Early Detection of Airborne Inoculum of Nothopassalora personata in Spore Trap Samples from Peanut Fields Using Quantitative PCR

It's a Trap! Part II: An Approachable Guide to Constructing and Using Rotating-Arm Air Samplers

An increasing number of researchers are looking to understand the factors affecting microbial dispersion but are often limited by the costs of commercially available air samplers. Some have reduced these costs by designing self-made versions; however, there are no published sampler designs, and there is limited information provided on the actual construction process. Lack of appropriate reference material limits the use of these self-made samplers by many researchers. This manuscript provides a guide to designing and constructing rotating-arm impaction air samplers by covering (i) environmental considerations, (ii) construction materials and equipment, (iii) the construction process, and (iv) air sampler deployment. Information regarding how to calculate rotational velocity, motor speed, and power supply requirements and to troubleshoot common issues is presented in an approachable format for individuals without experience in electronics or machining. Although many of the components discussed in this guide may change in their availability or be updated over time, this document is intended to serve as a "builder's guide" for future research into air sampling technology for phytopathology research.

It's a Trap! Part I: Exploring the Applications of Rotating-Arm Impaction Samplers in Plant Pathology

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.

Measuring the Distance and Effects of Weather Conditions on the Dispersal of Nothopassalora personata

Nothopassalora personata is one of the most economically severe pathogens of peanut in the United States. The fungus primarily relies on wind and rain for dispersal, which has been documented up to 10 m from an inoculum source. Spore traps have been used in a wide variety of pathosystems to study epidemiology, document detection, develop alert systems, and guide management programs. The objective of this study was to use spore traps and N. personata-specific qPCR primers to quantitatively evaluate dispersal of N. personata conidia at distances up to 70 m from an infected peanut field and to examine relationships between quantities captured and weather variables. Impaction spore samplers were placed at 4, 10, 30, 50, and 70 m from peanut fields at the Edisto Research and Education Center (six fields) and commercial peanut fields in Barnwell and Bamberg counties (one field each) from 2020 to 2022. Following initial detection, samples were collected at a 48-, 48-, 72-h interval until harvest. N. personata conidia were detected at all locations and distances, documenting dispersal up to 70 m from an inoculum source. This result is a reminder that volunteer management is crucial when rotating peanut in nearby fields. A model for predicting log spore quantities was developed using temperature and humidity variables. Temperature variables associated with observed sampling periods had a negative correlation with N. personata quantities, whereas parameters of relative humidity and mean windspeed were positively correlated.

Use of image analysis to assess radial growth of Passalora arachidicola and Nothopassalora personata on solid media

Despite significant research on early and late leaf spot diseases of peanut, in vitro study of the respective causal agents, Passalora arachidicola and Nothopassalora personata, has been limited due to cultural challenges that make growth of these fungi difficult to quantify with traditional methods. Studies were conducted to evaluate the practicality of image analysis to assess radial growth and tissue volume by correlating these assessments to dry mass. Image analysis was also used to estimate radial growth rates for these fungi over time. Tissue area and volume were significantly correlated to dry mass for P. arachidicola in two separate experiments, and for N. personata when medium had been removed from tissues prior to dry mass assessments. Tissue area densities were the same for P. arachidicola and Pseudocercospora smilacicola, evaluated as a nonstromatal cercosporoid comparison, whereas tissue volume densities were greater for P. archidicola and N. personata than P. smilacicola. A quadratic relationship was observed between radial growth and incubation time for all isolates evaluated. Growth rates of P. arachidicola isolates were 2 to 4 times faster than N. personata during the first week of incubation and slowed over time. Growth rates of NP18R, a phenotype variant of N. personata, increased after neighboring colonies met and was nearly 2.5 times faster than the fastest rates observed for P. arachidicola. These experiments demonstrate that when fungal tissues are observable, image analysis is a useful assessment tool for P. arachidicola and N. personata. Care should be taken to monitor fungal phenotypic changes in these species because phenotype degeneration can affect growth rates.

