BACKGROUND: Currently, real-time polymerase chain reaction (qPCR) is the technique most often used to quantify pathogen presence. Digital PCR (dPCR) is a new technique with the potential to have a substantial impact on plant pathology research owing to its reproducibility, sensitivity and low susceptibility to inhibitors. In this study, we evaluated the feasibility of using dPCR and qPCR to quantify Phytophthora nicotianae in several background matrices, including host tissues (stems and roots) and soil samples. RESULTS: In spite of the low dynamic range of dPCR (3 logs compared with 7 logs for qPCR), this technique proved to have very high precision applicable at very low copy numbers. The dPCR was able to detect accurately the pathogen in all type of samples in a broad concentration range. Moreover, dPCR seems to be less susceptible to inhibitors than qPCR in plant samples. Linear regression analysis showed a high correlation between the results obtained with the two techniques in soil, stem and root samples, with R(2) = 0.873, 0.999 and 0.995 respectively. CONCLUSIONS: These results suggest that dPCR is a promising alternative for quantifying soil-borne pathogens in environmental samples, even in early stages of the disease.
BACKGROUND: Currently, real-time polymerase chain reaction (qPCR) is the technique most often used to quantify pathogen presence. Digital PCR (dPCR) is a new technique with the potential to have a substantial impact on plant pathology research owing to its reproducibility, sensitivity and low susceptibility to inhibitors. In this study, we evaluated the feasibility of using dPCR and qPCR to quantify Phytophthora nicotianae in several background matrices, including host tissues (stems and roots) and soil samples. RESULTS: In spite of the low dynamic range of dPCR (3 logs compared with 7 logs for qPCR), this technique proved to have very high precision applicable at very low copy numbers. The dPCR was able to detect accurately the pathogen in all type of samples in a broad concentration range. Moreover, dPCR seems to be less susceptible to inhibitors than qPCR in plant samples. Linear regression analysis showed a high correlation between the results obtained with the two techniques in soil, stem and root samples, with R(2) = 0.873, 0.999 and 0.995 respectively. CONCLUSIONS: These results suggest that dPCR is a promising alternative for quantifying soil-borne pathogens in environmental samples, even in early stages of the disease.
Authors: Lucrecia Acosta Soto; Ana Belén Santísima-Trinidad; Fernando Jorge Bornay-Llinares; Marcos Martín González; José Antonio Pascual Valero; Margarita Ros Muñoz Journal: Biomed Res Int Date: 2017-03-09 Impact factor: 3.411
Authors: Katherine G Zulak; Belinda A Cox; Madeline A Tucker; Richard P Oliver; Francisco J Lopez-Ruiz Journal: Front Microbiol Date: 2018-04-13 Impact factor: 5.640
Authors: Sarah J Z Hansen; Wesley Morovic; Martha DeMeules; Buffy Stahl; Connie W Sindelar Journal: Front Microbiol Date: 2018-04-11 Impact factor: 5.640