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Molecular toolbox for the identification of unknown genetically modified organisms

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Abstract

Competent laboratories monitor genetically modified organisms (GMOs) and products derived thereof in the food and feed chain in the framework of labeling and traceability legislation. In addition, screening is performed to detect the unauthorized presence of GMOs including asynchronously authorized GMOs or GMOs that are not officially registered for commercialization (unknown GMOs). Currently, unauthorized or unknown events are detected by screening blind samples for commonly used transgenic elements, such as p35S or t-nos. If (1) positive detection of such screening elements shows the presence of transgenic material and (2) all known GMOs are tested by event-specific methods but are not detected, then the presence of an unknown GMO is inferred. However, such evidence is indirect because it is based on negative observations and inconclusive because the procedure does not identify the causative event per se. In addition, detection of unknown events is hampered in products that also contain known authorized events. Here, we outline alternative approaches for analytical detection and GMO identification and develop new methods to complement the existing routine screening procedure. We developed a fluorescent anchor-polymerase chain reaction (PCR) method for the identification of the sequences flanking the p35S and t-nos screening elements. Thus, anchor-PCR fingerprinting allows the detection of unique discriminative signals per event. In addition, we established a collection of in silico calculated fingerprints of known events to support interpretation of experimentally generated anchor-PCR GM fingerprints of blind samples. Here, we first describe the molecular characterization of a novel GMO, which expresses recombinant human intrinsic factor in Arabidopsis thaliana. Next, we purposefully treated the novel GMO as a blind sample to simulate how the new methods lead to the molecular identification of a novel unknown event without prior knowledge of its transgene sequence. The results demonstrate that the new methods complement routine screening procedures by providing direct conclusive evidence and may also be useful to resolve masking of unknown events by known events.

Molecular toolbox for the identification of genetically modified organisms

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Acknowledgements

T. Ruttink is supported by the Belgian Federal Public Service for Health, Food Chain Safety, and Environment (contract no. RT-06/6 GMOdetec). R. Demeyer is indebted to the Institute for Agricultural and Fisheries Research (ILVO) for a predoctoral fellowship. I. Taverniers was involved in the 6th Framework Programme Integrated Project Co-Extra, Contract No. 007158. We are thankful for the excellent technical support of Annique Staelens, Cindy Merckaert, Mieke Dhondt, and Sabine van Glabeke.

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Correspondence to Isabel Taverniers.

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T. Ruttink and R. Demeyer contributed equally to this work.

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Ruttink, T., Demeyer, R., Van Gulck, E. et al. Molecular toolbox for the identification of unknown genetically modified organisms. Anal Bioanal Chem 396, 2073–2089 (2010). https://doi.org/10.1007/s00216-009-3287-6

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  • DOI: https://doi.org/10.1007/s00216-009-3287-6

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