A stochastic optimization method to estimate the spatial distribution of a pathogen from a sample

Information on the spatial distribution of plant disease can be utilized to implement efficient and spatially targeted disease management interventions. We present a pathogen-generic method to estimate the spatial distribution of a plant pathogen using a stochastic optimization process which is epidemiologically motivated. Based on an initial sample, the method simulates the individual spread processes of a pathogen between patches of host to generate optimized spatial distribution maps. The method was tested on data sets of Huanglongbing of citrus and was compared with a kriging method from the field of geostatistics using the well-established kappa statistic to quantify map accuracy. Our method produced accurate maps of disease distribution with kappa values as high as 0.46 and was able to outperform the kriging method across a range of sample sizes based on the kappa statistic. As expected, map accuracy improved with sample size but there was a high amount of variation between different random sample placements (i.e., the spatial distribution of samples). This highlights the importance of sample placement on the ability to estimate the spatial distribution of a plant pathogen and we thus conclude that further research into sampling design and its effect on the ability to estimate disease distribution is necessary.     

Possibilities of avoidance and control of bacterial plant diseases when using pathogen-tested (certified) or -treated planting material

Testing of planting material for freedom from phytopathogenic bacteria is an important, although not exclusive, method for control of bacterial diseases of plants. Ideally, pathogen-free or pathogen-/disease-resistant planting material is desirable, but this situation is not always possible on a practical basis. For most bacterial pathogens, resistance is not available in cultivated hosts, and production of pathogen-free planting material requires strict certification schemes via several routes. These include (i) indexing, with subsequent removal of infected/contaminated material from the production chain; (ii) meristem and other tissue culture production systems; (iii) thermo- or chemotherapy; (iv) plant or seed surface disinfection for epiphytic bacterial pathogens; (v) avoidance or decontamination of contaminated production factors such as substrate, soil or irrigation water. These methods cannot guarantee 100% freedom from the pathogen or disease during crop multiplication from certified planting material, because of factors such as sampling error, experimental error, test sensitivities, limitations of therapies (e.g. phytotoxicity or insufficient penetration), re-introduction of the pathogen, insufficient hygiene or decontamination during planting and multiplication of clean propagating material, and manipulations during trade and production. These factors are discussed with reference to several bacterial plant diseases, in particular control of bacterial brown rot and ring rot of potato in Europe and North America. The most efficient control of bacterial diseases can be expected through a combination of the use of healthy/tested planting material and good cultivation practice, including strict crop and storage hygiene.     

A perspective on the measurement of time in plant disease epidemiology

The growth and development of plant pathogens and their hosts generally respond strongly to the temperature of their environment. However, most studies of plant pathology record pathogen/host measurements against physical time (e.g. hours or days) rather than thermal time (e.g. degree-days or degree-hours). This confounds the comparison of epidemiological measurements across experiments and limits the value of the scientific literature.     

Local maladaptation of the anther-smut fungus parasitizing Dianthus carthusianorum

Pathogens are generally expected to evolve faster than their hosts and are therefore likely to be locally adapted. However, some pathogens might lag behind in the co-evolutionary arms race because they do not have some of the advantages shared by most other pathogens (e.g., high mutation or recombination rates, short generation time, high dispersal ability). This is the case of Microbotryum fungi that cause the anther smut disease in plants of the family Caryophyllaceae. We investigated the patterns of local adaptation and maladaptation in Microbotryum carthusianorum and its host plant Dianthus carthusianorum. We performed a full cross-inoculation experiment using half-sib plant families and fungal samples originating from three naturally infected populations in the Czech Republic. We specifically asked, which components of pathogen fitness (i.e., infectivity and host manipulation) are affected by local (mal)adaptation. The pathogen was on average 1.6 times more successful in infecting plants from foreign populations compared to plants from its home population. Once the infection was successful, the pathogen accelerated the plant’s flowering and thus increased the opportunity for transmission to new hosts. However, the level of manipulation of host flowering did not differ between home and foreign populations. This study showed that the pathogen’s infectivity followed a clear pattern of local maladaptation, whereas the host manipulation did not. Our study taken together with previous studies of a related anther smut species reveals the pervasiveness of local maladaptation in this group of pathogens that arises as the result of their restricted gene flow and reduced recombination rates.

