Species identification and quantification in meat and meat products using droplet digital PCR (ddPCR)

Establishment of a Sensitive and Reliable Droplet Digital PCR Assay for the Detection of Bursaphelenchus xylophilus

Pine wilt disease (PWD), which poses a significant risk to pine plantations across the globe, is caused by the pathogenic agent Bursaphelenchus xylophilus, also referred to as the pine wood nematode (PWN). A droplet digital PCR (ddPCR) assay was developed for the quick identification of the PWN in order to improve detection sensitivity. The research findings indicate that the ddPCR assay demonstrated significantly higher analysis sensitivity and detection sensitivity in comparison to traditional quantitative PCR (qPCR). However, it had a more limited dynamic range. High specificity was shown by both the ddPCR and qPCR techniques in the diagnosis of the PWN. Assessments of reproducibility revealed that ddPCR had lower coefficients of variation at every template concentration. Inhibition tests showed that ddPCR was less susceptible to inhibitors. There was a strong linear association between standard template measurements obtained using ddPCR and qPCR (Pearson correlation = 0.9317; p < 0.001). Likewise, there was strong agreement (Pearson correlation = 0.9348; p < 0.001) between ddPCR and qPCR measurements in the evaluation of pine wood samples. Additionally, wood samples from symptomatic (100% versus 86.67%) and asymptomatic (31.43% versus 2.9%) pine trees were diagnosed with greater detection rates using ddPCR. This study's conclusions highlight the advantages of the ddPCR assay over qPCR for the quantitative detection of the PWN. This method has a lot of potential for ecological research on PWD and use in quarantines.

Discovery unbalanced DNA mixtures and evaluation mixing ratio via a droplet digital PCR method

BACKGROUND

Small amounts of DNA from a perpetrator collected during crime-scene investigations can be masked by large amounts of DNA from the victim. These samples can provide important information for the perpetrator's conviction. Short tandem repeat (STR) detection system is not sensitive enough to detect trace amounts of minor components in unbalanced mixed DNA. We developed a system using droplet digital polymerase chain reaction (ddPCR) capable of discovering trace components and accurately determining the ratio of mixed DNA in extremely unbalanced mixtures.

METHODS

The non-recombining regions of the X chromosome and Y chromosome were quantified in the DNA of male and female mixtures using duplex ddPCR. Absolute quantification of low-abundance portions of trace samples and unbalanced mixtures was done using different mixing ratios.

RESULTS

The ddPCR system could be used to detect low-abundance samples with < 5 copies of DNA components in an extremely unbalanced mixture at a mixing ratio of 10000:1. The high sensitivity and specificity of the system could identify the mixing ratio of mixed DNA accurately.

CONCLUSIONS

A ddPCR system was developed for evaluation of mixed samples of male DNA and female DNA. Our system could detect DNA quantities as low as 5 copies in extremely unbalanced mixed samples with good specificity and applicability. This method could assist forensic investigators in avoiding the omission of important physical evidence, and evaluating the ratio of mixed male/female trace samples.

Digital PCR assay for the specific detection and estimation of Salmonella contamination levels in poultry rinse

Strains of Salmonella are a frequent cause of foodborne illness and are known to contaminate poultry products. Most Salmonella testing methods can qualitatively detect Salmonella and cannot quantify or estimate the Salmonella load in samples. Therefore, the aim of this study was to standardize and validate a partitioned-based digital PCR (dPCR) assay for the detection and estimation of Salmonella contamination levels in poultry rinses. Pure culture Salmonella strains were cultured, enumerated, cold-stressed for 48 h, and used to inoculate whole carcass chicken rinse (WCCR) at 1-4 log CFU/30 mL and enriched at 37 °C for 5 h. Undiluted DNA samples with primer and probes targeting the Salmonella-specific invA gene were used for the dPCR assay. The dPCR assay was highly specific, with a limit of detection of 0.001 ng/μL and a limit of quantification of 0.01 ng/μL. The dPCR assay further showed no PCR reaction inhibition up to 5 μg of crude DNA extract. The assays accurately detected all cold-stressed Salmonella in inoculated WCCR samples following a 5-h enrichment. Most importantly, when converted to log, the dPCR copies/μL values accurately estimated the inoculated Salmonella levels. The dPCR assay standardized in this study is a robust method for the detection and estimation of Salmonella concentration in contaminated food samples. This approach can allow same-day decision-making for poultry processors attempting to maintain limits and controls on Salmonella contamination.

Fresh Meat Classification Using Laser-Induced Breakdown Spectroscopy Assisted by LightGBM and Optuna

To enhance the accuracy of identifying fresh meat varieties using laser-induced breakdown spectroscopy (LIBS), we utilized the LightGBM model in combination with the Optuna algorithm. The procedure involved flattening fresh meat slices with glass slides and collecting spectral data of the plasma from the surfaces of the fresh meat tissues (pork, beef, and chicken) using LIBS technology. A total of 900 spectra were collected. Initially, we established LightGBM and SVM (support vector machine) models for the collected spectra. Subsequently, we applied information gain and peak extraction algorithms to select the features for each model. We then employed Optuna to optimize the hyperparameters of the LightGBM model, while a 10-fold cross-validation was conducted to determine the optimal parameters for SVM. Ultimately, the LightGBM model achieved higher accuracy, macro-F1, and Cohen's kappa coefficient (kappa coefficient) values of 0.9370, 0.9364, and 0.9244, respectively, compared to the SVM model's values of 0.8888, 0.8881, and 0.8666. This study provides a novel method for the rapid classification of fresh meat varieties using LIBS.

