Cooperative adaptive responses in gene regulatory networks with many degrees of freedom.
Cooperative adaptive responses in gene regulatory networks with many degrees of freedom.
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DOI：
10.1371/journal.pcbi.1003001
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发表时间：
2013-04
影响因子：
4.3
通讯作者：
Kaneko K
中科院分区：
文献类型：
--
作者：
Inoue M;Kaneko K
细胞通常通过首先表现出立即反应，然后逐渐恢复到原始状态以实现稳态来适应环境变化。尽管由少数基因组成的简单网络基序已被证明表现出这种适应性动力学，但它们并不反映真实的细胞的复杂性，在这种复杂性中，大量基因的表达激活或抑制其他基因，从而允许适应性行为。在这里，我们研究了包含许多基因的基因调控网络的反应，这些基因经历了数值进化，由于只有一个目标基因的适应性反应而达到了高适应度;这个单一的目标基因对外部输入的变化做出反应，后来又恢复到基础水平。尽管设定了单一目标，但大多数基因在进化后都表现出适应性反应。这种适应性动态并不是由于少数基因中的共同基序;即使没有这样的基序，几乎所有的基因都表现出适应性，尽管有时是部分适应性，在这个意义上，表达水平并不总是回到原始水平。这些基因分为两组：第一组基因表现出最初的表达增加，然后恢复到基础水平，而第二组基因表现出相反的表达变化。根据这个模型，第一组中的基因从第一组中的其他基因接收正输入，但从第二组中的基因接收负输入，反之亦然。因此，两组基因的适应动力学得到了巩固。如果涉及的基因数量大于十个数量级，这种合作适应行为通常会被观察到。这些结果的集体反应的基因表达网络的微阵列测量的酵母酿酒酵母和具有许多组件的系统的生物稳态的意义的影响。稳态是生物系统的固有特性，其具有适应的一般趋势，即，在环境变化后恢复原状。在细胞中，这种适应是由蛋白质表达的变化介导的。最初，细胞通过改变基因/蛋白质表达来响应环境变化;随后，大多数基因的表达恢复到基础水平，尽管不是完全恢复，正如最近对酵母的实验分析所示。虽然通过网络基序（仅由几个基因组成）的简单适应机制已被很好地理解，但涉及许多相互激活或抑制的基因的调节网络如何产生适应行为尚不清楚。在这里，通过数值进化的基因调控网络，我们得到了一类基因，其表达动态显示适应几乎所有的基因，从中我们揭示了这种适应性动态的一般逻辑与许多自由度，这是不可还原的基序与几个基因。这种适应是合作的，即，一个基因的适应性相互依赖于其他基因的适应性表达。此外，这种集体行为对噪声和突变具有鲁棒性。本研究揭示了集体基因表达动态允许生物稳态的性质。
Cells generally adapt to environmental changes by first exhibiting an immediate response and then gradually returning to their original state to achieve homeostasis. Although simple network motifs consisting of a few genes have been shown to exhibit such adaptive dynamics, they do not reflect the complexity of real cells, where the expression of a large number of genes activates or represses other genes, permitting adaptive behaviors. Here, we investigated the responses of gene regulatory networks containing many genes that have undergone numerical evolution to achieve high fitness due to the adaptive response of only a single target gene; this single target gene responds to changes in external inputs and later returns to basal levels. Despite setting a single target, most genes showed adaptive responses after evolution. Such adaptive dynamics were not due to common motifs within a few genes; even without such motifs, almost all genes showed adaptation, albeit sometimes partial adaptation, in the sense that expression levels did not always return to original levels. The genes split into two groups: genes in the first group exhibited an initial increase in expression and then returned to basal levels, while genes in the second group exhibited the opposite changes in expression. From this model, genes in the first group received positive input from other genes within the first group, but negative input from genes in the second group, and vice versa. Thus, the adaptation dynamics of genes from both groups were consolidated. This cooperative adaptive behavior was commonly observed if the number of genes involved was larger than the order of ten. These results have implications in the collective responses of gene expression networks in microarray measurements of yeast Saccharomyces cerevisiae and the significance to the biological homeostasis of systems with many components. Homeostasis is an inherent property of biological systems, which have a general tendency to adapt, i.e., to recover their original state following environmental changes. In cells, this adaptation is mediated by changes in protein expression. Initially, cells respond to environmental changes by altered gene/protein expression; subsequently, the expression of most genes returns to basal levels, albeit not completely, as shown by recent experimental analyses of yeast. Although simple mechanisms for adaptation through network motifs, composed of just a few genes, are well understood, how regulatory networks involving many genes that activate or repress each other can generate adaptive behaviors is unclear. Here, by numerically evolving gene regulatory networks, we obtained a class of genes whose expression dynamics showed adaptation over almost all genes, from which we revealed the general logic underlying such adaptive dynamics with many degrees of freedom, which was not reducible to motifs with a few genes. This adaptation was cooperative, i.e., adaptation of one gene mutually relied upon others' adaptive expressions. Moreover, this collective behavior was robust to noise and mutations. The present study sheds a light on the nature of collective gene expression dynamics allowing for biological homeostasis.
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