Stratus not altocumulus: a new view of the yeast protein interaction network.
Stratus not altocumulus: a new view of the yeast protein interaction network.
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DOI：
10.1371/journal.pbio.0040317
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发表时间：
2006-10
期刊：
影响因子：
9.8
通讯作者：
Tyers M
中科院分区：
文献类型：
--
作者：
Batada NN;Reguly T;Breitkreutz A;Boucher L;Breitkreutz BJ;Hurst LD;Tyers M
系统生物学方法能够揭示基因型和表型之间的中间组织层次，这些层次往往是诸如多基因效应和蛋白质可有可无性等生物学现象的基础。一个重要的概念是模块，它大致被定义为执行特定细胞任务的一组蛋白质。基于对芽殖酵母酿酒酵母中有限的相互作用数据集的计算分析，有人提出全球蛋白质相互作用网络是分离的，即高度连接的蛋白质（称为枢纽蛋白）往往彼此不相连。此外，有人提出枢纽蛋白可分为两类：“聚会”枢纽蛋白与其伙伴共表达且共定位，而“约会”枢纽蛋白则与表达不一致且定位多样的伙伴相互作用，从而将全球网络的不同部分连接起来。这种结构可以与高积云相比较，即由细丝稀疏连接的棉球状结构。然而，这种组织形式可能反映了一个小的和/或有偏差的相互作用样本集。在一个经过多重验证的高可信度（HC）相互作用网络中，该网络由所有现存的酿酒酵母相互作用数据组装而成，包括最近可获得的全蛋白质组相互作用数据和大量可靠的文献衍生相互作用，我们发现枢纽 - 枢纽相互作用并没有被抑制。事实上，一个枢纽蛋白与其他枢纽蛋白的相互作用数量是预测该枢纽蛋白是否为必需蛋白的一个良好指标。我们发现“约会”枢纽蛋白对于网络对节点缺失的耐受性既不是必需的，与其他枢纽蛋白相比也没有独特的生物学属性。例如，“约会”枢纽蛋白和“聚会”枢纽蛋白的进化速率没有差异。我们的分析表明，全球蛋白质相互作用网络的组织是高度相互连接的，因此是相互依存的，更像是层云的连续密集聚集，而不是高积云的分离结构。如果网络以层云形式配置，蛋白质之间的串扰可能是噪声的一个主要来源。反过来，对连接最紧密的蛋白质的活性控制可能是至关重要的。事实上，我们发现连接最紧密的蛋白质的稳态水平波动是最小的。
对经过多重验证的蛋白质相互作用数据的分析揭示了比先前可获得的数据中所见的更分离的结构具有更高相互连接性的网络。为了帮助可视化这一点，作者将连续的层云和高积云进行了比较。
Systems biology approaches can reveal intermediary levels of organization between genotype and phenotype that often underlie biological phenomena such as polygenic effects and protein dispensability. An important conceptualization is the module, which is loosely defined as a cohort of proteins that perform a dedicated cellular task. Based on a computational analysis of limited interaction datasets in the budding yeast Saccharomyces cerevisiae, it has been suggested that the global protein interaction network is segregated such that highly connected proteins, called hubs, tend not to link to each other. Moreover, it has been suggested that hubs fall into two distinct classes: “party” hubs are co-expressed and co-localized with their partners, whereas “date” hubs interact with incoherently expressed and diversely localized partners, and thereby cohere disparate parts of the global network. This structure may be compared with altocumulus clouds, i.e., cotton ball–like structures sparsely connected by thin wisps. However, this organization might reflect a small and/or biased sample set of interactions. In a multi-validated high-confidence (HC) interaction network, assembled from all extant S. cerevisiae interaction data, including recently available proteome-wide interaction data and a large set of reliable literature-derived interactions, we find that hub–hub interactions are not suppressed. In fact, the number of interactions a hub has with other hubs is a good predictor of whether a hub protein is essential or not. We find that date hubs are neither required for network tolerance to node deletion, nor do date hubs have distinct biological attributes compared to other hubs. Date and party hubs do not, for example, evolve at different rates. Our analysis suggests that the organization of global protein interaction network is highly interconnected and hence interdependent, more like the continuous dense aggregations of stratus clouds than the segregated configuration of altocumulus clouds. If the network is configured in a stratus format, cross-talk between proteins is potentially a major source of noise. In turn, control of the activity of the most highly connected proteins may be vital. Indeed, we find that a fluctuation in steady-state levels of the most connected proteins is minimized. Analysis of multi-validated protein interaction data reveals networks with greater interconnectivity than the more segregated structures seen in previously available data. To help visualize this, the authors draw comparisons between continuous stratus clouds and altocumulus clouds.
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影响因子：
4.3
作者：
Batada NN;Hurst LD;Tyers M
通讯作者：
Tyers M
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7
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64.8
作者：
Gavin, AC;Aloy, P;Superti-Furga, G
通讯作者：
Superti-Furga, G