Recovery of the soil fungal microbiome after steam disinfection to manage the plant pathogen Fusarium solani.

Soil disinfection using high temperatures via steam is a promising approach to manage plant pathogens, pests, and weeds. Soil steaming is a viable option for growers who are moving away from dependence on chemical soil fumigants, especially in plant nursery or high tunnel environments. However, there are few studies that investigate how soil steaming causes substantial disturbance to the soil by killing both target pathogens and other soil biota. Steaming treatments also change the trajectory of the soil microbiome as it reassembles over time. Growers are interested in the health of soils after using steam-disinfection, especially if a virulent pathogen colonizes the soil and then flourishes in a situation where there are very few microbes to suppress its growth. Should recruitment of a virulent pathogen occur in the soil, this could have devasting effects on seed germination, seedling establishment and survival. Beneficial microbes are often used to prevent the colonization of plant pathogens, especially after a soil-steaming event. Here, we experimentally test how soil fungal communities assemble after steaming disinfection. We introduce to steam-treated soil Fusarium solani, an important fungal pathogen of soybean and Trichoderma harzianum, a known beneficial fungus used for soilborne pathogen suppression. Results show that F. solani significantly affects the relative abundance and diversity of the soil fungal microbiome, however, T. harzianum does not mitigate the amount of F. solani in the steam treated soil. Within the T. harzianum microbial addition, the soil fungal communities were similar to the control (steaming only). This result suggests inoculating the soil with T. harzianum does not drastically alter the assembly trajectory of the soil fungal microbiome. Other soil amendments such as a combination of Trichoderma spp. or other genera could suppress F. solani growth and shift soil microbiome composition and function post-steaming, however, more experimental research is needed.

Rotting Grapes Don't Improve with Age: Cluster Rot Disease Complexes, Management, and Future Prospects.

Cluster rots can be devastating to grape production around the world. There are several late-season rots that can affect grape berries, including Botrytis bunch rot, sour rot, black rot, Phomopsis fruit rot, bitter rot, and ripe rot. Tight-clustered varieties such as 'Pinot gris', 'Pinot noir', and 'Vignoles' are particularly susceptible to cluster rots. Symptoms or signs for these rots range from discolored berries or gray-brown sporulation in Botrytis bunch rot to sour rot, which smells distinctly of vinegar due to the presence of acetic acid bacteria. This review discusses the common symptoms and disease cycles of these different cluster rots. It also includes useful updates on disease diagnostics and management practices, including cultural practices in commercial vineyards and future prospects for disease management. By understanding what drives the development of different cluster rots, researchers will be able to identify new avenues for research to control these critical pathogens.

A Multiplex TaqMan qPCR Assay for Detection and Quantification of Clade 1 and Clade 2 Isolates of Pseudoperonospora cubensis and Pseudoperonospora humuli.

The ability to detect and quantify aerially dispersed plant pathogens is essential for developing effective disease control measures and epidemiological models that optimize the timing for control. There is an acute need for managing the downy mildew pathogens infecting cucurbits and hop incited by members of the genus Pseudoperonospora (Pseudoperonospora cubensis clade 1 and 2 isolates and Pseudoperonospora humuli, respectively). A highly specific multiplex TaqMan quantitative polymerase chain reaction (PCR) assay targeting unique sequences in the pathogens' mitochondrial genomes was developed that enables detection of all three taxa in a single multiplexed amplification. An internal control included in the reaction evaluated whether results were influenced by PCR inhibitors that can make it through the DNA extraction process. Reliable quantification of inoculum as low as three sporangia in a sample was observed. The multiplexed assay was tested with DNA extracted from purified sporangia, infected plant tissue, and environmental samples collected on impaction spore traps samplers. The ability to accurately detect and simultaneously quantify all three pathogens in a single multiplexed amplification should improve management options for controlling the diseases they cause.

A multi-omics approach to solving problems in plant disease ecology.

The swift rise of omics-approaches allows for investigating microbial diversity and plant-microbe interactions across diverse ecological communities and spatio-temporal scales. The environment, however, is rapidly changing. The introduction of invasive species and the effects of climate change have particular impact on emerging plant diseases and managing current epidemics. It is critical, therefore, to take a holistic approach to understand how and why pathogenesis occurs in order to effectively manage for diseases given the synergies of changing environmental conditions. A multi-omics approach allows for a detailed picture of plant-microbial interactions and can ultimately allow us to build predictive models for how microbes and plants will respond to stress under environmental change. This article is designed as a primer for those interested in integrating -omic approaches into their plant disease research. We review -omics technologies salient to pathology including metabolomics, genomics, metagenomics, volatilomics, and spectranomics, and present cases where multi-omics have been successfully used for plant disease ecology. We then discuss additional limitations and pitfalls to be wary of prior to conducting an integrated research project as well as provide information about promising future directions.

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.