Dynamic evolution of heterogeneous plasmid ensembles during bacterial growthView all posters
Northwestern University, United States
A grand challenge in synthetic biology is the development of engineered biological functions that operate robustly in multiple cell types and under a variety of conditions. Plasmid-based approaches to engineering microbes are convenient and widely-used, but in multi-plasmid systems, cell-to-cell variability in plasmid copy number and plasmid identity can generate heterogeneous phenotypes between different cells within a population. Moreover, such heterogeneity varies with both method of copy number regulation and regime of cell growth, which is tied to growth substrate utilized. Although these effects are known to exist and potentially complicate the engineering of complex synthetic functions, we lack a quantitative understanding and framework for incorporating these effects into the design and analysis of engineered cellular functions. To meet this need, we present a novel agent-based computational framework for describing and predicting the dynamics of heterogeneous plasmid ensembles within individual cells in a bacterial population. This model was calibrated against both bulk and single-cell experimental measures of cell count, plasmid content, and genome replication under various growth regimes. Our agent-based simulation provides the first computational tool for investigating plasmid ensemble dynamics at the individual cell level in a manner that explicitly incorporates mechanisms of cell growth and plasmid replication and regulation. This approach should facilitate analysis and design of improved plasmid-based synthetic functions. Because our modeling framework is mechanistically driven, this approach can be extended to incorporate and investigate other phenomena that are of both fundamental biological interest and may represent potential tools for synthetic biology, such as exchange of mobile genetic elements via bacteriophage and conjugation and plasmid coupling via toxin-antitoxin interactions.