Evolution and emergence: higher order information structure in protein interactomes across the tree of life.
Evolution and emergence: higher order information structure in protein interactomes across the tree of life.
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进化和出现：生命树中蛋白质相互作用组的高阶信息结构。
DOI：
10.1093/intbio/zyab020
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
M. Levin
中科院分区：
文献类型：
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作者：
Brennan Klein;Erik P. Hoel;A. Swain;Ross Griebenow;M. Levin
众所周知，生物系统的内部运作很难理解。由于进化系统中噪声和简并性的普遍存在，在许多情况下，从基因调控网络到蛋白质-蛋白质相互作用组网络的一切工作都仍然是黑匣子。这种黑箱性质的一个后果是，不清楚在什么尺度上分析生物系统才能最好地理解它们的功能。我们分析了1800多个物种的蛋白质相互作用组，共包含8 782 166个蛋白质-蛋白质相互作用，在不同的尺度。我们表明，出现了更高阶的“宏观尺度”在这些interactomes和这些生物宏观尺度与较低的噪音和简并性，因此较低的不确定性。此外，与不参与宏观尺度的节点相比，构成宏观尺度的相互作用组中的节点更具弹性。这些影响在真核生物的相互作用组中更为明显，与原核生物相比;即使在敏感性测试后，这些结果仍然存在，在敏感性测试中，我们重新计算了网络模拟下的紧急宏观尺度，在网络模拟中，我们向相互作用组添加了不同的边缘权重。这表明了宏观尺度上合理的进化适应：生物网络进化出信息丰富的宏观尺度，以获得较低尺度上的不确定性以增强其弹性，以及较高尺度上的“确定性”以提高其信息传输有效性的好处。我们的工作解释了理解生物网络工作的一些困难，因为它们通常在隐藏的更高尺度上提供最多信息，并演示了使这些信息更高尺度显式的工具。
The internal workings of biological systems are notoriously difficult to understand. Due to the prevalence of noise and degeneracy in evolved systems, in many cases the workings of everything from gene regulatory networks to protein-protein interactome networks remain black boxes. One consequence of this black-box nature is that it is unclear at which scale to analyze biological systems to best understand their function. We analyzed the protein interactomes of over 1800 species, containing in total 8 782 166 protein-protein interactions, at different scales. We show the emergence of higher order 'macroscales' in these interactomes and that these biological macroscales are associated with lower noise and degeneracy and therefore lower uncertainty. Moreover, the nodes in the interactomes that make up the macroscale are more resilient compared with nodes that do not participate in the macroscale. These effects are more pronounced in interactomes of eukaryota, as compared with prokaryota; these results hold even after sensitivity tests where we recalculate the emergent macroscales under network simulations where we add different edge weights to the interactomes. This points to plausible evolutionary adaptation for macroscales: biological networks evolve informative macroscales to gain benefits of both being uncertain at lower scales to boost their resilience, and also being 'certain' at higher scales to increase their effectiveness at information transmission. Our work explains some of the difficulty in understanding the workings of biological networks, since they are often most informative at a hidden higher scale, and demonstrates the tools to make these informative higher scales explicit.
DOI：
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发表时间：
2019
期刊：
--
影响因子：
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作者：
M. Zitnik;R. Sosič;M. Feldman;J. Leskovec
通讯作者：
M. Zitnik;R. Sosič;M. Feldman;J. Leskovec