Skip to main content
SpringerLink
Log in

Performance assessment of digital PCR for the quantification of GM-maize and GM-soya events

  • Research Paper
  • Published:
Analytical and Bioanalytical Chemistry Aims and scope Submit manuscript

Abstract

Accurate quantitative methods are needed to determine the amount of transgenic material in ingredients and comply with labelling GMO thresholds. Quantitative real-time PCR methods are usually applied for GMO quantification, but since a few years, digital PCR (dPCR) has been described as a potential alternative by quantifying DNA molecules directly without any standard curves. In this study, the performance of dPCR to quantify 9 GM-soya events and 15 GM-maize events was assessed. Following GMO validation guidelines, the trueness and precision were determined on high, medium and low levels of transgenic content. Results showed biases below ± 25% and satisfactory precision data. Limits of quantification were determined for each GM-event and were between 12 and 31 target copies. The reliability of GMO quantification by dPCR was further confirmed by analysing several proficiency test samples. Overall, dPCR showed accurate and precise GMO quantification on all the tested GM-events, from high to low transgenic amount. With its ease-of-use, dPCR was found to be an appealing alternative technology for routine GMO testing laboratories.

Graphical abstract

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Abbreviations

GMO:

Genetically modified organisms

PCR:

Polymerase chain reaction

dPCR:

Digital PCR

CRM:

Certified reference material

NTC:

No template control

LOQ:

Limit of quantification

References

  1. Cottenet G, Blancpain C, Sonnard V, Chuah PF. Two FAST multiplex real-time PCR reactions to assess the presence of genetically modified organisms in food. Food Chem. 2019;274:760–5.

    Article  CAS  PubMed  Google Scholar 

  2. Cottenet G, Blancpain C, Sonnard V, Chuah PF. Development and validation of a multiplex real-time PCR method to simultaneously detect 47 targets for the identification of genetically modified organisms. Anal Bioanal Chem. 2013;405:6831–44.

    Article  CAS  PubMed  Google Scholar 

  3. Bonfini L, Van Den Bulcke MH, Mazzara M, Ben E, Patak A. GMOMETHODS: the European Union database of reference methods for GMO analysis. J AOAC Int. 2012;95:1713–9.

    Article  CAS  PubMed  Google Scholar 

  4. Quan PL, Sauzade M, Brouzes E. dPCR : a technology review. Sensors. 2018. https://doi.org/10.3390/s18041271.

  5. Ren J, Deng T, Huang W, Chen Y, Ge Y. A digital PCR method for identifying and quantifying adulteration of meat species in raw and processed food. PLoS One. 2017. https://doi.org/10.1371/journal.pone.0173567.

  6. Corbisier P, Bhat S, Partis L, Xie VR, Emslie KR. Absolute quantification of genetically modified MON810 maize (Zea mays L.) by digital polymerase chain reaction. Anal Bioanal Chem. 2010;396:2143–50.

    Article  CAS  PubMed  Google Scholar 

  7. Iwobi A, Gerdes L, Busch U, Pecoraro S. Droplet digital PCR for routine analysis of genetically modified organisms (GMO) – a comparison with real-time quantitative PCR. Food Control. 2016;69:205–13.

    Article  CAS  Google Scholar 

  8. Köppel R, Bucher T. Rapid establishment of droplet digital PCR for quantitative GMO analysis. Eur Food Res Technol. 2015;241:427–39.

    Article  CAS  Google Scholar 

  9. Whale AS, Huggett JF, Tzonev S. Fundamentals of multiplexing with digital PCR. Biomol Detect Quantif. 2016;10:15–23.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Dobnik D, Spilsberg B, Kosir AB, Holst-Jensen A, Zel J. Multiplex quantification of 12 European Union authorized genetically modified maize lines with droplet digital polymerase chain reaction. Anal Chem. 2015;87:8218–26.

