RÉSUMÉ
This scientometric study reviews the scientific literature and CABI distribution records published in 2022 to find evidence of major disease outbreaks and first reports of pathogens in new locations or on new hosts. This is the second time we have done this, and this study builds on our work documenting and analyzing reports from 2021. Pathogens with three or more articles identified in 2022 literature were Xylella fastidiosa, Bursaphelenchus xylophilus, Meloidogyne species complexes, 'Candidatus Liberibacter asiaticus', Raffaelea lauricola, Fusarium oxysporum formae specialis, and Puccinia graminis f. sp. tritici. Our review of CABI distribution records found 29 pathogens with confirmed first reports in 2022. Pathogens with four or more first reports were Meloidogyne species complexes, Pantoea ananatis, grapevine red globe virus, and Thekopsora minima. Analysis of the proportion of new distribution records from 2022 indicated that grapevine red globe virus, sweet potato chlorotic stunt virus, and 'Ca. Phytoplasma vitis' may have been actively spreading. As we saw last year, there was little overlap between the pathogens identified by reviewing scientific literature versus distribution records. We hypothesize that this lack of concordance is because of the unavoidable lag between first reports of the type reported in the CABI database of a pathogen in a new location and any subsequent major disease outbreaks being reported in the scientific literature, particularly because the latter depends on the journal policy on types of papers to be considered, whether the affected crop is major or minor, and whether the pathogen is of current scientific interest. Strikingly, too, there was also no overlap between species assessed to be actively spreading in this year's study and those identified last year. We hypothesize that this is because of inconsistencies in sampling coverage and effort over time and delays between the first arrival of a pathogen in a new location and its first report, particularly for certain classes of pathogens causing only minor or non-economically damaging symptoms, which may have been endemic for some time before being reported. In general, introduction of new pathogens and outbreaks of extant pathogens threaten food security and ecosystem services. Continued monitoring of these threats is essential to support phytosanitary measures intended to prevent pathogen introductions and management of threats within a country.
RÉSUMÉ
Increased imports of plants and timber through global trade networks provide frequent opportunities for the introduction of novel plant pathogens that can cross-over from commercial to natural environments, threatening native species and ecosystem functioning. Prevention or management of such outbreaks relies on a diversity of cross-sectoral stakeholders acting along the invasion pathway. Yet, guidelines are often only produced for a small number of stakeholders, missing opportunities to consider ways to control outbreaks in other parts of the pathway. We used the infection of common juniper with the invasive pathogen Phytophthora austrocedri as a case study to explore the utility of decision tools for managing outbreaks of plant pathogens in the wider environment. We invited stakeholders who manage or monitor juniper populations or supply plants or management advice to participate in a survey exploring their awareness of, and ability to use, an existing decision tree produced by a coalition of statutory agencies augmented with new distribution maps designed by the authors. Awareness of the decision tree was low across all stakeholder groups including those planting juniper for restoration purposes. Stakeholders requested that decision tools contain greater detail about environmental conditions that increase host vulnerability to the pathogen, and clearer examples of when management practices implicated in pathogen introduction or spread should not be adopted. The results demonstrate the need to set clear objectives for the purpose of decision tools and to frame and co-produce them with many different stakeholders, including overlooked groups, such as growers and advisory agents, to improve management of pathogens in the wider environment.
RÉSUMÉ
Plant diseases significantly impact food security and food safety. It was estimated that food production needs to increase by 50% to feed the projected 9.3 billion people by 2050. Yet, plant pathogens and pests are documented to cause up to 40% yield losses in major crops, including maize, rice, and wheat, resulting in annual worldwide economic losses of approximately US$220 billion. Yield losses due to plant diseases and pests are estimated to be 21.5% (10.1 to 28.1%) in wheat, 30.3% (24.6 to 40.9%) in rice, and 22.6% (19.5 to 41.4%) in maize. In March 2023, The American Phytopathological Society (APS) conducted a survey to identify and rank key challenges in plant pathology in the next decade. Phytopathology subsequently invited papers that address those key challenges in plant pathology, and these were published as a special issue. The key challenges identified include climate change effect on the disease triangle and outbreaks, plant disease resistance mechanisms and its applications, and specific diseases including those caused by Candidatus Liberibacter spp. and Xylella fastidiosa. Additionally, disease detection, natural and man-made disasters, and plant disease control strategies were explored in issue articles. Finally, aspects of open access and how to publish articles to maximize the Findability, Accessibility, Interoperability, and Reuse of digital assets in plant pathology were described. Only by identifying the challenges and tracking progress in developing solutions for them will we be able to resolve the issues in plant pathology and ultimately ensure plant health, food security, and food safety.
