How Can We Better Detect Unauthorized GMOs in Food and Feed Chains?

Fraiture, Marie‐Alice; Herman, Philippe; Loose, Marc De; Debode, Frédéric; Roosens, Nancy

doi:10.1016/j.tibtech.2017.03.002

Cited by 43 publications

(39 citation statements)

References 47 publications

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“…Thus, the development of new detection methods is needed to cope with the increase in newly approved LMOs and continuous unintentional release of LMOs. In recent studies about detection analysis to LMOs, methods to discriminate each LMO event from others through PCR amplification were employed, as well as other various technologies such as qPCR, ME-qPCR, droplet digital PCR, microarray, nextgeneration sequencing, LAMP, PCR CGE and Luminex assay [12][13][14][15][16][17][18][19]. This study was intended for the development of an easy and moderate analytic method detecting LMOs in a Laboratory of Molecular Biology.…”

Section: Electronic Supplementary Materialsmentioning

confidence: 99%

Development and application of a novel multiplex PCR method for four living modified soybeans

Choi

Seol

et al. 2018

Appl Biol Chem

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Since the early 1990s when the first commercialization of living modified organism (LMO), LMO has been developed to improve nutrient quality and productivity of crops. As the self-sufficiency rate of soybean has gradually decreased in South Korea, most of soybeans have been imported. The cultivation and trade of LM crops are regulated in many countries and authorizations for the use are mandatory in most. In South Korea, the cultivation of LM crop is not allowed and unintentional release of LMO into the natural environment is prohibited. In this study, we developed a novel multiplex PCR method for four LM soybean events (CV127, MON87705, FG72 and MON87701) which were approved recently in South Korea. Multiplex PCR primers were designed for PCR amplification of four LMO event-specific fragments, and we analyzed 41 environmental monitoring samples to confirm the efficiency of this method. These results indicated that the multiplex PCR detection method is sufficient for four LM soybeans found in the natural environment. Based on our finding, we suggest that the new technique may be useful as a lead tool for the development of a detection method for various LMO/GMOs.

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Section: Electronic Supplementary Materialsmentioning

confidence: 99%

Development and application of a novel multiplex PCR method for four living modified soybeans

Choi

Seol

et al. 2018

Appl Biol Chem

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“…Next generation sequencing is a novel technique which is recently proposed with an aim of dealing with the challenges linked with detection of transgenic events of GMOs. It is a promising technology that allows for massively parallel DNA segment sequencing resulting in millions of sequencing read ( Willems et al, 2015 ; Fraiture et al, 2017 ). NGS is an efficient tool for transgenic events detection even in the absence of sequence information of such events ( Randhawa et al, 2016 ).…”

Section: Next Generation Sequencing (Ngs)mentioning

confidence: 99%

“…NGS is being efficiently employed for characterization of site addition, flanking regions, accidental addition as well as the determination of transgene copy number ( Milavec et al, 2014 ). Two main approaches (targeted sequencing strategy) or [whole genome sequencing (WGS) strategy], for samples sequencing which has been enriched previously with desire sequence regions have been identified ( Table 7 ) ( Fraiture et al, 2017 ).…”

Section: Next Generation Sequencing (Ngs)mentioning

confidence: 99%

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Molecular Approaches for High Throughput Detection and Quantification of Genetically Modified Crops: A Review

et al. 2017

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As long as the genetically modified crops are gaining attention globally, their proper approval and commercialization need accurate and reliable diagnostic methods for the transgenic content. These diagnostic techniques are mainly divided into two major groups, i.e., identification of transgenic (1) DNA and (2) proteins from GMOs and their products. Conventional methods such as PCR (polymerase chain reaction) and enzyme-linked immunosorbent assay (ELISA) were routinely employed for DNA and protein based quantification respectively. Although, these Techniques (PCR and ELISA) are considered as significantly convenient and productive, but there is need for more advance technologies that allow for high throughput detection and the quantification of GM event as the production of more complex GMO is increasing day by day. Therefore, recent approaches like microarray, capillary gel electrophoresis, digital PCR and next generation sequencing are more promising due to their accuracy and precise detection of transgenic contents. The present article is a brief comparative study of all such detection techniques on the basis of their advent, feasibility, accuracy, and cost effectiveness. However, these emerging technologies have a lot to do with detection of a specific event, contamination of different events and determination of fusion as well as stacked gene protein are the critical issues to be addressed in future.

