This essay has been submitted by a student. This is not an example of the work written by our professional essay writers.
Compulsory labeling of products containing genetically modified organisms (GMOs) above a certain threshold has been introduced in several countries. These regulations imply quantitative molecular analysis of the products and real-time quantitative polymerase chain reaction (qPCR) is currently being used for this task. However, the application of qPCR technology in GMO testing presents limitation for the detection and quantification of very low number of DNA targets, and in some difficult food and feed matrices. A recent methodology termed droplet digital PCR (ddPCR) has been demonstrated to accurately quantify absolute DNA copies. In this study, the applicability of ddPCR was assessed for the routine quantification of GMOs in samples. The amounts of MON810 transgene and hmg maize reference gene copies in DNA samples were measured using ddPCR duplex assays. Key performance parameters of the ddPCR assays were determined. The ddPCR system is shown to offer precise absolute and relative quantification of the GMO target, without the need of calibration curve. The sensitivity (five target DNA copies) of the ddPCR assay compares to those of the individual qPCR assays and of the recently assessed chamber digital PCR (cdPCR) approach, but ddPCR offers a wider dynamic range (over four orders of magnitude) than cdPCR. Moreover, the ddPCR assay shows lower sensitivity to inhibition and better repeatability at low concentration level. Finally, ddPCR throughput and cost are advantageous compared to those of qPCR for routine GMO quantification. These results indicate that ddPCR technology could be applied for routine accurate quantification of GMOs.
With an accumulated planted area between 1996 and 2010 exceeding one billion hectares1, genetically modified plants hereafter referred to as GM organisms (GMOs), and their products (also termed GMO in the following) are a significant part of global agriculture, food and feed systems. To take in account the societal and scientific concerns raised by the use of this technology, most countries around the world have implemented strict regulations for the development and the use of GMOs.2 In numerous countries, these regulations also include labeling of products containing GMOs or material derived from GMOs above specific thresholds, therefore introducing need for GMO content quantification.2 As an example, in the European Union, the threshold for labeling of approved GMOs is 0.9% in food and feed3, and 0.1% for unapproved GMOs in feed fulfilling specific requirements.4
Currently, the most common technology for testing GMOs in food and feed samples is the polymerase chain reaction (PCR). When thresholds for labeling is required, the use of real-time quantitative PCR (qPCR) is preferred because of its accuracy and precision.5 GMO content in food and feed samples is expressed in relative values as the ratio of the transgene (GM target, i.e. the nucleic acid fragment introduced in the host genome) quantity compared to the endogene (reference gene in the host genome) quantity.6 For the quantification of nucleic acids, the so-called standard curve approach is commonly used in GMO detection.7 In this approach, standard curves of the endogene and the transgene quantities are prepared separately using serial dilutions of DNA extracted from reference material. qPCR efficiency and hence quantification of endogene and transgene can be influenced by many factors - including inhibitors - present in food and feed samples leading to significant under- or over-estimation of GMO content using this relative quantification approach.7,8 Many efforts have been put into improvement of the qPCR quantification performance regarding the inhibition and matrix effects7, the low concentration level of targets in routine samples9,10, and deal with the absence of certified reference material.10 However, most of the proposed solutions are not practical and reliable quantification of GMOs in food and feed samples still remains a challenging task.
Digital PCR (dPCR) principle proposes to quantify absolute number of targets present in a sample using limiting dilutions, PCR and Poisson statistics.11 To do so, the PCR reaction is distributed across a large number of partitions containing none, one or more copies of the target nucleic acid. After end-point PCR amplification, each partition is scrutinized and defined as positive ("1", presence of PCR product) or negative ("0", no PCR product) hence the term "digital". The absolute number of target nucleic acid molecules contained in the original sample before partitioning can be directly calculated from the fraction of positive vs. total partitions using binomial Poisson statistics.12 Therefore, dPCR does not request the use of standard curves for quantification of a given target. As only the binary result (positive, negative) is taken in account, copy number determination with dPCR is more tolerant to variations of PCR amplification efficiency than with qPCR. Finally, with ddPCR, the higher the number of partitions is, the more precise is the target copy number calculation and the wider is the dynamic range.13
Currently, two approaches are used in the commercially available dPCR systems.12,14 One approach (cdPCR) relies on the partitioning in up to a few thousand individual reactions in microfluidic chambers. The second approach called droplet digital PCR (ddPCR) combines partitioning of the PCR reaction in several thousands or millions of individual droplets in a water-oil emulsion with the use of a flow cytometry to count positive PCR reactions.
dPCR has been adopted for a number of applications including copy number variation studies involving allelic discrimination or imbalance, point mutations detection, single cell gene expression, study of hyper-methylation, detection of low copy number nucleic acid target (reviewed in 15-17). Recently, a cdPCR commercial system has been demonstrated to allow suitable metrological performance for the copy number ratio certification of reference materials used in GMO testing.8,18 Several advantages can be presented for the use of dPCR instead of qPCR in routine GMO testing: 1) it allows absolute target copy number and avoids amplification efficiency bias observed with qPCR8,18; 2) it overcomes the dependency on the availability of references or standards16; 3) it provides data with high precision and confidence relevant for metrological use8,18; 4) it provides more accurate data at low target copy number than qPCR19 allowing low GMO content quantification; 4) because of its tolerance to inhibitors as an end-point measurement it can reduce the biases linked to matrix type often observed with qPCR.16 However, the application of cdPCR is limited by two important factors: its relative high price and the small dynamic range it offers (2-3 logs).