Use of Droplet Digital Polymerase Chain Reaction to Identify Biomarkers for Differentiation of Benign and Malignant Renal Masses

Several microRNAs (miRNAs) have been identified as cell-free biomarkers for detecting renal cell carcinoma (RCC). Droplet digital polymerase chain reaction (ddPCR) is a unique technology for nucleic acid quantification. It has the potential for superior precision, reproducibility, and diagnostic performance in identifying circulating miRNA biomarkers compared to conventional quantitative real-time PCR (qRT-PCR). This study aims to evaluate the performance of ddPCR compared to qRT- PCR in identifying miRNA biomarkers that differentiate malignant from benign renal masses. Potential biomarkers of RCC were identified from a literature review. RNA was extracted from the plasma of 56 patients. All the samples underwent analysis via ddPCR as well as qRT-PCR, and expression levels were recorded for the following miRNAs: miR-93, -144, -210, -221, and -222. Tumors were grouped into low-grade ccRCC, high-grade ccRCC, papillary RCC, and benign masses (primarily angiomyolipoma). The miRNA miR-210 (p = 0.034) and the combination of miRs-210 and miR-222 (p = 0.003) were expressed at significantly higher rates among those with RCC than those with benign masses, as measured by ddPCR. Using the combination of miR-210 and miR-222, ddPCR identified significant differences between the subgroups: papillary RCC versus benign (p = 0.03), low-grade ccRCC versus benign (p = 0.026), and high-grade ccRCC versus benign (p = 0.002). The only significant difference between these subgroups using qRT-PCR was between high-grade ccRCC and benign (p = 0.045). All the AUCs were significant when comparing each RCC subgroup with benign for both PCR technologies. Using a combination of miR-210 and miR-222, ddPCR identified significant differences between benign and malignant renal masses that were not identified as significant by conventional qRT-PCR.

A Droplet Digital PCR-Based Approach for Quantitative Analysis of the Adulteration of Atlantic Salmon with Rainbow Trout

Low-cost fish species are often used to adulterate or substitute for Atlantic salmon products, posing a serious threat to market order and public health. Hence, reliable techniques are urgently needed to detect Atlantic salmon adulteration. In this study, a precise method for identifying and quantifying adulterated Atlantic salmon with rainbow trout based on droplet digital PCR (ddPCR) testing was developed. Species-specific primers and probes were designed targeting the single-copy nuclear gene myoglobin of two salmonids. A quantitative formula for calculating the mass fraction of adulterated Atlantic salmon with rainbow trout was established based on a one-step conversion strategy, in which the DNA copy number ratios were directly transformed to meat mass fractions by introducing a fixed constant (the transfer coefficient). The dynamic range of the established ddPCR method was from 1% to 90%, with a limit of detection (LOD) of 0.2% and a limit of quantification (LOQ) of 0.8% for rainbow trout in Atlantic salmon, respectively. The quantification method demonstrated an acceptable level of repeatability and reproducibility, as the values of the relative standard deviation (RSD) for the tested meat mixtures with the known fractions were all less than 5%. Thermal and freezing treatments, as well as adding food additives within the recommended dosage limits, had no significant effect on the quantification accuracy. The method was successfully applied to detect rainbow trout adulteration in commercial raw and processed Atlantic salmon products. In comparison to real-time quantitative PCR (qPCR) testing, the established ddPCR method exhibited a higher level of stability and accuracy. Overall, the ddPCR-based quantitative method exhibited high levels of accuracy, stability, sensitivity, and practicability, suitable for applications in the routine surveillance and quality assurance of salmon products.

Development of Seven New dPCR Animal Species Assays and a Reference Material to Support Quantitative Ratio Measurements of Food and Feed Products

Laboratory testing methods to confirm the identity of meat products and eliminate food fraud regularly rely on PCR amplification of extracted DNA, with most published assays detecting mitochondrial sequences, providing sensitive presence/absence results. By targeting single-copy nuclear targets instead, relative quantification measurements are achievable, providing additional information on the proportions of meat species detected. In this Methods paper, new assays for horse, donkey, duck, kangaroo, camel, water buffalo and crocodile have been developed to expand the range of species that can be quantified, and a previously published reference assay targeting the myostatin gene has been modified to include marsupials and reptiles. The accuracy of this ratio measurement approach was demonstrated using dPCR with mixtures of meat DNA down to 0.1%. However, the limit of detection (LOD) of this approach is not just determined by the assay targets, but by the samples themselves, with food or feed ingredients and processing impacting the DNA yield and integrity. In routine testing settings, the myostatin assay can provide multiple quality control roles, including monitoring the yield and purity of extracted DNA, identifying the presence of additional meats not detected by the suite of species-specific assays and potentially estimating a sample-specific LOD based on measured copy numbers of the myostatin target. In addition to the myostatin positive control assay, a synthetic DNA reference material (RM) has been designed, containing PCR targets for beef, pork, sheep, chicken, goat, kangaroo, horse, water buffalo and myostatin, to be used as a positive template control. The availability of standardised measurement methods and associated RMs significantly improves the reliability, comparability and transparency of laboratory testing, leading to greater confidence in results.

Novel economical, accurate, sensitive, single-cell analytical method for mitochondrial DNA quantification in mtDNA mutation carriers

PURPOSE

Although a variety of analytical methods have been developed to detect mitochondrial DNA (mtDNA) heteroplasmy, there are special requirements of mtDNA heteroplasmy quantification for women carrying mtDNA mutations receiving the preimplantation genetic diagnosis (PGD) and prenatal diagnosis (PD) in clinic. These special requirements include various sample types, large sample number, long-term follow-up, and the need for detection of single-cell from biopsied embryos. Therefore, developing an economical, accurate, high-sensitive, and single-cell analytical method for mtDNA heteroplasmy is necessary.

METHODS

In this study, we developed the Sanger sequencing combined droplet digital polymerase chain reaction (ddPCR) method for mtDNA quantification and compared the results to next-generation sequencing (NGS). A total of seventeen families with twelve mtDNA mutations were recruited in this study.

RESULTS

The results showed that both Sanger sequencing and ddPCR could be used to analyze the mtDNA heteroplasmy in single-cell samples. There was no statistically significant difference in heteroplasmy levels in common samples with high heteroplasmy (≥ 5%), low heteroplasmy (< 5%), and single-cell samples, either between Sanger sequencing and NGS methods, or between ddPCR and NGS methods (P > 0.05). However, Sanger sequencing was unable to detect extremely low heteroplasmy accurately. But even in samples with extremely low heteroplasmy (0.40% and 0.92%), ddPCR was always able to quantify them. Compared to NGS, Sanger sequencing combined ddPCR analytical methods greatly reduced the cost of sequencing.

CONCLUSIONS

In conclusion, this study successfully established an economical, accurate, sensitive, single-cell analytical method based on the Sanger sequencing combined ddPCR methods for mtDNA heteroplasmy quantification in a clinical setting.

Droplet digital PCR versus real-time PCR for in-house validation of porcine detection and quantification protocol: An artificial recombinant plasmid approach

Authenticity and traceability are essential for modern food and medicine inspection, and reliable techniques are important for the trade of halal foods, which reach more than 20 percent of the world market. A sensitive and accurate porcine detection method is required to develop a conformity assessment system that includes laboratory testing for porcine-free certification. This study proposes a procedure that could be incorporated into the development of a standardized control and protocol for real-time PCR (qPCR) methods and their traceability using droplet digital PCR (ddPCR). The design used a recombinant pUC57 plasmid as an amplification target to carry the 97 bp fragment of the porcine ATCB gene. The absolute quantification and linearity assessment showed high precision with R2 values of 0.9971 and 0.9998 for qPCR and ddPCR, respectively. In general, both methods showed comparable results in terms of linearity and detection limit. However, both limit of detection assessments showed high sensitivity, although ddPCR showed a slightly higher sensitivity than that of qPCR, especially at low DNA concentrations. Multiple-sample and inter-participatory testing evaluations revealed a high sensitivity, broad applicability, and robustness of the qPCR method. Therefore, we conclude that based on a recombinant plasmid analysis with a low quantity (less than five copy number), the digital PCR method produced more reliable results. These results could provide scientific information for regulatory authorities, especially those in Indonesia, to consider the development and formulation of a well-established qPCR protocol for porcine detection using expected DNA concentrations.

Horizon scan of DNA-based methods for quality control and monitoring of herbal preparations

Herbal medicines and preparations are widely used in healthcare systems globally, but concerns remain about their quality and safety. New herbal products are constantly being introduced to the market under varying regulatory frameworks, with no global consensus on their definition or characterization. These biologically active mixtures are sold through complex globalized value chains, which create concerns around contamination and profit-driven adulteration. Industry, academia, and regulatory bodies must collaborate to develop innovative strategies for the identification and authentication of botanicals and their preparations to ensure quality control. High-throughput sequencing (HTS) has significantly improved our understanding of the total species diversity within DNA mixtures. The standard concept of DNA barcoding has evolved over the last two decades to encompass genomic data more broadly. Recent research in DNA metabarcoding has focused on developing methods for quantifying herbal product ingredients, yielding meaningful results in a regulatory framework. Techniques, such as loop-mediated isothermal amplification (LAMP), DNA barcode-based Recombinase Polymerase Amplification (BAR-RPA), DNA barcoding coupled with High-Resolution Melting (Bar-HRM), and microfluidics-based methods, offer more affordable tests for the detection of target species. While target capture sequencing and genome skimming are considerably increasing the species identification resolution in challenging plant clades, ddPCR enables the quantification of DNA in samples and could be used to detect intended and unwanted ingredients in herbal medicines. Here, we explore the latest advances in emerging DNA-based technologies and the opportunities they provide as taxa detection tools for evaluating the safety and quality of dietary supplements and herbal medicines.

Duplex droplet digital PCR (ddPCR) for simultaneous quantification of bovine and porcine gelatin in capsules

Detection of bovine and porcine in gelatin-based products is important as species fraud and product mislabeling may have a detrimental impact on customers who have health, ethical, and religious concerns about animal products. The duplex droplet digital PCR (ddPCR) assay using double-quenched probes has been developed for quantification and detection of porcine and bovine DNA in gelatin capsules. A DNA mixture derived from gelatin was found to have a limit of detection as low as 0.001 ng/µl for porcine samples and 0.01 ng/µl for bovine samples. DNA from 12 other distinct species was tested with the bovine and porcine probes, showing high specificity for this method. The test was validated using fifty-five commercial supplement and pharmaceutical capsules, of which 17 were positive for bovine and/or porcine DNA. This study shows that the duplex ddPCR is reliable for routine analysis in the identification of bovine and porcine origins for gelatin capsules.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10068-022-01204-x.

DNA barcoding in herbal medicine: Retrospective and prospective

DNA barcoding has been widely used for herb identification in recent decades, enabling safety and innovation in the field of herbal medicine. In this article, we summarize recent progress in DNA barcoding for herbal medicine to provide ideas for the further development and application of this technology. Most importantly, the standard DNA barcode has been extended in two ways. First, while conventional DNA barcodes have been widely promoted for their versatility in the identification of fresh or well-preserved samples, super-barcodes based on plastid genomes have rapidly developed and have shown advantages in species identification at low taxonomic levels. Second, mini-barcodes are attractive because they perform better in cases of degraded DNA from herbal materials. In addition, some molecular techniques, such as high-throughput sequencing and isothermal amplification, are combined with DNA barcodes for species identification, which has expanded the applications of herb identification based on DNA barcoding and brought about the post-DNA-barcoding era. Furthermore, standard and high-species coverage DNA barcode reference libraries have been constructed to provide reference sequences for species identification, which increases the accuracy and credibility of species discrimination based on DNA barcodes. In summary, DNA barcoding should play a key role in the quality control of traditional herbal medicine and in the international herb trade.

A confirmed association between DNA variants in CAPN9 , OSM , and ITGAM candidate genes and the risk of umbilical hernia in pigs

Umbilical hernia (UH) is one of the most prevalent defects of swine, affecting their welfare and causing considerable economic loss. The molecular mechanisms behind UH in pigs remain poorly understood. The aim of this study was to verify the association between UH and previously reported DNA variants in the CAPN9, OSM, ITGAM, and NUGGC genes. A case/control study design was applied in two different crossbred cohorts of commercial fatteners containing 412 and 171 pigs, respectively. SNPs within CAPN9, OSM, and ITGAM were analyzed using Sanger sequencing, and 10 SNPs in CAPN9, five in OSM, and two in ITGAM were identified. A structural variant in the NUGGC gene was studied by droplet-digital PCR, and an elevated copy number was detected in only a single individual. Significant differences in allele frequencies for four SNPs in CAPN9 were detected. The haplotype analysis showed the effect on the risk of UH for two genes. The CAGGA haplotype within OSM and AT haplotype in ITGAM reduced the relative risk of UH by 52% and 45%, respectively, confirming that variants in those genes are associated with the risk of UH in pigs. Moreover, the interaction between the CAPN9 haplotype and the sex of animals had also significant impact on UH risk.

Development of the Droplet Digital PCR Method for the Detection and Quantification of Erwinia pyrifoliae

Black shoot blight disease caused by Erwinia pyrifoliae has serious impacts on quality and yield in pear production in Korea; therefore, rapid and accurate methods for its detection are needed. However, traditional detection methods require a great deal of time and fail to achieve absolute quantification. In the present study, we developed a droplet digital polymerase chain reaction (ddPCR) method for the detection and absolute quantification of E. pyrifoliae using a pair of species-specific primers. The detection range was 103 - 107 copies/ml (DNA templates) and cfu/ml (cell culture templates). This new method exhibited good linearity and repeatability and was validated by absolute quantification of E. pyrifoliae DNA copies from samples of artificially inoculated immature pear fruits. Here, we present the first study of ddPCR assay for the detection and quantification of E. pyrifoliae. This method has potential applications in epidemiology and for the early prediction of black shoot blight outbreaks.

XX/XY Chimerism in Internal Genitalia of a Virilized Heifer

Five DSD heifers underwent genetic analysis in the present study. We cytogenetically analyzed in vitro cultured leukocytes and searched for SRY, AMELX/AMELY and ZFX/ZFY genes in leukocytes and hair follicles, finding that four of the studied heifers were freemartins (XX/XY leukocyte chimerism). The fifth case had an underdeveloped vulva localized ventrally and cranially to the mammary gland, a normal female sex chromosome complement (60,XX) in the leukocytes, and a lack of Y-chromosome-derived genes in the leukocytes and hair follicles. Postmortem anatomical examination of this heifer revealed the presence of normal ovaries with follicles, uterus, and oviducts, but molecular detection of the SRY, ZFX, ZFY,AMELX, and AMELY genes in these organs indicated the presence of a cell line carrying the Y chromosome. Further analysis of twelve microsatellite markers revealed the presence of additional variants at six loci in DNA samples derived from the reproductive organs; XX/XY chimerism was thus suspected in these samples. On the basis of the detection of AMELY (Y-linked) versus AMELX (X-linked) and SOX9 (autosomal) versus AMELY genes by droplet digital PCR (ddPCR), the Y/X and Y/autosome ratios were evaluated; they indicated the presence of XX and XY cell lines in the reproductive tissues. Our study showed that XX/XY chimerism can be present in the internal reproductive organs of the virilized heifers with a normal female set of sex chromosomes (60,XX) and a lack of Y-chromosome-derived genes in the leukocytes. The etiology of this phenomenon remains unknown.

Detection and Quantification of Adulterated Beef and Mutton Products by Multiplex Droplet Digital PCR

In order to seek high profit, businesses mix beef and mutton with cheap meat, such as duck, pork, and chicken. Five pairs of primers were designed for quintuple droplet digital PCR (qddPCR) of specific genomic regions from five selected species and specificity and amplification efficiency were determined. The mixed DNA template with an equal copy number was used for detecting the accuracy and limit of multiplex PCR. The results showed that the primers and probes of the five selected species had good specificity with the minimum number of detection copies: 0.15 copies/µL beef (Bos taurus), 0.28 copies/μL duck (Anas platyrhynchos), 0.37 copies/μL pork (Sus scrofa), 0.39 copies/μL chicken (Gallus gallus), and 0.41 copies/μL mutton (Ovis aries), respectively. The five sets of primers and probes could quickly judge whether the specified meat components existed in the food commodities.

Quantitative monitoring of experimental and human leishmaniasis employing amastigote-specific genes

The gold standard for diagnosis of leishmaniasis is the microscopic detection of amastigotes/Leishman Donovan (LD) bodies, but its moderate sensitivity necessitates the development of molecular approaches. This study aimed to quantify in experimental animal models and human leishmaniasis the expression of amastigote-specific virulence genes, A2 and amastin by droplet digital polymerase chain reaction (ddPCR). Total RNA was isolated from L. donovani-infected hamsters or murine peritoneal macrophages and lesional biopsies from patients with post kala-azar dermal leishmaniasis (PKDL). Following cDNA conversion, EvaGreen-based ddPCR was performed using specific primers for A2 or amastin and parasite load expressed in copies per μL. Assay was optimized and the specificity of amastigote-specific A2 and amastin was confirmed. In hepatic and splenic tissues of L. donovani-infected hamsters and peritoneal macrophages, ddPCR demonstrated a greater abundance of A2 than amastin. Treatment of L. donovani-infected peritoneal macrophages with conventional anti-leishmanials, miltefosine and amphotericin B translated into a dose-dependent reduction in copies per μL of A2 and amastin, and the extrapolated IC50 was comparable with results obtained by counting LD bodies in Giemsa-stained macrophages. Similarly, in dermal biopsies of patients with PKDL, A2 and amastin were detected. Overall, monitoring of A2 by ddPCR can be an objective measure of parasite burden and potentially adaptable into a high throughput approach necessary for drug development and monitoring disease progression when the causative species is L. donovani.

A dPCR Method for Quantitative Authentication of Wild Lingonberry (Vaccinium vitis-idaea) versus Cultivated American Cranberry (V. macrocarpon)

Berries of the genus Vaccinium are highly valued health-beneficial superfoods, which are commonly subjected to adulteration and mixed with each other, or with other common berry species. A quantitative DNA-based method utilizing a chip-based digital polymerase chain reaction (dPCR) technique was developed for identifying and quantifying wild lingonberry (V. vitis-idaea) and cultivated American cranberry (V. macrocarpon). The dPCR method with species-specific primers for mini-barcoding was designed based on the indel regions found in the trnI-CAU-trnL-CAA locus in the chloroplast genome. The designed primers were able to amplify only target species, enabling to distinguish the two closely related species with good sensitivity. Our results illustrated the ability of the method to identify lingonberry and American cranberry DNA using PCR without the need for probes or further sequencing. The dPCR method could also quantify the DNA copy number in mixed samples. Based on this study, the method provides a basis for a simple, fast, and sensitive quantitative authentication analysis of lingonberry and American cranberry by dPCR. Moreover, it can also provide a platform for authentication analyses of other plant species as well by utilizing the indel regions of chloroplast genomes.

Establishment of a fecal DNA quantification technique for rare and cryptic diet constituents in small mammals

DNA-based approaches have highly improved the applicability of dietary studies aimed at investigating ecological processes. These studies have provided direct insights into, otherwise difficult to measure, interactions between species and trophic levels, food web structure and ecosystem functioning. However, despite these advances, DNA-based methods have been struggling to accurately quantify the whole breadth of diet constituents because of methodological biases, such as amplification bias and digestive processes. This study is, to our knowledge, the first diet study that used droplet digital PCR to quantify diet constituents. We manipulated the diet of wild caught wood mice (Apodemus sylvaticus) by feeding them with a known amount of small vegetable seeds (onion and carrot) and quantified the DNA traces of these diet constituents in fecal samples. The sensitivity of the technique combined with the control on the experimental design allowed mitigation of methodological bias. We were able to accurately determine DNA concentrations of small vegetable seeds in the diet of wood mice. Quantification of target DNA demonstrated significant differences in DNA content when one vs. five seeds were consumed. These differences remained significant when the age, sex, and other diet constituents of the mice were altered. Different DNA markers, targeting different parts of the chloroplast, influenced onion DNA detectability. However, all onion and carrot markers showed higher DNA content for higher seed numbers. Overall, the sensitive DNA based approach developed in this study allows for minimally-invasive quantification of small diet constituents in feces, which would otherwise be undetectable with traditional methods.

Targeted genome-wide SNP genotyping in feral horses using non-invasive fecal swabs

The development of high-throughput sequencing has prompted a transition in wildlife genetics from using microsatellites toward sets of single nucleotide polymorphisms (SNPs). However, genotyping large numbers of targeted SNPs using non-invasive samples remains challenging due to relatively large DNA input requirements. Recently, target enrichment has emerged as a promising approach requiring little template DNA. We assessed the efficacy of Tecan Genomics’ Allegro Targeted Genotyping (ATG) for generating genome-wide SNP data in feral horses using DNA isolated from fecal swabs. Total and host-specific DNA were quantified for 989 samples collected as part of a long-term individual-based study of feral horses on Sable Island, Nova Scotia, Canada, using dsDNA fluorescence and a host-specific qPCR assay, respectively. Forty-eight samples representing 44 individuals containing at least 10 ng of host DNA (ATG’s recommended minimum input) were genotyped using a custom multiplex panel targeting 279 SNPs. Genotyping accuracy and consistency were assessed by contrasting ATG genotypes with those obtained from the same individuals with SNP microarrays, and from multiple samples from the same horse, respectively. 62% of swabs yielded the minimum recommended amount of host DNA for ATG. Ignoring samples that failed to amplify, ATG recovered an average of 88.8% targeted sites per sample, while genotype concordance between ATG and SNP microarrays was 98.5%. The repeatability of genotypes from the same individual approached unity with an average of 99.9%. This study demonstrates the suitability of ATG for genome-wide, non-invasive targeted SNP genotyping, and will facilitate further ecological and conservation genetics research in equids and related species.

Evaluation of Droplet Digital PCR for the Detection of Black Canker Disease in Tomato

Clavibacter michiganensis subsp. michiganensis, the cause of bacterial canker disease, is one of the most destructive pathogens in greenhouse and field tomato. The pathogen is now present in all main production areas of tomato and is widely distributed in the European and Mediterranean Plant Protection Organization region. The inspection and quarantine of the plant pathogens relies heavily on accurate detection tools. Primers and probes reported in previous studies do not distinguish the C. michiganensis subsp. michiganensis pathogen from other closely related subspecies of C. michiganensis, especially the nonpathogenic subspecies that were identified from tomato seeds recently. Here, we have developed a droplet digital PCR (ddPCR) method for the identification of this specific bacterium with primers/TaqMan probe set designed based on the pat-1 gene of C. michiganensis subsp. michiganensis. This new primers/probe set has been evaluated by real-time PCR (qPCR) and ddPCR. The detection results suggest that the ddPCR method established in this study was highly specific for the target strains. The result showed the positive amplification for all five C. michiganensis subsp. michiganensis strains, and no amplification was observed for the other 43 tested bacteria, including the closely related C. michiganensis strains. The detection threshold of ddPCR was 10.8 CFU/ml for both pure C. michiganensis subsp. michiganensis cell suspensions and infected tomato seed, which was 100-fold more sensitive than qPCR performed using the same primers and probe. The data obtained suggest that our established ddPCR could detect C. michiganensis subsp. michiganensis even with low bacterial load, which could facilitate both C. michiganensis subsp. michiganensis inspection for pathogen quarantine and the routine pathogen detection for disease control of black canker in tomato.

A quantitative detection of mung bean in chestnut paste using duplex digital PCR

Highly manufacturing process of chestnut paste leaves a considerable space for Economically Motivated Adulteration (EMA) with cheaper ingredients such as mung bean. In this paper a novel quantitative detection of mung bean in chestnut paste using duplex digital PCR was reported. Two sets of primers and probes were designed according to mung bean and chestnut specific genomic genes suitable for duplex droplet digital PCR (ddPCR) and duplex chip digital PCR (cdPCR) to set up a mass ratio quantitative detection method for mung bean, a common alternative plant-derived ingredient in chestnut paste products. The manufacturing process of chestnut paste products was considered to establish the linear relationship formula between mass ratio and gene copy number (CN) ratio of the two ingredients. The limits of quantification for gene CN concentrations (LOQ_copy) of mung bean and chestnut were both 6 copies/μL, at the same time a mass ratio of mung bean in chestnut paste range from 5% to 80% was able to be quantified accurately to provide technical support for the identification of fraudulent substitution or adventitious contamination.

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Establishment of quantitative analysis method on mung bean in chestnut paste.

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Duplex ddPCR and cdPCR to detect mung bean and chestnut simultaneously.

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Formulas to determine the mass ratio of relevant ingredients from copy numbers.

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Identification of 8 fraud chestnut pastes from 13 prepackaged samples.

Multiplexed analysis of small extracellular vesicle-derived mRNAs by droplet digital PCR and machine learning improves breast cancer diagnosis

Breast cancer has become the leading cause of global cancer incidence and a serious threat to women's health. Accurate diagnosis and early treatment are of great importance to prognosis. Although clinically used diagnostic approaches can be used for cancer screening, accurate diagnosis of breast cancer is still a critical unmet need. Here, we report a 4-plex droplet digital PCR technology for simultaneous detection of four small extracellular vesicle (sEV)-derived mRNAs (PGR, ESR1, ERBB2 and GAPDH) in combination with machine learning (ML) algorithms to improve breast cancer diagnosis. We evaluate the diagnsotic results with and without the assistance of the ML models. The results indicate that ML-assisted analysis exhibits higher diagnostic performance even using a single marker for breast cancer diagnosis, and demonstrate improved diagnostic performance under the best combination of biomarkers and suitable ML diagnostic model. Therefore, multiple sEV-derived mRNAs analysis coupled with ML not only provides the best combination of markers for breast cancer diagnosis, but also significantly improves the diagnostic efficiency of breast cancer.

Omics-Based Analytical Approaches for Assessing Chicken Species and Breeds in Food Authentication

Chicken is known to be the most common meat type involved in food mislabeling and adulteration. Establishing a method to authenticate chicken content precisely and identifying chicken breeds as declared in processed food is crucial for protecting consumers' rights. Categorizing the authentication method into their respective omics disciplines, such as genomics, transcriptomics, proteomics, lipidomics, metabolomics, and glycomics, and the implementation of bioinformatics or chemometrics in data analysis can assist the researcher in improving the currently available techniques. Designing a vast range of instruments and analytical methods at the molecular level is vital for overcoming the technical drawback in discriminating chicken from other species and even within its breed. This review aims to provide insight and highlight previous and current approaches suitable for countering different circumstances in chicken authentication.

Development of a two-level control system for the analysis of the composition of meat products

Because of the increased demand for processed meat, there is an urgent need to introduce specific identification methods. Strategies such as molecular genetics and the physical condition of meat are used to quickly explore multi-component products. However, a single methodology does not always unambiguously classify a product as counterfeit. In laboratory practice, as a rule, screening techniques are rarely used in the first stage, followed by arbitration. This work aimed to study individual methodologies using artificially falsified meat samples as examples and to identify their composition based on muscle tissue. For the experiments, the three most common types of raw meat were selected: pork, beef, and chicken. The calculation of the content of muscle tissue was carried out according to the BEFFE method. The study of muscle protein was carried out by ICA, ELISA, PCR, microstructural analysis, and mass spectrometric identification. In this connection, we proposed a multilevel control system for multicomponent meat products. Both classical methodologies, such as calculation by prescription bookmarks (BEFFE) and microstructural analysis, and approaches of highly sensitive methodologies, such as identification of muscle tissue by marker peptides (LC/MS-MRM) and semi-quantitative PCR analysis, were evaluated.

Competitiveness of Quantitative Polymerase Chain Reaction (qPCR) and Droplet Digital Polymerase Chain Reaction (ddPCR) Technologies, with a Particular Focus on Detection of Antibiotic Resistance Genes (ARGs)

With fast-growing polymerase chain reaction (PCR) technologies and various application methods, the technique has benefited science and medical fields. While having strengths and limitations on each technology, there are not many studies comparing the efficiency and specificity of PCR technologies. The objective of this review is to summarize a large amount of scattered information on PCR technologies focused on the two majorly used technologies: qPCR (quantitative polymerase chain reaction) and ddPCR (droplet-digital polymerase chain reaction). Here we analyze and compare the two methods for (1) efficiency, (2) range of detection and limitations under different disciplines and gene targets, (3) optimization, and (4) status on antibiotic resistance genes (ARGs) analysis. It has been identified that the range of detection and quantification limit varies depending on the PCR method and the type of sample. Careful optimization of target gene analysis is essential for building robust analysis for both qPCR and ddPCR. In our era where mutation of genes may lead to a pandemic of viral infectious disease or antibiotic resistance-induced health threats, this study hopes to set guidelines for meticulous detection, quantification, and analysis to help future prevention and protection of global health, the economy, and ecosystems.

Development and comparative evaluation of droplet digital PCR and quantitative PCR for the detection and quantification of Chlamydia psittaci

Chlamydia psittaci is a zoonotic pathogen mainly transmitted by psittacine birds and poultry. The low shedding rate of the pathogen in the apparently healthy birds and human clinical cases may result in false-negative results. In the present study, a droplet digital PCR (ddPCR) assay was developed and compared with optimized quantitative PCR (qPCR) for the detection of C. psittaci from the clinical samples. The ddPCR assay was found to be comparatively more sensitive than the qPCR, wherein the limit of detection (LOD) of ddPCR was upto 2.4 copies of the DNA template, whereas, the qPCR could detect upto 38 copies of the DNA template in the reaction mixture. Overall, the developed ddPCR assay was found to be robust, specific, and could reliably quantify up to 17.8 copies of the DNA template. Finally, the applicability of the developed ddPCR assay was tested by screening the field samples (n = 124), comprising lung tissues from dead poultry and feral birds; pooled faecal samples from the free-living birds, commercial and backyard poultry farms; pharyngeal and cloacal swabs collected from the duck farms. Of these, a total of seven samples were found to be positive by the ddPCR, whereas, three samples could be detected as positive using the qPCR. The developed ddPCR could serve as a reliable screening tool, particularly in those clinical samples wherein the shedding of C. psittaci is substantially very low.

Detection of Campylobacter jejuni from Fresh Produce: Comparison of Culture- and PCR-based Techniques, and Metagenomic Approach for Analyses of the Microbiome before and after Enrichment

ABSTRACT

In this study, we compared the efficiency of culture-based methods with or without membrane filtration, real-time PCR, and digital droplet PCR (ddPCR) for the detection of Campylobacter in fresh produce. Alfalfa sprouts, clover sprouts, coleslaw, and lettuce salad spiked with Campylobacter jejuni were enriched in Bolton broth for 48 h, and enrichment cultures were either directly inoculated onto modified charcoal-cefoperazone-deoxycholate agar or applied on membrane filters placed on the surface of plating media. In parallel, 2-mL Bolton broth cultures were taken to extract DNA for real-time PCR and ddPCR assays and bacterial community analysis. A developed primer set for ddPCR and real-time PCR was evaluated for its inclusivity and exclusivity using pure culture of C. jejuni and non-C. jejuni strains, respectively. In pure culture, the primer set reacted only with C. jejuni strains and showed negative reaction to non-C. jejuni strains. There was no significant difference (P > 0.05) in the detection efficiency of positive Campylobacter isolates from coleslaw and lettuce salad using four detection methods. However, for sprout samples, the detection efficiency of the culture method was significantly (P < 0.05) lower than those of the two PCR assays and the filtration method. The analysis also revealed the presence of Pseudomonas and Acinetobacter as the most prevalent competing microbiota in enriched culture and only Acinetobacter on agar plates in the selective culture step.

HIGHLIGHTS

Simultaneous quantitation of 3ADON and 15ADON chemotypes of DON-producing Fusarium species in Chinese wheat based on duplex droplet digital PCR assay

Pathogens within Fusarium species are the primary agents of Fusarium head blight (FHB) of wheat, which bring about yield reduction and deoxynivalenol (DON) contamination and are of great concern worldwide. DON-producing Fusarium species can be classified into 3-acetyldeoxynivalenol (3ADON) and 15-acetyldeoxynivalenol (15ADON) chemotypes according to the trichothecene metabolites they produce. The detection of these two chemotypes of pathogens is paramount to the successful implementation of disease management strategies and pathogen-related DON forecasting models. In this study, a duplex droplet digital PCR (duplex ddPCR) assay was developed that allowed for the simultaneous quantitation of 3ADON and 15ADON chemotypes of DON-producing Fusarium species. The assay specificity was tested against 30 isolates of target Fusarium species and several non-target Fusarium species that are frequently isolated from wheat in China. Analyzing 90 wheat samples collected from the North China plain and Yangtze River plain demonstrated that the duplex ddPCR assay coupled with magnetic bead-based DNA extraction was competent for investigating composition of 3ADON and 15ADON chemotypes in Chinese wheat. This assay will be useful for monitoring the epidemic and geographic distribution of 3ADON and 15ADON chemotypes of FHB pathogens, which will help with the disease control and DON management.

Application of Next-Generation Sequencing Technology Based on Single Gene Locus in Species Identification of Mixed Meat Products

Polymerase chain reaction (PCR) detection is a commonly used method for species identification of meat products. However, this method is not suitable for the analysis of meat products containing multiple mixtures. This study aimed to test whether next-generation sequencing (NGS) technology could be used as a method for the certification of mixed meat products. In this study, five kinds of common meat (pigs, cattle, sheep, chickens, and ducks) were mixed as samples with different proportions. The primers designed from mitochondrial 16S rRNA and nuclear genome gene (growth hormone receptor, GHR), respectively, were used to detect these meats. The sequencing results of NGS were analyzed using a self-designed bioinformatics program. The fragments with similar sequences were classified and compared with the database to determine their species. The results showed that all five kinds of meat components could be correctly identified using these two primers. The meat composition could be detected as low as 0.5% in the mixed samples using the NGS technology targeting GHR gene fragments, which was superior to those targeting mitochondrial 16S rRNA. However, the quantitative detection of species in the mixture was not likely to be quite accurate due to the amplification bias of PCR amplification. These results showed that the NGS technology could be applied to identify meat species in mixtures.

Development of a Duck Genomic Reference Material by Digital PCR Platforms for the Detection of Meat Adulteration

Low-cost meat, such as duck, is frequently used to adulterate more expensive foods like lamb or beef in many countries. However, the lack of DNA-based reference materials has limited the quality control and detection of adulterants. Here, we report the development and validation of duck genomic DNA certified reference materials (CRMs) through the detection of the duck interleukin 2 (IL2) gene by digital PCR (dPCR) for the identification of duck meat in food products. The certified value of IL2 in CRMs was 5.78 ± 0.51 × 10³ copies/μL with extended uncertainty (coverage factor k = 2) based on IL2 quantification by eight independent collaborating laboratories. Quantification of the mitochondrial gene cytb revealed a concentration of 2.0 × 10⁶ copies/μL, as an information value. The CRMs were also used to determine the limit of detection (LOD) for six commercial testing kits, which confirmed that these kits meet or exceed their claimed sensitivity and are reliable for duck detection.

Droplet digital polymerase chain reaction assay for identifying and quantifying pork products

Halal products are growing in consumer markets worldwide, and pork meat is classified as non-halal. Manufacturers of processed foods and products must ensure that their products follow Islamic dietary law because pork is prohibited for Muslims. Droplet digital polymerase chain reaction (PCR) (ddPCR) is a novel method for identifying pig species and quantifying pork products. This experiment aimed to investigate pork species and establish the proportion of pork in meat products using the mitochondrial cytochrome b gene (CYTB). The study found that the correlation coefficient between the meat weight and DNA concentration of pork was 0.997, and the correlation coefficient between the DNA concentration and the target DNA copy number of pork was 0.998. The accuracy of the ddPCR assay was verified using a sample of a known proportion of pork, and it was revealed that this method is highly precise in quantifying pork products. Nine products contained an undeclared meat proportion (90%). The limit of detection for pork was 0.0001 ng. The analysis indicated that the ddPCR assay has high accuracy and sensitivity for quantifying pork products. Therefore, the predictive model can be used in routine laboratories for quality assurance of halal food products.

Meat species identification accuracy improvement using sample set portioning based on joint x-y distance and laser-induced breakdown spectroscopy

Laser-induced breakdown spectroscopy (LIBS) was suitable for the identification of meat species due to fast and less sample preparation. However, the problem of low accuracy rate of the recognition model caused by improper selection of training set samples by random split has severely restricted the development of LIBS in meat detection. Sample set portioning based on the joint x-y distance (SPXY) method was applied for dividing the meat spectra into a training set and a test set. Then, the five kinds of meat samples (shrimp, chicken, beef, scallop, and pig liver) were classified by the support vector machine (SVM). With the random split method, Kennard-Stone method, and SPXY method, the recognition accuracies of the SVM model were 90.44%, 91.95%, and 94.35%, respectively. The multidimensional scaling method was used to visualize the results of the sample split for the interpretation of the classification. The results showed that the identification performance of the SPXY method combined with the SVM model was best, and the accuracy rates of shrimp, chicken, beef, scallop, and pig liver were 100.00%, 100.00%, 100.00%, 78.57%, and 92.00%, respectively. Moreover, to verify the broad adaptability of the SPXY method, the linear discriminant analysis model, the K-nearest neighbor model, and the ensemble learning model were applied as the meat species identification model. The results demonstrated that the accuracy rate of the classification model can be improved with the SPXY method. In light of the findings, the proposed sample portioning method can improve the accuracy rate of the recognition model using LIBS.