Sujet(s)
Produits agricoles , Maladies des plantes , Pathologie végétale , Maladies des plantes/microbiologie , Produits agricoles/microbiologie , Résistance à la maladie , Changement climatique , XylellaRÉSUMÉ
AbstractDisease control can induce both demographic and evolutionary responses in host-parasite systems. Foreseeing the outcome of control therefore requires knowledge of the eco-evolutionary feedback between control and system. Previous work has assumed that control strategies have a homogeneous effect on the parasite population. However, this is not true when control targets those traits that confer to the parasite heterogeneous levels of resistance, which can additionally be related to other key parasite traits through evolutionary trade-offs. In this work, we develop a minimal model coupling epidemiological and evolutionary dynamics to explore possible trait-dependent effects of control strategies. In particular, we consider a parasite expressing continuous levels of a trait-determining resource exploitation and a control treatment that can be either positively or negatively correlated with that trait. We demonstrate the potential of trait-dependent control by considering that the decision maker may want to minimize both the damage caused by the disease and the use of treatment, due to possible environmental or economic costs. We identify efficient strategies showing that the optimal type of treatment depends on the amount applied. Our results pave the way for the study of control strategies based on evolutionary constraints, such as collateral sensitivity and resistance costs, which are receiving increasing attention for both public health and agricultural purposes.
Sujet(s)
Parasites , Animaux , Évolution biologique , Interactions hôte-parasiteRÉSUMÉ
Increasing fungicide dose tends to lead to better short-term control of plant diseases. However, high doses select more rapidly for fungicide resistant strains, reducing long-term disease control. When resistance is qualitative and complete-i.e. resistant strains are unaffected by the chemical and resistance requires only a single genetic change-using the lowest possible dose ensuring sufficient control is well known as the optimal resistance management strategy. However, partial resistance (where resistant strains are still partially suppressed by the fungicide) and quantitative resistance (where a range of resistant strains are present) remain ill-understood. Here, we use a model of quantitative fungicide resistance (parametrized for the economically important fungal pathogen Zymoseptoria tritici) which handles qualitative partial resistance as a special case. Although low doses are optimal for resistance management, we show that for some model parametrizations the resistance management benefit does not outweigh the improvement in control from increasing doses. This holds for both qualitative partial resistance and quantitative resistance. Via a machine learning approach (a gradient-boosted trees model combined with Shapley values to facilitate interpretability), we interpret the effect of parameters controlling pathogen mutation and characterising the fungicide, in addition to the time scale of interest.
