A normalized model based on Taqman real-time PCR assay for quantitative comparison of chicken adulteration in raw and heat-treated hamburgers

Mislabeling of hamburgers with undeclared chicken has frequently been reported. A fast TaqMan real-time PCR assay was developed to estimate chicken percentage in raw and heat-treated hamburgers in the current work. The calibration curve was plotted with the normalization approach (ΔCt; the difference calculation between chicken-cytb and eukaryotic-18S rRNA assays) for five reference chicken mixtures (100–0.01%) using a duplex TaqMan-qPCR protocol. The R2 and efficiency values of the normalized curve were 0.9993 and ~ 100%, respectively. In the validation plan, analysis of model samples (raw, oven-cooked, and autoclaved) under repeatability conditions represented the bias values within the range of ± 25% and RSD values < 25%, except for a few autoclaved model samples. Therefore, this developed and validated model could be considered a useful and reliable method for estimating chicken species (with a sensitivity of 0.01%) in raw and cooked hamburgers.


Introduction
Meat and meat products contain essential amino acids, B-group vitamins, and macro-and microminerals (heme iron, zinc, selenium, and phosphorus) [1]. Greater demand for meat consumption following the world population growth leads to increase global competition and motivates producers to commit fraud for more economic gains [2].
The adulterations mainly include the undeclared substitutions of high commercial-valued meats by less-expensive animal species and/or vegetable proteins such as soybean [3,4]. However, the accurate information regarding the food composition and meat species makes consumers aware of their concerns about a balanced diet (daily calorie intake), lifestyle (veganism, organic and clean eating), safety (veterinary drug residues, biological and allergenic hazards), and religious dietary restrictions (the prohibition of eating pork in Islamic and Jewish communities) [5][6][7]. Consequently, species authentication in meat products is essential for maintaining fair trade and consumer trust [5].
The analytical techniques including sensory, physicochemical, chromatographic, spectroscopic, and DNA-based methods are applied to trace and authenticate food products [8]. DNA-based techniques are most widely applied to recognize the animal species in meat products for reasons of high detection sensitivity and specificity, multiplexing capabilities, and the rapid diagnosis of minute amounts of target DNA [3,8,9]. They are categorized into three groups including (i) PCR-based methods such as conventional PCR, PCR-RFLP, RAPD-PCR, ddPCR, and real-time PCR; (ii) hybridization-based methods such as slot blot analysis; and (iii) sequencing-based methods such as DNA barcoding and FINS techniques [10,11]. Among these techniques, real-time PCR (qPCR) is commonly used for both the identification and quantitation of meat species. The quantitative analysis discriminates between economically motivated adulteration (deliberate adulteration) and unintentional cross-contamination during manufacturing processes [12]. In qPCR, the Ct value (the cycle numbers at which the generated fluorescence crosses the threshold line) is used for the analysis, as it is inversely related to the initial amounts of target DNA [13].
Hamburger is one of the most popular meat products in the world, whose formulated meat may intentionally substitute with undeclared chicken meat due to its abundance and lower price [14][15][16][17][18][19]. It is possible to estimate the chicken percentage in the mislabeled meat products by different models of real-time PCR (absolute, relative, and normalized quantifications) [17].
Despite the high stability of DNA, particularly mitochondrial type, under different processing conditions, some studies found that the species identification could not be easily distinguished in the cooked meat products owing to an increase in the degree of DNA degradation and insufficient amount of amplifiable DNA extract [20][21][22][23]. Therefore, the current study aimed to develop a reliable, sensitive, specific, and fast qPCR assay using TaqMan MGB probe for chicken estimation in the raw hamburgers. Moreover, the assay results of the raw and heat-treated model samples were compared to evaluate the effect of possible degradation of DNA under thermal processing on the applicability of the developed method. Figure 1 shows the schematic diagram of the research process.

