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解析调控干扰素 α 信号转导敏化的分子机制。

Disentangling molecular mechanisms regulating sensitization of interferon alpha signal transduction.

机构信息

Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), Heidelberg, Germany.

Faculty of Biosciences, Heidelberg University, Heidelberg, Germany.

出版信息

Mol Syst Biol. 2020 Jul;16(7):e8955. doi: 10.15252/msb.20198955.

Abstract

Tightly interlinked feedback regulators control the dynamics of intracellular responses elicited by the activation of signal transduction pathways. Interferon alpha (IFNα) orchestrates antiviral responses in hepatocytes, yet mechanisms that define pathway sensitization in response to prestimulation with different IFNα doses remained unresolved. We establish, based on quantitative measurements obtained for the hepatoma cell line Huh7.5, an ordinary differential equation model for IFNα signal transduction that comprises the feedback regulators STAT1, STAT2, IRF9, USP18, SOCS1, SOCS3, and IRF2. The model-based analysis shows that, mediated by the signaling proteins STAT2 and IRF9, prestimulation with a low IFNα dose hypersensitizes the pathway. In contrast, prestimulation with a high dose of IFNα leads to a dose-dependent desensitization, mediated by the negative regulators USP18 and SOCS1 that act at the receptor. The analysis of basal protein abundance in primary human hepatocytes reveals high heterogeneity in patient-specific amounts of STAT1, STAT2, IRF9, and USP18. The mathematical modeling approach shows that the basal amount of USP18 determines patient-specific pathway desensitization, while the abundance of STAT2 predicts the patient-specific IFNα signal response.

摘要

紧密相互关联的反馈调节剂控制着信号转导途径激活所引发的细胞内反应的动力学。干扰素 α (IFNα) 在肝细胞中协调抗病毒反应,但对于不同 IFNα 剂量预刺激时定义途径敏化的机制仍未解决。我们基于对肝癌细胞系 Huh7.5 的定量测量,建立了一个 IFNα 信号转导的常微分方程模型,其中包括反馈调节剂 STAT1、STAT2、IRF9、USP18、SOCS1、SOCS3 和 IRF2。基于模型的分析表明,低剂量 IFNα 的预刺激通过信号蛋白 STAT2 和 IRF9 使途径超敏化。相比之下,高剂量 IFNα 的预刺激导致由负调节剂 USP18 和 SOCS1 介导的剂量依赖性脱敏,它们在受体处起作用。对原代人肝细胞中基础蛋白丰度的分析显示,STAT1、STAT2、IRF9 和 USP18 的患者特异性含量存在高度异质性。数学建模方法表明,USP18 的基础含量决定了患者特异性途径脱敏,而 STAT2 的丰度则预测了患者特异性 IFNα 信号反应。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/48d8/7373899/e3d0a2e7fe1e/MSB-16-e8955-g002.jpg

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