Jeroen P. van Dijk

Optimised padlock probe ligation and microarray detection of multiple (non-authorised) GMOs in a single reaction.

BackgroundTo maintain EU GMO regulations, producers of new GM crop varieties need to supply an event-specific method for the new variety. As a result methods are nowadays available for EU-authorised genetically modified organisms (GMOs), but only to a limited extent for EU-non-authorised GMOs (NAGs). In the last decade the diversity of genetically modified (GM) ingredients in food and feed has increased significantly. As a result of this increase GMO laboratories currently need to apply many different methods to establish to potential presence of NAGs in raw materials and complex derived products.ResultsIn this paper we present an innovative method for detecting (approved) GMOs as well as the potential presence of NAGs in complex DNA samples containing different crop species. An optimised protocol has been developed for padlock probe ligation in combination with microarray detection (PPLMD) that can easily be scaled up. Linear padlock probes targeted against GMO-events, -elements and -species have been developed that can hybridise to their genomic target DNA and are visualised using microarray hybridisation.In a tenplex PPLMD experiment, different genomic targets in Roundup-Ready soya, MON1445 cotton and Bt176 maize were detected down to at least 1%. In single experiments, the targets were detected down to 0.1%, i.e. comparable to standard qPCR.ConclusionCompared to currently available methods this is a significant step forward towards multiplex detection in complex raw materials and derived products. It is shown that the PPLMD approach is suitable for large-scale detection of GMOs in real-life samples and provides the possibility to detect and/or identify NAGs that would otherwise remain undetected.

Transcriptome analysis of potato tubers: Effects of different agricultural practices

The use of profiling techniques such as transcriptomics, proteomics, and metabolomics has been proposed to improve the detection of side effects of plant breeding processes. This paper describes the construction of a food safety-oriented potato cDNA microarray (FSPM). Microarray analysis was performed on a well-defined set of tuber samples of two different potato varieties, grown under different, well-recorded environmental conditions. Data were analyzed to assess the potential of transcriptomics to detect differences in gene expression due to genetic differences or environmental conditions. The most pronounced differences were found between the varieties Sante and Lady Balfour, whereas differences due to growth conditions were less significant. Transcriptomics results were confirmed by quantitative PCR. Furthermore, the bandwidth of natural variation of gene expression was explored to facilitate biological and/or toxicological evaluation in future assessments.

Gene expression profiling for food safety assessment: examples in potato and maize.

Since the mid 1990s, microarray analysis has become one of the few tools that can analyze the entire contents of a cell regarding a specific information type. Especially since the development of whole genome microarrays the technique can be considered truly holistic. Most DNA based microarrays are used for the analysis of the total of messenger RNAs (transcriptome) and provide a snap-shot of whats going on in a cell population at the time of sampling. Within the last few years also full genome plant microarrays have become available for several crop species. With these it has been shown that several growing conditions can be separated based on their transcriptome pattern, such as location, year of harvest and agricultural input system, but also different cultivars of the same crop species, including genetically modified ones. A database comprising expression levels of the transcriptome in many different circumstances with a history of safe use would be a good comparator for evaluation of new agricultural practices or cultivars, genetically modified or otherwise obtained. New techniques as next generation sequencing may overcome issues on throughput time and cost, standard operation procedures and array design for individual crops.

DNA enrichment approaches to identify unauthorized genetically modified organisms (GMOs)

With the increased global production of different genetically modified (GM) plant varieties, chances increase that unauthorized GM organisms (UGMOs) may enter the food chain. At the same time, the detection of UGMOs is a challenging task because of the limited sequence information that will generally be available. PCR-based methods are available to detect and quantify known UGMOs in specific cases. If this approach is not feasible, DNA enrichment of the unknown adjacent sequences of known GMO elements is one way to detect the presence of UGMOs in a food or feed product. These enrichment approaches are also known as chromosome walking or gene walking (GW). In recent years, enrichment approaches have been coupled with next generation sequencing (NGS) analysis and implemented in, amongst others, the medical and microbiological fields. The present review will provide an overview of these approaches and an evaluation of their applicability in the identification of UGMOs in complex food or feed samples.

