Antimicrobial Resistance Profiles and Molecular Characterization of Escherichia coli Isolated From Community-Acquired Urinary Tract Infections in South-West Nigeria
Background
Urinary tract infections are among the most common bacterial infections encountered in clinical practice, with Escherichia coli being the predominant causative organism. The increasing emergence of antimicrobial-resistant strains poses significant challenges to effective treatment and public health. In Nigeria, inappropriate antibiotic use, self-medication, and limited antimicrobial stewardship programs contribute to the growing burden of resistance. Molecular characterization of resistant isolates can provide valuable insights into resistance mechanisms and transmission patterns. This study seeks to investigate antimicrobial resistance profiles and characterize resistance-associated genes among Escherichia coli isolates obtained from community-acquired urinary tract infections in South-West Nigeria.
Research Objectives
- Determine the prevalence of Escherichia coli among urinary tract infection isolates.
- Assess antimicrobial susceptibility patterns of the isolates.
- Identify multidrug-resistant Escherichia coli strains.
- Characterize resistance-associated genes using molecular methods.
- Examine factors associated with antimicrobial resistance.
Research Questions
- What proportion of urinary tract infections are caused by Escherichia coli?
- What are the antimicrobial susceptibility patterns of the isolates?
- How prevalent are multidrug-resistant strains?
- Which resistance genes are present among the isolates?
- What factors are associated with antimicrobial resistance?
Suggested Methodology
A laboratory-based cross-sectional study will be conducted using urine samples collected from patients diagnosed with community-acquired urinary tract infections. Isolates will be identified using standard microbiological techniques. Antimicrobial susceptibility testing will be performed using the Kirby-Bauer disc diffusion method, while polymerase chain reaction assays will be used for molecular characterization. Statistical analyses will evaluate associations between resistance patterns and patient characteristics.
Suggested Sample
Keywords
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