Department of Biochemistry and Molecular Biology, School of Biomedical Sciences, Monash University, Clayton, Victoria, 3800, Australia.
Biomedicine Discovery Institute, Monash University, Clayton, Victoria, 3800, Australia.
Sci Rep. 2019 Jul 23;9(1):10637. doi: 10.1038/s41598-019-46592-z.
A properly functioning immune system is vital for an organism's wellbeing. Immune tolerance is a critical feature of the immune system that allows immune cells to mount effective responses against exogenous pathogens such as viruses and bacteria, while preventing attack to self-tissues. Activation-induced cell death (AICD) in T lymphocytes, in which repeated stimulations of the T-cell receptor (TCR) lead to activation and then apoptosis of T cells, is a major mechanism for T cell homeostasis and helps maintain peripheral immune tolerance. Defects in AICD can lead to development of autoimmune diseases. Despite its importance, the regulatory mechanisms that underlie AICD remain poorly understood, particularly at an integrative network level. Here, we develop a dynamic multi-pathway model of the integrated TCR signalling network and perform model-based analysis to characterize the network-level properties of AICD. Model simulation and analysis show that amplified activation of the transcriptional factor NFAT in response to repeated TCR stimulations, a phenomenon central to AICD, is tightly modulated by a coupled positive-negative feedback mechanism. NFAT amplification is predominantly enabled by a positive feedback self-regulated by NFAT, while opposed by a NFAT-induced negative feedback via Carabin. Furthermore, model analysis predicts an optimal therapeutic window for drugs that help minimize proliferation while maximize AICD of T cells. Overall, our study provides a comprehensive mathematical model of TCR signalling and model-based analysis offers new network-level insights into the regulation of activation-induced cell death in T cells.
一个正常运作的免疫系统对生物体的健康至关重要。免疫耐受是免疫系统的一个关键特征,它允许免疫细胞对病毒和细菌等外源性病原体产生有效反应,同时防止自身组织受到攻击。T 淋巴细胞中的激活诱导细胞死亡(AICD),即 T 细胞受体(TCR)的反复刺激导致 T 细胞的激活和随后的细胞凋亡,是 T 细胞稳态的主要机制,并有助于维持外周免疫耐受。AICD 的缺陷可导致自身免疫性疾病的发生。尽管其重要性不言而喻,但 AICD 背后的调节机制仍知之甚少,特别是在整合网络层面。在这里,我们构建了一个整合的 TCR 信号网络的动态多通路模型,并进行基于模型的分析,以描述 AICD 的网络级特性。模型模拟和分析表明,转录因子 NFAT 在反复 TCR 刺激下的扩增激活,是 AICD 的核心现象,受到一个耦合的正负反馈机制的紧密调节。NFAT 的扩增主要由 NFAT 自身调节的正反馈所启用,而 NFAT 通过 Carabin 诱导的负反馈则与之相反。此外,模型分析预测了一种有助于最大限度地减少 T 细胞增殖并最大限度地提高 AICD 的药物的最佳治疗窗口。总的来说,我们的研究提供了一个全面的 TCR 信号数学模型,基于模型的分析为 T 细胞激活诱导细胞死亡的调控提供了新的网络层面的见解。