Selection of reference genes for transcriptional analysis of edible tubers of potato (Solanum tuberosum L.)

Potato (Solanum tuberosum) yield has increased dramatically over the last 50 years and this has been achieved by a combination of improved agronomy and biotechnology efforts. Gene studies are taking place to improve new qualities and develop new cultivars. Reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) is a bench-marking analytical tool for gene expression analysis, but its accuracy is highly dependent on a reliable normalization strategy of an invariant reference genes. For this reason, the goal of this work was to select and validate reference genes for transcriptional analysis of edible tubers of potato. To do so, RT-qPCR primers were designed for ten genes with relatively stable expression in potato tubers as observed in RNA-Seq experiments. Primers were designed across exon boundaries to avoid genomic DNA contamination. Differences were observed in the ranking of candidate genes identified by geNorm, NormFinder and BestKeeper algorithms. The ranks determined by geNorm and NormFinder were very similar and for all samples the most stable candidates were C2, exocyst complex component sec3 (SEC3) and ATCUL3/ATCUL3A/CUL3/CUL3A (CUL3A). According to BestKeeper, the importin alpha and ubiquitin-associated/ts-n genes were the most stable. Three genes were selected as reference genes for potato edible tubers in RT-qPCR studies. The first one, called C2, was selected in common by NormFinder and geNorm, the second one is SEC3, selected by NormFinder, and the third one is CUL3A, selected by geNorm. Appropriate reference genes identified in this work will help to improve the accuracy of gene expression quantification analyses by taking into account differences that may be observed in RNA quality or reverse transcription efficiency across the samples.

Comparison and transfer testing of multiplex ligation detection methods for GM plants.

BackgroundWith the increasing number of GMOs on the global market the maintenance of European GMO regulations is becoming more complex. For the analysis of a single food or feed sample it is necessary to assess the sample for the presence of many GMO-targets simultaneously at a sensitive level. Several methods have been published regarding DNA-based multidetection. Multiplex ligation detection methods have been described that use the same basic approach: i) hybridisation and ligation of specific probes, ii) amplification of the ligated probes and iii) detection and identification of the amplified products. Despite they all have this same basis, the published ligation methods differ radically. The present study investigated with real-time PCR whether these different ligation methods have any influence on the performance of the probes. Sensitivity and the specificity of the padlock probes (PLPs) with the ligation protocol with the best performance were also tested and the selected method was initially validated in a laboratory exchange study.ResultsOf the ligation protocols tested in this study, the best results were obtained with the PPLMD I and PPLMD II protocols and no consistent differences between these two protocols were observed. Both protocols are based on padlock probe ligation combined with microarray detection. Twenty PLPs were tested for specificity and the best probes were subjected to further evaluation. Up to 13 targets were detected specifically and simultaneously. During the interlaboratory exchange study similar results were achieved by the two participating institutes (NIB, Slovenia, and RIKILT, the Netherlands).ConclusionsFrom the comparison of ligation protocols it can be concluded that two protocols perform equally well on the basis of the selected set of PLPs. Using the most ideal parameters the multiplicity of one of the methods was tested and 13 targets were successfully and specifically detected. In the interlaboratory exchange study it was shown that the selected method meets the 0.1% sensitivity criterion. The present study thus shows that specific and sensitive multidetection of GMO targets is now feasible.

Development of a multiplex DNA-based traceability tool for crop plant materials

The authenticity of food is of increasing importance for producers, retailers and consumers. All groups benefit from the correct labelling of the contents of food products. Producers and retailers want to guarantee the origin of their products and check for adulteration with cheaper or inferior ingredients. Consumers are also more demanding about the origin of their food for various socioeconomic reasons. In contrast to this increasing demand, correct labelling has become much more complex because of global transportation networks of raw materials and processed food products. Within the European integrated research project ‘Tracing the origin of food’ (TRACE), a DNA-based multiplex detection tool was developed—the padlock probe ligation and microarray detection (PPLMD) tool. In this paper, this method is extended to a 15-plex traceability tool with a focus on products of commercial importance such as the emmer wheat Farro della Garfagnana (FdG) and Basmati rice. The specificity of 14 plant-related padlock probes was determined and initially validated in mixtures comprising seven or nine plant species/varieties. One nucleotide difference in target sequence was sufficient for the distinction between the presence or absence of a specific target. At least 5% FdG or Basmati rice was detected in mixtures with cheaper bread wheat or non-fragrant rice, respectively. The results suggested that even lower levels of (un-)intentional adulteration could be detected. PPLMD has been shown to be a useful tool for the detection of fraudulent/intentional admixtures in premium foods and is ready for the monitoring of correct labelling of premium foods worldwide.

