Institute of Science and Technology Austria, Klosterneuburg, Austria.
The Robert H. Smith Institute of Plant Sciences and Genetics in Agriculture, Faculty of Agriculture, Hebrew University of Jerusalem, Rehovot, Israel.
PLoS Comput Biol. 2020 Feb 25;16(2):e1007642. doi: 10.1371/journal.pcbi.1007642. eCollection 2020 Feb.
Genes differ in the frequency at which they are expressed and in the form of regulation used to control their activity. In particular, positive or negative regulation can lead to activation of a gene in response to an external signal. Previous works proposed that the form of regulation of a gene correlates with its frequency of usage: positive regulation when the gene is frequently expressed and negative regulation when infrequently expressed. Such network design means that, in the absence of their regulators, the genes are found in their least required activity state, hence regulatory intervention is often necessary. Due to the multitude of genes and regulators, spurious binding and unbinding events, called "crosstalk", could occur. To determine how the form of regulation affects the global crosstalk in the network, we used a mathematical model that includes multiple regulators and multiple target genes. We found that crosstalk depends non-monotonically on the availability of regulators. Our analysis showed that excess use of regulation entailed by the formerly suggested network design caused high crosstalk levels in a large part of the parameter space. We therefore considered the opposite 'idle' design, where the default unregulated state of genes is their frequently required activity state. We found, that 'idle' design minimized the use of regulation and thus minimized crosstalk. In addition, we estimated global crosstalk of S. cerevisiae using transcription factors binding data. We demonstrated that even partial network data could suffice to estimate its global crosstalk, suggesting its applicability to additional organisms. We found that S. cerevisiae estimated crosstalk is lower than that of a random network, suggesting that natural selection reduces crosstalk. In summary, our study highlights a new type of protein production cost which is typically overlooked: that of regulatory interference caused by the presence of excess regulators in the cell. It demonstrates the importance of whole-network descriptions, which could show effects missed by single-gene models.
基因在表达频率和用于控制其活性的调节形式上存在差异。特别是，正或负调节可以导致基因在响应外部信号时被激活。以前的工作提出，基因的调节形式与其使用频率相关：在基因频繁表达时为正调节，在基因不频繁表达时为负调节。这种网络设计意味着，在没有其调节剂的情况下，基因处于其所需活性最低的状态，因此通常需要进行调节干预。由于基因和调节剂的数量众多，可能会发生称为“串扰”的虚假结合和解离事件。为了确定调节形式如何影响网络中的全局串扰，我们使用了一种包括多个调节剂和多个靶基因的数学模型。我们发现串扰与调节剂的可用性呈非单调关系。我们的分析表明，以前建议的网络设计中过度使用调节会导致在大部分参数空间中出现高串扰水平。因此，我们考虑了相反的“空闲”设计，其中基因的默认无调节状态是其经常需要的活性状态。我们发现，“空闲”设计最小化了调节的使用，从而最小化了串扰。此外，我们使用转录因子结合数据估计了 S. cerevisiae 的全局串扰。我们证明，即使是部分网络数据也足以估计其全局串扰，这表明它可适用于其他生物体。我们发现，S. cerevisiae 估计的串扰低于随机网络，这表明自然选择降低了串扰。总之，我们的研究强调了一种通常被忽视的新型蛋白质产生成本：细胞中存在过量调节剂引起的调节干扰成本。它展示了全网络描述的重要性，这种描述可以显示单个基因模型错过的效果。
