Isolation and Identification of Major Bacterial Contaminants in Beef and Abattoir Environment at Nekemte Municipal Abattoir, Western Ethiopia

Isolation and Identification of Major Bacterial Contaminants in Beef and Abattoir Environment at Nekemte Municipal Abattoir, Western Ethiopia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Isolation and Identification of Major Bacterial Contaminants in Beef and Abattoir Environment at Nekemte Municipal Abattoir, Western Ethiopia Abdi kidane Mengesha, Jobir Tesfa Adino, Tariku Desta Gelgelo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9008197/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 15 You are reading this latest preprint version Abstract Background foodborne disease caused by bacterial contamination of meat represent a major global public health challenge, particularly in developing countries where hygienic practices during meat processing are often inadequate. Objectives this study aimed to isolate and identify major bacterial contaminants from beef, abattoir equipment and workers hands at Nekemte municipal abattoir, western Ethiopia. Methods a cross sectional study was conducted from November 2024 to January 2025. A total of 92 sample were collected, including meat (n = 37), workers hand swabs (n = 30) and knife swabs (n = 25). Standard bacteriological culture techniques and biochemical tests were used for pathogen identification. Data were analyzed using SPSS version 16. Chi-square tests were performed to assess associations, with statistical significance set at p < 0.05. Result the overall prevalence of bacterial contamination was 56.52% (52/92).knife swabs showed the highest contamination rate (64.00%), followed by workers hand swabs (56.67%) and meat samples (51.35%). Salmonella spp. Were the most frequently isolated pathogens (42.31%), followed by Staphylococcus aureus (28.85%) and Escherichia coli (28.85%). No statistical significant contamination (p = 0.615). Conclusion the high prevalence of bacterial contamination indicates inadequate hygienic practices in the abattoir. Strengthening sanitation measures. Implementing structured training programs and adopting standardized food safety systems are recommended to improve meat safety. Bacterial contamination Meat hygiene Beef Salmonella spp Staphylococcus aureus Escherichia coli Ethiopia INTRODUCTION Foodborne disease remain a major global public health concern. According to the world health organization (WHO), approximately 600 million cases of foodborne illness and 420,000 deaths occur annually due to the consumption of contaminated food [ 1 ]. Among bacterial pathogens, salmonella species are responsible for an estimated 98.8 million cases of gastroenteritis and approximately 155,000 deaths worldwide each year [ 2 ]. In the United State alone, the Center for Disease Control and Prevention (CDC) reports approximately 1.35 million infections, 26,500 hospitalizations and 420 deaths annually due to salmonella infection [ 3 ]. Meat is an important source of high- quality protein and essential nutrients in the human diet. However, it is highly susceptible to microbial contamination due to its rich nutrient composition and moisture content (70–73%water, 20–22% protein and approximately 5% lipids). This composition provides an ideal environment for microbial growth. Although muscle tissue from healthy animals is sterile, contamination frequently occurs during slaughtering, dressing, processing, transportation and marketing [ 4 ] Microbial contamination may originate from animals skin, gastrointestinal tract, processing equipment, water sources, handlers hands, air processing equipment, water sources, hygiene practices during meat handling significantly increase the risk of contamination with pathogenic bacteria such as Escherichia coli, Salmonella spp. and Staphylococcus aureus [ 5 ]. Foodborne pathogens are responsible for more than 200 diseases, ranging from mild gastrointestinal disorders to sever systemic infections. Children under five years age account for approximately 40% of foodborne disease cases globally [ 6 ]. The economic burden associated with foodborne diseases includes healthcare costs, productivity loss and trade restrictions. Several bacterial pathogens are commonly associated with meat contamination, including E. coli, non-typhoid salmonella, campylobacter, listeria monocytogenes, Staphylococcus aureus and clostridium species [ 7 ]. These pathogens may originate from infected animals, contaminated equipment, handles or unsanitary environmental conditions. In Ethiopia, limited data are available regarding bacterial contamination along the meat production chain, particularly at municipal abattoirs. Therefore assessing bacterial contamination and identifying major pathogens is essential for developing effective intervention strategies. The objectives of the study To determine the major bacterial contaminations along the meat production value chain at Nekemte Municipal Abattoir. To isolate and identify major pathogenic bacteria present in beef samples. To assess contamination levels associated with equipment and workers hands. MATERIALS AND METHODS Study Area The study was conducted at Nekemte Municipal Abattoir, located in Nekemte Town, East Wollega Zone, Oromia Regional State, Western Ethiopia and approximately 335 Km west of Addis Ababa. The town lies at an attitude ranging from 1960 to 2170 meters above sea level and receives an annual rainfall of 1500-2200mm. The abattoir slaughters an average of 30 cattle per day. Study Design A cross-sectional study was conducted from November 2024 to January 2025 to isolate and identify major bacterial contaminants from beef and abattoir environments. Sample Size and Sampling Techniques A total of 92 samples were collected using purposive sampling based on the daily slaughter rate and availability of cattle, 37 meat sample, 30 workers hand swabs and 25 knife swabs samples were collected aseptically. Sample Collection and Transportation Beef samples were collected from cattle slaughtered at Nekemte Municipal Abattoir that were sourced from surrounding districts and local livestock markets. Swab samples were collected using sterile cotton swabs moistened with buffered peptone water. A 100 cm 2 surface area was swabbed according to ISO 17604 (2005) guidelines. Swabs were placed into sterile tubes containing 10 ml of buffered peptone water and transported in an ice box to the microbiology laboratory for analysis. Bacteriological Isolation and Identification Isolation and Identification of Staphylococcus Aureus Isolation and identification of staphylococcus aureus were conducted following standard microbiological procedure based on ISO guidelines. 