Two quantitative multiplex real-time PCR systems for the efficient GMO screening of food products

Monitoring of Infant Formula and Baby Food for the Pat and NOS Terminator of Genetically Modified Maize and Soybean by Real-time PCR in Iran

BACKGROUND

Soybean and maize are the most cultivated genetically modified (GM) plants. Because of the increase in the imports of GM products to Iran, infant formula and baby food, which is consumed by babies during their first month of life, can also contain soybean and maize. It has become fundamental to screen these types of products.

OBJECTIVES

The present study aimed to investigate the GM corn and soybean in baby food and infant formula using real-time polymerase chain reaction (PCR).

METHODS

A total of 60 baby food and infant formulas were collected randomly from the local drugstores in Tehran. Genomic DNA was extracted from all samples, then by real-time PCR detection, tested Pat/NOS. Internal control genes zein and lectin were used for maize and soybean, respectively.

RESULTS

Results showed that 5% of infant formulas and 5% of baby food, two Iranian and one imported baby food, and two imported and one Iranian infant formula were positive for pat. However, NOS was detected in none of the samples. The results showed positive results for the presence of the pat gene in the products without an appropriate label.

CONCLUSIONS

This article provides evidence of GM maize and soybean presence in baby food and infant formula in Iran.

QCM Sensor Arrays, Electroanalytical Techniques and NIR Spectroscopy Coupled to Multivariate Analysis for Quality Assessment of Food Products, Raw Materials, Ingredients and Foodborne Pathogen Detection: Challenges and Breakthroughs

Quality checks, assessments, and the assurance of food products, raw materials, and food ingredients is critically important to ensure the safeguard of foods of high quality for safety and public health. Nevertheless, quality checks, assessments, and the assurance of food products along distribution and supply chains is impacted by various challenges. For instance, the development of portable, sensitive, low-cost, and robust instrumentation that is capable of real-time, accurate, and sensitive analysis, quality checks, assessments, and the assurance of food products in the field and/or in the production line in a food manufacturing industry is a major technological and analytical challenge. Other significant challenges include analytical method development, method validation strategies, and the non-availability of reference materials and/or standards for emerging food contaminants. The simplicity, portability, non-invasive, non-destructive properties, and low-cost of NIR spectrometers, make them appealing and desirable instruments of choice for rapid quality checks, assessments and assurances of food products, raw materials, and ingredients. This review article surveys literature and examines current challenges and breakthroughs in quality checks and the assessment of a variety of food products, raw materials, and ingredients. Specifically, recent technological innovations and notable advances in quartz crystal microbalances (QCM), electroanalytical techniques, and near infrared (NIR) spectroscopic instrument development in the quality assessment of selected food products, and the analysis of food raw materials and ingredients for foodborne pathogen detection between January 2019 and July 2020 are highlighted. In addition, chemometric approaches and multivariate analyses of spectral data for NIR instrumental calibration and sample analyses for quality assessments and assurances of selected food products and electrochemical methods for foodborne pathogen detection are discussed. Moreover, this review provides insight into the future trajectory of innovative technological developments in QCM, electroanalytical techniques, NIR spectroscopy, and multivariate analyses relating to general applications for the quality assessment of food products.

Development and comparative study of a pat/bar real-time PCR assay for integrating the screening strategy of a GMO testing laboratory

BACKGROUND

The number and variety of genetically modified organisms (GMOs) used globally for the production of food and feed, and potentially circulating in the European Union (EU), is constantly increasing. This implies an additional effort for the EU enforcement laboratories to optimize available resources, to contain costs and time. A well established approach for streamlining the analytical workflow is the introduction of a screening step, typically based on a smart set of real-time polymerase chain reaction (PCR) screening methods. The multiplexing strategy, allowing the detection of several screening elements simultaneously, is a further optimization of this step.

RESULTS

In this study, we present the validation of a real-time PCR duplex assay for the pat and bar screening elements to be easily incorporated in the GMO diagnostic routine. We also provide a comparison between this method and the related singleplex and pre-spotted assays.

CONCLUSION

Our results fully respect all the validation parameters suggested by the Minimum Performance Criteria of the European Network of GMO Laboratories. Furthermore, the duplex assay is equivalent in terms of performance compared to the other two methods, but it shows a higher overall flexibility and cost effectiveness. © 2019 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Development of a multiplex polymerase chain reaction assay for the parallel detection of harmful algal bloom-forming species distributed along the Chinese coast