    Article  CAS  PubMed  Google Scholar 

  11. Kosir AB, Spilsberg B, Holst-Jensen A, Zel J, Dobnik D. Development and inter-laboratory assessment of droplet digital PCR assays for multiplex quantification of 15 genetically modified soybean lines. Sci Rep. 2017;7:8601.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Köppel R, Bucher T, Bär D, Van Velsen F, Ganeshan A. Validation of 13 duplex droplet digital PCR systems for quantitative GMO analysis of most prevalent GMO traits. Eur Food Res Technol. 2017;244:313–21.

    Article  CAS  Google Scholar 

  13. GMOMETHODS. EU Database of Reference Methods for GMO Analysis. 2018. http://gmo-crl.jrc.ec.europa.eu/gmomethods/. Accessed 16 February 2018.

  14. Demeke T, Dobnik D. Critical assessment of digital PCR for the detection and quantification of genetically modified organisms. Anal Bioanal Chem. 2018;410:4039–50.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Jacchia S, Kagkli D-M, Lievens A, Angers-Loustau A, Savini C, Emons H, et al. Identification of single target taxon-specific reference assays for the most commonly genetically transformed crops using digital droplet PCR. Food Control. 2018;93:191–200.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. ERM, European reference materials. Application note 4: use of certified reference materials for the quantification of GMO in food and feed. 2006. https://ec.europa.eu/jrc/sites/jrcsh/files/erm_application_note_4_en.pdf Accessed on 26 January 2018.

  17. ENGL, European network of GMO laboratories. Definition of minimum performance requirements for analytical methods of GMO testing. 2015. http://gmo-crl.jrc.ec.europa.eu/doc/MPR%20Report%20Application%2020_10_2015.pdf Accessed on 26 January 2018.

  18. Corbisier P, Barbante A, Berben G, Broothaerts W, De Loose M, Emons H, Georgieva TZ, Lievens A, Mazzara M, Papazova N, Perri E, Sowa S, Stebih D, Terzi V, Trapmann S. Recommendation for the unit of measurement and the measuring system to report traceable and comparable results expressing GM content in accordance with EU legislation. EUR28536 EN. 2017; https://doi.org/10.2760/177516

  19. Arumuganathan K, Earle ED. Nuclear content of some important plant species. Plant Mol Biol Rep. 1991;9:208–18.

    Article  CAS  Google Scholar 

  20. Majumdar N, Wessel T, Marks J. Digital PCR modeling for maximal sensitivity, dynamic range and measurement precision. PLOSone. 2015. https://doi.org/10.1371/journal.pone.0118833.

  21. Dobnik D, Demsar T, Huber I, Gerdes L, Broeders S, Roosens N, et al. Inter-laboratory analysis of selected genetically modified plant reference materials with digital PCR. Anal Bioanal Chem. 2018;410:211–21.

    Article  CAS  PubMed  Google Scholar 

  22. Chaouachi M, Berard A, Saïd K. Relative quantification in seed GMO analysis: state of art and bottlenecks. Transgenic Res. 2013;22:461–76.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The authors would like to thank Pia Scheu and Cyril Dubuck from Bio-Rad for their technical and scientific support during our study.

Author information

Authors and Affiliations

  1. Institute of Food Safety & Analytical Sciences - Nestlé Research, Vers-chez-les-Blanc, 1000, Lausanne 26, Switzerland

    Geoffrey Cottenet & Carine Blancpain

  2. Nestlé Quality Assurance Center, 29 Quality Road, Singapore, 618802, Singapore

    Poh Fong Chuah

Authors
  1. Geoffrey Cottenet
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Carine Blancpain
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Poh Fong Chuah
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Geoffrey Cottenet.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cottenet, G., Blancpain, C. & Chuah, P.F. Performance assessment of digital PCR for the quantification of GM-maize and GM-soya events. Anal Bioanal Chem 411, 2461–2469 (2019). https://doi.org/10.1007/s00216-019-01692-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00216-019-01692-7

Keywords

Search

Navigation