DNAFoil, a novel technology for the rapid detection of food pathogens: Preliminary validation on Salmonella and Listeria monocytogenes

Main Article Content

Aly El Sheikha

Keywords

DNAFoil technology; food pathogen detection techniques, food safety; foodborne diseases; health and economics threats

Abstract

Over the past decades, several tools have been developed for food pathogen detection, including proteomics, metabolomics, immunological, biosensor, and nucleic acid-based approaches. Although these techniques are reliable and precise, they are time-consuming, technically challenging, and costly. Hence, it is necessary to develop rapid techniques for food pathogen detection, which can be performed at the household level. DNAFoil mechanism is a portable, completely self-administered, on-site DNA test that does not need expensive instru-ments or settings to confirm food pathogen detection in as little as 30 min. DNAFoil was used successfully for detecting food contamination and adulteration with pork derivatives (down to 0.1%) and vegetal components (down to 0.01%), respectively. In this study, initial validation experiments of DNAFoil were investigated to detect Listeria monocytogenes and Salmonella contamination. To confirm the specificity of the proposed method toward Salmonella, 18 different Salmonella strains, 6 non-Salmonella bacteria, and 2 fungi were investigated; also, in the case of Listeria monocytogenes, five bacterial strains, two fungi, and Listeria monocytogenes were investigated. The results stated that the Swiss Decode Salmonella and L. monocytogenes solutions can detect as few as 1 and 10 copies of DNA per microliter, respectively. The results also showed that the accuracy of our method ranges between 92 and 100%, while the precision value ranged between 88 and 100%. In terms of quality control applicability, DNAFoil Salmonella and Listeria monocytogenes reactions could be visually detected with the naked eye using a lateral flow strip, which could be used for in-place quality control during manufacturing and also can be used for more lab tests. In terms of cost, DNAFoil is usually much cheaper than the traditional detection methods. Therefore, DNAFoil is proposed as a promising and universal detection technology for food pathogens.

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References

Adzitey, F. and Huda, N., 2010. Listeria monocytogenes in foods: incidences and possible control measures. African Journal of Microbiology Research 4: 2848–2855. Available at: http://www. academicjournals.org/ajmr
Adzitey, F. and Huda, N., 2011. Campylobacter in poultry: incidences and possible control measures. Research Journal of Microbiology 6: 182–192. https://doi.org/10.3923/jm.2011.182.192
Adzitey, F., Huda, N. and Gulam, R., 2011. Comparison of media for the isolation of Salmonella (XLD and Rambach) and Listeria species (ALOA and Palcam) in naturally contaminated duck samples. Internet Journal of Food Safety 13: 20–25.
Anderson, N.W., Buchan, B.W., Riebe, K.M., Parsons, L.N., Gnacinski, S. and Ledeboer, N.A., 2012. Effects of solid-medium type on routine identification of bacterial isolates by use of matrix-assisted laser desorption ionization-time of flight mass spectrometry. Journal of Clinical Microbiology 50: 1008–1013. https://doi.org/10.1128/JCM.05209-11
Aronoff, R., Vernez, I., Rotman, N. and Rando, G., 2018. Detection of milk adulteration using DNAFoil UniPlant. Application Note: v0.3 Available at: https://www.dropbox.com/s/ho5ich3fpzy5k0s/ application_note_UniPlant_1dec17.docx?dl=0. Accessed 27 January 2021.
Baraketi, A., Salmieri, S. and Lacroix, M., 2018. Foodborne patho-gens detection: persevering worldwide challenge. In: Rinken, T. and Kivirand, K. (eds.) Biosensing technologies for the detection of pathogens—a prospective way for rapid analysis. IntechOpen, Rijeka, Croatia, pp. 53–72. https://doi.org/10.5772/ intechopen.74421
Beale, D.J., Morrison, P.D. and Palombo, E.A., 2014. Detection of Listeria in milk using non-targeted metabolic profiling of Listeria monocytogenes: a proof-of-concept application. Food Control 42: 343–346. https://doi.org/10.1016/j.foodcont.2014.01.022
Bhunia, A., 2014. One day to one hour: how quickly can food-borne pathogens be detected? Future Microbiology 9: 935–946. https://doi.org/10.2217/FMB.14.61
Bintsis, T., 2017. Foodborne pathogens. AIMS Microbiology 3: 529– 563. https://doi.org/10.3934/microbiol.2017.3.529
Buchanan, R.L., Goris, L.G.M., Hayman, M.M., Jackson, T.C. and Whiting, R.C., 2017. A review of Listeria monocytogenes: an update on outbreaks, virulence, dose-response, ecology, and risk assessments. Food Control 75: 1–13. https://doi.org/10.1016/j. foodcont.2016.12.016
CDC (Centers for Disease Control and Prevention), 2020. Foodborne germs and illnesses. Last updated: March 18, 2020. Available at: https://www.cdc.gov/foodsafety/foodborne-germs. html. Accessed 27 January 2021.
