In-field distribution of Plasmodiophora brassicae measured using quantitative real-time PCR

By Stefano Ghignone, on August 31st, 2012

A protocol using real-time polymerase chain reaction (PCR) for the direct detection and quantification of Plasmodiophora brassicae in soil samples was developed and used on naturally and artificially infested soil samples containing different concentrations of P. brassicae. Species-specific primers and a TaqMan fluorogenic probe were designed to amplify a small region of P. brassicae ribosomal DNA. Total genomic DNA was extracted and purified from soil samples using commercial kits. The amount of pathogen DNA was quantified using a standard curve generated by including reactions containing different amounts of a plasmid carrying the P. brassicae target sequence. The PCR assay was optimized to give high amplification efficiency and three to four copies of the target DNA sequence were detected. Regression analysis showed that the standard curve was linear over at least six orders of magnitude (R^2 > 0.99) and that the amplification efficiency was >92%. The detection limit in soil samples corresponded to 500 resting spores g−1 soil. The intersample reproducibility was similar to, or higher than, that of assays for other pathogens quantified in soil samples. Bait plants were used to validate the real-time PCR assay. The protocol developed was used to investigate the spatial distribution of P. brassicae DNA in different fields and a significant difference was found between in-field sampling points. The reproducibility of soil sampling was evaluated and showed no significant differences for samples with low levels of inoculum, whereas at higher levels differences occurred. Indicator kriging was used for mapping the probability of detecting P. brassicae within a 2-ha area of a field. A threshold level of 5 fg plasmid DNA g−1 soil, corresponding to approximately 3 × 10^3 P. brassicae resting spores g−1 soil, is suggested for growing resistant cultivars. The results provide a robust and reliable technique for predicting the risk of disease development and for assessing the distribution of disease within fields.