Sujet(s)
Résistance des champignons aux médicaments , Apprentissage machine , Modèles biologiques , Antifongiques/composition chimique , Antifongiques/pharmacologie , Mycoses/traitement médicamenteux , Mycoses/épidémiologie , HumainsRÉSUMÉ
A synoptic review of plant disease epidemics and outbreaks was made using two complementary approaches. The first approach involved reviewing scientific literature published in 2021, in which quantitative data related to new plant disease epidemics or outbreaks were obtained via surveys or similar methodologies. The second approach involved retrieving new records added in 2021 to the CABI Distribution Database, which contains over a million global geographic records of organisms from over 50,000 species. The literature review retrieved 186 articles, describing studies in 62 categories (pathogen species/species complexes) across more than 40 host species on six continents. Pathogen species with more than five articles were Bursaphelenchus xylophilus, 'Candidatus Liberibacter asiaticus', cassava mosaic viruses, citrus tristeza virus, Erwinia amylovora, Fusarium spp. complexes, F. oxysporum f. sp. cubense, Magnaporthe oryzae, maize lethal necrosis co-infecting viruses, Meloidogyne spp. complexes, Pseudomonas syringae pvs., Puccinia striiformis f. sp. tritici, Xylella fastidiosa, and Zymoseptoria tritici. Automated searches of the CABI Distribution Database identified 617 distribution records new in 2021 of 283 plant pathogens. A further manual review of these records confirmed 15 pathogens reported in new locations: apple hammerhead viroid, apple rubbery wood viruses, Aphelenchoides besseyi, Biscogniauxia mediterranea, 'Ca. Liberibacter asiaticus', citrus tristeza virus, Colletotrichum siamense, cucurbit chlorotic yellows virus, Erwinia rhapontici, Erysiphe corylacearum, F. oxysporum f. sp. cubense Tropical race 4, Globodera rostochiensis, Nothophoma quercina, potato spindle tuber viroid, and tomato brown rugose fruit virus. Of these, four pathogens had at least 25% of all records reported in 2021. We assessed two of these pathogens-tomato brown rugose fruit virus and cucurbit chlorotic yellows virus-to be actively emerging in/spreading to new locations. Although three important pathogens-'Ca. Liberibacter asiaticus', citrus tristeza virus, and F. oxysporum f. sp. cubense-were represented in the results of both our literature review and our interrogation of the CABI Distribution Database, in general, our dual approaches revealed distinct sets of plant disease outbreaks and new records, with little overlap. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.
Sujet(s)
Citrus , Rhizobiaceae , Maladies des plantes , Épidémies de maladiesRÉSUMÉ
Plant pathogens respond to selection pressures exerted by disease management strategies. This can lead to fungicide resistance and/or the breakdown of disease-resistant cultivars, each of which significantly threaten food security. Both fungicide resistance and cultivar breakdown can be characterised as qualitative or quantitative. Qualitative (monogenic) resistance/breakdown involves a step change in the characteristics of the pathogen population with respect to disease control, often caused by a single genetic change. Quantitative (polygenic) resistance/breakdown instead involves multiple genetic changes, each causing a smaller shift in pathogen characteristics, leading to a gradual alteration in the effectiveness of disease control over time. Although resistance/breakdown to many fungicides/cultivars currently in use is quantitative, the overwhelming majority of modelling studies focus on the much simpler case of qualitative resistance. Further, those very few models of quantitative resistance/breakdown which do exist are not fitted to field data. Here we present a model of quantitative resistance/breakdown applied to Zymoseptoria tritici, which causes Septoria leaf blotch, the most prevalent disease of wheat worldwide. Our model is fitted to data from field trials in the UK and Denmark. For fungicide resistance, we show that the optimal disease management strategy depends on the timescale of interest. Greater numbers of fungicide applications per year lead to greater selection for resistant strains, although over short timescales this can be oset by the increased control oered by more sprays. However, over longer timescales higher yields are attained using fewer fungicide applications per year. Deployment of disease-resistant cultivars is not only a valuable disease management strategy, but also oers the secondary benefit of protecting fungicide effectiveness by delaying the development of fungicide resistance. However, disease-resistant cultivars themselves erode over time. We show how an integrated disease management strategy with frequent replacement of disease-resistant cultivars can give a large improvement in fungicide durability and yields.
Sujet(s)
Fongicides industriels , Fongicides industriels/pharmacologie , Triticum/génétique , Maladies des plantes/génétique , Maladies des plantes/prévention et contrôle , Hérédité multifactorielle , Feuilles de plante , Résistance à la maladie/génétiqueRÉSUMÉ
We used a green fluorescent protein marker gene for paternity analysis to determine if virus infection affected male reproductive success of tomato in bumblebee-mediated cross-pollination under glasshouse conditions. We found that bumblebees that visited flowers of infected plants showed a strong preference to subsequently visit flowers of non-infected plants. The behavior of the bumblebees to move toward non-infected plants after pollinating virus-infected plants appears to explain the paternity data, which demonstrate a statistically significant â¼10-fold bias for fertilization of non-infected plants with pollen from infected parents. Thus, in the presence of bumblebee pollinators, CMV-infected plants exhibit enhanced male reproductive success.
