Wiring Between Close Nodes in Molecular Networks Evolves More Quickly Than Between Distant Nodes.

IF 11 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Alejandro Gil-Gomez, Joshua S Rest
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Abstract

As species diverge, a wide range of evolutionary processes lead to changes in protein-protein interaction (PPI) networks and metabolic networks. The rate at which molecular networks evolve is an important question in evolutionary biology. Previous empirical work has focused on interactomes from model organisms to calculate rewiring rates, but this is limited by the relatively small number of species and sparse nature of network data across species. We present a proxy for variation in network topology: variation in drug-drug interactions (DDIs), obtained by studying drug combinations (DCs) across taxa. Here, we propose the rate at which DDIs change across species as an estimate of the rate at which the underlying molecular network changes as species diverge. We computed the evolutionary rates of DDIs using previously published data from a high-throughput study in gram-negative bacteria. Using phylogenetic comparative methods, we found that DDIs diverge rapidly over short evolutionary time periods, but that divergence saturates over longer time periods. In parallel, we mapped drugs with known targets in PPI and cofunctional networks. We found that the targets of synergistic DDIs are closer in these networks than other types of DCs and that synergistic interactions have a higher evolutionary rate, meaning that nodes that are closer evolve at a faster rate. Future studies of network evolution may use DC data to gain larger-scale perspectives on the details of network evolution within and between species.

分子网络中近距离节点之间的连接比远距离节点之间的连接发展得更快。
随着物种的分化,各种进化过程导致蛋白质-蛋白质相互作用网络和代谢网络发生变化。分子网络的进化速度是进化生物学的一个重要问题。以前的实证工作主要通过模式生物的相互作用组来计算重新布线的速度,但这受到物种数量相对较少和跨物种网络数据稀少的限制。我们提出了一种网络拓扑结构变异的替代方法:通过研究不同类群的药物组合(DCs)获得的药物相互作用(DDIs)变异。在这里,我们提出用不同物种间 DDIs 的变化率来估算物种分化过程中底层分子网络的变化率。我们利用之前发表的革兰氏阴性细菌高通量研究数据计算了DDIs的进化速率。利用系统发生学比较方法,我们发现 DDIs 在短进化时间段内迅速分化,但在较长的时间段内分化趋于饱和。与此同时,我们绘制了蛋白质-蛋白质相互作用和协同功能网络中已知靶点的药物图谱。我们发现,在这些网络中,协同 DDI 的靶点比其他类型的 DC 更接近,而且协同相互作用的进化速度更高,这意味着距离更近的节点进化速度更快。未来的网络进化研究可能会利用DC数据从更大规模的角度来了解物种内部和物种之间的网络进化细节。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Molecular biology and evolution
Molecular biology and evolution 生物-进化生物学
CiteScore
19.70
自引率
3.70%
发文量
257
审稿时长
1 months
期刊介绍: Molecular Biology and Evolution Journal Overview: Publishes research at the interface of molecular (including genomics) and evolutionary biology Considers manuscripts containing patterns, processes, and predictions at all levels of organization: population, taxonomic, functional, and phenotypic Interested in fundamental discoveries, new and improved methods, resources, technologies, and theories advancing evolutionary research Publishes balanced reviews of recent developments in genome evolution and forward-looking perspectives suggesting future directions in molecular evolution applications.
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