ArticleScientific reports2017
Prediction of Cross-resistance and Collateral Sensitivity by Gene Expression profiles and Genomic Mutations.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Collateral sensitivity-harnessing microbial vulnerabilities as a solution to antimicrobial resistance.Molecular biology reports · 2026Review
- Repeatability of gene expression evolution in experimental environmental adaptation.Nature communications · 2026Article
- Genetic properties underlying transcriptional variability across different perturbations.Nature communications · 2025Article
- Evolutionary trajectory of bacterial resistance to antibiotics and antimicrobial peptides inmSystems · 2025Article
- Systematic mapping of antibiotic cross-resistance and collateral sensitivity with chemical genetics.Nature microbiology · 2025Article
- Transcriptomic analysis reveals the rareness of genetic assimilation of gene expression in environmental adaptations.Science advances · 2023Article
- Pervasive genotype-by-environment interactions shape the fitness effects of antibiotic resistance mutations.Proceedings. Biological sciences · 2023Article
- Plasticity and Stereotypic Rewiring of the Transcriptome Upon Bacterial Evolution of Antibiotic Resistance.Molecular biology and evolution · 2023Article
- Analysis of the evolution of resistance to multiple antibiotics enables prediction of the Escherichia coli phenotype-based fitness landscape.PLoS biology · 2022Article
- Genomic Basis of Transcriptome Dynamics in Rice under Field Conditions.Plant & cell physiology · 2021Article
- Antifungal Activity of a Medical-Grade Honey Formulation againstJournal of fungi (Basel, Switzerland) · 2021Article
- Developing rapid growingMetabolic engineering communications · 2020Article
- High-throughput laboratory evolution reveals evolutionary constraints in Escherichia coli.Nature communications · 2020Article
- Entropy of a bacterial stress response is a generalizable predictor for fitness and antibiotic sensitivity.Nature communications · 2020Article
- Understanding metabolic adaptation by using bacterial laboratory evolution and trans-omics analysis.Biophysical reviews · 2020Review
- Phenotypic plasticity as a long-term memory easing readaptations to ancestral environments.Science advances · 2020Article
- Ciprofloxacin, amoxicillin, and aminoglycosides stimulate genetic and phenotypic changes in uropathogenic Escherichia coli strains.Virulence · 2019Article
- Integrated evolutionary analysis reveals antimicrobial peptides with limited resistance.Nature communications · 2019Article
- Opportunities for improving cancer treatment using systems biology.Current opinion in systems biology · 2019Article
- Understanding and engineering alcohol-tolerant bacteria using OMICS technology.World journal of microbiology & biotechnology · 2018Review
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In adaptive evolution, an increase in fitness to an environment is frequently accompanied by changes in fitness to other environmental conditions, called cross-resistance and sensitivity. Although the networks between fitness changes affect the course of evolution substantially, the mechanisms underlying such fitness changes are yet to be fully elucidated. Herein, we performed high-throughput laboratory evolution of Escherichia coli under various stress conditions using an automated culture system, and quantified how the acquisition of resistance to one stressor alters the resistance to other stressors. We demonstrated that resistance changes could be quantitatively predicted based on changes in the transcriptome of the resistant strains. We also identified several genes and gene functions, for which mutations were commonly fixed in the strains resistant to the same stress, which could partially explain the observed cross-resistance and collateral sensitivity. The integration of transcriptome and genome data enabled us to clarify the bacterial stress resistance mechanisms.
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