MOLECULAR IDENTIFICATION OF ESCHERICHIA COLI STRAIN ISOLATED FROM URINARY TRACT INFECTIONS AT A TERTIARY CARE HOSPITAL IN SIALKOT, PAKISTAN

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Background: Urinary tract infections (UTIs) caused by Escherichia coli remain a primary global health concern, with increasing multidrug resistance posing significant diagnostic and therapeutic challenges. Molecular techniques such as 16S rRNA sequencing provide a reliable approach for accurate identification and phylogenetic characterization of resistant strains. Objective: To isolate and identify multidrug-resistant (MDR) Escherichia coli strains from urinary tract infection patients in District Sialkot, Pakistan, using 16S rRNA sequencing. Study Design: Cross-sectional molecular study. Setting: Department of Microbiology, tertiary care hospital in Sialkot, Pakistan. Duration of Study: From July 2023 to December 2023. Methods: Twenty E. coli isolates were obtained from urine samples of patients with clinically diagnosed UTIs. Identification was performed using standard microbiological techniques. Antibiotic susceptibility testing was conducted using the Kirby–Bauer disc diffusion method against commonly used antibiotics. The isolate exhibiting multidrug resistance was subjected to molecular identification via 16S rRNA gene sequencing and phylogenetic analysis. Sequence data were compared with reference strains using BLAST and submitted to GenBank. Results: Antibiotic susceptibility testing revealed high levels of resistance to ceftriaxone (95.2%), cefoperazone (93.5%), ciprofloxacin (86.5%), cefotaxime (84.6%), and cefixime (86%). Molecular analysis confirmed the isolate as Escherichia coli, with phylogenetic analysis showing close homology to previously reported E. coli strains. The sequence of the multidrug-resistant strain was submitted to GenBank under the accession number Escherichia coli strain KS8861 (PP897401.1). Conclusion: 16S rRNA sequencing serves as a robust and accurate method for identifying multidrug-resistant E. coli strains associated with UTIs. Incorporating molecular diagnostics into routine microbiological workflows can enhance early detection and guide effective antimicrobial therapy.

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