Analytical and Bioanalytical Chemistry

, Volume 396, Issue 6, pp 2073–2089

Molecular toolbox for the identification of unknown genetically modified organisms

Authors

  • Tom Ruttink
    • Institute for Agricultural and Fisheries Research (ILVO), Technology and Food Science Unit—Product Quality and Innovation
  • Rolinde Demeyer
    • Institute for Agricultural and Fisheries Research (ILVO), Technology and Food Science Unit—Product Quality and Innovation
  • Elke Van Gulck
    • KaHo Sint-Lieven, Departement Gent
  • Bart Van Droogenbroeck
    • Institute for Agricultural and Fisheries Research (ILVO), Technology and Food Science Unit—Product Quality and Innovation
  • Maddalena Querci
    • Molecular Biology and Genomics Unit, European Commission - Joint Research Center (JRC)Institute for Health and Consumer Protection
    • Institute for Agricultural and Fisheries Research (ILVO), Technology and Food Science Unit—Product Quality and Innovation
  • Marc De Loose
    • Institute for Agricultural and Fisheries Research (ILVO), Technology and Food Science Unit—Product Quality and Innovation
    • Department of Molecular GeneticsGhent University
Original Paper

DOI: 10.1007/s00216-009-3287-6

Cite this article as:
Ruttink, T., Demeyer, R., Van Gulck, E. et al. Anal Bioanal Chem (2010) 396: 2073. doi:10.1007/s00216-009-3287-6

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.

https://static-content.springer.com/image/art%3A10.1007%2Fs00216-009-3287-6/MediaObjects/216_2009_3287_Figa_HTML.gif
Figure

Molecular toolbox for the identification of genetically modified organisms

Keywords

GMO screening analysis GMO identification Anchor-PCR Fingerprinting p35S t-nos

Supplementary material

216_2009_3287_MOESM1_ESM.pdf (1.9 mb)
ESM 1 (PDF 1957 kb)

Copyright information

© Springer-Verlag 2009