Abstract
Synthetic biology seeks to enable programmed control of cellular behavior though engineered biological systems. These systems typically consist of synthetic circuits that function inside, and interact with, complex host cells possessing pre-existing metabolic and regulatory networks. Nevertheless, while designing systems, a simple well-defined interface between the synthetic gene circuit and the host is frequently assumed. We describe the generation of robust but unexpected oscillations in the densities of bacterium Escherichia coli populations by simple synthetic suicide circuits containing quorum components and a lysis gene. Contrary to design expectations, oscillations required neither the quorum sensing genes (luxR and luxI) nor known regulatory elements in the PluxI promoter. Instead, oscillations were likely due to density-dependent plasmid amplification that established a population-level negative feedback. A mathematical model based on this mechanism captures the key characteristics of oscillations, and model predictions regarding perturbations to plasmid amplification were experimentally validated. Our results underscore the importance of plasmid copy number and potential impact of “hidden interactions” on the behavior of engineered gene circuits - a major challenge for standardizing biological parts. As synthetic biology grows as a discipline, increasing value may be derived from tools that enable the assessment of parts in their final context.
Highlights
Synthetic biology [1,2,3,4,5,6] seeks to enable predictable engineering of cells and biological systems with altered or expanded function
The E protein is an inhibitor of MraY, an enzyme that catalyzes the production of the first lipid intermediate in E. coli cell wall synthesis
Given the frequent application of the quorum sensing in gene circuits [41,42,43,44,45,46,47,48], it is perhaps surprising that quorum sensing-like behavior resulting from plasmid amplification has not been described or encountered in synthetic systems until now
Summary
Synthetic biology [1,2,3,4,5,6] seeks to enable predictable engineering of cells and biological systems with altered or expanded function Critical to this effort is the (re)design of information processing that establishes the timing and execution of cellular operations. The scale and scope of cellular physiology, coupled with an imperfect understanding of the system and host components, make the construction of such models quite challenging For this reason, simplified models that assume a well-defined interface between the circuit and host, while ignoring the background processes of host metabolism, are generally employed. If the predictions generated by the simple models deviate from the experimental implementation it indicates that the model insufficiently encompassed the critical components and interactions of the system In this manner, the validity of common simplifying assumptions can partially addressed and refined during the design process
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