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Team:Minnesota
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Welcome!
Welcome to the Team Minnesota Wiki for iGEM 2009!
We are a team of undergraduate and graduate students along with many advisors. This is the second year that Minnesota has sent a team to iGEM. Last year we were runners-up for the Best New BioBrick part (Natural) and we hope to accomplish even more with our design of a logical AND gate in E. coli this year.
The Mission
Synthetic biology is the design and construction of new biological parts, devices, and systems, and the re-design of existing, natural biological systems for useful purposes. Recently, the field of synthetic biology has produced genetic circuits that are capable of emulating logic circuits commonly found in digital electronics. One such circuit is an AND gate, which takes two inputs and produces a response if and only if both inputs are present. Otherwise the system produces no response. A system capable of generating these responses has been produced in both prokaryotes and eukaryotes. However, these systems are not high fidelity logic gates because of the fact that they are in biological systems. This is the problem our group will work on this summer.
We will use a very well studied AND gate, which is composed of elements of the Tet, Lac, and lambda-phage promoters and is responsive to the commonly-used inducers IPTG and aTc, producing GFP as an output signal. Instead of using the AND gate in its complete form, we will isolate elements of the gate and study them individually. This will allow for a greater understanding of how exactly this AND gate works, and will eventually allow for creation of better AND gates, and a more predictable response to inputs by the biological systems.
Our group will be doing both experimental and modeling work this year. These two approachs will both complement each other. The experimental data will be used to refine the mathematical models, while the models will determine good directions for the experiments to pursue. We will go into greater detail on both these aspects on theeir respective wiki pages. The approach we are taking can be applied to many other biological circuits and can lead to greater understanding of how to engineer biological circuits.
