利用细菌基因调控网络中纤维对称性预测同步基因共表达模式
Predicting synchronized gene coexpression patterns from fibration symmetries in gene regulatory networks in bacteria
摘要：
背景资料：基因调控网络协调基因在生理状态下的表达，并确保细胞子系统中基因的同步表达，这对细胞的连贯功能至关重要。在这里，我们解决的问题，是否有可能预测基因同步，从网络结构单独。我们最近表明，同步基因表达可以预测从对称性的基因调控网络（GRN）和对称纤维化的概念描述。我们发现，对称纤维化根据其“输入树”的对称性将基因划分为称为纤维的组，输入树是网络中信号可以到达基因的路径集。在理想化的动态基因表达模型中，纤维中的所有基因都是完全同步的，而不太理想化的模型--基因之间的基因输入函数不同--预测对称性破缺和去对称化。结果如下：为了研究基因纤维的功能作用，并测试一些纤维诱导的共表达是否仍然存在，我们分析了大肠杆菌基因调控网络的基因纤维化。杆菌和枯草subtilis并将它们与表达数据进行比较。我们发现近似的基因共表达模式与理想化的基因表达动力学对称纤维化一致。这表明，网络结构本身提供了有用的信息，基因同步化，并建议纤维内的基因输入功能可能会进一步精简的进化压力，以实现基因的共表达。结论：因此，基因纤维化提供了一个良好的概念工具来描述可调的共表达诱导的网络拓扑结构和塑造的机制细节的基因表达。
英文摘要：
Background: Gene regulatory networks coordinate the expression of genes across physiological states and ensure a synchronized expression of genes in cellular subsystems, critical for the coherent functioning of cells. Here we address the questions whether it is possible to predict gene synchronization from network structure alone. We have recently shown that synchronized gene expression may be predicted from symmetries in the gene regulatory networks (GRN) and described by the concept of symmetry fibrations. We showed that symmetry fibrations partition the genes into groups called fibers based on the symmetries of their 'input trees', the set of paths in the network through which signals can reach a gene. In idealized dynamic gene expression models, all genes in a fiber are perfectly synchronized, while less idealized models - with gene input functions differencing between genes - predict symmetry breaking and desynchronization. Results: To study the functional role of gene fibers and to test whether some of the fiber-induced coexpression remains in reality, we analyze gene fibrations for the gene regulatory networks of E. coli and B. subtilis and confront them with expression data. We find approximate gene coexpression patterns consistent with symmetry fibrations with idealized gene expression dynamics. This shows that network structure alone provides useful information about gene synchronization, and suggest that gene input functions within fibers may be further streamlined by evolutionary pressures to realize a coexpression of genes. Conclusions: Thus, gene fibrations provides a sound conceptual tool to describe tunable coexpression induced by network topology and shaped by mechanistic details of gene expression.
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