PLANT BIOLOGY
ANIMAL BIOLOGY
SUBSCRIPTION
E-SUBSCRIPTION
 
MAP
MAIN PAGE

 

 

 

 

doi: 10.15389/agrobiology.2025.4.739eng

UDC: 619:614.36:579.63

 

SEASONAL PATTERNS AND ANTIBIOTIC RESISTANCE OF PATHOGENIC MICROORGANISMS AT A POULTRY PROCESSING PLANT

Yu.K. Yushina1 , A.A. Makhova1, E.V. Zaiko1,
A.A. Semenova1, D.S. Bataeva1, R.V. Nekrasov2

1V.M. Gorbatov Federal Center for Food Systems RAS, 26, ul. Talalikhina, Moscow,109316 Russia, e-mail a.semenova@fncps.ru, labsens@mail.ru, v.pchelkina@fncps.ru, v.nasonova@fncps.ru, spbsl21@gmail.com;
2Ernst Federal Research Center for Animal Husbandry, 60, pos. Dubrovitsy, Podolsk District, Moscow Province, 142132 Russia, e-mail nek_roman@mail.ru (✉ corresponding author), 652202@mail.ru

ORCID:
Yushina Yu.K. orcid.org/0000-0001-9265-5511
Semenova A.A. orcid.org/0000-0002-4372-6448
Makhova A.A. orcid.org/0000-0002-2508-2888
Bataeva D.S. orcid.org/0000-0002-1374-2746
Zaiko E.V. orcid.org/0000-0002-5048-9321
Nekrasov R.V. orcid.org/0000-0003-4242-2239

Final revision received December 04, 2024
Accepted April 04, 2025

Due to the steady growth of the Russian poultry industry, the problem of microbiological safety of products is of exceptional importance Special control is required for the pathogens Salmonella spp., Campylobacter spp. and Listeria monocytogenes, which can cause food poisoning, while cross-contamination from poultry processing facilities is a key risk for the release of dangerous products. The danger is increased by the transmission of antibiotic-resistant pathogens in the production environment. This study is the first to establish the seasonal and zonal specificity of pathogenic microorganism contamination on abiotic surfaces within a poultry processing facility. It detected the highest probability of detecting Campylobacter spp., Salmonella spp., and Listeria monocytogenes in both the dirty and clean zones of the plant during the summer and shoulder seasons, the dominance of Campylobacter jejuni among the pathogens (83 % of cases). Their localization was identified on equipment in the slaughter and cooling zones. A statistically significant reduction total number of mesophilic aerobic and facultative anaerobic microorganisms (Total Viable Count, TVC) was demonstrated only in the clean zone compared to the dirty and intermediate zones. A seasonal imbalance was shown: maximum TVC values were recorded during the shoulder season, while the peak detection of pathogens occurred in summer. The aim of the work was to study the total number of mesophilic aerobic and facultative anaerobic microorganisms on abiotic objects in the production environment depending on the season and to identify pathogenic microorganisms sensitive to antibiotics. Samples at the poultry processing plant (Moscow Province) were collected at different times of the year: summer (end of August 2021), winter (end of February 2021), and the shoulder season, autumn (end of September 2020). The research methodology involved collecting 72 swabs in the middle of the work shift from 12 abiotic surfaces not in contact with the product, located in the dirty, intermediate, and clean zones. Pathogen detection was carried out using loop-mediated isothermal amplification (LAMP) on a 3M MDS device (3M, USA) followed by microbiological confirmation of positive results in accordance with GOST. The sensitivity of the isolated isolates to antimicrobial drugs was determined by the disk diffusion method according to CLSI and EUCAST recommendations. Quantitative accounting of TVC/APC was performed by plating on PCA agar with incubation at 30 °C for 72 hours. Given the non-normal distribution of the obtained data (d = 0.47 > d* = 0.20, Smirnov-Kolmogorov test), statistical analysis was performed using non-parametric methods: two-factor rank analysis of variance and Duncan's test for multiple comparisons at a significance level of a = 0.1. As a result of the study, the seasonally-dependent and zone-specific nature of contamination was established for the first time. The probability of detecting at least one pathogen was 33 %, distributed as 42 % (dirty zone), 17 % (intermediate zone), and 42 % (clean zone) along the production process, and depending on seasonality — 50 % (summer), 42 % (shoulder season), and 8 % (winter). The probability of detecting at least one pathogen was 33%, while during the production process it was distributed as 42 % (dirty zone), 17 % (intermediate zone) and 42 % (clean zone), and depending on the seasonality — 50 % (summer), 42 % (off-season) and 8 % (winter). The ranking of pathogens by probability of detection showed the dominance of Campylobacter spp. (17 %), followed by Listeria monocytogenes (14 %) and Salmonella spp. (11 %). Campylobacter jejuni was mainly detected in the slaughter and primary treatment area. Salmonella spp. were found in all zones, including the clean one, and Listeria monocytogenes was concentrated in the finishing and packaging zone. All Salmonella spp. strains exhibited resistance to nalidixic acid; a number of strains also showed resistance to co-trimoxazole, moxifloxacin, sulfamethoxazole, and tetracycline. An atypical resistance profile was identified in the Salmonella strain S_1 which showed selective resistance to moxifloxacin while remaining susceptible to other fluoroquinolones, which may be associated with accumulated mutations in genes or plasmids. Analysis of the antibiotic susceptibility of Listeria monocytogenes revealed limited resistance, manifested mainly to ceftazidime and tetracycline. One of the five strains was susceptible to all antimicrobials, and multidrug-resistant phenotypes were not detected. Strains of the genus Campylobacterexhibited resistance to ciprofloxacin, erythromycin, and tetracycline. Some of the studied isolates were identified as multidrug-resistant. When evaluating the TVC, a statistically significant decrease was shown only in the clean zone — (4.16±2.27)×104 CFU/cm2 vs dirty (5.23±1.95)×106 CFU/cm2 and intermediate (8.88±5.74)×105 CFU/cm2 zones (p < 0.05), while contamination of dirty and intermediate the zones did not differ significantly. The maximum TVC values (1.07±0.47)×106 CFU/cm² were recorded during the shoulder season. Thus, the results obtained comprehensively characterize the abiotic surfaces of poultry processing plants as hidden reservoirs of pathogens and antibiotic-resistant strains demonstrating complex seasonal and zonal dynamics. The identified high probability of clean zone contamination, the circulation of multidrug-resistant isolates and seasonal risk peaks indicate the need to revise existing approaches to sanitary and microbiological control, develop preventive strategies based on regular monitoring of pathogens directly during production, and tighten measures to limit the use of antibiotics in poultry farming to ensure the biosafety of poultry production.

