Area Wide Monitoring of Plant and Honey Bee (Apis mellifera) Viruses in Blueberry (Vaccinium corymbosum) Agroecosystems Facilitated by Honey Bee Pollination.

Healthy agroecosystems are dependent on a complex web of factors and inter-species interactions. Flowers are hubs for pathogen transmission, including the horizontal or vertical transmission of plant-viruses and the horizontal transmission of bee-viruses. Pollination by the European honey bee (Apis mellifera) is critical for industrial fruit production, but bees can also vector viruses and other pathogens between individuals. Here, we utilized commercial honey bee pollination services in blueberry (Vaccinium corymbosum) farms for a metagenomics-based bee and plant virus monitoring system. Following RNA sequencing, viruses were identified by mapping reads to a reference sequence database through the bioinformatics portal Virtool. In total, 29 unique plant viral species were found at two blueberry farms in British Columbia (BC). Nine viruses were identified at one site in Ontario (ON), five of which were not identified in BC. Ilarviruses blueberry shock virus (BlShV) and prune dwarf virus (PDV) were the most frequently detected viruses in BC but absent in ON, while nepoviruses tomato ringspot virus and tobacco ringspot virus were common in ON but absent in BC. BlShV coat protein (CP) nucleotide sequences were nearly identical in all samples, while PDV CP sequences were more diverse, suggesting multiple strains of PDV circulating at this site. Ten bee-infecting viruses were identified, with black queen cell virus frequently detected in ON and BC. Area-wide bee-mediated pathogen monitoring can provide new insights into the diversity of viruses present in, and the health of, bee-pollination ecosystems. This approach can be limited by a short sampling season, biased towards pollen-transmitted viruses, and the plant material collected by bees can be very diverse. This can obscure the origin of some viruses, but bee-mediated virus monitoring can be an effective preliminary monitoring approach.

Screening for Exotic Forest Pathogens to Increase Survey Capacity Using Metagenomics.

Anthropogenic activities have a major impact on the global environment. Canada's natural resources are threatened by the spread of fungal pathogens, which is facilitated by agricultural practices and international trade. Fungi are introduced to new environments and sometimes become established, in which case they can cause disease outbreaks resulting in extensive forest decline. Here, we describe how a nationwide sample collection strategy coupled to next-generation sequencing (NGS) (i.e., metagenomics) can achieve fast and comprehensive screening for exotic invasive species. This methodology can help provide guidance to phytopathology stakeholders such as regulatory agencies. Several regulated invasive species were monitored by processing field samples collected over 3 years (2013 to 2015) near high-risk areas across Canada. Fifteen sequencing runs were required on the Ion Torrent platform to process 398 samples that yielded 45 million reads. High-throughput screening of fungal and oomycete operational taxonomic units using customized fungi-specific ribosomal internal transcribed spacer 1 barcoded primers was performed. Likewise, Phytophthora-specific barcoded primers were used to amplify the adenosine triphosphate synthase subunit 9-nicotinamide adenine dinucleotide dehydrogenase subunit 9 spacer. Several Phytophthora spp. were detected by NGS and confirmed by species-specific quantitative polymerase chain reaction (qPCR) assays. The target species Heterobasidion annosum sensu stricto could be detected only through metagenomics. We demonstrated that screening target species using a variety of sampling techniques and NGS-the results of which were validated by qPCR-has the potential to increase survey capacity and detection sensitivity, reduce hands-on time and costs, and assist regulatory agencies to identify ports of entry. Considering that early detection and prevention are the keys in mitigating invasive species damage, our method represents a substantial asset in plant pathology management.

Advances in Diagnostics of Downy Mildews: Lessons Learned from Other Oomycetes and Future Challenges.

Downy mildews are plant pathogens that damage crop quality and yield worldwide. Among the most severe and notorious crop epidemics of downy mildew occurred on grapes in the mid-1880s, which almost destroyed the wine industry in France. Since then, there have been multiple outbreaks on sorghum and millet in Africa, tobacco in Europe, and recent widespread epidemics on lettuce, basil, cucurbits, and spinach throughout North America. In the mid-1970s, loss of corn to downy mildew in the Philippines was estimated at US$23 million. Today, crops that are susceptible to downy mildews are worth at least $7.5 billion of the United States' economy. Although downy mildews cause devastating economic losses in the United States and globally, this pathogen group remains understudied because they are difficult to culture and accurately identify. Early detection of downy mildews in the environment is critical to establish pathogen presence and identity, determine fungicide resistance, and understand how pathogen populations disperse. Knowing when and where pathogens emerge is also important for identifying critical control points to restrict movement and to contain populations. Reducing the spread of pathogens also decreases the likelihood of sexual recombination events and discourages the emergence of novel virulent strains. A major challenge in detecting downy mildews is that they are obligate pathogens and thus cannot be cultured in artificial media to identify and maintain specimens. However, advances in molecular detection techniques hold promise for rapid and in some cases, relatively inexpensive diagnosis. In this article, we discuss recent advances in diagnostic tools that can be used to detect downy mildews. First, we briefly describe downy mildew taxonomy and genetic loci used for detection. Next, we review issues encountered when identifying loci and compare various traditional and novel platforms for diagnostics. We discuss diagnosis of downy mildew traits and issues to consider when detecting this group of organisms in different environments. We conclude with challenges and future directions for successful downy mildew detection.