From deterministic to fuzzy decision-making in artificial cells

Ferdinand Greiss, Shirley S. Daube, Vincent Noireaux and Roy Bar-Ziv ()
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Ferdinand Greiss: Weizmann Institute of Science
Shirley S. Daube: Weizmann Institute of Science
Vincent Noireaux: University of Minnesota
Roy Bar-Ziv: Weizmann Institute of Science

Nature Communications, 2020, vol. 11, issue 1, 1-9

Abstract: Abstract Building autonomous artificial cells capable of homeostasis requires regulatory networks to gather information and make decisions that take time and cost energy. Decisions based on few molecules may be inaccurate but are cheap and fast. Realizing decision-making with a few molecules in artificial cells has remained a challenge. Here, we show decision-making by a bistable gene network in artificial cells with constant protein turnover. Reducing the number of gene copies from 105 to about 10 per cell revealed a transition from deterministic and slow decision-making to a fuzzy and rapid regime dominated by small-number fluctuations. Gene regulation was observed at lower DNA and protein concentrations than necessary in equilibrium, suggesting rate enhancement by co-expressional localization. The high-copy regime was characterized by a sharp transition and hysteresis, whereas the low-copy limit showed strong fluctuations, state switching, and cellular individuality across the decision-making point. Our results demonstrate information processing with low-power consumption inside artificial cells.

Date: 2020
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DOI: 10.1038/s41467-020-19395-4

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