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Testing the Role of Multicopy Plasmids in the Evolution of Antibiotic Resistance
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Forecasting Multitrait Resistance Evolution under Antibiotic Stress.

Suvam Roy1,2,3, Eric Libby2,3,4, Peter A Lind1,3

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Summary
This summary is machine-generated.

Predicting bacterial antibiotic resistance is crucial. This study uses a mathematical model to simulate mutations in efflux pump genes, revealing how bacteria evolve resistance and offering strategies to prevent it.

Keywords:
Pseudomonas aeruginosaantibiotic resistanceefflux pumpevolutiongene regulatory networkmathematical model

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Area of Science:

  • Microbiology
  • Evolutionary Biology
  • Computational Biology

Background:

  • Bacteria utilize efflux pumps to survive antibiotic stress.
  • Mutations in efflux pump genes or regulators increase pump expression, leading to antibiotic resistance.
  • Complex regulatory networks make experimental mapping of these mutations challenging.

Purpose of the Study:

  • To develop a mathematical framework for predicting mutation spectra in bacterial efflux pump regulation.
  • To simulate in silico evolution of Pseudomonas aeruginosa under antibiotic pressure.
  • To understand how regulatory networks and shared protein use shape resistance evolution.

Main Methods:

  • Developed a mathematical framework integrating dynamical equations for efflux pump regulation.
  • Employed a genetic algorithm for parameter estimation and evolutionary simulations.
  • Simulated in silico evolution of Pseudomonas aeruginosa exposed to meropenem, tobramycin, and ciprofloxacin.

Main Results:

  • Identified mutational spectra affecting four RND efflux pumps and their shared regulatory network in Pseudomonas aeruginosa.
  • Found that single-target regulators were the most frequently mutated genes, aligning with clinical observations.
  • Demonstrated that shared protein use (OprM) influences distinct mutational patterns and that mutations can lead to collateral sensitivity or cross-resistance.
  • Observed that efflux pump genes are lost in the absence of antibiotics, suggesting a potential strategy to reduce resistance evolution.

Conclusions:

  • The mathematical framework accurately predicts mutation spectra and evolutionary trajectories of bacterial efflux pumps.
  • Shared regulatory components and protein use significantly impact resistance evolution.
  • Bacterial evolution under antibiotic pressure can lead to complex phenotypes, including collateral sensitivity and cross-resistance.
  • Antibiotic withdrawal may be a viable strategy to decrease the bacterial capacity for evolving resistance.