ABSTRACT
KEY MESSAGE: A group of genes that were upregulated in a resistant cultivar while downregulated in a susceptible cultivar in a transcriptomics analysis of potato challenged by Spongospora subterranea infection, did not show the same expression pattern at the protein level.
Subject(s)
Gene Expression Regulation, Plant , Plant Diseases , Solanum tuberosum , Gene Expression Profiling , Transcriptome , Plant Diseases/parasitology , Plant Pathology , Genes, Plant , Solanum tuberosum/genetics , Solanum tuberosum/parasitology , Gene Expression Regulation, Plant/physiology , Protozoan Infections , Plasmodiophorida , Disease Resistance/geneticsABSTRACT
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.
Subject(s)
Crops, Agricultural , Plant Diseases , Plant Pathology , Plant Diseases/microbiology , Crops, Agricultural/microbiology , Disease Resistance , Climate Change , XylellaABSTRACT
Disaster plant pathology addresses how natural and human-driven disasters impact plant diseases and the requirements for smart management solutions. Local to global drivers of plant disease change in response to disasters, often creating environments more conducive to plant disease. Most disasters have indirect effects on plant health through factors such as disrupted supply chains and damaged infrastructure. There is also the potential for direct effects from disasters, such as pathogen or vector dispersal due to floods, hurricanes, and human migration driven by war. Pulse stressors such as hurricanes and war require rapid responses, whereas press stressors such as climate change leave more time for management adaptation but may ultimately cause broader challenges. Smart solutions for the effects of disasters can be deployed through digital agriculture and decision support systems supporting disaster preparedness and optimized humanitarian aid across scales. Here, we use the disaster plant pathology framework to synthesize the effects of disasters in plant pathology and outline solutions to maintain food security and plant health in catastrophic scenarios. We recommend actions for improving food security before and following disasters, including (i) strengthening regional and global cooperation, (ii) capacity building for rapid implementation of new technologies, (iii) effective clean seed systems that can act quickly to replace seed lost in disasters, (iv) resilient biosecurity infrastructure and risk assessment ready for rapid implementation, and (v) decision support systems that can adapt rapidly to unexpected scenarios. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.
Subject(s)
Plant Diseases , Plant Diseases/prevention & control , Humans , Plant Pathology , Disasters , Climate Change , Food SecurityABSTRACT
Although improved knowledge on the movement of airborne plant pathogens is likely to benefit plant health management, generating this knowledge is often far more complicated than anticipated. This complexity is driven by the dynamic nature of environmental variables, diversity among pathosystems that are targeted, and the unique needs of each research group. When using a rotating-arm impaction sampler, particle collection is dependent on the pathogen, environment, research objectives, and limitations (monetary, environmental, or labor). Consequently, no design will result in 100% collection efficiency. Fortunately, it is likely that multiple approaches can succeed despite these constraints. Choices made during design and implementation of samplers can influence the results, and recognizing this influence is crucial for researchers. This article is for beginners in the art and science of using rotating-arm impaction samplers; it provides a foundation for designing a project, from planning the experiment to processing samples. We present a relatively nontechnical discussion of the factors influencing pathogen dispersal and how placement of the rotating-arm air samplers alters propagule capture. We include a discussion of applications of rotating-arm air samplers to demonstrate their versatility and potential in plant pathology research as well as their limitations.
Subject(s)
Plant Diseases , Plant Diseases/microbiology , Air Microbiology , Plant Pathology , Plants/microbiology , Environmental Monitoring/instrumentation , Environmental Monitoring/methodsABSTRACT
The landscape of scientific publishing is experiencing a transformative shift toward open access, a paradigm that mandates the availability of research outputs such as data, code, materials, and publications. Open access provides increased reproducibility and allows for reuse of these resources. This article provides guidance for best publishing practices of scientific research, data, and associated resources, including code, in The American Phytopathological Society journals. Key areas such as diagnostic assays, experimental design, data sharing, and code deposition are explored in detail. This guidance aligns with that observed by other leading journals. We hope the information assembled in this paper will raise awareness of best practices and enable greater appraisal of the true effects of biological phenomena in plant pathology.
