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Use of DNA technologies for the examination of foodstuff

An integral component of the management system in the field of food safety is the examination of food products, which is based mostly on physical, chemical, physico-chemical and biochemical methods of research. Progress in the mastery of DNA diagnostic methods has become an incentive for the development and introduction into laboratory practice of highly sensitive methods for assessing the safety and quality of foodstuff, based on the polymerase chain reaction (PCR) method. In recent decades, the demand for molecular tools for food examination, authentication and traceability has increased significantly. This is due to the fact that legislation in the food sector is becoming increasingly strict, and market strategies are aimed at evaluating the food chain "from field to table" and ensuring that consumer choices match their expectations. An overview of proven and widely tested molecular approaches for the examination of food products is presented: PCR-RFLP method, RAPD-PCR, SSR-PCR, RTPCR. The potential and prospects of the latest technologies, such as SNP - single nucleotide polymorphisms, isothermal amplification, digital PCR, Whole-Genome Sequencing (WGS), DNA metabarcoding, are also described. The specified methods are characterized by high productivity, speed and scaling, enabling the study of biological systems at a new qualitative level. Examples of successful use of the specified methods for examination of foodstuff of plant and animal origin, their authentication and traceability are given. A broad panel of molecular methods is a powerful tool to protect both producers and consumers, providing consumers with freedom of choice and increasing transparency in food production systems, enabling honest producers to properly promote their products.

Key words: DNA-technologies, polymerase chain reaction, food safety, foodstuff examination.

 

DYMAN T.


DYMAN N.


  1. Arslan, A., Ilhak, I.O., Calicioglu, M., Karahan, M. (2005). Identification of meats using random amplified polymorphic DNA (RAPD) technique. Journal of Muscle Foods, 16 (1), pp. 37–45 DOI:10.1111/j.1745-4573.2004.07504.x
  2. Beck, K. L., Haiminen, N., Chambliss, D., et al. (2021). Monitoring the microbiome for food safety and quality using deep shotgun sequencing. NPJ Sci Food. 5 (3). DOI:10.1038/s41538-020-00083-y.
  3. Beltramo, C., Cerutti, F., Brusa, F., Mogliotti, P., et al. (2021). Exploring the botanical composition of polyfloral and monofloral honeys through DNA metabarcoding. Food Control, 128. DOI:10.1016/j. foodcont.2021.108175
  4. Belyh, І. А., Kleschev, N. F., Grek, А. М., Sakun, А. V. (2012). Analysis of methods of indication of microorganisms and products of their metabolism. Modern problems of toxicology, 3‒4, pp. 70‒80 (in Ukrainian)..
  5. Ben Ayed, R., Rebai, A. (2019). Tunisian table olive oil traceability and quality using SNP genotyping and bioinformatics tools. BioMed Res. Int. DOI:10.1155/2019/8291341.
  6. Bleve, G, Rizzotti, L, Dellaglio, F, Torriani, S. (2003). Development of reverse transcription (RT)-PCR and real-time RT-PCR assays for rapid detection and quantification of viable yeasts and molds contaminating yogurts and pasteurized food products. Appl Environ Microbiol, 69(7), pp. 4116‒4122. DOI:10.1128/AEM.69.7.4116-4122.2003.
  7. Boccacci, P., Chitarra, W., Schneider, A., Rolle, L., Gambino, G. (2020). Single-nucleotide polymorphism (SNP) genotyping assays for the varietal authentication of ‘Nebbiolo’ musts and wines. Food Chem., 312. DOI:10.1016/j.foodchem.2019.126100.
  8. Bustin, S. A., Nolan, T. (2004). Pitfalls of quantitative real-time reverse-transcription polymerase chain reaction. J Biomol Tech., 15 (3), pp. 155‒166.
  9. Chedid, E., Rizou, M., Kalaitzis, P. (2020). Application of high resolution melting combined with DNA-based markers for quantitative analysis of olive oil authenticity and adulteration. Food Chemistry, 6. DOI:10.1016/j.fochx.2020.100082.
  10. Cibecchini, G., Cecere, P., Tumino, G., Morcia, C., Ghizzoni, R., Carnevali, P., Terzi, V., Pompa, P.P. (2020). A fast, naked-eye assay for varietal traceability in the durum wheat production chain. Foods, 9 (11). DOI:10.3390/foods9111691.
