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通过对称性降低复杂性:揭示细菌逻辑计算的最小调控网络。

Complexity reduction by symmetry: Uncovering the minimal regulatory network for logical computation in bacteria.

作者信息

Álvarez-García Luis A, Liebermeister Wolfram, Leifer Ian, Makse Hernán A

机构信息

Levich Institute and Physics Department, City College of New York, New York, New York 10031, United States of America.

Université Paris-Saclay, INRAE, MaIAGE, 78350 Jouy-en-Josas, France.

出版信息

PLoS Comput Biol. 2025 Apr 24;21(4):e1013005. doi: 10.1371/journal.pcbi.1013005. eCollection 2025 Apr.

Abstract

Symmetry principles play an important role in geometry, and physics, allowing for the reduction of complicated systems to simpler, more comprehensible models that preserve the system's features of interest. Biological systems are often highly complex and may consist of a large number of interacting parts. Using symmetry fibrations, the relevant symmetries for biological "message-passing" networks, we introduce a scheme, called Complexity Reduction by Symmetry or CoReSym, to reduce the gene regulatory networks of Escherichia coli and Bacillus subtilis bacteria to core networks in a way that preserves the dynamics and uncovers the computational capabilities of the network. Gene nodes in the original network that share isomorphic input trees are collapsed by the fibration into equivalence classes called fibers, whereby nodes that receive signals with the same "history" belong to one fiber and synchronize. Then we reduce the networks to its minimal computational core via k-core decomposition. This computational core consists of a few strongly connected components or "signal vortices," in which signals can cycle through. While between them, these "signal vortices" transmit signals in a feedforward manner. These connected components perform signal processing and decision making in the bacterial cell by employing a series of genetic toggle-switch circuits that store memory, plus oscillator circuits. These circuits act as the central computation device of the network, whose output signals then spread to the rest of the network. Our reduction method opens the door to narrow the vast complexity of biological systems to their minimal parts in a systematic way by using fundamental theoretical principles of symmetry.

摘要

对称原理在几何学和物理学中发挥着重要作用,它能将复杂系统简化为更简单、更易理解的模型,同时保留系统的关键特征。生物系统通常高度复杂,可能由大量相互作用的部分组成。利用对称纤维化,即生物“信息传递”网络的相关对称性,我们引入了一种名为“对称降维法”(Complexity Reduction by Symmetry或CoReSym)的方案,以一种保留动力学并揭示网络计算能力的方式,将大肠杆菌和枯草芽孢杆菌的基因调控网络简化为核心网络。原始网络中共享同构输入树的基因节点通过纤维化被合并为称为纤维的等价类,即接收具有相同“历史”信号的节点属于一个纤维并同步。然后,我们通过k - 核分解将网络简化为其最小计算核心。这个计算核心由几个强连通分量或“信号涡旋”组成,信号可以在其中循环。而在它们之间,这些“信号涡旋”以前馈方式传输信号。这些连通分量通过采用一系列存储记忆的基因拨动开关电路以及振荡器电路,在细菌细胞中执行信号处理和决策。这些电路充当网络的中央计算设备,其输出信号随后传播到网络的其余部分。我们的降维方法为利用对称的基本理论原理,以系统的方式将生物系统的巨大复杂性缩小到其最小部分打开了大门。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e79/12048163/60a9c396ac9d/pcbi.1013005.g001.jpg

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