Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot, 76100, Israel.
Department of Physics, University of Minnesota, Minneapolis, MN, 55455, USA.
Nat Commun. 2020 Nov 6;11(1):5648. doi: 10.1038/s41467-020-19395-4.
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 10 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.
构建能够自我维持的自主人工细胞需要调控网络来收集信息并做出决策，而这需要耗费时间和能量。基于少量分子做出的决策可能不够准确，但却具有成本低、速度快的优势。用少量分子在人工细胞中实现决策仍然是一个挑战。在这里，我们展示了在具有恒定蛋白质周转率的人工细胞中，双稳态基因网络做出决策的过程。将基因拷贝数从每个细胞 10 个左右减少到大约 10 个，发现细胞从确定性和缓慢的决策转变为由小数量波动主导的模糊和快速状态。基因调控发生在低于平衡所需的 DNA 和蛋白质浓度下，这表明通过共表达定位增强了反应速率。高拷贝数状态的特点是急剧的转变和滞后，而低拷贝数极限则表现出强烈的波动、状态切换和细胞个体性，这些都跨越了决策点。我们的研究结果证明了低功耗信息处理可以在人工细胞内进行。