50ul of pre-enriched sample in buffered peptone water streaked onto tryptic Soya Agar (TSA) supplemented with 5% of sheep blood and incubated aerobically at 37 0 C for 24 hours. Presumptive colonies were subcultured onto mannitol Salt Agar (MSA). Yellow colonies surrounded by yellow zones after incubation at 37 0 C for 24 hours were considered presumptive S. aureus due to mannitol fermentation. Further identification was performed based on, colony morphology (round, smooth, golden-yellow colonies), hemolytic pattern on blood agar, gram staining (gram-positive cocci in cluster) and catalase test (positive reaction indicated by bubble formation were observed. Isolation and Identification of Escherichia coli Detection of E. coli was performed according to ISO standard procedures. Swab sample were inoculated into 9 ml of modified Tryptone Soya Broth and incubated at 41 0 C for 24 hours. Following enrichment, sample were streaked onto MacConkey agar and incubated at 37 0 C for 24 hours. Pink lactose fermenting colonies were considered presumptive E.coli. These colonies were further subcultured on to Eosin Methylene Blue (EMB) Agar. Colonies exhibiting a characteristic Metallic green sheen were identified as presumptive E. coli. Confirmation was performed using gram staining (gram negative rods), KOH test (positive with production blue color), Citrate utilization test and triple sugar iron (TSI) agar reaction with gas production and no H 2 S production. Identification and Isolation of Salmonella spp For salmonella isolation, 10 g of each sample was pre-enriched in lactose broth and incubated at 37 0 C for 24 hours. Selective enrichment was performed using selenite Broth, incubated at 37 0 C for 24 hours [ 12 ]. After enrichment, sample were streaked onto bismuth sulfite agar (BSA) and incubated at 37 0 C for 24hours [ 11 ] Presumptive salmonella colonies were identified based on; black or greenish colonies on BSA, Gram negative rod by gram stain and also identified by secondary biochemical test and characterized by oxidase negative by oxidase test, indole test negative, methyl red test positive, voges-proskauer (VP) test negative and TSI test positive with alkaline slant/acid butt with H 2 S production. Data Analysis Data were entered into Microsoft Excel and analyzed using statistical package for social science (SPSS) version 16. Descriptive statistics were used to calculate: prevalence (%) and frequency distributions. The chi-square (X 2 ) test was used to assess association between sample types and bacterial contamination. Statistical significance was determined at a 95% confidence interval with p-value < 0.05 considered statistically significant. RESULTS Overall Prevalence of Bacterial Contamination Out of 92 total samples examined, 52 (56.52%) were positive for bacterial contamination. Contamination by Sample Type Table 1 Prevalence of bacterial contamination by sample type Sample type Examined (n) Positive (n) Negative (n) Prevalence (%) Meat 37 19 18 51.35% Worker hand swab 30 17 13 56.67% Knife swab 25 16 9 64.00% Total 92 52 40 56.52% The highest contamination rate was observed in knife swabs (64.00%), followed by workers hand swabs (56.67%) and meat samples (51.35%). The chi-square analysis showed no statistically significant association between sample types and contamination (X 2 = 0.972, P = 0.615). Distribution of Bacterial Isolates Table 2 Frequency and percentage of isolated bacterial pathogens Bacterial Isolate Frequency (n) Percentage (n) Salmonella spp. 22 42.31% Staphylococcus aureus 15 28.85% Escherichia coli 15 28.85% Total 52 100% Salmonella spp. Were the most predominant isolates (42.31%), followed by S. aureus and E. coli, each accounting for 28.85% of the isolates. DISCUSSION The present study revealed an overall bacterial contamination prevalence of 56.52% among sample collected from beef, workers hand and knifes at Nekemte municipal abattoir. This finding indicates a substantial level of microbial contamination within the meat production environment and highlights potential public health risk associated with beef consumption in the study is compared to findings reported in similar investigations conducted in developing countries, where inadequate hygienic practices and limited sanitation infrastructure contributed significantly to meat contamination. Studies conducted in Nigeria and other African regions have reported similar contamination levels in abattoir environments, emphasizing the persistent challenges of meat hygiene in resource limited setting [ 8 , 9 ]. The highest contamination rate was recorded in knife swabs (64.00%), followed by workers hand swabs (56.67%) and meat samples (51.35%). Although the chi-square test showed no significant association between sample type and contamination (p > 0.05). The higher contamination observed on knifes suggests inadequate sanitation and improper cleaning protocols. Knifes serve as direct contact surfaces during carcass processing, if not properly sterilized between slaughtering procedures, they can act as mechanical vectors, transferring pathogens from one carcass to another. This cross contamination pathway in well documented in meat hygiene literature. Similarly, contamination of workers hands indicates poor personal hygiene practices. Handling meat without proper handwashing, using disinfectants or wearing protective gloves increases the risk of bacterial transmission. The findings support previous reports indicating that food handlers play a critical role in microbial dissemination within meat processing environments [ 10 ] Salmonella spp. Were the most frequently isolated pathogens (42.31%). This high prevalence suggests significant fecal contamination during slaughtering and processing. Salmonella is commonly associated with the gastrointestinal tract of animals and can contaminate carcass during slaughtering if proper handing is not maintained. The predominance of salmonella in