     

Real-Time Fluorescent Polymerase Chain Reaction Detection of Phytophthora ramorum and Phytophthora pseudosyringae Using Mitochondrial Gene Regions

ABSTRACT A real-time fluorescent polymerase chain reaction (PCR) detection method for the sudden oak death pathogen Phytophthora ramorum was developed based on mitochondrial DNA sequence with an ABI Prism 7700 (TaqMan) Sequence Detection System. Primers and probes were also developed for detecting P. pseudosyringae, a newly described species that causes symptoms similar to P. ramorum on certain hosts. The species-specific primer-probe systems were combined in a multiplex assay with a plant primer-probe system to allow plant DNA present in extracted samples to serve as a positive control in each reaction. The lower limit of detection of P. ramorum DNA was 1 fg of genomic DNA, lower than for many other described PCR procedures for detecting Phytophthora species. The assay was also used in a three-way multiplex format to simultaneously detect P. ramorum, P. pseudosyringae, and plant DNA in a single tube. P. ramorum was detected down to a 10(-5) dilution of extracted tissue of artificially infected rhododendron 'Cunningham's White', and the amount of pathogen DNA present in the infected tissue was estimated using a standard curve. The multiplex assay was also used to detect P. ramorum in infected California field samples from several hosts determined to contain the pathogen by other methods. The real-time PCR assay we describe is highly sensitive and specific, and has several advantages over conventional PCR assays used for P. ramorum detection to confirm positive P. ramorum finds in nurseries and elsewhere.     

Detection and Quantification of Phytophthora ramorum from California Forests Using a Real-Time Polymerase Chain Reaction Assay

ABSTRACT The timely and accurate detection of pathogens is a critical aid in the study of the epidemiology and biology of plant diseases. In the case of regulated organisms, the availability of a sensitive and reliable assay is essential when trying to achieve early detection of the pathogen. We developed and tested a real-time, nested polymerase chain reaction (PCR) assay for the detection of Phytophthora ramorum, causal agent of sudden oak death. This technique then was implemented as part of a widespread environmental screen throughout California. The method here described is sensitive, detecting less than 12 fg of pathogen DNA, and is specific for P. ramorum when tested across 21 Phytophthora spp. Hundreds of symptomatic samples from 33 sites in 14 California counties were assayed, resulting in the discovery of 10 new host species and 23 infested areas, including 4 new counties. With the exception of a single host, PCR-based discovery of new hosts and infested areas always was confirmed by traditional pathogen isolations and inoculation studies. Nonetheless, molecular diagnostics were key in early pathogen detection, and steered the direction of further research on this newly discovered and generalist Phytophthora species.     

Molecular diagnostics for fungal plant pathogens

Accurate identification of fungal phytopathogens is essential for virtually all aspects of plant pathology, from fundamental research on the biology of pathogens to the control of the diseases they cause. Although molecular methods, such as polymerase chain reaction (PCR), are routinely used in the diagnosis of human diseases, they are not yet widely used to detect and identify plant pathogens. Here we review some of the diagnostic tools currently used for fungal plant pathogens and describe some novel applications. Technological advances in PCR-based methods, such as real-time PCR, allow fast, accurate detection and quantification of plant pathogens and are now being applied to practical problems. Molecular methods have been used to detect several pathogens simultaneously in wheat, and to study the development of fungicide resistance in wheat pathogens. Information resulting from such work could be used to improve disease control by allowing more rational decisions to be made about the choice and use of fungicides and resistant cultivars. Molecular methods have also been applied to the study of variation in plant pathogen populations, for example detection of different mating types or virulence types. PCR-based methods can provide new tools to monitor the exposure of a crop to pathogen inoculum that are more reliable and faster than conventional methods. This information can be used to improve disease control decision making. The development and application of molecular diagnostic methods in the future is discussed and we expect that new developments will increase the adoption of these new technologies for the diagnosis and study of plant disease.     

