Research Article
Implementing in vivo Cellular Automata using Toggle Switch and Inter-Bacteria Communication Mechanism
@INPROCEEDINGS{10.4108/ICST.BIONETICS2007.2410, author={Yasubumi Sakakibara and Hirotaka Nakagawa and Yusaku Nakashima and Katsuyuki Yugi}, title={Implementing in vivo Cellular Automata using Toggle Switch and Inter-Bacteria Communication Mechanism}, proceedings={1st International ICST Workshop on Computing and Communications from Biological Systems: Theory and Applications}, proceedings_a={CCBS}, year={2008}, month={8}, keywords={Biological systems Cancer Circuits Communication switching Genetics In vivo Logic gates Protein engineering Switches Turing machines}, doi={10.4108/ICST.BIONETICS2007.2410} }- Yasubumi Sakakibara
Hirotaka Nakagawa
Yusaku Nakashima
Katsuyuki Yugi
Year: 2008
Implementing in vivo Cellular Automata using Toggle Switch and Inter-Bacteria Communication Mechanism
CCBS
IEEE
DOI: 10.4108/ICST.BIONETICS2007.2410
Abstract
Artificial genetic circuits have been recently proposed to realize unprecedented biological systems which do not exist in nature by combining several genes. For example, recombinant Escherichia coli provides novel artificial functions such as blinking periodically or invading cancer cells. In protein engineering, new functional proteins have been created by site-directed mutagenesis methods. The main purpose of our research is to implement the Cellular Automata (CA) in vivo employing these methods. Computational capacity of CA is equivalent to the universal Turing Machine. CA are multi-cellular systems in which uniform cells are allocated on lattice grid. Each cell has a finite number of states. The state transition is determined by the current state and the states of neighbor cells. Three mechanisms are required to implement CA in bacteria: (1) Sending and receiving signals between cells, (2) Sustaining the state, (3) Sensing input signals and changing the state following the state transition rules. To encode signals for the mechanism (1), we use small molecules inducing transcription. For the mechanism (2), the toggle switch circuit was employed to represent a finite number of states using gene expression. If one gene does express and the other does not, the state is 1, and vice versa, 0. For the mechanism (3), the state transition functions were implemented as logic gates using transcriptional regulatory proteins which bind to specific signal molecules (chemicals). In this paper, we applied this method to in vivo implementation of one-dimensional CA and corroborated whether it behaves correctly. In principle, this method can be applied to any dimensional CA by employing more signal molecules Permission to make digital or hard copies of all or part of this work for to construct more complex logic gate. Furthermore, we succeeded to execute one step calculation of one-dimensional CA in vivo in a laboratory experiment.