Cevallos-Cevallos, J.M., Danyluk, M.D. and Reyes-De-Corcuera, J.I., 2011. GC-MS based metabolomics for rapid simultaneous detec-tion of Escherichia coli O157: H7, Salmonella Typhimurium, Salmonella Muenchen, and Salmonella Hartford in ground beef and chicken. Journal of Food Science 76: M238–M246. https:// doi.org/10.1111/j.1750-3841.2011.02132.x
Chlebicz, A. and ?li?ewska, K., 2018. Campylobacteriosis, salmonel-losis, yersiniosis, and listeriosis as zoonotic foodborne diseases: a review. International Journal of Environmental Research and Public Health 15: 863. https://doi.org/10.3390/ijerph15050863
Corry, J.E.L., Atabay, H.I., Forsythe, S.J. and Mansfield, L.P., 2003. Culture media for the isolation of Campylobacters, Helicobacters and Arcobacters. In: Corry, J.E.L., Curtis, G.D.W. and Baird,  R.M. (eds.) Handbook of culture media for food microbiology. 2nd ed. Elsevier Science, Amsterdam, pp. 271– 315. https://doi.org/10.1016/S0079-6352(03)80021-8
Cossarizza, A., Chang, H.-D., Radbruch, A., Akdis, M., Andrä,  I., Annunziato, F., et al. 2017. Guidelines for the use of flow cytometry and cell sorting in immunological studies. European Journal of Immunology 47: 1584–1797. https://doi.org/10.1002/ eji.201646632
Drabik, A., Bodzo?-Ku?akowska, A. and Silberring, J., 2016. Gel electrophoresis. In: Ciborowski, P. and Silberring, J. (eds.) Proteomic profiling and analytical chemistry. 2nd ed. Elsevier, Amsterdam, Netherlands, pp. 115–143. https://doi.org/10.1016/ B978-0-444-63688-1.00007-0
Dwivedi, H.P. and Jaykus, L., 2011. Detection of pathogens in foods: the current state-of-the-art and future directions. Critical Reviews in Microbiology 37: 40–63. https://doi.org/10.3109/10 40841X.2010.506430
EFSA and ECDC (European Food Safety Authority and European Centre for Disease Prevention and Control), 2016. The European Union summary report on trends and sources of zoonoses, zoo-notic agents and food-borne outbreaks in 2015. EFSA Journal 14: 4634–4865. https://doi.org/10.2903/j.efsa.2016.4634
El Sheikha, A.F., 2010. Determination of geographical origin of Shea tree and Physalis fruits by using the genetic fingerprints of the microbial community by PCR/DGGE. Analysis of biological properties of some fruit extracts. PhD thesis. University of Montpellier 2, Montpellier, France.
