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T 细胞活化过程中细胞内信号级联反应的时间蛋白表达模式:一项计算研究。

Temporal protein expression pattern in intracellular signalling cascade during T-cell activation: a computational study.

作者信息

Ganguli Piyali, Chowdhury Saikat, Bhowmick Rupa, Sarkar Ram Rup

机构信息

Chemical Engineering and Process Development Division, CSIR-National Chemical Laboratory, Pune 411 008, India.

出版信息

J Biosci. 2015 Oct;40(4):769-89. doi: 10.1007/s12038-015-9561-1.

Abstract

Various T-cell co-receptor molecules and calcium channel CRAC play a pivotal role in the maintenance of cell's functional responses by regulating the production of effector molecules (mostly cytokines) that aids in immune clearance and also maintaining the cell in a functionally active state. Any defect in these co-receptor signalling pathways may lead to an altered expression pattern of the effector molecules. To study the propagation of such defects with time and their effect on the intracellular protein expression patterns, a comprehensive and largest pathway map of T-cell activation network is reconstructed manually. The entire pathway reactions are then translated using logical equations and simulated using the published time series microarray expression data as inputs. After validating the model, the effect of in silico knock down of co-receptor molecules on the expression patterns of their downstream proteins is studied and simultaneously the changes in the phenotypic behaviours of the T-cell population are predicted, which shows significant variations among the proteins expression and the signalling routes through which the response is propagated in the cytoplasm. This integrative computational approach serves as a valuable technique to study the changes in protein expression patterns and helps to predict variations in the cellular behaviour.

摘要

各种T细胞共受体分子和钙通道CRAC通过调节效应分子(主要是细胞因子)的产生,在维持细胞功能反应中起关键作用,这些效应分子有助于免疫清除,并使细胞保持在功能活跃状态。这些共受体信号通路中的任何缺陷都可能导致效应分子表达模式的改变。为了研究此类缺陷随时间的传播及其对细胞内蛋白质表达模式的影响,手动重建了一个全面且最大的T细胞激活网络通路图。然后使用逻辑方程翻译整个通路反应,并使用已发表的时间序列微阵列表达数据作为输入进行模拟。在验证模型后,研究了共受体分子的计算机模拟敲除对其下游蛋白质表达模式的影响,同时预测了T细胞群体表型行为的变化,这表明蛋白质表达和反应在细胞质中传播的信号通路存在显著差异。这种综合计算方法是研究蛋白质表达模式变化的宝贵技术,并有助于预测细胞行为的变化。

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