Multistability is central to biological systems as 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 loop (MI), b) a mutual activation loop (MA), and c) self-activation, all three of them known to give rise to bistability. However, the characteristic differences in the bistability exhibited by these motifs are 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 improve our understanding of the control structures involved in robust cell-fate decisions and provide a way to achieve controlled decision-making in synthetic systems.


中文翻译：

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耦合相互抑制和相互激活基序作为细胞命运控制的工具

多重稳定性是生物系统的核心，因为它在适应、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。此类反馈回路中最简单的是 a) 相互抑制回路 (MI)、b) 相互激活回路 (MA) 和 c) 自激活，已知这三种回路都会产生双稳态。然而，这些图案所表现出的双稳态特征差异相对较少被理解。在这里，我们使用跨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态特性。此外，我们研究了这些基序的效用，以通过它们之间的循环和平行耦合实现协调表达。我们的分析表明，与基于 MA 的架构相比，基于 MI 的架构对基因表达、多稳定性和多个基因之间的协调表达提供了离散和稳健的控制。然后，我们设计了 MI 和 MA 架构的组合，以提高协调性和多稳定性。这样的设计有助于提高我们对稳健细胞命运决策中涉及的控制结构的理解，并提供一种在合成系统中实现受控决策的方法。