El Sheikha, A.F., 2015. Food safety issues in Saudi Arabia. Nutrition and Food Technology: Open Access 1: 1–4. https://doi. org/10.16966/nftoa.103
El Sheikha, A.F., 2019. DNAFoil: novel technology for the rapid detection of food adulteration. Trends in Food Science & Technology 86: 544–552. https://doi.org/10.1016/j.tifs.2018. 11.012
El Sheikha, A.F. and Hu, D.-H., 2020. Molecular techniques reveal more secrets of fermented foods. Critical Reviews in Food Science and Nutrition 60: 11–32. https://doi.org/10.1080/10408 398.2018.1506906
El Sheikha, A.F., Levin, R.E. and Xu, J., 2018. Molecular techniques in food biology: safety, biotechnology, authenticity & traceability. 1st ed. John Wiley & Sons, Ltd., Chichester, UK. https://doi. org/10.1002/9781119374633
Ellis, D.I., Muhamadali, H., Chisanga, M. and Goodacre, R., 2019. Omics methods for the detection of foodborne pathogens. In: Melton, L., Shahidi, F. and Varelis, P. (eds.) Encyclopedia of food chemistry. Academic Press, Oxford, pp. 364–370. https://doi. org/10.1016/B978-0-08-100596-5.21793-9
Engberg, J., On, S.L.W., Harrington, C.S. and Gerner-Smidt, P., 2000. Prevalence of Campylobacter, Arcobacter, Helicobacter and Sutterella spp. in human faecal samples as estimated by reevaluating of isolation methods for Campylobacters. Journal of Clinical Microbiology 38: 286–291.
Faour-Klingbeil, D. and Todd, E.C.D., 2020. Prevention and control of foodborne diseases in Middle-East North African countries: review of national control systems. International Journal of Environmental Research and Public Health 17: 70. https://doi. org/10.3390/ijerph17010070
FDA (U.S. Food and Drug Administration), 2021. Most common foodborne illnesses. Available at: https://www.fda.gov/ files/food/published/Most-Common-Foodborne-Illnesses-%28PDF%29.pdf. Accessed 27 January 2021.
Foddai, A.C.G. and Grant, I.R., 2020. Methods for detection of viable foodborne pathogens: current state-of-art and future prospects. Applied Microbiology and Biotechnology 104: 4281– 4288. https://doi.org/10.1007/s00253-020-10542-x
Food Safety Education Program, 2016. Causes and prevention of foodborne illness. Updated 12/2016. Available at: https://web. uri.edu/foodsafety/cause-and-prevention-of-foodborne-illness/. Accessed 27 January 2021.
Hall, A.C., 2020. A comparison of DNA stains and staining methods for Agarose Gel Electrophoresis. https://doi.org/10.1101/568253 (In press).
Hemalata, V.B. and Virupakshaiah, D.B.M., 2016. Isolation and identification of food borne pathogens from spoiled food samples. International Journal of Current Microbiology and Applied Sciences 5: 1017–1025. https://doi.org/10.20546/ ijcmas.2016.506.108
Hoffmann, S. and Scallan, E., 2017. Epidemiology, cost, and risk analysis of foodborne disease. In: Dodd, C.E.R., Aldsworth, T., Stein, R.A., Cliver, D.O. and Riemann, H.P. (eds.) Foodborne diseases. 3rd ed. Academic Press, Elsevier, London, UK, pp. 31–63. https://doi.org/10.1016/B978-0-12-385007-2.00002-4
Jadhav, S.R., Shah, R.M., Karpe, A.V., Morrison, P.D., Kouremenos, K., Beale, D.J. and Palombo, E.A., 2018. Detection of foodborne pathogens using proteomics and metabolomics-based approaches. Frontiers in Microbiology 9: 3132. https:// doi.org/10.3389/fmicb.2018.03132
Jasson, V., Jacxsens, L., Luning, P., Rajkovic, A. and Uyttendaele, M., 2010. Alternative microbial methods: an overview and selec-tion criteria. Food Microbiology 27: 710–730. https://doi. org/10.1016/j.fm.2010.04.008
Keramas, G., Bang, D.D., Lund, M., Madsen, M., Bunkenborg, H., Telleman, P. and Christensen, C.B.V., 2004. Use of culture, PCR analysis and DNA microarrays for detection of Campylobacter jejuni and Campylobacter coli from chicken faeces. Journal of Clinical Microbiology 47: 3985–3991. https://doi.org/10.1128/ JCM.42.9.3985-3991.2004
Law, J.W.-F., Ab Mutalib, N.-S., Chan, K.-G. and Lee, L.-H., 2015. Rapid methods for the detection of foodborne bacterial patho-gens: principles, applications, advantages and limitations. Frontiers in Microbiology 5: 770. https://doi.org/10.3389/ fmicb.2014.00770
Li, H. and Zhu, J., 2017. Targeted metabolic profiling rapidly differ-entiates Escherichia coli and Staphylococcus aureus at species and strain level. Rapid Communications in Mass Spectrometry 31: 1669–1676. https://doi.org/10.1002/rcm.7949
Lüdin, P., Rando, G. and Sahi, B., 2018. Nouveau test rapide pour la détection des contrefaçons de fromages. Alimenta 10: 20–21. (In French Language). Available at: https://uploads.striking-lycdn.com/files/fe0d684e-50ab-4e83-a14c-97c31e73ea4e/ SwissDeCode_Artikel%20DNA%20Foil_Alimenta.pdf. Accessed 27 January 2021.
