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Center for Nonlinear Studies |
Bacteria employ quorum sensing, a form of cell-cell communication, to sense changes in the population density and regulate gene expression accordingly [6]. A number of bacteria regulate virulence factors using this communication, including the opportunistic human pathogen Pseudomonas aeruginosa [5], which is responsible for death in cystic fibrosis patients and high mortality rates in immunocompromised individuals. Additionally, this communication has been re-engineered in bacteria for biotechnology applications such as tumor therapy [1] and pattern formation [2]. While mathematical modeling has provided a systems-level understanding of quorum sensing and enhanced our ability to re-engineer it, several key predictions have yet to be experimentally verified.
First, modeling predicts that genes regulated by quorum sensing should exhibit hysteresis in their expression [4]. By rewiring one quorum-sensing module, the lux circuit from the marine bacterium Vibrio fischeri, we experimentally verified the steady-state behaviors of different network architectures and identified those capable of hysteresis. We also used these findings to predict the behaviors of quorum-sensing operons in bacterial pathogens.
Second, quorum sensing is commonly thought to coordinate population behavior [6]. Experimentally, we find that the choice of network architecture determines the extent of this coordination, with the best population coordination being achieved by an architecture in which the signaling molecule is manipulated by positive feedback. Interestingly, this architecture is commonly found in autocrine signaling, such as Spitz signaling in Drosophila development [3] and the interferon antiviral response [7]. Hence signal manipulation appears to be a fundamental principle for coordinating cellular decision making.
References
1. Anderson et al. 2006. J. Mol. Biol. 355:619–627.
2. Basu et al. 2005. Nature 434:1130–1134.
3. Freeman 2000. Nature 408:313–319.
4. James et al. 2000. J. Mol. Biol. 296:1127–1137.
5. Lazdunski et al. 2004. Nat. Rev. Microbiol. 2:581–592.
6. Miller and Bassler 2001. Annu. Rev. Microbiol. 55:165–199.
7. Taniguchi and Takaoka 2001. Nat. Rev. Mol. Cell. Biol. 2:378–386.