Given the higher number of replicates allowed by ddPCR vs. cdPCR and the relative lower price per analyzed sample of the former, it has been envisaged that ddPCR could allow better precision14, confidence and easier adoption of digital PCR technology in laboratories for daily analysis.12 The aim of this study was therefore to evaluate the key performance parameters of ddPCR for GMO testing obtained from the QX100 droplet system (Bio-Rad, Pleasanton, CA) and compare them to the current qPCR performance as well as the recently studied performance of cdPCR.8,16 The linearity of the response, the absolute limits of detection and quantification, the repeatability over the dynamic range of the 20 000- droplet ddPCR endogene and transgene assays were assessed. The applicability of ddPCR with different sample matrices and the practicability of use for routine GMO testing were also assessed.
Material and methods
Several MON810 maize seed powder based certified reference materials (CRM) were purchased from the EU Joint Research Centre, IRMM (Institute for Reference Materials and Measurements, Geel, Belgium). These CRMs are all certified for the mass to mass (m/m) transgene/endogene ratio. Some of them are also certified for the copy/copy (cp/cp) ratio. In this study, the following CRM were used: ERM-BF413d (1% Â±0.3% m/m and 0.57% Â±0.17% cp/cp), ERM-BF413f (5% Â±0.2% m/m), ERM-BF413ek (1.98% Â± 0.15% m/m and 0.77% Â± 0.08% cp/cp) and ERM-BF413gk (9.9% Â± 0.5% m/m).
The CRM (ERM-BF413gk) is only certified for the mass/mass ratio. However, this CRM belongs to the same series than ERM-BF413ek, meaning that they were both prepared with the same wild-type and MON810 maize powdered material.20 Therefore, based on the correction factor between the mass/mass and the copy/copy certified values in the ERM-BF413ek CRM (factor 2.57), one can estimate the copy/copy MON810 content in ERM-BF413gk (3.85% Â±0.2% cp/cp) from its mass/mass certified value. A similar evaluation can be applied for the copy/copy ratio in ERM-BF413f (2.85% Â±0.1% cp/cp) issued from the same CRM series than ERM-BF413d21 using the correction factor between the mass/mass and the copy/copy certified values in the ERM-BF413d CRM (factor 1.75).
Other samples containing the MON810 maize event and previously assayed by qPCR were also used in this study. Several maize seed-powder flour samples were tested: G0009/04 from the USDA-GIPSA proficiency program (measured 0.29% Â±0.13% cp/cp by qPCR, assigned value 0.3% m/m); G0180/07 from the USDA-GIPSA proficiency program (measured 0.04% Â±0.02% cp/cp by qPCR, assigned below 0.1% m/m); G211/10 from the ILC-CRL-GMFF proficiency program (measured 0.50% Â±0.15% cp/cp by qPCR, assigned value 0.45% Â± 0.098% cp/cp) and G212/10 from the ILC-CRL-GMFF proficiency program (measured 2.30% Â±0.7% cp/cp by qPCR, assigned value 2.10% Â± 0.35% cp/cp). A wheat seed-powder flour samples with maize contamination from the GEMMA proficiency test program was tested (G0147/08, measured 29.6% Â±8.9% cp/cp with qPCR, no assigned value). Two samples from routine GMO testing were included in the evaluation: corn flakes (G231/11, 2.64% Â±0.8% cp/cp), and feed containing maize (G254/11, 3.82% Â±1.1% cp/cp).
DNA was extracted and purified from all samples using the NucleoSpin Food kit (Macherey-Nagel GmbH & Co. KG, Düren, Germany). In parallel, DNA from sample G0147/08 was also extracted and purified according to a CTAB method22 with the following modifications: 200 mg of starting material, 600 Î¼L of added water, 1000 Î¼L of CTAB extraction buffer, and 40 Î¼L of each RNase and proteinase K.
Dilutions of the stock extracted DNA solutions were made with nuclease-, protease-free water (Sigma-Aldrich Chemie Gmbh, Munich, Germany), using pipettes calibrated with a SAG285 precision weighing module (Mettler-Toledo d.o.o., Ljubljana, Slovenia).
