Journal of Microbiology and Biotechnology

The Korean Society for Microbiology and Biotechnology (한국미생물·생명공학회)
권호 표지
DOI QR코드

DOI QR Code

Evaluating the Prevalence of Foodborne Pathogens in Livestock Using Metagenomics Approach

  • Kim, Hyeri (Department of Animal Resources Science, Dankook University) ;
  • Cho, Jin Ho (Division of Food and Animal Science, Chungbuk National University) ;
  • Song, Minho (Division of Animal and Dairy Science, Chungnam National University) ;
  • Cho, Jae Hyoung (Department of Animal Resources Science, Dankook University) ;
  • Kim, Sheena (Department of Animal Resources Science, Dankook University) ;
  • Kim, Eun Sol (Department of Animal Resources Science, Dankook University) ;
  • Keum, Gi Beom (Department of Animal Resources Science, Dankook University) ;
  • Kim, Hyeun Bum (Department of Animal Resources Science, Dankook University) ;
  • Lee, Ju-Hoon (Department of Food Animal Biotechnology, Department of Agricultural Biotechnology, Center for Food and Bioconvergence, Seoul National University)
  • Received : 2021.09.17
  • Accepted : 2021.10.13
  • Published : 2021.12.28
Download PDF
⟨ Previous Next ⟩

Abstract

Food safety is the most important global health issue due to foodborne pathogens after consumption of contaminated food. Foodborne bacteria such as Escherichia coli, Salmonella enterica, Staphylococcus aureus, Campylobacter spp., Bacillus cereus, Vibrio spp., Yersinia enterocolitica and Clostridium perfringens are leading causes of the majority of foodborne illnesses and deaths. These foodborne pathogens often come from the livestock feces, thus, we analyzed fecal microbial communities of three different livestock species to investigate the prevalence of foodborne pathogens in livestock feces using metagenomics analysis. Our data showed that alpha diversities of microbial communities were different according to livestock species. The microbial diversity of cattle feces was higher than that of chicken or pig feces. Moreover, microbial communities were significantly different among these three livestock species (cattle, chicken, and pig). At the genus level, Staphylococcus and Clostridium were found in all livestock feces, with chicken feces having higher relative abundances of Staphylococcus and Clostridium than cattle and pig feces. Genera Bacillus, Campylobacter, and Vibrio were detected in cattle feces. Chicken samples contained Bacillus, Listeria, and Salmonella with low relative abundance. Other genera such as Corynebacterium, Streptococcus, Neisseria, Helicobacter, Enterobacter, Klebsiella, and Pseudomonas known to be opportunistic pathogens were also detected in cattle, chicken, and pig feces. Results of this study might be useful for controlling the spread of foodborne pathogens in farm environments known to provide natural sources of these microorganisms.

Keywords

Acknowledgement

The present study was supported by the research fund (19162MFDS037) from the Ministry of Food and Drug Safety, Republic of Korea.

