Background The type I interferon (IFN) response is an ancient pathway that protects cells against viral pathogens by inducing the transcription of hundreds of IFN-stimulated genes. Comprehensive catalogs of IFN-stimulated genes have been established across species and cell types by transcriptomic and biochemical approaches, but their antiviral mechanisms remain incompletely characterized. Here, we apply a combination of quantitative proteomic approaches to describe the effects of IFN signaling on the human proteome, and apply protein correlation profiling to map IFN-induced rearrangements in the human protein-protein interaction network. Results We identify > 26,000 protein interactions in IFN-stimulated and unstimulated cells, many of which involve proteins associated with human disease and are observed exclusively within the IFN-stimulated network. Differential network analysis reveals interaction rewiring across a surprisingly broad spectrum of cellular pathways in the antiviral response. We identify IFN-dependent protein-protein interactions mediating novel regulatory mechanisms at the transcriptional and translational levels, with one such interaction modulating the transcriptional activity of STAT1. Moreover, we reveal IFN-dependent changes in ribosomal composition that act to buffer IFN-stimulated gene protein synthesis. Conclusions Our map of the IFN interactome provides a global view of the complex cellular networks activated during the antiviral response, placing IFN-stimulated genes in a functional context, and serves as a framework to understand how these networks are dysregulated in autoimmune or inflammatory disease.

中文翻译：

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通过干扰素信号传导对人类相互作用组进行动态重新布线


背景 I 型干扰素 (IFN) 反应是一种古老的途径，通过诱导数百个 IFN 刺激基因的转录来保护细胞免受病毒病原体的侵害。已经通过转录组学和生化方法建立了跨物种和细胞类型的 IFN 刺激基因的综合目录，但其抗病毒机制仍未完全表征。在这里，我们应用定量蛋白质组学方法的组合来描述 IFN 信号传导对人类蛋白质组的影响，并应用蛋白质相关性分析来绘制人类蛋白质-蛋白质相互作用网络中 IFN 诱导的重排。结果我们在 IFN 刺激和未刺激的细胞中鉴定出超过 26,000 个蛋白质相互作用，其中许多涉及与人类疾病相关的蛋白质，并且仅在 IFN 刺激的网络中观察到。微分网络分析揭示了抗病毒反应中令人惊讶的广泛细胞途径之间的相互作用重新布线。我们确定了 IFN 依赖性蛋白质-蛋白质相互作用在转录和翻译水平上介导新的调节机制，其中一种相互作用调节 STAT1 的转录活性。此外，我们揭示了核糖体组成中干扰素依赖性的变化，其作用是缓冲干扰素刺激的基因蛋白质合成。结论 我们的 IFN 相互作用图谱提供了抗病毒反应期间激活的复杂细胞网络的全局视图，将 IFN 刺激的基因置于功能背景中，并作为了解这些网络在自身免疫或炎症性疾病中如何失调的框架。