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RESEARCH PRODUCT

Simulating the Influence of Conjugative Plasmids Kinetic Values on the Multilevel Dynamics of Antimicrobial Resistance in a Membrane Computing Model

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AbstractPlasmids harboring antibiotic resistance genes differ in their kinetic values as plasmid conjugation rate, segregation rate by incompatibility with related plasmids, rate of stochastic loss during replication, cost reducing the host-cell fitness, and frequency of compensatory mutations to reduce plasmid cost, depending on the cell mutation frequency. How variation in these values influence the success of a plasmid and their resistance genes in complex ecosystems, as the microbiota? Genes are located in plasmids, plasmids in cells, cells in populations. These populations are embedded in ensembles of species in different human hosts, are able to exchange between them bacterial ensembles during cross-infection and are located in the hospital or the community setting, under various levels of antibiotic exposure. Simulations using new membrane computing methods help predict the influence of plasmid kinetic values on such multilevel complex system. In our simulation, conjugation frequency needed to be at least 10−3to clearly influence the dominance of a strain with a resistant plasmid. Host strains able to stably maintain two copies of similar plasmids harboring different resistances, coexistence of these resistances can occur in the population. Plasmid loss rates of 10−4or 10−5or plasmid fitness costs ≥0.06 favor the plasmids located in the most abundant species. The beneficial effect of compensatory mutations for plasmid fitness cost is proportional to this cost, only at high mutation frequencies (10−3-10−5). Membrane computing helps set a multilevel landscape to study the effect of changes in plasmid kinetic values on the success of resistant organisms in complex ecosystems.