RÉSUMÉ
Infectious diseases of plants present an ongoing and increasing threat to international biosecurity, with wide-ranging implications. An important challenge in plant disease management is achieving early detection of invading pathogens, which requires effective surveillance through the implementation of appropriate monitoring programmes. However, when monitoring relies on visual inspection as a means of detection, surveillance is often hindered by a long incubation period (delay from infection to symptom onset) during which plants may be infectious but not displaying visible symptoms. 'Sentinel' plants-alternative susceptible host species that display visible symptoms of infection more rapidly-could be introduced to at-risk populations and included in monitoring programmes to act as early warning beacons for infection. However, while sentinel hosts exhibit faster disease progression and so allow pathogens to be detected earlier, this often comes at a cost: faster disease progression typically promotes earlier onward transmission. Here, we construct a computational model of pathogen transmission to explore this trade-off and investigate how including sentinel plants in monitoring programmes could facilitate earlier detection of invasive plant pathogens. Using Xylella fastidiosa infection in Olea europaea (European olive) as a current high profile case study, for which Catharanthus roseus (Madagascan periwinkle) is a candidate sentinel host, we apply a Bayesian optimisation algorithm to determine the optimal number of sentinel hosts to introduce for a given sampling effort, as well as the optimal division of limited surveillance resources between crop and sentinel plants. Our results demonstrate that including sentinel plants in monitoring programmes can reduce the expected prevalence of infection upon outbreak detection substantially, increasing the feasibility of local outbreak containment.
Sujet(s)
Olea , Espèces sentinelles , Théorème de Bayes , Maladies des plantes , PlantesRÉSUMÉ
There is a strong consensus that selection for fungicide resistant pathogen strains can be most effectively limited by using applications of mixtures of fungicides designed to balance disease control against selection. However, how to do this in practice is not entirely characterized. Previous work indicates optimal mixtures of pairs of fungicides which are both at a high risk of resistance can be constructed using pairs of doses that select equally for both single resistant strains in the first year of application. What has not been addressed thus far is the important real-world case in which the initial levels of resistance to each fungicide differ, for example because the chemicals have been available for different lengths of time. We show how recommendations based on equal selection in the first year can be suboptimal in this case. We introduce a simple alternative approach, based on equalizing the frequencies of single resistant strains in the year that achieving acceptable levels of control is predicted to become impossible. We show that this strategy is robust to changes in parameters controlling pathogen epidemiology and fungicide efficacy. We develop our recommendation using a preexisting, parameterized model of Zymoseptoria tritici (the pathogen causing Septoria leaf blotch on wheat), which exemplifies the range of plant pathogens that predominantly spread clonally, but for which sexual reproduction forms an important component of the life cycle. We show that pathogen sexual reproduction can influence the rate at which fungicide resistance develops but does not qualitatively affect our optimal resistance management recommendation. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.
Sujet(s)
Fongicides industriels , Fongicides industriels/pharmacologie , Maladies des plantes/prévention et contrôle , Résistance des champignons aux médicaments , Reproduction , PlantesRÉSUMÉ
Previous models of growers' decision-making during epidemics have unrealistically limited disease management choices to just two options. Here, we expand previous game-theoretic models of grower decision-making to include three control options: a crop that is tolerant, resistant or susceptible to disease. Using tomato yellow leaf curl virus (TYLCV) as a case study, we investigate how growers can be incentivized to use different control options to achieve socially optimal outcomes. To do this, we consider the efforts of a 'social planner' who moderates the price of crops. We find that subsidizing a tolerant crop costs the social planner more in subsidies, as its use encourages selfishness and widespread adoption. Subsidizing a resistant crop, however, provides widespread benefits by reducing the prevalence of disease across the community of growers, including those that do not control, reducing the number of subsidies required from the social planner. We then use Gini coefficients to measure equitability of each subsidization scheme. This study highlights how grower behaviour can be altered using crop subsidies to promote socially optimal outcomes during epidemics.