Subject(s)
Plant Pathology , Reproducibility of Results , Publishing/standards , Guidelines as Topic , Access to Information , Information DisseminationABSTRACT
Plant viruses are a group of intracellular pathogens that persistently threaten global food security. Significant advances in plant virology have been achieved by Chinese scientists over the last 20 years, including basic research and technologies for preventing and controlling plant viral diseases. Here, we review these milestones and advances, including the identification of new crop-infecting viruses, dissection of pathogenic mechanisms of multiple viruses, examination of multilayered interactions among viruses, their host plants, and virus-transmitting arthropod vectors, and in-depth interrogation of plant-encoded resistance and susceptibility determinants. Notably, various plant virus-based vectors have also been successfully developed for gene function studies and target gene expression in plants. We also recommend future plant virology studies in China.
Subject(s)
Plant Pathology , Plant Viruses , Plant Diseases/genetics , Plants/genetics , Plants/metabolism , ChinaABSTRACT
Disease severity in plant pathology is often measured by the amount of a plant or plant part that exhibits disease symptoms. This is typically assessed using a numerical scale, which allows a standardized, convenient, and quick method of rating. These scales, known as quantitative ordinal scales (QOS), divide the percentage scale into a predetermined number of intervals. There are various ways to analyze these ordinal data, with traditional methods involving the use of midpoint conversion to represent the interval. However, this may not be precise enough, as it is only an estimate of the true value. In this case, the data may be considered interval-censored, meaning that we have some knowledge of the value but not an exact measurement. This type of uncertainty is known as censoring, and techniques that address censoring, such as survival analysis (SA), use all available information and account for this uncertainty. To investigate the pros and cons of using SA with QOS measurements, we conducted a simulation based on three pathosystems. The results showed that SA almost always outperformed midpoint conversion with data analyzed using a t test, particularly when data were not normally distributed. Midpoint conversion is currently a standard procedure. In certain cases, the midpoint approach required a 400% increase in sample size to achieve the same power as the SA method. However, as the mean severity increases, fewer additional samples are needed (approximately an additional 100%), regardless of the assessment method used. Based on these findings, we conclude that SA is a valuable method for enhancing the power of hypothesis testing when analyzing QOS severity data. Future research should investigate the wider use of survival analysis techniques in plant pathology and their potential applications in the discipline.
Subject(s)
Plant Diseases , Plant Pathology , Computer Simulation , Patient Acuity , Survival AnalysisABSTRACT
The field of plant pathology has revealed many of the mechanisms underlying the arms race, providing crucial knowledge and genetic resources for improving plant health. Although the host-microbe interaction seemingly favors rapidly evolving pathogens, it has also generated a vast evolutionary history of largely unexplored plant immunodiversity. We review studies that characterize the scope and distribution of genetic and ecological diversity in model and non-model systems with specific reference to pathogen effector diversity, plant immunodiversity in both cultivated species and their wild relatives, and diversity in the plant-associated microbiota. We show how the study of evolutionary and ecological processes can reveal patterns of genetic convergence, conservation, and diversification, and that this diversity is increasingly tractable in both experimental and translational systems. Perhaps most importantly, these patterns of diversity provide largely untapped resources that can be deployed for the rational engineering of durable resistance for sustainable agriculture.
Subject(s)
Plant Pathology , Plants/genetics , Biological EvolutionABSTRACT
Key principles pertaining to RNA biology not infrequently have their origins in plant virology. Examples have arisen from studies on viral RNA-intrinsic properties and the infection process from gene expression, replication, movement, and defense evasion to biotechnological applications. Since RNA is at the core of the central dogma in molecular biology, how plant virology assisted in the reinforcement or adaptations of this concept, while at other instances shook up elements of the doctrine, is discussed. Moreover, despite the negative effects of viral diseases in agriculture worldwide, plant viruses can be considered a scientific treasure trove. Today they remain tools of discovery for biotechnology, studying evolution, cell biology, and host-microbe interactions.
