European Union Reference Laboratory for monitoring bacteriological and viral contamination of bivalve molluscs

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1 European Union Reference Laboratory for monitoring bacteriological and viral contamination of bivalve molluscs Guidance note for the determination of limit of detection (LOD95) and limit of quantification (LOQ) characteristics for the method for quantification of norovirus in oysters INTRODUCTION This document comprises guidance from the EURL for monitoring bacterial and viral contamination of bivalve molluscs, to laboratories wishing to determine limit of detection (LOD 95) and limit of quantification (LOQ) characteristics for the method for quantification of norovirus in oysters as applied in their laboratory. Many different approaches to determination of LOD 95 and LOQ are available; this document describes a method using a log 2 dilution series of norovirus GI and GII prepared in oyster supernatant. Multiple subsamples at each level of the dilution series are tested, and the s used to determine LOD 95 using a probability of detection function recommended by ISO/TC 34/SC 9/WG2 Statistics. The LOQ is determined as the lowest level above the LOD 95 where the standard deviation of the log-transformed s is <0.33. This guidance is suitable for characterisation of methods compliant with the forthcoming reissue of ISO ; Microbiology of the food chain -- Horizontal method for determination of hepatitis A virus and norovirus in food using real-time RT-PCR -- Part 1: Method for quantification, for example the method described in the EURL generic protocol for Quantitative detection of norovirus and hepatitis A virus in bivalve molluscan shellfish:- For designated testing laboratories taking part in the forthcoming EFSA EU European baseline survey of norovirus in oysters it is an obligatory requirement to report LOQ:- For designated laboratories that have not already determined their LOQ, this guidance document can be considered a suitable approach for determining LOQ for the method detailed in their baseline survey bench protocol. Page 1 of 8

2 REPLICATION A minimum of 10 replicate extractions at each contamination level should be used to generate LOD 95 and LOQ characteristics using the methods described below. This allows for a small number of missing data points due to unacceptable RT-PCR inhibition or extraction efficiency s. The use of fewer replicates, or the presence of large numbers of missing data points due to unacceptable RT-PCR inhibition or extraction efficiency s will in a less robust estimate of LOD and LOQ values. NEGATIVE OYSTER SUPERNATANT Dissect sufficient norovirus-negative oysters to produce at least 60g digestive tissues. NOTE: the norovirus-negativity of the oysters used as matrix in this procedure should be established through a suitable testing procedure, e.g. testing of multiple subsamples of oysters with increased numbers of real-time RT-PCR replicates. In addition, determination of typical extraction efficiency and RT-PCR inhibition levels for the oysters used to produce the supernatant should be determined, to ensure that use of supernatant from these oysters is unlikely to in large numbers of unacceptable s (see above). Split the digestive tissues into aliquots of no more than 10g. Carry out virus extraction on all aliquots by proteinase K digestion as described in the method protocol undergoing characterisation, but modified such that the amount of proteinase K solution and process control virus material is increased proportionately to the quantity of digestive tissues used (e.g. with 10g digestive tissues use 10ml proteinase K solution and 50µl process control virus material). After virus extraction pool together supernatant from all extractions. Record the weight in g of digestive tissues processed and volume of supernatant recovered. Remove a 1.5ml portion and store both this and the remaining supernatant at -20 C. NOTE: an absolute minimum of 55ml supernatant must be produced by this procedure; if less than this amount is produced the process should be repeated with additional oysters and the supernatants pooled together. INITIAL CALIBRATION EXTRACTIONS NOTE: the s generated by the calibration extractions do not form part of the method characterisation data. This part of the process is designed to help each lab optimize contamination levels for the method characterisation. The EURL may be able to supply norovirus stock materials to laboratories upon request. In this case additional guidance on contamination for the initial calibration extractions will be supplied. Defrost the 1.5ml portion of digestive tissue supernatant. Use both GI and GII norovirus stocks to artificially contaminate the supernatant [where prior information on stock concentrations are available aim to add approximately 10,000 copies per ml of supernatant]. Split into 3 x 500µl aliquots and subject to RNA extraction and real-time RT-PCR according to the method protocol undergoing characterisation. Test for GI, GII and the process control virus. Discount any s where the RT-PCR inhibition or extraction efficiency s are below the acceptable threshold. Page 2 of 8

3 PREPARATION OF DILUTION SERIES Prepare a log 2 dilution series of norovirus GI and GII in digestive tissue supernatant as follows:- 1. Defrost the digestive tissue supernatant. Transfer 10.4ml to one tube (labelled e.g. neat ) and 5.2ml to each of 8 tubes (labelled e.g. 1:2, 1:4, 1:8, 1:16, 1:32, 1:64, 1:128, 1:256 ). 2. Taking into account the s of the calibration extractions, use GI and GII norovirus stocks to artificially contaminate the supernatant in the neat tube to levels that will provide s of copies/g. Mix well. 3. Transfer 5.2ml of contaminated supernatant to the tube labelled 1:2 to create a 1:2 dilution. Mix well. 4. Transfer 5.2ml of contaminated supernatant from the tube labelled 1:2 to the tube labelled 1:4 to create a 1:4 dilution. Mix well. 5. Repeat step 4 until a log 2 dilution series down to 1:256 has been produced. 6. Label 10 x 1.5ml tubes for each dilution ( neat to 1:256 ). Transfer 500µl of the relevant dilution to each tube and store these subsamples at -20 C. TESTING/GENERATION OF DATA Defrost one subsample from each dilution (9 tubes in total). Subject to RNA extraction (alongside 500µl water as a negative control) and real-time RT-PCR according to the method protocol undergoing characterisation. Test for GI, GII and the process control virus and calculate the levels recorded in each subsample. Discount any s where the RT- PCR inhibition or extraction efficiency s are below the acceptable threshold. Repeat until all stored subsamples have been extracted and analysed by real-time RT-PCR. NOTE: this will entail 10 extractions of 9 samples (plus a negative control) a total of 90 individual extractions (or 100 including negative controls). ANTICIPATED VALUES After all real-time RT-PCR analysis is complete generate anticipated s for each dilution as follows:- geometric mean of obtained s for all subsamples where the RT-PCR inhibition and extraction efficiency s are acceptable (n=10 where all s are acceptable) at the neat dilution multiplied by the dilution factor. EXAMPLE:- Where the 10 neat subsamples give s of 804, 968, 1129, 1186, 1182, 1067, 1167, 1124, 1099 and 862 copies/g respectively (geometric mean = copies/g), the anticipated s for the different dilutions are as follows:- Page 3 of 8