Sample preparation
The muscles of chicken (Gallus gallus) and beef (Bos taurus) were used to prepare the reference and model samples.
Raw reference samples: these samples were used for plotting a standard curve. The samples were made through a tenfold sequential series of chicken meat samples (0.001-100%, w/w) admixed in the minced beef matrix.
Raw model samples: they were applied to validate the developed method. The model binary mixtures included 2.5%, 5%, 10%, 25%, and 50% (w/w) of chicken meat. Also, 750 g of chicken meat, 750 g of minced beef, 500 g of onion, 100 g of toasted flour, 50 g of wheat fiber, 50 g of wheat gluten, 30 g of salt, 25 g of bell pepper, 25 g of special seasonings and 220 g of ice cold water were formulated to prepare a model burger 30% (w/w) of chicken meat.
Heat-treated model samples: the effect of thermal treatments on the DNA integrity, repeatability, and reproducibility of assay results was also investigated on two groups of model samples including (i) autoclaved model samples (covered with aluminum foil and treated at 121 °C under 100 kPa for 15 min), and (ii) oven-cooked model samples (covered Fig. 1 The schematic diagram of the research process with aluminum foil until oven reached 180 °C which took 30 min). Two types of thermal processing were performed before the DNA extraction stage. All samples and their DNA extracts were quickly stored at -20 °C without the repeated freeze-thaw cycles.

DNA extraction
The DNA was isolated from samples (30 mg) using the FavorPrep™ Tissue Genomic DNA extraction Mini Kit (Favorgen, Taiwan) according to the manufacturer's instructions. Each piece was mixed with FATG1 buffer (200 μL) and protease K (20 μL) and incubated at 60 °C until the tissues were completely lysed. Afterward, FATG2 buffer (200 μL) was added to the mixture and incubated (at 70 °C for 10 min). The lysate was mixed with ethanol (200 μL) and was passed entirely through the FATG mini-column and centrifugation was carried out (~ 18,000×g, 1 min). Then, the column was washed and centrifuged (~ 18,000×g, 1 min) twice with wash buffer 1 (400 μL) and wash buffer 2 (750 μL), respectively. Additionally, the column was centrifuged (~ 18,000×g, 3 min) without adding any solution to remove liquid residues, and the DNA absorbed into the column was finally eluted with elution buffer (50 μL) and centrifuged (~ 18,000×g, 2 min).
The concentration, extraction efficiency, and purity of the DNA extracts were determined using a Thermo Scientific NanoDrop 1000 Spectrophotometer. An A 260 (OD) of 1.0 = 50 μg/mL dsDNA solution and an A 260 /A 280 value ≥ 1.7 is known as pure DNA extract.

Primers/probes set
The synthesis of oligonucleotide primer pairs and TaqMan-MGB probes was done by Metabion-Arian Gene Gostar Company (Tehran, Iran) according to the studies of Tanabe et al. and Rojas et al. for chicken identification and endogenous control, respectively [24,25] (Table 1).
The amplification program was run in a StepOneTM Real-time PCR System, (Applied Biosystem) with the following thermal cycling conditions: an initial denaturation and enzyme activation at 95 °C for 3 min, then 40 two-stage cycles (denaturation at 95 °C for 5 s and annealing/extension at 57 °C for 20 s).

