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Checkerboard synergistic data analysis using a Hill function-based approach.

William G Gutheil1

  • 1Division of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Missouri-Kansas City, Kansas City, Missouri 64108, USA.

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|February 20, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a novel checkerboard assay analysis using Hill functions to determine antibiotic synergy. The method provides precise fractional inhibitory concentration index calculations and reveals antibiotic interaction steepness.

Keywords:
CheckerboardHill functioncurve fittinghysteresissynergy

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Area of Science:

  • Microbiology
  • Pharmacology
  • Computational Biology

Background:

  • Checkerboard assays are standard for evaluating antibiotic synergy.
  • Traditional analysis methods may not fully capture complex drug interactions.
  • A quantitative approach is needed to analyze the steepness and nature of synergistic effects.

Purpose of the Study:

  • To develop and validate a novel data analysis approach for checkerboard assays.
  • To quantitatively assess antibiotic synergy and antagonism using Hill function fitting.
  • To derive formulas for fractional inhibitory concentrations (FICIs) and analyze interaction steepness.

Main Methods:

  • Applied Hill function fitting to individual rows and columns of checkerboard data.
  • Generated isobolograms by plotting MIC_row vs. MIC_col values.
  • Performed secondary Hill function fitting on isobologram data in both x-y and y-x directions.
  • Developed a simultaneous fitting method using overlapping Hill functions.
  • Derived formulas for FICIs based on derived fit parameters.

Main Results:

  • The analysis yields MIC values (K) and steepness parameters (n) for each antibiotic.
  • Steepness values (n) can vary significantly, indicating concentration-dependent interactions.
  • The method allows for simultaneous fitting in both dimensions, improving analysis efficiency.
  • Derived formulas provide a quantitative measure of fractional inhibitory concentrations (FICIs).

Conclusions:

  • This Hill function-based checkerboard analysis offers a robust method for quantifying antibiotic synergy.
  • The approach provides insights into the concentration-dependent nature and steepness of drug interactions.
  • The MATLAB implementation facilitates statistical analysis and model comparison for improved drug interaction studies.