  11. di Rienzo, V., Fanelli, V., Miazzi, M. M., Savino, V., et al. (2017). A reliable analytical procedure to discover table grape DNA adulteration in industrial wines and musts. Acta Hortic. DOI:10.17660/ ActaHortic.2017.1188.49.
  12. Du, M., Li, J., Liu, Q., Wang, Y., Chen, E., Kang, F., Tu, C. (2021). Rapid detection of trace Salmonella in milk using an effective pretreatment combined with droplet digital polymerase chain reaction. Microbiol Res., 251. DOI:10.1016/j.micres.2021.126838.
  13. Fanelli, V., Mascio, I., Miazzi, M. M., Savoia, M. A., et al. (2021). Molecular Approaches to AgriFood Traceability and Authentication: An Updated Review. Foods, 10 (7). DOI:10.3390/foods10071644.
  14. Fang, W., Meinhardt, L. W., Mischke, S., Bellato, C. M., et al. (2014). Accurate determination of genetic identity for a single cacao bean, using molecular markers with a nanofluidic system, ensures cocoa authentication. J. Agric. Food Chem., 62. DOI:10.1021/ jf404402v. Epub 2013Dec 31.
  15. Fang, W. P., Meinhardt, L. W., Tan, H.W., Zhou, L., et al. (2014). Varietal identification of tea (Camellia sinensis) using nanofluidic array of single nucleotide polymorphism (SNP) markers. Hortic. Res., 1. DOI:10.1038/hortres.2014.35.
  16. Gaidey, O. S., Garkavenko, Т. О., Pischanskii, O. V. (2018). Food allergens. Relevance and problems in Ukraine. Veterinary biotechnology, 32 (1), pp. 453– 458 (in Ukrainian)..
  17. Galimberti, A., Casiraghi, M., Bruni, I., Guzzetti, L., et al. (2019). From DNA barcoding to personalized nutrition: The evolution of food traceability. Curr. Opin. Food Sci., 28. DOI:10.1016/j. cofs.2019.07.008.
  18. Garcia, A. A. F., Banchimol L. L., Barbosa A. M. M. (2004). Comparison of RAPD, RFLP, AFLP and SSR markers for diversity studies intropical maize inbred lines. Genetics and Molecular Biology, 27 (4). pp. 579–588.
  19. Gouvêa-Barros Selma., Maria do Carmo Bittencourt-Oliveira. (2012). Semi-Quantitative PCR for Quantification of Hepatotoxic Cyanobacteria. Journal of Environmental Protection, 3. DOI:10.4236/ jep.2012.35053.
  20. Haiminen, N., Edlund, S., Chambliss, D., Kunitomi, M., et al. (2019). Food authentication from shotgun sequencing reads with an application on high protein powders. NPJ Sci Food, 3, 24. DOI:10.1038/ s41538-019-0056-6
  21. Haynes, E., Jimenez, E., Pardo, M.A., Helyar, S.J. (2019). The future of NGS (Next Generation Sequencing) analysis in testing food authenticity. Food Control, 101, pp. 134–143. DOI:10.1016/j. foodcont.2019.02.010.
  22. Hernaandez, M., Esteve, T., Pla, M. (2005). Real-Time Polymerase chain reaction based assays for quantitative detection of barley, rice, sunflower, and wheat. Journal of Agriculture and Food Chemistry, 53, pp. 7003–7009.
  23. Hilton, A. C., Mortiboy, D., Banks, J. G., Penn, C. W. (1997). RAPD analysis of environmental, food and clinical isolates of Campylobacter spp. FEMS Immunol Med Microbiol., 18(2), pp. 119‒124. DOI:10.1111/j.1574-695X.1997.tb01036.x.
  24. Hu, Y., Lu, X. (2020). Rapid pomegranate juice authentication using a simple sample-toanswer hybrid paper/polymer-based lab-on-achip device. ACS Sens., 5, pp. 2168–2176. DOI:10.1021/ acssensors.0c00786.
  25. Jonker, K., Tilburg, J., Hagele, G., De Boer, E. (2008). Species identification in meat products using real-time PCR. Food Additives and Contaminants, 25 (5), pp. 527–533. DOI:10.1080/02652030701584041.
  26. Liaskovskii, Т. М. (2008). Identification of probiotic strains of lactic acid bacteria. Journal of microbiology, 70 (6), pp. 3–9 (in Ukrainian).
  27. Lin, C. C., Tang, P. C., Chiang, H. I. (2019). Development of RAPD-PCR assay Cattle for meat adulteration detection. Food Sci Biotechnol., 28(6). pp. 1769‒1777. DOI:10.1007/s10068-019-00607-7.
