Revised Guidance on the Detection of Genetically Modified Rice Originating from China Using Real-Time PCR for the detection of P-35S, T-nos and Cry1Ab/Ac

In support to the Commission Implementing Decision 2013/287/EU , amending Decision 2011/884/EU , the European Union Reference Laboratory for Genetically Modified Food and Feed (EU-RL GMFF) prepared a revision of the previously published guidance document. This document provides further guidance on the correct use of the methods indicated in the Decision, including measures aimed at improving the specificity of the detection approach. This revised guidance, as its previous version, is exclusively meant for the implementation of Decision 2013/287/EU and should not be used for other screening activities. Laboratories should apply it only in conjunction with good standard practices for testing for the presence of GMOs (e.g. use of appropriate controls).JRC.I.3-Molecular Biology and Genomic

Simulation of between repeat variability in real time PCR reactions

While many decisions rely on real time quantitative PCR (qPCR) analysis few attempts have hitherto been made to quantify bounds of precision accounting for the various sources of variation involved in the measurement process. Besides influences of more obvious factors such as camera noise and pipetting variation, changing efficiencies within and between reactions affect PCR results to a degree which is not fully recognized. Here, we develop a statistical framework that models measurement error and other sources of variation as they contribute to fluorescence observations during the amplification process and to derived parameter estimates. Evaluation of reproducibility is then based on simulations capable of generating realistic variation patterns. To this end, we start from a relatively simple statistical model for the evolution of efficiency in a single PCR reaction and introduce additional error components, one at a time, to arrive at stochastic data generation capable of simulating the variation patterns witnessed in repeated reactions (technical repeats). Most of the variation in C-q values was adequately captured by the statistical model in terms of foreseen components. To recreate the dispersion of the repeats' plateau levels while keeping the other aspects of the PCR curves within realistic bounds, additional sources of reagent consumption (side reactions) enter into the model. Once an adequate data generating model is available, simulations can serve to evaluate various aspects of PCR under the assumptions of the model and beyond

Enhanced analysis of real-time PCR data by using a variable efficiency model : FPK-PCR

Current methodology in real-time Polymerase chain reaction (PCR) analysis performs well provided PCR efficiency remains constant over reactions. Yet, small changes in efficiency can lead to large quantification errors. Particularly in biological samples, the possible presence of inhibitors forms a challenge. We present a new approach to single reaction efficiency calculation, called Full Process Kinetics-PCR (FPK-PCR). It combines a kinetically more realistic model with flexible adaptation to the full range of data. By reconstructing the entire chain of cycle efficiencies, rather than restricting the focus on a 'window of application', one extracts additional information and loses a level of arbitrariness. The maximal efficiency estimates returned by the model are comparable in accuracy and precision to both the golden standard of serial dilution and other single reaction efficiency methods. The cycle-to-cycle changes in efficiency, as described by the FPK-PCR procedure, stay considerably closer to the data than those from other S-shaped models. The assessment of individual cycle efficiencies returns more information than other single efficiency methods. It allows in-depth interpretation of real-time PCR data and reconstruction of the fluorescence data, providing quality control. Finally, by implementing a global efficiency model, reproducibility is improved as the selection of a window of application is avoided

Enhanced analysis of real-time PCR data by using a variable efficiency model: FPK-PCR

Current methodology in real-time Polymerase chain reaction (PCR) analysis performs well provided PCR efficiency remains constant over reactions. Yet, small changes in efficiency can lead to large quantification errors. Particularly in biological samples, the possible presence of inhibitors forms a challenge. We present a new approach to single reaction efficiency calculation, called Full Process Kinetics-PCR (FPK-PCR). It combines a kinetically more realistic model with flexible adaptation to the full range of data. By reconstructing the entire chain of cycle efficiencies, rather than restricting the focus on a ‘window of application’, one extracts additional information and loses a level of arbitrariness. The maximal efficiency estimates returned by the model are comparable in accuracy and precision to both the golden standard of serial dilution and other single reaction efficiency methods. The cycle-to-cycle changes in efficiency, as described by the FPK-PCR procedure, stay considerably closer to the data than those from other S-shaped models. The assessment of individual cycle efficiencies returns more information than other single efficiency methods. It allows in-depth interpretation of real-time PCR data and reconstruction of the fluorescence data, providing quality control. Finally, by implementing a global efficiency model, reproducibility is improved as the selection of a window of application is avoided.JRC.I.3-Molecular Biology and Genomic

Report on the Verification of the Performance of a Testing Strategy for the Detection of Wheat MON71800 Event Using Real-Time PCR

In response to a request of DG SANCO to provide National Reference Laboratories (NRLs) as soon as possible with a method to test soft white wheat consignments for the presence of unauthorised GM glyphosate-resistant wheat harbouring the event MON71800, the European Union Reference Laboratory for Genetically Modified Food and Feed (EU-RL GMFF) developed, in collaboration with the European Network of GMO Laboratories (ENGL), a testing strategy intended to be immediately implementable by EU NRLs. The testing strategy is based on a combination of three validated screening methods that allow excluding (detectable) presence of Monsanto’s GM glyphosate-resistant wheat (MON71800) in wheat grain or food/feed products and confirming its presence whenever other GMOs can be excluded. The present report describes the results of the tests carried out by the EU-RL GMFF to verify the testing strategy proposed; the tests were conducted using the positive control sample represented by a crude DNA lysate of MON71800 provided by Monsanto and genomic DNA samples of genetically modified organisms harbouring the CTP2-CP4epsps element for which a validated event-specific method is available. The sensitivity of the three methods was assessed by verifying the relative limit of detection (LODrel) on MON71800 wheat DNA. The LODrel is approximately 0.03% for the P-35S and for T-nos methods and 0.06% for the CTP2-CP4epsps method in 300 nanograms of wheat genomic DNA. Further experimental evidence confirmed that the three methods react against genomic DNA extracted from GM events containing the CTP2-CP4epsps element for which a validated event-specific method is available. The experimental verification hereby reported confirmed the validity of the EU-RL GMFF guidance on testing for GM glyphosate-resistant wheat (MON71800) in wheat grain or in food/feed products containing wheat flour originating or consigned from the US, provided that DNA of acceptable quality can be obtained.JRC.I.3-Molecular Biology and Genomic