Enzymatic restriction of genomic DNA
For enzyme digestion, approximately 50 ng of MON810 genomic DNA were used in a total reaction volume of 30 Î¼L containing the NEB4 10x restriction buffer, and 40 unit of TaqI (New England Biolabs GmbH, Frankfurt am Main, Germany). The final volume was adjusted with nuclease-, protease-free water (Sigma-Aldrich Chemie Gmbh, Munich, Germany) and incubated for 2 h at 65 Â°C. The TaqI enzyme was inactivated by incubating at 80 Â°C for 10 min. 6 Î¼L of digested genomic DNA were analyzed on a 1% agarose gel to confirm complete digestion.
qPCR reactions and data analysis
The hmg gene was used as endogenous control gene for maize. A unique, single copy DNA integration-border region of the genomic sequence and the inserted sequence element originating from CaMV (35S promoter) was used for specifically detect and quantify the MON810 event. Probe and primers nucleotide sequences were the same as in the inter-laboratory validated protocol23 but the TAMRA quencher in the probes was replaced by the Black Hole Quencher 1 (BHQ-1) (see Table S1 in supplementary material). The same primers and probes were used for both qPCR and ddPCR experiments.
Singleplex qPCR reaction mixes comprised of 1Ã- TaqMan Universal mastermix (Applied Biosystems, Foster City, CA), the relevant primers at final concentration of 300 nM, the relevant probe at final concentration of 180 nM, and 4 Î¼L DNA template. Duplex qPCR reaction mixes comprised of 1Ã- Taqman Universal mastermix (Applied Biosystems, CA, USA), the hmg primers at final concentration ranging from 150 nM to 300 nM, the MON810 primers at final concentration ranging from 300 nM to 600 nM (ratio hmg/MON810 primer from 1 to 4), the hmg probe at final concentration ranging from 90 nM to 180 nM, the MON810 probe at final concentration ranging from 180 nM to 360 nM (ratio hmg/MON810 primer from 1 to 4), and 4 Î¼L DNA template.
All qPCR reactions were performed on a 7900HT Fast Real-Time PCR System (Applied BioSystems, Foster City, CA) with the following thermal cycling conditions: 2 min uracil-N-glycosylase (AmpEraseÂ®) step at 50Â°c, 10 min activation step at 95 Â°C, followed by 45 cycles of a two-step thermal profile comprising 15 s denaturation at 95 Â°C, and 60 s annealing/extension at 60 Â°C. Data acquisition and analysis was performed using the SDS 2.3 software (Applied Biosystems, Foster City, CA) after manual adjustment of the baseline and fluorescence threshold. After being exported, further data analysis was performed in a Microsoft Excel spreadsheet (Microsoft, Redmond, WA).
Determination with qPCR of MON810 content was done using relative quantification according to the standard curve approach. Standard curves were prepared from five serial dilutions of copy/copy ratio certified reference materials (starting from approximately 100 ng to 1 ng DNA per reaction) and used in two replicates. For each sample, the quantification was done based on two replicates of three dilutions. Results of quantification performed with CRM certified for transgene/endogene copy ratio were expressed in percentage of the copy/copy ratio.
Droplet Digital PCR reactions and data analysis
Duplex ddPCR reaction mixes were prepared as follows. 10 Î¼L of 2Ã- ddPCR Master Mix (Bio-Rad, Pleasanton, CA) and 1 Î¼L of each primer (final concentration of 300 nM) and probe (final concentration of 180 nM) (see in supplementary material) were mixed, and 4 Î¼L DNA template were added to complete the 20 Î¼L reaction volume. For singleplex reactions, 3 Î¼L of nuclease-, protease-free water (Sigma-Aldrich Chemie Gmbh, Munich, Germany) were added to complete a 20 Î¼L reaction volume. Final primers and probes concentrations in ddPCR reactions are identical to the qPCR conditions used in this study, and to those in the previously described chamber digital PCR (cdPCR) conditions 8. All reactions were prepared using pipettes calibrated at NIB with a SAG285 precision weighing module (Mettler-Toledo d.o.o., Ljubljana, Slovenia) or at a service provider laboratory (LotriÄ Metrology ltd, Slovenia).
Droplet generation was performed in 8-well cartridges using the QX100 droplet generator (Bio-Rad, Pleasanton, CA) as previously described.12 Water-in-oil emulsions were amplified in a conventional calibrated Geneamp 9700 PCR cycler (Applied BioSystems, Foster City, CA). Thermal cycling conditions were the following: 10 min denaturation at 95 Â°C, followed by 40 cycles of a two step thermal profile comprising 15 seconds denaturation at 95 Â°C, and 60 s annealing/extension at 100% ramp rate at 60 Â°C. After amplification, products were denaturated at 98Â°C for 10 minutes and cooled to 12Â°C. Then plates were transferred in the QX100 droplet reader (Bio-Rad, Pleasanton, CA). Data acquisition and analysis was performed using QuantaSoft (Bio-Rad, Pleasanton, CA).
