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面向人工细胞器的膜限制液-液相分离

Membrane-confined liquid-liquid phase separation toward artificial organelles.

作者信息

Mu Wenjing, Ji Zhen, Zhou Musen, Wu Jianzhong, Lin Yiyang, Qiao Yan

机构信息

Beijing National Laboratory for Molecular Sciences (BNLMS), Laboratory of Polymer Physics and Chemistry, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China.

University of Chinese Academy of Sciences, Beijing 100049, China.

出版信息

Sci Adv. 2021 May 28;7(22). doi: 10.1126/sciadv.abf9000. Print 2021 May.

DOI:10.1126/sciadv.abf9000
PMID:34049872
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8163073/
Abstract

As the basic unit of life, cells are compartmentalized microreactors with molecularly crowded microenvironments. The quest to understand the cell origin inspires the design of synthetic analogs to mimic their functionality and structural complexity. In this work, we integrate membraneless coacervate microdroplets, a prototype of artificial organelles, into a proteinosome to build hierarchical protocells that may serve as a more realistic model of cellular organization. The protocell subcompartments can sense extracellular signals, take actions in response to these stimuli, and adapt their physicochemical behaviors. The tiered protocells are also capable of enriching biomolecular reactants within the confined organelles, thereby accelerating enzymatic reactions. The ability of signal processing inside protocells allows us to design the Boolean logic gates (NOR and NAND) using biochemical inputs. Our results highlight possible exploration of protocell-community signaling and render a flexible synthetic platform to study complex metabolic reaction networks and embodied chemical computation.

摘要

作为生命的基本单位,细胞是具有分子拥挤微环境的区室化微反应器。对细胞起源的探索激发了合成类似物的设计,以模仿其功能和结构复杂性。在这项工作中,我们将无膜凝聚微滴(一种人工细胞器的原型)整合到蛋白体中,构建分层原细胞,其可作为更现实的细胞组织模型。原细胞亚区室能够感知细胞外信号,对这些刺激做出反应,并调整其物理化学行为。分层原细胞还能够在受限的细胞器内富集生物分子反应物,从而加速酶促反应。原细胞内部的信号处理能力使我们能够利用生化输入设计布尔逻辑门(或非门和与非门)。我们的结果突出了对原细胞群落信号传导进行探索的可能性,并提供了一个灵活的合成平台来研究复杂的代谢反应网络和具体的化学计算。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2415/8163073/b8a9684a55ed/abf9000-F3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2415/8163073/29bb81ce81d1/abf9000-F1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2415/8163073/58e2fcf55efb/abf9000-F2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2415/8163073/b8a9684a55ed/abf9000-F3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2415/8163073/29bb81ce81d1/abf9000-F1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2415/8163073/58e2fcf55efb/abf9000-F2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2415/8163073/b8a9684a55ed/abf9000-F3.jpg

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本文引用的文献

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Artificial cells drive neural differentiation.人工细胞驱动神经分化。
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