High-throughput laboratory evolution reveals evolutionary constraints in Escherichia coli.

ABSTRACT: Understanding the constraints that shape the evolution of antibiotic resistance is critical for predicting and controlling drug resistance. Despite its importance, however, a systematic investigation of evolutionary constraints is lacking. Here, we perform a high-throughput laboratory evolution of Escherichia coli under the addition of 95 antibacterial chemicals and quantified the transcriptome, resistance, and genomic profiles for the evolved strains. Utilizing machine learning techniques, we analyze the phenotype-genotype data and identified low dimensional phenotypic states among the evolved strains. Further analysis reveals the underlying biological processes responsible for these distinct states, leading to the identification of trade-off relationships associated with drug resistance.

SUBMITTER: Maeda T 

PROVIDER: S-EPMC7686311 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature