John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA.
Program in Biophysics, Harvard University, Boston, MA, 02115, USA.
Nat Commun. 2021 Jan 8;12(1):130. doi: 10.1038/s41467-020-20472-x.
Homeostasis of protein concentrations in cells is crucial for their proper functioning, requiring steady-state concentrations to be stable to fluctuations. Since gene expression is regulated by proteins such as transcription factors (TFs), the full set of proteins within the cell constitutes a large system of interacting components, which can become unstable. We explore factors affecting stability by coupling the dynamics of mRNAs and proteins in a growing cell. We find that mRNA degradation rate does not affect stability, contrary to previous claims. However, global structural features of the network can dramatically enhance stability. Importantly, a network resembling a bipartite graph with a lower fraction of interactions that target TFs has a higher chance of being stable. Scrambling the E. coli transcription network, we find that the biological network is significantly more stable than its randomized counterpart, suggesting that stability constraints may have shaped network structure during the course of evolution.
细胞内蛋白质浓度的稳态对于其正常功能至关重要,需要使稳态浓度稳定以应对波动。由于基因表达受转录因子(TFs)等蛋白质的调节,细胞内的全套蛋白质构成了一个相互作用的组件的大系统,该系统可能变得不稳定。我们通过在生长的细胞中耦合 mRNA 和蛋白质的动力学来探索影响稳定性的因素。我们发现,mRNA 降解率不会像之前声称的那样影响稳定性。然而,网络的全局结构特征可以显著增强稳定性。重要的是,具有较低 TF 靶向相互作用分数的类似于二部图的网络更有可能稳定。通过打乱大肠杆菌转录网络,我们发现生物网络比随机对应的网络显著更稳定,这表明稳定性约束可能在进化过程中塑造了网络结构。