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A working group established in the framework of the EUPHRESCO European collaborative project aimed to compare and validate diagnostic protocols for the detection of “Flavescence dorée” (FD) phytoplasma in grapevines. Seven molecular protocols were compared in an interlaboratory test performance study where each laboratory had to analyze the same panel of samples consisting of DNA extracts prepared by the organizing laboratory. The tested molecular methods consisted of universal and group-specific real-time and end-point nested PCR tests. Different statistical approaches were applied to this collaborative study. Firstly, there was the standard statistical approach consisting in analyzing samples which are known to be positive and samples which are known to be negative and reporting the proportion of false-positive and false-negative results to respectively calculate diagnostic specificity and sensitivity. This approach was supplemented by the calculation of repeatability and reproducibility for qualitative methods based on the notions of accordance and concordance. Other new approaches were also implemented, based, on the one hand, on the probability of detection model, and, on the other hand, on Bayes’ theorem. These various statistical approaches are complementary and give consistent results. Their combination, and in particular, the introduction of new statistical approaches give overall information on the performance and limitations of the different methods, and are particularly useful for selecting the most appropriate detection scheme with regards to the prevalence of the pathogen. Three real-time PCR protocols (methods M4, M5 and M6 respectively developed by Hren (2007), Pelletier (2009) and under patent oligonucleotides) achieved the highest levels of performance for FD phytoplasma detection. This paper also addresses the issue of indeterminate results and the identification of outlier results. The statistical tools presented in this paper and their combination can be applied to many other studies concerning plant pathogens and other disciplines that use qualitative detection methods. [ABSTRACT FROM AUTHOR]

Xylella fastidiosa (Xf) is a quarantine plant pathogen bacterium originating from the Americas and that has emerged in Europe in 2013. Xf can be detected directly on plant macerate using molecular methods such as real-time PCR, which is a sensitive technique. However, some plants may contain components that can act as PCR reaction inhibitors, which can lead to false negative results or an underestimation of the bacterial concentration present in the analyzed plant sample. Droplet digital PCR (ddPCR) is an innovative tool based on the partitioning of the PCR reagents and the DNA sample into thousands of droplets, allowing the quantification of the absolute number of target DNA molecules present in a reaction mixture, or an increase of the detection sensitivity. In this study, a real-time PCR protocol, already used for Xf detection in the framework of official surveys in the European Union, was transferred and optimized for Xf detection using ddPCR. This new assay was evaluated and compared to the initial real-time PCR on five plant matrices artificially inoculated and on naturally infected plants. In our conditions, this new ddPCR enabled the detection of Xf on all artificially inoculated plant macerates with a similar limit of detection, or a slight benefit for Quercus ilex. Moreover, ddPCR improved diagnostic sensitivity as it enabled detection of Xf in samples of Polygala myrtifolia or Q. ilex that were categorized as negative or close to the limit of detection using the real-time PCR. Here, we report for the first time a ddPCR assay for the detection of the bacterium Xf. • A known Taqman qPCR for Xylella fastidiosa detection was transferred to a ddPCR test. • The ddPCR developed allows Xf detection in the five inoculated plants tested. • ddPCR improved diagnostic sensitivity of naturally infected oak and polygala samples. [ABSTRACT FROM AUTHOR]