Discrimination between positive droplets containing amplification products and negative droplets without amplification products was done by applying a fluorescence amplitude threshold in QuantaSoft software (Bio-Rad, Pleasanton, CA). The threshold was manually set at the lowest point of the negative droplet cluster as visualized using both the fluorescence amplitude vs. event number, and the histogram of events vs. amplitude data streams, on each of the FAM and VIC channels.
Data generated by QX100 droplet reader were rejected from subsequent analysis (i) if a clog was detected by the Quantasoft software or (ii) if a low number (<10,000) of droplets was measured per 20 Î¼L PCR. After being exported, further data analysis was performed in Microsoft Excel spreadsheets (Microsoft, Redmond, WA).
The percentage of positive droplets for a given amplicon was calculated as the percentage of droplets showing signal for the amplicon in the total number of analyzed droplets.
ddPCR key performance parameters determination
Comparison singleplex vs. duplex reactions
For the ddPCR duplex assay evaluation, three different 8-well cartridges were evaluated, containing either of the singleplex hmg, singleplex MON810 or the duplex ddPCR assays. In each cartridge, one well was filled with a none template (NTC) ddPCR reaction mix, while the seven other wells contained ddPCR reactions with DNA extracted from the ERM-BF413ek CRM (average of 46,571 hmg copies and 324 MON810 copies). Droplet generation was made for each individual cartridge, and the droplet containing PCR reaction of the three cartridges were transferred on a single PCR plate for amplification, followed by droplet count.
Dynamic range, repeatability limits of detection and quantification
A dilution series was prepared with MON810 maize DNA extracted from the ERM-BF413gk CRM. DNA quantification in the initial MON810 maize DNA solution was estimated by qPCR as previously described.24 The dilution series consisted of 14 solutions containing in average 87400, 65500, 16490, 3240, 1080, 360, 120, 60, 40, 13, 4, 1.5, 0.2 and 0.02 copies of hmg, and 3200, 2400, 600, 120, 40, 13, 4, 2, 1.5, 0.5, 0.2, 0.05, 0.006 and 0.0006 copies of MON810, respectively). Five replicates of the dilution series and of a non template control (NTC) were measured by ddPCR. For qPCR, measurements were done in duplicates. In the following, only the copy numbers measured by ddPCR will be used, and the copy numbers estimated by qPCR will not be mentioned anymore. The linearity over the dynamic range was determined by the coefficient of correlation R2 calculated on the average of the target copy numbers measured in the replicated dilution series for both qPCR and ddPCR. The repeatability over the dynamic range was determined by the coefficient of variation (cv) of the measured target copy number or the MON810 content between the replicates of the dilution series. The absolute limit of quantification (aLOQ) and absolute limit of detection (aLOD) for qPCR and ddPCR were determined on these experimental results.
An additional set of experiments was performed to establish the repeatability between different emulsification runs. Intra- and inter cartridge (ddPCR 8 well chips) repeatability was determined on five independent series consisting of seven replicates of the ERM-BF413ek (approximately 100 ng and average of 46571 hmg copies and 324 copies of MON810 per 20 Î¼l reaction) and one NTC. All amplification reactions were simultaneously performed on the same 96-well plate, providing a total of 35 replicate positive ddPCR reactions.
Samples representative of four different maize-containing matrices from routine GMO testing were used to test the applicability: seed-powder flour, corn flakes, wheat seed-powder flour with maize contamination and feed containing maize (see the section "Test material" for details).
The ddPCR amplicons used for this study were directly imported from qPCR singleplex assays that were inter-laboratory validated and for which specificity was carefully checked at this stage. Moreover, the method parameters (primer and probe concentration, thermal profiles) were not modified. Therefore, the specificity of the ddPCR amplicon was not verified as it is believed that it should be the same as for the qPCR singleplex assays.
Results and discussion
Given the limitations of qPCR for the quantification of GMO in food and feed samples, especially at low target level and in some difficult matrices, a set of experiments was done to evaluate the capacity of ddPCR to perform routine GMO quantification satisfying the generally accepted method minimum performance criteria.25,26
In order to avoid as much as possible biases when comparing qPCR and ddPCR quantification, we have transferred the inter-laboratory validated qPCR hmg- and MON810-specific assays to ddPCR technology with a minimum of adaptation and optimization. Therefore, beside the mastermix and settings that are specific to the QX100 droplet system, primers and probe nucleotide sequences and concentrations, DNA concentration, and PCR thermo-profile were kept identical to the qPCR assays. Only the TAMRA quencher in both probes of the original qPCR assays was substituted with the non-fluorescent BHQ-1 quencher.
