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Newcastle University iGEM 2008

The Gram Positve BugBuster

We are developing a diagnostic tool that enables the detection of a range of gram-positive bacterial pathogens endemic in patients around the world. Currently detection of these pathogens ranges from a few hours to several days. The system will use genetically engineered Bacillus subtilis, to detect a range of gram positive bacterial pathogens. Our principal targets at this stage are Staphylococcus aureus, and Streptococcus pneumonia. We are also considering the detection of a range of Bacillus species, Clostridium difficile, and Staphylococcus epidermis. This new system will enable visual detection of these pathogens within minutes. The bacteria will be detected by the Quorum sensing peptides that they secrete extracellularly. This will activate the expression of fluorescence proteins in our engineered Bacillus subtilis chassis that can be viewed under U.V light.

Our Bioinformatics approach will involve the production of a workbench that will incorporate a designed parts repository, constraints repository and an evolutionary algorithm. The EA will input from the parts repository and constraints repository to carry out a neural network simulation. Eventually the fittest model will be output that can be used to produce a DNA sequence. This will be synthesized and cloned into the Bacillus subtilis chassis.

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