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Meat Science
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A SYBR Green real-time PCR assay to detect and quantify pork meat in processedpoultry meat products
Sónia Soares a, Joana S. Amaral a,b, M. Beatriz P.P. Oliveira a, Isabel Mafra a,⁎a REQUIMTE, Departamento de Ciências Químicas, Faculdade de Farmácia, Universidade do Porto, Rua de Jorge Viterbo Ferreira, 228, 4050-313, Portugalb ESTiG, Instituto Politécnico de Bragança, Campus de Sta. Apolónia, 5301-857 Bragança, Portugal
⁎ Correspondence to: I. Mafra, REQUIMTE, DepartamFaculdade de Farmácia, Universidade do Porto, Rua d4050-313, Portugal. Tel.: +351 220428640.
Species identification in meat products has grown in interest in recent years since these foodstuffs are sus-ceptible targets for fraudulent labelling. In this work, a real-time PCR approach based on SYBR Green dyewas proposed for the quantitative detection of pork meat in processed meat products. For the developmentof the method, binary meat mixtures containing known amounts of pork meat in poultry meat were used toobtain a normalised calibration model from 0.1 to 25% with high linear correlation and PCR efficiency. Themethod revealed high specificity by melting curve analysis, being successfully validated through its applica-tion to blind meat mixtures, which confirmed its adequacy for pork meat determination. The fully applicabil-ity of the method was further demonstrated in commercial meat products, allowing verification of labellingcompliance and identification of meat species in processed foods.
Species identification is amajor concern due to the increased aware-ness of consumers regarding the composition of foods and the need toverify labelling statements. Processedmeat products are susceptible tar-gets for fraudulent labelling due to the economic profit that results fromselling cheaper meats as partial or total replacement for high-valuedmeats. Lower amounts of meat than declared on the label and the sub-stitution of muscle protein by cheaper vegetable protein are also com-mon concerns in meat products (Ballin, 2011; Kesmen, Gulluce, Sahin,& Yetim, 2009). In the case of pork, food manufacturers may choose touse porcine derivatives because they are cheap and readily available(Aida, Man, Wong, Raha, & Son, 2005). Porcine derivatives used includepork fat (lard), mechanically recoveredmeats and porcine blood plasma(Nakyinsige, Man, & Sazili, 2012). These practices are of concern for rea-sons such as: (i) economic, since it leads to unfair competition amongproducers; (ii) religious, since the consumption of certain species isnot allowed in some religions; (iii) ethical, reflecting lifestyles such asvegetarianism; and (iv) health concerns.
The increasing demand for transparency in the meat industry andthe enforcement of proper labelling have provided a driving force forthe development of suitable analytical methodologies for meat species
ento de Ciências Químicas,e Jorge Viterbo Ferreira, 228,
identification. Methods based either on protein or DNA analyses havebeen suggested. Protein based techniques, including electrophoretic,chromatographic (Toorop, Murch, & Ball, 1997) and immunological(Asensio, González, García, & Martín, 2008; Hajmeer, Cliver, & Provost,2003; Macedo-Silva et al., 2000) techniques, have some advantageswhen applied to raw meats, such as high sensitivity and samplethroughput (Martín et al., 2009), but they are limited when applied tospecies identification in cured and highly processed meats, since pro-teins can be denatured during thermal, high pressures and other pro-cessing technologies. The ability of DNA molecules to withstand heatand pressure processing, when compared to proteins, and their ubiquityin every type of cell have led to DNA analysis for species identification inprocessed foods (Mafra, Ferreira, & Oliveira, 2008). Analysis of DNAcoupled with polymerase chain reaction (PCR) is considered to be fast,sensitive and highly specific for species identification in processed meatproducts. Studies have reported the application of PCR techniques forthe qualitative detection of pork by