Aggressiveness and its role in the adaptation of plant pathogens

Aggressiveness, the quantitative component of pathogenicity, and its role in the adaptation of plant pathogens are still insufficiently investigated. Using mainly examples of biotrophic and necrotrophic fungal pathogens of cereals and Phytophthora infestans on potato, the empirical knowledge on the nature of aggressiveness components and their evolution in response to host and environment is reviewed. Means of measuring aggressiveness components are considered, as well as the sources of environmental variance in these traits. The adaptive potential of aggressiveness components is evaluated by reviewing evidence for their heritability, as well as for constraints on their evolution, including differential interactions between host and pathogen genotypes and trade-offs between components of pathogenicity. Adaptations of pathogen aggressiveness components to host and environment are analysed, showing that: (i) selection for aggressiveness in pathogen populations can be mediated by climatic parameters; (ii) global population changes or remarkable population structures may be explained by variation in aggressiveness; and (iii) selection for quantitative traits can influence pathogen evolution in agricultural pathosystems and can result in differential adaptation to host cultivars, sometimes leading to erosion of quantitative resistance. Possible links with concepts in evolutionary ecology are suggested.     

A hypersensitive response was induced by virulent bacteria in transgenic tobacco plants overexpressing a plant ferredoxin-like protein (PFLP)

The hypersensitive response (HR) displayed by resistance plants against invading pathogens is a prominent feature of an incompatible plant pathogen interaction. It has been shown that tobacco cell cultures transgenic for a plant ferredoxin-like protein (PFLP) that functions as an electron acceptor of Photosystem I increased harpin-mediate HR. In this work we report increased bacterial disease resistance of pflp transgenic tobacco. Compared to the controls, four distinctive characteristics were found in the pflp-transgenics after inoculation with virulent bacterial cells Erwinia carotovora subsp. carotovora and Pseudomonas syringae pv. tabaci: (i) instead of typical disease symptoms, an HR-like necrosis was observed; (ii) the proliferation of the virulent pathogen was highly retarded; (iii) the expression of hsr203j, an HR marker gene, was apparently induced; (iv)H₂O₂ accumulation was induced immediately. Together, those results demonstrate that enhanced production of PFLP in the transgenic plant conditions the induction of a hypersensitive response during compatible pathogen attack.     

Plant community diversity influences vector behaviour and Barley yellow dwarf virus population structure

The species composition of a plant community can affect the distribution and abundance of other organisms including plant pathogens. The goal of this study was to understand the role of host diversity in the transmission of two Barley yellow dwarf virus (BYDV) species that share insect vectors and hosts. Greenhouse experiments measured the transmission rate of BYDV species PAV and PAS from infected oat plants to healthy agricultural and wild grasses and from these species back to healthy oat seedlings. In the field component of the study, the rate of spread of PAV and PAS was measured in monoculture plots planted with agricultural grasses. In greenhouse experiments, the aphid vector more readily transmitted PAV from agricultural grasses and more readily inoculated PAS to the wild grass species assayed. In the field experiment, disease prevalence was greater in wheat, but there was no difference in the rate of spread of PAV and PAS. These results indicate an interaction between vector and host genotype that selects for greater PAV transmission in grain crops, contributes to differences in disease prevalence between grass types, and maintains pathogen diversity within the larger plant community (i.e. agricultural and non‐agricultural hosts).     

What have we learned from studies of wild plant-pathogen associations?—the dynamic interplay of time,space and life-history

The interplay of host and pathogen life history traits with disease epidemiology and the selective pressures exerted on hosts drives genetic change and the long-term coevolutionary trajectories of host-pathogen associations. Many studies have addressed various aspects of the ways in which hosts and their pathogens interact but have tended to focus on individual populations, on comparisons made at single points in time, or on broader comparisons that confound patterns from different epidemiological and evolutionary units. While such studies provide valuable information, their essentially ‘static’ snap-shot nature limits the ability to interpret the nature of the underpinning coevolutionary processes. An increasing number of long-term studies involving repeat sampling of multiple interaction demes distributed across space are giving insight into the complexity of the numerical and genetic dynamics of host and pathogen interactions. These illustrate: (a) the ephemerality of disease in individual populations in contrast to its predictability at the metapopulation scale; (b) the spatial and temporal dynamics of selection ‘hot-spots’, rates of extinction and recolonization; and (c) differences in coevolutionary dynamics among demes within a metapopulation. Such long-term studies further emphasise the interplay between life history traits, time and space, and the importance of developing a framework to classify the seemingly daunting diversity of host-pathogen associations.     

