EVE

EVE implements a morbidostat-like feedback system that dynamically adjusts antibiotic concentration to perform experimental evolution studies of bacterial populations, including Escherichia coli under chloramphenicol, to investigate the development of antibiotic resistance.


Key Features:

  • Automatic Adjustment of Antibiotic Concentration: Implements morbidostat-like automatic modulation of antibiotic levels in response to measured bacterial growth dynamics.
  • Continuous Growth Monitoring and Dynamic Dosing: Continuously monitors bacterial growth and iteratively adjusts antibiotic concentrations to maintain selective pressure.
  • Experimental Validation with Replicate Populations: Validated by evolving replicate Escherichia coli populations under chloramphenicol and comparing results to existing literature.
  • Automated Selection Regime: Provides an automated iterative selection process that simulates evolutionary pressures driving antibiotic resistance.

Scientific Applications:

  • Study of Antibiotic Resistance Evolution: Enables controlled experimental evolution to investigate how bacterial populations, such as Escherichia coli, develop resistance to antibiotics like chloramphenicol.
  • Mechanistic Investigation of Resistance Development: Facilitates testing hypotheses about mechanisms and trajectories of resistance emergence by comparing evolved populations to published data.
  • Simulation of Dynamic Selection Pressures: Allows observation of adaptation under dynamically adjusted drug concentrations to model fluctuating selective environments.

Methodology:

The system continuously monitors bacterial growth and iteratively adjusts antibiotic concentrations during experimental evolution of bacteria (e.g., Escherichia coli exposed to chloramphenicol).

Topics

Details

License:
MIT
Tool Type:
command-line tool
Programming Languages:
JavaScript, Python
Added:
11/14/2019
Last Updated:
1/14/2021

Operations

Publications

Gopalakrishnan V, Crozier D, Card KJ, Chick LD, Krishnan NP, McClure E, Pelesko J, Williamson DF, Nichol D, Mandal S, Bonomo RA, Scott JG. A low-cost, open-source evolutionary bioreactor and its educational use. Unknown Journal. 2019. doi:10.1101/729434.

Links