GENETIC DEVICES PROCESS IN LIVING CELLS

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Forward engineering of synthetic genetic circuits-based artificial information processing devices, termed synthetic genetic devices, has been carried out by applying hierarchical computer and electronic design principles to biology in order to accomplish cellular biocomputing. Such devices with high computing power can process higher level information in microbes and mammalian cells. Expansion of the computing power of these devices with increasing complexity might lead to the solving of complex computing problems in certain areas where living cell-based biocomputing might outperform traditional computers. This thesis centrally focuses on distributed computing in engineered bacteria. Here artificial neural network (ANN) is adapted as a computing system in living Escherichia coli cells to develop a design framework for building complex computing functions including a 2-to-4 decoder and a 4-to-2 priority encoder. The basic concept of single layer ANN architecture is mapped into engineered E. coli cells where individual engineered bacterial cells, termed bactoneurons, carry cellular devices and act as artificial neuro-synapses. A complete set of rules is established to distribute the truth table of a function among multiple fragmented truth tables followed by the derivation of unit bactoneurons from those fragmented truth tables without considering the electronic circuit design of that function. When those bactoneurons are cultured together, they work similar to a single layer ANN type architecture and give rise to the original computing function.