Optimizing sampling strategies for nematode-transmitted viruses and their vectors1

The detection of virus-vector nematodes and the viruses they transmit depends upon the efficiency of the sampling and extraction procedures. A knowledge of the horizontal and vertical distribution and population dynamics of the vectors is required to maximize the chances of detecting small numbers of nematodes, while data on the size of virus patches are needed for quantifying the probability of finding the virus in the field. Information on the spatial and temporal distribution of both vectors and viruses is reviewed and, in light of the limited present knowledge, optimum sampling strategies are recommended.     

Sampling in seed health testing

ABSTRACT Seed health tests are usually performed on a sample of a seed lot; therefore, it is crucial that the test sample be as homogeneous as possible and representative of the lot. Seed sampling procedures appropriate for seed health testing have been developed by seed testing organizations such as the International Seed Testing Association and the Association of Official Seed Analysts. Seed lot size is generally not a constraint when the distribution of contaminated/infected seed in the lot is relatively homogeneous; if the distribution is heterogeneous, increased sampling intensity is required. Sample size is determined by the damage threshold (intolerable infection level) for the pathogen and the probability of detection desired, commonly 95 or 99%. The probability of detection at a given damage threshold is greater as sample size increases, and this probability and the appropriate sample size can be determined by statistical methods. Most seed health tests utilize qualitative data based on the presence or absence of the pathogen in the test sample, with the lot being rejected if the pathogen is detected in the sample and accepted if the sample is negative.     

Phytophthora infestans in a subtropical region: survival on tomato debris, temporal dynamics of airborne sporangia and alternative hosts

Little is known about inoculum dynamics of late blight caused by Phytophthora infestans in tropical/subtropical areas, particularly in Brazil. The objectives of the present study were to assess (i) the survival of the pathogen on stems, leaflets and tomato fruits, either buried or not in soil; (ii) the pathogenicity of P . infestans to mostly solanaceous plant species commonly found in Brazil that could act as inoculum reservoir; and (iii) the temporal dynamics of airborne sporangia. Phytophthora infestans survived in tomato plant parts for less than 36 days under greenhouse and field conditions. In greenhouse tests, pathogen structures were detected earlier on crop debris kept in dry than in wet soil conditions. Isolates of two clonal lineages of P. infestans , US-1 from tomato, and BR-1 from potato, were inoculated on 43 plant species. In addition to potato and tomato, Petunia  ×  hybrida and Nicotiana benthamiana were susceptible to the pathogen. Airborne inoculum was monitored with Rotorod and Burkard spore traps as well as with tomato and potato trap plants. Sporangia were sampled in most weeks throughout 2004 and in the first two weeks of 2005. Under tropical/subtropical conditions, airborne inoculum is abundant and is more important to late blight epidemics than inoculum from crop debris or alternative hosts.     

植物病害分子流行学概述

 本文概要地介绍了植物病理学新研究领域——植物病害分子流行学的基本概念、进展和在几个主要方面的研究实例。分子生物技术在病原鉴定方面得到了广泛应用;定量的分子生物技术在测定病菌初侵染源方面显示出特有的快速、准确的优势;分子流行学应用分子生物技术监测病害和病原菌群体的动态,克服了传统流行学方法的弱点;作为有力的补充,分子生物技术正在用于探讨和推测病原菌远距离传播的路径,并注重研究病原菌群体的时、空动态变化,病原菌的长期进化,以及与病害发展的关系;病原群体的竞争将得到更深入的研究以揭示其变化是如何导致植物病害大流行;应用分子流行学手段,植物抗病性的鉴定将大大加速和简化;病害防治策略的制定将具有更科学的依据。宏观与微观研究手段的结合将越来越显示其在植物病害流行学研究中的巨大潜力。     

