Antibiotic Susceptibility Profiles of Post-Chlorination Bacterial Isolates from Urban Wastewater Treatment Plants in Gujarat, India

This dataset offers a thorough examination of the patterns of antibiotic susceptibility in bacterial isolates that were found in the chlorinated wastewater of five sewage treatment plants (STPs) in Gujarat, India—two in Vadodara and three in Anand. In total, 19 bacterial isolates have been obtained after in situ chlorination that includes 11 Gram-positive and 8 Gram-negative strains. Antimicrobial susceptibility testing was performed on these isolates using the Kirby-Bauer disk diffusion technique, and the findings were interpreted according to the Clinical and Laboratory Standards Institute (CLSI) M100-S25 Guidelines. This study's main goal was to determine the distribution and prevalence of antimicrobial resistance (AMR) in bacteria that survive final-stage disinfection in municipal solid waste treatment plants. Thirty-one antibiotics were examined: Penicillin-G, Oxacillin, Ampicillin, Cefotaxime, Vancomycin, Teicoplanin, Tetracycline, Gentamicin, Erythromycin, Azithromycin, Chloramphenicol, Clindamycin, Norfloxacin, Ofloxacin, and Co-Trimazine are among the 16 antibiotics that target Gram-positive bacteria, while 15 antibiotics that target Gram-negative bacteria include Piperacillin/Tazobactam, Cefoperazone/Sulbactam, Carbenicillin, Tetracycline, Doxycycline Hydrochloride, Amikacin, Gentamicin, Streptomycin, Kanamycin, Ciprofloxacin, Ofloxacin, Gatifloxacin, Co-Trimazine, and Nitrofurantoin. In both bacterial groups, the effects of four broad-spectrum antibiotics—Tetracycline, Gentamicin, Ofloxacin, and Co-Trimazine—were examined. Based on CLSI breakpoints, each zone of inhibition (ZOI) was classified as susceptible, intermediate, or resistant and measured in millimetres. With color-coded annotations—green for susceptible, yellow for intermediate, and red for resistant—the data are displayed in a comprehensive categorization matrix. The widespread nature of resistance across bacterial species and antibiotic classes may be easily understood using this approach. Two sets of comparative graphical analyses are included in the dataset to improve interpretability. Potential multi-drug resistance is highlighted in the first set, which shows the antibiotic resistance profile for each distinct isolate. In order to determine which antibiotics are the most and least effective in the post-chlorination setting, the second set evaluates the effectiveness of each antibiotic across all isolates. These visual representations provide helpful insights on the effectiveness of disinfection processes and microbial tolerance to chlorine stress. The area of environmental AMR surveillance is growing, and this dataset adds to it, especially for treated wastewater systems, which are frequently not included in national monitoring programs. Integrated AMR monitoring inside STPs is necessary because of the documented resistance in post-treatment isolates, which highlights the possible risk of releasing resistant bacteria into natural environments.