species-specific primers or the anal-ysis of restriction fragment length polymorphisms (PCR–RFLP) (Aida etal., 2005; Alaraidh, 2008; Che Man, Aida, Raha, & Son, 2007; Haunshi etal., 2009; Kesmen, Sahin, & Yetim, 2007; Matsunaga et al., 1999;Montiel-Sosa et al., 2000; Murugaiah et al., 2009; Soares, Amaral,Mafra, & Oliveira, 2010). Although species-specific PCR based on duplexamplification can be used as a semi-quantitative approach to estimateanimal species in meat products (Soares et al., 2010) or dairy products(Mafra, Ferreira, Faria, & Oliveira, 2004; Mafra, Roxo, Ferreira, &Oliveira, 2007), the use of a real-time PCR approach is recommendedfor more accurate quantitative information and to increase specificity.The simplest, least expensive andmost directfluorescent systemadapted
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to real-time PCR detection involves the incorporation of SYBR Green Idye. To verify the specificity of amplified products, DNA melting curvescan distinguish false positive signals due to non-specific amplificationor primer-dimers (Fajardo, González, Rojas, García, & Martín, 2010).The use of fluorescent DNA intercalating dyes such as the SYBR Green Ihas the advantage of being a more flexible method without the needfor individual probe design (Fajardo et al., 2008; Farrokhi & Joozani,2011; Sawyer, Wood, Shanahan, Gout, & McDowell, 2003; Terzi et al.,2004). Application of real-time PCR techniques for the specific detectionof porkmeat has been reported, but some only used the technique for thespecific detection of pork species without achieving quantification (Ali etal., 2012; Cammà, Domenico, & Monaco, 2012; Dooley, Paine, Garret, &Brown, 2004; Farrokhi & Joozani, 2011; Kesmen et al., 2009; Laube,Zagon, & Broll, 2007; Rodríguez, García, González, Hernández, & Martín,2005). Moreover, most reports lack validation and applicability assaysto commercial food samples. A recent method proposed by Ballin,Vogensen, and Karlsson (2012)was based on the use of PCR LUX primersto amplify repetitive and single copy sequences to establish the speciesdependent number of amplified repetitive sequences per genome.Though the approach gave promising results regarding relative porkmeat quantification, further improvement is required to increasespecificity.
In this work, a SYBR Green I real-time PCR approach is proposed as asimple, fast, sensitive and reliable method for pork meat detection andquantification. Themethodwas validated using blindmixtures and sub-sequently applied to quantify the presence of pork meat in poultryprocessed meat products available commercially.
2. Materials and methods
2.1. Samples
Reference sampleswere prepared in the laboratorywith poultry andpork muscles from a local retail market. Immediately after purchase,both meats were cut and the outside portions rejected. The sampleswere then minced separately and reference binary mixtures containing0.1%, 0.5%, 1%, 5%, 10% and 25% (w/w) of pork in poultrymeatwere pre-pared to a final weight of 100 g. After the addition of 15 mL of sterilephosphate-buffered saline (136 mM NaCl, 1.4 mM KH2PO4, 8.09 mMNa2HPO4·12H2O, and 2.6 mM KCl, pH 7.2), each mixture washomogenised using a laboratory knife mill Grindomix GM200 (Retsch,Haan, Germany) using containers and material, previously treatedwith a DNA decontamination solution. To validate the estimation ap-proach, blind validation samples containing 1%, 2.5%, 7.5% and 20% ofpork in poultry meat (w/w) were prepared similar to the referencemixtures.
Samples of commercial processed meat products having poultry asthe main ingredient were purchased in local supermarkets, includingdifferent brands of Frankfurter type (boiled) sausages (9 brands), barbe-cue sausages (2 brands), hamburgers (3 brands) andnuggets (3 brands).For each brand of processed meat products, two samples were acquiredin different supermarkets to guarantee that they were from differentproduction batches. The two samples were combined, minced andhomogenised in a laboratory knife mill Grindomix GM200 (Retsch,Haan, Germany) using containers and material, previously treated witha DNA decontamination solution.