Dynamics of Puccinia striiformis f. sp. tritici Urediniospores in Longnan, a Critical Oversummering Region of China

Wheat stripe rust, caused by Puccinia striiformis f. sp. tritici Erikss. (Pst), is a devastating disease resulting in yield reduction. Because the temperature limits the overwintering and oversummering of Pst, it cannot complete the whole year cycle in most areas of China. Longnan, located in the southeast of Gansu Province, is one of the annual cycle areas of Pst, which can supply urediniospores in autumn to eastern wheat-growing areas in China. In this study, a TaqMan real-time quantitative PCR (TaqMan-qPCR) detection system for Pst urediniospores was established, and the detection limit was a single urediniospore. The dynamics of Pst urediniospores in Longnan were monitored by spore trapping and TaqMan-qPCR for 3 years. Meanwhile, the meteorological conditions including air temperature, relative humidity, and precipitation were recorded. Results showed that Pst urediniospores can be captured from March to December, and two peaks of urediniospore density appeared in May and June, respectively. The density of urediniospore is closely related to temperature and precipitation from March to June. In addition, we found that the density of Pst urediniospore had the peak value when the average air temperature was 10 to 21°C, and the relative humidity was 60 to 85% from May to June. The exponential model could describe the variation of Pst urediniospore density based on average temperature and precipitation from March to June. It is worth mentioning that the exponential model based on average temperature 7 days before spore capture has a great advantage in predicting the urediniospore density in the air. This study laid a foundation for establishment of a prediction model for wheat stripe rust based on the density of urediniospores and meteorological factors.

A Method for Capture and Detection of Crop Airborne Disease Spores Based on Microfluidic Chips and Micro Raman Spectroscopy

Airborne crop diseases cause great losses to agricultural production and can affect people's physical health. Timely monitoring of the situation of airborne disease spores and effective prevention and control measures are particularly important. In this study, a two-stage separation and enrichment microfluidic chip with arcuate pretreatment channel was designed for the separation and enrichment of crop disease spores, which was combined with micro Raman for Raman fingerprinting of disease conidia and quasi identification. The chip was mainly composed of arc preprocessing and two separated enriched structures, and the designed chip was numerically simulated using COMSOL multiphysics5.5, with the best enrichment effect at W2/W1 = 1.6 and W4/W3 = 1.1. The spectra were preprocessed with standard normal variables (SNVs) to improve the signal-to-noise ratio, which was baseline corrected using an iterative polynomial fitting method to further improve spectral features. Raman spectra were dimensionally reduced using principal component analysis (PCA) and stability competitive adaptive weighting (SCARS), support vector machine (SVM) and back-propagation artificial neural network (BPANN) were employed to identify fungal spore species, and the best discrimination effect was achieved using the SCARS-SVM model with 94.31% discrimination accuracy. Thus, the microfluidic-chip- and micro-Raman-based methods for spore capture and identification of crop diseases have the potential to be precise, convenient, and low-cost methods for fungal spore detection.

LAMP for in-field quantitative assessments of airborne grapevine downy mildew inoculum

AIMS

Cheap, rapid tools for measuring emissions of Plasmopara viticola sporangia directly in the field are required to protect grapevines efficiently and sustainably against downy mildew. To this end, we adapted an existing loop-mediated isothermal amplification (LAMP) protocol based on ITS2 sequences, coupled with a rotating-arm sampler and simple cell lysis, for the in-field measurement of airborne sporangia of P. viticola.

METHODS AND RESULTS

We estimated the sensitivity and specificity of the molecular reaction with an unpurified DNA template in controlled conditions, using the Droplet Digital PCR (ddPCR) as a reference. We show that the LAMP lower limit of quantification is 3.3 sporangia.m^-3 air sampled. Cell lysis in KOH solution was less efficient than CTAB for DNA extraction, but the repeatability of the method was good. We tested this protocol directly in a plot at Chateau Dillon (Blanquefort, France) in which we monitored P. viticola sporangia concentrations from March to October 2020 (88 samples which revealed concentrations ranging from 0 to 243 sporangia.m^-3 ). There was a significant quantitative correlation (R² = 0.52) between ddPCR and LAMP results.