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Population-scale effects of resistant or tolerant crop varieties have received little consideration from epidemiologists. When growers deploy tolerant crop, population-scale disease pressures are often unaffected. This only benefits growers using tolerant varieties, selfishly decreasing yields for others. However, resistant crop can reduce disease pressure for all. We coupled an epidemiological model with game theory to understand how this affects uptake of control. Each time a grower plants a new crop, they must decide whether to use an improved (i.e. tolerant/resistant) or unimproved variety. This decision is based on strategic-adaptive expectations in our model, with growers comparing last season's profit with an estimate of what is expected from the alternative crop. Despite the positive feedback loop promoting use of a tolerant variety whenever it is available, a mixed unimproved- and tolerant-crop equilibrium can persist. Tolerant crop can also induce bistability between a scenario in which all growers use tolerant crop and the disease-free equilibrium, where no growers do. However, due to 'free-riding' by growers of unimproved crop, resistant crop nearly always exists in a mixed equilibrium. This work highlights how growers respond to contrasting incentives caused by tolerant and resistant varieties, and the distinct effects on yields and population-scale deployment.
Sujet(s)
Agriculture , PlantesRÉSUMÉ
Cucumber mosaic virus (CMV), a major tomato pathogen, is aphid-vectored in the non-persistent manner. We investigated if CMV-induced volatile organic compounds (VOCs) or other virus-induced cues alter aphid-tomato interactions. Y-tube olfactometry showed that VOCs emitted by plants infected with CMV (strain Fny) attracted generalist (Myzus persicae) and Solanaceae specialist (Macrosiphum euphorbiae) aphids. Myzus persicae preferred settling on infected plants (3 days post-inoculation: dpi) at 1h post-release, but at 9 and 21 dpi, aphids preferentially settled on mock-inoculated plants. Macrosiphum euphorbiae showed no strong preference for mock-inoculated versus infected plants at 3 dpi but settled preferentially on mock-inoculated plants at 9 and 21 dpi. In darkness aphids showed no settling or migration bias towards either mock-inoculated or infected plants. However, tomato VOC blends differed in light and darkness, suggesting aphids respond to a complex mix of olfactory, visual, and other cues influenced by infection. The LS-CMV strain induced no changes in aphid-plant interactions. Experiments using inter-strain recombinant and pseudorecombinant viruses showed that the Fny-CMV 2a and 2b proteins modified tomato interactions with Macrosiphum euphorbiae and Myzus persicae, respectively. The defence signal salicylic acid prevents excessive CMV-induced damage to tomato plants but is not involved in CMV-induced changes in aphid-plant interactions.
Sujet(s)
Aphides , Cucumovirus , Infections à cytomégalovirus , Solanum lycopersicum , Composés organiques volatils , Animaux , Cucumovirus/métabolisme , Solanum lycopersicum/métabolisme , Maladies des plantes , Composés organiques volatils/métabolisme , Composés organiques volatils/pharmacologieRÉSUMÉ
While the spread of plant disease depends strongly on biological factors driving transmission, it also has a human dimension. Disease control depends on decisions made by individual growers, who are in turn influenced by a broad range of factors. Despite this, human behaviour has rarely been included in plant epidemic models. Considering Cassava Brown Streak Disease, we model how the perceived increase in profit due to disease management influences participation in clean seed systems (CSS). Our models are rooted in game theory, with growers making strategic decisions based on the expected profitability of different control strategies. We find that both the information used by growers to assess profitability and the perception of economic and epidemiological parameters influence long-term participation in the CSS. Over-estimation of infection risk leads to lower participation in the CSS, as growers perceive that paying for the CSS will be futile. Additionally, even though good disease management can be achieved through the implementation of CSS, and a scenario where all controllers use the CSS is achievable when growers base their decision on the average of their entire strategy, CBSD is rarely eliminated from the system. These results are robust to stochastic and spatial effects. Our work highlights the importance of including human behaviour in plant disease models, but also the significance of how that behaviour is included.