this study aligns with global reports identifying it as one of the leading causes of foodborne gastrointestitis. Its presence in meat and contact surfaces is a strong indicator of inadequate hygienic measures during slaughtering and carcass dressing. The isolation S. aureus (28.85%) suggests contamination originating from human (handlers), as this organism is commonly found on human skin, nasal passages and hands. Poor personal hygiene practices such as sneezing, coughing or handling meat without gloves can introduce this pathogen into the processing environment. The presence of S. aureus is particularly concerning due to its ability to produce heat stable enterotoxins, which may cause food poisoning even after cooking. The detection of Escherichia coli (28.85%) indicates fecal contamination and inadequate sanitary conditions. E. coli is widely recognized as an indicator organism for hygiene quality in meat production. Its presence suggests improper slaughtering techniques, contamination from intestinal contents or unsanitary water used during processing. Comparable findings have been reported in studies assessing microbial contamination in abattoirs and butcher shops, where E. coli was frequently isolated from meat and contact surfaces [ 8 ]. The simultaneous presence of salmonella, S. aureus and E. coli demonstrates multiple contamination routes including; fecal contamination, cross contamination from equipment and handlers. This findings highlight significant public health concerns, particularly in areas where raw or un cooked meat consumption is common. The risk is further exacerbated by inadequate refrigeration and transportation systems, which allow bacterial proliferation. Foodborne infections not only affect individual health but also impose economic burdens through healthcare costs and productivity losses. Therefore, improving hygienic practices within abattoir is essential for safeguarding community health. Although this study provides important insights into bacterial contamination at Nekemte municipal abattoir, several limitations should be acknowledged: The study relied solely on conventional culture and biochemical identification methods without molecular confirmation. Antimicrobial susceptibility testing was not performed. The sample size was relatively limited to one municipal abattoir. Future studies incorporating molecular techniques and antimicrobial resistance profiling would provide more comprehensive epidemiological data. CONCLUSION This study demonstrated a substantial level of bacterial contamination (56.52%) in beef and abattoir related contact surfaces at Nekemte Municipal Abattoir. The highest contamination was observed in knife swabs (64.00%), followed by workers hand swabs (56.67%) and meat sample (51.35%). Among the isolated pathogens, salmonella spp. Were the most predominant (42.31), followed by S. aureus (28.85%) and E. coli (28.85%). The detection of these pathogens indicates multiple contamination routes, including fecal contamination, cross contamination from equipment and poor personal hygiene practices among meat handlers. The presence of these foodborne pathogens in meat and contact surfaces highlights inadequate sanitation procedures, insufficient hygienic practices and limited implementation of preventive control measures in abattoir. If not addressed, these conditions pose significant public health risk, particularly in communities where raw or uncooked meat consumption is common. Overall, the findings underscore the urgent need for improved meat hygiene management system to ensure food safety and protect public health in the study area. RECOMMENDATIONS Based on the findings of this stud, the following recommendations are proposed: Strengthening hygienic practices through regular cleaning and disinfection of knife, equipment and processing surfaces should be strictly enforced. Implementation of standardized sanitation protocols before, during and after slaughtering operation. Periodic training programs should be organized for abattoir workers on personal hygiene, safe meat handling practices and prevention of cross contamination Implementation of meat safety control systems, routine microbiological monitoring of meat and contact surfaces and regularly medical screening of abattoir workers. Provision of adequate water supply and sanitation facilities, uses of refrigerated transport systems to maintain cold chain integrity and separation of clean and dirty processing areas to reduce cross contamination. For the future research Molecular identification and antimicrobial susceptibility testing to assess resistance patterns must have established Abbreviations BPW Buffered Peptone Water BSA Bismuth Sulfite Agar CDC Central for Disease Control EMB Eosin Methylene Blue ISO International for Organization Standardization KOH Potassium Hydroxide LB Lactose Broth MBD Meat borne Disease MR Methyl-Red MSA Mannitol salt Agar SB Selenite Broth SPSS Statistical Package for social Science SVM School Veterinary Medicine TSA Triple sugar Iron TSA Triple sugar Agar VP Voges Proskauer WHO World Health Organization Declarations Ethics Approval and Consent to Participate Ethical approval for this study was obtained from the institutional review board (IBR) of Wollega University. The study was conducted in accordance with the principle of Declaration of Helsinki. Informed consent was obtained from all abattoir worker prior to collecting hand swab samples. Participation in the study was voluntary and confidentiality of the participants was maintained throughout the research process. Consent for Publication Not applicable AVAILABILITY OF DATA AND MATERIALS The datasets generated and analyzed during the current study are available from corresponding author upon reasonable request. COMPETING INTERESTS The authors declare that they have no competing interests. FUNDING No specific funding was received for this study. References Organization WH. WHO estimates of the global burden of foodborne diseases: foodborne disease burden epidemiology reference group 2007–2015. World Health Organization; 2015. Majowicz SE, Musto J, Scallan E, Angulo FJ, Kirk M, O’Brien SJ, Jones TF, Fazil A, Hoekstra RM. (2010). The global burden of nontyphoidal salmonella gastroenteritis. In Clinical Infectious Diseases (Vol. 50, pp. 