Team:ETH Zurich/project/overview/summary

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Emergence of complex patterns in nature is a fascinating and widely spread phenomenon, which is not fully understood yet. Mosai''coli'' aims to investigate emergence of complex patterns from a simple rule by engineering a cellular automaton into ''E. coli'' bacteria. This automaton comprises a grid of colonies on a 3D-printed millifluidic chip. Each colony is either in an ON or OFF state and updates its state by integrating signals from its neighbors according to a genetically pre-programmed logic rule. Complex patterns such as Sierpinski triangles are visualized by fluorescence after several steps of row-wise propagation. Sequential logic computation based on quorum sensing is challenged by leakiness and crosstalk present in biological systems. Mosai''coli'' overcomes these issues by exploiting multichannel orthogonal communication, riboregulators and integrase-based XOR logic gates. Engineering such a reliable system not only enables a better understanding of emergent patterns, but also provides novel building blocks for biological computers.
Emergence of complex patterns in nature is a fascinating and widely spread phenomenon, which is not fully understood yet. Mosai''coli'' aims to investigate emergence of complex patterns from a simple rule by engineering a cellular automaton into ''E. coli'' bacteria. This automaton comprises a grid of colonies on a 3D-printed millifluidic chip. Each colony is either in an ON or OFF state and updates its state by integrating signals from its neighbors according to a genetically pre-programmed logic rule. Complex patterns such as Sierpinski triangles are visualized by fluorescence after several steps of row-wise propagation. Sequential logic computation based on quorum sensing is challenged by leakiness and crosstalk present in biological systems. Mosai''coli'' overcomes these issues by exploiting multichannel orthogonal communication, riboregulators and integrase-based XOR logic gates. Engineering such a reliable system not only enables a better understanding of emergent patterns, but also provides novel building blocks for biological computers.
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Revision as of 17:57, 1 October 2014



Mosaicoli : from simplicity to complexity with biologic gates

Scientific abstract



Emergence of complex patterns in nature is a fascinating and widely spread phenomenon, which is not fully understood yet. Mosaicoli aims to investigate emergence of complex patterns from a simple rule by engineering a cellular automaton into E. coli bacteria. This automaton comprises a grid of colonies on a 3D-printed millifluidic chip. Each colony is either in an ON or OFF state and updates its state by integrating signals from its neighbors according to a genetically pre-programmed logic rule. Complex patterns such as Sierpinski triangles are visualized by fluorescence after several steps of row-wise propagation. Sequential logic computation based on quorum sensing is challenged by leakiness and crosstalk present in biological systems. Mosaicoli overcomes these issues by exploiting multichannel orthogonal communication, riboregulators and integrase-based XOR logic gates. Engineering such a reliable system not only enables a better understanding of emergent patterns, but also provides novel building blocks for biological computers.

Emergence of the pattern

Every cell of the cellular automaton on the grid below computes an XOR of the two signals coming from above in the figure below. XOR means that if only one of the two signals (red or blue) is received, the cell receiving should turn ON (and show green fluorescence), whereas if none or both of the signals are received, the cell should stay OFF (do nothing).




Pass the mouse on the different colonies to understand how they process the signals coming from the top and make the pattern appear.

Input
3OC12HSL added to the first well



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