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耦合的相互抑制和相互激活基序作为细胞命运控制的工具。

Coupled Mutual Inhibition and Mutual Activation Motifs as Tools for Cell-Fate Control.

机构信息

Department of Biotechnology, Indian Institute of Technology Madras, Chennai, India.

Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, India.

出版信息

Cells Tissues Organs. 2024;213(4):283-296. doi: 10.1159/000529558. Epub 2023 Feb 9.

DOI:10.1159/000529558
PMID:36758523
Abstract

Multistability is central to biological systems. It plays a crucial role in adaptation, evolvability, and differentiation. The presence of positive feedback loops can enable multistability. The simplest of such feedback loops are (a) a mutual inhibition (MI) loop, (b) a mutual activation (MA) loop, and (c) self-activation. While it is established that all three motifs can give rise to bistability, the characteristic differences in the bistability exhibited by each of these motifs is relatively less understood. Here, we use dynamical simulations across a large ensemble of parameter sets and initial conditions to study the bistability characteristics of these motifs. Furthermore, we investigate the utility of these motifs for achieving coordinated expression through cyclic and parallel coupling amongst them. Our analysis revealed that MI-based architectures offer discrete and robust control over gene expression, multistability, and coordinated expression among multiple genes, as compared to MA-based architectures. We then devised a combination of MI and MA architectures to improve coordination and multistability. Such designs help enhance our understanding of the control structures involved in robust cell-fate decisions and provide a way to achieve controlled decision-making in synthetic systems.

摘要

多稳定性是生物系统的核心。它在适应、进化和分化中起着至关重要的作用。正反馈回路的存在可以实现多稳定性。最简单的反馈回路包括(a)相互抑制(MI)回路、(b)相互激活(MA)回路和(c)自我激活。虽然已经确定这三个基序都可以产生双稳性,但每个基序所表现出的双稳性的特征差异相对较少被理解。在这里,我们使用大量参数集和初始条件的动力学模拟来研究这些基序的双稳性特征。此外,我们还研究了通过它们之间的循环和并行耦合来实现协调表达的这些基序的用途。我们的分析表明,与基于 MA 的架构相比,基于 MI 的架构在基因表达、多稳定性和多个基因的协调表达方面提供了离散和稳健的控制。然后,我们设计了一种 MI 和 MA 架构的组合来提高协调和多稳定性。这种设计有助于我们深入了解稳健细胞命运决策中涉及的控制结构,并为在合成系统中实现受控决策提供了一种方法。

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