Assessing Salmonella quantification methods: MPN and MPN-LAMP perform equally in artificial contamination, while dPCR lacks sensitivity for naturally contaminated samples
DOI:
https://doi.org/10.5327/fst.00470Keywords:
food safety, Salmonella detection, quantification protocols, microbiological control, MPN-LAMP, dPCRAbstract
Identifying and quantifying Salmonella in chicken carcasses is crucial for food safety and public health. Recent efforts focus on improving detection methods by combining traditional microbiology with molecular biology for better accuracy and speed. This study compared two protocols for Salmonella quantification: the conventional most probable number (MPN) and a combined approach integrating MPN with loop-mediated isothermal amplification (LAMP). The second phase evaluated MPN-LAMP and digital polymerase chain reaction for detecting and quantifying Salmonella in naturally contaminated chicken samples. The results indicated no statistically significant difference between the conventional MPN and MPN-LAMP methods in the evaluated steps. Both methods had similar performance, suggesting that MPN-LAMP can be used as a faster alternative. Upon application of this methodology to naturally contaminated chicken carcasses, 4 out of 16 samples (25%) exhibited contamination levels exceeding the detection thresholds when quantified using the MPN-LAMP method, with values ranging from 3.6 MPN/g to 15 MPN/g. However, the digital polymerase chain reaction technique could not detect or quantify samples in naturally contaminated chicken carcasses, highlighting challenges in pathogen detection in food. The results emphasize the need to compare methods in routine samples for microbiological surveillance and improve quantification techniques, ensuring food safety and implementing innovative Salmonella detection protocols.
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Ahmad, F., Stedtfeld, R. D., Waseem, H., Williams, M. R., Cupples, A. M., Tiedje, J. M., & Hashsham, S. A. (2017). Most probable number - loop mediated isothermal amplification (MPN-LAMP) for quantifying waterborne pathogens in < 25 min. Journal of Microbiological Methods, 132, 27–33. https://doi.org/10.1016/j.mimet.2016.11.010
Barbau-Piednoir, E., Bertrand, S., Mahillon, J., Roosens, N. H., & Botteldoorn, N. (2013). SYBR®Green qPCR Salmonella detection system allowing discrimination at the genus, species and subspecies levels. Applied Microbiology and Biotechnology, 97, 9811–9824. https://doi.org/10.1007/s00253-013-5234-x
Bari, M. L., & Yeasmin, S. (2022). Microbes culture methods. In N. Rezaei (Ed.), Encyclopedia of Infection and Immunity (Vol. 4, pp. 77–98). Elsevier. https://doi.org/10.1016/B978-0-12-818731-9.00128-2
Blodgett, R. (2010). Bacterial Analytical Manual, Appendix 2: Most probable number from serial dilutions. United States Food and Drug Administration. Retrieved May 21, 2024, from http://www.fda.gov/Food/FoodScienceResearch/LaboratoryMethods/ucm109656.htm
Corrêa, I. M. O., Pereira, L. Q., Silva, I. G. O., Altarugio, R., Smaniotto, B. D., Silva, T. M., Okamoto, A. S., & Andreatti Filho, R. L. (2018). Comparison of three diagnostic methods for Salmonella enterica serovars detection in chicken rinse. Pesquisa Veterinária Brasileira, 38(7), 1300–1306. https://doi.org/10.1590/1678-5150-PVB-5211
Fang, Z., Zhou, X., Wang, X., & Shi, X. (2023). Development of a 3-plex droplet digital PCR for identification and absolute quantification of Salmonella and its two important serovars in various food samples. Food Control, 145, Article 109465. https://doi.org/10.1016/j.foodcont.2022.109465
Forsythe, S. J. (2013). Microbiologia da segurança dos alimentos (2nd ed.). Artmed.