882–889). https://doi.org/10.1086/650733 Papp JR. (2024). CDC laboratory recommendations for syphilis testing, United States, 2024. MMWR Recommendations Rep, 73 . Pal M. (2018). Microbiological and hygienic quality of Meat and Meat Products . Newell DG, Koopmans M, Verhoef L, Duizer E, Aidara-Kane A, Sprong H, Opsteegh M, Langelaar M, Threfall J, Scheutz F, der Giessen J, Kruse H. (2010). Food-borne diseases - The challenges of 20years ago still persist while new ones continue to emerge. International Journal of Food Microbiology , 139 . https://doi.org/10.1016/j.ijfoodmicro.2010.01.021 Oliver SP, Jayarao BM, Almeida RA. (2005). Foodborne pathogens in milk and the dairy farm environment: Food safety and public health implications. In Foodborne Pathogens and Disease (Vol. 2, pp. 115–129). https://doi.org/10.1089/fpd.2005.2.115 Bauerfeind R, Von Graevenitz A, Kimmig P, Schiefer HG, Schwarz T, Slenczka W, Zahner H. Zoonoses: Infectious diseases transmissible from animals to humans. Wiley; 2020. Ukut I-OE, Okonko IO, Ikpoh IS, Nkang AO, Udeze AO, Babalola TA, Mejeha OK, Fajobi EA. (2010). ASSESSMENT OF BACTERIOLOGICAL QUALITY OF FRESH MEATS SOLD IN CALABAR METROPOLIS, NIGERIA. Https://Openurl.Ebsco.Com/EPDB%3Agcd%3A15%3A7852719/Detailv2?Sid=ebsco%3Aplink%3Ascholar&id=ebsco%3Agcd%3A47789876&crl = c&link_origin=scholar.Google.Com. Enabulele SA, Uraih N. Enterohaemorrhagic Escherichia coli 0157: H7 Prevalence in meat and vegetables sold in Benin City, Nigeria. Afr J Microbiol Res. 2009;3(5):276–9. Castro A, Santos C, Meireles H, Silva J, Teixeira P. Food handlers as potential sources of dissemination of virulent strains of Staphylococcus aureus in the community. J Infect Public Health. 2016;9:153–60. https://doi.org/10.1016/j.jiph.2015.08.001 . Özkalp B. Isolation and identification of Salmonellas from different samples. InTech Published. 2012;1:123–56. Hammack TS, Amaguaña RM, June GA, Sherrod PS, Andrews WH. Relative effectiveness of selenite cystine broth, tetrathionate broth, and Rappaport-Vassiliadis medium for the recovery of Salmonella spp. from foods with a low microbial load. J Food Prot. 1999;62:16–21. https://doi.org/10.4315/0362-028X-62.1.16 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 09 Apr, 2026 Reviews received at journal 09 Apr, 2026 Reviewers agreed at journal 07 Apr, 2026 Reviewers agreed at journal 03 Apr, 2026 Reviews received at journal 03 Apr, 2026 Reviewers agreed at journal 02 Apr, 2026 Reviewers agreed at journal 01 Apr, 2026 Reviewers agreed at journal 01 Apr, 2026 Reviewers agreed at journal 01 Apr, 2026 Reviewers agreed at journal 01 Apr, 2026 Reviewers invited by journal 01 Apr, 2026 Editor invited by journal 01 Apr, 2026 Editor assigned by journal 12 Mar, 2026 Submission checks completed at journal 12 Mar, 2026 First submitted to journal 12 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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According to the world health organization (WHO), approximately 600\u0026nbsp;million cases of foodborne illness and 420,000 deaths occur annually due to the consumption of contaminated food [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Among bacterial pathogens, salmonella species are responsible for an estimated 98.8\u0026nbsp;million cases of gastroenteritis and approximately 155,000 deaths worldwide each year [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In the United State alone, the Center for Disease Control and Prevention (CDC) reports approximately 1.35\u0026nbsp;million infections, 26,500 hospitalizations and 420 deaths annually due to salmonella infection [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMeat is an important source of high- quality protein and essential nutrients in the human diet. However, it is highly susceptible to microbial contamination due to its rich nutrient composition and moisture content (70\u0026ndash;73%water, 20\u0026ndash;22% protein and approximately 5% lipids). This composition provides an ideal environment for microbial growth. Although muscle tissue from healthy animals is sterile, contamination frequently occurs during slaughtering, dressing, processing, transportation and marketing [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eMicrobial contamination may originate from animals skin, gastrointestinal tract, processing equipment, water sources, handlers hands, air processing equipment, water sources, hygiene practices during meat handling significantly increase the risk of contamination with pathogenic bacteria such as Escherichia coli, Salmonella spp. and Staphylococcus aureus [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFoodborne pathogens are responsible for more than 200 diseases, ranging from mild gastrointestinal disorders to sever systemic infections. Children under five years age account for approximately 40% of foodborne disease cases globally [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The economic burden associated with foodborne diseases includes healthcare costs, productivity loss and trade restrictions. Several bacterial pathogens are commonly associated with meat contamination, including E. coli, non-typhoid salmonella, campylobacter, listeria monocytogenes, Staphylococcus aureus and clostridium species [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. These pathogens may originate from infected animals, contaminated equipment, handles or unsanitary environmental conditions.\u003c/p\u003e \u003cp\u003eIn Ethiopia, limited data are available regarding bacterial contamination along the meat production chain, particularly at municipal abattoirs. Therefore assessing bacterial contamination and identifying major pathogens is essential for developing effective intervention strategies.\u003c/p\u003e\n\u003ch3\u003eThe objectives of the study\u003c/h3\u003e\n\u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eTo determine the major bacterial contaminations along the meat production value chain at Nekemte Municipal Abattoir.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTo isolate and identify major pathogenic bacteria present in beef samples.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTo assess contamination levels associated with equipment and workers hands.