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A Delayed Inoculation Model of Chronic Pseudomonas aeruginosa Wound Infection
06:56

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Published on: February 20, 2020

Mathematical modeling to characterize the inoculum effect.

Pratik Bhagunde1, Kai-Tai Chang, Renu Singh

  • 1Department of Chemical and Biomolecular Engineering, University of Houston, 4800 Calhoun Avenue, Houston, TX 77204, USA.

Antimicrobial Agents and Chemotherapy
|September 1, 2010
PubMed
Summary
This summary is machine-generated.

The inoculum effect reduces beta-lactam antibiotic killing in dense bacterial populations. A new mathematical model explains this phenomenon by linking reduced drug concentration to higher bacterial biomass, improving predictions of antibiotic efficacy.

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Area of Science:

  • Pharmacodynamics
  • Microbiology
  • Mathematical Modeling

Background:

  • The inoculum effect describes reduced antibiotic killing against dense bacterial populations, a phenomenon not fully understood.
  • Beta-lactam antibiotics are known to be less effective against high bacterial loads in vitro.
  • Understanding the inoculum effect is crucial for predicting antibiotic treatment outcomes.

Purpose of the Study:

  • To propose and validate a semi-mechanistic mathematical model for the inoculum effect.
  • To investigate the relationship between bacterial inoculum density, drug concentration, and killing kinetics.
  • To assess the impact of initial bacterial load on piperacillin efficacy against Escherichia coli.

Main Methods:

  • Performed time-kill studies using Escherichia coli ATCC 25922 with four different baseline inocula (10^5 to 10^8 CFU/ml).
  • Exposed bacteria to escalating piperacillin concentrations (0.25x to 256x MIC) over 24 hours.
  • Quantified viable bacterial burden and developed a mathematical model to capture killing profiles and biomass.
  • Assessed bacterial biomass using a colorimetric method.

Main Results:

  • The inoculum effect was successfully modeled as a reduction in effective drug concentration, dependent on baseline inoculum.
  • The mathematical model accurately captured 28 killing profiles with high correlation (r^2 = 0.88).
  • Higher initial inocula (10^8 CFU/ml) resulted in significantly greater bacterial biomass after 24 hours compared to lower inocula (10^5 CFU/ml) (P = 0.002).

Conclusions:

  • Bacterial inoculum density significantly impacts in vitro killing by piperacillin.
  • The proposed mathematical model provides a robust framework for understanding and predicting the inoculum effect.
  • This model can enhance the prediction of bacterial responses to antibiotic exposure in future research.