The binary reference and validation meat mixtures and commer-cial samples were immediately stored at −20 °C after preparationuntil DNA extraction.
2.2. DNA extraction
DNA was extracted using the Wizard method described by Mafra,Silva, Moreira, Silva, and Oliveira (2008) with minor modifications.Briefly, 100 mg of ground and homogenised sample was transferred toa 2 mL sterile reaction tube followed by the addition of 860 μL of TNE
extraction buffer (10 mM Tris, 150 mM NaCl, 2 mM EDTA, 1% SDS),100 μL of 5 M guanidine hydrochloride solution and 40 μL proteinaseK solution (20 mg/mL). After incubation at 60 °C for 3 h,with occasionalstirring, the suspension was centrifuged (15 min, 18,514 g) and 500 μLof the supernatant was mixed with 1 mL of Wizard DNA purificationresin (Promega, Madison, WI, USA). The mixture was eluted through acolumn and the resin was washed with 2 mL of isopropanol solution(80%, v/v). After drying the column, the DNA was eluted by centrifuga-tion (1 min 10,000 g) with 100 μL of Tris–EDTA buffer (10 mM Tris,1 mM EDTA) at 70 °C to a new reaction tube. The extractions wereperformed in duplicate assays for each binary mixture.
The quality of extracted DNA was analysed by electrophoresis in a1.0% agarose gel in TAE buffer (40 mM Tris–acetate, 1 mM EDTA) for40 min at 120 V, stained with ethidium bromide (0.4 μg mL−1 for5 min) and destained in distilled water for 20 min. The agarose gelwas visualised under UV light and a digital image was obtained usinga Kodak Digital Science™ DC120 (Rochester, NY, USA).
2.3. DNA quantification and purity
The DNA was quantified by spectrophotometry using a ShimadzuUV-1800 spectrophotometer (Shimadzu Corporation, Kyoto, Japan).The DNA concentration was determined by absorbance at 260 nm(1 absorbance unit corresponds to 50 ng/μL of dsDNA). The purity ofthe extracts was evaluated based on the ratio of the absorbance at260 and 280 nm, and values between 1.7 and 2.0 were obtained.The DNA yields ranged from 716 to 1034 ng/μL.
2.4. Oligonucleotide primers
The oligonucleotide primers used in this work are presented inTable 1. The primers were synthesised by Eurofins MWG Operon(Ebersberg, Germany).
2.5. Qualitative PCR
The amplifications by polymerase chain reaction (PCR)were carriedout in 25 μL total reaction volume containing 2 μL (20 ng) of DNA ex-tract, 15 mM Tris–HCl (pH 8.3), 50 mM KCl, 0.4 μM of each primerPork-F/Pork-R, 0.2 mM of each dNTP (Invitrogene, Carlsbad, CA, USA),1 mM of MgCl2 and 1 U of DNA polymerase AmpliTaq Gold® (AppliedBiosystems, Branchburg, NJ, USA).
The reactions were performed in a thermal cycler PTC-100 (MJ Re-search, Inc., Watertown, MA, USA) using the following program: initialdenaturation at 94 °C for 5 min; 35 cycles at 94 °C for 30 s, 60 °C for60 s and 72 °C for 60 s; and a final extension at 72 °C for 5 min. The am-plified fragmentswere analysed by electrophoresis in a 2.0% agarose gelin TAE buffer (40 mM Tris–acetate, 1 mM EDTA) for 60 min at 120 V,stained with ethidium bromide (0.4 μg mL−1 for 5 min) and destainedin distilled water for 30 min. The agarose gel was visualised under UVlight and a digital image was obtained using a Kodak Digital Science™DC120 (Rochester, NY, USA).