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy Area\u003c/h2\u003e \u003cp\u003e The study was conducted at Nekemte Municipal Abattoir, located in Nekemte Town, East Wollega Zone, Oromia Regional State, Western Ethiopia and approximately 335 Km west of Addis Ababa. The town lies at an attitude ranging from 1960 to 2170 meters above sea level and receives an annual rainfall of 1500-2200mm. The abattoir slaughters an average of 30 cattle per day.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Design\u003c/h3\u003e\n\u003cp\u003eA cross-sectional study was conducted from November 2024 to January 2025 to isolate and identify major bacterial contaminants from beef and abattoir environments.\u003c/p\u003e\n\u003ch3\u003eSample Size and Sampling Techniques\u003c/h3\u003e\n\u003cp\u003eA total of 92 samples were collected using purposive sampling based on the daily slaughter rate and availability of cattle, 37 meat sample, 30 workers hand swabs and 25 knife swabs samples were collected aseptically.\u003c/p\u003e\n\u003ch3\u003eSample Collection and Transportation\u003c/h3\u003e\n\u003cp\u003e Beef samples were collected from cattle slaughtered at Nekemte Municipal Abattoir that were sourced from surrounding districts and local livestock markets.\u003c/p\u003e \u003cp\u003eSwab samples were collected using sterile cotton swabs moistened with buffered peptone water. A 100 cm\u003csup\u003e2\u003c/sup\u003e surface area was swabbed according to ISO 17604 (2005) guidelines. Swabs were placed into sterile tubes containing 10 ml of buffered peptone water and transported in an ice box to the microbiology laboratory for analysis.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eBacteriological Isolation and Identification\u003c/h2\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003eIsolation and Identification of Staphylococcus Aureus\u003c/h2\u003e \u003cp\u003e Isolation and identification of staphylococcus aureus were conducted following standard microbiological procedure based on ISO guidelines. 50ul of pre-enriched sample in buffered peptone water streaked onto tryptic Soya Agar (TSA) supplemented with 5% of sheep blood and incubated aerobically at 37\u003csup\u003e0\u003c/sup\u003eC for 24 hours.\u003c/p\u003e \u003cp\u003ePresumptive colonies were subcultured onto mannitol Salt Agar (MSA). Yellow colonies surrounded by yellow zones after incubation at 37\u003csup\u003e0\u003c/sup\u003eC for 24 hours were considered presumptive S. aureus due to mannitol fermentation. Further identification was performed based on, colony morphology (round, smooth, golden-yellow colonies), hemolytic pattern on blood agar, gram staining (gram-positive cocci in cluster) and catalase test (positive reaction indicated by bubble formation were observed.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eIsolation and Identification of Escherichia coli\u003c/h3\u003e\n\u003cp\u003eDetection of E. coli was performed according to ISO standard procedures. Swab sample were inoculated into 9 ml of modified Tryptone Soya Broth and incubated at 41\u003csup\u003e0\u003c/sup\u003eC for 24 hours. Following enrichment, sample were streaked onto MacConkey agar and incubated at 37\u003csup\u003e0\u003c/sup\u003eC for 24 hours.\u003c/p\u003e \u003cp\u003ePink lactose fermenting colonies were considered presumptive E.coli. These colonies were further subcultured on to Eosin Methylene Blue (EMB) Agar. Colonies exhibiting a characteristic Metallic green sheen were identified as presumptive E. coli. Confirmation was performed using gram staining (gram negative rods), KOH test (positive with production blue color), Citrate utilization test and triple sugar iron (TSI) agar reaction with gas production and no H\u003csub\u003e2\u003c/sub\u003eS production.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eIdentification and Isolation of Salmonella spp\u003c/h2\u003e \u003cp\u003eFor salmonella isolation, 10 g of each sample was pre-enriched in lactose broth and incubated at 37\u003csup\u003e0\u003c/sup\u003eC for 24 hours. Selective enrichment was performed using selenite Broth, incubated at 37\u003csup\u003e0\u003c/sup\u003eC for 24 hours [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. After enrichment, sample were streaked onto bismuth sulfite agar (BSA) and incubated at 37\u003csup\u003e0\u003c/sup\u003eC for 24hours [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/p\u003e \u003cp\u003ePresumptive salmonella colonies were identified based on; black or greenish colonies on BSA, Gram negative rod by gram stain and also identified by secondary biochemical test and characterized by oxidase negative by oxidase test, indole test negative, methyl red test positive, voges-proskauer (VP) test negative and TSI test positive with alkaline slant/acid butt with H\u003csub\u003e2\u003c/sub\u003eS production.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eData were entered into Microsoft Excel and analyzed using statistical package for social science (SPSS) version 16. Descriptive statistics were used to calculate: prevalence (%) and frequency distributions.\u003c/p\u003e \u003cp\u003eThe chi-square (X\u003csup\u003e2\u003c/sup\u003e) test was used to assess association between sample types and bacterial contamination. Statistical significance was determined at a 95% confidence interval with p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eOverall Prevalence of Bacterial Contamination\u003c/h2\u003e \u003cp\u003eOut of 92 total samples examined, 52 (56.52%) were positive for bacterial contamination.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eContamination by Sample Type\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrevalence of bacterial contamination by sample type\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExamined (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePositive (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNegative (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePrevalence (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e51.35%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWorker hand swab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e56.67%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKnife swab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e64.00%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e56.52%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe highest contamination rate was observed in knife swabs (64.00%), followed by workers hand swabs (56.67%) and meat samples (51.35%). The chi-square analysis showed no statistically significant association between sample types and contamination (X\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.972, P\u0026thinsp;=\u0026thinsp;0.615).