Oscillations by minimal bacterial suicide circuits reveal hidden facets of host-circuit physiology.
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 P(luxI) 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.
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Journal articlePermalink
https://hdl.handle.net/10161/4558Published Version (Please cite this version)
10.1371/journal.pone.0011909Publication Info
Marguet, Philippe; Tanouchi, Yu; Spitz, Eric; Smith, Cameron; & You, Lingchong (2010). Oscillations by minimal bacterial suicide circuits reveal hidden facets of host-circuit
physiology. PLoS One, 5(7). pp. e11909. 10.1371/journal.pone.0011909. Retrieved from https://hdl.handle.net/10161/4558.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Lingchong You
James L. Meriam Distinguished Professor of Biomedical Engineering
The You lab uses a combination of mathematical modeling, machine learning, and quantitative
experiments to elucidate principles underlying the dynamics of microbial communities
in time and space and to control these dynamics for applications in computation, engineering,
and medicine.

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