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单细胞自噬囊泡动力学的计算模型。

Computational model for autophagic vesicle dynamics in single cells.

机构信息

Laboratory of Systems Biology, Van Andel Research Institute, Grand Rapids, MI, USA.

出版信息

Autophagy. 2013 Jan;9(1):74-92. doi: 10.4161/auto.22532. Epub 2012 Nov 29.

DOI:10.4161/auto.22532
PMID:23196898
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3542220/
Abstract

Macroautophagy (autophagy) is a cellular recycling program essential for homeostasis and survival during cytotoxic stress. This process, which has an emerging role in disease etiology and treatment, is executed in four stages through the coordinated action of more than 30 proteins. An effective strategy for studying complicated cellular processes, such as autophagy, involves the construction and analysis of mathematical or computational models. When developed and refined from experimental knowledge, these models can be used to interrogate signaling pathways, formulate novel hypotheses about systems, and make predictions about cell signaling changes induced by specific interventions. Here, we present the development of a computational model describing autophagic vesicle dynamics in a mammalian system. We used time-resolved, live-cell microscopy to measure the synthesis and turnover of autophagic vesicles in single cells. The stochastically simulated model was consistent with data acquired during conditions of both basal and chemically-induced autophagy. The model was tested by genetic modulation of autophagic machinery and found to accurately predict vesicle dynamics observed experimentally. Furthermore, the model generated an unforeseen prediction about vesicle size that is consistent with both published findings and our experimental observations. Taken together, this model is accurate and useful and can serve as the foundation for future efforts aimed at quantitative characterization of autophagy.

摘要

自噬(自噬作用)是一种细胞内的回收程序,对于细胞在细胞毒性应激下的内稳态和存活至关重要。这个过程在疾病病因学和治疗方面的作用日益显现,它通过 30 多种蛋白质的协调作用分四个阶段进行。对于研究自噬等复杂细胞过程,一种有效的策略是构建和分析数学或计算模型。当这些模型从实验知识中发展和完善后,可以用于研究信号通路,提出关于系统的新假设,并对特定干预措施引起的细胞信号变化进行预测。在这里,我们介绍了一个描述哺乳动物系统中自噬小泡动力学的计算模型的开发。我们使用时间分辨的活细胞显微镜来测量单个细胞中自噬小泡的合成和周转。随机模拟模型与基础状态和化学诱导自噬条件下获得的数据一致。该模型通过对自噬机制的遗传调节进行了测试,发现它可以准确预测实验观察到的小泡动力学。此外,该模型还产生了一个关于小泡大小的意外预测,这与已发表的研究结果和我们的实验观察结果一致。总的来说,这个模型是准确和有用的,可以作为未来定量描述自噬的努力的基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd4c/3542220/9c14ac4f0272/auto-9-74-g9.jpg
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