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LsrR quorum sensing "switch" is revealed by a bottom-up approach.


ABSTRACT: Quorum sensing (QS) enables bacterial multicellularity and selective advantage for communicating populations. While genetic "switching" phenomena are a common feature, their mechanistic underpinnings have remained elusive. The interplay between circuit components and their regulation are intertwined and embedded. Observable phenotypes are complex and context dependent. We employed a combination of experimental work and mathematical models to decipher network connectivity and signal transduction in the autoinducer-2 (AI-2) quorum sensing system of E. coli. Negative and positive feedback mechanisms were examined by separating the network architecture into sub-networks. A new unreported negative feedback interaction was hypothesized and tested via a simple mathematical model. Also, the importance of the LsrR regulator and its determinant role in the E. coli QS "switch", normally masked by interfering regulatory loops, were revealed. Our simple model allowed mechanistic understanding of the interplay among regulatory sub-structures and their contributions to the overall native functioning network. This "bottom up" approach in understanding gene regulation will serve to unravel complex QS network architectures and lead to the directed coordination of emergent behaviors.

SUBMITTER: Hooshangi S 

PROVIDER: S-EPMC3182856 | biostudies-literature | 2011 Sep

REPOSITORIES: biostudies-literature

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LsrR quorum sensing "switch" is revealed by a bottom-up approach.

Hooshangi Sara S   Bentley William E WE  

PLoS computational biology 20110929 9


Quorum sensing (QS) enables bacterial multicellularity and selective advantage for communicating populations. While genetic "switching" phenomena are a common feature, their mechanistic underpinnings have remained elusive. The interplay between circuit components and their regulation are intertwined and embedded. Observable phenotypes are complex and context dependent. We employed a combination of experimental work and mathematical models to decipher network connectivity and signal transduction  ...[more]

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