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

ArXiv Pub Date : 2025-02-25
Luis A Álvarez-García, Wolfram Liebermeister, Ian Leifer, Hernán A Makse
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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 ComSym, 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.

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纤维对称揭示了细菌中逻辑计算的最小调节网络。
对称原理已被证明在物理学、深度学习和几何中很重要,可以将复杂的系统简化为更简单、更容易理解的模型,从而保留系统的兴趣特征。生物系统通常表现出高度的复杂性,并由大量相互作用的部分组成。使用对称性fibrations,即生物“信息传递”网络的相关对称性,我们以一种保留信息流并突出网络计算能力的方式减少了大肠杆菌和枯草芽孢杆菌的基因调控网络。共享同构输入树的节点被分组到称为纤维的等价类中,从而接收具有相同“历史”的信号的基因属于一个纤维并同步。我们通过k核分解去除“悬空端”,进一步将网络简化为其计算核心。网络的计算核心由几个强连接的组件组成,其中信号可以循环,而信号以线性前馈方式在这些“信息漩涡”之间传输。这些组件通过使用一系列存储记忆的遗传拨动开关电路和振荡电路来负责细菌细胞的决策。这些电路充当网络的中央计算机,其输出信号随后传播到网络的其余部分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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