the nymphal spirochete load declined by 80% over a period of 3 months. An engorged larval tick acquired ~100 spirochetes, and this population was 20 times larger in a young, unfed nymph. The spirochete load also appeared to decline in adult ticks. Comparison between wild and laboratory populations found that lab ticks were more susceptible to acquiring B. afzelii.ConclusionThe spirochete load of B. afzelii declines dramatically over time in domesticated I. ricinus nymphs under laboratory conditions. Future studies should investigate whether temporal declines in spirochete load occur in wild Ixodes ticks under natural conditions and whether these declines influence the tick-to-host transmission of Borrelia.

Local demographic and epidemiological patterns in the Linum marginale–Melampsora lini association: a multi‐year study

Summary Many theoretical and empirical studies operate from an assumption that pathogens have a significant influence on the fecundity and life span of their host species. However, there are surprisingly little data investigating the long‐term fitness impacts and genetic consequences that arise from pathogen infection in natural populations. Here, we address this gap through the analysis of a dataset investigating the local population dynamics of a native host plant (Linum marginale) and an associated rust pathogen (Melampsora lini) across 12 years. To investigate patterns of disease prevalence and severity and track effects on host fecundity and demography, we conducted censuses on an annual basis at a single site. Annual M. lini infection prevalence ranged from 0% to 99%. Severe epidemics occurred in 3‐ to 4‐year cycles causing high overwintering mortality and subsequent changes in the relative abundance of different host phenotypes. Host population size oscillated in response to epidemics and declined towards the end of the observation period. Changes in host numbers were found to affect disease severity but not infection prevalence. Melampsora lini infection increased L. marginale fecundity; the infected plants produced threefold more seed capsules on average than uninfected plants (13·3 vs. 4·3 seed capsules per plant). To investigate how variation in environmental conditions affects epidemiology and host demography, we identified climatic factors affecting host growth, overwintering and disease severity. Winter (June) rainfall increased host overwintering success and summer (December) rainfall favoured host growth. The progress of M. lini disease epidemics benefited from optimal temperatures in February and suffered from rainfall in January. We further examined links between the genetic structure of the pathogen population and disease dynamics. There was a positive correlation between mean pathogen infectivity (as measured across a host differential set) and the severity of disease epidemics. Synthesis. Our results provide new insights into local drivers and consequences of pathogen epidemiology in natural populations. Melampsora lini infection can have profound consequences on the phenotype, demography and population structure of Linum marginale by increasing host fecundity, overwinter mortality and disease resistance.

28‐year temporal sequence of epidemic dynamics in a natural rust–host plant metapopulation

Summary A long‐term study of disease dynamics caused by the rust Uromyces valerianae in 31 discrete populations of Valeriana salina provides a rare opportunity to explore extended temporal patterns in the epidemiology of a natural host–pathogen metapopulation. Over a 28‐year period, pathogen population dynamics varied across the metapopulation with disease incidence (presence/absence), prevalence (% plants infected) and severity (% leaf area covered by lesions) all showing strong population and year effects, indicative of heterogeneity among years and host populations in the suitability of conditions for the pathogen. Disease incidence within individual host populations was significantly affected by host population size, disease prevalence the previous year and the proximity of neighbouring populations infected in the current year. After accounting for these variables there was still a marked temporal component with winter sea level having a significant effect; as did summer rainfall in the second part of the study period (1997–2011). Disease prevalence was also effected by host population size and disease prevalence in the previous year. However, it was less affected by spatial aspects of disease spread than was disease incidence. Winter sea level and June rainfall significantly affected disease prevalence. Assessment of disease impact on plant performance found strong variation in disease severity associated with the aspect and positioning of host populations. Plants growing in lower disease environments produced significantly more seeds than those growing in high disease sites. Significant variation in reaction to infection by U. valerianae was detected among plants within four populations and between these different populations. Synthesis. The epidemiology of Uromyces valerianae was highly influenced by host population size, previous disease and distance. After accounting for these factors, there was a clear temporal signal of change in disease incidence linked to winter sea level and summer rainfall. These patterns reinforce the importance of considering interactions in multiple populations over long periods of time in order to obtain a clear picture of the variability in disease‐induced selection pressures across time and space. The behaviour of the pathogen fitted that predicted for a metapopulation with considerable asynchrony in epidemiological patterns among demes.

Field Pathogenomics: An Advanced Tool for Wheat Rust Surveillance.

