Advances in molecular and optical detection strategies for grape downy mildew

Within vineyards, downy mildew (DM) of grapes, caused by Plasmopara viticola (Berk. & M.A. Curtis) Berl. & De Toni, is an aggressive polycyclic disease. This hemi-biotrophic oomycete pathogen overwinters in leaf litter as oospores and causes infections throughout the season as zoospore secondary inoculum spread by way of water splash or wind turbulence (Gessler, et al. 2011). Control of grapevine downy mildew is accomplished using chemical control as well as cultural practices, but resistance to numerous fungicides has developed over the years due to poor chemical rotation and excessive use.


Introduction
Within vineyards, downy mildew (DM) of grapes, caused by Plasmopara viticola (Berk. & M.A. Curtis) Berl. & De Toni, is an aggressive polycyclic disease. This hemi-biotrophic oomycete pathogen overwinters in leaf litter as oospores and causes infections throughout the season as zoospore secondary inoculum spread by way of water splash or wind turbulence (Gessler, et al. 2011). Control of grapevine downy mildew is accomplished using chemical control as well as cultural practices, but resistance to numerous fungicides has developed over the years due to poor chemical rotation and excessive use. To understand inoculum load and mutations in a field found throughout a growing season, molecular detection methods using quantitative polymerase chain reaction (qPCR) and TaqMan probes are used. These tools allow for pathogen quantification as well as low-inoculum detection within fields for asymptomatic diagnosis (Salcedo et al. 2021). Diagnostic tools are often paired with a method of disease sampling, like air or water collection, to understand pathogen levels across a site.

Spore trapping technologies and advances
Across numerous mildew pathosystems, spore trapping technologies have been implemented to monitor pathogen inoculum load, fungicide resistance, and pathogen genotype (Klosterman et al. 2016;Kunjeti et al. 2016;Thiessen et al. 2016). The ability of the spores to travel great distances contributes to high diversity within pathogen populations spread from one field, or state, to another (Aylor 2017). Trapping and quantifying spores to measure disease pressure throughout a season, within a field or vineyard, allows growers to better control disease levels while also understanding changes in population genetics. Coupling spore trapping devices with molecular techniques designed with the ability to detect mutated isolates provides growers with rapid identification of resistant or sensitive isolates within their fields that then can influence season-long fungicide applications. Spore trapping is, and has been, a common method for monitoring disease, with recent trends indicating an increased use in these methods. More recently, trap deployment is used for purposes beyond pathogen detection, such as identifying fungicide resistance and understanding associated shifting population structures. In contrast, impaction spore traps (Fig 2 B) are highly affordable, easily adapted, traps that are intended for molecular downstream analysis. While the impaction traps, designed by Dr. Walt Mahaffee (United States Department of Agriculture-Agricultural Research Service [USDA-ARS], Corvallis, OR), are very versatile in design and affordability, they require more seasonal maintenance. Trapping systems are chosen based on the crop being monitored, the location, cost, and the purpose for trapping. Due to agricultural requirements, such as location and canopy management, modifications to the trapping systems are often necessary. To accommodate these changes as well as improve ease of access to data, spore monitoring devices have been recently redesigned to optically observe aerial pathogens, requiring less molecular involvement for detection. The Scanit Technologies SporeCam™ (Fig. 2 C-D) uses autonomous technology to actively capture airborne particles onto a cassette to then be processed and analyzed by machine learning. The SporeCam™ device is a more expensive option, likely limiting its accessibility to larger growing operations. The collected data, including weather data, is then reported back to the scientist or grower managing the site using Wi-Fi or 4G wireless to provide quick and accurate information pertaining to the pathogen type and level found in a field (Scanit Technologies). The SporeCam™ can be taught specific disease signatures to recognize pathogens in a field, such as grapevine downy mildew. Spore classification can be carried out with spores as small as 6µm and as large as 1000µm, creating a range of pathogen morphology that can be captured, analyzed, and confirmed. When using the SporeCam™, downstream analysis is limited to optical analysis using machine learning and classification algorithms, leading to possible concerns in misidentification of pathogens with similar morphologies, like P. cubensis and P. humuli.
In this study, three spore trapping technologies were deployed at the Michigan State University Clarksville Research Station (Clarksville, MI): Burkard volumetric trap, impaction spore traps, and the Scanit SporeCam™. The objective of this study was to uncover the benefits and pitfalls of these individual spore trapping technologies and the subsequent molecular techniques as pertains to grapevine downy mildew and other grape pathogens.
A SporeCam™ training module device was taught the disease signature for P. viticola using a controlled environment at Michigan State University and pure cultures of numerous P. viticola isolates over a combined 6-week period. After completing training and data processing through Scanit, a SporeCam™ field device was installed and deployed in a vineyard site to be used alongside the Burkard and 12-impaction spore traps in an unsprayed 'Vignoles' block. The impaction spore trap custom design was acquired from Dr. Walt Mahaffee and deployed in similar manner to those used in Erysiphe necator studies (Thiessen et al. 2016). The impaction spore trap rods were collected twice a week, sampling every 3 and 4 days. This field experiment extended over the course of 13-weeks in 2021 and will be repeated in 2022. Upon collection, DNA was extracted from impaction rod samples to be used for downstream analysis using qPCR (Klosterman et al. 2014).

