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<p>The increasing prevalence of antibiotic resistance poses a serious threat to public health, significantly reducing the effectiveness of conventional antibiotics against bacterial infections, particularly those caused by multidrug-resistant <i>Escherichia coli</i> (<i>E. coli</i>). As monotherapy becomes increasingly unreliable due to the rapid evolution of resistance, combination therapy has emerged as a promising strategy to address this challenge. In this context, the present study aimed to evaluate the effect of cuminaldehyde (CA) in combination with two conventional antibiotics, gentamicin (GN) and ciprofloxacin (CF), against five drug-resistant clinical strains of <i>E. coli</i>. In silico analyses using PASS Online, SwissADME, ProTox 3.0, and Osiris predicted the potential antimicrobial properties of the test compounds. In vitro investigations further demonstrated significant antimicrobial activity, with minimum inhibitory concentration (MIC) values ranging from 400 to 450&#xa0;µg/mL for CA, 6–8&#xa0;µg/mL for GN, and 2–3&#xa0;µg/mL for CF against different <i>E. coli</i> strains. Furthermore, fractional inhibitory concentration index (FICI) analysis revealed that diverse interaction patterns, including synergistic effects, exist between CA and the conventional antibiotics. To optimize these combinations, response surface methodology (RSM) was employed to determine the optimal doses of the test compounds. The experimental validation of the RSM model showed high predictive accuracy (98–99%), confirming its robustness and reliability. Overall, the present findings successfully identified potent synergistic triple-drug combinations exhibiting significant inhibitory effects against drug-resistant <i>E. coli</i>, thereby proposing a promising approach for developing effective therapeutic strategies to combat antibiotic resistance.</p>

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Cuminaldehyde potentiates antimicrobial efficacy of gentamicin and ciprofloxacin against Escherichia coli: a response surface methodology (RSM) based study

  • 期刊论文

  • 发表日期：

    2026年5月15日

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  • Alakesh Maity,
  • Rathin Bhowmik,
  • Awantika Das,
  • Saranya Trivedi,
  • Sumit Kumar Mondal,
  • Anirban Das Gupta,
  • Payel Paul,
  • Sharmistha Das,
  • Poulomi Chakraborty,
  • Prosun Tribedi

摘要

The increasing prevalence of antibiotic resistance poses a serious threat to public health, significantly reducing the effectiveness of conventional antibiotics against bacterial infections, particularly those caused by multidrug-resistant Escherichia coli (E. coli). As monotherapy becomes increasingly unreliable due to the rapid evolution of resistance, combination therapy has emerged as a promising strategy to address this challenge. In this context, the present study aimed to evaluate the effect of cuminaldehyde (CA) in combination with two conventional antibiotics, gentamicin (GN) and ciprofloxacin (CF), against five drug-resistant clinical strains of E. coli. In silico analyses using PASS Online, SwissADME, ProTox 3.0, and Osiris predicted the potential antimicrobial properties of the test compounds. In vitro investigations further demonstrated significant antimicrobial activity, with minimum inhibitory concentration (MIC) values ranging from 400 to 450 µg/mL for CA, 6–8 µg/mL for GN, and 2–3 µg/mL for CF against different E. coli strains. Furthermore, fractional inhibitory concentration index (FICI) analysis revealed that diverse interaction patterns, including synergistic effects, exist between CA and the conventional antibiotics. To optimize these combinations, response surface methodology (RSM) was employed to determine the optimal doses of the test compounds. The experimental validation of the RSM model showed high predictive accuracy (98–99%), confirming its robustness and reliability. Overall, the present findings successfully identified potent synergistic triple-drug combinations exhibiting significant inhibitory effects against drug-resistant E. coli, thereby proposing a promising approach for developing effective therapeutic strategies to combat antibiotic resistance.