ddPCR can be easily set as duplex applications
Because the GMO content is calculated based on the ratio of transgene/endogene quantities, it would be more practical to perform endogene - transgene duplex qPCR and ddPCR reactions to avoid inter-well bias. For this reason, evaluation of duplex qPCR and ddPCR assays was performed and compared to singleplex assays performance. The primers and probes of both the hmg and MON810 systems were mixed in the qPCR or ddPCR reactions to a final concentration equal to the concentration in the original singleplex assays. Other parameters (thermo-profile, DNA template quantity) remained unchanged. Preliminary results of qPCR duplex systems evaluation suggested that the hmg system performed the same in duplex and singleplex qPCR reactions, while the MON810 amplification was significantly affected in the duplex reactions, showing signal approximately 5.5 Cq values later than in singleplex reactions (data not shown). An attempt to optimize the duplex qPCR reaction was made by varying primers and probe concentration and ratios of both systems. However, in all the tested conditions the hmg and MON810 appeared either differently affected introducing under-estimations of the MON810 content, and/or loss of sensitivity (data not shown). These results are not a surprise. The difficulty to multiplex qPCR assays is well documented, including for GMO quantification application.27-29 The limitations include the design of amplicons showing similar short length, the presence of numerous primers and probe that can potentially create dimers, the complex determination of optimal primer and probe concentrations. Another difficulty linked to GMO detection is that the event-specific amplicons needed for reliable and specific GMO quantification must usually target the junction region between the transgene and the host plant genome, leaving a very narrow window for design and increasing further the flexibility for a multiplex design. Also, the laboratories usually need to quantify low concentrations of transgene (down to 0.1%) in a background of high endogene quantities. This asymmetry in concentration renders even more difficult the establishment of a qPCR duplex assay targeting both the MON810 transgene and the hmg endogene. In the following experiments, only results of the singleplex qPCR assays were used for comparison with ddPCR assay results.
For ddPCR, no significant variation of the measured target copy number was observed between the singleplex and the duplex ddPCR reactions for both hmg (bias = -1.8%) and MON810 systems (bias = 3.7%). Similarly, no significant variation of the measured MON810 content was observed between the singleplex and the duplex ddPCR reactions (bias = 5.8%) (see Table S2 in supplementary material). Additionally, the repeatability of the duplex assay in the measurement of the MON810 content appeared comparable to that of the singleplex assays with slightly lower variability. As a conclusion to these results, it was assumed that the duplex ddPCR assay performs as well as the singleplex ddPCR assays without any optimization of the original reactions conditions. This observation was further confirmed by the successful establishment of several additional duplex ddPCR assays from singleplex qPCR assays without optimization (data not shown). This duplex assay was therefore used in further analyses.
Enzymatic restriction of genomic DNA
It was recently suggested that it is preferable to expose gDNA to endonuclease restriction in order to improve the amplification efficiency and to increase the accuracy of GMO target copy number measurement with cdPCR.18 The effect of gDNA endonuclease restriction on ddPCR accuracy was also evaluated. Two series (non digested, and digested with TaqI) of four dilutions of DNA extracted from the ERM-BF413ek CRM were evaluated with the duplex ddPCR assay.
Both series showed similar results in terms of linearity for the targets: 0.9995 and 0.9982 for the hmg and MON810 targets in the non-digested (native) gDNA series, 0.9994 and 0.9966 for the hmg and MON810 targets in the TaqI digested gDNA series (data not shown). Copy number estimations were slightly different: estimations in digested genomic DNA were about 30% lower in comparison with the native DNA. Moreover, the copy number determination between dilution levels is more variable with the digested than with the native DNA (Table S3 of the supplementary material). However, the measured MON810 contents were very similar between both series through all the dilution series (bias = -0.28%).
Digestion of DNA for digital PCR analysis may be necessary in the case of a possible linkage between targets such as multiple copies of target physically linked on a same chromosome, or if targets present on a same plasmid need to be quantified. In the case of GMO quantification, an event-specific amplicon is targeted, which usually consist in the unique junction region between the host plant genome and the transgene. Similarly, the target chosen for endogene quantification is a gene present in a unique copy in the host plant genome. In the case of the MON810 maize, the two dimensional analysis of the droplet signals is very similar between samples treated by endonuclease and non-digested DNA samples. This observation suggests the absence of linkage between MON810 positive droplets and hmg positive droplets in digested and undigested DNA samples, thus confirming the independency between both targets (Figure S1 in supplementary data). For practicability reason, it was chosen to proceed further with the ddPCR performance characterization using non-digested gDNA.
Dynamic Range, precision and limit of quantification
A recent study has estimated that the theoretical ddPCR dynamic range is 105 target copies, and experimentally established a dynamic range covers more than 4 orders of magnitude.12
The ddPCR duplex assay response was investigated over target concentrations ranging from approximately 0.02 to 87,400 hmg copies and from approximately 0.001 to 3,200 MON810 copies per 20 Î¼L of ddPCR reaction. The dynamic range was estimated from five replicates of a 14 data point dilution series providing a total of 70 data for each target of the ddPCR duplex assay. From this dataset, data from one reaction were excluded from data analysis. This reaction was excluded because of pipetting errors noticed after loading the 8-well cartridges with ddPCR reaction mixes. The average number of droplets read for each ddPCR reaction included in the data analysis was 13,606 with a standard deviation of 931 droplets (coefficient of variation cv = 6.8%).