4 DILUTION ANTICIPATED VALUE neat x 1 = copies/g 1: x 1/2 = copies/g 1: x 1/4 = copies/g 1: x 1/8 = copies/g 1: x 1/16 = copies/g 1: x 1/32 = copies/g 1: x 1/64 = copies/g 1: x 1/128 = 8.21 copies/g 1: x 1/256 = 4.10 copies/g DATA ANALYSIS An example data set is given in Annex 1; annotated spreadsheets demonstrating the analysis of this data set according to the following instructions are included as supplementary files. Note the examples and the text below describe analysis for one norovirus genogroup. The process must be repeated for both GI and GII. Determination of LOD 95 Determine the LOD for the data using the approach given in: Wilrich C, Wilrich PT Estimation of the POD function and the LOD of a qualitative microbiological measurement method. J AOAC Int. 92(6): Calculator PODLOD_ver7.xls available at 1. Ensure that macros are enabled. 2. In the spreadsheet enter: a. Sample size A 0 as 2 1 b. Total no. of matrices as 1 c. Total no. of contamination levels as the number used (9 for the example data given in Annex 1) This will generate a data input table. 3. Enter the calculated anticipated values in the left hand column. 4. Enter the total number of valid s at each anticipated value in the second column. 5. Enter the number of positive s at each anticipated value in the third column. 6. Press control b to start the calculation. 1 Sample size entered does not affect the calculation of the LOD but cannot be left blank Page 4 of 8

5 Two boxes containing the s of the calculation will appear. For only one matrix, the values in row one of each box will be the same. Record the LOD 95 value (the confidence limits may be recorded but are not required for the determination of the LOQ). Page 5 of 8

6 Sub-selection of data to use for determining linearity and the LOQ Discard the data points where the anticipated values are lower than the determined LOD 95 value. Determination of linearity 1. Use the data points remaining after discarding those below the LOD Determine the slope of the linear regression line for the log 10-transformed obtained values (y axis) plotted against log 10-transformed anticipated values (x axis). [In Excel, use either the function LINEST or the function SLOPE: if the Analysis Toolpak add-in has been activated, the Regression function can be used. Do not constrain the regression line to pass through the origin: i.e. if using the LINEST function, ensure that argument Const is set to 1 or omitted; if using the Regression function, ensure that the Constant is Zero box is not checked]. 3. If the value of the slope lies between 0.9 and 1.1, accept that the response is linear. In this case all of the data points retained after determination of the LOD are used to determine the LOQ. 4. If the value for the slope lies outside that range, repeat the calculation of the slope parameter after excluding the data points corresponding to the lowest remaining anticipated value. a. If the value of the slope is now between 0.9 and 1.1, the data points used for this estimation are used to determine LOQ. b. If the value still lies outside the range 0.9 to 1.1, seek advice from the EURL. Determination of the LOQ 1. Using all data retained after determination of linearity, separately determine the standard deviation 2 (SD) of the log 10-transformed obtained s for each anticipated value (if there are no QC failures, this will be the SD of 10 s for each anticipated value). 2. The LOQ is the lowest anticipated level where the SD is <0.33 3,4 and where the SDs of all higher anticipated levels are also <0.33. If all of the SD values are <0.33, then the LOQ equals the lowest anticipated value in the data set retained after determination of linearity. 3. Round the LOQ value to a whole number and report to a maximum of three significant figures (i.e becomes 55; becomes 1140). 4. The assessment may be presented visually by plotting the SD against the anticipated level with a reference line at 0.33 SD. 2 This should be the sample standard deviation (e.g. using the function STDEV.S in Microsoft Excel) and not the population standard deviation 3 The critical level for the standard deviation of the log10 transformed s has been set at 0.33 based on appraisal of historic EURL data from e.g. ring trial homogeneity testing and the formal validation of ISO Alternatively, the user laboratory may set an LOQ that is interpolated between anticipated values using an appropriate function derived from the recorded data, to determine the level at which the standard deviation of the log10 transformed s would be expected to be In no case should the LOQ be set below the lowest anticipated value retained after determination of linearity. Page 6 of 8

7 Anticipated value (copies/g) ANNEX 1. EXAMPLE DATA SET Obtained (copies/g) Log 10 anticipated Log 10 obtained Dilution neat neat neat neat neat neat neat neat neat neat : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : Page 7 of 8

8 Anticipated value (copies/g) Obtained (copies/g) Log 10 anticipated Log 10 obtained Dilution 1: : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : Page 8 of 8