Comparison of Droplet Digital PCR and Quantitative PCR Assays for Quantitative Detection of Xanthomonas citri Subsp. citri - Zhao, Yun (PLoS One, 2016)
Droplet digital polymerase chain reaction (ddPCR) is a novel molecular biology technique providing absolute quantification of target nucleic acids without the need for an external calibrator. Despite its emerging applications in medical diagnosis, there are few reports of its use for the detection of plant pathogens. This work was designed to assess the diagnosis potential of the ddPCR for absolute quantitative detection of Xanthomonas citri subsp. citri, a quarantine plant pathogenic bacterium that causes citrus bacterial canker in susceptible Citrus species. We transferred an established quantitative PCR (qPCR) assay for citrus bacterial canker diagnosis directly to the ddPCR format and compared the performance of the two methods. The qPCR assay has a broader dynamic range compared to the ddPCR assay and the ddPCR assay has a significantly higher degree of sensitivity compared to the qPCR assay. The influence of PCR inhibitors can be reduced considerably in the ddPCR assay because the collection of end-point fluorescent signals and the counting of binomial events (positive or negative droplets) are associated with a Poisson algorithm. The ddPCR assay also shows lower coefficient of variation compared to the qPCR assay especially in low target concentration. The linear association of the measurements by ddPCR and qPCR assays is strong (Pearson correlation = 0.8633; P<0.001). Receiver operating characteristic analysis indicates the ddPCR methodology is a more robust approach for diagnosis of citrus bacterial canker. In summary, the results demonstrated that the ddPCR assay has the potential for the quantitative detection of X. citri subsp. citri with high precision and accuracy as compared with the results from qPCR assay. Further studies are required to evaluate and validate the value of ddPCR technology in the diagnosis of plant disease and quarantine applications.