Team:UNIPV-Pavia

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UNIPV-Pavia
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<h2 class="art-postheader">The project</h2>
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<p align='justify'>Our work aims at implementing the engineering concept of closed-loop control in <em>E. coli</em>, exploiting quorum sensing. As a proof of concept, we designed a simple genetic controller that regulates the concentration of 3OC6-HSL signalling molecule around  a user-defined set-point. The controlled variable (3OC6-HSL) increases as a function of the exogenous anhydroTetracycline input, that triggers LuxI expression. The controller senses the 3OC6-HSL concentration and activates the production of AiiA, that degrades it.
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To observe the desired behaviour, a fine tuning of the system was necessary.  The transcriptional/translational strength of the regulatory elements (promoter+RBS in several combinations) and the enzyme activities were measured and exploited to identify a mathematical model able to predict the behaviour of the controlled system. These predictions made possible an in silico rational fine tuning of the circuit: the most promising modules were selected and assembled into the final circuit, avoiding a cost and time expensive combinatorial approach.
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Latest revision as of 13:14, 19 September 2011

UNIPV TEAM 2011


The project

Our work aims at implementing the engineering concept of closed-loop control in E. coli, exploiting quorum sensing. As a proof of concept, we designed a simple genetic controller that regulates the concentration of 3OC6-HSL signalling molecule around a user-defined set-point. The controlled variable (3OC6-HSL) increases as a function of the exogenous anhydroTetracycline input, that triggers LuxI expression. The controller senses the 3OC6-HSL concentration and activates the production of AiiA, that degrades it. To observe the desired behaviour, a fine tuning of the system was necessary. The transcriptional/translational strength of the regulatory elements (promoter+RBS in several combinations) and the enzyme activities were measured and exploited to identify a mathematical model able to predict the behaviour of the controlled system. These predictions made possible an in silico rational fine tuning of the circuit: the most promising modules were selected and assembled into the final circuit, avoiding a cost and time expensive combinatorial approach.


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Laboratory for Biomedical Informatics | Centre of Tissutal Engineering

University of Pavia
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