A case study to determine the geographical origin of unknown GM papaya in routine food sample analysis, followed by identification of papaya events 16-0-1 and 18-2-4

During routine monitoring for GMOs in food in the Netherlands, papaya-containing food supplements were found positive for the genetically modified (GM) elements P-35S and T-nos. The goal of this study was to identify the unknown and EU unauthorised GM papaya event(s). A screening strategy was applied using additional GM screening elements including a newly developed PRSV coat protein PCR. The detected PRSV coat protein PCR product was sequenced and the nucleotide sequence showed identity to PRSV YK strains indigenous to China and Taiwan. The GM events 16-0-1 and 18-2-4 could be identified by amplifying and sequencing events-specific sequences. Further analyses showed that both papaya event 16-0-1 and event 18-2-4 were transformed with the same construct. For use in routine analysis, derived TaqMan qPCR methods for events 16-0-1 and 18-2-4 were developed. Event 16-0-1 was detected in all samples tested whereas event 18-2-4 was detected in one sample. This study presents a strategy for combining information from different sources (literature, patent databases) and novel sequence data to identify unknown GM papaya events.

ALF: a strategy for identification of unauthorized GMOs in complex mixtures by a GW-NGS method and dedicated bioinformatics analysis

The majority of feed products in industrialised countries contains materials derived from genetically modified organisms (GMOs). In parallel, the number of reports of unauthorised GMOs (UGMOs) is gradually increasing. There is a lack of specific detection methods for UGMOs, due to the absence of detailed sequence information and reference materials. In this research, an adapted genome walking approach was developed, called ALF: Amplification of Linearly-enriched Fragments. Coupling of ALF to NGS aims for simultaneous detection and identification of all GMOs, including UGMOs, in one sample, in a single analysis. The ALF approach was assessed on a mixture made of DNA extracts from four reference materials, in an uneven distribution, mimicking a real life situation. The complete insert and genomic flanking regions were known for three of the included GMO events, while for MON15985 only partial sequence information was available. Combined with a known organisation of elements, this GMO served as a model for a UGMO. We successfully identified sequences matching with this organisation of elements serving as proof of principle for ALF as new UGMO detection strategy. Additionally, this study provides a first outline of an automated, web-based analysis pipeline for identification of UGMOs containing known GM elements.

Tuber proteome comparison of five potato varieties by principal component analysis

BACKGROUND Data analysis of omics data should be performed by multivariate analysis such as principal component analysis (PCA). The way data are clustered in PCA is of major importance to develop some classification systems based on multivariate analysis, such as soft independent modeling of class analogy (SIMCA). In a previous study a one-class classifier based on SIMCA was built using microarray data from a set of potatoes. The PCA grouped the transcriptomic data according to varieties. The present work aimed to use PCA to verify the clustering of the proteomic profiles for the same potato varieties. RESULTS Proteomic profiles of five potato varieties (Biogold, Fontane, Innovator, Lady Rosetta and Maris Piper) were evaluated by two-dimensional gel electrophoresis (2-DE) performed on two immobilized pH gradient (IPG) strip lengths, 13 and 24 cm, both under pH range 4-7. For each strip length, two gels were prepared from each variety; in total there were ten gels per analysis. For 13 cm strips, 199-320 spots were detected per gel, and for 24 cm strips, 365-684 spots. CONCLUSION All four PCAs performed with these datasets presented clear grouping of samples according to the varieties. The data presented here showed that PCA was applicable for proteomic analysis of potato and was able to separate the samples by varieties.