The construction of the standard curve
The ΔCt method was applied to quantify the chicken meat (%) by TaqMan-qPCR assay. The ΔCt values were obtained by the equation of ΔCt = Ct (target species gene) − Ct (endogenous reference gene), where Ct (target) is the cycle threshold (Ct) value obtained from the chicken-cytb gene content (chicken-specific system) in the reaction mixture, Ct (reference) is the Ct value obtained from eukaryotic 18S rRNA gene content (eukaryotic-reference system) in the reaction mixture, and ΔCt is difference between the Ct values of the target and reference genes. As a result, the ΔCt curve or normalized calibration curve was constructed by the mean ΔCt values (y axis) versus the logarithmic chicken percentage of reference samples (x axis), giving the equation ΔCt = a (log reference mixture) + b, where "a" and "b" are the slope and intercept of the calibration curve, respectively.
The coefficient of determination (R 2 ) of a standard curve should be > 0.98. The amplification efficiency (E%) is calculated using the slope of a calibration curve with the equation E = [10 (−1/−a) − 1] × 100, and should be within the acceptable range of 90 ≤ E% ≤ 110 which is corresponded to a slope of − 3.6 to − 3.1.
To construct the normalized standard curve, the DNA extracts of the reference mixtures (0.01% to 100%, w/w) were adjusted to 5 ng/μL and subsequently, the reaction mixtures containing 10 ng template DNA were analyzed using duplex TaqMan-qPCR in triplicate on 3 days.
Meanwhile, for the determination of the limits of detection (LOD) and quantification (LOQ), the DNA extracts were analyzed in 20 replicates. LOD is the lowest target concentration that can be detected with probability ≥ 95%, ensuring a false-negative rate of < 5%. While, LOQ is the lowest target concentration that can be quantitatively determined with the satisfactory RSD (the relative standard deviation) and bias values [17,26,27].

Validation of the developed method
The model burgers and mixtures (raw, autoclaved, and ovencooked samples) containing 2.5%, 5%, 10%, 25%, 30%, and 50% (w/w) of chicken meat were analyzed by the described TaqMan-qPCR procedure in triplicate on 3 days. The chicken percentages of model samples were estimated using the equation of the normalized calibration curve. Then, the precision and bias parameters were separately calculated for each model sample to validate the developed TaqMan-qPCR according to the defined criteria for qPCR assays.

Statistical analysis
All calculations (mean, SD, RSD, and bias) and the curve creation were accomplished using Microsoft Excel. According to the acceptance criteria of real-time PCR assays, the developed method is validated if all assays of the raw and heat-treated model samples have the values of bias within ± 25% and RSD less than 25% [28,29]. The precision represents the relative standard deviation (RSD) value of assay results under repeatability and reproducibility conditions [intra-day (three times a day) and interday (3 consecutive days), respectively]. The bias (trueness value) is calculated according to the formula Bias = ((mean measured value − actual value)/actual value) × 100 [17].

Quantitative and qualitative analyses of DNA extracts
The absorbance rates of A 260 /A 280 were 1.76-1.98, and the DNA concentrations ranged from 54.6 to 372.9 ng/μL, showing that high-quality and high-quantity DNA solutions were extracted from all samples.

