Advanced search
1 file | 2.05 MB Add to list

Integrated DNA walking system to characterize a broad spectrum of GMOs in food/feed matrices

Author
Organization
Abstract
Background: In order to provide a system fully integrated with qPCR screening, usually used in GMO routine analysis, as well as being able to detect, characterize and identify a broad spectrum of GMOs in food/feed matrices, two bidirectional DNA walking methods targeting p35S or tNOS, the most common transgenic elements found in GM crops, were developed. These newly developed DNA walking methods are completing the previously implemented DNA walking method targeting the t35S pCAMBIA element. Results: First, the newly developed DNA walking methods, anchored on the sequences used for the p35S or tNOS qPCR screening, were tested on Bt rice that contains these two transgenic elements. Second, the methods were assessed on a maize sample containing a low amount of the GM MON863 event, representing a more complex matrix in terms of genome size and sensitivity. Finally, to illustrate its applicability in GMO routine analysis by enforcement laboratories, the entire workflow of the integrated strategy, including qPCR screening to detect the potential presence of GMOs and the subsequent DNA walking methods to characterize and identify the detected GMOs, was applied on a GeMMA Scheme Proficiency Test matrix. Via the characterization of the transgene flanking region between the transgenic cassette and the plant genome as well as of a part of the transgenic cassette, the presence of GMOs was properly confirmed or infirmed in all tested samples. Conclusion: Due to their simple procedure and their short time-frame to get results, the developed DNA walking methods proposed here can be easily implemented in GMO routine analysis by the enforcement laboratories. In providing crucial information about the transgene flanking regions and/or the transgenic cassettes, this DNA walking strategy is a key molecular tool to prove the presence of GMOs in any given food/feed matrix.
Keywords
REAL-TIME PCR, FLANKING SEQUENCE DETERMINATION, UNAUTHORIZED GMOS, PRODUCTS, GENES, FOOD

Downloads

  • Fraiture MA 2015b.pdf
    • full text
    • |
    • open access
    • |
    • PDF
    • |
    • 2.05 MB

Citation

Please use this url to cite or link to this publication:

MLA
Fraiture, Marie-Alice et al. “Integrated DNA Walking System to Characterize a Broad Spectrum of GMOs in Food/feed Matrices.” BMC BIOTECHNOLOGY 15 (2015): n. pag. Print.
APA
Fraiture, M.-A., Herman, P., Lefèvre, L., Taverniers, I., De Loose, M., Deforce, D., & Roosens, N. H. (2015). Integrated DNA walking system to characterize a broad spectrum of GMOs in food/feed matrices. BMC BIOTECHNOLOGY, 15.
Chicago author-date
Fraiture, Marie-Alice, Philippe Herman, Loic Lefèvre, Isabel Taverniers, Marc De Loose, Dieter Deforce, and Nancy H Roosens. 2015. “Integrated DNA Walking System to Characterize a Broad Spectrum of GMOs in Food/feed Matrices.” Bmc Biotechnology 15.
Chicago author-date (all authors)
Fraiture, Marie-Alice, Philippe Herman, Loic Lefèvre, Isabel Taverniers, Marc De Loose, Dieter Deforce, and Nancy H Roosens. 2015. “Integrated DNA Walking System to Characterize a Broad Spectrum of GMOs in Food/feed Matrices.” Bmc Biotechnology 15.
Vancouver
1.
Fraiture M-A, Herman P, Lefèvre L, Taverniers I, De Loose M, Deforce D, et al. Integrated DNA walking system to characterize a broad spectrum of GMOs in food/feed matrices. BMC BIOTECHNOLOGY. 2015;15.
IEEE
[1]
M.-A. Fraiture et al., “Integrated DNA walking system to characterize a broad spectrum of GMOs in food/feed matrices,” BMC BIOTECHNOLOGY, vol. 15, 2015.
@article{6842118,
  abstract     = {Background: In order to provide a system fully integrated with qPCR screening, usually used in GMO routine analysis, as well as being able to detect, characterize and identify a broad spectrum of GMOs in food/feed matrices, two bidirectional DNA walking methods targeting p35S or tNOS, the most common transgenic elements found in GM crops, were developed. These newly developed DNA walking methods are completing the previously implemented DNA walking method targeting the t35S pCAMBIA element.
Results: First, the newly developed DNA walking methods, anchored on the sequences used for the p35S or tNOS qPCR screening, were tested on Bt rice that contains these two transgenic elements. Second, the methods were assessed on a maize sample containing a low amount of the GM MON863 event, representing a more complex matrix in terms of genome size and sensitivity. Finally, to illustrate its applicability in GMO routine analysis by enforcement laboratories, the entire workflow of the integrated strategy, including qPCR screening to detect the potential presence of GMOs and the subsequent DNA walking methods to characterize and identify the detected GMOs, was applied on a GeMMA Scheme Proficiency Test matrix. Via the characterization of the transgene flanking region between the transgenic cassette and the plant genome as well as of a part of the transgenic cassette, the presence of GMOs was properly confirmed or infirmed in all tested samples.
Conclusion: Due to their simple procedure and their short time-frame to get results, the developed DNA walking methods proposed here can be easily implemented in GMO routine analysis by the enforcement laboratories. In providing crucial information about the transgene flanking regions and/or the transgenic cassettes, this DNA walking strategy is a key molecular tool to prove the presence of GMOs in any given food/feed matrix.},
  articleno    = {76},
  author       = {Fraiture, Marie-Alice and Herman, Philippe and Lefèvre, Loic and Taverniers, Isabel and De Loose, Marc and Deforce, Dieter and Roosens, Nancy H},
  issn         = {1472-6750},
  journal      = {BMC BIOTECHNOLOGY},
  keywords     = {REAL-TIME PCR,FLANKING SEQUENCE DETERMINATION,UNAUTHORIZED GMOS,PRODUCTS,GENES,FOOD},
  language     = {eng},
  pages        = {11},
  title        = {Integrated DNA walking system to characterize a broad spectrum of GMOs in food/feed matrices},
  url          = {http://dx.doi.org/10.1186/s12896-015-0191-3},
  volume       = {15},
  year         = {2015},
}

Altmetric
View in Altmetric
Web of Science
Times cited: