Quantification of animal species using quantitative real-time PCR (qPCR) to verify fraud in meat products
DOI:
https://doi.org/10.33448/rsd-v12i1.38972Keywords:
Real-time qPCR; Validation; Beef and chicken meat; Myostatin.Abstract
Food labeling is fundamental to avoid eating a specific kind of meat for religious and cultural reasons, but mainly to avoid fraud with the purpose of obtaining financial advantages. The real-time qPCR method is commonly used to quantify DNA in a given sample by relative quantification (concentration of specific target DNA over concentration of endogenous DNA). In studies that use qPCR to quantify contaminating species, normalization is performed using a single-copy reference gene, such as myostatin, present in most mammals and birds. This study aimed to standardize the real-time qPCR technique to obtain relative quantitative results in rigged beef. For method standardization, the limit of detection (LD) resulted in a Cq fluorescence signal of 36.80 cycles in at least 9 out of 10 repetitions (90%) at a concentration of 0.008% in horse and Cq of 36.60 cycles in at least 7 of 10 repetitions (70%) at a concentration of 0.0005% in chicken. The lowest concentration at which the relative standard deviation (RSD) was ≤25% was between 0.125% and 0.031% for both horse and chicken. Even using standard quantitation curves containing 50% meat blends or 100% pure target meat, curve slope, amplification efficiency, and linear correlation were within recommended acceptance criteria. The test is sensitive and an alternative in the routine inspection of products for both human and animal consumption.
References
Alikord, M., Momtaz, H., Kadivar, M., & Rad, A. H. (2018). Species identification and animal authentication in meat products: a review. Journal of Food Measurement and Characterization, 12(1), 145-155.
Ballin, N. Z. (2010). Authentication of meat and meat products. Meat science, 86(3), 577-587.
Bariani, J. L. (2021). Food Satefty Brazil. Escândalo da carne de cavalo: Brasil dez anos atrasado. Website Food Satefty Brazil. https://foodsafetybrazil.org/escandalo-da-carne-de-cavalo-brasil-dez-anos-atrasado/jose-luiz-bariani/2021/.
Brasil. (2020). Instrução Normativa - IN N° 75, de 8 de outubro de 2020. Estabelece os requisitos técnicos para declaração da rotulagem nutricional nos alimentos embalados. Ministério da Saúde. Agência Nacional de Vigilância Sanitária (Anvisa). http://antigo.anvisa.gov.br/documents/10181/3882585/IN_75_2020_COMP.pdf/e89784b5-ed18-4bdd-a4d4-139724a56d4d.
Chen, X., Lu, L., Xiong, X., Xiong, X., & Liu, Y. (2020). Development of a real-time PCR assay for the identification and quantification of bovine ingredient in processed meat products. Scientific reports, 10(1), 1-10.
Dolch, K., Judas, M., Schwägele, F., & Brüggemann, D. A. (2019). Development and validation of two triplex real-time PCR systems for the simultaneous detection of six cereal species in processed meat products. Food Control, 101, 180-188.
Druml, B., Mayer, W., Cichna-Markl, M., & Hochegger, R. (2015). Development and validation of a TaqMan real-time PCR assay for the identification and quantification of roe deer (Capreolus capreolus) in food to detect food adulteration. Food Chemistry, 178, 319-326.
Druml, B., Kaltenbrunner, M., Hochegger, R., & Cichna-Markl, M. (2016). A novel reference real-time PCR assay for the relative quantification of (game) meat species in raw and heat-processed food. Food Control, 70, 392-400.
Drummond, M. G., Brasil, B. S. A. F., Dalsecco, L. S., Brasil, R. S. A. F., Teixeira, L. V., & Oliveira, D. A. A. (2013). A versatile real-time PCR method to quantify bovine contamination in buffalo products. Food Control, 29(1), 131-137.
ENGL, European Network of GMO Laboratories. (2015). Definition of Minimum Performance Requirements for Analytical Methods of GMO Testing. JRC Technical Report. chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://gmo-crl.jrc.ec.europa.eu/doc/MPR%20Report%20Application%2020_10_2015.pdf.
Furutani, S., Hagihara, Y., & Nagai, H. (2017). On-site identification of meat species in processed foods by a rapid real-time polymerase chain reaction system. Meat science, 131, 56-59.
Giglioti, R., Polli, H., Azevedo, B. T., Katiki, L. M., & Vercesi Filho, A. E. (2022). Detection and quantification of adulteration in milk and dairy products: A novel and sensitive qPCR-based method. Food Chemistry: Molecular Sciences, 4, 100074.
Hou, B., Meng, X., Zhang, L., Guo, J., Li, S., & Jin, H. (2015). Development of a sensitive and specific multiplex PCR method for the simultaneous detection of chicken, duck and goose DNA in meat products. Meat science, 101, 90-94.
Ifs food. (2020). Norma para avaliar a conformidade de produtos e processos em relação à segurança de alimentos e qualidade. https://www.ifs-certification.com/images/standards/ifs_food7/documents/standards/IFS_Food7_pt.pdf.
Inmetro. (2016). Coordenação Geral de Acreditação. Orientação sobre Validação de Métodos Analíticos. DOQ-CGCRE-008. chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/http://www.inmetro.gov.br/Sidoq/Arquivos/Cgcre/DOQ/DOQ-Cgcre-8_05.pdf.
ISO. (2020). Organization for Standardization/Technical Specification. ISO/TS 20224-1. Molecular biomarker analysis – Detection of animal-derived materials in foodstuffs and feedstuffs by real-time PCR – Part 1: Bovine DNA detection method. 1st.Edition.