  28. Low, H., Chan, S. J., Soo, G. H., Ling, B., Tan, E. L. (2017). Clarity™ digital PCR system: A novel platform for absolute quantification of nucleic acids. Anal. Bioanal. Chem., 409, pp. 1869–1875. DOI:10.1007/s00216-016-0131-7.
  29. Martinez, I., Rorvik, L. M., Brox, V., Lassen, et al. (2003). Genetic variability among isolates of Listeria monocytogenes from food products, clinical samples and processing environments, estimated by RAPD typing. Int J Food Microbiol., 84 (3), pp. 285‒297. DOI:10.1016/s0168-1605(02)00423-3.
  30. Mayer, F., Haase, I., Graubner, A., Heising, F., Paschke-Kratzin, A., Fischer, M. (2012). Use of polymorphisms in the γ-gliadin gene of spelt and wheat as a tool for authenticity control. J Agric Food Chem., 60 (6), pp. 1350–1357. DOI:10.1021/jf203945d. Epub 2012 Feb 7.
  31. Miraglia, M., Berdal, K. G., Brera, C., Corbisier, P. et al. (2004). Detection and traceability of genetically modified organisms in the food production chain. Food and Chemical Toxicology, 42 (7), pp. 1157–1180. DOI:10.1016/j.fct.2004.02.018.
  32. Oblap, R. V., Novak N. B., Dyman T. M. (2014). Development of test systems based on RT-PCR to determine the species affiliation of tissues in foodstuff composition. Animal Husbandry Products Production and Processing. BNAU, 2 (112), pp. 112–115 (in Ukrainian).
  33. Oblap, R. V., Novak N. B., Dyman T. M. (2018). Monitoring of foodstuff, feed and agricultural raw materials in Ukraine for GM ingredients content. Bioresources and nature management, 10 (3‒4), pp. 49–55 (in Ukrainian).
  34. Oblap, R. V., Novak, N. B., Semenovich, V. K., Dyman, T. M. (2015). Determination of the presence of gluten from cereal crops in foodstuff by RT-PCR method. Animal Husbandry Products Production and Processing. BNAU. no. 1(116), pp. 111–116 (in Ukrainian).
  35. Pinczinger, D., von Reth, M., Hanke, M.V., Flachowsky, H. (2020). SSR fingerprinting of raspberry cultivars traded in Germany clearly showed that certainty about the genotype authenticity is a prerequisite for any horticultural experiment. Eur. J. Hortic., 85, pp. 79–85.
  36. Raime, K., Krjutškov, K., Remm, M. (2020). Method for the identification of plant DNA in food using alignment-free analysis ofsequencing reads: A case study on lupin. Front. Plant Sci., 11. DOI:10.3389/ fpls.2020.00646.
  37. Rasmussen, H-B. Restriction Fragment Length Polymorphism Analysis of PCR-Amplified Fragments (PCR-RFLP) and Gel Electrophoresis – Valuable Tool for Genotyping and Genetic Fingerprinting Available at: https://cdn.intechopen.com/pdfs/35104/ InTech-Restriction_ fragment_length_polymorphism_ analysis_of_pcr_amplified_fragments_pcr_rflp_and_ gel_electrophoresis_valuable_tool_for_genotyping_ and_genetic_fingerprinting.pdf
  38. R-BiopharmAG. SureFood®/SureFast® набори для проведення ПЛР в реальному часі: Каталог продукції. Available at:http://biola-lab.com/content/ pages/files/2014-05_surefood_ Продукти_2014.pdf.
  39. Ripp, F., Krombholz, C.F., Liu, Y., Weber, M. et al. (2014). All-Food-Seq (AFS): A quantifiable screen for species in biological samples by deep DNA sequencing. BMC Genom, 15. DOI:10.1186/1471- 2164-15-639.
  40. Saadat, S., Pandya, H., Dey, A., Rawtani, D. (2022). Food forensics: Techniques for authenticity determination of food products. Forensic Sci Int., 333. DOI:10.1016/j.forsciint. 2022.111243.
  41. Sabetta, W., Miazzi, M.M., di Rienzo, V., Fanelli, V. et al. (2017). Development and application of protocols to certify the authenticity and traceability of Apulian typical products in olive sector. Riv. Ital. Delle Sostanze Grasse, 94 (1), pp. 37–43.