Fu, J., Chiang, E. L. C., Medriano, C. A. D., Li, L., & Bae, S. (2021). Rapid quantification of fecal indicator bacteria in water using the most probable number - loop-mediated isothermal amplification (MPN-LAMP) approach on a polymethyl methacrylate (PMMA) microchip. Water Research, 199, Article 117172. https://doi.org/10.1016/j.watres.2021.117172
International Organization for Standardization. (2017). International Standard ISO 6579-1. Microbiology of the food chain-horizontal method for the detection, enumeration and serotyping of Salmonella-Part 1: Detection of Salmonella spp. International Organization for Standardization.
Kanitkar, Y. H., Stedtfeld, R. D., Hatzinger, P. B., Hashsham, S. A., & Cupples, A. M. (2017). Most probable number with visual based LAMP for the quantification of reductive dehalogenase genes in groundwater samples. Journal of Microbiological Methods, 143, 44–49. https://doi.org/10.1016/j.mimet.2017.10.003
Kirk, M. D., Pires, S. M., Black, R. E., Caipo, M., Crump, J. A., Devleesschauwer, B., Döpfer, D., Fazil, A., Fischer-Walker, C. L., Hald, T., Hall, A. J., Keddy, K. H., Lake, R. J., Lanata, C. F., Torgerson, P. R., Havelaar, A. H., & Angulo, F. J. (2015). World Health Organization estimates of the global and regional disease burden of 22 foodborne bacterial, protozoal, and viral diseases, 2010: A data synthesis. PLOS Medicine, 12(12), Article e1001921. https://doi.org/10.1371/journal.pmed.1001921
Kuypers, J., & Jerome, K. R. (2017). Applications of digital PCR for clinical microbiology. Journal of Clinical Microbiology, 55(6), 1621–1628. https://doi.org/10.1128/JCM.00211-17
Lei, S., Chen, S., & Zhong, Q. (2021). Digital PCR for accurate quantification of pathogens: Principles, applications, challenges and future prospects. International Journal of Biological Macromolecules, 184, 750–759. https://doi.org/10.1016/j.ijbiomac.2021.06.132
Machado, S. C. A., Pereira, V. L. A., Aquino, M. H. C., Giombeli, A., Rodrigues, D. P., & Nascimento, E. R. (2020). Qualitative and quantitative analysis of Salmonella spp. in broilers technological processing and determination of a performance objective (PO) for frozen chicken breast. Brazilian Journal of Poultry Science, 22(1), 1–12. https://doi.org/10.1590/1806-9061-2019-1196
Moon, Y.-J., Lee, S.-Y., & Oh, S.-W. (2022). A review of isothermal amplification methods and food-origin inhibitors against detecting food-borne pathogens. Foods, 11(3), Article 322. https://doi.org/10.3390/foods11030322
Murray, R. T., Cruz-Cano, R., Nasko, D., Blythe, D., Ryan, P., Boyle, M., Wilson, S., & Sapkota, A. R. (2021). Prevalence of private drinking water wells is associated with salmonellosis incidence in Maryland, USA: An ecological analysis using Foodborne Diseases Active Surveillance Network (FoodNet) data (2007–2016). Science of the Total Environment, 787, Article 147682. https://doi.org/10.1016/j.scitotenv.2021.147682
Ndraha, N., Lin, H.-Y., Wang, C.-Y., Hsiao, H.-I., & Lin, H.-J. (2023). Rapid detection methods for foodborne pathogens based on nucleic acid amplification: Recent advances, remaining challenges, and possible opportunities. Food Chemistry and Molecular Sciences, 7, Article 100183. https://doi.org/10.1016/j.fochms.2023.100183
Neyaz, L. A., Alghamdi, H. S., Alghashmari, R. M., Alswat, S. S., Almaghrabi, R. O., Bazaid, F. S., Albarakaty, F. M., Elbanna, K., & Abulreesh, H. H. (2024). A comprehensive review on the current status of culture media for routine standardized isolation of Salmonella and Shigella spp. from contaminated food. Journal of Umm Al-Qura University for Applied Sciences, 1–14. https://doi.org/10.1007/s43994-024-00205-2
