小胶质细胞中 PI3K/Akt 通路的数学建模

IF 2.7 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Alireza Poshtkohi;John Wade;Liam McDaid;Junxiu Liu;Mark L. Dallas;Angela Bithell
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引用次数: 0

摘要

小胶质细胞的运动涉及细胞内信号通路,这些通路主要受控于细胞膜 Ca2+ 的变化和 PI3K/Akt(磷脂酰肌醇-3-激酶/蛋白激酶 B)的激活。在这封信中,我们为小胶质细胞中 PI3K/Akt 通路的细胞膜 Ca2+ 激活建立了一个新的生物物理模型,其中 Ca2+ 的流入由 P2Y 嘌呤能受体(P2YR)和 P2X 嘌呤能受体(P2XR)介导。模型参数的估算采用了优化技术,使模型与磷酸化 Akt(pAkt)实验模型/体外数据相匹配。综合模型支持这样的假设,即通过 P2YR 和 P2XR 流入的 Ca2+ 可以解释实验报告中测量 pAkt 水平的双相瞬时反应。我们的预测揭示了 P2R 在生理相互作用和瞬时反应方面如何调控 Ca2+ 和 Akt 的新定量见解。研究表明,通过重复应用激动剂上调 P2X 受体会导致基线[Ca2+]持续增加,从而使双相反应变成单相反应,延长 pAkt 水平升高的时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mathematical Modeling of PI3K/Akt Pathway in Microglia
The motility of microglia involves intracellular signaling pathways that are predominantly controlled by changes in cytosolic Ca2+ and activation of PI3K/Akt (phosphoinositide-3-kinase/protein kinase B). In this letter, we develop a novel biophysical model for cytosolic Ca2+ activation of the PI3K/Akt pathway in microglia where Ca2+ influx is mediated by both P2Y purinergic receptors (P2YR) and P2X purinergic receptors (P2XR). The model parameters are estimated by employing optimization techniques to fit the model to phosphorylated Akt (pAkt) experimental modeling/in vitro data. The integrated model supports the hypothesis that Ca2+ influx via P2YR and P2XR can explain the experimentally reported biphasic transient responses in measuring pAkt levels. Our predictions reveal new quantitative insights into P2Rs on how they regulate Ca2+ and Akt in terms of physiological interactions and transient responses. It is shown that the upregulation of P2X receptors through a repetitive application of agonist results in a continual increase in the baseline [Ca2+], which causes the biphasic response to become a monophasic response which prolongs elevated levels of pAkt.
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来源期刊
Neural Computation
Neural Computation 工程技术-计算机:人工智能
CiteScore
6.30
自引率
3.40%
发文量
83
审稿时长
3.0 months
期刊介绍: Neural Computation is uniquely positioned at the crossroads between neuroscience and TMCS and welcomes the submission of original papers from all areas of TMCS, including: Advanced experimental design; Analysis of chemical sensor data; Connectomic reconstructions; Analysis of multielectrode and optical recordings; Genetic data for cell identity; Analysis of behavioral data; Multiscale models; Analysis of molecular mechanisms; Neuroinformatics; Analysis of brain imaging data; Neuromorphic engineering; Principles of neural coding, computation, circuit dynamics, and plasticity; Theories of brain function.
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