Noncommutative Biology: Sequential Regulation of Complex Networks.
Noncommutative Biology: Sequential Regulation of Complex Networks.
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DOI：
10.1371/journal.pcbi.1005089
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发表时间：
2016-08
影响因子：
4.3
通讯作者：
Cai L
中科院分区：
文献类型：
--
作者：
Letsou W;Cai L
基因表达的单细胞变异性对于产生不同的细胞类型很重要，但目前尚不清楚细胞如何使用相同的调控分子来特异性控制类似的调控基因。虽然组合结合的转录因子在启动子已被提出作为细胞类型特异性基因表达的解决方案，我们发现，这样的模型导致大量的信息瓶颈。我们试图理解采用顺序逻辑的后果，其中因素的时间顺序决定了最终结果。我们发现，使用非交换控制，可以独立地控制目标，否则将使用组合逻辑同时激活。因此，顺序逻辑克服了复杂网络中固有的信息瓶颈。我们推导出两个非交换模型的调节，磷酸化/神经网络和染色体折叠的动机，分别的比例律，并表明他们的规模超指数的监管机构的数量。我们还表明，控制的特异性对调节器的丢失是鲁棒的。最后，我们将这些理论结果与真实的生物网络联系起来，这些网络在滥交的背景下表现出特异性。这些结果表明，要达到预期的结果，往往需要迂回的步骤。DNA是生命的蓝图。然而，细胞遵循这些指令的顺序使其能够产生数千种不同的命运。如何从潜在的基因调控网络中提取这些信息尚不清楚，特别是考虑到生物网络是高度互连的，并且信号通路的数量相对较少（约5-10）。增加有限的一组监管机构的信息能力的传统方法是将它们结合起来使用。令人惊讶的是，组合逻辑并没有增加目标配置或细胞命运的多样性，而是导致信息瓶颈。另一种方法称为时序逻辑，它使用一小部分调节器的非交换序列来驱动网络达到大量新的配置。如果某些目标首先受到保护，那么即使是混杂的调节剂也可以激活谱系特异性目标的特定子集。在本文中，我们将展示如何顺序逻辑优于组合逻辑，并认为，非交换序列的基础上的一些情况下的生物调控，例如，如何少量的信号通路产生大量的多样性的细胞类型的发展。除了解释生物网络，时序逻辑可能是合成和单细胞生物学中的一般实验设计策略。
Single-cell variability in gene expression is important for generating distinct cell types, but it is unclear how cells use the same set of regulatory molecules to specifically control similarly regulated genes. While combinatorial binding of transcription factors at promoters has been proposed as a solution for cell-type specific gene expression, we found that such models resulted in substantial information bottlenecks. We sought to understand the consequences of adopting sequential logic wherein the time-ordering of factors informs the final outcome. We showed that with noncommutative control, it is possible to independently control targets that would otherwise be activated simultaneously using combinatorial logic. Consequently, sequential logic overcomes the information bottleneck inherent in complex networks. We derived scaling laws for two noncommutative models of regulation, motivated by phosphorylation/neural networks and chromosome folding, respectively, and showed that they scale super-exponentially in the number of regulators. We also showed that specificity in control is robust to the loss of a regulator. Lastly, we connected these theoretical results to real biological networks that demonstrate specificity in the context of promiscuity. These results show that achieving a desired outcome often necessitates roundabout steps. DNA is the blueprint of life. Yet the order in which a cell follows these instructions makes it capable of generating thousands of different fates. How this information is extracted from underlying gene regulatory networks is unclear, especially given that biological networks are highly interconnected, and that the number of signaling pathways is relatively small (approximately 5–10). The conventional approach for increasing the information capacity of a limited set of regulators is to use them in combination. Surprisingly, combinatorial logic does not increase the diversity of target configurations or cell fates, but instead causes information bottlenecks. A different approach, called sequential logic, uses noncommutative sequences of a small set of regulators to drive networks to a large number of novel configurations. If certain targets are first protected, then even promiscuous regulators can activate specific subsets of lineage-specific targets. In this paper we show how sequential logic outperforms combinatorial logic, and argue that noncommutative sequences underlie a number of cases of biological regulation, e.g. how a small number of signaling pathways generates a large diversity of cell types in development. In addition to explaining biological networks, sequential logic may be a general experimental design strategy in synthetic and single-cell biology.