The specificity of primer/probe sets
In this study, the used primers/probe sets targeted the small DNA sequences of the chicken mitochondrial cytb gene (with 106 bp) and eukaryotic 18S rRNA gene (with 141 bp) ( Table 1). Short amplicon lengths (< 150 bp) are recommended for the development and sensitivity improvement of species-specific PCR assays in complex and processed products [12]. In addition to the formation of short amplicons, the amplification of mitochondrial DNA (mtDNA) sequences is more likely than nuclear DNA (nDNA) in heavily processed meat products because of high mtDNA copy numbers per cell, smaller size, and stronger protection by the mitochondrial double membrane, causing more effective stability [6,30].
The mtDNA sequences of various species have been phylogenetically studied and extensively used to detect the animal species in highly processed meat products [31]. Also, because mtDNA evolves at a faster rate than nDNA, it has been applied to discriminate the target species from similar species [22].
Generally, the genetic markers of cytochrome b (cytb), cytochrome oxidase, 16S ribosomal RNA (16S rRNA), 12S ribosomal RNA (12S rRNA), NADH dehydrogenase, displacement loop (D-loop) and ATPase on the mitochondrial genome (known as multi-copy genes), and also the lactoferrin gene promoter region, epidermal growth factor pseudogene, interleukin-2 precursor gene, non-coding regions of the cGMP phosphodiesterase gene and the ryanodine receptor gene located on the nuclear DNA (known as single-copy genes) have been mostly reported for meat species identification in previous studies [3,8,17].
The distribution of mitochondria varies in different tissues of a species, inter and intra-species [27]. Accordingly, for better modeling in this study, firstly, the minced beef and chicken meats for the preparation of samples were obtained from different individuals and tissues of both species and secondly, the obtained results from chicken-cytb assays in the chicken-specific system were normalized with eukaryotic-18S rRNA assays, which exceptionally known as multiple nuclear gene sequences.
The fragments of 106 bp and 141 bp were amplified in the PCR reaction mixtures containing pure chicken extracts (positive control) using a duplex-qPCR with the mean Ct values of 21.52 ± 0.19 (chicken-specific system) and 22.67 ± 0.07 (eukaryotic-reference system), respectively. The amplicons in the reaction mixtures containing pure beef DNA (negative control) were quantified in the Ct values of 35.04 ± 0.18 and 21.73 ± 0.09, respectively. Therefore, there was a Ct difference of 13.5 cycles (n) between the reaction strips of chicken DNA with those of bovine DNA in the chicken-specific system, causing a cross-reactivity percentage of 0.008% (1/2 n × 100). Also, a cycle difference of < 1 between the mean Ct values of positive and negative controls in the eukaryotic-reference system showed that the 18S rRNA region selected as an endogenous control could properly normalize the Ct values obtained from the chickenspecific system. Furthermore, no amplification signal was detected in the PCR reaction mixtures without any DNA extract (NTC) after 40 cycles for both systems. Meanwhile, the reaction mixtures containing the DNA extracts of 12 species (Sus scrofa, Camelus dromedaries, Equus caballus, Ovis aries, Equus asinus, Capra hircus, Anas platyrhynchos, Meleagris gallopavo, Anser anser, Coturnix coturnix, Phasianus colchicus, and Struthio camelus) showed no positive amplification signals up to cycle 35 for the chicken-specific system, while Ct values between 21 to 23 were detected for the eukaryotic-reference system. As a result, all the cases mentioned above proved the high-throughput specificity of both primer/probe sets used in this study.

Interpretation of the standard curve
In this study, a normalized calibration curve was proposed for the quantification of chicken percentage in samples by TaqMan-qPCR assay. The calibration curve was plotted by the mean ΔCt values against five magnitude orders of chicken [0.01%, 0.1%, 1%, 10%, and 100% (w/w)] (Fig. 2). All PCR reaction mixtures for amplification initially included 10 ng of DNA extract derived from the reference samples.
The outcome of this analysis was the equation y = − 3.322x + 5.614, in which "y" is the mean ΔCt value, " − 3.322" is the slope of the regression line (a), "x" is the log 10 chicken percentage and "5.614" is the intercept of the regression line (b). The intercept of "5.614" relates to the mean ΔCt value for the reference chicken mixture of 1%. Consequently, an ideal linear calibration curve was created with an R 2 of 0.9993 and PCR efficiency of ~ 100%. The efficiency of 100% shows that the tenfold sequential increases of chicken meat in the reference mixtures ideally cause the intervals of 3.3 cycles in the plotted standard curve. The chicken quantities (%) of unknown samples were estimated via interpolation of their ΔCt value in the plotted curve and using the formula of chicken percentage (%) = 10 [(ΔCt − b)/a] .
The inhibitors/enhancers of PCR in the matrix of a food product as well as the processing treatments may affect the dsDNA denaturation, primer hybridization, and Taq DNA polymerase activity, causing an over or under-estimation in species detection due to the reduction or increase in the Ct value, respectively [17,32,33]. Hence, the use of a reference gene (e.g., 18S rRNA, myostatin, and β-actin) as endogenous control could assess the inhibition and enhancement of PCR amplification leading to the false negative or positive results of qPCR, respectively [34,35]. Therefore, to have a reliable and effective quantification in the current work, the developed TaqMan-qPCR method was performed according to a duplex-qPCR with the simultaneous amplification of both sequences of the chicken-cytb and eukaryotic-18S rRNA genes in the PCR reaction mixtures.
This model has been previously applied to quantify the undeclared pork in processed meat products by Eva Green-qPCR [12] and in processed poultry products by SYBR Green-qPCR [35], and also the adulteration of processed products with horse meat in by Eva Green-qPCR [34].

