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Stochastic modelling for gradient sensing by chemotactic cells

机译：趋化细胞的梯度感应的随机建模

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摘要

Chemotaxis, the process by which cells move toward attractant molecules, operates in a range of biological processes including immunity, neuronal patterning, and morphogenesis. Dictyostelium discoideum cells display a strong chemotactic response to cyclic adenosine 3′,5′-monophosphate (cAMP), which binds to a cell surface receptor. Each Dictyostelium has ca. 80000 cAMP receptors, and can transduce shallow spatial chemoattractant gradients into strongly localized intracellular responses in spite of large statistical fluctuation of receptor occupancy even in the case of very low cAMP concentration. In this study, we develop a stochastic model for gradient sensing by chemotactic cells. We simulate the binding of cAMP molecules to receptors by a Monte-Carlo method in order to account for statistical fluctuation of receptor occupancy and treat intracellular signal processing by a diffusion-translocation model, which includes the production of second-messenger molecules and positive feedback mechanisms mediated by effector molecules. Our simulation results show that the fluctuation of second-messenger concentration is much smaller than that of receptor occupancy, and that a shallow chemoattractant gradient are transduced into a large second-messenger concentration gradient through nonlinear signal amplification.
机译：趋化性是细胞向吸引分子移动的过程，它在一系列生物学过程中起作用，包括免疫，神经元模式和形态发生。盘基网柄菌细胞对结合细胞表面受体的环状腺苷3'，5'-单磷酸酯（cAMP）表现出强烈的趋化反应。每个双歧杆菌都有约。 80000个cAMP受体，即使在cAMP浓度很低的情况下，尽管受体占有率的统计波动很大，但仍可以将浅的空间趋化因子梯度转化为强烈的细胞内定位反应。在这项研究中，我们开发了一种趋化细胞进行梯度传感的随机模型。我们通过蒙特卡洛方法模拟cAMP分子与受体的结合，以解决受体占有率的统计波动，并通过扩散易位模型处理细胞内信号处理，该模型包括第二信使分子的产生和正反馈机制由效应分子介导。我们的仿真结果表明，第二信使浓度的波动远小于受体占有率的波动，并且通过非线性信号放大将浅的趋化因子梯度转换为大的第二信使浓度梯度。

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