Proficiency of real-time PCR detection of latent <em>Monilinia</em> spp. infection in nectarine flowers and fruit

Abstract

Rapid and reliable detection of Monilinia latent infections is needed to prevent and control dispersion of Monilinia spp. in infected localities and non-infected countries. A fast multiplex quantitative real-time PCR method (qPCR) for the detection and identification of Monilinia spp. latent infections in blossoms and fruit of nectarine trees (Prunus persica var. nucipersica) was tested in an inter-laboratory trial. The test performance study involving five laboratories was conducted to validate the sensitivity and specificity of several real-time PCR platforms for the detection of low amounts of Monilinia DNA (latent infections), using a common protocol, and to identify possible difficulties when these tests were implemented by diagnostic laboratories or national reference centres. The method has two hydrolysis probes distinguishing between Monilinia fructicola and M. fructigena/M. laxa. Validation included test performance accuracy, analytical specificity and sensitivity, repeatability, and reproducibility, as defined by standard PM7/98 of the European Plant Protection Organization (EPPO). All qPCR platforms detected Monilinia latent infections and mycelium samples with both hydrolysis probes, and healthy flowers and fruit samples gave negative results. The method specificity was consistent between different laboratories, despite different equipment used, and there were no laboratories with z-scores in the unacceptable region. Monilinia fructicola latent infection samples were correctly detected by all laboratories, but some M. laxa samples were cross-detected as if they were M. fructicola. Monilinia laxa cross-detection could be compensated by including the allelic discrimination step in qPCR runs, which permitted differentiating between M. fructicola and M. laxa samples. The inter-laboratory comparison demonstrated the robustness of the developed method and confirmed in-house validation data. This method could be used to detect latent infections of Monilinia in asymptomatic nectarine fruit and flowers.