Notomi, T., Okayama, H., Masubuchi, H., Yonekawa, T., Watanabe, K., Amino, N., & Hase, T. (2000). Loop-mediated isothermal amplification of DNA. Nucleic Acids Research, 28(12), Article e63. https://doi.org/10.1093/nar/28.12.e63
Oblinger, J. L., & Koburger, J. A. (1975). Understanding and teaching the most probable number technique. Journal of Food Protection, 38(9), 540–545. https://doi.org/10.4315/0022-2747-38.9.540
Patel, A., Wolfram, A., & Desin, T. S. (2024). Advancements in detection methods for Salmonella in food: A comprehensive review. Pathogens, 13(12), Article 1075. https://doi.org/10.3390/pathogens13121075
Possebon, F. S., Ullmann, L. S., Malossi, C. D., Miodutzki, G. T., Silva, E. C., Machado, E. F., Braga, I. S., Pelaquim, I. F., & Araujo Jr., J. P. (2022). A fast and cheap in-house magnetic bead RNA extraction method for COVID-19 diagnosis. Journal of Virological Methods, 300, Article 114414. https://doi.org/10.1016/j.jviromet.2021.114414
Rortana, C., Nguyen-Viet, H., Tum, S., Unger, F., Boqvist, S., Dang-Xuan, S., Koam, S., Grace, D., Osbjer, K., Heng, T., Sarim, S., Phirum, O., Sophia, R., & Lindahl, J. F. (2021). Prevalence of Salmonella spp. and Staphylococcus aureus in chicken meat and pork from Cambodian markets. Pathogens, 10(5), Article 556. https://doi.org/10.3390/pathogens10050556
Rosniawati, T., Rahayu, W. P., Kusumaningrum, H. D., Indrotristanto, N., & Nikastri, E. (2021). Prevalence and level of Salmonella spp. contamination on selected pathways of preparation and cooking of fried chicken at the household level. Food Science and Technology, 41(1), 41–46. https://doi.org/10.1590/fst.10120
Salipante, S. J., & Jerome, K. R. (2020). Digital PCR—An emerging technology with broad applications in microbiology. Clinical Chemistry, 66(1), 117–123. https://doi.org/10.1373/clinchem.2019.304048
Schrader, C., Schielke, A., Ellerbroek, L., & Johne, R. (2012). PCR inhibitors – occurrence, properties and removal. Journal of Applied Microbiology, 113(5), 1014–1026. https://doi.org/10.1111/j.1365-2672.2012.05384.x
Shanker, R., Singh, G., Jyoti, A., Dwivedi, P. D., & Singh, S. P. (2014). Nanotechnology and detection of microbial pathogens. In A. S. Verma, & A. Singh (Eds.), Animal Biotechnology (pp. 525–540). Academic Press. https://doi.org/10.1016/B978-0-12-416002-6.00028-6
Velez, F. J., Kandula, N., Blech-Hermoni, Y., Jackson, C. R., Bosilevac, J. M., & Singh, P. (2024). Digital PCR assay for the specific detection and estimation of Salmonella contamination levels in poultry rinse. Current Research in Food Science, 9, Article 100807. https://doi.org/10.1016/j.crfs.2024.100807
Villamil, C., Calderon, M. N., Arias, M. M., & Leguizamon, J. E. (2020). Validation of droplet digital polymerase chain reaction for Salmonella spp. quantification. Frontiers in Microbiology, 11, Article 1512. https://doi.org/10.3389/fmicb.2020.01512
Waghamare, R. N., Paturkar, A. M., Vaidya, V. M., Zende, R. J., & Ingole, S. D. (2019). Quantifying the Salmonella spp. at critical stages of poultry processing by miniature MPN techniques (mMPN). Journal of Entomology and Zoology Studies, 7(2), 1089–1093. https://www.researchgate.net/publication/332554750_Quantifying_the_Salmonella_spp_at_critical_stages_of_poultry_processing_by_miniature_MPN_techniques_mMPN
Xu, W., Gao, J., Zheng, H., Yuan, C., Hou, J., Zhang, L., & Wang, G. (2019). Establishment and application of polymerase spiral reaction amplification for Salmonella detection in food. Journal of Microbiology and Biotechnology, 29(10), 1543–1552. https://doi.org/10.4014/jmb.1906.06027