Magistrado, P., Carcia, M. and Raymundo, A., 2001. Isolation and polymerase chain reaction-base detection of Campylobacter jejuni and Campylobacter coli from poultry in Philippines. International Journal of Food Microbiology 70: 194–206. https:// doi.org/10.1016/S0168-1605(01)00537-2
Mandal, P., Biswas, A., Choi, K. and Pal, U., 2011. Methods for rapid detection of foodborne pathogens: an overview. American Journal of Food Technology 6: 87–102. https://doi.org/10.3923/ ajft.2011.87.102
Mayo Clinic, 2019. Salmonella infection. Oct. 11, 2019. Available at: https://www.mayoclinic.org/diseases-conditions/salmonella/ symptoms-causes/syc-20355329. Accessed 27 January 2021.
Mayo Clinic, 2020a. Listeria infection. Jan. 18, 2020. Available at: https://www.mayoclinic.org/diseases-conditions/listeria-infection/symptoms-causes/syc-20355269. Accessed 27 January 2021.
Mayo Clinic, 2020b. Shigella infection. Nov. 12, 2020. Available at: https://www.mayoclinic.org/diseases-conditions/shigella/symptoms-causes/syc-20377529. Accessed 27 January 2021.
Mayo Clinic, 2020c. Toxoplasmosis. Oct. 13, 2020. Available at: https:// www.mayoclinic.org/diseases-conditions/toxoplasmosis/ symptoms-causes/syc-20356249. Accessed 27 January 2021.
Meat and Livestock Australia Limited (MLA), 2018. Evaluation of novel DNA-based test kits. Final report ABN 39 081 678 364 (MLA). Meat & Livestock Australia Limited, North Sydney.
Mirmajlessi, S.M., Destefanis, M., Gottsberger, R.A., Mänd,  M. and Loit, E., 2015. PCR-based specific techniques used for detecting the most important pathogens on strawberry: a systematic review. Systematic Reviews 4: 9. https://doi. org/10.1186/2046-4053-4-9
Myint, M.S., Johnson, Y.J., Tablante, N.L. and Heckert, R.A., 2006. The effect of pre-enrichment protocol on the sensitivity and specificity of PCR for detection of naturally contaminated Salmonella in raw poultry compared to conventional culture. Food Microbiology 23: 599–604. https://doi.org/10.1016/j. fm.2005.09.002
NCBI (National Centre for Biotechnology Information), 2016. Entamoebiasis. Available at: https://www.ncbi.nlm.nih.gov/ mesh/68004749. Accessed 27 January 2021.
NCBI (National Centre for Biotechnology Information), 2017. Available at: https://www.ncbi.nlm.nih.gov/genome. Accessed 27 January 2021.
Ontario Ministry of Health and Long-Term Care, 2018. Yersiniosis. Last Modified: 2018-08-08. Available at: http://www.health.gov.on.ca/en/public/publications/disease/yersiniosis.aspx. Accessed 27 January 2021.
Ontario Ministry of Health and Long-Term Care, 2020. Campylobacteriosis. Last Modified: 2020-09-09. Available at: http://www.health.gov.on.ca/en/public/publications/disease/ campylobacter.aspx. Accessed 27 January 2021.
Park, K., 2015. Park’s textbook of preventive and social medicine. 23rd ed. Banarsidas Bhanot Publishers, Jabalpur, India.
