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Daily Transfers, Archiving Populations, and Measuring Fitness in the Long-Term Evolution Experiment with Escherichia coli
Published on: August 18, 2023
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High-throughput laboratory evolution reveals evolutionary constraints in Escherichia coli.
Tomoya Maeda1, Junichiro Iwasawa2, Hazuki Kotani3
1RIKEN Center for Biosystems Dynamics Research, 6-2-3 Furuedai, Suita, Osaka, 565-0874, Japan. tomoya.maeda@riken.jp.
Nature Communications
|November 25, 2020
Summary
This study reveals evolutionary trade-offs in antibiotic resistance by evolving Escherichia coli with 95 chemicals. It identified distinct resistance states and a slower evolution of beta-lactam resistance under certain stresses.
Area of Science:
- Evolutionary biology
- Microbiology
- Genomics
Background:
- Antibiotic resistance evolution is critical for public health.
- Systematic investigation of evolutionary constraints on antibiotic resistance is lacking.
Purpose of the Study:
- To systematically investigate evolutionary constraints on antibiotic resistance.
- To identify trade-off relationships and distinct phenotypic states in drug resistance evolution.
Main Methods:
- High-throughput laboratory evolution of Escherichia coli with 95 antibacterial chemicals.
- Quantification of transcriptome, resistance, and genomic profiles.
- Machine learning analysis of phenotype-genotype data.
Main Results:
- Identification of low-dimensional phenotypic states among evolved strains.
- Discovery of biological processes underlying distinct resistance states and trade-offs.
- Observation of decelerated beta-lactam resistance evolution under certain stresses.
Conclusions:
- Findings bridge genotypic, gene expression, and drug resistance gaps.
- Enhanced understanding of evolutionary constraints on antibiotic resistance.
- Provides insights into predicting and controlling drug resistance.