The population dynamics of disease on short and long time-scales

Observational evidence is scarce concerning the distribution of plant pathogen population sizes or densities as a function of time-scale or spatial scale. For wild pathosystems we can only get indirect evidence from evolutionary patterns and the consequences of biological invasions. We have little or no evidence bearing on extermination of hosts by pathogens, or successful escape of a host from a pathogen. Evidence over the last couple of centuries from crops suggest that the abundance of particular pathogens in the spectrum affecting a given host can vary hugely on decadal time-scales. However, this may be an artefact of domestication and intensive cultivation. Host-pathogen dynamics can be formulated mathematically fairly easily–for example as SIR-type differential equation or difference equation models, and this has been the (successful) focus of recent work in crops. “Long-term” is then discussed in terms of the time taken to relax from a perturbation to the asymptotic state. However, both host and pathogen dynamics are driven by environmental factors as well as their mutual interactions, and both host and pathogen co-evolve, and evolve in response to external factors. We have virtually no information about the importance and natural role of higher trophic levels (hyperpathogens) and competitors, but they could also induce long-scale fluctuations in the abundance of pathogens on particular hosts. In wild pathosystems the host distribution cannot be modelled as either a uniform density or even a uniform distribution of fields (which could then be treated as individuals). Patterns of short-term density-dependence and the detail of host distribution are therefore critical to long-term dynamics. Host density distributions are not usually scale-free, but are rarely uniform or clearly structured on a single scale. In a (multiply structured) metapopulation with co-evolution and external disturbances it could well be the case that the time required to attain equilibrium (if it exists) based on conditions stable over a specified time-scale is longer than that time-scale. Alternatively, local equilibria may be reached fairly rapidly following perturbations but the meta-population equilibrium be attained very slowly. In either case, meta-stability on various time-scales is a more relevant than equilibrium concepts in explaining observed patterns.     

Modelling effects of vector acquisition threshold on disease progression in a perennial crop following deployment of a partially resistant variety

Deployment of resistant varieties is a key strategy to mitigating economic losses due to arthropod‐transmitted plant pathogens of perennial crops. In many cases, the best available resistant traits for introgression confer only partial resistance. Plants displaying partial resistance have lower pathogen titres than susceptible counterparts, but remain hosts for the pathogen. As partially resistant varieties maintain yield after infection, infected plants are unlikely to be rogued (i.e. removed). Accordingly, there is a risk that partially resistant plants could serve as a source of inoculum for pathogen spread to susceptible plants. Here, a mathematical model that tracked spread of an arthropod‐transmitted pathogen in a plant population consisting of susceptible and partially resistant plants was used to identify a threshold acquisition rate from partially resistant plants that resulted in limited spread of the pathogen from partially resistant plants to susceptible plants. The acquisition threshold from partially resistant plants varied with parameters influenced by disease management decisions such as number of vectors per plant, vector turnover, replacement of susceptible plants, and proportion of plants that were partially resistant. In model simulations, effects of deploying a partially resistant variety on disease incidence in a susceptible variety depended on the extent to which pathogen spread among susceptible plants was suppressed and acquisition rates from partially resistant plants. Collectively, the results indicate that risk of partially resistant plants serving as inoculum sources could be assessed prior to deployment, thereby enabling design of complementary disease management tactics to minimize economic losses in susceptible varieties following deployment.     

Why are plant pathogens under-represented in eco-climatic niche modelling?

Abstract

Eco-climatic niche models are powerful tools for assessing the potential range of plant pests and pathogens, widely applied in comprehensive pest risk assessments globally. We conducted a bibliometric analysis comparing the number of CLIMEX models developed for plant pathogens and plant arthropod pests. We found that plant pathogens were statistically significantly under-represented, with fungal plant pathogens less than half as likely as plant insect pests to be the subject of a published CLIMEX niche model. We explore key factors that may account for this disparity, including inconsistent experimental paradigms and lack of cross-disciplinary (i.e., plant pathology and modelling) expertise.