Integrative network modeling reveals mechanisms underlying T cell exhaustion
Integrative network modeling reveals mechanisms underlying T cell exhaustion
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DOI：
10.1038/s41598-020-58600-8
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发表时间：
2020-02-05
影响因子：
4.6
通讯作者：
Ratushny, Alexander
中科院分区：
文献类型：
--
作者：
Bolouri, Hamid;Young, Mary;Ratushny, Alexander
未能清除抗原会导致CD8(+)T细胞变得越来越功能低下，这种状态被称为衰竭。我们将从已发表的文献中手动提取的信息与来自不同模型系统的基因表达数据相结合，以推断一组支撑疲惫的分子调控相互作用。网络的拓扑分析和模拟建模表明，CD8(+)T细胞在刺激后经历了两次主要的状态转换。细胞处于早期前记忆/增殖(PP)状态的时间是网络结构的固定和固有属性。精疲力竭需要转换到第二种状态。结合网络拓扑分析和仿真建模的见解，我们预测网络中每个节点将细胞推向耗尽状态的程度。我们通过实验测试药物诱导的对EZH2功能的干扰会增加激活后早期支持记忆/增殖细胞的比例，从而证明了我们方法的有效性。
Failure to clear antigens causes CD8(+) T cells to become increasingly hypo-functional, a state known as exhaustion. We combined manually extracted information from published literature with gene expression data from diverse model systems to infer a set of molecular regulatory interactions that underpin exhaustion. Topological analysis and simulation modeling of the network suggests CD8(+) T cells undergo 2 major transitions in state following stimulation. The time cells spend in the earlier pro-memory/proliferative (PP) state is a fixed and inherent property of the network structure. Transition to the second state is necessary for exhaustion. Combining insights from network topology analysis and simulation modeling, we predict the extent to which each node in our network drives cells towards an exhausted state. We demonstrate the utility of our approach by experimentally testing the prediction that drug-induced interference with EZH2 function increases the proportion of pro-memory/proliferative cells in the early days post-activation.