Subject(s)
Plant Pathology , Plant Viruses , Plant Viruses/genetics , RNA, Viral/genetics , RNA, Viral/metabolism , Plant DiseasesABSTRACT
One of the most challenging problems associated with the development of accurate and reliable application of computer vision and artificial intelligence in agriculture is that, not only are massive amounts of training data usually required, but also, in most cases, the images have to be properly labeled before models can be trained. Such a labeling process tends to be time consuming, tiresome, and expensive, often making the creation of large labeled datasets impractical. This problem is largely associated with the many steps involved in the labeling process, requiring the human expert rater to perform different cognitive and motor tasks in order to correctly label each image, thus diverting brain resources that should be focused on pattern recognition itself. One possible way to tackle this challenge is by exploring the phenomena in which highly trained experts can almost reflexively recognize and accurately classify objects of interest in a fraction of a second. As techniques for recording and decoding brain activity have evolved, it has become possible to directly tap into this ability and to accurately assess the expert's level of confidence and attention during the process. As a result, the labeling time can be reduced dramatically while effectively incorporating the expert's knowledge into artificial intelligence models. This study investigates how the use of electroencephalograms from plant pathology experts can improve the accuracy and robustness of image-based artificial intelligence models dedicated to plant disease recognition. Experiments have demonstrated the viability of the approach, with accuracies improving from 96% with the baseline model to 99% using brain generated labels and active learning approach.
Subject(s)
Brain Waves , Plant Pathology , Humans , Artificial Intelligence , Reproducibility of Results , ElectroencephalographyABSTRACT
Plant pathology plays a critical role in safeguarding plant health, food security, and food safety through science-based solutions to protect plants against recurring and emerging diseases. In addition, plant pathology contributed significantly to basic discoveries that have had broad impacts on the life sciences beyond plant pathology. In December 2021, The American Phytopathological Society (APS) conducted a survey among its members and among the readership of its journals to identify and rank key discoveries in plant pathology that have had broad impacts on science and/or practical disease management during the past half century. Based on the responses received, key discoveries that have broadly impacted the life sciences during that period include the Agrobacterium Ti plasmid and its mechanism in T-DNA transfer, bacterial ice nucleation, cloning of resistance genes, discovery of viroids, effectors and their mechanisms, pattern-triggered immunity and effector-triggered immunity, RNA interference and gene silencing, structure and function of R genes, transcription activator-like effectors, and type-III secretion system and hrp/hrc. Major advances that significantly impacted practical disease management include the deployment and management of host resistance genes; the application of disease models and forecasting systems; the introduction of modern systemic fungicides and host resistance inducers, along with a better understanding of fungicide resistance mechanisms and management; and the utilization of biological controls and suppressive soils, including the implementation of methyl-bromide alternatives. In this special issue, experts from the pertinent fields review the discovery process, recent progress, and impacts of some of the highest ranked discoveries in each category while also pointing out future directions for new discoveries in fundamental and applied plant pathology.
Subject(s)
Plant Pathology , Plant Diseases/microbiology , Plants/microbiology , Bacteria , Disease Management , Plant Immunity , Host-Pathogen InteractionsABSTRACT
KEY MESSAGE: Long-read sequencing technologies are revolutionizing the sequencing and analysis of plant and pathogen genomes and transcriptomes, as well as contributing to emerging areas of interest in plant-pathogen interactions, disease management techniques, and the introduction of new plant varieties or cultivars. Long-read sequencing (LRS) technologies are progressively being implemented to study plants and pathogens of agricultural importance, which have substantial economic effects. The variability and complexity of the genome and transcriptome affect plant growth, development and pathogen responses. Overcoming the limitations of second-generation sequencing, LRS technology has significantly increased the length of a single contiguous read from a few hundred to millions of base pairs. Because of the longer read lengths, new analysis methods and tools have been developed for plant and pathogen genomics and transcriptomics. LRS technologies enable faster, more efficient, and high-throughput ultralong reads, allowing direct sequencing of genomes that would be impossible or difficult to investigate using short-read sequencing approaches. These benefits include genome assembly in repetitive areas, creating more comprehensive and exact genome determinations, assembling full-length transcripts, and detecting DNA and RNA alterations. Furthermore, these technologies allow for the identification of transcriptome diversity, significant structural variation analysis, and direct epigenetic mark detection in plant and pathogen genomic regions. LRS in plant pathology is found efficient for identifying and characterization of effectors in plants as well as known and unknown plant pathogens. In this review, we investigate how these technologies are transforming the landscape of determination and characterization of plant and pathogen genomes and transcriptomes efficiently and accurately. Moreover, we highlight potential areas of interest offered by LRS technologies for future study into plant-pathogen interactions, disease control strategies, and the development of new plant varieties or cultivars.