Identification and semi-quantification of Atlantic salmon in processed and mixed seafood products using Droplet Digital PCR (ddPCR)

Fishery products are often subject to substitution fraud, which is hard to trace due to a lack of morphologic traits when processed, gutted, or decapitated. Traditional molecular methods (DNA barcoding) fail to identify products containing multiple species and cannot estimate original weight percentages. As a proof of concept, an Atlantic salmon (Salmo salar) specific ddPCR assay was designed to authenticate mixed food products. The method proved to be specific and able to accurately quantify S. salar when using DNA extracts, even in the presence of DNA from closely related salmon species. The ddPCR estimates correlated well with the percentage of S. salar in artificially assembled tissue mixtures. The effect of common salmon processing techniques (freezing, smoking, poaching with a "Bellevue" recipe and marinating with a 'Gravad lax' recipe) on the ddPCR output was investigated and freezing and marinating appeared to lower the copies detected by the ddPCR. Finally, the assay was applied to 46 retail products containing Atlantic or Pacific salmon, and no indications of substitution fraud were detected. The method allows for a semi-quantitative evaluation of the S. salar content in processed food products and can rapidly screen Atlantic salmon products and flag potentially tampered samples for further investigation.

Droplet Digital PCR (ddPCR) Analysis for the Detection and Quantification of Cow DNA in Buffalo Mozzarella Cheese

Simple Summary

Buffalo mozzarella cheese, sold as a Protected Designation of Origin (PDO) product, is made exclusively from Mediterranean buffalo (Bubalus bubalis) milk. To maximize their profits and overcome seasonal shortages of buffalo milk, some producers have started to produce “PDO” buffalo mozzarella cheese by adulterating buffalo milk with milk from different species. such as bovine, thus defrauding consumers. This practice has led the Italian government to reinforce controls on food mislabeling and fraud through traceability mechanisms. The aim of this work is the development of a molecular assay—droplet digital Polymerase Chain Reaction technique (ddPCR)—able to detect the DNA of cow and/or buffalo milk in PDO buffalo mozzarella cheese, thus revealing fraud. The results have highlighted that, thanks to its high precision and sensitivity, the ddPCR could represent an efficacious means of supporting the official controls aimed at combating the adulteration of buffalo mozzarella cheese with bovine milk.

Abstract

Buffalo mozzarella cheese is one of the most appreciated traditional Italian products and it is certified as a Protected Designation of Origin (PDO) product under the European Commission Regulation No. 1151/2012. It is obtained exclusively from buffalo milk. If made from cow milk, or a mixture of buffalo and cow milk, buffalo mozzarella cheese does not qualify as a PDO product. In order to maximize their profits, some producers market buffalo mozzarella that also contains cow milk as a PDO product, thus defrauding consumers. New methods for revealing this fraud are therefore needed. One such method is the droplet digital Polymerase Chain Reaction (ddPCR). Thanks to its high precision and sensitivity, the ddPCR could prove an efficacious means for detecting the presence of cow milk in buffalo mozzarella cheese that is marketed as a PDO product. ddPCR has proved able to detect the DNA of cow and/or buffalo milk in 33 buffalo mozzarella cheeses labelled as PDO products, and experimental evidence could support its application in routine analyses.

An effective analytical droplet digital PCR approach for identification and quantification of fur-bearing animal meat in raw and processed food

Available nuclear gene sequences for meat detection are still rare and little applicability in the investigation of new types of meat adulteration such as fox, mink and raccoon dog was performed. In the present work, we developed a reliable qualitative and quantitative detection method for fur-bearing animal meat based on droplet digital PCR (ddPCR). Three sets of primers and probes targeted nuclear genes for fox, mink and raccoon dog were designed for ddPCR system; In addition, turkey was selected as internal reference to transform the copy numbers to the fraction of target species. Results indicated that the dynamic ranges of three fur-bearing animals were all from 1% to 90%; the limit of detection (LOD) and limit of quantification (LOQ) for three fur-bearing animals were same, with LOD 0.1% (w/w) and LOQ 1% (w/w). Moreover, we confirmed that different additives had no effect on quantification accuracy in the ddPCR assay.

The equine graying with age mutation of the STX17 gene: A copy number study using droplet digital PCR reveals a new pattern

The equine graying with age causative mutation in the syntaxin-17 gene (STX17) has been known for over a decade, but proper genotyping of this variant remains challenging due to its molecular character (4.6-kb tandem duplication). Precise information on gray mutation status is important for horse breeders and veterinarians, since gray homozygous horses are more prone to developing aggressive melanoma tumors than heterozygotes. Since recent studies have confirmed that droplet digital PCR is a valuable technique for copy number analysis, we decided to investigate whether this method can be used for accurate genotyping of the horse graying-related variant and established the copy numbers of the 4.6-kb fragment in the available cohort (n = 75) of gray and nongray horses of various breeds. Surprisingly, we found that our STX17 genotype results varied from what has been previously published, suggesting that gray phenotype is associated with the presence of six (GG) or four (Gg) copies of studied region. All the examined nongray horses (gg) have the two copies of these fragments. This new pattern and its inheritance were also confirmed by an analysis conducted for the Polish Warmblood horse family. We noted no further copy number variation in the entire tested samples set. Our study confirmed the usefulness and accuracy of droplet digital PCR for genotyping STX17 gene variant. Further studies on a broader range of materials are needed to fully understand the origin and molecular structure of the graying causative mutation in the horse STX17.

Development of Wild Boar Species-Specific DNA Markers for a Potential Quality Control and Traceability Method in Meat Products

In the food supply chain, quality control has a very important role in maintaining customer confidence. In the EU, food safety aspects are strictly regulated; however, composition requirements and standard control methods are generally undefined. The rapidly increasing wild boar population has a growing market share in venison or game meat production. Several methods have been described for species identification and control of composition in food products, but only some of these are suitable for routine measurements. The aim of our research was to design a rapid, reliable and simple PCR insertion/deletion (InDel)-based genetic tool suitable for species identification in food quality control laboratories. In total, 59 different swine (Sus scrofa) whole genomes were tested with bioinformatic tools to identify wild boar-specific insertions or deletions. Three independent InDels were suitable for marker development, multiplex PCR amplification and separation in agarose gel. Altogether, 209 samples of wild boar and ten other domestic pig breeds were taken for DNA extraction and validation of the three multiplexed InDel markers. Statistical analysis showed a very high combined predictive value (0.996), indicating the capability of the newly developed markers to detect wild boars with a probability over 99%. Breed assignment tests confirm that the InDel markers developed are suitable for rapid, sensitive and reliable identification of the wild boar meat content of food products. The use of the reported method in food quality control can mean a simple and cost-effective way to maintain consumer confidence and to support the competitiveness of fair producers.