The determination of sensitivity and cross-reactivity
The DNA extracts derived from standard samples of 0.001%, 0.01%, and 0.1% (w/w) were analyzed in 20 replicates by duplex TaqMan-qPCR to determine the LOD and LOQ values. The chicken percentage of each concentration was estimated by interpolating their mean ΔCt values (y) in the normalized equation (Table 2). The 0.1% and 0.01% concentrations were successfully detected in 20 replicates with acceptable values of RSD (18.80% and 8.95%, respectively) and bias (10.73% and 21.21%, respectively). Therefore, the concentration of 0.01% was reliably reported as the LOD and LOQ of the developed method, because it is the lowest chicken concentration that its RSD and bias values were obtained below 25% from the ΔCt values of 20 replicates. This sensitivity was better in comparison with the results of previous studies such as Cammà [14,36].
However, an unsatisfactory value of bias was obtained for the meat mixture of 0.001%, because the interval of 3.1 to 3.6 cycles was not observed between this concentration (0.001%) and a higher chicken concentration (0.01%). Also, the mean Ct value of the meat mixture of 0.001% was nearly similar to the negative control sample (pure beef), probably resulting from the cross-reaction of chicken-specific assays with beef DNA in cycles above 35. Hence, the concentration of 0.001% was not considered in plotting the standard curve. Such cross-reactivity between the target and nontarget DNAs in PCR reactions has been described in a study by Dooley et al. [23].

The model validation
To validate the normalized qPCR method, the precision and bias parameters were assessed for the model samples under repeatability conditions. For this purpose, three sets of in-house chicken models (raw, oven-cooked, and autoclaved samples) containing 2.5%, 5%, 10%, 25%, 30%, and 50% (w/w) of chicken meat were quantified (in triplicate on 3 days) by the normalized equation in "Interpretation of the standard curve" section. The oven-cooked and autoclaved model samples were applied to evaluate the effect of high temperatures on the estimation of chicken percentage using the normalized curve that was constructed based on the raw reference samples (0.01-100%, w/w). As can be observed in Table 3, the estimated chicken percentages were listed in the front of actual chicken concentrations of each model sample.
The RSD obtained under repeatability conditions ranged from 1.44 to 14%, showing the precision values of all model samples in an acceptable range (≤ 25%) [28,29].
The calculated bias values were within the range of ± 25% for raw and oven-cooked model samples, which demonstrated a close agreement between the actual and estimated values [28,29]. However, the most bias values belonged to the autoclaved model samples, especially the mixtures of 25% (− 26.26%) and 5% (− 34.43%), which deviated from the acceptance criterion, probably due to the simultaneous impact of the temperature and pressure used in the autoclave on the degradation of selected gene regions. Some studies reported that the quantification of target species using qPCR is affected by the temperature, duration of heat treatment, and size of the mitochondrial template DNA [22,37,38].
Meanwhile, the Ct values of both chicken and eukaryotic assays in the model chicken burger 30% were even lower than those in the model chicken mixture 50%, possibly because of the enhancer substances in the burger matrix.
Enhancers (such as additives and onion sulfoxides) accelerate the PCR reactions in three steps of denaturation, annealing, and extension, and cause an overestimation of undeclared species by reducing Ct values [17,32]. However, the model proposed by considering the ΔCt values (the difference between the Ct values from the chicken and eukaryotic systems) can reliably quantify the chicken presence in the processed meat products without interference from the inhibitors/enhancers of PCR.

Conclusion
The results showed that the developed ΔCt method in this study could estimate the chicken percentage in the raw and cooked beef burgers with acceptable precision and trueness parameters without the interference of inhibitor/enhancer compounds and heat processing. Meanwhile, the tested model could reliably estimate the chicken spiked in the beef matrix to 0.01% without any cross-reaction. Further studies are needed to improve the estimation of meat species in processed foods using the qPCR-based normalized curves.