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eDistribution of Bacterial Isolates\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFrequency and percentage of isolated bacterial pathogens\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBacterial Isolate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage (n)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSalmonella spp.\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.31%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eStaphylococcus aureus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.85%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eEscherichia coli\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.85%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSalmonella spp. Were the most predominant isolates (42.31%), followed by S. aureus and E. coli, each accounting for 28.85% of the isolates.\u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe present study revealed an overall bacterial contamination prevalence of 56.52% among sample collected from beef, workers hand and knifes at Nekemte municipal abattoir. This finding indicates a substantial level of microbial contamination within the meat production environment and highlights potential public health risk associated with beef consumption in the study is compared to findings reported in similar investigations conducted in developing countries, where inadequate hygienic practices and limited sanitation infrastructure contributed significantly to meat contamination. Studies conducted in Nigeria and other African regions have reported similar contamination levels in abattoir environments, emphasizing the persistent challenges of meat hygiene in resource limited setting [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe highest contamination rate was recorded in knife swabs (64.00%), followed by workers hand swabs (56.67%) and meat samples (51.35%). Although the chi-square test showed no significant association between sample type and contamination (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The higher contamination observed on knifes suggests inadequate sanitation and improper cleaning protocols. Knifes serve as direct contact surfaces during carcass processing, if not properly sterilized between slaughtering procedures, they can act as mechanical vectors, transferring pathogens from one carcass to another. This cross contamination pathway in well documented in meat hygiene literature.\u003c/p\u003e \u003cp\u003eSimilarly, contamination of workers hands indicates poor personal hygiene practices. Handling meat without proper handwashing, using disinfectants or wearing protective gloves increases the risk of bacterial transmission. The findings support previous reports indicating that food handlers play a critical role in microbial dissemination within meat processing environments [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eSalmonella spp. Were the most frequently isolated pathogens (42.31%). This high prevalence suggests significant fecal contamination during slaughtering and processing. Salmonella is commonly associated with the gastrointestinal tract of animals and can contaminate carcass during slaughtering if proper handing is not maintained. The predominance of salmonella in this study aligns with global reports identifying it as one of the leading causes of foodborne gastrointestitis. Its presence in meat and contact surfaces is a strong indicator of inadequate hygienic measures during slaughtering and carcass dressing.\u003c/p\u003e \u003cp\u003eThe isolation S. aureus (28.85%) suggests contamination originating from human (handlers), as this organism is commonly found on human skin, nasal passages and hands. Poor personal hygiene practices such as sneezing, coughing or handling meat without gloves can introduce this pathogen into the processing environment. The presence of S. aureus is particularly concerning due to its ability to produce heat stable enterotoxins, which may cause food poisoning even after cooking.\u003c/p\u003e \u003cp\u003eThe detection of Escherichia coli (28.85%) indicates fecal contamination and inadequate sanitary conditions. E. coli is widely recognized as an indicator organism for hygiene quality in meat production. Its presence suggests improper slaughtering techniques, contamination from intestinal contents or unsanitary water used during processing. Comparable findings have been reported in studies assessing microbial contamination in abattoirs and butcher shops, where E. coli was frequently isolated from meat and contact surfaces [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe simultaneous presence of salmonella, S. aureus and E. coli demonstrates multiple contamination routes including; fecal contamination, cross contamination from equipment and handlers. This findings highlight significant public health concerns, particularly in areas where raw or un cooked meat consumption is common. The risk is further exacerbated by inadequate refrigeration and transportation systems, which allow bacterial proliferation.\u003c/p\u003e \u003cp\u003eFoodborne infections not only affect individual health but also impose economic burdens through healthcare costs and productivity losses. Therefore, improving hygienic practices within abattoir is essential for safeguarding community health. Although this study provides important insights into bacterial contamination at Nekemte municipal abattoir, several limitations should be acknowledged:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eThe study relied solely on conventional culture and biochemical identification methods without molecular confirmation.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eAntimicrobial susceptibility testing was not performed.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eThe sample size was relatively limited to one municipal abattoir.