The effect of inhibition of PP1 and TNFα signaling on pathogenesis of SARS coronavirus.
The effect of inhibition of PP1 and TNFα signaling on pathogenesis of SARS coronavirus.
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DOI：
10.1186/s12918-016-0336-6
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发表时间：
2016-09-23
影响因子：
--
通讯作者：
Waters KM
中科院分区：
文献类型：
--
作者：
McDermott JE;Mitchell HD;Gralinski LE;Eisfeld AJ;Josset L;Bankhead A 3rd;Neumann G;Tilton SC;Schäfer A;Li C;Fan S;McWeeney S;Baric RS;Katze MG;Waters KM
感染期间病毒复制和宿主免疫反应之间复杂的相互作用仍然知之甚少。虽然已知许多病毒采用抗免疫策略来促进其复制，但高致病性病毒感染也可引起过度的免疫应答，其加剧而不是降低致病性。为了研究严重急性呼吸综合征冠状病毒（SARS-CoV）中的这种二分法，我们开发了小鼠中SARS-CoV感染的转录网络模型，并使用该模型优先考虑候选调控靶点以供进一步研究。我们在18种不同的敲除（KO）小鼠品系中验证了我们的预测，表明网络拓扑结构为识别对病毒感染重要的基因提供了显着的预测能力。我们发现了一种新的病毒感染免疫反应的参与者，Kepi，蛋白磷酸酶1（PP1）复合物的抑制性亚基，可防止SARS-CoV发病。我们还发现，促炎细胞因子肿瘤坏死因子α（TNF α）的受体促进发病机制，可能是通过过度炎症。目前的研究提供了网络建模方法的验证，用于识别病毒感染发病机制中的重要参与者，并在理解宿主对重要传染病的反应方面向前迈出了一步。本研究结果提示Kepi在宿主对SARS-CoV的应答中的作用，以及在SARS-CoV感染中通过TNF α信号传导驱动发病机制的炎症活性。虽然我们之前已经报道了这种方法在细菌和细胞培养研究中的实用性，但这是第一个全面的研究，证实网络拓扑结构可用于预测小鼠的表型，并进行了实验验证。本文的在线版本（doi：10.1186/s12918 - 016 - 0336 - 6）包含补充材料，可供授权用户使用。
The complex interplay between viral replication and host immune response during infection remains poorly understood. While many viruses are known to employ anti-immune strategies to facilitate their replication, highly pathogenic virus infections can also cause an excessive immune response that exacerbates, rather than reduces pathogenicity. To investigate this dichotomy in severe acute respiratory syndrome coronavirus (SARS-CoV), we developed a transcriptional network model of SARS-CoV infection in mice and used the model to prioritize candidate regulatory targets for further investigation. We validated our predictions in 18 different knockout (KO) mouse strains, showing that network topology provides significant predictive power to identify genes that are important for viral infection. We identified a novel player in the immune response to virus infection, Kepi, an inhibitory subunit of the protein phosphatase 1 (PP1) complex, which protects against SARS-CoV pathogenesis. We also found that receptors for the proinflammatory cytokine tumor necrosis factor alpha (TNFα) promote pathogenesis, presumably through excessive inflammation. The current study provides validation of network modeling approaches for identifying important players in virus infection pathogenesis, and a step forward in understanding the host response to an important infectious disease. The results presented here suggest the role of Kepi in the host response to SARS-CoV, as well as inflammatory activity driving pathogenesis through TNFα signaling in SARS-CoV infections. Though we have reported the utility of this approach in bacterial and cell culture studies previously, this is the first comprehensive study to confirm that network topology can be used to predict phenotypes in mice with experimental validation. The online version of this article (doi:10.1186/s12918-016-0336-6) contains supplementary material, which is available to authorized users.
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影响因子：
3.7
作者：
McDermott JE;Vartanian KB;Mitchell H;Stevens SL;Sanfilippo A;Stenzel-Poore MP
通讯作者：
Stenzel-Poore MP
影响因子：
7.4
作者：
Eligini, Sonia;Arenaz, Izaskun;Colli, Susanna
通讯作者：
Colli, Susanna
影响因子：
8.2
作者：
Kang, H. P.;Yang, X.;Chen, R.;Zhang, B.;Corona, E.;Schadt, E. E.;Butte, A. J.
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Butte, A. J.
影响因子：
7.3
作者：
He, L.;Ding, Y.;Jiang, S.
通讯作者：
Jiang, S.
影响因子：
--
作者：
McDermott, Jason E.;Costa, Michelle;Tilton, Susan C.
通讯作者：
Tilton, Susan C.