The proteins were most abundant in southeast Mexico Veracruz State but were also present in the west-central region Guanajuato and Oaxaca State. A novel element of this study was the inclusion of a social dimension to the empirical data—estimating critical parameters of seed population dynamics using household survey data and combining these estimates with analytical results to examine presumed sources and mechanisms of dispersal.
For the first time, their social data indicated that diffusion of seed and grain imported from the United States might explain the frequency and distribution of transgenes in west-central Mexico, although not in the southeast. This was the second time that transgenes were found to be present in areas outside the Oaxaca region, with a much larger sampling effort, and the evidence provided in this report also received no published criticism by the scientific community. In summary then, the published empirical research on transgene flow into landrace maize in Mexico has involved: a studies conducted across different years, b studies conducted in different locations, c studies using a range of sampling strategies and sizes, d studies using different test materials i.
It is perhaps therefore no surprise that results and conclusions have varied across them. What is particularly relevant to note though is that even within studies using the same material, different results have been obtained through the use of different methods, as well as across different laboratories performing the analysis which may use slightly different procedures, subsamples or detection limits. Furthermore, although studies using the DNA-based technique of PCR have been critiqued in the published literature, interestingly both studies using non-DNA based methods to detect transgenic proteins have reported positive results without receiving methodological critique from the scientific community.
This is despite the fact that ELISA, as any protein-based method, is also prone to false positives and negatives.
False positives can for example occur when other proteins cross-talk with epitopes developed for target GM proteins Prakoso et al. False negatives can occur if the concentration of GM proteins is below the limit of detection, which can happen because methods for GM protein detection depend on the expression level of targeted proteins and this varies according to the plant tissues and the plant developmental stage Fraiture et al. Moreover, target proteins might be degraded or denatured by sample processing and any modification in the targeted proteins could alter the specificity and sensitivity of the assay Fraiture et al.
Also worth noting is that although studies have been done to show the potential for pollination and hybridization between transgenic maize and its wild relative teosinte Baltazar et al. Despite the controversy and high-level significance of this issue in scientific, policy and public arenas, no further experimental work on GM detection in landraces of maize in Mexico has been published since Indeed, while the methodological limitations and ongoing uncertainty surrounding the most reliable and appropriate methods for transgene detection in landraces and wild relatives may not be the only reason for the absence of testing since , this methodological uncertainty clearly affects the ability to perform reliable research that can robustly stand up to critique and produce results that can be trusted to pass through peer-review to publication.
In the following sections we therefore draw out exactly what these methodological challenges are and make recommendations for how to proceed with future research. The different results indicating both transgene absence and presence have significant implications for the political, legal and regulatory arenas Bonneuil et al. Although the debate is amplified by the social and political importance of the findings, there are legitimate differences in scientific method that allow the lack of consensus to persist.
These different approaches in scientific method arguably remain debated because of the unique challenges facing transgene detection in landraces and wild relatives and the uncertainty that remains around how to handle detection of low level presence. Successful and sound detection of transgenes in landraces or wild relatives faces a number of unique methodological challenges that complicate the task of monitoring, particularly for the type of low level presence that is likely to occur in the field in places like Mexico where commercial cultivation is not approved.
Furthermore, methodological controls are typically based on endogenous genes or proteins and since these might differ in landraces and wild relatives, detection is dependent on developing relevant and adapted controls. However, all available detection methods also have intrinsic problems that become particularly relevant for working with landraces or wild relatives, such as quantitative limits for detecting small amounts of a substance.
Only comprehensive and transparent detection methodologies can provide an estimation of the quantitative uncertainties involved Box 1.
In what follows below, we summarise what we see as the three key challenge areas of environmental sampling, DNA isolation in heterogeneous samples, and the potential for false positives and negatives in PCR. Sampling design also directly affects the statistical analysis Dyer et al.
This was particularly in terms of what size sampling area would be sufficiently representative to allow conclusions about the entire state of Oaxaca to be drawn and how the estimation of effective population size is performed to make claims regarding transgene frequency. If the objective of sampling is to determine presence or absence of transgenes in an area, landrace populations should be identified with the highest probability of containing them Cleveland et al. On the other hand, if the objective is determining the frequency of transgenes in the landrace population of a given area, it is necessary to use a sampling strategy that maximizes the probability of finding rare alleles in the reference population and is also representative of that population Cleveland et al.
In this case, it is important to take them from the maximum number of sampling units at each level e. In addition, an equal number of seeds should be sampled from each sampling unit Cleveland et al. These are concepts originating from population genetics and rarely applied to investigate transgene presence in centres of origin.
Drawing on and making better use of state of the art knowledge in population genetics and dynamics could certainly help design the appropriate sampling strategy for specific transgene monitoring objectives and indicates the potential value of incorporating a range of different disciplines in the development of study method and design.
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DNA-based detection methods such as PCR are undoubtedly the most commonly applied approach to transgene detection. Nonetheless, they depend on efficient DNA extraction, as well as strict cross-contamination controls. These are not pre-requisites specific to landraces and wild relatives but applying the standard quality control protocols might pose extra challenges to heterogeneous DNA samples, such as those from landraces. Uncertainty does, however, remain regarding how much interference these characteristics might have on with PCR efficiency in detecting transgenes and internal control genes and how to adapt current methodologies to overcome these.
