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.