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-	[[Berkeley2006-NandMain | Logic Computation in Cellular Networks]]<br>	+	[[Berkeley2006-NandMain | Logic Computation in Bacterial Networks]]<br>
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-	[[Berkeley2006-NetworksMain | Extending to Cellular Networks]] <br>	+	[[Berkeley2006-NetworksMain | Trained Learning in a Bacterial Network]] <br>

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Revision as of 04:26, 28 October 2006

Addressable Conjugation in Bacterial Networks

Networks of interacting cells provide the basis for neural learning. We have developed the process of addressable conjugation for communication within a network of E. coli bacteria. Here, bacteria send messages to one another via conjugation of plasmid DNAs, but the message is only meaningful to cells with a matching address sequence. In this way, the Watson Crick base-pairing of addressing sequences replaces the spatial connectivity present in neural systems. To construct this system, we have adapted natural conjugation systems as the communication device. Information contained in the transferred plasmids is only accessable by "unlocking" the message using RNA based 'keys'. The resulting addressable conjugation process is being adapted to construct a network of NAND logic gates in bacterial cultures. Ultimately, this will allow us to develop networks of bacteria capable of trained learning.

Our Team High School Matt Fleming Kaitlin A. Davis Undergrads Bryan Hernandez Jennifer Lu Samantha Liang Daniel Kluesing Will Bosworth Postdocs John E. Dueber J. Christopher Anderson Faculty Advisors Adam P. Arkin Jay D. Keasling

The specific goals of our project were to: Construct high-performance riboregulator pairs Harness the process of bacterial conjugation Demonstrate transmission of a coded message Develop promoter tools to tune gene expression To learn more about our system, follow the series of descriptions below: High-performance Riboregulators Harnessing Bacterial Conjugation Tuning Constitutive Expression Levels Logic Computation in Bacterial Networks Trained Learning in a Bacterial Network

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