Antibiotic resistance and prevalence of bacterial contaminants in street-vended suya meat in Benin City, Nigeria

This study investigates the antibiotic resistance and prevalence of bacterial contaminants in street-vended suya meat in Benin City, Nigeria. Suya meat, a popular street food, is vulnerable to bacterial contamination due to improper handling, storage, and environmental exposure. A total of fifty (50) suya meat samples were collected from various vendors across the city for microbiological analysis. Standard microbiological methods were employed to isolate and identify bacterial pathogens, including Bacillus spp., Citrobacter spp., Klebsiella spp., Escherichia coli, Pseudomonas spp., Salmonella spp., and Staphylococcus aureus. The prevalence of bacterial contamination showed that 46% of samples were positive for Escherichia coli, 38% for Staphylococcus aureus, and 30% for Pseudomonas spp. Antibiotic susceptibility testing was performed using the disc diffusion method, revealing a high resistance rate, particularly among E. coli (70%), Klebsiella spp. (60%), and Pseudomonas spp. (55%) against ampicillin and tetracycline. Salmonella spp. displayed resistance to ampicillin (50%) and ciprofloxacin (40%). The analysis showed that Staphylococcus aureus was resistant to penicillin (50%) and clindamycin (45%). Statistical analysis conducted with SPSS version 23 revealed significant differences in antibiotic resistance patterns across bacterial species (p < 0.05). The results showed high resistance to Pefloxacin, Gentamycin, and Cotrimoxazole across most bacterial species, with Pseudomonas and Klebsiella exhibiting the highest resistance rates. Statistical analysis revealed significant correlations in antibiotic resistance between certain bacterial species, notably between Citrobacter and Klebsiella (r = 0.939, p = 0.0001) and between Pseudomonas and Salmonella (r = 0.773, p = 0.015). The results showed that E. coli emerged as the predominant pathogen, followed by Pseudomonas species and Staphylococcus aureus as major contributors to contamination. This study underscores the public health risk posed by bacterial contamination in street-vended suya meat, emphasizing the need for improved food safety measures and regulatory oversight to mitigate foodborne infections in Nigeria.

Authors

Institutions

Publication Details

Journal
European Journal of Life Sciences
Published
2025-04-30
DOI
https://doi.org/10.55971/ejls.1588830
Primary Topic
Identification and Quantification in Food
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Antibiotic resistance and prevalence of bacterial contaminants in street-vended suya meat in Benin City, Nigeria

Frances Ngozi Olisaka, Olodu Blessing Adoh
European Journal of Life Sciences
Identification and Quantification in Food
article

Antibiotic resistance and prevalence of bacterial contaminants in street-vended suya meat in Benin City, Nigeria

Frances Ngozi Olisaka, Olodu Blessing Adoh
article en

Abstract

This study investigates the antibiotic resistance and prevalence of bacterial contaminants in street-vended suya meat in Benin City, Nigeria. Suya meat, a popular street food, is vulnerable to bacterial contamination due to improper handling, storage, and environmental exposure. A total of fifty (50) suya meat samples were collected from various vendors across the city for microbiological analysis. Standard microbiological methods were employed to isolate and identify bacterial pathogens, including Bacillus spp., Citrobacter spp., Klebsiella spp., Escherichia coli, Pseudomonas spp., Salmonella spp., and Staphylococcus aureus. The prevalence of bacterial contamination showed that 46% of samples were positive for Escherichia coli, 38% for Staphylococcus aureus, and 30% for Pseudomonas spp. Antibiotic susceptibility testing was performed using the disc diffusion method, revealing a high resistance rate, particularly among E. coli (70%), Klebsiella spp. (60%), and Pseudomonas spp. (55%) against ampicillin and tetracycline. Salmonella spp. displayed resistance to ampicillin (50%) and ciprofloxacin (40%). The analysis showed that Staphylococcus aureus was resistant to penicillin (50%) and clindamycin (45%). Statistical analysis conducted with SPSS version 23 revealed significant differences in antibiotic resistance patterns across bacterial species (p < 0.05). The results showed high resistance to Pefloxacin, Gentamycin, and Cotrimoxazole across most bacterial species, with Pseudomonas and Klebsiella exhibiting the highest resistance rates. Statistical analysis revealed significant correlations in antibiotic resistance between certain bacterial species, notably between Citrobacter and Klebsiella (r = 0.939, p = 0.0001) and between Pseudomonas and Salmonella (r = 0.773, p = 0.015). The results showed that E. coli emerged as the predominant pathogen, followed by Pseudomonas species and Staphylococcus aureus as major contributors to contamination. This study underscores the public health risk posed by bacterial contamination in street-vended suya meat, emphasizing the need for improved food safety measures and regulatory oversight to mitigate foodborne infections in Nigeria.

European Journal of Life SciencesVol. 4(1)
Benson Idahosa University (NG), Godfrey Okoye University (NG)
Openalex Percentile: Top 92%
Identification and Quantification in Food
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.