A Multiplex PCR Assay Mediated by Universal Primers for the Detection of Adulterated Meat in Mutton

Nanopore-Based Biomimetic ssDNA Reporters for Multiplexed Detection of Meat Adulteration

Meat adulteration detection is crucial for ensuring food safety, protecting consumer rights, and maintaining market integrity. However, the current methods face challenges in achieving multiplexed detection through efficient signal conversion and output. This study introduces a nanopore-based approach for the simultaneous detection of multiple meat adulteration. Leveraging the interaction between DADA dipeptide and vancomycin, we designed a series of biomimetic ssDNA reporters with DADA-Van tags for multiplexed signal output. These ssDNA reporters can generate highly distinctive current blockage signals, which can be discriminated simultaneously by the current waveform. Combined with PCR-based strand displacement, ssDNA reporters can be released from magnetic beads in the presence of the target gene and are analyzed using α-hemolysin (α-HL) nanopores for multiplexed signal output. The signal frequency for each target gene has a linear relationship with the specific concentration range (for duck: 1 × 10-3 ∼ 10 nmol/L, for pork: 1 × 10-2 ∼ 10 nmol/L, and for chicken: 1 × 10-3 ∼ 10 nmol/L). The limits of detection are as follows: 0.418 pmol/L for duck, 4.473 pmol/L for pork, and 0.531 pmol/L for chicken. This method effectively enables the simultaneous detection of adulterated chicken, pork, and duck meat in lamb samples and holds potential for broad applications in ensuring the authenticity and safety of meat products.

Multiplex-PCR method application to identify duck blood and its adulterated varieties

This study applied and validated the Multiplex-PCR method to identify the authenticity of duck blood and four common adulterated animal blood varieties. To this end, the genomic DNAs of duck blood and its counterfeit products were extracted using an efficient high-throughput extraction method. Specific primers were designed using the cytochrome b gene. The reaction system and conditions of a multiplex (namely, Five-plex) PCR were optimized, and the proposed methodology was verified, proving its good specificity, repeatability, and sensitivity. The Five-plex PCR system detected nine duck blood samples sold in the local market, revealing the adulteration of duck blood products. The Multiplex-PCR system can accurately and quickly detect adulterated animal blood in duck blood products, effectively finding counterfeits and identifying the authenticity of genuine duck blood products.

A Novel Universal Primer Multiplex Real-Time PCR (UP-M-rtPCR) Approach for Specific Identification and Quantitation of Cat, Dog, Fox, and Mink Fractions Using Nuclear DNA Sequences

Adulteration of meat with carnivorous animals (such as cats, dogs, foxes, and minks) can cause ethical problems and lead to disease transmission; however, DNA quantitative methods for four carnivorous species in one tube reaction are still rare. In this study, a carnivore-specific nuclear DNA sequence that is conserved in carnivorous animals but has base differences within the sequence was used to design universal primers for its conserved region and corresponding species-specific probes for the hypervariable region. A novel universal primer multiplex real-time PCR (UP-M-rtPCR) approach was developed for the specific identification and quantitation of cat, dog, fox, and mink fractions in a single reaction, with a 0.05 ng absolute limit of detection (LOD) and 0.05% relative LOD. This approach simplifies the PCR system and improves the efficiency of simultaneous identification of multiple animal-derived ingredients in meat. UP-M-rtPCR showed good accuracy (0.48-7.04% relative deviation) and precision (1.42-13.78% relative standard deviation) for quantitative analysis of cat, dog, fox, and mink DNA as well as excellent applicability for the evaluation of meat samples.

Heat-Treated Meat Origin Tracing and Authenticity through a Practical Multiplex Polymerase Chain Reaction Approach

Meat adulteration have become a global issue, which has increasingly raised concerns due to not only economic losses and religious issues, but also public safety and its negative effects on human health. Using optimal primers for seven target species, a multiplex PCR method was developed for the molecular authentication of camel, cattle, dog, pig, chicken, sheep and duck in one tube reaction. Species-specific amplification from the premixed total DNA of seven species was corroborated by DNA sequencing. The limit of detection (LOD) is as low as 0.025 ng DNA for the simultaneous identification of seven species in both raw and heat-processed meat or target meat: as little as 0.1% (w/w) of the total meat weight. This method is strongly reproducible even while exposed to intensively heat-processed meat and meat mixtures, which renders it able to trace meat origins in real-world foodstuffs based on the authenticity assessment of commercial meat samples. Therefore, this method is a powerful tool for the inspection of meat adulterants and has broad application prospects.

Discrimination of Minced Mutton Adulteration Based on Sized-Adaptive Online NIRS Information and 2D Conventional Neural Network

Single-probe near-infrared spectroscopy (NIRS) usually uses different spectral information for modelling, but there are few reports about its influence on model performance. Based on sized-adaptive online NIRS information and the 2D conventional neural network (CNN), minced samples of pure mutton, pork, duck, and adulterated mutton with pork/duck were classified in this study. The influence of spectral information, convolution kernel sizes, and classifiers on model performance was separately explored. The results showed that spectral information had a great influence on model accuracy, of which the maximum difference could reach up to 12.06% for the same validation set. The convolution kernel sizes and classifiers had little effect on model accuracy but had significant influence on classification speed. For all datasets, the accuracy of the CNN model with mean spectral information per direction, extreme learning machine (ELM) classifier, and 7 × 7 convolution kernel was higher than 99.56%. Considering the rapidity and practicality, this study provides a fast and accurate method for online classification of adulterated mutton.