References

  1. Oliver SP, Jayarao BM, Almeida RA. 2005. Foodborne pathogens in milk and the dairy farm environment: food safety and public health implications. Foodborne Pathog. Dis. 2: 115-129. https://doi.org/10.1089/fpd.2005.2.115
  2. Velusamy V, Arshak K, Korostynska O, Oliwa K, Adley C. 2010. An overview of foodborne pathogen detection: in the perspective of biosensors. Biotechnol. Adv. 28: 232-254. https://doi.org/10.1016/j.biotechadv.2009.12.004
  3. R.Beuchat L. 1999. Listeria monocytogenes: incidence on vegetables Food Control 7: 6.
  4. Heiman KE, Garalde VB, Gronostaj M, Jackson KA, Beam S, Joseph L, et al. 2016. Multistate outbreak of listeriosis caused by imported cheese and evidence of cross-contamination of other cheeses, USA, 2012. Epidemiol. Infect. 144: 2698-2708. https://doi.org/10.1017/S095026881500117X
  5. Fawcett AMSL. 2002. Tracking and traceability in the meat processing industry: a solution. Br. Food J. 104: 13.
  6. Zhao X, Lin CW, Wang J, Oh DH. 2014. Advances in rapid detection methods for foodborne pathogens. J. Microbiol. Biotechnol. 24: 297-312. https://doi.org/10.4014/jmb.1310.10013
  7. Lundberg DS, Lebeis SL, Paredes SH, Yourstone S, Gehring J, Malfatti S, et al. 2012. Defining the core Arabidopsis thaliana root microbiome. Nature 488: 86-90. https://doi.org/10.1038/nature11237
  8. Janda JM, Abbott SL. 2007. 16S rRNA gene sequencing for bacterial identification in the diagnostic laboratory: pluses, perils, and pitfalls. J. Clin. Microbiol. 45: 2761-2764. https://doi.org/10.1128/JCM.01228-07
  9. Kim M, Lee KH, Yoon SW, Kim BS, Chun J, Yi H. 2013. Analytical tools and databases for metagenomics in the next-generation sequencing era. Genomics Inform. 11: 102-113. https://doi.org/10.5808/GI.2013.11.3.102
  10. Ku HJ, Lee JH. 2014. Development of a novel long-range 16S rRNA universal primer set for metagenomic analysis of gastrointestinal microbiota in newborn infants. J. Microbiol. Biotechnol. 24: 812-822. https://doi.org/10.4014/jmb.1403.03032
  11. Hanshew AS, Mason CJ, Raffa KF, Currie CR. 2013. Minimization of chloroplast contamination in 16S rRNA gene pyrosequencing of insect herbivore bacterial communities. J.Microbiol. Methods 95: 149-155. https://doi.org/10.1016/j.mimet.2013.08.007
  12. Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R. 2011. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27: 2194-2200. https://doi.org/10.1093/bioinformatics/btr381
  13. Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, et al. 2010. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7: 335-336. https://doi.org/10.1038/nmeth.f.303
  14. Cole JR, Chai B, Farris RJ, Wang Q, Kulam SA, McGarrell DM, et al. 2005. The Ribosomal Database Project (RDP-II): sequences and tools for high-throughput rRNA analysis. Nucleic Acids Res. 33: D294-296. https://doi.org/10.1093/nar/gki038
  15. Jose A Navas-Molina JMP-S, Antonio Gonzalez, Paul J McMurdie, Yoshiki Vazquez-Baeza, Zhenjiang Xu, Luke K Ursell, et al. 2013. Advancing our understanding of the human microbiome using QIIME. Methods Enzymol. 531: 371. https://doi.org/10.1016/B978-0-12-407863-5.00019-8
  16. Parks DH, Beiko RG. 2010. Identifying biologically relevant differences between metagenomic communities. Bioinformatics 26: 715-721. https://doi.org/10.1093/bioinformatics/btq041
  17. Doyle MP, Erickson MC. 2006. Reducing the carriage of foodborne pathogens in livestock and poultry. Poult. Sci. 85: 960-973. https://doi.org/10.1093/ps/85.6.960
