Research Article
Synthetic ecosystem of Escherichia coli for discovery of novel cooperative and self-adaptive algorithms
@INPROCEEDINGS{10.4108/ICST.BIONETICS2008.4683, author={Kazufumi Hosoda and Kotaro Mori and Tetsuya Yomo and Yasunori Shiroguchi and Yoshinori Yamauchi and Akiko Kashiwagi}, title={Synthetic ecosystem of Escherichia coli for discovery of novel cooperative and self-adaptive algorithms}, proceedings={3d International ICST Conference on Bio-Inspired Models of Network, Information, and Computing Systems}, publisher={ICST}, proceedings_a={BIONETICS}, year={2010}, month={5}, keywords={Synthetic ecosystem Obligate mutualism Self-adaptive algorithm}, doi={10.4108/ICST.BIONETICS2008.4683} }
- Kazufumi Hosoda
Kotaro Mori
Tetsuya Yomo
Yasunori Shiroguchi
Yoshinori Yamauchi
Akiko Kashiwagi
Year: 2010
Synthetic ecosystem of Escherichia coli for discovery of novel cooperative and self-adaptive algorithms
BIONETICS
ICST
DOI: 10.4108/ICST.BIONETICS2008.4683
Abstract
Symbiosis of different biosystems is equivalent to the merge (adaptation) of different information networks. In order to understand the basis underlying symbiosis, we artificially constructed the simplest obligate and mutual symbiosis (obligate mutualism) composed of two different nutrient requiring mutants (auxotrophs) of Escherichia coli (E. coli), to find out a novel cooperative and self-adaptive algorithm. The constructed synthetic symbiosis grew with cooperative interactions and kept its growth in multiple subcultures. From the quantitative analyses, we found that E. coli in co-culture must keep their nutrient production rates at least 20-fold higher than those in solo-culture, indicating the presence of cooperative and self-adaptive mechanism regulating bacterial internal conditions for the symbiosis. Furthermore, we performed “on plate” culture and succeeded in finding a typical spatial pattern of the symbiotic colony. Further analyses of this synthetic symbiosis would provide a novel algorithm for self-organization of multiple biological networks, which is likely to be applicable for information networks.