Model for tuning GMO detection in seed and grain

Macarthur, Roy; Murray, Alistair; Allnutt, Theo R.; Deppe, Carola; Hird, Heather; Kerins, Gerard M.; Blackburn, James; Brown, Joy; Stones, Robert; Hugo, Sarah

doi:10.1038/nbt0207-169

Cited by 18 publications

(8 citation statements)

References 4 publications

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“…Within the GMO sector significant work has been undertaken on investigating and developing sampling strategies for the analysis of GMOs in bulk consignments. [18][19][20] Within the Kernel lot distribution assessment (KeLDA) project 20 the GMO content of 15 soybean lots imported into the EU was estimated by analysing 100 increment samples systematically sampled from each lot at predetermined time intervals during the whole off-loading process. The distribution of GMO material was inferred by the temporal distribution of contaminated increments.…”

Section: Samplingmentioning

confidence: 99%

Measurement issues associated with quantitative molecular biology analysis of complex food matrices for the detection of food fraud

Burns¹,

Wiseman

Knight

et al. 2016

Analyst

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Following a report on a significant amount of horse DNA being detected in a beef burger product on sale to the public at a UK supermarket in early 2013, the Elliott report was published in 2014 and contained a list of recommendations for helping ensure food integrity. One of the recommendations included improving laboratory testing capacity and capability to ensure a harmonised approach for testing for food authenticity. Molecular biologists have developed exquisitely sensitive methods based on the polymerase chain reaction (PCR) or mass spectrometry for detecting the presence of particular nucleic acid or peptide/protein sequences. These methods have been shown to be specific and sensitive in terms of lower limits of applicability, but they are largely qualitative in nature. Historically, the conversion of these qualitative techniques into reliable quantitative methods has been beset with problems even when used on relatively simple sample matrices. When the methods are applied to complex sample matrices, as found in many foods, the problems are magnified resulting in a high measurement uncertainty associated with the result which may mean that the assay is not fit for purpose. However, recent advances in the technology and the understanding of molecular biology approaches have further given rise to the re-assessment of these methods for their quantitative potential. This review focuses on important issues for consideration when validating a molecular biology assay and the various factors that can impact on the measurement uncertainty of a result associated with molecular biology approaches used in detection of food fraud, with a particular focus on quantitative PCR-based and proteomics assays.

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Section: Samplingmentioning

confidence: 99%

Measurement issues associated with quantitative molecular biology analysis of complex food matrices for the detection of food fraud

Burns¹,

Wiseman

Knight

et al. 2016

Analyst

View full text Add to dashboard Cite

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“…Vice versa, the cost of the analysis can be higher if multiple small samples are taken from the lot of origin and analysed. A mathematical model for tuning GMO detection in seed and grain was proposed by Macarthur et al (2007).…”

Section: Cost Of Samplingmentioning

confidence: 99%

The relevance of sampling for the control of genetically modified organisms in the agri-food chain

Brera¹,

Santis²,

Prantera³

et al. 2011

Food Chain Integrity

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“…Therefore, many of the previous studies also performed other forms of confirmatory analysis, such as southern blots. Macarthur et al (2007) have applied a model to examine the detection of unauthorized events in oilseed rape, Brassica napus, and in particular to explore how heterogeneity in the sampled lot affects the limit of detection (LOD), as well as how LOD values can be modified by choice of sampling plan, analytical replication scheme and reliable indication of false-positive rate. LOD refers to the lowest amount of transgenic material that the method is able to detect.…”

Section: The Potential For False Negatives and False Positives In Pcrmentioning

confidence: 99%

“…The model of Macarthur et al (2007) reveals three things: (a) that the LOD can vary by a factor of 100, depending on the degree of lot heterogeneity; (b) it can vary by an order of magnitude depending on the control plan used to detect GMOs, such as pooling of sub-samples and/or number of replicates; and (c) it can be underestimated by a factor of 20 if it is estimated using validation of the analytical method alone. The authors concluded that the three observations show the importance of an integrated assessment of the whole detection system and consideration of potential lot heterogeneity, which is frequently overlooked in practice (Macarthur et al 2007). This is particularly the case for commercially prepared PCR kits for GMO detection, which still do not consider heterogeneous samples.…”

Section: The Potential For False Negatives and False Positives In Pcrmentioning

confidence: 99%

Challenges for transgene detection in landraces and wild relatives: learning from 15 years of debate over GM maize in Mexico

Agapito-Tenfen

Wickson

2017

Biodivers Conserv

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Maize is one of the world's five staple cereals and its traditional varieties constitute a global resource critical to future agricultural development. Fifteen years ago, claims that transgenes had spread into traditional landrace maize in Mexico started an international discussion on the scale and significance of transgene flow from genetically modified (GM) crops to centres of crop origin and genetic diversity. The initial discovery of transgenes in landrace maize sparked an intense environmental dispute in which the culture and traditions of indigenous people were seen as threatened by the unchecked spread of biotechnological inventions from multinational corporations. This dispute was reflected in a political and legal battle over the regulatory status of GM crops in Mexico, which continues today as approvals of GM maize for cultivation remain subject to contestation in the courts. These legal, political and environmental disputes have been fanned by the existence of a significant scientific controversy over the methods for GM detection. The use of various approaches and a lack of harmonized methods specific for monitoring and detection of transgenes in landraces has generated both positive and negative results for GM contamination in Mexico over the years. In this paper, we review the peerreviewed literature on transgene detection in Mexican maize and highlight the challenges associated with transgene detection in landraces. In doing so, we identify the key methodological aspects under dispute and pinpoint the research bottlenecks and needs for building the capacity to effectively monitor transgene escape from GM crops to wild relatives or landraces.

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Model for tuning GMO detection in seed and grain

Cited by 18 publications

References 4 publications

Measurement issues associated with quantitative molecular biology analysis of complex food matrices for the detection of food fraud

Measurement issues associated with quantitative molecular biology analysis of complex food matrices for the detection of food fraud

The relevance of sampling for the control of genetically modified organisms in the agri-food chain

Challenges for transgene detection in landraces and wild relatives: learning from 15 years of debate over GM maize in Mexico

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