驱动细胞命运转变的相互关联的反馈回路的工作原理。

IF 3.5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY NPJ Systems Biology and Applications Pub Date : 2025-01-02 DOI:10.1038/s41540-024-00483-w
Mubasher Rashid, Abhiram Hegade
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引用次数: 0

摘要

相互关联的反馈回路在生物机制中普遍存在,包括癌症中由表观遗传机制激活的细胞命运转变。然而,这些网络的运作原理在很大程度上仍未被探索。在这里,我们确定了涉及细胞谱系决策的许多相互关联的反馈回路,我们发现这是低维和高维状态空间的标志。我们证明了具有较高中心性节点的网络具有有限的状态空间,而具有较低中心性节点的网络具有较高的状态空间。具有相同节点数或环路数的拓扑结构不同的网络具有不同的稳态分布,突出了网络结构对紧急动力学的重要影响。此外,无论拓扑结构如何,具有自动调节节点的网络表现出多个稳定状态,从而将网络动态从绝对拓扑控制中“解放”出来。这些发现揭示了与命运决策有关的多稳定网络的设计原则,并对工程或理解多命运决策电路具有重要意义。
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Operating principles of interconnected feedback loops driving cell fate transitions.

Interconnected feedback loops are prevalent across biological mechanisms, including cell fate transitions enabled by epigenetic mechanisms in carcinomas. However, the operating principles of these networks remain largely unexplored. Here, we identify numerous interconnected feedback loops implicated in cell lineage decisions, which we discover to be the hallmarks of lower- and higher-dimensional state space. We demonstrate that networks having higher centrality nodes have restricted state space while those with lower centrality nodes have higher dimensional state space. The topologically distinct networks with identical node or loop counts have different steady-state distributions, highlighting the crucial influence of network structure on emergent dynamics. Further, regardless of topology, networks with autoregulated nodes exhibit multiple steady states, thereby "liberating" network dynamics from absolute topological control. These findings unravel the design principles of multistable networks implicated in fate decisions and can have crucial implications in engineering or comprehending multi-fate decision circuits.

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来源期刊
NPJ Systems Biology and Applications
NPJ Systems Biology and Applications Mathematics-Applied Mathematics
CiteScore
5.80
自引率
0.00%
发文量
46
审稿时长
8 weeks
期刊介绍: npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.
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