ArticleAntimicrobial agents and chemotherapy2014
Interaction between mutations and regulation of gene expression during development of de novo antibiotic resistance.
Article in Antimicrobial agents and chemotherapy, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
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40 citing papers in PubMed, 73 citations in OpenAlex.
- Collateral sensitivity-harnessing microbial vulnerabilities as a solution to antimicrobial resistance.Molecular biology reports · 2026Review
- The shape of fitness functions and the distribution of mutational effect sizes jointly limit adaptation by regulatory mutations.Nature ecology & evolution · 2026Article
- Reinforcement learning for adaptive control of phenotypically heterogeneous bacterial populations.bioRxiv : the preprint server for biology · 2025Article
- Heterogeneity in responses to ribosome-targeting antibiotics mediated by bacterial RNA repair.Nature communications · 2025Article
- Stringent response-mediated ferroptosis-like death resistance underliesApplied and environmental microbiology · 2025Article
- Driving factors for beta-lactam resistance gene amplification duringAntimicrobial agents and chemotherapy · 2025Article
- Collateral sensitivity and cross-resistance in six species of bacteria exposed to six classes of antibiotics.Microbiology spectrum · 2025Article
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- Spatial population dynamics of bacterial colonies with social antibiotic resistance.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Fluoroquinolone-specific resistance trajectories in E. coli and their dependence on the SOS-response.BMC microbiology · 2025Article
- High-throughput method characterizes hundreds of previously unknown antibiotic resistance mutations.Nature communications · 2025Article
- Drug delivery dynamics dictate evolution of bacterial antibiotic responses.The ISME journal · 2025Article
- Genetic adaptation to amoxicillin in Escherichia coli: The limited role of dinB and katE.PloS one · 2025Article
- Dynamics of drug delivery determines course of evolution of antibiotic responses in bacteria.bioRxiv : the preprint server for biology · 2024Article
- How can we escape the ESKAPEs: Antimicrobial resistance mechanisms and what lies ahead?PLoS pathogens · 2024Review
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- Reactive oxygen species accelerateiScience · 2023Article
- Contrasting genes conferring short- and long-term biofilm adaptation inMicrobial genomics · 2023Article
- Disrupting the ArcA Regulatory Network Amplifies the Fitness Cost of Tetracycline Resistance in Escherichia coli.mSystems · 2023Article
- Prevalence and distribution of extended-spectrum β-lactamase and AmpC-producingFrontiers in microbiology · 2022Article
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5 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Bacteria can become resistant not only by horizontal gene transfer or other forms of exchange of genetic information but also by de novo by adaptation at the gene expression level and through DNA mutations. The interrelationship between changes in gene expression and DNA mutations during acquisition of resistance is not well documented. In addition, it is not known whether the DNA mutations leading to resistance always occur in the same order and whether the final result is always identical. The expression of >4,000 genes in Escherichia coli was compared upon adaptation to amoxicillin, tetracycline, and enrofloxacin. During adaptation, known resistance genes were sequenced for mutations that cause resistance. The order of mutations varied within two sets of strains adapted in parallel to amoxicillin and enrofloxacin, respectively, whereas the buildup of resistance was very similar. No specific mutations were related to the rather modest increase in tetracycline resistance. Ribosome-sensed induction and efflux pump activation initially protected the cell through induction of expression and allowed it to survive low levels of antibiotics. Subsequently, mutations were promoted by the stress-induced SOS response that stimulated modulation of genetic instability, and these mutations resulted in resistance to even higher antibiotic concentrations. The initial adaptation at the expression level enabled a subsequent trial and error search for the optimal mutations. The quantitative adjustment of cellular processes at different levels accelerated the acquisition of antibiotic resistance.
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