ArticleAntimicrobial agents and chemotherapy2020
Simulating the Influence of Conjugative-Plasmid Kinetic Values on the Multilevel Dynamics of Antimicrobial Resistance in a Membrane Computing Model.
Article in Antimicrobial agents and chemotherapy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 26 citations in OpenAlex.
- What are the missing pieces needed to stop antibiotic resistance?Microbial biotechnology · 2023Review
- Co-evolutionary adaptations ofEvolutionary applications · 2022Article
- Stress-Induced Mutagenesis, Gambler Cells, and Stealth Targeting Antibiotic-Induced Evolution.mBio · 2022Review
- Models for Gut-Mediated Horizontal Gene Transfer by Bacterial Plasmid Conjugation.Frontiers in microbiology · 2022Review
- Simulating the efficacy of vaccines on the epidemiological dynamics of SARS-CoV-2 in a membrane computing model.microLife · 2022Article
- Predicting plasmid persistence in microbial communities by coarse-grained modeling.BioEssays : news and reviews in molecular, cellular and developmental biology · 2021Article
- Simulating the impact of non-pharmaceutical interventions limiting transmission in COVID-19 epidemics using a membrane computing model.microLife · 2021Article
- The ecology of plasmid-coded antibiotic resistance: a basic framework for experimental research and modeling.Computational and structural biotechnology journal · 2021Review
- Antibiotic resistance: Time of synthesis in a post-genomic age.Computational and structural biotechnology journal · 2021Review
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Authors and funding
7 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Bacterial plasmids harboring antibiotic resistance genes are critical in the spread of antibiotic resistance. It is known that plasmids differ in their kinetic values, i.e., conjugation rate, segregation rate by copy number incompatibility with related plasmids, and rate of stochastic loss during replication. They also differ in cost to the cell in terms of reducing fitness and in the frequency of compensatory mutations compensating plasmid cost. However, we do not know how variation in these values influences the success of a plasmid and its resistance genes in complex ecosystems, such as the microbiota. Genes are in plasmids, plasmids are in cells, and cells are in bacterial populations and microbiotas, which are inside hosts, and hosts are in human communities at the hospital or the community under various levels of cross-colonization and antibiotic exposure. Differences in plasmid kinetics might have consequences on the global spread of antibiotic resistance. New membrane computing methods help to predict these consequences. In our simulation, conjugation frequency of at least 10
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