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Testing our Assumptions of Biological Systems

One of the most important aspects of synthetic biology is that it allows us to definitively test our knowledge of systems biology. By building rationally designed networks of genes, we can determine if our understanding of how networks function is incomplete. At such an early stage in the development of the field of synthetic biology, the construction of synthetic cellular memory is a particularly effective method of performing these tests of our understanding. The memory networks described in this paper are relatively simple, and they closely mimic common networks that are observed in nature. Based on the accuracy of the mathematical models that were presented in the three papers discussed, it is obvious that we have a fairly accurate level of understanding of these simple networks. Establishing simple but functional networks will allow for more effective troubleshooting of more complex networks. In this way, synthetic biology can build on past research of simple systems to find holes in our understanding of complex systems.

Real World Applications

In the long run, modular synthetic cellular memory circuits will likely be used in many different types of synthetic devices. To create modularity, the inputs and outputs of memory circuits need to be changeable. As our library of activators/repressors expands, it will be easier to construct memory circuits that are sensitive to a variety of environmental inputs. Memory outputs can be modified by exchanging a reporter gene with a gene or set of genes that will perform some specific cellular function. Obvious real world applications of such memory circuits include the detection of harmful chemicals in various environments (e.g. drinking water) and computation through the use of living organisms. When included in more complex gene networks, modular cellular memory could be implemented in gene therapies and in the engineering of controlled cell differentiation (Gardner, 2000 and Ajo-Franklin, 2007).

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