Plasmids play a central role in the spread of antibiotic resistance among bacterial species, thereby decreasing the effectiveness of various chemotherapeutic agents for the treatment of infectious diseases. These mobile genetic elements are very common in bacteria and their horizontal transfer is key in the adaptive evolution of these organisms. The long-term goal of this study is to understand the population biology of transmissible plasmids in spatially structured microbial communities: What are the mechanisms that drive the horizontal transfer and persistence of these mobile genetic elements? Why do they persist, even in the absence of selection for any of the genes they carry? How does the spatial structure of natural microbial communities influence the ecological and evolutionary dynamics of plasmid-bacteria interactions? Therefore, a joint theoretical and experimental investigation into the role of spatial structure in the spread and persistence of self-transmissible antibiotic resistance plasmids is proposed.
The specific aims of this proposal are to construct 2-dimensional and 3-dimensional stochastic cellular automata (CA) models that can be used to accurately predict the spread and persistence of natural antibiotic resistance plasmids in bacterial colonies growing on agar surfaces and in biofilms. These two settings are needed for carefully controlled comparisons with non-spatial (liquid) environments and estimation of spatially relevant parameters, and for understanding the extent to which the complex spatially heterogeneous structure of biofilms further influences plasmid transfer and persistence. To validate and/or modify the models, a sequence of parallel in vitro and in silico experiments will be performed. Each such pair of experiments will serve to (a) validate or reject the particular model as pertains to a specific biological hypothesis; (b) suggest model refinements; (c) test the biological hypothesis; and (d) formulate alternative hypotheses in the event that the original hypothesis is rejected.
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