Harmful algal blooms (HABs) have adverse effects on the marine ecological environment, public health, and marine economy. Thus, methods for the accurate and rapid identification of harmful algal species are urgently needed for the effective monitoring of the occurrence of HABS. A method for the parallel detection of harmful algal species must be established because various HAB-forming algal species coexist in the marine environment. This work developed a multiplex PCR (mPCR) method that can simultaneously detect six common HAB-forming microalgal species distributed along the coast of China: Karlodinium veneficum (Kv), Chattonella marina (Cm), Skeletonema spp., Scrippsiella trochoidea (St), Karenia mikimotoi (Km), and Prorocentrum donghaiense (Pd). Specific mPCR primers were designed from the internal transcribed spacer rDNA or large subunit rDNA gene of the target algal species. The mPCR conditions were optimized. Each mPCR primer was subjected to a cross-reactivity test with other microalgae to confirm the specificity of the developed mPCR system. The results of the system stability test indicated that the background concentration of DNA tested did not affect the performance of the established mPCR system. The results of the sensitivity test showed that the detection limit of the proposed mPCR system for Kv, Cm, Km, and Pd was 0.6 ng μL^-1 and that for Skeletonema spp. and St was 0.06 ng μL^-1. Additional mPCR analysis with spiked field samples revealed that the detection limit of the mPCR system for Km, Pd, and Kv was 60 cells, whereas that for Cm, Skeletonema spp., and St was 6 cells. The convenience and accuracy of the established mPCR assay were further validated through tests with field samples. The proposed mPCR assay is characterized by parallel analysis, strong specificity, and stability and can be used to supplement morphology-based detection methods for algal species.

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

In most countries, systems are in place to analyse food products for the potential presence of genetically modified organisms (GMOs), to enforce labelling requirements and to screen for the potential presence of unauthorised GMOs. With the growing number of GMOs on the world market, a larger diversity of methods is required for informative analyses. In this paper, the specificity of an extended screening set consisting of 32 screening methods to identify different crop species (endogenous genes) and GMO elements was verified against 59 different GMO reference materials. In addition, a cost- and time-efficient strategy for DNA isolation, screening and identification is presented. A module for semiautomated analysis of the screening results and planning of subsequent event-specific tests for identification has been developed. The Excel-based module contains information on the experimentally verified specificity of the element methods and of the EU authorisation status of the GMO events. If a detected GMO element cannot be explained by any of the events as identified in the same sample, this may indicate the presence of an unknown unauthorised GMO that may not yet have been assessed for its safety for humans, animals or the environment.

Development and Interlaboratory Validation of a Simple Screening Method for Genetically Modified Maize Using a ΔΔC(q)-Based Multiplex Real-Time PCR Assay

A number of genetically modified (GM) maize events have been developed and approved worldwide for commercial cultivation. A screening method is needed to monitor GM maize approved for commercialization in countries that mandate the labeling of foods containing a specified threshold level of GM crops. In Japan, a screening method has been implemented to monitor approved GM maize since 2001. However, the screening method currently used in Japan is time-consuming and requires generation of a calibration curve and experimental conversion factor (C(f)) value. We developed a simple screening method that avoids the need for a calibration curve and C(f) value. In this method, ΔC(q) values between the target sequences and the endogenous gene are calculated using multiplex real-time PCR, and the ΔΔC(q) value between the analytical and control samples is used as the criterion for determining analytical samples in which the GM organism content is below the threshold level for labeling of GM crops. An interlaboratory study indicated that the method is applicable independently with at least two models of PCR instruments used in this study.

Current and new approaches in GMO detection: challenges and solutions

In many countries, genetically modified organisms (GMO) legislations have been established in order to guarantee the traceability of food/feed products on the market and to protect the consumer freedom of choice. Therefore, several GMO detection strategies, mainly based on DNA, have been developed to implement these legislations. Due to its numerous advantages, the quantitative PCR (qPCR) is the method of choice for the enforcement laboratories in GMO routine analysis. However, given the increasing number and diversity of GMO developed and put on the market around the world, some technical hurdles could be encountered with the qPCR technology, mainly owing to its inherent properties. To address these challenges, alternative GMO detection methods have been developed, allowing faster detections of single GM target (e.g., loop-mediated isothermal amplification), simultaneous detections of multiple GM targets (e.g., PCR capillary gel electrophoresis, microarray, and Luminex), more accurate quantification of GM targets (e.g., digital PCR), or characterization of partially known (e.g., DNA walking and Next Generation Sequencing (NGS)) or unknown (e.g., NGS) GMO. The benefits and drawbacks of these methods are discussed in this review.

Statistical framework for detection of genetically modified organisms based on Next Generation Sequencing

Because the number and diversity of genetically modified (GM) crops has significantly increased, their analysis based on real-time PCR (qPCR) methods is becoming increasingly complex and laborious. While several pioneers already investigated Next Generation Sequencing (NGS) as an alternative to qPCR, its practical use has not been assessed for routine analysis. In this study a statistical framework was developed to predict the number of NGS reads needed to detect transgene sequences, to prove their integration into the host genome and to identify the specific transgene event in a sample with known composition. This framework was validated by applying it to experimental data from food matrices composed of pure GM rice, processed GM rice (noodles) or a 10% GM/non-GM rice mixture, revealing some influential factors. Finally, feasibility of NGS for routine analysis of GM crops was investigated by applying the framework to samples commonly encountered in routine analysis of GM crops.