ArticleMolecular biology and evolution2020
Stochastic Gene Expression Influences the Selection of Antibiotic Resistance Mutations.
Article in Molecular biology and evolution, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 12 citations in OpenAlex.
- Gillespie-based simulation and inference for non-Markovian stochastic reaction networks.Briefings in bioinformatics · 2026Article
- Simple birth-death-mutation models predict some-but not all-aspects of the experimental evolution of antibiotic resistance.PLoS computational biology · 2026Article
- The impact of inoculation methods on bacterial aggregation and antimicrobial susceptibility testing.Microbiology (Reading, England) · 2026Article
- Eco-evolutionary dynamics and environmental detoxification jointly shape bacterial community response to antibiotic perturbation.The ISME journal · 2026Article
- Gene Editing for Enhanced Swine Production: Current Advances and Prospects.Animals : an open access journal from MDPI · 2025Review
- Phenotypic and genotypic characterization of antibiotic-resistant bacteria from Swiss ready-to-eat meat products.Frontiers in microbiology · 2025Article
- Plasmid-mediated phenotypic noise leads to transient antibiotic resistance in bacteria.Nature communications · 2024Article
- The Impact ofPathogens (Basel, Switzerland) · 2023Article
- Strategies to prevent, curb and eliminate biofilm formation based on the characteristics of various periods in one biofilm life cycle.Frontiers in cellular and infection microbiology · 2022Review
- Investigating heterogeneities of live mesenchymal stromal cells using AI-based label-free imaging.Scientific reports · 2021Article
- Review
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Bacteria can resist antibiotics by expressing enzymes that remove or deactivate drug molecules. Here, we study the effects of gene expression stochasticity on efflux and enzymatic resistance. We construct an agent-based model that stochastically simulates multiple biochemical processes in the cell and we observe the growth and survival dynamics of the cell population. Resistance-enhancing mutations are introduced by varying parameters that control the enzyme expression or efficacy. We find that stochastic gene expression can cause complex dynamics in terms of survival and extinction for these mutants. Regulatory mutations, which augment the frequency and duration of resistance gene transcription, can provide limited resistance by increasing mean expression. Structural mutations, which modify the enzyme or efflux efficacy, provide most resistance by improving the binding affinity of the resistance protein to the antibiotic; increasing the enzyme's catalytic rate alone may contribute to resistance if drug binding is not rate limiting. Overall, we identify conditions where regulatory mutations are selected over structural mutations, and vice versa. Our findings show that stochastic gene expression is a key factor underlying efflux and enzymatic resistances and should be taken into consideration in future antibiotic research.
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Registered trials
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