Michael Smith Laboratories, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada.
Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada.
Genome Biol. 2020 Jun 15;21(1):140. doi: 10.1186/s13059-020-02050-y.
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.
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.
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.
I 型干扰素（IFN）反应是一种古老的途径，通过诱导数百种 IFN 刺激基因的转录，保护细胞免受病毒病原体的侵害。通过转录组学和生化方法，在不同物种和细胞类型中已经建立了 IFN 刺激基因的综合目录，但它们的抗病毒机制仍未完全阐明。在这里，我们应用定量蛋白质组学方法的组合来描述 IFN 信号对人类蛋白质组的影响，并应用蛋白质相关分析来绘制 IFN 诱导的人类蛋白质-蛋白质相互作用网络中的重排。
我们在 IFN 刺激和未刺激的细胞中鉴定出 >26000 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。差异网络分析揭示了抗病毒反应中细胞途径的广泛相互作用重排。我们确定了 IFN 依赖性蛋白质-蛋白质相互作用，介导转录和翻译水平的新调节机制，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的 IFN 依赖性变化，这些变化可缓冲 IFN 刺激基因的蛋白质合成。
我们的 IFN 相互作用组图谱提供了抗病毒反应中激活的复杂细胞网络的全局视图，将 IFN 刺激基因置于功能背景下，并作为理解这些网络在自身免疫或炎症性疾病中失调的框架。