Plasmopara viticola: a species complex impacting diagnostic tools
Rouxel et al., 2014 describes P. viticola as a unique species (P. viticola sensu lato) complex infecting eight Vitis (grape) species. This characterization gives insight into the pathogen's infectivity and aggressiveness towards its various hosts. Currently, three P. viticola clades have been reported on cultivated grape: clades aestivalis, riparia, and vinifera (Fig. 3). This research describes P. viticola clade aestivalis as the predominant pathogen species in Eastern North America, with P. viticola clade vinifera and clade riparia as the other identified clades in the region. Currently, there are no methods for differentiating these key cryptic species of P. viticola sensu lato, thus making further analysis of the predominant species challenging without using expensive sequencing technology. Methods for rapid differentiation would provide better understanding of P. viticola clade distribution that could impact disease management decisions and strategies (Rouxel et al. 2014).
Riparia Vinifera Aestivalis The current marker system for P. viticola is designed using the internal transcribed spacer 1 (ITS1) and -5.8S rDNA to detect P. viticola as a general species (Valsesia et al. 2005). The ITS region in downy mildew species known to be variable and often contain significant heterogeneity and insertions, making amplification challenging (Salcedo et al. 2021). Within this study, new conserved amplification primers were developed along with a P. viticola sensu lato probe capable of detecting all pathogen types. Probes specific for P. viticola clade vinifera, riparia, and aestivalis were also developed to provide rapid detection of grapevine downy mildew, and identify the cryptic species present as well as the prevalence of each clade throughout the course of the growing season (Fig. 5). The locus used in this system is a Plasmopara-unique mitochondrial gene order, allowing for improved specificity and sensitivity (Crandall et al. 2018). Genus-and species-specific primers and probes were studied and developed to optimally detect P. viticola within vineyards from impaction style spore traps and Burkard Melinex-style tapes. The developed system was compared with the ITS system designed by Valsesia et al. 2005 to determine sensitivity and specificity when used both in pure and field samples. The sensu lato TaqMan probe and clade vinifera TaqMan probe were determined to be able to detect at approximately 1pg and 0.1pg respectively (Fig. 4). The clade aestivalis and riparia probes are still in the process of optimization. Primers and probes were validated against other Plasmopara spp. as well as species within the Peronosporales. To confirm clade identification, the ITS 1region was sequenced in the tested isolates.

Future directions and conclusions
Future work for this project includes the continued optimization of the P. viticola sensu-lato and clade TaqMan marker systems to detect each clade accurately, particularly at low sample volumes. These marker systems, and the ITS system designed by Valsesia et al. 2005, will be tested using DNA samples from Melinex-type tapes from a Burkard, spore rod samples from impaction traps, Tough Spot samples, and infected leaf tissue.
This work provides foundational data to encourage the focus of detection to shift from Burkard volumetric sampling to the cheaper, easily replicable option of impaction spore traps, which can be modified as needed. Impaction traps can be paired with the autonomous optical detection method using the Scanit SporeCam™, thus alleviating the need for long term rod sampling to identify initial inoculum levels. Upon initial SporeCam™ detection, the impaction traps can be deployed to identify molecular differences in a vineyard, or other field.
This study aims to better understand which methods of sampling and detecting are optimal for downy mildew of grape. The research performed in this study will provide the foundational knowledge needed to further analyze downy mildew populations regarding fungicide resistance and population diversity and structure. The development of diagnostic tools and technology used to monitor pathogen prevalence plays a critical role in integrative disease management for increased control of recurrent and resistant populations of downy mildew in vineyards.