Literature DB >> 18346452

Detection of nonauthorized genetically modified organisms using differential quantitative polymerase chain reaction: application to 35S in maize.

Katarina Cankar1, Valérie Chauvensy-Ancel, Marie-Noelle Fortabat, Kristina Gruden, André Kobilinsky, Jana Zel, Yves Bertheau.   

Abstract

Detection of nonauthorized genetically modified organisms (GMOs) has always presented an analytical challenge because the complete sequence data needed to detect them are generally unavailable although sequence similarity to known GMOs can be expected. A new approach, differential quantitative polymerase chain reaction (PCR), for detection of nonauthorized GMOs is presented here. This method is based on the presence of several common elements (e.g., promoter, genes of interest) in different GMOs. A statistical model was developed to study the difference between the number of molecules of such a common sequence and the number of molecules identifying the approved GMO (as determined by border-fragment-based PCR) and the donor organism of the common sequence. When this difference differs statistically from zero, the presence of a nonauthorized GMO can be inferred. The interest and scope of such an approach were tested on a case study of different proportions of genetically modified maize events, with the P35S promoter as the Cauliflower Mosaic Virus common sequence. The presence of a nonauthorized GMO was successfully detected in the mixtures analyzed and in the presence of (donor organism of P35S promoter). This method could be easily transposed to other common GMO sequences and other species and is applicable to other detection areas such as microbiology.

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Year:  2008        PMID: 18346452     DOI: 10.1016/j.ab.2008.02.013

Source DB:  PubMed          Journal:  Anal Biochem        ISSN: 0003-2697            Impact factor:   3.365


  4 in total

1.  A theoretical introduction to "combinatory SYBRGreen qPCR screening", a matrix-based approach for the detection of materials derived from genetically modified plants.

Authors:  Marc Van den Bulcke; Antoon Lievens; Elodie Barbau-Piednoir; Guillaume MbongoloMbella; Nancy Roosens; Myriam Sneyers; Amaya Leunda Casi
Journal:  Anal Bioanal Chem       Date:  2009-12-04       Impact factor: 4.142

2.  Quantitative analysis of food and feed samples with droplet digital PCR.

Authors:  Dany Morisset; Dejan Štebih; Mojca Milavec; Kristina Gruden; Jana Žel
Journal:  PLoS One       Date:  2013-05-02       Impact factor: 3.240

3.  Optimised padlock probe ligation and microarray detection of multiple (non-authorised) GMOs in a single reaction.

Authors:  Theo W Prins; Jeroen P van Dijk; Henriek G Beenen; Am Angeline Van Hoef; Marleen M Voorhuijzen; Cor D Schoen; Henk J M Aarts; Esther J Kok
Journal:  BMC Genomics       Date:  2008-12-04       Impact factor: 3.969

4.  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

  4 in total

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