  42. Sandberg, M., Lundberg, L., Ferm, M., Malmheden Yman, I. (2003). Real-time PCR for the detection and discrimination of cereal cantamination in gluten free foods. European Food Research and Technology, 217, pp. 344–349.
  43. Spaniolas, S., Bazakos, C., Tucker, G. A., Bennett, M. J. (2014). Comparison of SNPbased detection assays for food analysis: Coffee authentication. J AOAC Int., 97 (4), pp. 1114‒1120. DOI:10.5740/jaoacint.13-237.
  44. Uddin, S., Hossain, M., Chowdhury, Z., Johan, M. (2022). Detection, and discrimination of seven highly consumed meat species simultaneously in food products using heptaplex PCR-RFLP assay. Journal of Food Composition and Analysis, 100, pp. 938‒944.
  45. VanGuilder, H. D., Vrana, K. E., Freeman, W. M. (2008). Twenty-five years of quantitative PCR for gene expression analysis. Biotechniques, 44, pp. 619‒626. DOI:10.2144/ 000112776.
  46. Verdone, M., Rao, R.,Coppola, M., Corrado, G. (2018). Identification of zucchini varieties in commercial food products by DNA typing. Food Control, 84, pp. 197–204.
  47. Voelkerding, K. V., Dames, S. A., Durtschi, J. D. (2009). Next-generation Sequencing: From Basic Research to Diagnostics. Clinical Chemistry, 55 (4), pp. 651‒658. DOI:10.1373/ clinchem.2008.112789.
  48. Wang, C., Yang, C. J. (2013). Application of Molecular Beacons in Real-Time PCR. Molecular Beacons, 18, pp. 45–59. DOI:10.1007/978-3-642- 39109-5_3.
  49. Wenne, R., Prądzińska, A., Poćwierz-Kotus, A.,Larraín M-A., Araneda C., Zbawicka M. (2022). Provenance of Mytilus food products in Europe using SNP genetic markers.Aquaculture, 554. DOI:10.1016/j. aquaculture.2022.738135. 1. Wolf, C., Burgener, M., Hubner, P., Luthy, J. (2000). PCR-RFLP Analysis of Mitochondrial DNA: differentiation of fishspecies. Lebensm.-Wiss. u.- Technol., 33, pp. 144‒150.
  50. World Health Organization. WHO estimates of the global burden of foodborne diseases: Foodborne Disease Burden Epidemiology Reference Group 2007–2015. Geneva: WHO Press, 2015. Available at:https:// www.who.int/foodsafety/publications/foodborne_ disease/ fergreport/en/.
  51. Zambelli, R. A., Brasil, I. M. (2022). Molecular Techniques for identification applied to food: A review. Int J Agric Sc Food Technol., 8(4), pp. 305‒315. DOI:10.17352/2455-815X.000182.
  52. Zambianchi, S., Soffritti, G., Stagnati, L., Patrone, V., et al. (2021). Applicability of DNA traceability along the entire wine production chain in the real case of a large Italian cooperative winery. Food Control, 124. DOI:10.1016/ j.foodcont.2021.107929.
  53. Zane, L., Bargelloni, L., Patarnello, T. (2002). Strategies for microsatellite isolation: a review. Mol. Ecol., 11, pp.1–16.
  54. Zhang, D., Vega, F.E., Infante, F., Solano,W. et al. (2020). Accurate differentiation of green beans of Arabica and Robusta coffee using nanofluidic array of Single Nucleotide Polymorphism (SNP) markers. J. AOAC Int., 103, pp. 315–324. DOI:10.1093/jaocint/qsz002.
  55. Zhang, X., Lowe, S. B., Gooding, J. J. (2014). Brief review of monitoring methods for loop-mediated isothermal amplification (LAMP). Biosens. Bioelectron, 61, pp.491–499. DOI: 10.1016/j.bios.2014.05.039.
  56. Zhao, J., Li, A., Jin, X., Pan, L. (2020). Technologies in individual animal identification and meat products traceability. Biotechnol. Biotechnol. Equip., 34, pp. 48–57. DOI:10.1080/ 13102818.2019.1711185.
  57. Zhao, M., Shi, Y., Wu, L., Guo, L., et al. (2016). Rapid authentication of the precious herb saffron by loop-mediated isothermal amplification (LAMP) based on internal transcribed spacer 2 (ITS2) sequence. Sci. Rep., 6. DOI:10.1038/srep25370.
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BTF №2 2023