Keywords: swabs, Salmonella spp., Campylobacter spp., Listeria monocytogenes, total aerobic microbial count, TAMC, antibiotic resistance.

 

REFERENCES

  1. Makeeva Yu. Veterinariya i zhizn’. Informatsionniy portal i gazeta, 2023 goda. Available: https://vetandlife.ru/sobytiya/proizvodstvo-myasa-pticy-v-rossii-uvelichilos-na-4-9. Accessed: 05/18/2020 (in Russ.).
  2. Sharon A.J., Sathu T., Vasudevan, V.N., Mathew B., Athira P., Ajith M.C. Effect of slaughter operations on the microbial load of broiler duck carcasses. Int. J. Pure App. Biosci., 2018, 6(2): 84-89 CrossRef
  3. Ricke S.C., Dittoe D.K., Brown J.A., Thompson D.R. Practical opportunities for microbiome analyses and bioinformatics in poultry processing. Poultry Science, 2022, 101(5): 101787 CrossRef
  4. Chen S.H., Fegan N., Kocharunchitt C., Bowman J.P., Duffy L.L. Impact of poultry processing operating parameters on bacterial transmission and persistence on chicken carcasses and their shelf life. Applied and Environmental Microbiology, 2020, 86(12): e00594-20 CrossRef
  5. Vargas D.A., De Villena J.F., Larios V., Bueno López R., Chávez-Velado D.R., Casas D.E., Jiménez R.L., Blandon S.E., Sanchez-Plata M.X. Data-Mining poultry processing bio-mapping counts of pathogens and indicator organisms for food safety management decision making. Foods, 2023, 12(4): 898 CrossRef
  6. Sahoo M., Panigrahi C., Aradwad P. Management strategies emphasizing advanced food processing approaches to mitigate food borne zoonotic pathogens in food system. Food Frontiers, 2022, 3(4): 641-665 CrossRef
  7. FSIS-GD-2021-0005. FSIS guideline for controlling Salmonella in raw poultry. Available: https://www.fsis.usda.gov/sites/default/files/media_file/2021-07/FSIS-GD-2021-0005.pdf. Accessed: 05/18/2020.
  8. FSIS-GD-2021-0006. FSIS guideline for controlling Campylobacter in raw poultry. Available: https://www.fsis.usda.gov/sites/default/files/media_file/2021-07/FSIS-GD-2021-0006.pdf. Accessed: 05/18/2020.
  9. Chen H., Yan H., Xiu Y., Jiang L., Zhang J., Chen G., Yu X., Zhu H., Zhao X., Li Y., Tang W., Zhang X. Seasonal dynamics in bacterial communities of closed-cage broiler houses. Front. Vet. Sci., 2022, 9: 1019005 CrossRef
  10. Dávalos-Almeyda M., Guerrero A., Medina G., Dávila-Barclay A., Salvatierra G., Calderón M., Gilman R.H., Tsukayama P. Antibiotic use and resistance knowledge assessment of personnel on chicken farms with high levels of antimicrobial resistance: a cross-sectional survey in Ica, Peru. Antibiotics, 2022, 11(2): 190 CrossRef
  11. Vounba P., Arsenault J., Bada-Alambédji R., Fairbrother J.M. Prevalence of antimicrobial resistance and potential pathogenicity, and possible spread of third generation cephalosporin resistance, in Escherichia coli isolated from healthy chicken farms in the region of Dakar, Senegal. PLoS ONE, 2019, 14(3): e0214304 CrossRef
  12. CLSI. Performance Standards for Antimicrobial Disk Susceptibility Tests, M100S. 29th ed. Volume 39 CLSI. Wayne, PA, USA, 2019.
