Semiautomated TaqMan PCR screening of GMO labelled samples for (unauthorised) GMOs

Event-specific quantitative polymerase chain reaction methods for detection of double-herbicide-resistant genetically modified corn MON 87419 based on the 3'-junction of the insertion site

MON 87419 was one of the new transgenic corn events developed in US with the trait of herbicide resistance to both dicamba and glyphosate. To monitor unintended release of genetically modified organism in the future, as well as to meet GM-labeling requirements, it is requisite to develop a reliable method for the detection and quantification of MON 87419, an event-specific primer pair was designed to amplify the 3'-junction site between the endogenous genome sequence and the transferred DNA of GM event MON 87419, amplicons of desired size were produced by qualitative polymerase chain reaction (PCR) assay. For the validation of this quantitative method, the mixed samples containing 10%, 1%, and 0.1% MON 87419 ingredient were quantified. The precisions were expressed as relative standard deviations, deviated by 7.87%, 12.94%, and 19.98%, respectively. These results clearly demonstrate that the PCR methods we developed herein can be used for event-specific quantitative testing of the double-herbicide-resistant corn MON 87419.

Molecular Characterization and Event-Specific Real-Time PCR Detection of Two Dissimilar Groups of Genetically Modified Petunia (Petunia x hybrida) Sold on the Market

Petunia plants with unusual orange flowers were noticed on the European market and confirmed to be genetically modified (GM) by the Finnish authorities in spring 2017. Later in 2017, inspections and controls performed by several official laboratories of national competent authorities in the European Union detected several GM petunia varieties with orange flowers, but also another group of unusually colored flowers. In the latter group, a so far undetected gene coding for a flavonoid 3'5' hydroxylase (F3'5'H) responsible for the purple color was identified by German and Dutch authorities, suggesting that the petunias found on the markets contain different genetic constructs. Here, a strategy is described for the identification of GM petunia varieties. It is based on an initial GMO screening for known elements using (real-time) PCR and subsequent identification of the insertion sites by a gene walking-like approach called ALF (amplification of linearly-enriched fragments) in combination with Sanger and MinION sequencing. The results indicate that the positively identified GM petunias can be traced back to two dissimilar GM events used for breeding of the different varieties. The test results also confirm that the transgenic petunia event RL01-17 used in the first German field trial in 1991 is not the origin of the GM petunias sold on the market. On basis of the obtained sequence data, event-specific real-time PCR confirmatory methods were developed and validated. These methods are applicable for the rapid detection and identification of GM petunias in routine analysis. In addition, a decision support system was developed for revealing the most likely origin of the GM petunia.

Multiplex quantitative PCR for single-reaction genetically modified (GM) plant detection and identification of false-positive GM plants linked to Cauliflower mosaic virus (CaMV) infection

Background

Most genetically modified (GM) plants contain a promoter, P35S, from the plant virus, Cauliflower mosaic virus (CaMV), and many have a terminator, TNOS, derived from the bacterium, Agrobacterium tumefaciens. Assays designed to detect GM plants often target the P35S and/or TNOS DNA sequences. However, because the P35S promoter is derived from CaMV, these detection assays can yield false-positives from non-GM plants infected by this naturally-occurring virus.

Results

Here we report the development of an assay designed to distinguish CaMV-infected plants from GM plants in a single multiplexed quantitative PCR (qPCR) reaction. Following initial testing and optimization via PCR and singleplex-to-multiplex qPCR on both plasmid and plant DNA, TaqMan qPCR probes with different fluorescence wavelengths were designed to target actin (a positive-control plant gene), P35S, P3 (a CaMV-specific gene), and TNOS. We tested the specificity of our quadruplex qPCR assay using different DNA extracts from organic watercress and both organic and GM canola, all with and without CaMV infection, and by using commercial and industrial samples. The limit of detection (LOD) of each target was determined to be 1% for actin, 0.001% for P35S, and 0.01% for both P3 and TNOS.

Conclusions

This assay was able to distinguish CaMV-infected plants from GM plants in a single multiplexed qPCR reaction for all samples tested in this study, suggesting that this protocol is broadly applicable and readily transferrable to any interested parties with a qPCR platform.

ALF: a strategy for identification of unauthorized GMOs in complex mixtures by a GW-NGS method and dedicated bioinformatics analysis

The majority of feed products in industrialised countries contains materials derived from genetically modified organisms (GMOs). In parallel, the number of reports of unauthorised GMOs (UGMOs) is gradually increasing. There is a lack of specific detection methods for UGMOs, due to the absence of detailed sequence information and reference materials. In this research, an adapted genome walking approach was developed, called ALF: Amplification of Linearly-enriched Fragments. Coupling of ALF to NGS aims for simultaneous detection and identification of all GMOs, including UGMOs, in one sample, in a single analysis. The ALF approach was assessed on a mixture made of DNA extracts from four reference materials, in an uneven distribution, mimicking a real life situation. The complete insert and genomic flanking regions were known for three of the included GMO events, while for MON15985 only partial sequence information was available. Combined with a known organisation of elements, this GMO served as a model for a UGMO. We successfully identified sequences matching with this organisation of elements serving as proof of principle for ALF as new UGMO detection strategy. Additionally, this study provides a first outline of an automated, web-based analysis pipeline for identification of UGMOs containing known GM elements.