Prevalence and Molecular Detection of Shiga Toxin-Producing Escherichia coli in Raw Beef Sold in Major Abattoirs in South-West Nigeria
Background
Shiga toxin-producing Escherichia coli (STEC) are important foodborne pathogens capable of causing severe gastrointestinal disease, hemorrhagic colitis, and hemolytic uremic syndrome. Raw meat products may become contaminated during slaughtering, processing, or transportation. In Nigeria, increasing demand for fresh meat and variations in hygienic practices within abattoirs raise concerns regarding food safety and public health. Molecular detection of shiga toxin genes provides a reliable approach for identifying potentially pathogenic strains. Understanding the prevalence and molecular characteristics of STEC in beef products is essential for strengthening food safety surveillance and reducing foodborne disease risks.
Research Objectives
- Determine the prevalence of STEC in raw beef samples.
- Identify shiga toxin genes among Escherichia coli isolates.
- Assess antimicrobial resistance profiles of STEC isolates.
- Evaluate hygienic practices associated with contamination.
- Compare contamination levels across selected abattoirs.
Research Questions
- What is the prevalence of STEC in raw beef samples?
- Which shiga toxin genes are present among isolates?
- What are the antimicrobial resistance profiles of the isolates?
- Which slaughterhouse practices are associated with contamination?
- Do contamination rates differ across abattoirs?
Suggested Methodology
A laboratory-based cross-sectional study will be conducted using beef samples collected from selected abattoirs. Isolation and identification of Escherichia coli will be performed using standard microbiological techniques. PCR assays will be used for detection of shiga toxin genes, while antimicrobial susceptibility testing will follow CLSI guidelines. Statistical analyses will evaluate contamination rates and associated factors.
Suggested Sample
Keywords
Need Help With Data Analysis?
Get support with statistical analysis, dashboards, interpretation, Chapter 4 reporting, and public health research analytics.