DNA-PK and ATM drive phosphorylation signatures that antagonistically regulate cytokine responses to herpesvirus infection or DNA damage

IF 9 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Joshua L. Justice, Tavis J. Reed, Brett Phelan, Todd M. Greco, Josiah E. Hutton, Ileana M. Cristea
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引用次数: 0

Abstract

The DNA-dependent protein kinase, DNA-PK, is an essential regulator of DNA damage repair. DNA-PK-driven phosphorylation events and the activated DNA damage response (DDR) pathways are also components of antiviral intrinsic and innate immune responses. Yet, it is not clear whether and how the DNA-PK response differs between these two forms of nucleic acid stress—DNA damage and DNA virus infection. Here, we define DNA-PK substrates and the signature cellular phosphoproteome response to DNA damage or infection with the nuclear-replicating DNA herpesvirus, HSV-1. We establish that DNA-PK negatively regulates the ataxia-telangiectasia-mutated (ATM) DDR kinase during viral infection. In turn, ATM blocks the binding of DNA-PK and the nuclear DNA sensor IFI16 to viral DNA, thereby inhibiting cytokine responses. However, following DNA damage, DNA-PK enhances ATM activity, which is required for IFN-β expression. These findings demonstrate that the DDR autoregulates cytokine expression through the opposing modulation of DDR kinases.
DNA-PK 和 ATM 驱动的磷酸化特征可拮抗地调节细胞因子对疱疹病毒感染或 DNA 损伤的反应
DNA 依赖性蛋白激酶(DNA-PK)是 DNA 损伤修复的重要调节因子。DNA-PK 驱动的磷酸化事件和激活的 DNA 损伤应答(DDR)途径也是抗病毒内在和先天免疫应答的组成部分。然而,DNA-PK 反应在这两种核酸应激形式--DNA 损伤和 DNA 病毒感染之间是否存在差异以及如何差异尚不清楚。在这里,我们定义了DNA-PK底物以及细胞对DNA损伤或感染核复制DNA疱疹病毒HSV-1的标志性磷酸蛋白组反应。我们发现,在病毒感染期间,DNA-PK 负向调节共济失调-特朗吉赛突变(ATM)DDR 激酶。反过来,ATM 会阻止 DNA-PK 和核 DNA 传感器 IFI16 与病毒 DNA 的结合,从而抑制细胞因子反应。然而,DNA损伤后,DNA-PK会增强ATM的活性,这是IFN-β表达所必需的。这些研究结果表明,DDR 通过对 DDR 激酶的对立调节来自动调节细胞因子的表达。
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来源期刊
Cell Systems
Cell Systems Medicine-Pathology and Forensic Medicine
CiteScore
16.50
自引率
1.10%
发文量
84
审稿时长
42 days
期刊介绍: In 2015, Cell Systems was founded as a platform within Cell Press to showcase innovative research in systems biology. Our primary goal is to investigate complex biological phenomena that cannot be simply explained by basic mathematical principles. While the physical sciences have long successfully tackled such challenges, we have discovered that our most impactful publications often employ quantitative, inference-based methodologies borrowed from the fields of physics, engineering, mathematics, and computer science. We are committed to providing a home for elegant research that addresses fundamental questions in systems biology.
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