Pinu, F.R., 2016. Early detection of food pathogens and food spoilage microorganisms: application of metabolomics. Trends in Food Science & Technology 54: 213–215. https://doi.org/10.1016/j. tifs.2016.05.018
Rajapaksha, P., Elbourne, A., Gangadoo, S., Brown, R., Cozzolino, D. and Chapman, J., 2019. A review of methods for the detection of pathogenic microorganisms. Analyst 144: 396–411. https://doi. org/10.1039/c8an01488d
Rasetti-Escargueil, C., Lemichez, E. and Popoff, M.R., 2020. Public health risk associated with botulism as foodborne zoonoses. Toxins (Basel) 12: 17. https://doi.org/10.3390/toxins12010017
Reta, D.H., Tessema, T.S., Ashenef, A.S., Desta, A.F., Labisso, W.L., Gizaw, S.T., et al. 2020. Molecular and immunological diagnostic techniques of medical viruses. International Journal of Microbiology 2020: 8832728. https://doi.org/10.1155/2020/8832728
Rossen, L., Norskov, P., Holmstrom, K. and Rasmussen, O.F., 1992. Inhibition of PCR by components of food samples, microbial diagnostic assays and DNA extraction solutions. International Journal of Food Microbiology 17: 37–45. https:// doi.org/10.1016/0168-1605(92)90017-W
Singh, A.K., Ulanov, A.V., Li, Z., Jayaswal, R.K. and Wilkinson, B.J., 2011. Metabolomes of the psychrotolerant bacterium Listeria monocytogenes 10403S grown at 37°C and 8°C. International Journal of Food Microbiology 148: 107–114. https://doi. org/10.1016/j.ijfoodmicro.2011.05.008
Singhal, N., Kumar, M., Kanaujia, P.K. and Virdi, J.S., 2015. MALDI-TOF mass spectrometry: an emerging technology for microbial identification and diagnosis. Frontiers in Microbiology 6: 791. https://doi.org/10.3389/fmicb.2015.00791
Toscano, M., de Grandi, R. and Drago, L., 2018. Proteomics: the new era of microbiology. Microbiologia Medica 32: 7348. https://doi. org/10.4081/mm.2017.7348
Tyco Integrated Security, 2012. Recall: the food industry’s biggest threat to profitability. Food Safety Magazine October 11, 2012. Available at: https://www.food-safety.com/articles/2542-recall-the-food-industrys-biggest-threat-to-profitability. Accessed 27 January 2021.
USDA ERS (United States Department of Agriculture Economic Research Service), 2014. Cost estimates of foodborne illnesses. Last updated: Tuesday, August 20, 2019. Available at: https:// www.ers.usda.gov/data-products/cost-estimates-of-food-borne-illnesses.aspx#48446. Accessed 1 January 2021.
Valderrama, W.B., Dudley, E.G., Doores, S. and Cutter, C.N., 2016. Commercially available rapid methods for detection of selected food-borne pathogens. Critical Reviews in Food Science and Nutrition 56: 1519–1531. https://doi.org/10.1080/10408398.20 13.775567
WHO (World Health Organization), 2020. Food safety. 30 April 2020. Available at: https://www.who.int/news-room/fact-sheets/ detail/food-safety. Accessed 27 January 2021.
WHO (World Health Organization), 2021. Foodborne diseases. Available at: https://www.who.int/health-topics/foodborne-diseases#tab=tab_1. Accessed 27 January 2021.
Wilson, I.G., 1997. Inhibition and facilitation of nucleic acid amplification. Applied and Environmental Microbiology 63: 3741– 3751. https://doi.org/10.1128/AEM.63.10.3741-3751.1997
Wu, F., Zhong, F. and He, F., 2016. Microbial proteomics: approaches, advances, and applications. Journal of Bioinformatics, Proteomics and Imaging Analysis 2: 85–91. https://doi.org/10.15436/2381-0793.16.004
Yang, Y., Hu, M., Yu, K., Zeng, X. and Liu, X., 2015. Mass spectrometry- based proteomic approaches to study pathogenic bacteria-host interactions. Protein & Cell 6: 265–274. https:// doi.org/10.1007/s13238-015-0136-6
Zhao, X., Lin, C.-W., Wang, J. and Oh, D.H., 2014. Advances in rapid detection methods for foodborne pathogens. Journal of Microbiology and Biotechnology 24: 297–312. https://doi. org/10.4014/jmb.1310.10013