2.6. Real-time PCR
The amplifications by real-time PCR were carried out in 20 μLcontaining 2 μL (20 ng) of DNA extract, 1× iQ™ SYBR® Green Supermix(Bio-Rad Laboratories, Hercules, CA, USA) and 500 nM of each primer(Table 1) prepared in parallel reactions for each target sequence. Thereal-time PCR assays were performed on a fluorimetric thermal cycleriCycler iQ™Real-timeDetection System (Bio-Rad Laboratories, Hercules,CA, USA) using the following conditions: 95 °C for 5 min, 45 cycles at95 °C for 30 s and 65 °C for 1 min, with collection of fluorescence signalat the end of each cycle. For melting curve data, the temperature was in-creased by 0.5 °C from65 °C to 94 °C. Datawere collected and processedusing an iCycler iQ™ Real-Time Detection System Software version 3.1.
Table 1Oligonucleotide primers used in the PCR amplifications.
cytb Pork-F ATGAAACATTGGAGTAGTCCTACTATTTACC 149 Dooley et al. (2004)Pork-R CTACGAGGTCTGTTCCGATATAAGG
18S rRNA 18SEU-F TCTGCCCTATCAACTTTCGATGG 140 Fajardo et al. (2008)18SEU-R TAATTTGCGCGCCTGCTG
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3. Results and discussion
3.1. Qualitative PCR
In this study, the primers Pork-F/Pork-R were used to amplify aninternal fragment (149 bp) of the mitochondrial cytochrome b gene(cytb). In previous studies, the selected primers showed no primer-dimerisation and a high specificity, demonstrated by sequence similaritysearch in NCBI databases and no cross-reactivity with DNA from otherspecies (Dooley et al., 2004). The use of both multi-copy target se-quences, such asmitochondrial genes, and shortDNA sequences is partic-ularly advised in the case of thermally processed foods, where DNA canbe degraded, because it increases the possibility of DNA amplification,improving the assay sensitivitywhen compared to single or low copy nu-clear DNA targets (Girish et al., 2005; Rodríguez et al., 2005). Moreover,the large variability of mitochondrial genes enables an appropriate andreliable identification at the level of species (Montiel-Sosa et al., 2000).
The end-point PCR conditions used in this work were optimisedthrough the amplification of DNA extracts obtained from the modelreference samples (binary meat mixtures), enabling the detection of0.1% of pork meat in turkey meat (data not shown). The optimisedPCR conditions were subsequently applied to the commercial samplesto verify the presence of pork meat and the compliance with labelstatements (Fig. 1 and Table 3). From the seventeen tested products,three declared the addition of pork meat on the label and four statedpork fat/uncured bacon as an ingredient. The results show that porkDNA was detected in all samples declaring pork, with the exceptionof sample 9, which indicated pork fat on the label. Regarding theremaining samples with no allegation for pork meat or fat, only sam-ples 12 and 14 were positive with faint bands for the amplification ofpork, which suggests the presence of pork material at trace amounts.
3.2. Real-time PCR
Compared to conventional end-point PCR, the main advantage of areal-time approach is the possibility of performing quantitative mea-surements. Nevertheless, to develop a robust quantitative methodolo-gy, both species-specific and endogenous control primers should beused in combination (Martín et al., 2009). The use of an endogenouscontrol is of utmost importance for quantitative purposes, especially
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 C M
149 bp
Fig. 1. Agarose gel electrophoresis of PCR products targeting the mitochondrial cytb genefor pork species detection in commercialmeat processed products. Lanes 1–8 and10: boiledsausages; lanes 9 and 11: barbeque sausages; lanes 12, 13, 17: nuggets; lanes 14–16: ham-burgers. lane C: negative control; M: 100 bp ladder (Bioron, Ludwigshafen, Germany).
when processed products with complex composition are considered.In this work, the developed real-time PCR approach was based on theSYBRGreen I dye and the use of species-specific primers targeting an in-ternal fragment (149 bp) of the mitochondrial cytb gene of pork incombination with the endogenous control to target DNA from all eu-karyotic organisms based on amplification of the nuclear 18S rRNAgene, with approximately the same efficiency.
