基于 ODE 的自噬信号网络模型

IF 3.4 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Markus Galhuber , Kathrin Thedieck
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引用次数: 0

摘要

新陈代谢和营养处理失常是癌症的特征。自噬是一种分解代谢过程,可清除大分子并为合成代谢提供代谢中间产物。自噬保护健康细胞免受肿瘤发生,同时调动代谢物促进肿瘤生长。自噬由 mTOR 信号网络与 AMPK 和 ULK1 共同控制。这种激酶三元组具有高度交织的反馈和前馈机制,使营养和药物反应的预测变得复杂。基于 ODE 的模型提供了一种确定性方法,常用于信号动力学的探索。最近的 mTOR-AMPK-ULK1 网络 ODE 模型揭示了非线性行为、双稳态开关和振荡模式,阐明了自噬控制的稳健性和适应性。我们强调了关于 AMPK 在 mTORC1-ULK1 相互协作中的作用的新观点,以及可纳入未来模型的机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ODE-based models of signaling networks in autophagy

Aberrant metabolism and nutrient processing are hallmarks of cancer. Autophagy is a catabolic process, clearing macromolecules and providing metabolite intermediates for anabolism. Autophagy safeguards healthy cells from tumorigenesis while mobilizing metabolites promoting tumor growth. Autophagy is controlled by the mTOR signaling network in conjunction with AMPK and ULK1. This kinase triad features highly intertwined feedback and feedforward mechanisms, complicating predictions on nutrient and drug response. ODE-based models offer a deterministic approach frequently used for the exploration of signaling dynamics. Recent ODE models of the mTOR-AMPK-ULK1 network revealed non-linear behaviors, bistable switches, and oscillatory patterns, shedding light on the robustness and adaptability of autophagy control. We highlight emerging perspectives on AMPK in mTORC1-ULK1 crosstalk and mechanisms for integration into future models.

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来源期刊
Current Opinion in Systems Biology
Current Opinion in Systems Biology Mathematics-Applied Mathematics
CiteScore
7.10
自引率
2.70%
发文量
20
期刊介绍: Current Opinion in Systems Biology is a new systematic review journal that aims to provide specialists with a unique and educational platform to keep up-to-date with the expanding volume of information published in the field of Systems Biology. It publishes polished, concise and timely systematic reviews and opinion articles. In addition to describing recent trends, the authors are encouraged to give their subjective opinion on the topics discussed. As this is such a broad discipline, we have determined themed sections each of which is reviewed once a year. The following areas will be covered by Current Opinion in Systems Biology: -Genomics and Epigenomics -Gene Regulation -Metabolic Networks -Cancer and Systemic Diseases -Mathematical Modelling -Big Data Acquisition and Analysis -Systems Pharmacology and Physiology -Synthetic Biology -Stem Cells, Development, and Differentiation -Systems Biology of Mold Organisms -Systems Immunology and Host-Pathogen Interaction -Systems Ecology and Evolution
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