Literature DB >> 19937431

Molecular toolbox for the identification of unknown genetically modified organisms.

Tom Ruttink1, Rolinde Demeyer, Elke Van Gulck, Bart Van Droogenbroeck, Maddalena Querci, Isabel Taverniers, Marc De Loose.   

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.

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Year:  2009        PMID: 19937431     DOI: 10.1007/s00216-009-3287-6

Source DB:  PubMed          Journal:  Anal Bioanal Chem        ISSN: 1618-2642            Impact factor:   4.142


  9 in total

Review 1.  Relative quantification in seed GMO analysis: state of art and bottlenecks.

Authors:  Maher Chaouachi; Aurélie Bérard; Khaled Saïd
Journal:  Transgenic Res       Date:  2013-02-12       Impact factor: 2.788

Review 2.  Current perspectives on genetically modified crops and detection methods.

Authors:  Madhu Kamle; Pradeep Kumar; Jayanta Kumar Patra; Vivek K Bajpai
Journal:  3 Biotech       Date:  2017-07-03       Impact factor: 2.406

3.  Development and validation of real-time PCR screening methods for detection of cry1A.105 and cry2Ab2 genes in genetically modified organisms.

Authors:  Andréia Z Dinon; Theo W Prins; Jeroen P van Dijk; Ana Carolina M Arisi; Ingrid M J Scholtens; Esther J Kok
Journal:  Anal Bioanal Chem       Date:  2011-03-29       Impact factor: 4.142

Review 4.  How to deal with the upcoming challenges in GMO detection in food and feed.

Authors:  Sylvia R M Broeders; Sigrid C J De Keersmaecker; Nancy H C Roosens
Journal:  J Biomed Biotechnol       Date:  2012-10-21

5.  The GMOseek matrix: a decision support tool for optimizing the detection of genetically modified plants.

Authors:  Annette Block; Frédéric Debode; Lutz Grohmann; Julie Hulin; Isabel Taverniers; Linda Kluga; Elodie Barbau-Piednoir; Sylvia Broeders; Ingrid Huber; Marc Van den Bulcke; Petra Heinze; Gilbert Berben; Ulrich Busch; Nancy Roosens; Eric Janssen; Jana Žel; Kristina Gruden; Dany Morisset
Journal:  BMC Bioinformatics       Date:  2013-08-22       Impact factor: 3.169

6.  Characterization of GM events by insert knowledge adapted re-sequencing approaches.

Authors:  Litao Yang; Congmao Wang; Arne Holst-Jensen; Dany Morisset; Yongjun Lin; Dabing Zhang
Journal:  Sci Rep       Date:  2013-10-03       Impact factor: 4.379

7.  GMOseek: a user friendly tool for optimized GMO testing.

Authors:  Dany Morisset; Petra Kralj Novak; Darko Zupanič; Kristina Gruden; Nada Lavrač; Jana Žel
Journal:  BMC Bioinformatics       Date:  2014-08-01       Impact factor: 3.169

Review 8.  Current and new approaches in GMO detection: challenges and solutions.

Authors:  Marie-Alice Fraiture; Philippe Herman; Isabel Taverniers; Marc De Loose; Dieter Deforce; Nancy H Roosens
Journal:  Biomed Res Int       Date:  2015-10-15       Impact factor: 3.411

9.  Data in support of the detection of genetically modified organisms (GMOs) in food and feed samples.

Authors:  Noor Alasaad; Hussein Alzubi; Ahmad Abdul Kader
Journal:  Data Brief       Date:  2016-02-20
  9 in total

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