However, DNA extraction methods and DNA quality standards are frequently only tested in highly homogeneous samples, such as modern maize varieties. One example is the ISO method of nucleic acid extraction for the detection of genetically modified organisms and derived products ISO In applying such protocols, the DNA extraction from a landrace sample will most likely vary in both amount and quality due to its heterogeneity.
The document further acknowledges methodological bottlenecks, such as the impact of different instrumentation, PCR reaction mixes, primer concentrations, etc. In heterogeneous samples, these criteria might be very difficult to achieve because slight differences in DNA target and inhibitors concentrations might affect Ct values and therefore perhaps other criteria should be applied to measure extracted DNA quality from such sources.
Although the ability to detect transgenic constructs is a pre-requisite for effective risk analysis, regulation and monitoring of GMOs Lezaun , this does not mean that the methods used necessarily operate in a flawless manner, nor that the knowledge available to carry out the methods is always complete. This is especially the case when the detection method is being applied to landraces and wild relatives rather the GM crop itself or its conventional alternatives. Many inhibitory molecules can interfere with primer binding and DNA amplification, consequently leading to false negative results.
On the other hand, primers are also prone to unspecific binding to highly homologous, but not identical, sequences, which might then lead to false positive results. False positive results might also arise from cross-contamination of samples during PCR reaction preparation. Therefore, many of the previous studies also performed other forms of confirmatory analysis, such as southern blots. Macarthur et al.
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LOD refers to the lowest amount of transgenic material that the method is able to detect. The model of Macarthur et al. 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. This is particularly the case for commercially prepared PCR kits for GMO detection, which still do not consider heterogeneous samples.
The LOD is always a critical matter. At near LOD concentrations, there is always a significant risk of false negative results for individual tests Holst-Jensen et al. When transgene flow or introgression have taken place in a landrace or wild relative, the copy numbers of PCR targets i. If two screening targets are present in a GMO but with different insert copy numbers, e.
However, this information is always unknown. According to Holst-Jensen et al. While the latter can be extrapolated from standard curves, it should be remembered that there is a possibility that the target present in the GMO may exhibit slightly divergent PCR performance from the target present in the standards.
None of the published papers on GM detection in maize in Mexico make reference to the application of such international guidelines in their testing. Partly this is simply because these guidelines were not fully developed at the time of the first publications and for later studies, the authors may have found them fit for purpose.
In fact, as noted in our review, PCR testing was frequently criticized and the call for non-PCR validation was observed in all critiques. International guidelines such as those from ENGL provide a set of parameters and acceptance criteria but do not mention the need for non-PCR methods to validate a PCR method, as was frequently called for in the Mexican case. Every measurement is subject to some uncertainty and, therefore, a measurement result is only complete within scientific studies if a statement of its uncertainty accompanies it.
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Measurement uncertainties can come from different sources, such as: the measuring instrument, the item being measured, the environment, the operator, etc. These uncertainties can be estimated using statistical analysis of a set of measurements, or using other kinds of information about the measurement process Bell The most applied approach to calculate measurement uncertainty MU in the field of GMO detection is a top-down approach, in which data from collaborative trials including all the factors influencing the MU during the analytical procedure are used as a source for the estimation of MU.
This approach is described in detail in the guidance document on measurement uncertainty for GMO testing laboratories produced by the ENGL working group on measurement uncertainty Zel et al.
When the outcome of the measurement of uncertainty is not adequate the performance characteristics do not satisfy all performance criteria set prior to the measurement , the method might be considered to be unreliable for its purpose. Detecting the presence of transgenes depends on analytical methods and their measurement uncertainties and there is currently no agreed and defined framework or harmonized methods specific for the detection of transgenes in landrace varieties and wild relatives in which low level presence may be the norm CBD There also seems to be a vacuum in the current international regulatory arena that deals with the potential risks of GMOs to the environment and animal and human health—the Cartagena Protocol on Biosafety under the umbrella of the Convention on Biological Diversity—since it also gives no specific attention to the unique challenges facing GM detection in landraces and wild relatives.
There is now an immensely valuable set of tools, approaches and international guidelines that continue to develop and provide a way to evaluate transgene presence. To support this ongoing development and to steer it in directions that are particularly useful for addressing the challenges associated with detection in landraces and wild relatives, here we offer lessons from our review of the published literature and scientific debate on the Mexican maize case for future work in this area.
The determination of a positive or negative result from a transgene testing analysis has two major stages. The first stage is related to the analysis and control of steps prior to the endpoint measurement e. In other words, what are the factors affecting the Ct value obtained in real-time experiments or the presence, absence or even the intensity of a band in a gel, and the confidence in the obtained value?
Transgene introgression from genetically modified crops to their wild relatives
The second stage is then the interpretation of the endpoint measurement. We discuss issues connected to both of these stages in turn below. The start of any study is clearly sampling and for the challenges associated with environmental sampling, it is important to have established a priori what scope of inference the research is going to take and then use this to help identify the appropriate sampling strategy. For environmental sampling and GMO monitoring in landraces or wild relatives, particular attention should also be given to identifying the environmental protection goals that are of interest, including what is important for different stakeholders such as regulators, farmers, researchers etc.
Wickson et al. This can help to guide the selection of boundaries for the environmental sampling.