ISO. (2020). Organization for Standardization/Technical Specification. ISO/TS 20224-2. Molecular biomarker analysis – Detection of animal-derived materials in foodstuffs and feedstuffs by real-time PCR – Part 2: Ovine DNA detection method. 1st.Edition.
ISO. (2020). Organization for Standardization/Technical Specification. ISO/TS 20224-3. Molecular biomarker analysis – Detection of animal-derived materials in foodstuffs and feedstuffs by real-time PCR – Part 3: Porcine DNA detection method. 1st.Edition.
ISO. (2020). Organization for Standardization/Technical Specification. ISO/TS 20224-4. Molecular biomarker analysis – Detection of animal-derived materials in foodstuffs and feedstuffs by real-time PCR – Part 4: Chicken DNA detection method. 1st.Edition.
ISO. (2020). Organization for Standardization/Technical Specification. ISO/TS 20224-6. Molecular biomarker analysis – Detection of animal-derived materials in foodstuffs and feedstuffs by real-time PCR – Part 6: Horse DNA detection method. 1st.Edition.
Iwobi, A., Sebah, D., Kraemer, I., Losher, C., Fischer, G., Busch, U., & Huber, I. (2015). A multiplex real-time PCR method for the quantification of beef and pork fractions in minced meat. Food chemistry, 169, 305-313.
Kang, T. S., & Tanaka, T. (2018). Comparison of quantitative methods based on SYBR Green real-time qPCR to estimate pork meat adulteration in processed beef products. Food chemistry, 269, 549-558.
Köppel, R., van Velsen, F., Ganeshan, A., Pietsch, K., Weber, S., Graf, C., & Licina, A. (2020). Multiplex real-time PCR for the detection and quantification of DNA from chamois, roe, deer, pork and beef. European Food Research and Technology, 246(5), 1007-1015.
Laube, I., Zagon, J., & Broll, H. (2007). Quantitative determination of commercially relevant species in foods by real‐time PCR. International journal of food science & technology, 42(3), 336-341.
Li, J., Li, J., Liu, R., Wei, Y., & Wang, S. (2021a). Identification of eleven meat species in foodstuff by a hexaplex real-time PCR with melting curve analysis. Food Control, 121, 107599.
Li, T., Wang, J., Wang, Z., Qiao, L., Liu, R., Li, S., & Chen, A. (2021b). Quantitative determination of mutton adulteration with single-copy nuclear genes by real-time PCR. Food Chemistry, 344, 128622.
Lubis, H., Salihah, N. T., Hossain, M. M., & Ahmed, M. U. (2017). Development of fast and sensitive real-time qPCR assay based on a novel probe for detection of porcine DNA in food sample. LWT, 84, 686-692.
Marchetti, P., Mottola, A., Tantillo, G., Castrica, M., & Di Pinto, A. (2021). Detection of undeclared presence of bovine milk in buffalo yogurt. Journal of Dairy Science, 104(4), 4056-4061.
Oliveira, A. C. D. S., Ferreira, B. C. A., Cardoso, G. V. F., Silva, C. L., da Silva, A. S., da Silva, F., & de Moraes, C. M. (2015). Avaliação da técnica PCR multiplex para detecção de fraude por adição de carne bubalina em carne moída bovina. Revista do Instituto Adolfo Lutz, 74(4), 371-379.
QIAGEN. (2020). DNeasy mericon Food Handbook. https://www.qiagen.com/gb/resources/resourcedetail?id=bd9cc2a8-aa71-4cb5-b6f7-97b3d7fc306d&lang=en.
QIAGEN. (2013). QuantiNova™ Probe PCR Handbook. https://www.qiagen.com/us/resources/resourcedetail?id=5167d782-9fef-4202-bc79-95f358be7d8c&lang=en.
Lazaro, D. R. (2013). Real-Time PCR in Food Science: Current Technology and Applications. Caister Academic Press.
Sarlak, Z., Shojaee-Aliabadi, S., Rezvani, N., Hosseini, H., Rouhi, M., & Dastafkan, Z. (2022). Development and validation of TaqMan real-time PCR assays for quantification of chicken adulteration in hamburgers. Journal of Food Composition and Analysis, 106, 104302.
Sincabima. Fraude alimentar. Uma realidade no setor industrial. https://sincabima.org.br/2019/03/18/fraude-alimentar-uma-realidade-no-setor-industrial/.
Soares, S., Amaral, J. S., Oliveira, M. B. P., & Mafra, I. (2013). A SYBR Green real-time PCR assay to detect and quantify pork meat in processed poultry meat products. Meat Science, 94(1), 115-120.
Thanakiatkrai, P., & Kitpipit, T. (2017). Meat species identification by two direct-triplex real-time PCR assays using low resolution melting. Food chemistry, 233, 144-150.
Visciano, P., & Schirone, M. (2021). Food frauds: Global incidents and misleading situations. Trends in Food Science & Technology, 114, 424-442.
Xu, R., Wei, S., Zhou, G., Ren, J., Liu, Z., Tang, S., & Wu, X. (2018). Multiplex TaqMan locked nucleic acid real-time PCR for the differential identification of various meat and meat products. Meat science, 137, 41-46.
Zhang, C. (2013). Semi-nested multiplex PCR enhanced method sensitivity of species detection in further-processed meats. Food Control, 31(2), 326-330.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Hans Fröder; Eléia Righi
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
1) Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
2) Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
3) Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.