The ddPCR response was linear over concentrations ranging from an average of 5 to 118,000 hmg copies (0.02% to 99.5% positive droplets) with a coefficient of correlation (R2) of 0.9990. Similarly, the ddPCR response for MON810 was linear from 6 to 4,340 MON810 copies in average (R2 = 0.9993; 0.03% to 17.9% positive droplets in average) (). This performance was similar to the one of both singleplex qPCR assays, linear over the same dynamic ranges (R2 hmg = 0.9939 and R2 MON810= 0.9958) (data not shown). The ddPCR linear response for the MON810/hmg duplex assays covered a broader range than the same assays tested in cdPCR which was limited to 2-3 orders of magnitude.16,18 This wider range of concentrations could be attributed to high number of partitions available for reactions in ddPCR (13,606 droplets in average in this work) compared to the number of partitions (765) available for cdPCR reaction. It has been already said that qPCR offers much broader dynamic range than digital PCR.14 However, the dynamic range observed for ddPCR is covering the whole range of target concentrations a laboratory usually meets for GMO routine testing (0.1% to 100% GMO/endogene ratio cp/cp).
For individual targets and the GMO content, the coefficient of correlation R2 obtained with ddPCR met the requirements (R2 > 0.98) set by the European Union Reference Laboratory for GM Food and Feed26 for acceptance of a quantitative PCR-based detection method for GMO.
All samples used for the dynamic range determination came from serial dilution of a single stock MON 810 maize DNA sample. At higher concentration (118,000 hmg copies per 20 Î¼l ddPCR reaction), each droplet contains in average 5.9 hmg molecules, which is the upper recommended concentration for use of the droplet system (Bio-Rad, personal communication). This finding supports the fact that the duplex MON810/hmg ddPCR assay can be used on a wide range of target concentration to determine the MON810 content in a given sample and that values around 115,000 copies are the upper range of quantification with ddPCR.
The absolute limit of quantification (aLOQ) is the lowest target copy number in a sample that can be reliably quantified with an acceptable level of precision and accuracy (acceptance criterion as defined in 26). The aLOQ of the hmg or MON810 ddPCR systems was estimated as the lowest copy number within the dynamic range with a coefficient of variation (cv) of the measured copy number â‰¤ 25%. Based on this criterion, aLOQ was estimated around 5 copies for the hmg system, and 18 copies for the MON810 system and for the duplex ddPCR assay (Supplementary Table S4). As a comparison, it is usually agreed that aLOQ of qPCR assays ranges from 30 to 100 target copies per reaction.9,30 The aLOQ of the qPCR MON810 specific method used in this study was previously estimated to be 10 copies of the target MON810 sequence23, and in a higher range of 31 - 63 copies.16 The aLOQ of the duplex ddPCR assay was therefore in range with the best estimations for the qPCR performance. Similarly, the aLOQ of the duplex ddPCR assay was also in the range with the aLOQ measured in cdPCR (15 - 56 transgene copies), assessed only on the MON810 assay.16
The absolute limit of detection (aLOD) is the lowest target copy number in a sample, which can be reliably detected, but not necessarily quantified (acceptance criterion as defined in 26). For this study, aLOD was calculated based on experimental data obtained to determine the dynamic range. aLOD was determined as the last concentration level for which all five ddPCR replicates resulted in at least two positive droplets. aLOD was estimated at five copies for the hmg system, and six copies for the MON810 system and is suitable for routine GMO testing. The absolute sensitivity is comparable with the one observed for the MON810 singleplex qPCR assay (five copies)23, verified at around three copies according to our own assessment (data not shown), and the MON810 assay tested in cdPCR (around one copy).16
Intra- and inter-cartridge repeatability of the ddPCR was assessed for both hmg and MON810 target copy number determination and for MON810 content determination. Low variability was observed within each of the five cartridges for the determination of hmg copies, of MON 810 copies, and of MON810 content with variability of measured values below 10%. Similarly, comparison of the values between the five cartridges showed low variability (cv < 10%) for the three measured parameters: hmg copy number, MON 810 copy number and MON810 content ( and Supplementary Table S5).
The overall repeatability performance could also be estimated by analyzing the results of the experiment performed for the aLOQ and dynamic range determination. All along the dynamic range, the cv of the determined hmg copies, MON 810 copies, and MON810 content stayed beyond the threshold for acceptance of quantitative methods (cv below 25%) (Supplementary Table S4).
In all experiments and for all three parameters (hmg and MON 810 copy number, MON810 content), the coefficient of variability measured at each point of the dynamic range stays far below the 25% threshold set in international guidance documents for GMO testing method validation.25,26 These experiments demonstrate that using ddPCR, one can obtain repeatable and comparable quantitative estimation of GMO target number or content.