Subject(s)
High-Throughput Nucleotide Sequencing , Plant Pathology , Sequence Analysis, DNA/methods , High-Throughput Nucleotide Sequencing/methods , Genomics , Plants/genetics , TechnologyABSTRACT
Cladosporium spp. are among the most important plant pathogens, plant endophytes, insect parasites and human pathogens in nature. The aim of this study was to increase the speed and accuracy of Cladosporium spp. spore counting using UV-visible spectrophotometry based on the regression model in a water suspension. Spores of C. ramotenellum AM55, C. limoniforme Br15, C. tenuissimum K15 and C. cladosporioides Ld13 fungi were diluted in sterile distilled water several times. Spore concentration/ml (SC) was counted with a hemocytometer. The spectrophotometer visible light absorption (ABS) was measured under 14 wavelengths from 300 to 950 nm for each dilution. The results showed that the morphological variation of the spores greatly affect the determination of the suitable wavelength. 650, 750, 500 and 400 nm wavelengths had the highest coefficient of determination (R2) values respectively for C. ramotenellum AM55, C. limoniforme Br15, C. tenuissimum K15 and C. cladosporioides Ld13 on the linear regression model. R2 values were 0.9874, 0.9647, 0.8856 and 0.9711 respectively, for the 650, 750, 500 and 400 nm wavelengths. The linear equation of SC = 107 × ABS-133,040 with the highest R2 value of 0.9532 had the best fit under a combinatorial regression model where SC and ABS of all Cladosporium spp. were presented. The proposed linear regression models can be used under in vivo and in vitro conditions for medicine or plant pathology studies which certainly increase the accuracy and speed of the future experiments compared to the hemocytometer method.
Subject(s)
Cladosporium , Plant Pathology , Humans , Spectrophotometry , Spores, Fungal , WaterABSTRACT
High-throughput sequencing is a basic tool of biological research, and it is extensively used in plant pathology projects. Here, we describe how to handle data coming from a variety of sequencing experiments, focusing on the analysis of Illumina reads. We describe how to perform genome assembly and annotation with DNA reads, correctly analyze RNA-seq data to discover differentially expressed genes, handle amplicon sequencing data from microbial communities, and utilize small RNA sequencing data to predict miRNA sequences and their putative targets.
Subject(s)
MicroRNAs , Plant Pathology , Base Sequence , High-Throughput Nucleotide Sequencing , MicroRNAs/genetics , Sequence Analysis, RNAABSTRACT
Nicotiana benthamiana is an indigenous plant species distributed across northern Australia. The laboratory accession (LAB) of N. benthamiana has become widely adopted as a model host for plant viruses, and it is distinct from other accessions morphologically, physiologically, and by having an attenuation-of-function mutation in the RNA-dependent RNA polymerase 1 (NbRdr1) gene, referred to as NbRdr1m. Recent historical evidence suggested LAB was derived from a 1936 collection by John Cleland at The Granites of the Northern Territory, although no scientific evidence was provided. We provide scientific evidence and further historical evidence supporting the origin of LAB as The Granites. Analysis of a herbarium specimen of N. benthamiana collected by Cleland in 1936 revealed that The Granites population contains plants heterozygous for the NbRdr1 locus, having both the functional NbRdr1 and the mutant NbRdr1m alleles. N. benthamiana was an important cultural asset actively utilised as the narcotic Pituri (chewing tobacco) by the Warlpiri Aboriginal people at the site, who prevented women of child-bearing age from consuming it. We propose that Aboriginal people selected some of the unique traits of LAB that have subsequently facilitated its adoption as a model plant, such as lack of seed dormancy, fast maturity, low nornicotine content, and gracility.