3.2.1. Specificity and sensitivity (detection limit)To develop a quantitative approach, model reference mixtures with
known amounts of pork addition were amplified in parallel reactionstargeting fragments of the referred genes. The amplification curves arepresented in Fig. 2 for pork (A) and eukaryotic (B) DNA. To verify thespecificity of the reactions using SYBR Green I as a fluorescent dye, melt-ing curve analysis was performed (Fig. 3). The analysis of the denatur-ation curves enables the calculation of the melting temperatures (Tm)and to verify the absence of unwanted double-stranded DNA fragmentsdue to unspecific amplification. The obtained melting curves showedhigh specificity for the target fragments, presenting characteristic melt-ing temperatures of 83.5 °C (Fig. 3A) and 87.5 °C (Fig. 3B) for pork andeukaryotic detection systems, respectively.
The amplification of the DNA extracts obtained from the model ref-erence mixtures by real-time PCR allowed the detection of pork DNAwith a relative detection limit of 0.1%. The sensitivity of both amplifica-tion systems (pork and eukaryotic) was determined by amplification ofDNA 10-fold serially diluted. In both systems amplification wasachieved until the lowest level of 5 pg of pork DNA. The suggestedreal-time PCR approach had a lower sensitivity compared to the systemproposed by Rodríguez et al. (2005) using a TaqMan real-time PCR(0.01 ng DNA).
3.2.2. Construction of the calibration curve and linearityThe construction of the calibration curve based on real-time PCR
normalisation is essential for reliable quantitative analysis becausethis process controls variations in extraction yields and efficiency of am-plification. The endogenous control allows verifying if amplificationvariations found with the species-specific primers were due to differ-ences in target species content or to other factors such as DNA degrada-tion, inhibition or differences in the amount and quality of the DNAobtained from the sample. Bearing in mind that processed meat prod-ucts generally have several ingredients, including those from vegetablesources, and different processing treatments thatmight affect the targetgene amplification, the use of an endogenous control enables these var-iations to be controlled. For this purpose, the application of ΔΔCt meth-od to construct a calibration model was proposed by calculating:
ΔΔCt ¼ Ctpork–Cteuk
where Cteuk and Ctpork are the cycle thresholds for eukaryotic and porksystems, respectively, obtained through the amplification of binarymodel mixtures (Fig. 2). By plotting the ΔΔCt vs. the logarithm of porkmeat percentage, it is possible to obtain a calibration curve (Fig. 4).This approach allows the estimation of added pork meat at concentra-tions of 0.1% to 25% that covers a linear dynamic range of a least of 3 or-ders of magnitude as suggested by the guidelines for real-time PCRexperiments of Bustin et al. (2009), with a high correlation coefficient
B
0.1%
0.5%
1%
5%
10%
25%
A
Fig. 2. Amplification curves of binary reference mixtures (0.1 to 25% of pork meat) by real-time PCR with SYBR Green I dye for pork (A) and eukaryotic (B) systems.
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(R2=0.9912). A high PCR efficiency (92%) is particularly important, in-dicating a robust and precise quantitative PCR assay (Bustin et al., 2009).
3.2.3. Assay validationValidation mixtures containing known amounts of pork in poultry
meat were analysed in blind assays using the proposed standard
Fig. 3. Melting curves of binary reference mixtures (0.1 to 25% of pork meat) by r
calibration curve in Fig. 4. Table 2 shows the predicted and actualvalues of pork meat percentage for the validation mixtures of 1.0,2.5, 7.5 and 20.0%. The close agreement between the average valuesobtained for the tested concentrations is evidenced by the high prox-imity between true and predicted values. This is indicated by the lowstandard errors, with repeatability lower than 25%, demonstrating the
eal-time PCR with SYBR Green I dye for pork (A) and eukaryotic (B) systems.
y = -3.5449x + 5.5578R² = 0.9912
0.0
2.0
4.0
6.0
8.0
10.0
12.0
-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0
ΔCt
Log (pork meat %)
Fig. 4. Normalised calibration curve for the estimation of the adulteration level of poultry meat with pork meat using eukaryotic amplification as a reference gene and the ΔΔCtmethod (n=6).