It was already observed with both ddPCR12 and cdPCR18 that the relative uncertainty in target copy number varies across the dynamic range, with higher uncertainty and consequently higher measurement variability as the target copy number decreases. In this study, it was observed similar higher variability of the measured target copy numbers (Supplementary Table S4 and ) and of the MON810 content at lower target concentration (Supplementary Table S4 and ).
Trueness is defined as the closeness of agreement between the average value obtained from a series of test results and an accepted reference value.26 As a general acceptance criterion, the trueness shall be within Â±25 % of the accepted reference value over the whole dynamic range.25,26
To assess the trueness, data generated by the experiments for the dynamic range determination and for the intra- and inter-cartridge repeatability performance were used. In absence of a DNA reference material certified for absolute copy number concentration, trueness could only be assessed for the MON810 content.
In the experiment performed to determine the intra- and inter-cartridge repeatability performance (on CRM ERM-BF413ek), the average value of the pooled ddPCR data showed good agreement with the certified value () and in every case, the MON810 content measured by ddPCR (within the dynamic range) was within Â±25 % of the certified value (). By comparison, the MON810 content measured by qPCR was close to the limit of acceptance ().
The average value of the pooled ddPCR duplex assay data at each dilution level of the dynamic range showed good agreement with the reference value (ERM-BF413gk, 3.85% cp/cp) (). The MON810 content measured by qPCR was similar to that of the ddPCR value, the later being slightly closer to the target value (). Throughout the dynamic range, each individual ddPCR measurement of the MON810 content fell within Â±25 % of the certified value (). It is noteworthy that the deviation between the MON810 content measured by ddPCR and the reference value tended to increase with lower target copy number. Still, the MON810/hmg ddPCR duplex assay met trueness acceptance criteria throughout the whole dynamic range. Trueness was also evaluated on two additional CRMs: ddPCR results showed better agreement with the target values than qPCR ().
In addition to the CRMs, trueness of the ddPCR duplex assay can be evaluated on the ILC-CRL-GMFF proficiency program results which are provided in copy/copy ratio. As shown in , the measurements obtained on two samples from ILC-CRL-GMFF proficiency program are in very good agreement with the assigned values, and in accordance with the trueness acceptance criterion.
According to our results, the trueness of the duplex ddPCR assay assessed on CRM and proficiency program samples fully satisfies the acceptance criterion set for a DNA-based quantification method and is often better than trueness from qPCR singleplex assays.
Another important factor when introducing new methods or technologies for testing GMOs in food and feed is their applicability. More specifically, their ability to perform with different sample matrices and within a range of concentrations relevant for GMO testing should be demonstrated.25
As shown in , MON810 contents measured by the ddPCR duplex MON810/hmg assay in maize seed-powder flour samples and corn flakes samples are in good accordance with the values measured with the qPCR singleplex MON810 and hmg assays ().
During qPCR tests, we detected the presence of inhibition in the stock DNA solution of two samples (wheat seed-powder flour with maize contamination and maize feed), exemplified by the high deviation between MON810 content (cv > 25%) calculated from different sample dilutions. Consequently, the diluted DNA samples were used to determine the MON810 content with qPCR. In the case of the wheat sample, a second DNA extraction following CTAB protocol was additionally performed given the very high inhibition observed in the DNA extracted with the Nucleospin food kit (NSF). Both stock and diluted DNA solutions from this CTAB extract could be used for the MON810 content determination with qPCR. The ddPCR measurements of MON810 content were in agreement with the accepted values obtained with qPCR but with bias slightly above the acceptance limit for the wheat seed-powder flour sample ( and Supplementary Table S6). Interestingly, very low deviation was observed between the MON810 content determined by ddPCR in the stock (presenting inhibition with qPCR) and the diluted DNA solutions for both matrices (Supplementary Table S6). This result suggests that the ddPCR duplex assay is less sensitive to inhibitors found in the food and feed matrix than the qPCR assays, as theorized previously.16 There is a long empirical knowledge of DNA extraction methods efficiency according to the sample matrix of interest: GMO laboratories use adapted DNA extraction methods that in some case may lead to limited inhibition during the qPCR analysis. Following this practice, there is no risk that substances in DNA extract would totally inhibit the qPCR or ddPCR amplification reaction resulting in false negatives. As such, ddPCR could be even more reliable than qPCR for quantitative analysis in some difficult matrices.
In summary, the ddPCR MON810/hmg duplex assay can be applied for routine quantification of the MON810 maize, as demonstrated on a large range of transgene content covering three logs of magnitude (experimentally from 0.04% to 29.6%). Moreover, its usability in several types of food, feed and seed matrices commonly found in routine samples has been verified.