Traditionally, diagnostic tools for plant pathogens were limited to the analysis of purified pathogen isolates subjected to phenotypic characterization and/or PCR-based genotypic analysis. However, these approaches detect only already known pathogenic agents, may not always recognize novel races, and can introduce bias in the results. Recent advances in next-generation sequencing technologies have provided new opportunities to integrate high-resolution genotype data into pathogen surveillance programs. Here, we describe some of the key bioinformatics analysis used in the newly developed "Field Pathogenomics" pathogen surveillance technique. This technique is based on RNA-seq data generated directly form pathogen-infected plant leaf samples collected in the field, providing a unique opportunity to characterize the pathogen population and its host directly in their natural environment. We describe two main analyses: (1) a phylogenetic analysis of the pathogen isolates that have been collected to understand how they are related to each other, and (2) a population structure analysis to provide insight into the genetic substructure within the pathogen population. This provides a high-resolution representation of pathogen population dynamics directly in the field, providing new insights into pathogen biology, population structure, and pathogenesis.

Control of postharvest storage rots of apples and pears in The Netherlands

Postharvest diseases are a major problem in long storage of apples and pears in The Netherlands. Despite intensive preharvest spraying programs significant losses occur. Over 150 heavily affected many apples (mainly 'Elstar') and pears (mainly 'Conference') from packinghouses in different regions of The Netherlands were evaluated for decay symptoms and causal organisms. Assessments showed that the most important pathogens are Neofabraea spp. (apples and pears) and Cadophora spp. (pears). Infection by these two pathogens occurs in the orchard but remains latent until storage. Other pathogens such as Botrytis spp., Pencillium spp., Fusarium spp., Alternaria spp., and Cladosporium spp. were isolated at low frequencies and are considered of minor importance. However, new problems with sooty blotch and lenticel rot of apple were noticed, most likely caused by other, not yet identified pathogens. Pathogenicity testing and characterization of isolates are on-going. For major pathogens, qPCR assays are developed. Samples of substrates (e.g., leaves, cankers, soil) were monthly taken from 10 apple and 10 pear orchards in 2012. Samples were assessed using the qPCR assays for presence and dynamics of pathogen populations. This information on the pathogen life cycles is needed for the development of innovative strategies to prevent postharvest losses. Storage conditions may significantly influence disease development. Recently, the project “KWALIFRUIT” was launched to identify the optimum harvest stage of pome fruit and optimal storage conditions for maximum fruit quality and storage life and minimal postharvest losses.

Eco-social processes influencing infectious disease emergence and spread.

The complexity and connectedness of eco-social processes have major influence on the emergence and spread of infectious diseases amongst humans and animals. The disciplinary nature of most research activity has made it difficult to improve our understanding of interactions and feedback loops within the relevant systems. Influenced by the One Health approach, increasing efforts have recently been made to address this knowledge gap. Disease emergence and spread is strongly influenced by host density and contact structures, pathogen characteristics and pathogen population and molecular evolutionary dynamics in different host species, and host response to infection. All these mechanisms are strongly influenced by eco-social processes, such as globalization and urbanization, which lead to changes in global ecosystem dynamics, including patterns of mobility, human population density and contact structures, and food production and consumption. An improved understanding of epidemiological and eco-social processes, including their interdependence, will be essential to be able to manage diseases in these circumstances. The interfaces between wild animals, domestic animals and humans need to be examined to identify the main risk pathways and put in place appropriate mitigation. Some recent examples of emerging infectious disease are described to illustrate eco-social processes that are influencing disease emergence and spread.

Toward agent-based models for pre-harvest food safety

The safety of fresh produce is a concern because many types of produce are consumed raw, and the incidence of produce-borne diseases appears to be increasing. Good agricultural practices (GAPs) can limit the chances for contamination of produce, but farms are open systems where interactions with surrounding lands can override benefits from GAPs. The extent to which interactions between farms and the surrounding landscape contribute to sporadic disease is not yet clear, but outbreaks have arisen from contamination of produce by wildlife, manure, or irrigation water. We hypothesize that the ability to control transmission of pathogens to produce, before harvest, partially depends on understanding the dynamics of pathogen populations, with some landscapes exhibiting combinations of characteristics that increase pathogen dispersal to croplands. The landscape processes leading to contamination are difficult to predict with current techniques. In this perspectives paper, we advance a foundation for modeling food contamination processes in agricultural landscapes using a combination of remote-sensing technologies and ecological modeling of pathogen dispersal, enabled by geographic information systems. With the development of predictive models, cultivation practices can be adapted to local conditions to reduce food contamination by controlling the connectivity between foodborne pathogen reservoirs and food production blocks on farms.