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trueness of the proposed technique for estimating the level of addi-tion of pork in poultry meat in the range 1–20%.
Table 3Results of pork species cytb gene PCR amplification and real-time quantitative PCR forthe commercial meat samples.
1 x 25% +++ 4.55±0.872 x 5%b +++ >20.03 x NDc b14 x ND b15 x ND b1
3.2.4. Estimative of pork addition in commercial processed meat productsThe developed and validated assay was further applied to the seven-
teen commercial meat products for quantification purposes. Table 3shows the real-time PCR results in comparison with end-point PCR re-sults and labelled information. The samples labelled as containing porkmeat or fat that gave strong PCR bands (samples 1, 2, 6, 10, 11 and 17),were confirmed positive to pork species by real-time PCR. Comparingthe predicted pork amount with the declared value (when available), itcan be noted that for samples 10, 11 and 17 the estimated pork percent-ages were close to the declared amounts, suggesting compliance withthe label. In sample 1, the estimated pork meat was substantially lower(5%) than the declared (25%), indicating non-compliance with labellingdue to decreased of pork. On the other hand, in sample 2 that stated onthe label 5% of pork fat, in fact containedmore than the maximum valueof the dynamic range, suggesting the fraudulent addition of pork.
In relation to samples 6 and 9 declaring pork fat addition, it waspossible to estimate 2% of pork material in sample 6, indicating alsothe probable presence of pork meat, whilst in sample 9 pork wasdetected at trace amounts, which agrees with labelling due to difficul-ties in obtaining DNA from fat.
Concerning the samples with no declared pork material, only 13,15 and 16 were negative to pork amplification by both qualitativeand real-time PCR and, thus, in compliance with labelling. However,in the other samples (3–5, 7, 8, 12 and 14) pork DNA was detectedat trace amounts (lower than the minimum value in the dynamicrange of 0.1%), confirming the positive results obtained in end-pointPCR for samples 12 and 14, and suggesting the possible occurrencecross-contamination during the production to these samples. Theundeclared addition of pork fat to these samples might be another ex-planation for the mislabelling of these samples.
Table 2Results for the validation of the real-time PCR quantitative assay.
a Values are the mean of replicate assays (n=4).b SD — standard deviation.c CV — coefficient of variation.d Error=(mean value−true value)/true value.
According to these results, the proposed SYBR Green I real-timePCR method proved to be a more accurate and sensitive method com-pared to the conventional end-point PCR approach, allowing both thedetection and quantification of pork DNA in complex meat mixtures.
4. Conclusion
The proposed SYBR Green I real-time PCR method proved to be apowerful and simple technique, highly specific and sensitive for porkspecies identification without requiring any post-PCR treatment andthe use of more expensive fluorescent probes. The developed real-timequantitative PCR assay allowed the detection and quantification ofpork meat in the linear dynamic range of 0.1–25% with high correlationand PCR efficiency, being successfully validated in the range of 1–20%.
Finally, the applicability of the proposed method was demonstratedby the analysis of processed meat products containing other similarpoultry species as themain ingredient, highlighting its adequacy to esti-mate adulteration with pork meat and the need to control processedmeat products regarding mislabelling. Hence, it demonstrated that itcould be used in inspection programs to enforce labelling regulation inthe meat industry.
6 x xb ++ 2.32±0.897 x ND b18 x ND b19 x xb ND b110 x 10% +++ 12.6±0.111 x 5% +++ 7.11±0.1412 x + b113 x ND ND14 x + b115 x ND ND16 x ND ND17 x 9% +++ 7.00±0.75
a SD — standard deviation.b Uncured bacon (salted pork fat).c ND — not detected.
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