Stochastic delay accelerates signaling in gene networks.
Stochastic delay accelerates signaling in gene networks.
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DOI：
10.1371/journal.pcbi.1002264
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发表时间：
2011-11
影响因子：
4.3
通讯作者：
Bennett MR
中科院分区：
文献类型：
--
作者：
Josić K;López JM;Ott W;Shiau L;Bennett MR
从DNA中产生蛋白质是一个由转录、翻译和蛋白质折叠等众多反应组成的动态过程。这些反应中的每一个都进一步由成百上千个子步骤组成，这些步骤必须在蛋白质完全成熟之前完成。因此，产生一种单一蛋白质所需的时间取决于反应链中步骤的数量和每一步的性质。在基因调控网络模型中解释这些反应的一种方法是纳入动态延迟。然而，产生蛋白质所必需的反应的随机性导致等待时间是随机分布的。在这里，我们使用排队论来检验这种分布式延迟对通过转录调控的遗传网络传播信息的影响。在一个易于分析的模型中，我们发现增加蛋白质生产延迟的随机性可以提高转录网络中的信号速度。这一效应在随机模拟中得到了证实，并在几个常见的转录基序中展示了它的影响。特别地，我们证明了在前馈环路中，信令时间和幅度受到分布式时延的显著影响。此外，先前已经证明，延迟会导致负反馈电路中的稳定振荡。结果表明，随着时滞变化的增加，振荡的周期和幅度单调减小。基因调控网络的延迟通常是由于从DNA产生全功能蛋白质所需的大量连续反应造成的。虽然蛋白质产生和成熟背后的分子机制是已知的，但由此产生的延迟在多大程度上影响转录网络中的信号仍是未知的。与以前研究基因网络中固定延迟的后果不同，这里我们调查延迟时间的可变性如何影响所产生的动力学。“转录延迟”的确切分布尚不清楚，很可能在很大程度上取决于内在和外在因素。然而，我们能够推断分布延迟对转录信号的特定影响，这些影响独立于潜在的分布。我们发现，编码转录因子的基因向其下游靶标发出信号所需的时间随着延迟可变性的增加而减少。我们利用排队论推导出一个描述这一结果的简单关系，并用随机模拟来证实它。还讨论了几个常见转录基序的分布延迟的后果。
The creation of protein from DNA is a dynamic process consisting of numerous reactions, such as transcription, translation and protein folding. Each of these reactions is further comprised of hundreds or thousands of sub-steps that must be completed before a protein is fully mature. Consequently, the time it takes to create a single protein depends on the number of steps in the reaction chain and the nature of each step. One way to account for these reactions in models of gene regulatory networks is to incorporate dynamical delay. However, the stochastic nature of the reactions necessary to produce protein leads to a waiting time that is randomly distributed. Here, we use queueing theory to examine the effects of such distributed delay on the propagation of information through transcriptionally regulated genetic networks. In an analytically tractable model we find that increasing the randomness in protein production delay can increase signaling speed in transcriptional networks. The effect is confirmed in stochastic simulations, and we demonstrate its impact in several common transcriptional motifs. In particular, we show that in feedforward loops signaling time and magnitude are significantly affected by distributed delay. In addition, delay has previously been shown to cause stable oscillations in circuits with negative feedback. We show that the period and the amplitude of the oscillations monotonically decrease as the variability of the delay time increases. Delay in gene regulatory networks often arises from the numerous sequential reactions necessary to create fully functional protein from DNA. While the molecular mechanisms behind protein production and maturation are known, it is still unknown to what extent the resulting delay affects signaling in transcriptional networks. In contrast to previous studies that have examined the consequences of fixed delay in gene networks, here we investigate how the variability of the delay time influences the resulting dynamics. The exact distribution of “transcriptional delay” is still unknown, and most likely greatly depends on both intrinsic and extrinsic factors. Nevertheless, we are able to deduce specific effects of distributed delay on transcriptional signaling that are independent of the underlying distribution. We find that the time it takes for a gene encoding a transcription factor to signal its downstream target decreases as the delay variability increases. We use queueing theory to derive a simple relationship describing this result, and use stochastic simulations to confirm it. The consequences of distributed delay for several common transcriptional motifs are also discussed.
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DOI：
10.1126/science.1202142
发表时间：
2011-04-22
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Larson DR;Zenklusen D;Wu B;Chao JA;Singer RH
通讯作者：
Singer RH
影响因子：
4.4
作者：
Lan, Yueheng;Elston, Timothy C.;Papoian, Garegin A.
通讯作者：
Papoian, Garegin A.
影响因子：
2
作者：
Bel, Golan;Munsky, Brian;Nemenman, Ilya
通讯作者：
Nemenman, Ilya
DOI：
10.1073/pnas.0408507102
发表时间：
2005-03-08
影响因子：
11.1
作者：
Hooshangi, S;Thiberge, S;Weiss, R
通讯作者：
Weiss, R
影响因子：
1.9
作者：
MAHAFFY, JM;PAO, CV
通讯作者：
PAO, CV