  13. The European Committee on Antimicrobial Susceptibility Testing. Breakpoint tables for interpretation of MICs and zone diameters. Version 12.0, 2022. Available: http://www.eucast.org. No date.
  14. Kallistova A.Yu., Sabrekov A.F., Goncharov V.M., Pimenov N.V., Glagolev M.V. Mikrobiologiya, 2019, 88(2): 230-239 CrossRef (in Russ.).
  15. Chlebicz A., Śliżewska K. Campylobacteriosis, salmonellosis, yersiniosis, and listeriosis as zoonotic foodborne diseases: a review. Int. J. Environ. Res. Public Health, 2018, 15(5): 863 CrossRef
  16. Kostoglou D., Simoni M., Vafeiadis G., Kaftantzis N.-M., Giaouris E. Prevalence of Campylobacter spp., Salmonella spp., and Listeria monocytogenes, and population levels of food safety indicator microorganisms in retail raw chicken meat and ready-to-eat fresh leafy greens salads sold in Greece. Foods, 2023, 12(24): 4502 CrossRef
  17. Lee H., Yoon Y. Etiological agents implicated in foodborne illness world wide. Food Science of Animal Resources, 2021, 41(1): 1-7 CrossRef
  18. Boubendir S., Arsenault J., Quessy S., Thibodeau A., Fravalo P., Thériault W.P., Fournaise S., Gaucher M.L. Salmonella contamination of broiler chicken carcasses at critical steps of the slaughter process and in the environment of two slaughter plants: prevalence, genetic profiles, and association with the final carcass status. Journal of Food Protection, 2021, 84(2): 321-332 CrossRef
  19. Shai B., Leishman E.M. Quality and processability of modern poultry meat. Animals, 2022, 12(20): 2766 CrossRef
  20. Reich F., Valero A., Schill F., Bungenstock L., Klein G. Characterisation of Campylobacter contamination in broilers and assessment of microbiological criteria for the pathogen in broiler slaughterhouses. Food Control, 2018, 87: 60-69 CrossRef
  21. Chen S.H., Fegan N., Kocharunchitt C., Bowman J.P., Duffy L.L. Changes of the bacterial community diversity on chicken carcasses through an Australian poultry processing line. Food Microbiology, 2020, 86: 103350 CrossRef
  22. Yenilmez F., Yılmaz N., Bulancak A., Uruk E., Baylan M., Baykal ÇelikL., Kutlu H. Comparison of dry and wet de-feathering methods on the quality characteristics and shelf life of broiler carcasses. Journal of Agricultural Sciences, 2023, 29(1): 343-351 CrossRef
  23. Kers J.G., Velkers F.C., Fischer E.A., Hermes G.D., Stegeman J.A., Smidt H. Host andenvironmental factors affecting the intestinal microbiota in chickens. Frontiers in Microbiology, 2018, 9: 235 CrossRef
  24. Marmion M., Ferone M.T., Whyte P., Scannell A.G.M. The changing microbiome of poultry meat; from farm to fridge. Food Microbiol., 2021, 99: 103823 CrossRef
  25. Wang W., Dang G., Khan I., Ye X., Liu L., Zhong R., Chen L., Ma T., Zhang H. Bacterial community characteristics shaped by artificial environmental PM2.5 control in intensive broiler houses. International Journal of Environmental Research and Public Health, 2023, 20(1): 723 CrossRef
  26. Loshchinin M.N., Sokolova N.A., Abdullaeva A.M. Health, Food & Biotechnology, 2020, 2(2): 22-32 CrossRef (in Russ.).
