In-House Validation of Four Duplex Droplet Digital PCR Assays to Quantify GM Soybean Events

Due to the increasing number of authorized events in the European Union, it is crucial for the official laboratories to enforce market control to detect and quantify genetically modified organisms. In this study, an in-house validation of quantitative duplex ddPCR methods was performed involving MON87701, MON87769, MON89788 and CV-127-9 assays with respect to the lectin reference gene. Since the ddPCR methods provide accurate quantification, show less sensitivity to PCR inhibitors and are more suitable for multiplexing compared to the real-time PCR, the optimization of the existing assays was performed with the exception of MON87701, according to the JRC Guidance documents and technical reports. However, some concerns related to practical settings for the quantitative multiplex of ddPCR methods and their validation were encountered; therefore, a general workflow to develop and validate a ddPCR-based method is shown. The obtained data and the validation performance parameters such as specificity, cross-talk, robustness, dynamic range, linearity, the limit of quantification, trueness and precision comply with international recommendations for GMO quantification methods. The duplex ddPCR methods here investigated are equivalent in terms of performance compared to the singleplex real-time PCR methods, showing higher flexibility and cost effectiveness.

Authors

Institutions

Publication Details

Journal
Foods
Published
2024-12-11
DOI
https://doi.org/10.3390/foods13244011
Citations
3
Primary Topic
Genetically Modified Organisms Research
Type
article
Field-Weighted Citation Impact
1.80

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

In-House Validation of Four Duplex Droplet Digital PCR Assays to Quantify GM Soybean Events

Ugo Marchesi, Davide La Rocca, Cristiana Fusco, Katia Spinella et al.
3 citations
Foods
Genetically Modified Organisms Research
1.80
article

In-House Validation of Four Duplex Droplet Digital PCR Assays to Quantify GM Soybean Events

Ugo Marchesi, Davide La Rocca, Cristiana Fusco, Katia Spinella, Sara Ciuffa, Stefania Peddis, Cinzia Quarchioni, Marisa Misto, Pamela Bonini, Daniela Verginelli, Lorella Peroni
article en
3 citations

Abstract

Due to the increasing number of authorized events in the European Union, it is crucial for the official laboratories to enforce market control to detect and quantify genetically modified organisms. In this study, an in-house validation of quantitative duplex ddPCR methods was performed involving MON87701, MON87769, MON89788 and CV-127-9 assays with respect to the lectin reference gene. Since the ddPCR methods provide accurate quantification, show less sensitivity to PCR inhibitors and are more suitable for multiplexing compared to the real-time PCR, the optimization of the existing assays was performed with the exception of MON87701, according to the JRC Guidance documents and technical reports. However, some concerns related to practical settings for the quantitative multiplex of ddPCR methods and their validation were encountered; therefore, a general workflow to develop and validate a ddPCR-based method is shown. The obtained data and the validation performance parameters such as specificity, cross-talk, robustness, dynamic range, linearity, the limit of quantification, trueness and precision comply with international recommendations for GMO quantification methods. The duplex ddPCR methods here investigated are equivalent in terms of performance compared to the singleplex real-time PCR methods, showing higher flexibility and cost effectiveness.

FoodsVol. 13(24)
Istituto Zooprofilattico Sperimentale delle Regioni Lazio e Toscana (IT)
Ministero della Salute
Openalex Percentile: Top 12%
Genetically Modified Organisms Research
1.80
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.