Department of Biochemistry, Université de Montréal, 2900 Edouard Montpetit Blvd, Montreal, QC, H3T 1J4, Canada.
The Biomedical Informatics R&D Center, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka, Fukuoka, 820-8502, Japan.
BMC Bioinformatics. 2019 Dec 27;20(1):734. doi: 10.1186/s12859-019-3315-2.
Cellular memory is a ubiquitous function of biological systems. By generating a sustained response to a transient inductive stimulus, often due to bistability, memory is central to the robust control of many important biological processes. However, our understanding of the origins of cellular memory remains incomplete. Stochastic fluctuations that are inherent to most biological systems have been shown to hamper memory function. Yet, how stochasticity changes the behavior of genetic circuits is generally not clear from a deterministic analysis of the network alone. Here, we apply deterministic rate equations, stochastic simulations, and theoretical analyses of Fokker-Planck equations to investigate how intrinsic noise affects the memory function in a mutual repression network.
We find that the addition of negative autoregulation improves the persistence of memory in a small gene regulatory network by reducing stochastic fluctuations. Our theoretical analyses reveal that this improved memory function stems from an increased stability of the steady states of the system. Moreover, we show how the tuning of critical network parameters can further enhance memory.
Our work illuminates the power of stochastic and theoretical approaches to understanding biological circuits, and the importance of considering stochasticity when designing synthetic circuits with memory function.
细胞记忆是生物系统的普遍功能。通过对瞬态诱导刺激产生持续的反应，通常是由于双稳态，记忆是许多重要生物过程的强大控制的核心。然而，我们对细胞记忆的起源的理解仍然不完整。大多数生物系统固有的随机波动会阻碍记忆功能。然而，从网络的确定性分析来看，随机波动如何改变遗传电路的行为通常并不清楚。在这里，我们应用确定性速率方程、随机模拟和福克-普朗克方程的理论分析来研究内在噪声如何影响相互抑制网络中的记忆功能。
我们发现，通过减少随机波动，负反馈的加入可以通过减少随机波动来提高小基因调控网络的记忆持久性。我们的理论分析表明，这种改进的记忆功能源于系统稳态稳定性的提高。此外，我们还展示了如何调整关键网络参数可以进一步增强记忆。
我们的工作阐明了随机和理论方法在理解生物电路方面的强大功能，以及在设计具有记忆功能的合成电路时考虑随机性的重要性。
