Walloon Agricultural Research Center Walloon Agricultural Research Center (CRA-W) * Agriculture and Natural Environment Department (D3) – ** Life Sciences Department (D1) Agricultural systems, Territory and Information Technologies Unit (U11) – Pest Biology and Monitoring Unit (U3) Léon Lacroix Building - Rue de Liroux, 9 - Emile Marchal Building – Rue de Liroux, 4 - B–5030 GEMBLOUX (Belgium) Tel : + 32 (0) Fax : + 32 (0) Tel : + 32 (0) Fax : + 32 (0) Estimation of - the normal standard variable Z for a wide range of concentration level - the corresponding probability Phytophthora ramorum is a fungus of the subclass of Oomycetes. Phytophthora ramorum has been found mainly on Rhododendron and Viburnum, but the list of plant species affected by the disease is large (Camelia, Kalmia, Syringa, Vaccinium, Arbutus, Quercus, Fagus, etc..). The manifestation of symptoms of Phytophthora ramorum is very rapid on Viburnum species, Camelia and Rhododendron species. Due to its regulated status, the identification of Phytophthora ramorum infection must be notified to the national Plant Protection Service (Commission decision 2002/757/EC). In this context, it is therefore highly recommended to have a reliable detection method. Determination of cycle cut off in real time PCR for the detection of regulated plant pathogens (Phytophthora ramorum) Viviane PLANCHON *, Robert OGER *, Anne CHANDELIER ** AGROSTAT 2010 February 23-26, 2010 Benevento, Italy Introduction and background Methodology and results First step : cut-off determination Conclusions Real time PCR : concepts of threshold cycle and cut-off The real-time PCR approach has gained increasing acceptance as a laboratory technique suitable for diagnostic purposes, notably for quarantine fungi. Given the high importance of an accurate detection for quarantine plant pathogens, and the risk of false positive or false negative results, a detection method must be correctly validated. Objectives To develop a statistical procedure to determine : the cycle cut off the corresponding limit of detection (LOD) of a real-time PCR used as a qualitative method (presence/absence) for the detection for a quarantine plant pathogen (Phytophtora ramorum). This approach takes into account the risks of false positive and false negative results, both probabilities being fixed at a defined value  The cycle cut off is an important parameter in the real time PCR interpretation, especially for samples with low pathogen concentration  It is a relative value which depends on numerous parameters : its determination should be based on validation data, at the laboratory level  A statistical approach has been developed to establish the cut-off and the LOD; the number of observations used to estimate the cut-off is a limiting factor for the estimation of the parameters of the truncated distribution  When using real time PCR, there is a risk of false positive and false negative (as with any detection method). These risks should be fixed and known by the customer Symtoms are leaf spots, shoots wilting and necrosis of twigs. The petiole is often necrotic. On Fagaceae (beech, oak), it forms cankers on the trunk and branches, with the presence of spots and viscous exudates (reddish brown to black). Real-time PCR = enzymatic reaction for the amplification of DNA fragment with a fluorescent detection. The production of fluorescence at each cycle depend on the concentration of targeted DNA in the reaction. Threshold Log (DRn) PCR cycle Ct threshold = fixed level of fluorescence in the exponential phase Ct value = PCR cycle number at which the fluorescence passes the threshold, enable to distinguish a positive from a negative sample Problematic results with late signals : Ct value close to the end of the PCR run The cycle cut off or cut-off = PCR cycles number above which any sample response is considered as a false positive Threshold Log (DRn) PCR cycle Ct1 Negative sample Positive sample Positive or negative sample (?) Ct2 Cut-off The cut-off is a relative value which depends on different parameters (method, threshold, PCR machine, reagents, …) Data : genomic DNA from a pure culture of P. ramorum diluted in DNA from healthy plant (Rhododendron) Population of positive samples Population of negative samples Cut-off ? Producer’s risk (risk of false positive results) = the risk to reject a negative sample Second step : LOD determination Threshold DRn PCR cycle Exponential phase Ct Third step : validation of the method Data set : Cut-off = LOD = 45 fg/PCR Normal quantiles Ct Similar results for the lab Data set 2009 : Cut-off = LOD = 53 fg/PCR Data : another data set ( ) negative samples : N=81 – 32 determined Ct values The best distribution = normal distribution Normality of the distribution for each concentration level Relationships between : the mean and the log transformed DNA concentration the standard deviation and the log transformed DNA concentration LOD (P = 95%) for a cut-off of ? P = probability corresponding to the normal standard variable Z Data : samples from the survey organised by the Belgian Plant Protection Service (N=120) in 2009 Negative sample (truncated dist.) Producer’s risk (1%) Consumer’s risk (5%) Determination of the parameters of the distribution of the Ct values for a set of 86 negative samples (truncated distribution), for a producer’s risk of 1% Distributions of Ct values for a set of positive samples (standard) at different concentrations PCR cycles Relative frequency (%) End of the PCR run Distribution of Ct values for a set of negative samples (truncated distribution) Cut-off = Producers’ risk (1%) Probability of non detection (5%) - 6 DNA concentration levels (1 ng, 100 pg, 10 pg, 1 pg, 100 fg, 10 fg/PCR) - N=30 replicates/concentration P = 95% ( µ) Z = σ LOD = 53 fg DNA/PCR Relative frequency (%) PCR cycles End of the PCR run Cut-off Producer’s risk (1%) Exponential distribution Ct = θ – (1/λ)*log (1 – F(x)) Ct = – 12.65* log (1 – 0.01) = Exponential quantiles Ct Cut-off = (a) (b) Best distribution based on RMSE : normal distribution X = 2,5 % in 2009 (N=120) Cut-off End of PCR) (40 cycles) PCR cycles Relative frequency (%) In this area, X % of the samples will be considered as negative while they are infected by P. ramorum below 53 fg with a probability of 95% In this area, 1 % of the negative samples will be considered as positive while they are negative Reference: Chandelier A, Planchon V, Oger R (2010). Determination of cycle cut off in real-time PCR for the detection of regulated plant pathogens. EPPO Bulletin. In press. To fit a distribution to these Ct values, the method of quantiles was used (PROC NLIN, SAS) to get initial parameters values. The choice of a distribution (normal, exponential, etc.), that gives the best adjustment of the left part of the negative samples truncated distribution, was based on root mean square error (RMSE). The distribution with the lowest RMSE was selected and its parameters used to evaluate Ct with a defined risk of false positive results. Consumer’s risk (risk of false negative results) = the risk to accept a positive sample = probability on non detection What is LOD (limit of detection) What is LOD (limit of detection) ? It corresponds to the minimum result (number of copies) which, with a stated probability, can be distinguished from a suitable blank value Positive and negative status are defined by reference methods Negative sample (truncated dist.)