Sujet(s)
Manihot , Potyviridae , Humains , Maladies des plantes/prévention et contrôleRÉSUMÉ
Epidemics can particularly threaten certain sub-populations. For example, for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the elderly are often preferentially protected. For diseases of plants and animals, certain sub-populations can drive mitigation because they are intrinsically more valuable for ecological, economic, socio-cultural or political reasons. Here, we use optimal control theory to identify strategies to optimally protect a 'high-value' sub-population when there is a limited budget and epidemiological uncertainty. We use protection of the Redwood National Park in California in the face of the large ongoing state-wide epidemic of sudden oak death (caused by Phytophthora ramorum) as a case study. We concentrate on whether control should be focused entirely within the National Park itself, or whether treatment of the growing epidemic in the surrounding 'buffer region' can instead be more profitable. We find that, depending on rates of infection and the size of the ongoing epidemic, focusing control on the high-value region is often optimal. However, priority should sometimes switch from the buffer region to the high-value region only as the local outbreak grows. We characterize how the timing of any switch depends on epidemiological and logistic parameters, and test robustness to systematic misspecification of these factors due to imperfect prior knowledge.
Sujet(s)
COVID-19 , Épidémies , Quercus , Sujet âgé , Animaux , Humains , Maladies des plantes/prévention et contrôle , Facteurs de risque , SARS-CoV-2RÉSUMÉ
Aphids are the primary vector of plant viruses. Transient aphids, which probe several plants per day, are considered to be the principal vectors of non-persistently transmitted (NPT) viruses. However, resident aphids, which can complete their life cycle on a single host and are affected by agronomic practices, can transmit NPT viruses as well. Moreover, they can interfere both directly and indirectly with transient aphids, eventually shaping plant disease dynamics. By means of an epidemiological model, originally accounting for ecological principles and agronomic practices, we explore the consequences of fertilization and irrigation, pesticide deployment and roguing of infected plants on the spread of viral diseases in crops. Our results indicate that the spread of NPT viruses can be i) both reduced or increased by fertilization and irrigation, depending on whether the interference is direct or indirect; ii) counter-intuitively increased by pesticide application and iii) reduced by roguing infected plants. We show that a better understanding of vectors' interactions would enhance our understanding of disease transmission, supporting the development of disease management strategies.
Sujet(s)
Aphides/virologie , Produits agricoles/virologie , Vecteurs insectes/virologie , Maladies des plantes/virologie , Virus des plantes , Animaux , Lutte contre les insectes , Virus des plantes/génétique , Virus des plantes/physiologieRÉSUMÉ
Many plant viruses are transmitted by insect vectors. Transmission can be described as persistent or non-persistent depending on rates of acquisition, retention, and inoculation of virus. Much experimental evidence has accumulated indicating vectors can prefer to settle and/or feed on infected versus noninfected host plants. For persistent transmission, vector preference can also be conditional, depending on the vector's own infection status. Since viruses can alter host plant quality as a resource for feeding, infection potentially also affects vector population dynamics. Here we use mathematical modelling to develop a theoretical framework addressing the effects of vector preferences for landing, settling and feeding-as well as potential effects of infection on vector population density-on plant virus epidemics. We explore the consequences of preferences that depend on the host (infected or healthy) and vector (viruliferous or nonviruliferous) phenotypes, and how this is affected by the form of transmission, persistent or non-persistent. We show how different components of vector preference have characteristic effects on both the basic reproduction number and the final incidence of disease. We also show how vector preference can induce bistability, in which the virus is able to persist even when it cannot invade from very low densities. Feedbacks between plant infection status, vector population dynamics and virus transmission potentially lead to very complex dynamics, including sustained oscillations. Our work is supported by an interactive interface https://plantdiseasevectorpreference.herokuapp.com/. Our model reiterates the importance of coupling virus infection to vector behaviour, life history and population dynamics to fully understand plant virus epidemics.