  27. Nagshetty K., Manjula N., Math G., Mohan A., Shivannavar C., Gaddad S. Resistance to fluoroquinolones and other antimicrobials in culture-positive Salmonella typhi isolates in Gulbarga, South India. Advances in Microbiology, 2021, 11: 16-26 CrossRef
  28. Gulyás D., Kamotsay K., Szabó D., Kocsis B. Investigation of delafloxacin resistance in multidrug-resistant Escherichia coli strains and the detection of E. coli ST43 international high-risk clone. Microorganisms, 2023, 11(6): 1602 CrossRef
  29. Becnel Boyd L., Maynard M.J., Morgan-Lin-nell S.K., Horton L.B., Sucgang R, Hamill R.J. Jimenez J.R., Versalovic J., Steffen D., Zechiedrich L. Relationships among ciprofloxacin, gatifloxacin, levofloxacin, and norfloxa-cin MICs for fluoroquinolone-resistant Escherichia coli clinical isolates. Antimicrobial Agents and Chemotherapy, 2009, 53(1): 229-234 CrossRef
  30. Morgan-Linnell S.K., Becnel Boyd L., Steffen D., Zechiedrich L. Mechanisms accounting for fluoroquinolone resistance in Escherichia coli clinical isolates. Antimicrobial Agents and Chemotherapy, 2009, 53(1): 235-241 CrossRef
  31. Castro-Vargas R.E., Herrera-Sánchez M.P., Rodríguez-Hernández R., Rondón-Barragán I.S. Antibiotic resistance in Salmonella spp. isolated from poultry: a global overview. Veterinary World, 2020, 13(10): 2070-2084 CrossRef
  32. Rakitin A.L., Yushina Y.K., Zaiko E.V., Bataeva D.S., Kuznetsova O.A., Semenova A.A., Ermolaeva S.A., Beletskiy A.V., Kolganova T.V., Mardanov A.V., Shapovalov S.O., Tkachik T.E. Evaluation of antibiotic resistance of Salmonella serotypes and whole-genome sequencing of multiresistant strains isolated from food products in Russia. Antibiotics, 2022, 11(1): 1 CrossRef
  33. Baquero F., Lanza V.F., Duval M., Coque T.M. Ecogenetics of antibiotic resistance in Listeria monocytogenes. Mol. Microbiol., 2020, 113(3): 570-579 CrossRef
  34. Andriyanov P.A., Zhurilov P.A., Liskova E.A., Karpova T.I., Sokolova E.V., Yushina Y.K., Zaiko E.V., Bataeva D.S., Voronina O.L., Psareva E.K., Tartakovsky I.S., Kolbasov D.V., Ermolaeva S.A. Antimicrobial resistance of Listeria monocytogenes strains isolated from humans, animals, and food products in Russia in 1950-1980, 2000-2005, and 2018-2021. Antibiotics, 2021, 10(10): 1206 CrossRef
  35. Gao F., Tu L., Chen M., Chen H., Zhang X., Zhuang Y., Luo J., Chen M. Erythromycin resistance of clinical Campylobacter jejuni and Campylobacter coli in Shanghai, China. Front. Microbiol., 2023, 14: 1145581 CrossRef
  36. Bolinger H.K., Zhang Q., Miler W.G., Kathariou S. Lack of evidence for erm(B) infiltration into erythromycin-resistant Campylobacter coli and Campylobacter jejuni from commercial Turkey production in Eastern North Carolina: a major Turkey-growing region in the United States. Foodborne Pathogens and Disease, 2018, 15(11): 698-700 CrossRef
  37. Tazalova E.V. Dal’nevostochniy meditsinskiy zhurnal, 2012, 3: 120-123 (in Russ.).
  38. Efimochkina N.R., Korotkevich Yu.V., Stetsenko V.V., Pichugina T.V., Bikova I.B., Markova Yu.M., Minaeva L.P., Sheveleva S.A. Voprosi pitaniya, 2017, 86(1): 17-27 (in Russ.).

 

back

 


CONTENTS

 

Full article PDF (Rus)