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“…Yuan and colleagues [1] review contemporary sequencing technologies, sometimes called next-generation or second-generation sequencing, as they are applied to the particularly tricky problem of crop genomics. Fraiture and colleagues [2] propose a workflow incorporating omics data and next-generation sequencing to detect genetic elements associated with genetically modified organisms in food and feed supplies, an especially timely idea as governments across the world grapple with whether and how to regulate genetically modified foods. Goh, Wang, and Wong [3] describe their perspective on avoiding and correcting 'batch effects', which can create artifactual conclusionsor mask biologically important onesin omics data gathered from different experiments that were (ostensibly) performed identically.…”

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confidence: 99%

Computing in Biotechnology: Omics and Beyond

Pavlovich¹

2017

Trends in Biotechnology

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It's become cliché to describe the ubiquity of computers in nearly every facet of modern society: how our telephones have orders of magnitude more computational power than the first integrated circuits that guided humans into space, how our thermostats and doorbells have become automated and controllable from anywhere with an Internet connection, how every year our cars better understand how to drive themselves.Computation has proliferated in applied biology as much as it has in daily life, and the myriad applications of computation to biology form the basis of this special issue of Trends in Biotechnology. Perhaps the most salient expression of contemporary computational biology is bioinformatics, in particular using computers to navigate the vast seas of data generated in the omics disciplines. Yuan and colleagues [1] review contemporary sequencing technologies, sometimes called next-generation or second-generation sequencing, as they are applied to the particularly tricky problem of crop genomics. Fraiture and colleagues [2] propose a workflow incorporating omics data and next-generation sequencing to detect genetic elements associated with genetically modified organisms in food and feed supplies, an especially timely idea as governments across the world grapple with whether and how to regulate genetically modified foods. Goh, Wang, and Wong [3] describe their perspective on avoiding and correcting 'batch effects', which can create artifactual conclusionsor mask biologically important onesin omics data gathered from different experiments that were (ostensibly) performed identically. Finally, a short article by Franceschi and colleagues [4] describes how certain amino acid sequences are correlated with protein toxicity and suggests that proteomics approaches can help to predict whether a newly engineered protein may pose health risks.One common theme to many of the articles in this issue is using cloud and Web computing to solve complicated biological problems, either as a distributed parallel computing platform or as a way to make bioinformatics workflows available to researchers and practitioners who don't necessarily have access to supercomputers. FoldIt (https://fold.it/portal/), a gamified and crowdsourced approach to understanding protein structures and structure-function relationships, was an early success in decentralized computing in biotechnology. Many cloud-based solutions in metabolomics and genomics have followed, as discussed in short articles by Warth and colleagues [5] and Celesti and colleagues [6].Beyond omics applications, computational approaches have been used to model biological systems on a wide range of scales, from single-molecule interactions to organism-wide metabolism. Fernández and Scott [7] give a thermodynamic rationale for apparently counterintuitive results in lead optimization in drug design and emphasize the need to model multi-body interactions to better understand how candidate drugs interact with target proteins. In addition, Yuan, Chan, and Hu [8] review the use of Web bro...

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How Can We Better Detect Unauthorized GMOs in Food and Feed Chains?

Cited by 43 publications

References 47 publications

Development and application of a novel multiplex PCR method for four living modified soybeans

Development and application of a novel multiplex PCR method for four living modified soybeans

Molecular Approaches for High Throughput Detection and Quantification of Genetically Modified Crops: A Review

Computing in Biotechnology: Omics and Beyond

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