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研究正反馈和细胞异质性在病毒感染后 I 型干扰素反应中的功能作用。

Investigating Functional Roles for Positive Feedback and Cellular Heterogeneity in the Type I Interferon Response to Viral Infection.

机构信息

Department of Mathematics and Statistics, Georgetown University, Washington, DC 20057, USA.

Department of Mathematical Sciences, George Mason University, Fairfax, VA 22030, USA.

出版信息

Viruses. 2018 Sep 21;10(10):517. doi: 10.3390/v10100517.

Abstract

Secretion of type I interferons (IFN) by infected cells mediates protection against many viruses, but prolonged or excessive type I IFN secretion can lead to immune pathology. A proper type I IFN response must therefore maintain a balance between protection and excessive IFN secretion. It has been widely noted that the type I IFN response is driven by positive feedback and is heterogeneous, with only a fraction of infected cells upregulating IFN expression even in clonal cell lines, but the functional roles of feedback and heterogeneity in balancing protection and excessive IFN secretion are not clear. To investigate the functional roles for feedback and heterogeneity, we constructed a mathematical model coupling IFN and viral dynamics that extends existing mathematical models by accounting for feedback and heterogeneity. We fit our model to five existing datasets, reflecting different experimental systems. Fitting across datasets allowed us to compare the IFN response across the systems and suggested different signatures of feedback and heterogeneity in the different systems. Further, through numerical experiments, we generated hypotheses of functional roles for IFN feedback and heterogeneity consistent with our mathematical model. We hypothesize an inherent tradeoff in the IFN response: a positive feedback loop prevents excessive IFN secretion, but also makes the IFN response vulnerable to viral antagonism. We hypothesize that cellular heterogeneity of the IFN response functions to protect the feedback loop from viral antagonism. Verification of our hypotheses will require further experimental studies. Our work provides a basis for analyzing the type I IFN response across systems.

摘要

受感染细胞分泌的 I 型干扰素 (IFN) 介导了对许多病毒的保护,但 I 型 IFN 的持续或过度分泌可能导致免疫病理学。因此,适当的 I 型 IFN 反应必须在保护和过度 IFN 分泌之间保持平衡。人们广泛注意到,I 型 IFN 反应是由正反馈驱动的,并且具有异质性,即使在克隆细胞系中,也只有一小部分感染细胞上调 IFN 表达,但反馈和异质性在平衡保护和过度 IFN 分泌方面的功能作用尚不清楚。为了研究反馈和异质性的功能作用,我们构建了一个将 IFN 和病毒动力学耦合在一起的数学模型,该模型通过考虑反馈和异质性扩展了现有的数学模型。我们将模型拟合到五个现有的数据集,反映了不同的实验系统。跨数据集的拟合使我们能够比较不同系统中的 IFN 反应,并提示不同系统中的反馈和异质性具有不同的特征。此外,通过数值实验,我们生成了与我们的数学模型一致的 IFN 反馈和异质性的功能作用假设。我们假设 IFN 反应中存在内在的权衡:正反馈环可防止 IFN 过度分泌,但也使 IFN 反应容易受到病毒拮抗作用的影响。我们假设 IFN 反应的细胞异质性可保护反馈环免受病毒拮抗作用的影响。我们的假设需要进一步的实验研究来验证。我们的工作为跨系统分析 I 型 IFN 反应提供了基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3c43/6213501/7c766b6a837e/viruses-10-00517-g001.jpg

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