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Nat Commun. 2014;5:3102. doi: 10.1038/ncomms4102.

Programming a Pavlovian-like conditioning circuit in Escherichia coli.

Author information

1
1] Peking-Tsinghua Joint Centre for Life Sciences, Peking University, Beijing 100871, China [2] Peking University Team for the International Genetically Engineered Machine Competition (iGEM), Peking University, Beijing 100871, China [3] Centre for Quantitative Biology, Peking University, Beijing 100871, China [4].
2
1] Peking University Team for the International Genetically Engineered Machine Competition (iGEM), Peking University, Beijing 100871, China [2].
3
Peking University Team for the International Genetically Engineered Machine Competition (iGEM), Peking University, Beijing 100871, China.
4
1] Peking University Team for the International Genetically Engineered Machine Competition (iGEM), Peking University, Beijing 100871, China [2] Centre for Quantitative Biology, Peking University, Beijing 100871, China.
5
1] Peking-Tsinghua Joint Centre for Life Sciences, Peking University, Beijing 100871, China [2] Centre for Quantitative Biology, Peking University, Beijing 100871, China [3] The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics, School of Physics, Peking University, Beijing 100871, China.

Abstract

Synthetic genetic circuits are programmed in living cells to perform predetermined cellular functions. However, designing higher-order genetic circuits for sophisticated cellular activities remains a substantial challenge. Here we program a genetic circuit that executes Pavlovian-like conditioning, an archetypical sequential-logic function, in Escherichia coli. The circuit design is first specified by the subfunctions that are necessary for the single simultaneous conditioning, and is further genetically implemented using four function modules. During this process, quantitative analysis is applied to the optimization of the modules and fine-tuning of the interconnections. Analogous to classical Pavlovian conditioning, the resultant circuit enables the cells to respond to a certain stimulus only after a conditioning process. We show that, although the conditioning is digital in single cells, a dynamically progressive conditioning process emerges at the population level. This circuit, together with its rational design strategy, is a key step towards the implementation of more sophisticated cellular computing.

PMID:
24434523
DOI:
10.1038/ncomms4102
[Indexed for MEDLINE]

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