Sujet(s)
Vecteurs insectes , Maladies des plantes , Virus des plantes , Animaux , Biologie informatique , Aptitude génétique , Interactions hôte-pathogène , Vecteurs insectes/génétique , Vecteurs insectes/physiologie , Vecteurs insectes/virologie , Modèles biologiques , Maladies des plantes/statistiques et données numériques , Maladies des plantes/virologie , Virus des plantes/génétique , Virus des plantes/pathogénicitéRÉSUMÉ
Plant disease outbreaks are increasing and threaten food security for the vulnerable in many areas of the world. Now a global human pandemic is threatening the health of millions on our planet. A stable, nutritious food supply will be needed to lift people out of poverty and improve health outcomes. Plant diseases, both endemic and recently emerging, are spreading and exacerbated by climate change, transmission with global food trade networks, pathogen spillover, and evolution of new pathogen lineages. In order to tackle these grand challenges, a new set of tools that include disease surveillance and improved detection technologies including pathogen sensors and predictive modeling and data analytics are needed to prevent future outbreaks. Herein, we describe an integrated research agenda that could help mitigate future plant disease pandemics.
Sujet(s)
Changement climatique , Écosystème , Sécurité alimentaire , Maladies des plantes , HumainsRÉSUMÉ
The phloem-limited 'Candidatus Liberibacter asiaticus' (Las) causes huanglongbing, a destructive citrus disease. Graft-inoculated potted plants were used to assess Las speed of movement in phloem in the greenhouse, and the impacts of temperature on plant colonization in growth-chamber experiments. For assessment of Las speed, plants were inoculated at the main stem and assessed over time by quantitative PCR (qPCR) or symptoms at various distances from the inoculum. For colonization, the plants were inoculated in one of two opposite top branches, maintained at from 8 to 20°C, from 18 to 30°C, or from 24 to 38°C daily range, and assessed by qPCR of samples taken from noninoculated shoots. For all experiments, frequencies of Las-positive sites were submitted to analysis of variance and binomial generalized linear model and logistic regression analyses. Probabilities of detecting Las in greenhouse plants were functions of time and distance from the inoculation site, which resulted in 2.9 and 3.8 cm day-1 average speed of movement. In growth chambers, the temperature impacted plant colonization by Las, new shoot emission, and symptom expression. After a 7-month exposure time, Las was absent in all new shoots in the cooler environment (average three per plant), and present in 70% at the milder environment (six shoots, severe symptoms) and 25% in the warmer environment (eight shoots, no visible symptoms). Temperature of 25.7°C was the optimum condition for plant colonization. This explains the higher impact and incidence of huanglongbing disease during the winter months or regions of milder climates in Brazil.
Sujet(s)
Citrus , Brésil , Liberibacter (genre) , Maladies des plantesRÉSUMÉ
Bean common mosaic virus (BCMV), bean common mosaic necrosis virus (BCMNV), and cucumber mosaic virus (CMV) are important pathogens of common bean (Phaseolus vulgaris), a crop vital for food security in sub-Saharan Africa. These viruses are vectored by aphids non-persistently, with virions bound loosely to stylet receptors. These viruses also manipulate aphid-mediated transmission by altering host properties. Virus-induced effects on host-aphid interactions were investigated using choice test (migration) assays, olfactometry, and analysis of insect-perceivable volatile organic compounds (VOCs) using gas chromatography (GC)-coupled mass spectrometry, and GC-coupled electroantennography. When allowed to choose freely between infected and uninfected plants, aphids of the legume specialist species Aphis fabae, and of the generalist species Myzus persicae, were repelled by plants infected with BCMV, BCMNV, or CMV. However, in olfactometer experiments with A. fabae, only the VOCs emitted by BCMNV-infected plants repelled aphids. Although BCMV, BCMNV, and CMV each induced distinctive changes in emission of aphid-perceivable volatiles, all three suppressed emission of an attractant sesquiterpene, α-copaene, suggesting these three different viruses promote migration of virus-bearing aphids in a similar fashion.