Subject(s)
Nicotiana , Plant Viruses , Female , Humans , Models, Biological , Native Hawaiian or Other Pacific Islander , Northern Territory , Plant Pathology , Plant Viruses/genetics , RNA-Dependent RNA Polymerase/genetics , Nicotiana/genetics , Tobacco, SmokelessABSTRACT
Transmission electron microscopy (TEM) is an important tool for observing the ultrastructure of plant virions and their host cells. The two main applicable TEM technologies used in plant virology are negative staining and ultrathin section. Negative staining is mainly used to observe the high-resolution structure of virus particles under a transmission electron microscope. Sample preparation for negative staining is convenient and fast, making it suitable for studying the virions in crude sap or purified solution. A modification of negative staining, by combining immunological reaction, named as technique of immuno-negative staining, is used to enrich or identify viruses. Ultrathin section is used for ultrastructural cytopathological studies in the virus-infected host cells, including the morphology of virus particles, the structure of viral induced inclusion bodies, the subcellular distribution of virions and the structural alteration of the host cell induced by viral infection. Such information is valuable to analyze the behavior of virus in replication, assembly, and intercellular transportation, and thus to understand the viral infection cycle. The present chapter describes the operation details of negative staining and ultrathin section TEM.
Subject(s)
Plant Pathology , Electrons , Microscopy, Electron, Transmission , Negative Staining , Plant Viruses , VirionABSTRACT
Engineered nanomaterials (ENM) have a high potential for use in several areas of agriculture including plant pathology. Nanoparticles (NPs) alone can be applied for disease management due to their antimicrobial properties. Moreover, nanobiosensors allow a rapid and sensitive diagnosis of pathogens because NPs can be conjugated with nucleic acids, proteins and other biomolecules. The use of ENM in diagnosis, delivery of fungicides and therapy is an eco-friendly and economically viable alternative. This review focuses on different promising studies concerning ENM used for plant disease management including viruses, fungi, oomycetes and bacteria; diagnosis and delivery of antimicrobials and factors affecting the efficacy of nanomaterials, entry, translocation and toxicity. Although much research is required on metallic NPs due to the possible risks to the final consumer, ENMs are undoubtedly very useful tools to achieve food security in the world. KEY POINTS: ⢠Increasing global population and fungicides have necessitated alternative technologies. ⢠Nanomaterials can be used for detection, delivery and therapy of plant diseases. ⢠The toxicity issues and safety should be considered before the use of nanomaterials.
Subject(s)
Metal Nanoparticles , Nanostructures , Plant Pathology , Agriculture , Plant Diseases/prevention & controlABSTRACT
But. Décrire les caractéristiques épidémiologiques et mycologiques de l'otomycose à Niamey. Méthodologie.Il s'est agi d'une étude rétrospective menée sur 3ans au service d'ORL et CCF de l'Hôpital Général de Référence, portant sur les patients chez qui le diagnostic d'otomycose a été posé. Les paramètres étudiés étaient épidémiologiques et mycologiques. Résultats. En 3 ans, nous avons enregistré 447 consultations pour otites dont 56 avaient une otomycose, soit une fréquence de 12,53% de l'ensemble des otites et 58,92% des otites externes. L'âgemoyen était de 35,75 ans (extrêmes de 2 et 70 ans). La tranche d'âge de 31 à 60 ans représentait 58,93% des patients. Nous avons retrouvéune prédominance féminine (67,85%), (p=0,0752). Les principaux facteurs favorisant l'otomycose étaient le nettoyage de l'oreille au coton tige ou à la plume de volaille : (53,57%),le port du turban ou de couvre-chef, (46,42%), la baignade (16.07%), l'étroitesse du conduit auditif externe (8,92%) et le port de prothèse auditive externe intra-conduit (5,35%,). Sur le plan mycologique, le Candida albicanset l'Aspergilus nigeront représenté respectivement 19,44% et 33,33% des espèces fongiques isolées en culture. Conclusion. L'otomycose est une infection fréquente en Orl à Niamey. Le nettoyage de l'oreille au coton tige ou à la plume de volaille venait au premier rang des facteurs favorisant l'otite fongique. L'Aspergilus nigeret le Candida albicansétaient les germes les plus fréquemment isolés.