  18. Burnett SL, Beuchat LR. 2001. Human pathogens associated with raw produce and unpasteurized juices, and difficulties in decontamination. J. Ind. Microbiol. Biotechnol. 27: 104-110. https://doi.org/10.1038/sj/jim/7000199
  19. Rahn K, De Grandis SA, Clarke RC, McEwen SA, Galan JE, Ginocchio C, et al. 1992. Amplification of an invA gene sequence of Salmonella typhimurium by polymerase chain reaction as a specific method of detection of Salmonella. Mol. Cell. Probes 6: 271-279. https://doi.org/10.1016/0890-8508(92)90002-f
  20. Miller RR, Montoya V, Gardy JL, Patrick DM, Tang P. 2013. Metagenomics for pathogen detection in public health. Genome Med. 5: 81. https://doi.org/10.1186/gm485
  21. Friedman CR, Neimann J, Wegener HC, Tauxe RV. 2000.
  22. Anonymous. 2004. Annual Report on Zoonoses in Denmark 2003.
  23. Anonymous. 2000. Annual report on zoonoses in Denmark 1999.
  24. Anonymous. 2002. Annual report on zoonoses in Denmark 2001.
  25. Weber A, Lembke C, Schafer R. 1985. [Isolation of Campylobacter jejuni and Campylobacter coli in fecal samples of healthy slaughter swine depending on the season]. Zentralbl. Veterinarmed. B. 32: 40-45. https://doi.org/10.1111/j.1439-0450.1985.tb01935.x
  26. Finlay RC, Mann ED, Horning JL. 1986. Prevalence of Salmonella and Campylobacter contamination in manitoba Swine carcasses. Can. Vet. J. 27: 185-187.
  27. Lammerding AM, Garcia MM, Mann ED, Robinson Y, Dorward WJ, Ruscott RB, et al. 1988. Prevalence of Salmonella and thermophilic Campylobacter in fresh pork, beef, veal and poultry in Canada. J. Food Prot. 51: 47-52. https://doi.org/10.4315/0362-028x-51.1.47
  28. Moore JE, Madden RH. 1998. Occurrence of thermophilic Campylobacter spp. in porcine liver in Northern Ireland. J. Food Prot. 61: 409-413. https://doi.org/10.4315/0362-028X-61.4.409
  29. Harvey RB, Young CR, Ziprin RL, Hume ME, Genovese KJ, Anderson RC, et al. 1999. Prevalence of Campylobacter spp. isolated from the intestinal tract of pigs raised in an integrated swine production system. J. Am. Vet. Med. Assoc. 215: 1601-1604.
  30. Brynestad S, Granum PE. 2002. Clostridium perfringens and foodborne infections. Int. J. Food Microbiol. 74: 195-202. https://doi.org/10.1016/S0168-1605(01)00680-8
  31. Suh J PO, Kang Y, Ahn JE, Jung JS, An YS, Park SH, et al. 2013. Risk assessment on nitrate and nitrite in vegetables available in Korean diet. J. Appl. Biol. Chem. 56: 205-211. https://doi.org/10.3839/jabc.2013.033
  32. Mafart P, Couvert O, Gaillard S, Leguerinel I. 2002. On calculating sterility in thermal preservation methods: application of the Weibull frequency distribution model. Int. J. Food Microbiol. 72: 107-113. https://doi.org/10.1016/S0168-1605(01)00624-9
  33. Anonymous. 2018. Foodborne disease outbreak.
  34. Hu WS, Kim H, Koo OK. 2018. Molecular genotyping, biofilm formation and antibiotic resistance of enterotoxigenic Clostridium perfringens isolated from meat supplied to school cafeterias in South Korea. Anaerobe 52: 115-121. https://doi.org/10.1016/j.anaerobe.2018.06.011
  35. Jeong D, Kim DH, Kang IB, Chon JW, Kim H, Om AS, et al. 2017. Prevalence and toxin type of Clostridium perfringens in beef from four different types of meat markets in Seoul, Korea. Food Sci. Biotechnol. 26: 545-548. https://doi.org/10.1007/s10068-017-0075-5