CONCLUSION

LAMP analysis of an unpurified DNA matrix is a simple and reliable method for in-field estimations of the concentration of airborne P. viticola sporangia.

SIGNIFICANCE AND IMPACT OF STUDY

This study constitutes a first step towards the development of a regional grapevine downy mildew monitoring network in the vineyards of Bordeaux.

A Long-Amplicon Viability-qPCR Test for Quantifying Living Pathogens that Cause Bacterial Spot in Tomato Seed

Bacterial spot is one of the most serious diseases of tomato. It is caused by four species of Xanthomonas: X. euvesicatoria, X. gardneri, X. perforans, and X. vesicatoria. Contaminated or infected seed can be a major source of inoculum for this disease. The use of certified pathogen-free seed is one of the primary management practices to reduce the inoculum load in commercial production. Current seed testing protocols rely mainly on plating the seed extract and conventional PCR; however, the plating method cannot detect viable but nonculturable cells, and the conventional PCR assay has limited capability to differentiate DNA extracted from viable or dead bacterial cells. To improve the sensitivity and specificity of the tomato seed testing method for bacterial spot pathogens, a long-amplicon quantitative PCR (qPCR) assay coupled with propidium monoazide (PMA-qPCR) was developed to quantify selectively the four pathogenic Xanthomonas species in tomato seed. The optimized PMA-qPCR procedure was evaluated on pure bacterial suspensions, bacteria-spiked seed extracts, and seed extracts of inoculated and naturally infected seed. A crude DNA extraction protocol also was developed, and PMA-qPCR with crude bacterial DNA extracts resulted in accurate quantification of 10⁴ to 10⁸ CFU/ml of viable bacteria when mixed with dead cells at concentrations as high as 10⁷ CFU/ml in the seed extracts. With DNA purified from concentrated seed extracts, the PMA-qPCR assay was able to detect DNA of the target pathogens in seed samples spiked with ≥75 CFU/ml (about 0.5 CFU/seed) of the viable pathogens. Latent class analysis of the inoculated and naturally infected seed samples showed that the PMA-qPCR assay had greater sensitivity than plating the seed extracts on the semiselective modified Tween Medium B and CKTM media for all four target species. Being much faster and more sensitive than dilution plating, the PMA-qPCR assay has potential to be used as a standalone tool or in combination with the plating method to improve tomato seed testing and advance the production of clean seed.

Assessing the Use of DNA Detection Platforms Combined with Passive Wind-Powered Spore Traps for Early Surveillance of Potato and Tomato Late Blight in Canada

Quantitative PCR (qPCR), loop-mediated amplification (LAMP), and lateral flow strip-based recombinase polymerase amplification (RPA-LFS) assays were assessed for early detection of Phytophthora infestans, the global causal agent of potato and tomato late blight, on passive wind-powered spore traps known as Spornados. Spore traps were deployed in potato and tomato fields during the 2018, 2019, and 2020 growing seasons in the provinces of Alberta, British Columbia, Manitoba, Prince Edward Island, and Ontario. All assays used DNA extracts from Spornado cassette membranes targeting the P. infestans nuclear ribosomal internal transcribed spacer. A total of 1,003 Spornado samples were qPCR tested, yielding 115 positive samples for P. infestans spores. In further assessment of these samples, LAMP detected P. infestans in 108 (93.9%) of 115 qPCR positive samples, and RPA-LFS detected it in 103 (89.6%). None of the assays showed cross-reaction with other Phytophthora species or pathogenic fungi known to infect potato and tomato. The qPCR detected ≤1 fg of P. infestans DNA, and LAMP and RPA-LFS amplified 10 fg in as little as 10 min. All assays detected P. infestans before the first report of late blight symptoms in commercial potato or tomato fields within each region or province. The combination of Spornado passive samplers with qPCR, LAMP, or RPA-LFS proved a valuable spore trapping system for early surveillance of late blight in potato and tomato. Both LAMP and RPA-LFS showed potential as alternative approaches to qPCR for in-field monitoring of P. infestans.