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Updated: May 22, 2025

Isolation and Identification of Waterborne Antibiotic-Resistant Bacteria and Molecular Characterization of their Antibiotic Resistance Genes
Published on: March 3, 2023
Highly Drug-Resistant Escherichia coli from Hospital Wastewater with Several Evolutionary Mutations: An Integrated
Khadija Shams1, Ibrar Khan2, Sajjad Ahmad3,4
1Centre of Biotechnology and Microbiology, University of Peshawar, Khyber Pakhtunkhwa, Pakistan.
Abstract:
Many people around the world are still unable to get access to clean drinking water. Escherichia coli is a common waterborne pathogen that frequently results from insufficient hygiene measures and needs attention to address health problems. The present study aimed to evaluate antibiotic resistance of Escherichia coli isolated from wastewater and drinking water samples of hospital and non-hospital settings at Peshawar. Out of 462 samples collected, 111 tested positive for E. coli. The majority of isolates were resistant to many antibiotics including Ampicillin, Gentamicin, Tobramycin, Imipenem, Meropenem, Tetracycline, Cefepime, Amikacin, Piperacillin, Levofloxacin, Ciprofloxacin, Ceftriaxone, and Cefazolin. However, they showed susceptibility to Chloramphenicol, Fosfomycin 200 mg, Colistin, and Tigecycline. Genetic analysis revealed various antibiotic resistance genes within the isolates, i.e., marA(20%), marB(40%) marR(30%), rob(30%), and soxS(35%). Following PCR, the resulting products underwent next-generation sequencing. marA exhibited T10P and D101H mutations, while MarR showed substitutions at M1G, V142S, L143P, and P144C positions. In Rob, D2I, A4P, L10F, I12N, and L253P mutations were observed. The SoxS displayed alterations at H105P, R106A, and L107V positions. Asinex antibacterial library was used to study molecular docking based on virtual screening. SWISS ADME was used to in silico evaluate the pharmacokinetics of these substances. 100 ns molecular dynamics simulation was conducted to estimate free binding energies, confirmation, and stability of the binding mode of the identified compounds. Screening results revealed that LAS-52505571, LAS52171241, LAS52202332, and LAS22461675 compounds showed high affinity to MarA, MarR, SoxS, and Rob proteins, respectively, with the lowest binding energies across the library. In brief, the current study aimed at establishing potential chemical entities that could facilitate the evolution of silicon drugs against antibiotic-resistant E. coli strains.
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