The infection of Pseudomonas syringae pv. actinidiae in kiwifruit is currently assessed by numerous methodologies, each with their own limitations. Most studies are based on either a laborious method of growth quantification of the pathogen or qualitative assessments by visual scoring following stem or cutting inoculation. Additionally, when assessing for resistance against specific pathogen effectors, confounding interactions between multiple genes in the pathogen can make mapping resistance phenotypes nearly impossible. Here we present robust alternative methods to quantify pathogen load based on rapid bacterial DNA quantification by PCR, the use of Pseudomonas fluorescens (Pfo), and a transient reporter eclipse assay, for assessing resistance conferred by isolated bacterial avirulence genes. These assays compare well with bacterial plate counts to assess bacterial colonization as a result of plant resistance activation. The DNA-based quantification, when coupled with the Pfo and reporter eclipse assays to independently identify bacterial avirulence genes, is rapid, highly reproducible, and scalable for high-throughput screens of multiple cultivars or genotypes. Application of these methodologies will allow rapid and high-throughput identification of resistant cultivars and the bacterial avirulence genes they recognize, facilitating resistance gene discovery for plant breeding programs.

Chemical treatments are used widely in agricultural and natural settings to protect plants from diseases; however, they may exert an important selection pressure on plant pathogens, promoting the development of tolerant isolates through adaptive evolution. Phosphite is used to manage diseases caused by Phytophthora species which include a large number of the most economically damaging plant pathogens worldwide. Phosphite controls the growth of Phytophthora species in planta without killing it; as a result, isolates can develop tolerance to phosphite after prolonged exposure. We investigated the inter- and intra-specific variability in phosphite tolerance of eleven Phytophthora species, including P. ramorum, an internationally important, highly regulated pathogen. Phytophthora ramorum is a good model system because it is comprised of multiple genetically homogeneous lineages. Seven species were found to be consistently sensitive to phosphite based on the low Effective Concentration (EC) 50 values of all isolates tested (amount of phosphite required to inhibit mycelial growth by 50% relative to growth in the absence of phosphite). However, P. ramorum, P. lateralis, P. crassamura and P. cambivora showed intraspecific variability in sensitivity to phosphite, with at least one isolate showing significantly higher tolerance than the other isolates. Within the three P. ramorum evolutionarily divergent lineages tested, NA1 was the most susceptible to phosphite, the NA1 and EU1 lineages showed intralineage variability and the NA2 lineage showed a decreased sensitivity to phosphite overall as all isolates were relatively tolerant. This finding is relevant because NA1 is dominant in the wild and can be controlled using phosphite, while the EU1 lineage has recently been identified in the wild and is phosphite-tolerant, making the treatment approach potentially less effective. Phytophthora ramorum, P. lateralis and P. crassamura are either selfing, homothallic species, or are known to reproduce exclusively clonally, indicating tolerance to phosphite can emerge even in the absence of sexual recombination.

Pseudomonas syringae pv. actinidiae (Psa) is the etiological agent of kiwifruit canker disease, causing severe economic losses in kiwifruit production areas around the world. Rapid diagnosis, understanding of bacterial virulence and rate of infection in kiwifruit cultivars is important in applying effective measures of disease control. Psa load in kiwifruit is currently determined by a labor-intense colony counting method with no high-throughput and specific quantification method being validated. In this work we used three alternative Psa quantification methods in two infected kiwifruit cultivars: start of growth time, quantitative qPCR (qPCR), and droplet digital PCR (ddPCR). Method performance in each case was compared to the colony counting method. Methods were validated using calibration curves obtained with serial dilutions of Psa3 inoculum and standard growth curves obtained from kiwifruit samples infected with Psa3 inoculum. All three alternative methods showed high correlation (r > 0.85) with the colony counting method. qPCR and ddPCR were very specific, sensitive (5 × 102 CFU/cm2), highly correlated to each other (r = 0.955) and flexible allowing for sample storage. The inclusion of a kiwifruit biomass marker increased the methods’ accuracy. The qPCR method was efficient and allowed for high-throughput processing and the ddPCR method showed highly accurate results but was more expensive and time consuming. While not ideal for high-throughput processing, ddPCR was useful in developing accurate standard curves for the qPCR method. The combination of the two methods is high-throughput, specific for Psa3 quantification and useful for research studies e.g. disease phenotyping and host-pathogen interactions.

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