Enhancing fish species identification using novel markers and emerging technologies

Establishing an efficient traceability framework for fish products is crucial for consumer protection and fisheries management and conservation. This is well reflected in the EU legislation. The EU general food law emphasizes strongly that European citizens must have access to safe and wholesome food of the highest standard. Consumer protection is supported by a stringent traceability concept as stipulated in Regulation (EC) 178/2002. This notion is also expressed in the Common Fisheries Policy (CFP) basic regulation (EU) 1380/2013, according to which fishing and aquaculture must be environmentally, economically and socially sustainable while providing a source of healthy food for all EU citizens. Under the CFP the need for traceability is not exclusively raised in the context of consumer protection, but also as a necessary component for fisheries control and enforcement in Regulation (EU) 1224/2009 and in the context of the EU’s ambitious strategy to fight Illegal, Unreported and Unregulated (IUU) fishing under the remit of Regulation (EC) 1005/2008. Recent scientific advances, particularly in the fields of genetics and genomics, have led to the development of novel and improved technologies, and efforts are under way to harness their potential for the species identification of unknown fish samples or products. This report reviews these efforts, describing the technologies and the early results obtained for fish product traceability. Each of these technologies have the potential to fill some specific existing gaps, although they come with their own individual set of disadvantages. Understanding those and monitoring progress is thus crucial for their proper integration in existing traceability frameworks.JRC.F.7-Knowledge for Health and Consumer Safet

A theoretical introduction to “Combinatory SYBR®Green qPCR Screening”, a matrix-based approach for the detection of materials derived from genetically modified plants

The detection of genetically modified (GM) materials in food and feed products is a complex multi-step analytical process invoking screening, identification, and often quantification of the genetically modified organisms (GMO) present in a sample. “Combinatory qPCR SYBR®Green screening” (CoSYPS) is a matrix-based approach for determining the presence of GM plant materials in products. The CoSYPS decision-support system (DSS) interprets the analytical results of SYBR®GREEN qPCR analysis based on four values: the Ct- and Tm values and the LOD and LOQ for each method. A theoretical explanation of the different concepts applied in CoSYPS analysis is given (GMO Universe, “Prime number tracing”, matrix/combinatory approach) and documented using the RoundUp Ready soy GTS40-3-2 as an example. By applying a limited set of SYBR®GREEN qPCR methods and through application of a newly developed “prime number”-based algorithm, the nature of subsets of corresponding GMO in a sample can be determined. Together, these analyses provide guidance for semi-quantitative estimation of GMO presence in a food and feed product

Overview and recommendations for the application of digital PCR

The digital Polymerase Chain Reaction (dPCR), for the detection and absolute quantification of DNA, is a relatively new technique but its application in analytical laboratories is steadily increasing. In contrast to quantitative real-time PCR, DNA (fragments) can be quantified without the need for standard curves. Using dPCR, the PCR mix containing the (target) DNA is partitioned – depending on the device used – currently into a maximum of 10,000,000 small compartments with a volume as low as a few picoliters. These can be either physically distinct compartments on a chip (referred to as chamber-based digital PCR [cdPCR]), or these compartments correspond to water-in-oil droplets (referred to as droplet digital [ddPCR]). Common to both approaches, once PCR has been carried out simultaneously in all compartments/droplets, the number of positive and negative signals for each partition is counted by fluorescence measurement. With this technique, an absolute quantification of DNA copy numbers can be performed with high precision and trueness, even for very low DNA copy numbers. Furthermore, dPCR is considered less susceptible than qPCR to PCR inhibitory substances that can be co-extracted during DNA extraction from different sources. Digital PCR has already been applied in various fields, for example for the detection and quantification of GMOs, species (animals, plants), human diseases, food viruses and bacteria including pathogens. When establishing dPCR in a laboratory, different aspects have to be considered. These include, but are not limited to, the adjustment of the type of the PCR master mix used, optimised primer and probe concentrations and signal separation of positive and negative compartments. This document addresses these and other aspects and provides recommendations for the transfer of existing real-time PCR methods into a dPCR format.JRC.F.5-Food and Feed Complianc

The Digital MIQE Guidelines Update: Minimum Information for Publication of Quantitative Digital PCR Experiments for 2020

Digital PCR (dPCR) has developed considerably since the publication of the Minimum Information for Publication of Digital PCR Experiments (dMIQE) guidelines in 2013, with advances in instrumentation, software, applications, and our understanding of its technological potential. Yet these developments also have associated challenges; data analysis steps, including threshold setting, can be difficult and preanalytical steps required to purify, concentrate, and modify nucleic acids can lead to measurement error. To assist independent corroboration of conclusions, comprehensive disclosure of all relevant experimental details is required. To support the community and reflect the growing use of dPCR, we present an update to dMIQE, dMIQE2020, including a simplified dMIQE table format to assist researchers in providing key experimental information and understanding of the associated experimental process. Adoption of dMIQE2020 by the scientific community will assist in standardizing experimental protocols, maximize efficient utilization of resources, and further enhance the impact of this powerful technology