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识别生化网络中的脆弱性:Fas信号诱导凋亡的稳健性能分析

Identifying fragilities in biochemical networks: robust performance analysis of Fas signaling-induced apoptosis.

作者信息

Shoemaker Jason E, Doyle Francis J

机构信息

Department of Chemical Engineering, University of California, Santa Barbara, California, USA.

出版信息

Biophys J. 2008 Sep 15;95(6):2610-23. doi: 10.1529/biophysj.107.123398. Epub 2008 Jun 6.

DOI:10.1529/biophysj.107.123398
PMID:18539637
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2527273/
Abstract

Proper control of apoptotic signaling is critical to immune response and development in multicellular organisms. Two tools from control engineering are applied to a mathematical model of Fas ligand signaling-induced apoptosis. Structured singular value analysis determines the volume in parameter space within which the system parameters may exist and still maintain efficacious signaling, but is limited to linear behaviors. Sensitivity analysis can be applied to nonlinear systems but is difficult to relate to performance criteria. Thus, structured singular value analysis is used to quantify performance during apoptosis rejection, ensuring that the system remains sensitive but not overly so to apoptotic stimuli. Sensitivity analysis is applied when the system has switched to the death-inducing, apoptotic steady state to determine parameters significant to maintaining the bistability. The analyses reveal that the magnitude of the death signal is fragile to perturbations in degradation parameters (failures in the ubiquitin/proteasome mechanism) while the timing of signal expression can be tuned by manipulating local parameters. Simultaneous parameter uncertainty highlights apoptotic fragility to disturbances in the ubiquitin/proteasome system. Sensitivity analysis reveals that the robust signaling characteristics of the apoptotic network is due to network architecture, and the apoptotic signaling threshold is best manipulated by interactions upstream of the apoptosome.

摘要

凋亡信号的适当控制对于多细胞生物体的免疫反应和发育至关重要。控制工程中的两种工具被应用于Fas配体信号诱导凋亡的数学模型。结构奇异值分析确定了系统参数可能存在且仍能维持有效信号传导的参数空间体积,但仅限于线性行为。灵敏度分析可应用于非线性系统,但难以与性能标准相关联。因此,结构奇异值分析用于量化凋亡抑制过程中的性能,确保系统对凋亡刺激保持敏感但不过度敏感。当系统切换到诱导死亡的凋亡稳态时,应用灵敏度分析来确定对维持双稳态至关重要的参数。分析表明,死亡信号的幅度对降解参数的扰动(泛素/蛋白酶体机制的故障)很脆弱,而信号表达的时间可以通过操纵局部参数来调整。同时参数不确定性突出了凋亡对泛素/蛋白酶体系统干扰的脆弱性。灵敏度分析表明,凋亡网络的稳健信号特征归因于网络架构,并且凋亡信号阈值最好通过凋亡小体上游的相互作用来操纵。

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本文引用的文献

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