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Signal-amplifying genetic circuit enables in vivo observation of weak promoter activation in the Rhl quorum sensing system.

by: D Karig, R Weiss
Biotechnol Bioeng, Vol. 89, No. 6. (20 March 2005), pp. 709-718.


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Small changes in transcriptional activity often significantly affect phenotype but are not detectable in vivo by conventional means. To address this problem, we present a technique for detecting weak transcriptional responses using signal-amplifying genetic circuits. We apply this technique to reveal previously undetectable log phase responses of several Rhl quorum sensing controlled (qsc) promoters from Pseudomonas aeruginosa. Genetic circuits with Rhl promoters and transcriptional amplification components were built and tested in Escherichia coli. This enabled us to isolate the behavior of the promoters under study from Las and quinolone interactions. To amplify qsc promoter responses to acyl-homoserine lactones (AHL), the highly efficient lambda repressor gene was placed downstream of several Rhl promoters and coupled to a fluorescent reporter under the control of the lambda P(R) promoter. With amplification, up to approximately 100-fold differences in fluorescence levels between AHL induced and noninduced cultures were observed for promoters whose responses were otherwise not detectable. In addition, the combination of using signal amplification and performing experiments in E. coli simplified the analysis of AHL signal crosstalk. For example, we discovered that while a C4HSL/RhlR complex activates both qscrhlA and qscphzA1, a 3OC12HSL/RhlR complex activates qscphzA1 but not qscrhlA in our system. This crosstalk information is particularly important since one of the potential uses of amplification constructs is for the detection of specific quorum sensing signals in environmental and clinical isolates. Furthermore, the process of decomposing networks into basic parts, isolating these components in a well-defined background, and using amplification to characterize both crosstalk and cognate signal responses embodies an important approach to understanding complex genetic networks.


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