Before introducing a new technology in a laboratory, one has to verify its practicability for daily use. Regarding routine food analysis, Codex Alimentarius suggests to assess the practicability "by considering parameters such as: the quantity of samples that can be processed within a given time, estimated fixed costs to implement the method and the approximate cost per sample, practical difficulties on daily use or under particular conditions, as well as other factors that could be of importance for the operators".25
One needs to consider the throughput and cost of the new technology to assess it practicability for routine use. To do so, calculations were made based on the quantification of four samples, an average number for middle-size GMO laboratories. Following the quality assurance established for routine GMO testing at the National Institute of Biology, the quantitative analysis of four samples using hmg and MON810 singleplex qPCR assays requires a total of 96 reactions (see set up A, Table S7 in supplementary material). This high number of reactions is mainly due to the use of inter-laboratory validated singleplex methods, to the need for controlling inhibition that requires several dilution levels, and to the reactions needed for establishing the standard curve. With ddPCR, standard curve is not needed and a duplex MON810/hmg assay with a wide dynamic range is used. As inhibition is substantially tested during the screening and identification phases of GMO testing and given the observed tolerance of the assay for amplification inhibition, it is not necessary to control the inhibition at the ddPCR quantification stage. Given these parameters, a simple ddPCR testing set-up is proposed (set up B, Table S7 in supplementary material) that includes two replicate reactions for each test portion of the sample, in accordance with the ISO 21570:2005 standard.31 With this set-up, a total of 8 ddPCR reactions are necessary for the quantification of MON810 in two independent test portions. Including NTC and quantification control reactions in the set-up, a total of 20 reactions would be necessary to reliably quantify MON810 in four samples.
Based on the experience acquired for this study and assuming the samples and mixes are prepared, the simultaneous analysis of these four samples with ddPCR would require approximately 190 minutes. As a comparison, qPCR would take 160 minutes to generate results (see Table S7 in supplementary material). The main difference between both approaches relies on the time needed by the droplet reader to analyze individual droplets.
Considering the cost of reagents, consumables and labor at NIB and the above proposed set-ups for GMO testing, the quantification in four samples of a given transgene with ddPCR would cost approximately US$20.9 per sample and US$22.3 using qPCR. Another calculation shows even better throughput and smaller cost for the ddPCR if more samples must be handled simultaneously (see Table S7 in supplementary material for detailed calculations). For the cdPCR and given the list prices per chip or plate (from US$150 to US$400 each)14, adopting the same set-up than for ddPCR (four runs i.e. chips or plate per sample) would lead to cost per sample not compatible with routine detection of GMOs in most of the laboratories.
Quantification of routine samples using ddPCR is therefore practical and has the potential to provide better throughput and cost-efficiency than qPCR to GMO laboratories.
The intention of this study was to demonstrate the usability of this technology in real-life routine diagnostics, rather than re-investigating the recently reported metrological characteristics of ddPCR.12 In this study, the applicability of ddPCR was investigated for the quantification of GMO in food, feed and seed samples. The herein presented ddPCR MON810/hmg duplex assay implemented without optimization from the inter-laboratory validated singleplex qPCR assays achieves a wide dynamic range close to five orders of magnitude with an upper limit of quantification of about 118,000 target copies. It also shows very good sensitivity, suitable with GMO testing. Thanks to these performance parameters, quantification of samples from usual matrices and using DNA extracted with common methods can be done without up-front DNA quantity estimation. Also, the limits of quantification, the trueness and the repeatability of the assay for both systems comply with international recommendations25,26 and are comparable or superior to those of the inter-laboratory validated qPCR singleplex assays.
Applicability of the technology was verified on representative matrices found in routine samples, and on a range of GMO content usually found in routine samples and relevant to different international labeling requests. Unlike qPCR, ddPCR has been found relatively insensitive to amplification inhibition present in some of the tested samples, and very precise at very low levels of target content. The use of the ddPCR duplex assay in routine GMO analysis was shown to be practical, following a new test set-up proposed in this study.
It was recently discussed that price is a limitation to the adoption of ddPCR in laboratory.14 The data provided herein shows that in the context of GMO quantification, ddPCR running cost over performs the standard qPCR technology in a superior throughput, especially when numerous samples must be simultaneously handled. Increasing the multiplexing will certainly also give additional advantage to the ddPCR in terms of cost and through-put and could allow its use already at the screening and/or identification steps. Interestingly, the establishment of duplex reactions is straightforward and does not need optimization. This characteristic presents the advantages of reducing the cost of analysis, and of decreasing the uncertainty linked to the droplet volume variation and dilution pipetting errors.18
As recently commented14, one should properly check that a method based on digital PCR performs properly in terms of sensitivity and specificity before use. To be employed in GMO routine testing, methods based on ddPCR shall be properly validated through ring-trials and verified during the introduction in GMO laboratories to demonstrate their fitness for purpose. However, the ddPCR performance demonstrated in this study for the GMO quantification on real routine samples should allow better confidence and easier adoption of digital PCR technology in laboratories to generate more precise data on their every day tests, at better cost per sample.
Additional information as noted in text. This material is available free of charge via the Internet at XXX.