A Heptaplex PCR Assay for Molecular Traceability of Species Origin With High Efficiency and Practicality in Both Raw and Heat Processing Meat Materials

Frequent meat frauds have become a global issue because adulteration risks the food safety, breaches market rules, and even threatens public health. Multiplex PCR is considered to be a simple, fast, and inexpensive technique that can be applied for the identification of meat products in food industries. However, relatively less is known about a multiplex PCR method authenticating seven animal species simultaneously in one reaction due to technological challenge. Through screening new species-specific primers and optimizing PCR system, a heptaplex PCR method was established, which could simultaneously detect seven meat ingredients of camel (128 bp), pigeon (157 bp), chicken (220 bp), duck (272 bp), horse (314 bp), beef (434 bp), and pork (502 bp) in a single-tube reaction. DNA sequencing solidly validated that each set of primers specifically amplified target species from total DNA mixtures of seven meat species. The developed multiplex assay was stable and sensitive enough to detect 0.01–0.025 ng DNA from various meat treatments including raw, boiled, and autoclaved meat samples or target meat content of 0.1% total meat weight, suggesting the suitability of the heptaplex PCR technique for tracing target meats with high accuracy and precision. Most importantly, a market survey validated the availability of this multiplex PCR technique in real-world meat products with a good application foreground.

A quantitative method for detecting meat contamination based on specific polypeptides

OBJECTIVE

This study was aimed to establish a quantitative detection method for meat contamination based on specific polypeptides.

METHODS

Thermally stable peptides with good responses were screened by high resolution liquid chromatography tandem mass spectrometry. Standard curves of specific polypeptide were established by triple quadrupole mass spectrometry. Finally, the adulteration of commercial samples was detected according to the standard curve.

RESULTS

Fifteen thermally stable peptides with good responses were screened. The selected specific peptides can be detected stably in raw meat and deep processed meat with the detection limit up to 1% and have a good linear relationship with the corresponding muscle composition.

CONCLUSION

This method can be effectively used for quantitative analysis of commercial samples.

QCM Sensor Arrays, Electroanalytical Techniques and NIR Spectroscopy Coupled to Multivariate Analysis for Quality Assessment of Food Products, Raw Materials, Ingredients and Foodborne Pathogen Detection: Challenges and Breakthroughs

Quality checks, assessments, and the assurance of food products, raw materials, and food ingredients is critically important to ensure the safeguard of foods of high quality for safety and public health. Nevertheless, quality checks, assessments, and the assurance of food products along distribution and supply chains is impacted by various challenges. For instance, the development of portable, sensitive, low-cost, and robust instrumentation that is capable of real-time, accurate, and sensitive analysis, quality checks, assessments, and the assurance of food products in the field and/or in the production line in a food manufacturing industry is a major technological and analytical challenge. Other significant challenges include analytical method development, method validation strategies, and the non-availability of reference materials and/or standards for emerging food contaminants. The simplicity, portability, non-invasive, non-destructive properties, and low-cost of NIR spectrometers, make them appealing and desirable instruments of choice for rapid quality checks, assessments and assurances of food products, raw materials, and ingredients. This review article surveys literature and examines current challenges and breakthroughs in quality checks and the assessment of a variety of food products, raw materials, and ingredients. Specifically, recent technological innovations and notable advances in quartz crystal microbalances (QCM), electroanalytical techniques, and near infrared (NIR) spectroscopic instrument development in the quality assessment of selected food products, and the analysis of food raw materials and ingredients for foodborne pathogen detection between January 2019 and July 2020 are highlighted. In addition, chemometric approaches and multivariate analyses of spectral data for NIR instrumental calibration and sample analyses for quality assessments and assurances of selected food products and electrochemical methods for foodborne pathogen detection are discussed. Moreover, this review provides insight into the future trajectory of innovative technological developments in QCM, electroanalytical techniques, NIR spectroscopy, and multivariate analyses relating to general applications for the quality assessment of food products.

Quantitative determination of mutton adulteration with single-copy nuclear genes by real-time PCR

Mitochondrial genes were generally adopted for PCR-based meat adulteration authentication due to their excellent specificity to species and numerous copies in one cell. However, the number of mitochondrial gene copies varies according to cells and tissues, which leads to quantification errors for meat adulteration. To address this problem, single-copy nuclear genes were selected to develop a quantitative method for identifying mutton adulteration in this study. Both single-copy genes specific to sheep species and single-copy reference genes show good linearity between Ct values and series diluted DNA concentrations, with the correlation coefficients of 0.9999 and 0.9993, respectively. Meanwhile, a constant (correction factor) was introduced to transform DNA concentrations into mutton proportions in adulterated meat. With this method, simulated mutton-pork, mutton-chicken and mutton-duck adulteration samples could be accurately quantified with the recovery rates of 89.56%, 107.13% and 95.20%, respectively.

Comparative review and the recent progress in detection technologies of meat product adulteration

Meat adulteration, mainly for the purpose of economic pursuit, is widespread and leads to serious public health risks, religious violations, and moral loss. Rapid, effective, accurate, and reliable detection technologies are keys to effectively supervising meat adulteration. Considering the importance and rapid advances in meat adulteration detection technologies, a comprehensive review to summarize the recent progress in this area and to suggest directions for future progress is beneficial. In this review, destructive meat adulteration technologies based on DNA, protein, and metabolite analyses and nondestructive technologies based on spectroscopy were comparatively analyzed. The advantages and disadvantages, application situations of these technologies were discussed. In the future, determining suitable indicators or markers is particularly important for destructive methods. To improve sensitivity and save time, new interdisciplinary technologies, such as biochips and biosensors, are promising for application in the future. For nondestructive techniques, convenient and effective chemometric models are crucial, and the development of portable devices based on these technologies for onsite monitoring is a future trend. Moreover, omics technologies, especially proteomics, are important methods in laboratory detection because they enable multispecies detection and unknown target screening by using mass spectrometry databases.