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eFuture studies incorporating molecular techniques and antimicrobial resistance profiling would provide more comprehensive epidemiological data.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study demonstrated a substantial level of bacterial contamination (56.52%) in beef and abattoir related contact surfaces at Nekemte Municipal Abattoir. The highest contamination was observed in knife swabs (64.00%), followed by workers hand swabs (56.67%) and meat sample (51.35%). Among the isolated pathogens, salmonella spp. Were the most predominant (42.31), followed by S. aureus (28.85%) and E. coli (28.85%). The detection of these pathogens indicates multiple contamination routes, including fecal contamination, cross contamination from equipment and poor personal hygiene practices among meat handlers. The presence of these foodborne pathogens in meat and contact surfaces highlights inadequate sanitation procedures, insufficient hygienic practices and limited implementation of preventive control measures in abattoir. If not addressed, these conditions pose significant public health risk, particularly in communities where raw or uncooked meat consumption is common.\u003c/p\u003e \u003cp\u003eOverall, the findings underscore the urgent need for improved meat hygiene management system to ensure food safety and protect public health in the study area.\u003c/p\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eRECOMMENDATIONS\u003c/h2\u003e \u003cp\u003eBased on the findings of this stud, the following recommendations are proposed:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eStrengthening hygienic practices through regular cleaning and disinfection of knife, equipment and processing surfaces should be strictly enforced. Implementation of standardized sanitation protocols before, during and after slaughtering operation.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePeriodic training programs should be organized for abattoir workers on personal hygiene, safe meat handling practices and prevention of cross contamination\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eImplementation of meat safety control systems, routine microbiological monitoring of meat and contact surfaces and regularly medical screening of abattoir workers.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eProvision of adequate water supply and sanitation facilities, uses of refrigerated transport systems to maintain cold chain integrity and separation of clean and dirty processing areas to reduce cross contamination.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eFor the future research Molecular identification and antimicrobial susceptibility testing to assess resistance patterns must have established\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBPW Buffered Peptone Water \u003c/p\u003e\n\u003cp\u003eBSA Bismuth Sulfite Agar\u003c/p\u003e\n\u003cp\u003eCDC Central for Disease Control \u003c/p\u003e\n\u003cp\u003eEMB Eosin Methylene Blue\u003c/p\u003e\n\u003cp\u003eISO International for Organization Standardization \u003c/p\u003e\n\u003cp\u003eKOH Potassium Hydroxide \u003c/p\u003e\n\u003cp\u003eLB Lactose Broth \u003c/p\u003e\n\u003cp\u003eMBD Meat borne Disease\u003c/p\u003e\n\u003cp\u003eMR Methyl-Red \u003c/p\u003e\n\u003cp\u003eMSA Mannitol salt Agar \u003c/p\u003e\n\u003cp\u003eSB Selenite Broth \u003c/p\u003e\n\u003cp\u003eSPSS Statistical Package for social Science \u003c/p\u003e\n\u003cp\u003eSVM School Veterinary Medicine \u003c/p\u003e\n\u003cp\u003eTSA Triple sugar Iron \u003c/p\u003e\n\u003cp\u003eTSA Triple sugar Agar\u003c/p\u003e\n\u003cp\u003eVP Voges Proskauer\u003c/p\u003e\n\u003cp\u003eWHO World Health Organization \u003c/p\u003e\n\n"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval for this study was obtained from the institutional review board (IBR) of Wollega University. The study was conducted in accordance with the principle of Declaration of Helsinki. Informed consent was obtained from all abattoir worker prior to collecting hand swab samples. Participation in the study was voluntary and confidentiality of the participants was maintained throughout the research process.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAVAILABILITY OF DATA AND MATERIALS \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed during the current study are available from corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003eCOMPETING INTERESTS\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFUNDING \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNo specific funding was received for this study.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eOrganization WH. WHO estimates of the global burden of foodborne diseases: foodborne disease burden epidemiology reference group 2007\u0026ndash;2015. World Health Organization; 2015.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMajowicz SE, Musto J, Scallan E, Angulo FJ, Kirk M, O\u0026rsquo;Brien SJ, Jones TF, Fazil A, Hoekstra RM. (2010). The global burden of nontyphoidal salmonella gastroenteritis. In \u003cem\u003eClinical Infectious Diseases\u003c/em\u003e (Vol. 50, pp. 882\u0026ndash;889). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1086/650733\u003c/span\u003e\u003cspan address=\"10.1086/650733\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePapp JR. (2024). CDC laboratory recommendations for syphilis testing, United States, 2024. MMWR Recommendations Rep, \u003cem\u003e73\u003c/em\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePal M. (2018). \u003cem\u003eMicrobiological and hygienic quality of Meat and Meat Products\u003c/em\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNewell DG, Koopmans M, Verhoef L, Duizer E, Aidara-Kane A, Sprong H, Opsteegh M, Langelaar M, Threfall J, Scheutz F, der Giessen J, Kruse H. (2010). Food-borne diseases - The challenges of 20years ago still persist while new ones continue to emerge. \u003cem\u003eInternational Journal of Food Microbiology\u003c/em\u003e, \u003cem\u003e139\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ijfoodmicro.2010.01.021\u003c/span\u003e\u003cspan address=\"10.1016/j.ijfoodmicro.2010.01.021\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOliver SP, Jayarao BM, Almeida RA. (2005). Foodborne pathogens in milk and the dairy farm environment: Food safety and public health implications. 