ArticleNPJ biofilms and microbiomes2018
How do environment-dependent switching rates between susceptible and persister cells affect the dynamics of biofilms faced with antibiotics?
Article in NPJ biofilms and microbiomes, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Matrix-producing cells' orientation order facilitates Bacillus subtilis biofilm self-healing.Archives of microbiology · 2024Article
- Optimization of periodic treatment strategies for bacterial biofilms using an agent-basedJournal of the Royal Society, Interface · 2024Article
- Reaching unreachables: Obstacles and successes of microbial cultivation and their reasons.Frontiers in microbiology · 2023Review
- Analytics and visualization tools to characterize single-cell stochasticity using bacterial single-cell movie cytometry data.BMC bioinformatics · 2021Article
- Design, synthesis, and antibacterial activity ofRSC medicinal chemistry · 2021Article
- Agent Based Models of Polymicrobial Biofilms and the Microbiome-A Review.Microorganisms · 2021Review
- Persistence as an Optimal Hedging Strategy.Biophysical journal · 2021Article
- The ecology of plasmid-coded antibiotic resistance: a basic framework for experimental research and modeling.Computational and structural biotechnology journal · 2021Review
- Article
- Intra-colony channels in E. coli function as a nutrient uptake system.The ISME journal · 2020Article
- Pulse Dosing of Antibiotic Enhances Killing of aFrontiers in microbiology · 2020Article
- Ampicillin-treated Lactococcus lactis MG1363 populations contain persisters as well as viable but non-culturable cells.Scientific reports · 2019Article
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Authors and funding
4 authors.
Funding
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Abstract
Persisters form sub-populations of stress-tolerant cells that play a major role in the capacity of biofilms to survive and recover from disturbances such as antibiotic treatments. The mechanisms of persistence are diverse and influenced by environmental conditions, and persister populations are more heterogeneous than formerly suspected. We used computational modeling to assess the impact of three switching strategies between susceptible and persister cells on the capacity of bacterial biofilms to grow, survive and recover from antibiotic treatments. The strategies tested were: (1) constant switches, (2) substrate-dependent switches and (3) antibiotic-dependent switches. We implemented these strategies in an individual-based biofilm model and simulated antibiotic shocks on virtual biofilms. Because of limited available data on switching rates in the literature, nine parameter sets were assessed for each strategy. Substrate and antibiotic-dependent switches allowed high switching rates without affecting the growth of the biofilms. Compared to substrate-dependent switches, constant and antibiotic-dependent switches were associated with higher proportions of persisters in the top of the biofilms, close to the substrate source, which probably confers a competitive advantage within multi-species biofilms. The constant and substrate-dependent strategies need a compromise between limiting the wake-up and death of persisters during treatments and leaving the persister state fast enough to recover quickly after antibiotic-removal. Overall, the simulations gave new insights into the relationships between the dynamics of persister populations in biofilms and their dynamics of growth, survival and recovery when faced with disturbances.
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Registered trials
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