Liquid-phase hybridization based PCR-ELISA for detection of genetically modified organisms in food

Detection of GM Canola MS11, DP-073496-4, and MON88302 events using multiplex PCR coupled with capillary electrophoresis

As of 2020, 11 GM canola events have been authorized as food for humans in Korea. However, there are no simultaneous multiplex detection methods for 3 GM canola events (DP-073496-4, MON88302, and MS11). Thus, we established the multiplex polymerase chain reaction (PCR) method coupled with capillary electrophoresis to detect 3 GM canola events. To verify the specificity of event-specific primers, various GM crops of 3 GM soybean events, 6 GM maize events, 2 GM cotton events and 11 GM canola events were prepared. The limit of detection of the developed multiplex PCR was approximately 0.0125% for 3 GM canola events. Certified GM canola and stacked events were analyzed to validate the developed multiplex PCR. This study focuses on establishing multiplex PCR coupled with capillary electrophoresis for newly approved GM canola events and contributes to efficient monitoring GM canola samples in Korea.

Ultrasensitive Single Fluorescence-Labeled Probe-Mediated Single Universal Primer-Multiplex-Droplet Digital Polymerase Chain Reaction for High-Throughput Genetically Modified Organism Screening

As genetically modified (GM) technology develops and genetically modified organisms (GMOs) become more available, GMOs face increasing regulations and pressure to adhere to strict labeling guidelines. A singleplex detection method cannot perform the high-throughput analysis necessary for optimal GMO detection. Combining the advantages of multiplex detection and droplet digital polymerase chain reaction (ddPCR), a single universal primer-multiplex-ddPCR (SUP-M-ddPCR) strategy was proposed for accurate broad-spectrum screening and quantification. The SUP increases efficiency of the primers in PCR and plays an important role in establishing a high-throughput, multiplex detection method. Emerging ddPCR technology has been used for accurate quantification of nucleic acid molecules without a standard curve. Using maize as a reference point, four heterologous sequences ( 35S, NOS, NPTII, and PAT) were selected to evaluate the feasibility and applicability of this strategy. Surprisingly, these four genes cover more than 93% of the transgenic maize lines and serve as preliminary screening sequences. All screening probes were labeled with FAM fluorescence, which allows the signals from the samples with GMO content and those without to be easily differentiated. This fiveplex screening method is a new development in GMO screening. Utilizing an optimal amplification assay, the specificity, limit of detection (LOD), and limit of quantitation (LOQ) were validated. The LOD and LOQ of this GMO screening method were 0.1% and 0.01%, respectively, with a relative standard deviation (RSD) < 25%. This method could serve as an important tool for the detection of GM maize from different processed, commercially available products. Further, this screening method could be applied to other fields that require reliable and sensitive detection of DNA targets.

Discrimination of transgenic soybean seeds by terahertz spectroscopy

Discrimination of genetically modified organisms is increasingly demanded by legislation and consumers worldwide. The feasibility of a non-destructive discrimination of glyphosate-resistant and conventional soybean seeds and their hybrid descendants was examined by terahertz time-domain spectroscopy system combined with chemometrics. Principal component analysis (PCA), least squares-support vector machines (LS-SVM) and PCA-back propagation neural network (PCA-BPNN) models with the first and second derivative and standard normal variate (SNV) transformation pre-treatments were applied to classify soybean seeds based on genotype. Results demonstrated clear differences among glyphosate-resistant, hybrid descendants and conventional non-transformed soybean seeds could easily be visualized with an excellent classification (accuracy was 88.33% in validation set) using the LS-SVM and the spectra with SNV pre-treatment. The results indicated that THz spectroscopy techniques together with chemometrics would be a promising technique to distinguish transgenic soybean seeds from non-transformed seeds with high efficiency and without any major sample preparation.

Discrimination of genetically modified sugar beets based on terahertz spectroscopy

The objective of this paper was to apply terahertz (THz) spectroscopy combined with chemometrics techniques for discrimination of genetically modified (GM) and non-GM sugar beets. In this paper, the THz spectra of 84 sugar beet samples (36 GM sugar beets and 48 non-GM ones) were obtained by using terahertz time-domain spectroscopy (THz-TDS) system in the frequency range from 0.2 to 1.2 THz. Three chemometrics methods, principal component analysis (PCA), discriminant analysis (DA) and discriminant partial least squares (DPLS), were employed to classify sugar beet samples into two groups: genetically modified organisms (GMOs) and non-GMOs. The DPLS method yielded the best classification result, and the percentages of successful classification for GM and non-GM sugar beets were both 100%. Results of the present study demonstrate the usefulness of THz spectroscopy together with chemometrics methods as a powerful tool to distinguish GM and non-GM sugar beets.

Discrimination of transgenic tomatoes based on visible/near-infrared spectra

VIS-NIR spectroscopy combined with multivariate analysis after the appropriate spectral data pre-treatment has been proved to be a very powerful tool for judgment of the relative pattern of the objects that have very similar properties. In this study, seventy transgenic tomatoes with antisense LeETR2 and 94 of their parents, non-transgenic ones were measured in VIS-NIR diffuse reflectance mode. Principal component analysis (PCA), discriminant analysis (DA) and partial least-squares discriminant analysis (PLSDA) were applied to classify tomatoes with different genes into two groups. Calibrations were developed using PLS regression with the leave-one-out cross-validation technique. The results show that differences between transgenic and non-transgenic tomatoes do exist and excellent classification can be obtained after optimizing spectral pre-treatment. The correct classifications for transgenic and non-transgenic tomatoes were both 100% using PLSDA after derivative spectral pre-treatment. The raw spectra with PLSDA model after the second derivative pre-treatment had the best satisfactory calibration and prediction abilities, with r(c)=0.97964, root mean square error of calibration (RMSEC)=0.099, r(cv)=0.97963, root mean square error of cross-validation (RMSECV)=0.0993 and a factor. The results in the present study show VIS-NIR spectroscopy together with chemometrics techniques could be used to differentiate transgenic tomato, which offers the benefit of avoiding time-consuming, costly and laborious chemical and sensory analysis.

Microchip capillary gel electrophoresis using programmed field strength gradients for the ultra-fast analysis of genetically modified organisms in soybeans

We have developed a novel method for the ultra-fast analysis of genetically modified organisms (GMOs) in soybeans by microchip capillary gel electrophoresis (MCGE) using programmed field strength gradients (PFSG) in a conventional glass double-T microchip. Under the programmed electric field strength and 0.3% poly(ethylene oxide) sieving matrix, the GMO in soybeans was analyzed within only 11 s of the microchip. The MCGE-PFSG method was a program that changes the electric field strength during GMO analysis, and was also applied to the ultra-fast analysis of PCR products. Compared to MCGE using a conventional and constantly applied electric field, the MCGE-PFSG analysis generated faster results without the loss of resolving power and reproducibility for specific DNA fragments (100- and 250-bp DNA) of GM-soybeans. The MCGE-PFSG technique may prove to be a new tool in the GMO analysis due to its speed, simplicity, and high efficiency.

The use of genetically modified Saccharomyces cerevisiae strains in the wine industry

In recent decades, science and food technology have contributed at an accelerated rate to the introduction of new products to satisfy nutritional, socio-economic and quality requirements. With the emergence of modern molecular genetics, the industrial importance of Saccharomyces cerevisiae, is continuously extended. The demand for suitable genetically modified (GM) S. cerevisiae strains for the biofuel, bakery and beverage industries or for the production of biotechnological products (e.g. enzymes, pharmaceutical products) will continuously grow in the future. Numerous specialised S. cerevisiae wine strains were obtained in recent years, possessing a wide range of optimised or novel oenological properties, capable of satisfying the demanding nature of modern winemaking practise. The unlocking of transcriptome, proteome and metabolome complexities will contribute decisively to the knowledge about the genetic make-up of commercial yeast strains and will influence wine strain improvement via genetic engineering. The most relevant advances regarding the importance and implications of the use of GM yeast strains in the wine industry are discussed in this mini-review. In this work, various aspects are considered including the strategies used for the construction of strains with respect to current legislation requirements, the environmental risk evaluations concerning the deliberate release of genetically modified yeast strains, the methods for detection of recombinant DNA and protein that are currently under evaluation, and the reasons behind the critical public perception towards the application of such strains.