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Https://Openurl.Ebsco.Com/EPDB%3Agcd%3A15%3A7852719/Detailv2?Sid=ebsco%3Aplink%3Ascholar\u0026amp;id=ebsco%3Agcd%3A47789876\u0026amp;crl\u0026thinsp;=\u0026thinsp;c\u0026amp;link_origin=scholar.Google.Com.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEnabulele SA, Uraih N. Enterohaemorrhagic Escherichia coli 0157: H7 Prevalence in meat and vegetables sold in Benin City, Nigeria. Afr J Microbiol Res. 2009;3(5):276\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCastro A, Santos C, Meireles H, Silva J, Teixeira P. Food handlers as potential sources of dissemination of virulent strains of Staphylococcus aureus in the community. J Infect Public Health. 2016;9:153\u0026ndash;60. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jiph.2015.08.001\u003c/span\u003e\u003cspan address=\"10.1016/j.jiph.2015.08.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u0026Ouml;zkalp B. Isolation and identification of Salmonellas from different samples. InTech Published. 2012;1:123\u0026ndash;56.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHammack TS, Amagua\u0026ntilde;a RM, June GA, Sherrod PS, Andrews WH. Relative effectiveness of selenite cystine broth, tetrathionate broth, and Rappaport-Vassiliadis medium for the recovery of Salmonella spp. from foods with a low microbial load. J Food Prot. 1999;62:16\u0026ndash;21. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4315/0362-028X-62.1.16\u003c/span\u003e\u003cspan address=\"10.4315/0362-028X-62.1.16\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mcro","sideBox":"Learn more about [BMC Microbiology](http://bmcmicrobiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mcro","title":"BMC Microbiology","twitterHandle":"#bmcmicrobiology","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Bacterial contamination, Meat hygiene, Beef, Salmonella spp, Staphylococcus aureus, Escherichia coli, Ethiopia","lastPublishedDoi":"10.21203/rs.3.rs-9008197/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9008197/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003efoodborne disease caused by bacterial contamination of meat represent a major global public health challenge, particularly in developing countries where hygienic practices during meat processing are often inadequate.\u003c/p\u003e\u003ch2\u003eObjectives\u003c/h2\u003e \u003cp\u003ethis study aimed to isolate and identify major bacterial contaminants from beef, abattoir equipment and workers hands at Nekemte municipal abattoir, western Ethiopia.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003ea cross sectional study was conducted from November 2024 to January 2025. A total of 92 sample were collected, including meat (n\u0026thinsp;=\u0026thinsp;37), workers hand swabs (n\u0026thinsp;=\u0026thinsp;30) and knife swabs (n\u0026thinsp;=\u0026thinsp;25). Standard bacteriological culture techniques and biochemical tests were used for pathogen identification. Data were analyzed using SPSS version 16. Chi-square tests were performed to assess associations, with statistical significance set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003ch2\u003eResult\u003c/h2\u003e \u003cp\u003e the overall prevalence of bacterial contamination was 56.52% (52/92).knife swabs showed the highest contamination rate (64.00%), followed by workers hand swabs (56.67%) and meat samples (51.35%). Salmonella spp. Were the most frequently isolated pathogens (42.31%), followed by Staphylococcus aureus (28.85%) and Escherichia coli (28.85%). No statistical significant contamination (p\u0026thinsp;=\u0026thinsp;0.615).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003ethe high prevalence of bacterial contamination indicates inadequate hygienic practices in the abattoir. Strengthening sanitation measures. Implementing structured training programs and adopting standardized food safety systems are recommended to improve meat safety.\u003c/p\u003e","manuscriptTitle":"Isolation and Identification of Major Bacterial Contaminants in Beef and Abattoir Environment at Nekemte Municipal Abattoir, Western Ethiopia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-06 09:03:27","doi":"10.21203/rs.3.rs-9008197/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-09T11:25:58+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-09T10:15:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"6715406178150578925243580146032825274","date":"2026-04-07T06:13:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"124522877361083492486819894138518371431","date":"2026-04-03T14:16:00+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-03T06:57:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"64177786232230579396587683924371146388","date":"2026-04-02T14:55:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"46080162433000793501543420048684708281","date":"2026-04-01T18:03:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"235142579552899973348794794159778248779","date":"2026-04-01T15:57:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"90778517504240711454353474122537505149","date":"2026-04-01T15:51:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"339832270598596623741041460602203948850","date":"2026-04-01T15:40:35+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-01T15:06:51+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-01T10:04:23+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-12T16:16:29+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-12T15:24:40+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Microbiology","date":"2026-03-12T12:20:22+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mcro","sideBox":"Learn more about [BMC Microbiology](http://bmcmicrobiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mcro","title":"BMC Microbiology","twitterHandle":"#bmcmicrobiology","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cc1e7c96-115c-4368-87a5-a3f1e07ed2e7","owner":[],"postedDate":"April 6th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-18T12:08:20+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-06 09:03:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9008197","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9008197","identity":"rs-9008197","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}