Center for Theoretical Biological Physics, Rice University, Houston, TX, 77005, USA.
Department of Physics and Astronomy, Rice University, Houston, TX, 77005, USA.
Nat Commun. 2024 Jul 31;15(1):6453. doi: 10.1038/s41467-024-50510-x.
Long and stable timescales are often observed in complex biochemical networks, such as in emergent oscillations. How these robust dynamics persist remains unclear, given the many stochastic reactions and shorter time scales demonstrated by underlying components. We propose a topological model that produces long oscillations around the network boundary, reducing the system dynamics to a lower-dimensional current in a robust manner. Using this to model KaiC, which regulates the circadian rhythm in cyanobacteria, we compare the coherence of oscillations to that in other KaiC models. Our topological model localizes currents on the system edge, with an efficient regime of simultaneously increased precision and decreased cost. Further, we introduce a new predictor of coherence from the analysis of spectral gaps, and show that our model saturates a global thermodynamic bound. Our work presents a new mechanism and parsimonious description for robust emergent oscillations in complex biological networks.
复杂的生化网络(如涌现的振荡)中经常观察到长而稳定的时间尺度。鉴于底层组件表现出许多随机反应和更短的时间尺度,这些稳健的动力学如何持续存在尚不清楚。我们提出了一种拓扑模型,该模型在网络边界周围产生长的振荡,以稳健的方式将系统动力学降低到低维电流。使用该模型对调节蓝藻生物钟的 KaiC 进行建模,我们将振荡的相干性与其他 KaiC 模型进行了比较。我们的拓扑模型将电流定位于系统边缘,同时具有提高精度和降低成本的有效模式。此外,我们从频谱间隙分析中引入了一个新的相干性预测指标,并表明我们的模型饱和了全局热力学边界。我们的工作为复杂生物网络中稳健涌现的振荡提供了一种新的机制和简约描述。