  36. Van Immerseel F, De Buck J, Pasmans F, Huyghebaert G, Haesebrouck F, Ducatelle R. 2004. Clostridium perfringens in poultry: an emerging threat for animal and public health. Avian Pathol. 33: 537-549. https://doi.org/10.1080/03079450400013162
  37. Asghar Arshi SN, Hamidreza Kabiri, Arman Akbarpour, Rassoul Hashemzehi, Behnaz Mansouri, Ayse Kilic, et al. 2017. Incidence of Clostridium perfringens in intestinal contents of domestic livestock detected by PCR. Int. J. Anim. Res. 1: 1-6.
  38. Balaban N, Rasooly A. 2000. Staphylococcal enterotoxins. Int. J. Food Microbiol. 61: 1-10. https://doi.org/10.1016/S0168-1605(00)00377-9
  39. Le Loir Y, Baron F, Gautier M. 2003. Staphylococcus aureus and food poisoning. Genet. Mol. Res. GMR 2: 63-76.
  40. Hennekinne JA, De Buyser ML, Dragacci S. 2012. Staphylococcus aureus and its food poisoning toxins: characterization and outbreak investigation. FEMS Microbiol. Rev. 36: 815-836. https://doi.org/10.1111/j.1574-6976.2011.00311.x
  41. Lowy FD. 2003. Antimicrobial resistance: the example of Staphylococcus aureus. J. Clin. Invest. 111: 1265-1273. https://doi.org/10.1172/JCI18535
  42. Fraser JD, Proft T. 2008. The bacterial superantigen and superantigen-like proteins. Immunol. Revi. 225: 226-243. https://doi.org/10.1111/j.1600-065X.2008.00681.x
  43. Spaulding AR, Salgado-Pabon W, Kohler PL, Horswill AR, Leung DY, Schlievert PM. 2013. Staphylococcal and streptococcal superantigen exotoxins. Clin. Microbiol. Rev. 26: 422-447. https://doi.org/10.1128/CMR.00104-12
  44. Baele M, Decostere A, Vandamme P, Ceelen L, Hellemans A, Mast J, et al. 2008. Isolation and characterization of Helicobactersuis sp. nov. from pig stomachs. Int. J. Syst. Evol. Microbiol. 58: 1350-1358. https://doi.org/10.1099/ijs.0.65133-0
  45. Haesebrouck F, Pasmans F, Flahou B, Smet A, Vandamme P, Ducatelle R. 2011. Non-Helicobacter pylori Helicobacter species in the human gastric mucosa: a proposal to introduce the terms H. heilmannii sensu lato and sensu stricto. Helicobacter 16: 339-340. https://doi.org/10.1111/j.1523-5378.2011.00849.x
  46. Cantet F, Magras C, Marais A, Federighi M, Megraud F. 1999. Helicobacter species colonizing pig stomach: molecular characterization and determination of prevalence. Appl. Environ. Microbiol. 65: 4672-4676. https://doi.org/10.1128/aem.65.10.4672-4676.1999
  47. Lowy FD. 1998. Staphylococcus aureus infections. New Eng. J. Med. 339: 520-532. https://doi.org/10.1056/NEJM199808203390806
  48. Freney J, Hansen W, Etienne J, Vandenesch F, Fleurette J. 1988. Postoperative infant septicemia caused by Pseudomonas luteola (CDC group Ve-1) and Pseudomonas oryzihabitans (CDC group Ve-2). J. Clin. Microbiol. 26: 1241-1243. https://doi.org/10.1128/jcm.26.6.1241-1243.1988
  49. Arnold DL, Preston GM. 2019. Pseudomonas syringae: enterprising epiphyte and stealthy parasite. Microbiology 165: 251-253. https://doi.org/10.1099/mic.0.000715
  50. Diggle SP, Whiteley M. 2020. Microbe Profile: Pseudomonas aeruginosa: opportunistic pathogen and lab rat. Microbiology 166: 30-33. https://doi.org/10.1099/mic.0.000860
  51. Van Delden C, Iglewski BH. 1998. Cell-to-cell signaling and Pseudomonas aeruginosa infections. Emerg. Infect. Dis. 4: 551-560. https://doi.org/10.3201/eid0404.980405
  52. Ryan KJ, Ray CG, Sherris JC. 2004. Sherris medical microbiology: an introduction to infectious diseases, pp. 997. 4th Ed. McGraw-Hill, New York, USA